Qualitative analysis of a discrete thermostatted kinetic framework modeling complex adaptive systems

NASA Astrophysics Data System (ADS)

Bianca, Carlo; Mogno, Caterina

2018-01-01

This paper deals with the derivation of a new discrete thermostatted kinetic framework for the modeling of complex adaptive systems subjected to external force fields (nonequilibrium system). Specifically, in order to model nonequilibrium stationary states of the system, the external force field is coupled to a dissipative term (thermostat). The well-posedness of the related Cauchy problem is investigated thus allowing the new discrete thermostatted framework to be suitable for the derivation of specific models and the related computational analysis. Applications to crowd dynamics and future research directions are also discussed within the paper.

Clinical time series prediction: Toward a hierarchical dynamical system framework.

PubMed

Liu, Zitao; Hauskrecht, Milos

2015-09-01

Developing machine learning and data mining algorithms for building temporal models of clinical time series is important for understanding of the patient condition, the dynamics of a disease, effect of various patient management interventions and clinical decision making. In this work, we propose and develop a novel hierarchical framework for modeling clinical time series data of varied length and with irregularly sampled observations. Our hierarchical dynamical system framework for modeling clinical time series combines advantages of the two temporal modeling approaches: the linear dynamical system and the Gaussian process. We model the irregularly sampled clinical time series by using multiple Gaussian process sequences in the lower level of our hierarchical framework and capture the transitions between Gaussian processes by utilizing the linear dynamical system. The experiments are conducted on the complete blood count (CBC) panel data of 1000 post-surgical cardiac patients during their hospitalization. Our framework is evaluated and compared to multiple baseline approaches in terms of the mean absolute prediction error and the absolute percentage error. We tested our framework by first learning the time series model from data for the patients in the training set, and then using it to predict future time series values for the patients in the test set. We show that our model outperforms multiple existing models in terms of its predictive accuracy. Our method achieved a 3.13% average prediction accuracy improvement on ten CBC lab time series when it was compared against the best performing baseline. A 5.25% average accuracy improvement was observed when only short-term predictions were considered. A new hierarchical dynamical system framework that lets us model irregularly sampled time series data is a promising new direction for modeling clinical time series and for improving their predictive performance. Copyright © 2014 Elsevier B.V. All rights reserved.

THE EPA MULTIMEDIA INTEGRATED MODELING SYSTEM SOFTWARE SUITE

EPA Science Inventory

The U.S. EPA is developing a Multimedia Integrated Modeling System (MIMS) framework that will provide a software infrastructure or environment to support constructing, composing, executing, and evaluating complex modeling studies. The framework will include (1) common software ...

Conceptual Modeling of a Quantum Key Distribution Simulation Framework Using the Discrete Event System Specification

DTIC Science & Technology

2014-09-18

and full/scale experimental verifications towards ground/ satellite quantum key distribution0 Oat Qhotonics 4235>9+7,=5;9!អ \\58^ Zin K. Dao Z. Miu T...Conceptual Modeling of a Quantum Key Distribution Simulation Framework Using the Discrete Event System Specification DISSERTATION Jeffrey D. Morris... QUANTUM KEY DISTRIBUTION SIMULATION FRAMEWORK USING THE DISCRETE EVENT SYSTEM SPECIFICATION DISSERTATION Presented to the Faculty Department of Systems

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.

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.

Graphical Means for Inspecting Qualitative Models of System Behaviour

ERIC Educational Resources Information Center

Bouwer, Anders; Bredeweg, Bert

2010-01-01

This article presents the design and evaluation of a tool for inspecting conceptual models of system behaviour. The basis for this research is the Garp framework for qualitative simulation. This framework includes modelling primitives, such as entities, quantities and causal dependencies, which are combined into model fragments and scenarios.…

Model-theoretic framework for sensor data fusion

NASA Astrophysics Data System (ADS)

Zavoleas, Kyriakos P.; Kokar, Mieczyslaw M.

1993-09-01

The main goal of our research in sensory data fusion (SDF) is the development of a systematic approach (a methodology) to designing systems for interpreting sensory information and for reasoning about the situation based upon this information and upon available data bases and knowledge bases. To achieve such a goal, two kinds of subgoals have been set: (1) develop a theoretical framework in which rational design/implementation decisions can be made, and (2) design a prototype SDF system along the lines of the framework. Our initial design of the framework has been described in our previous papers. In this paper we concentrate on the model-theoretic aspects of this framework. We postulate that data are embedded in data models, and information processing mechanisms are embedded in model operators. The paper is devoted to analyzing the classes of model operators and their significance in SDF. We investigate transformation abstraction and fusion operators. A prototype SDF system, fusing data from range and intensity sensors, is presented, exemplifying the structures introduced. Our framework is justified by the fact that it provides modularity, traceability of information flow, and a basis for a specification language for SDF.

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

A structural model decomposition framework for systems health management

NASA Astrophysics Data System (ADS)

Roychoudhury, I.; Daigle, M.; Bregon, A.; Pulido, B.

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.

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.

Public Acceptance and User Response to ATIS Products and Services: Modeling Framework and Data Requirements

DOT National Transportation Integrated Search

1993-12-01

This report presents a comprehensive modeling framework for user responses to Advanced Traveler Information Systems (ATIS) services and identifies the data needs for the validation of such a framework. The authors present overviews of the framework b...

Qualitative, semi-quantitative, and quantitative simulation of the osmoregulation system in yeast

PubMed Central

Pang, Wei; Coghill, George M.

2015-01-01

In this paper we demonstrate how Morven, a computational framework which can perform qualitative, semi-quantitative, and quantitative simulation of dynamical systems using the same model formalism, is applied to study the osmotic stress response pathway in yeast. First the Morven framework itself is briefly introduced in terms of the model formalism employed and output format. We then built a qualitative model for the biophysical process of the osmoregulation in yeast, and a global qualitative-level picture was obtained through qualitative simulation of this model. Furthermore, we constructed a Morven model based on existing quantitative model of the osmoregulation system. This model was then simulated qualitatively, semi-quantitatively, and quantitatively. The obtained simulation results are presented with an analysis. Finally the future development of the Morven framework for modelling the dynamic biological systems is discussed. PMID:25864377

Representing natural and manmade drainage systems in an earth system modeling framework

DOE Office of Scientific and Technical Information (OSTI.GOV)

Li, Hongyi; Wu, Huan; Huang, Maoyi

Drainage systems can be categorized into natural or geomorphological drainage systems, agricultural drainage systems and urban drainage systems. They interact closely among themselves and with climate and human society, particularly under extreme climate and hydrological events such as floods. This editorial articulates the need to holistically understand and model drainage systems in the context of climate change and human influence, and discusses the requirements and examples of feasible approaches to representing natural and manmade drainage systems in an earth system modeling framework.

Clinical time series prediction: towards a hierarchical dynamical system framework

PubMed Central

Liu, Zitao; Hauskrecht, Milos

2014-01-01

Objective Developing machine learning and data mining algorithms for building temporal models of clinical time series is important for understanding of the patient condition, the dynamics of a disease, effect of various patient management interventions and clinical decision making. In this work, we propose and develop a novel hierarchical framework for modeling clinical time series data of varied length and with irregularly sampled observations. Materials and methods Our hierarchical dynamical system framework for modeling clinical time series combines advantages of the two temporal modeling approaches: the linear dynamical system and the Gaussian process. We model the irregularly sampled clinical time series by using multiple Gaussian process sequences in the lower level of our hierarchical framework and capture the transitions between Gaussian processes by utilizing the linear dynamical system. The experiments are conducted on the complete blood count (CBC) panel data of 1000 post-surgical cardiac patients during their hospitalization. Our framework is evaluated and compared to multiple baseline approaches in terms of the mean absolute prediction error and the absolute percentage error. Results We tested our framework by first learning the time series model from data for the patient in the training set, and then applying the model in order to predict future time series values on the patients in the test set. We show that our model outperforms multiple existing models in terms of its predictive accuracy. Our method achieved a 3.13% average prediction accuracy improvement on ten CBC lab time series when it was compared against the best performing baseline. A 5.25% average accuracy improvement was observed when only short-term predictions were considered. Conclusion A new hierarchical dynamical system framework that lets us model irregularly sampled time series data is a promising new direction for modeling clinical time series and for improving their predictive performance. PMID:25534671

Unified Simulation and Analysis Framework for Deep Space Navigation Design

NASA Technical Reports Server (NTRS)

Anzalone, Evan; Chuang, Jason; Olsen, Carrie

2013-01-01

As the technology that enables advanced deep space autonomous navigation continues to develop and the requirements for such capability continues to grow, there is a clear need for a modular expandable simulation framework. This tool's purpose is to address multiple measurement and information sources in order to capture system capability. This is needed to analyze the capability of competing navigation systems as well as to develop system requirements, in order to determine its effect on the sizing of the integrated vehicle. The development for such a framework is built upon Model-Based Systems Engineering techniques to capture the architecture of the navigation system and possible state measurements and observations to feed into the simulation implementation structure. These models also allow a common environment for the capture of an increasingly complex operational architecture, involving multiple spacecraft, ground stations, and communication networks. In order to address these architectural developments, a framework of agent-based modules is implemented to capture the independent operations of individual spacecraft as well as the network interactions amongst spacecraft. This paper describes the development of this framework, and the modeling processes used to capture a deep space navigation system. Additionally, a sample implementation describing a concept of network-based navigation utilizing digitally transmitted data packets is described in detail. This developed package shows the capability of the modeling framework, including its modularity, analysis capabilities, and its unification back to the overall system requirements and definition.

A Flexible Modeling Framework For Hydraulic and Water Quality Performance Assessment of Stormwater Green Infrastructure

EPA Science Inventory

A flexible framework has been created for modeling multi-dimensional hydrological and water quality processes within stormwater green infrastructures (GIs). The framework models a GI system using a set of blocks (spatial features) and connectors (interfaces) representing differen...

Distributed software framework and continuous integration in hydroinformatics systems

NASA Astrophysics Data System (ADS)

Zhou, Jianzhong; Zhang, Wei; Xie, Mengfei; Lu, Chengwei; Chen, Xiao

2017-08-01

When encountering multiple and complicated models, multisource structured and unstructured data, complex requirements analysis, the platform design and integration of hydroinformatics systems become a challenge. To properly solve these problems, we describe a distributed software framework and it’s continuous integration process in hydroinformatics systems. This distributed framework mainly consists of server cluster for models, distributed database, GIS (Geographic Information System) servers, master node and clients. Based on it, a GIS - based decision support system for joint regulating of water quantity and water quality of group lakes in Wuhan China is established.

Modelling Participatory Geographic Information System for Customary Land Conflict Resolution

NASA Astrophysics Data System (ADS)

Gyamera, E. A.; Arko-Adjei, A.; Duncan, E. E.; Kuma, J. S. Y.

2017-11-01

Since land contributes to about 73 % of most countries Gross Domestic Product (GDP), attention on land rights have tremendously increased globally. Conflicts over land have therefore become part of the major problems associated with land administration. However, the conventional mechanisms for land conflict resolution do not provide satisfactory result to disputants due to various factors. This study sought to develop a Framework of using Participatory Geographic Information System (PGIS) for customary land conflict resolution. The framework was modelled using Unified Modelling Language (UML). The PGIS framework, called butterfly model, consists of three units namely, Social Unit (SU), Technical Unit (TU) and Decision Making Unit (DMU). The name butterfly model for land conflict resolution was adopted for the framework based on its features and properties. The framework has therefore been recommended to be adopted for land conflict resolution in customary areas.

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.

Koopman Operator Framework for Time Series Modeling and Analysis

NASA Astrophysics Data System (ADS)

Surana, Amit

2018-01-01

We propose an interdisciplinary framework for time series classification, forecasting, and anomaly detection by combining concepts from Koopman operator theory, machine learning, and linear systems and control theory. At the core of this framework is nonlinear dynamic generative modeling of time series using the Koopman operator which is an infinite-dimensional but linear operator. Rather than working with the underlying nonlinear model, we propose two simpler linear representations or model forms based on Koopman spectral properties. We show that these model forms are invariants of the generative model and can be readily identified directly from data using techniques for computing Koopman spectral properties without requiring the explicit knowledge of the generative model. We also introduce different notions of distances on the space of such model forms which is essential for model comparison/clustering. We employ the space of Koopman model forms equipped with distance in conjunction with classical machine learning techniques to develop a framework for automatic feature generation for time series classification. The forecasting/anomaly detection framework is based on using Koopman model forms along with classical linear systems and control approaches. We demonstrate the proposed framework for human activity classification, and for time series forecasting/anomaly detection in power grid application.

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.

Real-Time Reliability Verification for UAV Flight Control System Supporting Airworthiness Certification.

PubMed

Xu, Haiyang; Wang, Ping

2016-01-01

In order to verify the real-time reliability of unmanned aerial vehicle (UAV) flight control system and comply with the airworthiness certification standard, we proposed a model-based integration framework for modeling and verification of time property. Combining with the advantages of MARTE, this framework uses class diagram to create the static model of software system, and utilizes state chart to create the dynamic model. In term of the defined transformation rules, the MARTE model could be transformed to formal integrated model, and the different part of the model could also be verified by using existing formal tools. For the real-time specifications of software system, we also proposed a generating algorithm for temporal logic formula, which could automatically extract real-time property from time-sensitive live sequence chart (TLSC). Finally, we modeled the simplified flight control system of UAV to check its real-time property. The results showed that the framework could be used to create the system model, as well as precisely analyze and verify the real-time reliability of UAV flight control system.

Real-Time Reliability Verification for UAV Flight Control System Supporting Airworthiness Certification

PubMed Central

Xu, Haiyang; Wang, Ping

2016-01-01

In order to verify the real-time reliability of unmanned aerial vehicle (UAV) flight control system and comply with the airworthiness certification standard, we proposed a model-based integration framework for modeling and verification of time property. Combining with the advantages of MARTE, this framework uses class diagram to create the static model of software system, and utilizes state chart to create the dynamic model. In term of the defined transformation rules, the MARTE model could be transformed to formal integrated model, and the different part of the model could also be verified by using existing formal tools. For the real-time specifications of software system, we also proposed a generating algorithm for temporal logic formula, which could automatically extract real-time property from time-sensitive live sequence chart (TLSC). Finally, we modeled the simplified flight control system of UAV to check its real-time property. The results showed that the framework could be used to create the system model, as well as precisely analyze and verify the real-time reliability of UAV flight control system. PMID:27918594

Qualitative, semi-quantitative, and quantitative simulation of the osmoregulation system in yeast.

PubMed

Pang, Wei; Coghill, George M

2015-05-01

In this paper we demonstrate how Morven, a computational framework which can perform qualitative, semi-quantitative, and quantitative simulation of dynamical systems using the same model formalism, is applied to study the osmotic stress response pathway in yeast. First the Morven framework itself is briefly introduced in terms of the model formalism employed and output format. We then built a qualitative model for the biophysical process of the osmoregulation in yeast, and a global qualitative-level picture was obtained through qualitative simulation of this model. Furthermore, we constructed a Morven model based on existing quantitative model of the osmoregulation system. This model was then simulated qualitatively, semi-quantitatively, and quantitatively. The obtained simulation results are presented with an analysis. Finally the future development of the Morven framework for modelling the dynamic biological systems is discussed. Copyright © 2015 The Authors. Published by Elsevier Ireland Ltd.. All rights reserved.

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 and Outcomes Research (ISPOR). Published by Elsevier Inc. All rights reserved.

A stochastic hybrid systems based framework for modeling dependent failure processes

PubMed Central

Fan, Mengfei; Zeng, Zhiguo; Zio, Enrico; Kang, Rui; Chen, Ying

2017-01-01

In this paper, we develop a framework to model and analyze systems that are subject to dependent, competing degradation processes and random shocks. The degradation processes are described by stochastic differential equations, whereas transitions between the system discrete states are triggered by random shocks. The modeling is, then, based on Stochastic Hybrid Systems (SHS), whose state space is comprised of a continuous state determined by stochastic differential equations and a discrete state driven by stochastic transitions and reset maps. A set of differential equations are derived to characterize the conditional moments of the state variables. System reliability and its lower bounds are estimated from these conditional moments, using the First Order Second Moment (FOSM) method and Markov inequality, respectively. The developed framework is applied to model three dependent failure processes from literature and a comparison is made to Monte Carlo simulations. The results demonstrate that the developed framework is able to yield an accurate estimation of reliability with less computational costs compared to traditional Monte Carlo-based methods. PMID:28231313

A stochastic hybrid systems based framework for modeling dependent failure processes.

PubMed

Fan, Mengfei; Zeng, Zhiguo; Zio, Enrico; Kang, Rui; Chen, Ying

2017-01-01

In this paper, we develop a framework to model and analyze systems that are subject to dependent, competing degradation processes and random shocks. The degradation processes are described by stochastic differential equations, whereas transitions between the system discrete states are triggered by random shocks. The modeling is, then, based on Stochastic Hybrid Systems (SHS), whose state space is comprised of a continuous state determined by stochastic differential equations and a discrete state driven by stochastic transitions and reset maps. A set of differential equations are derived to characterize the conditional moments of the state variables. System reliability and its lower bounds are estimated from these conditional moments, using the First Order Second Moment (FOSM) method and Markov inequality, respectively. The developed framework is applied to model three dependent failure processes from literature and a comparison is made to Monte Carlo simulations. The results demonstrate that the developed framework is able to yield an accurate estimation of reliability with less computational costs compared to traditional Monte Carlo-based methods.

Machine Learning-based discovery of closures for reduced models of dynamical systems

NASA Astrophysics Data System (ADS)

Pan, Shaowu; Duraisamy, Karthik

2017-11-01

Despite the successful application of machine learning (ML) in fields such as image processing and speech recognition, only a few attempts has been made toward employing ML to represent the dynamics of complex physical systems. Previous attempts mostly focus on parameter calibration or data-driven augmentation of existing models. In this work we present a ML framework to discover closure terms in reduced models of dynamical systems and provide insights into potential problems associated with data-driven modeling. Based on exact closure models for linear system, we propose a general linear closure framework from viewpoint of optimization. The framework is based on trapezoidal approximation of convolution term. Hyperparameters that need to be determined include temporal length of memory effect, number of sampling points, and dimensions of hidden states. To circumvent the explicit specification of memory effect, a general framework inspired from neural networks is also proposed. We conduct both a priori and posteriori evaluations of the resulting model on a number of non-linear dynamical systems. This work was supported in part by AFOSR under the project ``LES Modeling of Non-local effects using Statistical Coarse-graining'' with Dr. Jean-Luc Cambier as the technical monitor.

System modeling with the DISC framework: evidence from safety-critical domains.

PubMed

Reiman, Teemu; Pietikäinen, Elina; Oedewald, Pia; Gotcheva, Nadezhda

2012-01-01

The objective of this paper is to illustrate the development and application of the Design for Integrated Safety Culture (DISC) framework for system modeling by evaluating organizational potential for safety in nuclear and healthcare domains. The DISC framework includes criteria for good safety culture and a description of functions that the organization needs to implement in order to orient the organization toward the criteria. Three case studies will be used to illustrate the utilization of the DISC framework in practice.

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.

Three-dimensional hydrogeologic framework model for use with a steady-state numerical ground-water flow model of the Death Valley regional flow system, Nevada and California

USGS Publications Warehouse

Belcher, Wayne R.; Faunt, Claudia C.; D'Agnese, Frank A.

2002-01-01

The U.S. Geological Survey, in cooperation with the Department of Energy and other Federal, State, and local agencies, is evaluating the hydrogeologic characteristics of the Death Valley regional ground-water flow system. The ground-water flow system covers an area of about 100,000 square kilometers from latitude 35? to 38?15' North to longitude 115? to 118? West, with the flow system proper comprising about 45,000 square kilometers. The Death Valley regional ground-water flow system is one of the larger flow systems within the Southwestern United States and includes in its boundaries the Nevada Test Site, Yucca Mountain, and much of Death Valley. Part of this study includes the construction of a three-dimensional hydrogeologic framework model to serve as the foundation for the development of a steady-state regional ground-water flow model. The digital framework model provides a computer-based description of the geometry and composition of the hydrogeologic units that control regional flow. The framework model of the region was constructed by merging two previous framework models constructed for the Yucca Mountain Project and the Environmental Restoration Program Underground Test Area studies at the Nevada Test Site. The hydrologic characteristics of the region result from a currently arid climate and complex geology. Interbasinal regional ground-water flow occurs through a thick carbonate-rock sequence of Paleozoic age, a locally thick volcanic-rock sequence of Tertiary age, and basin-fill alluvium of Tertiary and Quaternary age. Throughout the system, deep and shallow ground-water flow may be controlled by extensive and pervasive regional and local faults and fractures. The framework model was constructed using data from several sources to define the geometry of the regional hydrogeologic units. These data sources include (1) a 1:250,000-scale hydrogeologic-map compilation of the region; (2) regional-scale geologic cross sections; (3) borehole information, and (4) gridded surfaces from a previous three-dimensional geologic model. In addition, digital elevation model data were used in conjunction with these data to define ground-surface altitudes. These data, properly oriented in three dimensions by using geographic information systems, were combined and gridded to produce the upper surfaces of the hydrogeologic units used in the flow model. The final geometry of the framework model is constructed as a volumetric model by incorporating the intersections of these gridded surfaces and by applying fault truncation rules to structural features from the geologic map and cross sections. The cells defining the geometry of the hydrogeologic framework model can be assigned several attributes such as lithology, hydrogeologic unit, thickness, and top and bottom altitudes.

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 as OWL and RDF and written to XML Metadata Interchange (XMI) files for import into UML tools.

Classification framework for partially observed dynamical systems

NASA Astrophysics Data System (ADS)

Shen, Yuan; Tino, Peter; Tsaneva-Atanasova, Krasimira

2017-04-01

We present a general framework for classifying partially observed dynamical systems based on the idea of learning in the model space. In contrast to the existing approaches using point estimates of model parameters to represent individual data items, we employ posterior distributions over model parameters, thus taking into account in a principled manner the uncertainty due to both the generative (observational and/or dynamic noise) and observation (sampling in time) processes. We evaluate the framework on two test beds: a biological pathway model and a stochastic double-well system. Crucially, we show that the classification performance is not impaired when the model structure used for inferring posterior distributions is much more simple than the observation-generating model structure, provided the reduced-complexity inferential model structure captures the essential characteristics needed for the given classification task.

Design tool for estimating chemical hydrogen storage system characteristics for light-duty fuel cell vehicles

DOE Office of Scientific and Technical Information (OSTI.GOV)

Brooks, Kriston P.; Sprik, Samuel J.; Tamburello, David A.

The U.S. Department of Energy (DOE) has developed a vehicle framework model to simulate fuel cell-based light-duty vehicle operation for various hydrogen storage systems. This transient model simulates the performance of the storage system, fuel cell, and vehicle for comparison to DOE’s Technical Targets using four drive cycles/profiles. Chemical hydrogen storage models have been developed for the Framework model for both exothermic and endothermic materials. Despite the utility of such models, they require that material researchers input system design specifications that cannot be easily estimated. To address this challenge, a design tool has been developed that allows researchers to directlymore » enter kinetic and thermodynamic chemical hydrogen storage material properties into a simple sizing module that then estimates the systems parameters required to run the storage system model. Additionally, this design tool can be used as a standalone executable file to estimate the storage system mass and volume outside of the framework model and compare it to the DOE Technical Targets. These models will be explained and exercised with existing hydrogen storage materials.« less

Information system modeling for biomedical imaging applications

NASA Astrophysics Data System (ADS)

Hoo, Kent S., Jr.; Wong, Stephen T. C.

1999-07-01

Information system modeling has historically been relegated to a low priority among the designers of information systems. Often times, there is a rush to design and implement hardware and software solutions after only the briefest assessments of the domain requirements. Although this process results in a rapid development cycle, the system usually does not satisfy the needs of the users and the developers are forced to re-program certain aspects of the system. It would be much better to create an accurate model of the system based on the domain needs so that the implementation of the solution satisfies the needs of the users immediately. It would also be advantageous to build extensibility into the model so that updates to the system could be carried out in an organized fashion. The significance of this research is the development of a new formal framework for the construction of a multimedia medical information system. This formal framework is constructed using visual modeling which provides a way of thinking about problems using models organized around real- world ideas. These models provide an abstract way to view complex problems, making them easier for one to understand. The formal framework is the result of an object-oriented analysis and design process that translates the systems requirements and functionality into software models. The usefulness of this information framework is demonstrated with two different applications in epilepsy research and care, i.e., surgical planning of epilepsy and decision threshold determination.

Models for evaluating the performability of degradable computing systems

NASA Technical Reports Server (NTRS)

Wu, L. T.

1982-01-01

Recent advances in multiprocessor technology established the need for unified methods to evaluate computing systems performance and reliability. In response to this modeling need, a general modeling framework that permits the modeling, analysis and evaluation of degradable computing systems is considered. Within this framework, several user oriented performance variables are identified and shown to be proper generalizations of the traditional notions of system performance and reliability. Furthermore, a time varying version of the model is developed to generalize the traditional fault tree reliability evaluation methods of phased missions.

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.

Software Engineering Support of the Third Round of Scientific Grand Challenge Investigations: Earth System Modeling Software Framework Survey

NASA Technical Reports Server (NTRS)

Talbot, Bryan; Zhou, Shu-Jia; Higgins, Glenn; Zukor, Dorothy (Technical Monitor)

2002-01-01

One of the most significant challenges in large-scale climate modeling, as well as in high-performance computing in other scientific fields, is that of effectively integrating many software models from multiple contributors. A software framework facilitates the integration task, both in the development and runtime stages of the simulation. Effective software frameworks reduce the programming burden for the investigators, freeing them to focus more on the science and less on the parallel communication implementation. while maintaining high performance across numerous supercomputer and workstation architectures. This document surveys numerous software frameworks for potential use in Earth science modeling. Several frameworks are evaluated in depth, including Parallel Object-Oriented Methods and Applications (POOMA), Cactus (from (he relativistic physics community), Overture, Goddard Earth Modeling System (GEMS), the National Center for Atmospheric Research Flux Coupler, and UCLA/UCB Distributed Data Broker (DDB). Frameworks evaluated in less detail include ROOT, Parallel Application Workspace (PAWS), and Advanced Large-Scale Integrated Computational Environment (ALICE). A host of other frameworks and related tools are referenced in this context. The frameworks are evaluated individually and also compared with each other.

Reactive system verification case study: Fault-tolerant transputer communication

NASA Technical Reports Server (NTRS)

Crane, D. Francis; Hamory, Philip J.

1993-01-01

A reactive program is one which engages in an ongoing interaction with its environment. A system which is controlled by an embedded reactive program is called a reactive system. Examples of reactive systems are aircraft flight management systems, bank automatic teller machine (ATM) networks, airline reservation systems, and computer operating systems. Reactive systems are often naturally modeled (for logical design purposes) as a composition of autonomous processes which progress concurrently and which communicate to share information and/or to coordinate activities. Formal (i.e., mathematical) frameworks for system verification are tools used to increase the users' confidence that a system design satisfies its specification. A framework for reactive system verification includes formal languages for system modeling and for behavior specification and decision procedures and/or proof-systems for verifying that the system model satisfies the system specifications. Using the Ostroff framework for reactive system verification, an approach to achieving fault-tolerant communication between transputers was shown to be effective. The key components of the design, the decoupler processes, may be viewed as discrete-event-controllers introduced to constrain system behavior such that system specifications are satisfied. The Ostroff framework was also effective. The expressiveness of the modeling language permitted construction of a faithful model of the transputer network. The relevant specifications were readily expressed in the specification language. The set of decision procedures provided was adequate to verify the specifications of interest. The need for improved support for system behavior visualization is emphasized.

The ASCA Model and a Multi-Tiered System of Supports: A Framework to Support Students of Color with Problem Behavior

ERIC Educational Resources Information Center

Belser, Christopher T.; Shillingford, M. Ann; Joe, J. Richelle

2016-01-01

The American School Counselor Association (ASCA) National Model and a multi-tiered system of supports (MTSS) both provide frameworks for systematically solving problems in schools, including student behavior concerns. The authors outline a model that integrates overlapping elements of the National Model and MTSS as a support for marginalized…

A unifying framework for systems modeling, control systems design, and system operation

NASA Technical Reports Server (NTRS)

Dvorak, Daniel L.; Indictor, Mark B.; Ingham, Michel D.; Rasmussen, Robert D.; Stringfellow, Margaret V.

2005-01-01

Current engineering practice in the analysis and design of large-scale multi-disciplinary control systems is typified by some form of decomposition- whether functional or physical or discipline-based-that enables multiple teams to work in parallel and in relative isolation. Too often, the resulting system after integration is an awkward marriage of different control and data mechanisms with poor end-to-end accountability. System of systems engineering, which faces this problem on a large scale, cries out for a unifying framework to guide analysis, design, and operation. This paper describes such a framework based on a state-, model-, and goal-based architecture for semi-autonomous control systems that guides analysis and modeling, shapes control system software design, and directly specifies operational intent. This paper illustrates the key concepts in the context of a large-scale, concurrent, globally distributed system of systems: NASA's proposed Array-based Deep Space Network.

A Coupled Modeling Framework of the Co-evolution of Humans and Water: Case Study of Tarim River Basin, Western China

NASA Astrophysics Data System (ADS)

Liu, D.; Tian, F.; Lin, M.; Sivapalan, M.

2014-12-01

The complex interactions and feedbacks between humans and water are very essential issues but are poorly understood in the newly proposed discipline of socio-hydrology (Sivapalan et al., 2012). An exploratory model with the appropriate level of simplification can be valuable to improve our understanding of the co-evolution and self-organization of socio-hydrological systems driven by interactions and feedbacks operating at different scales. In this study, a simple coupled modeling framework for socio-hydrology co-evolution is developed for the Tarim River Basin in Western China, and is used to illustrate the explanatory power of such a model. The study area is the mainstream of the Tarim River, which is divided into two modeling units. The socio-hydrological system is composed of four parts, i.e., social sub-system, economic sub-system, ecological sub-system, and hydrological sub-system. In each modeling unit, four coupled ordinary differential equations are used to simulate the dynamics of the social sub-system represented by human population, the economic sub-system represented by irrigated crop area, the ecological sub-system represented by natural vegetation cover and the hydrological sub-system represented by stream discharge. The coupling and feedback processes of the four dominant sub-systems (and correspondingly four state variables) are integrated into several internal system characteristics interactively and jointly determined by themselves and by other coupled systems. For example, the stream discharge is coupled to the irrigated crop area by the colonization rate and mortality rate of the irrigated crop area in the upper reach and the irrigated area is coupled to stream discharge through irrigation water consumption. The co-evolution of the Tarim socio-hydrological system is then analyzed within this modeling framework to gain insights into the overall system dynamics and its sensitivity to the external drivers and internal system variables. In the modeling framework, the state of each subsystem is holistically described by one state variable and the framework is flexible enough to comprise more processes and constitutive relationships if they are needed to illustrate the interaction and feedback mechanisms of the human-water system.

Evolutionary game based control for biological systems with applications in drug delivery.

PubMed

Li, Xiaobo; Lenaghan, Scott C; Zhang, Mingjun

2013-06-07

Control engineering and analysis of biological systems have become increasingly important for systems and synthetic biology. Unfortunately, no widely accepted control framework is currently available for these systems, especially at the cell and molecular levels. This is partially due to the lack of appropriate mathematical models to describe the unique dynamics of biological systems, and the lack of implementation techniques, such as ultra-fast and ultra-small devices and corresponding control algorithms. This paper proposes a control framework for biological systems subject to dynamics that exhibit adaptive behavior under evolutionary pressures. The control framework was formulated based on evolutionary game based modeling, which integrates both the internal dynamics and the population dynamics. In the proposed control framework, the adaptive behavior was characterized as an internal dynamic, and the external environment was regarded as an external control input. The proposed open-interface control framework can be integrated with additional control algorithms for control of biological systems. To demonstrate the effectiveness of the proposed framework, an optimal control strategy was developed and validated for drug delivery using the pathogen Giardia lamblia as a test case. In principle, the proposed control framework can be applied to any biological system exhibiting adaptive behavior under evolutionary pressures. Copyright © 2013 Elsevier Ltd. All rights reserved.

Enhancing the Resilience of Interdependent Critical Infrastructure Systems Using a Common Computational Framework

NASA Astrophysics Data System (ADS)

Little, J. C.; Filz, G. M.

2016-12-01

As modern societies become more complex, critical interdependent infrastructure systems become more likely to fail under stress unless they are designed and implemented to be resilient. Hurricane Katrina clearly demonstrated the catastrophic and as yet unpredictable consequences of such failures. Resilient infrastructure systems maintain the flow of goods and services in the face of a broad range of natural and manmade hazards. In this presentation, we illustrate a generic computational framework to facilitate high-level decision-making about how to invest scarce resources most effectively to enhance resilience in coastal protection, transportation, and the economy of a region. Coastal Louisiana, our study area, has experienced the catastrophic effects of several land-falling hurricanes in recent years. In this project, we implement and further refine three process models (a coastal protection model, a transportation model, and an economic model) for the coastal Louisiana region. We upscale essential mechanistic features of the three detailed process models to the systems level and integrate the three reduced-order systems models in a modular fashion. We also evaluate the proposed approach in annual workshops with input from stakeholders. Based on stakeholder inputs, we derive a suite of goals, targets, and indicators for evaluating resilience at the systems level, and assess and enhance resilience using several deterministic scenarios. The unifying framework will be able to accommodate the different spatial and temporal scales that are appropriate for each model. We combine our generic computational framework, which encompasses the entire system of systems, with the targets, and indicators needed to systematically meet our chosen resilience goals. We will start with targets that focus on technical and economic systems, but future work will ensure that targets and indicators are extended to other dimensions of resilience including those in the environmental and social systems. The overall model can be used to optimize decision making in a probabilistic risk-based framework.

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...

Design and Application of an Ontology for Component-Based Modeling of Water Systems

NASA Astrophysics Data System (ADS)

Elag, M.; Goodall, J. L.

2012-12-01

Many Earth system modeling frameworks have adopted an approach of componentizing models so that a large model can be assembled by linking a set of smaller model components. These model components can then be more easily reused, extended, and maintained by a large group of model developers and end users. While there has been a notable increase in component-based model frameworks in the Earth sciences in recent years, there has been less work on creating framework-agnostic metadata and ontologies for model components. Well defined model component metadata is needed, however, to facilitate sharing, reuse, and interoperability both within and across Earth system modeling frameworks. To address this need, we have designed an ontology for the water resources community named the Water Resources Component (WRC) ontology in order to advance the application of component-based modeling frameworks across water related disciplines. Here we present the design of the WRC ontology and demonstrate its application for integration of model components used in watershed management. First we show how the watershed modeling system Soil and Water Assessment Tool (SWAT) can be decomposed into a set of hydrological and ecological components that adopt the Open Modeling Interface (OpenMI) standard. Then we show how the components can be used to estimate nitrogen losses from land to surface water for the Baltimore Ecosystem study area. Results of this work are (i) a demonstration of how the WRC ontology advances the conceptual integration between components of water related disciplines by handling the semantic and syntactic heterogeneity present when describing components from different disciplines and (ii) an investigation of a methodology by which large models can be decomposed into a set of model components that can be well described by populating metadata according to the WRC ontology.

An Integrated Modeling Framework Forecasting Ecosystem Exposure-- A Systems Approach to the Cumulative Impacts of Multiple Stressors

NASA Astrophysics Data System (ADS)

Johnston, J. M.

2013-12-01

Freshwater habitats provide fishable, swimmable and drinkable resources and are a nexus of geophysical and biological processes. These processes in turn influence the persistence and sustainability of populations, communities and ecosystems. Climate change and landuse change encompass numerous stressors of potential exposure, including the introduction of toxic contaminants, invasive species, and disease in addition to physical drivers such as temperature and hydrologic regime. A systems approach that includes the scientific and technologic basis of assessing the health of ecosystems is needed to effectively protect human health and the environment. The Integrated Environmental Modeling Framework 'iemWatersheds' has been developed as a consistent and coherent means of forecasting the cumulative impact of co-occurring stressors. The Framework consists of three facilitating technologies: Data for Environmental Modeling (D4EM) that automates the collection and standardization of input data; the Framework for Risk Assessment of Multimedia Environmental Systems (FRAMES) that manages the flow of information between linked models; and the Supercomputer for Model Uncertainty and Sensitivity Evaluation (SuperMUSE) that provides post-processing and analysis of model outputs, including uncertainty and sensitivity analysis. Five models are linked within the Framework to provide multimedia simulation capabilities for hydrology and water quality processes: the Soil Water Assessment Tool (SWAT) predicts surface water and sediment runoff and associated contaminants; the Watershed Mercury Model (WMM) predicts mercury runoff and loading to streams; the Water quality Analysis and Simulation Program (WASP) predicts water quality within the stream channel; the Habitat Suitability Index (HSI) model scores physicochemical habitat quality for individual fish species; and the Bioaccumulation and Aquatic System Simulator (BASS) predicts fish growth, population dynamics and bioaccumulation of toxic substances. The capability of the Framework to address cumulative impacts will be demonstrated for freshwater ecosystem services and mountaintop mining.

An Integrated Ensemble-Based Operational Framework to Predict Urban Flooding: A Case Study of Hurricane Sandy in the Passaic and Hackensack River Basins

NASA Astrophysics Data System (ADS)

Saleh, F.; Ramaswamy, V.; Georgas, N.; Blumberg, A. F.; Wang, Y.

2016-12-01

Advances in computational resources and modeling techniques are opening the path to effectively integrate existing complex models. In the context of flood prediction, recent extreme events have demonstrated the importance of integrating components of the hydrosystem to better represent the interactions amongst different physical processes and phenomena. As such, there is a pressing need to develop holistic and cross-disciplinary modeling frameworks that effectively integrate existing models and better represent the operative dynamics. This work presents a novel Hydrologic-Hydraulic-Hydrodynamic Ensemble (H3E) flood prediction framework that operationally integrates existing predictive models representing coastal (New York Harbor Observing and Prediction System, NYHOPS), hydrologic (US Army Corps of Engineers Hydrologic Modeling System, HEC-HMS) and hydraulic (2-dimensional River Analysis System, HEC-RAS) components. The state-of-the-art framework is forced with 125 ensemble meteorological inputs from numerical weather prediction models including the Global Ensemble Forecast System, the European Centre for Medium-Range Weather Forecasts (ECMWF), the Canadian Meteorological Centre (CMC), the Short Range Ensemble Forecast (SREF) and the North American Mesoscale Forecast System (NAM). The framework produces, within a 96-hour forecast horizon, on-the-fly Google Earth flood maps that provide critical information for decision makers and emergency preparedness managers. The utility of the framework was demonstrated by retrospectively forecasting an extreme flood event, hurricane Sandy in the Passaic and Hackensack watersheds (New Jersey, USA). Hurricane Sandy caused significant damage to a number of critical facilities in this area including the New Jersey Transit's main storage and maintenance facility. The results of this work demonstrate that ensemble based frameworks provide improved flood predictions and useful information about associated uncertainties, thus improving the assessment of risks as when compared to a deterministic forecast. The work offers perspectives for short-term flood forecasts, flood mitigation strategies and best management practices for climate change scenarios.

Sequential-Optimization-Based Framework for Robust Modeling and Design of Heterogeneous Catalytic Systems

DOE PAGES

Rangarajan, Srinivas; Maravelias, Christos T.; Mavrikakis, Manos

2017-11-09

Here, we present a general optimization-based framework for (i) ab initio and experimental data driven mechanistic modeling and (ii) optimal catalyst design of heterogeneous catalytic systems. Both cases are formulated as a nonlinear optimization problem that is subject to a mean-field microkinetic model and thermodynamic consistency requirements as constraints, for which we seek sparse solutions through a ridge (L 2 regularization) penalty. The solution procedure involves an iterative sequence of forward simulation of the differential algebraic equations pertaining to the microkinetic model using a numerical tool capable of handling stiff systems, sensitivity calculations using linear algebra, and gradient-based nonlinear optimization.more » A multistart approach is used to explore the solution space, and a hierarchical clustering procedure is implemented for statistically classifying potentially competing solutions. An example of methanol synthesis through hydrogenation of CO and CO 2 on a Cu-based catalyst is used to illustrate the framework. The framework is fast, is robust, and can be used to comprehensively explore the model solution and design space of any heterogeneous catalytic system.« less

Sequential-Optimization-Based Framework for Robust Modeling and Design of Heterogeneous Catalytic Systems

DOE Office of Scientific and Technical Information (OSTI.GOV)

Rangarajan, Srinivas; Maravelias, Christos T.; Mavrikakis, Manos

Here, we present a general optimization-based framework for (i) ab initio and experimental data driven mechanistic modeling and (ii) optimal catalyst design of heterogeneous catalytic systems. Both cases are formulated as a nonlinear optimization problem that is subject to a mean-field microkinetic model and thermodynamic consistency requirements as constraints, for which we seek sparse solutions through a ridge (L 2 regularization) penalty. The solution procedure involves an iterative sequence of forward simulation of the differential algebraic equations pertaining to the microkinetic model using a numerical tool capable of handling stiff systems, sensitivity calculations using linear algebra, and gradient-based nonlinear optimization.more » A multistart approach is used to explore the solution space, and a hierarchical clustering procedure is implemented for statistically classifying potentially competing solutions. An example of methanol synthesis through hydrogenation of CO and CO 2 on a Cu-based catalyst is used to illustrate the framework. The framework is fast, is robust, and can be used to comprehensively explore the model solution and design space of any heterogeneous catalytic system.« less

Model Based Mission Assurance: Emerging Opportunities for Robotic Systems

NASA Technical Reports Server (NTRS)

Evans, John W.; DiVenti, Tony

2016-01-01

The emergence of Model Based Systems Engineering (MBSE) in a Model Based Engineering framework has created new opportunities to improve effectiveness and efficiencies across the assurance functions. The MBSE environment supports not only system architecture development, but provides for support of Systems Safety, Reliability and Risk Analysis concurrently in the same framework. Linking to detailed design will further improve assurance capabilities to support failures avoidance and mitigation in flight systems. This also is leading new assurance functions including model assurance and management of uncertainty in the modeling environment. Further, the assurance cases, a structured hierarchal argument or model, are emerging as a basis for supporting a comprehensive viewpoint in which to support Model Based Mission Assurance (MBMA).

A framework for human-hydrologic system model development integrating hydrology and water management: application to the Cutzamala water system in Mexico

NASA Astrophysics Data System (ADS)

Wi, S.; Freeman, S.; Brown, C.

2017-12-01

This study presents a general approach to developing computational models of human-hydrologic systems where human modification of hydrologic surface processes are significant or dominant. A river basin system is represented by a network of human-hydrologic response units (HHRUs) identified based on locations where river regulations happen (e.g., reservoir operation and diversions). Natural and human processes in HHRUs are simulated in a holistic framework that integrates component models representing rainfall-runoff, river routing, reservoir operation, flow diversion and water use processes. We illustrate the approach in a case study of the Cutzamala water system (CWS) in Mexico, a complex inter-basin water transfer system supplying the Mexico City Metropolitan Area (MCMA). The human-hydrologic system model for CWS (CUTZSIM) is evaluated in terms of streamflow and reservoir storages measured across the CWS and to water supplied for MCMA. The CUTZSIM improves the representation of hydrology and river-operation interaction and, in so doing, advances evaluation of system-wide water management consequences under altered climatic and demand regimes. The integrated modeling framework enables evaluation and simulation of model errors throughout the river basin, including errors in representation of the human component processes. Heretofore, model error evaluation, predictive error intervals and the resultant improved understanding have been limited to hydrologic processes. The general framework represents an initial step towards fuller understanding and prediction of the many and varied processes that determine the hydrologic fluxes and state variables in real river basins.

A Generalized Decision Framework Using Multi-objective Optimization for Water Resources Planning

NASA Astrophysics Data System (ADS)

Basdekas, L.; Stewart, N.; Triana, E.

2013-12-01

Colorado Springs Utilities (CSU) is currently engaged in an Integrated Water Resource Plan (IWRP) to address the complex planning scenarios, across multiple time scales, currently faced by CSU. The modeling framework developed for the IWRP uses a flexible data-centered Decision Support System (DSS) with a MODSIM-based modeling system to represent the operation of the current CSU raw water system coupled with a state-of-the-art multi-objective optimization algorithm. Three basic components are required for the framework, which can be implemented for planning horizons ranging from seasonal to interdecadal. First, a water resources system model is required that is capable of reasonable system simulation to resolve performance metrics at the appropriate temporal and spatial scales of interest. The system model should be an existing simulation model, or one developed during the planning process with stakeholders, so that 'buy-in' has already been achieved. Second, a hydrologic scenario tool(s) capable of generating a range of plausible inflows for the planning period of interest is required. This may include paleo informed or climate change informed sequences. Third, a multi-objective optimization model that can be wrapped around the system simulation model is required. The new generation of multi-objective optimization models do not require parameterization which greatly reduces problem complexity. Bridging the gap between research and practice will be evident as we use a case study from CSU's planning process to demonstrate this framework with specific competing water management objectives. Careful formulation of objective functions, choice of decision variables, and system constraints will be discussed. Rather than treating results as theoretically Pareto optimal in a planning process, we use the powerful multi-objective optimization models as tools to more efficiently and effectively move out of the inferior decision space. The use of this framework will help CSU evaluate tradeoffs in a continually changing world.

An evaluation framework for Health Information Systems: human, organization and technology-fit factors (HOT-fit).

PubMed

Yusof, Maryati Mohd; Kuljis, Jasna; Papazafeiropoulou, Anastasia; Stergioulas, Lampros K

2008-06-01

The realization of Health Information Systems (HIS) requires rigorous evaluation that addresses technology, human and organization issues. Our review indicates that current evaluation methods evaluate different aspects of HIS and they can be improved upon. A new evaluation framework, human, organization and technology-fit (HOT-fit) was developed after having conducted a critical appraisal of the findings of existing HIS evaluation studies. HOT-fit builds on previous models of IS evaluation--in particular, the IS Success Model and the IT-Organization Fit Model. This paper introduces the new framework for HIS evaluation that incorporates comprehensive dimensions and measures of HIS and provides a technological, human and organizational fit. Literature review on HIS and IS evaluation studies and pilot testing of developed framework. The framework was used to evaluate a Fundus Imaging System (FIS) of a primary care organization in the UK. The case study was conducted through observation, interview and document analysis. The main findings show that having the right user attitude and skills base together with good leadership, IT-friendly environment and good communication can have positive influence on the system adoption. Comprehensive, specific evaluation factors, dimensions and measures in the new framework (HOT-fit) are applicable in HIS evaluation. The use of such a framework is argued to be useful not only for comprehensive evaluation of the particular FIS system under investigation, but potentially also for any Health Information System in general.

A prototype framework for models of socio-hydrology: identification of key feedback loops and parameterisation approach

NASA Astrophysics Data System (ADS)

Elshafei, Y.; Sivapalan, M.; Tonts, M.; Hipsey, M. R.

2014-06-01

It is increasingly acknowledged that, in order to sustainably manage global freshwater resources, it is critical that we better understand the nature of human-hydrology interactions at the broader catchment system scale. Yet to date, a generic conceptual framework for building models of catchment systems that include adequate representation of socioeconomic systems - and the dynamic feedbacks between human and natural systems - has remained elusive. In an attempt to work towards such a model, this paper outlines a generic framework for models of socio-hydrology applicable to agricultural catchments, made up of six key components that combine to form the coupled system dynamics: namely, catchment hydrology, population, economics, environment, socioeconomic sensitivity and collective response. The conceptual framework posits two novel constructs: (i) a composite socioeconomic driving variable, termed the Community Sensitivity state variable, which seeks to capture the perceived level of threat to a community's quality of life, and acts as a key link tying together one of the fundamental feedback loops of the coupled system, and (ii) a Behavioural Response variable as the observable feedback mechanism, which reflects land and water management decisions relevant to the hydrological context. The framework makes a further contribution through the introduction of three macro-scale parameters that enable it to normalise for differences in climate, socioeconomic and political gradients across study sites. In this way, the framework provides for both macro-scale contextual parameters, which allow for comparative studies to be undertaken, and catchment-specific conditions, by way of tailored "closure relationships", in order to ensure that site-specific and application-specific contexts of socio-hydrologic problems can be accommodated. To demonstrate how such a framework would be applied, two socio-hydrological case studies, taken from the Australian experience, are presented and the parameterisation approach that would be taken in each case is discussed. Preliminary findings in the case studies lend support to the conceptual theories outlined in the framework. It is envisioned that the application of this framework across study sites and gradients will aid in developing our understanding of the fundamental interactions and feedbacks in such complex human-hydrology systems, and allow hydrologists to improve social-ecological systems modelling through better representation of human feedbacks on hydrological processes.

The SAM framework: modeling the effects of management factors on human behavior in risk analysis.

PubMed

Murphy, D M; Paté-Cornell, M E

1996-08-01

Complex engineered systems, such as nuclear reactors and chemical plants, have the potential for catastrophic failure with disastrous consequences. In recent years, human and management factors have been recognized as frequent root causes of major failures in such systems. However, classical probabilistic risk analysis (PRA) techniques do not account for the underlying causes of these errors because they focus on the physical system and do not explicitly address the link between components' performance and organizational factors. This paper describes a general approach for addressing the human and management causes of system failure, called the SAM (System-Action-Management) framework. Beginning with a quantitative risk model of the physical system, SAM expands the scope of analysis to incorporate first the decisions and actions of individuals that affect the physical system. SAM then links management factors (incentives, training, policies and procedures, selection criteria, etc.) to those decisions and actions. The focus of this paper is on four quantitative models of action that describe this last relationship. These models address the formation of intentions for action and their execution as a function of the organizational environment. Intention formation is described by three alternative models: a rational model, a bounded rationality model, and a rule-based model. The execution of intentions is then modeled separately. These four models are designed to assess the probabilities of individual actions from the perspective of management, thus reflecting the uncertainties inherent to human behavior. The SAM framework is illustrated for a hypothetical case of hazardous materials transportation. This framework can be used as a tool to increase the safety and reliability of complex technical systems by modifying the organization, rather than, or in addition to, re-designing the physical system.

Development of a Dynamically Configurable, Object-Oriented Framework for Distributed, Multi-modal Computational Aerospace Systems Simulation

NASA Technical Reports Server (NTRS)

Afjeh, Abdollah A.; Reed, John A.

2003-01-01

The following reports are presented on this project:A first year progress report on: Development of a Dynamically Configurable,Object-Oriented Framework for Distributed, Multi-modal Computational Aerospace Systems Simulation; A second year progress report on: Development of a Dynamically Configurable, Object-Oriented Framework for Distributed, Multi-modal Computational Aerospace Systems Simulation; An Extensible, Interchangeable and Sharable Database Model for Improving Multidisciplinary Aircraft Design; Interactive, Secure Web-enabled Aircraft Engine Simulation Using XML Databinding Integration; and Improving the Aircraft Design Process Using Web-based Modeling and Simulation.

Analysis of Implicit Uncertain Systems. Part 1: Theoretical Framework

DTIC Science & Technology

1994-12-07

Analysis of Implicit Uncertain Systems Part I: Theoretical Framework Fernando Paganini * John Doyle 1 December 7, 1994 Abst rac t This paper...Analysis of Implicit Uncertain Systems Part I: Theoretical Framework 5a. CONTRACT NUMBER 5b. GRANT NUMBER 5c. PROGRAM ELEMENT NUMBER 6. AUTHOR(S...model and a number of constraints relevant to the analysis problem under consideration. In Part I of this paper we propose a theoretical framework which

A framework for scalable parameter estimation of gene circuit models using structural information.

PubMed

Kuwahara, Hiroyuki; Fan, Ming; Wang, Suojin; Gao, Xin

2013-07-01

Systematic and scalable parameter estimation is a key to construct complex gene regulatory models and to ultimately facilitate an integrative systems biology approach to quantitatively understand the molecular mechanisms underpinning gene regulation. Here, we report a novel framework for efficient and scalable parameter estimation that focuses specifically on modeling of gene circuits. Exploiting the structure commonly found in gene circuit models, this framework decomposes a system of coupled rate equations into individual ones and efficiently integrates them separately to reconstruct the mean time evolution of the gene products. The accuracy of the parameter estimates is refined by iteratively increasing the accuracy of numerical integration using the model structure. As a case study, we applied our framework to four gene circuit models with complex dynamics based on three synthetic datasets and one time series microarray data set. We compared our framework to three state-of-the-art parameter estimation methods and found that our approach consistently generated higher quality parameter solutions efficiently. Although many general-purpose parameter estimation methods have been applied for modeling of gene circuits, our results suggest that the use of more tailored approaches to use domain-specific information may be a key to reverse engineering of complex biological systems. http://sfb.kaust.edu.sa/Pages/Software.aspx. Supplementary data are available at Bioinformatics online.

A simulation framework for the CMS Track Trigger electronics

NASA Astrophysics Data System (ADS)

Amstutz, C.; Magazzù, G.; Weber, M.; Palla, F.

2015-03-01

A simulation framework has been developed to test and characterize algorithms, architectures and hardware implementations of the vastly complex CMS Track Trigger for the high luminosity upgrade of the CMS experiment at the Large Hadron Collider in Geneva. High-level SystemC models of all system components have been developed to simulate a portion of the track trigger. The simulation of the system components together with input data from physics simulations allows evaluating figures of merit, like delays or bandwidths, under realistic conditions. The use of SystemC for high-level modelling allows co-simulation with models developed in Hardware Description Languages, e.g. VHDL or Verilog. Therefore, the simulation framework can also be used as a test bench for digital modules developed for the final system.

The ABLe change framework: a conceptual and methodological tool for promoting systems change.

PubMed

Foster-Fishman, Pennie G; Watson, Erin R

2012-06-01

This paper presents a new approach to the design and implementation of community change efforts like a System of Care. Called the ABLe Change Framework, the model provides simultaneous attention to the content and process of the work, ensuring effective implementation and the pursuit of systems change. Three key strategies are employed in this model to ensure the integration of content and process efforts and effective mobilization of broad scale systems change: Systemic Action Learning Teams, Simple Rules, and Small Wins. In this paper we describe the ABLe Change Framework and present a case study in which we successfully applied this approach to one system of care effort in Michigan.

Development of an "Alert Framework" Based on the Practices in the Medical Front.

PubMed

Sakata, Takuya; Araki, Kenji; Yamazaki, Tomoyoshi; Kawano, Koichi; Maeda, Minoru; Kushima, Muneo; Araki, Sanae

2018-05-09

At the University of Miyazaki Hospital (UMH), we have accumulated and semantically structured a vast amount of medical information since the activation of the electronic health record system approximately 10 years ago. With this medical information, we have decided to develop an alert system for aiding in medical treatment. The purpose of this investigation is to not only to integrate an alert framework into the electronic heath record system, but also to formulate a modeling method of this knowledge. A trial alert framework was developed for the staff in various occupational categories at the UMH. Based on findings of subsequent interviews, a more detailed and upgraded alert framework was constructed, resulting in the final model. Based on our current findings, an alert framework was developed with four major items. Based on the analysis of the medical practices from the trial model, it has been concluded that there are four major risk patterns that trigger the alert. Furthermore, the current alert framework contains detailed definitions which are easily substituted into the database, leading to easy implementation of the electronic health records.

Pattern-oriented modeling of agent-based complex systems: Lessons from ecology

USGS Publications Warehouse

Grimm, Volker; Revilla, Eloy; Berger, Uta; Jeltsch, Florian; Mooij, Wolf M.; Railsback, Steven F.; Thulke, Hans-Hermann; Weiner, Jacob; Wiegand, Thorsten; DeAngelis, Donald L.

2005-01-01

Agent-based complex systems are dynamic networks of many interacting agents; examples include ecosystems, financial markets, and cities. The search for general principles underlying the internal organization of such systems often uses bottom-up simulation models such as cellular automata and agent-based models. No general framework for designing, testing, and analyzing bottom-up models has yet been established, but recent advances in ecological modeling have come together in a general strategy we call pattern-oriented modeling. This strategy provides a unifying framework for decoding the internal organization of agent-based complex systems and may lead toward unifying algorithmic theories of the relation between adaptive behavior and system complexity.

Pattern-Oriented Modeling of Agent-Based Complex Systems: Lessons from Ecology

NASA Astrophysics Data System (ADS)

Grimm, Volker; Revilla, Eloy; Berger, Uta; Jeltsch, Florian; Mooij, Wolf M.; Railsback, Steven F.; Thulke, Hans-Hermann; Weiner, Jacob; Wiegand, Thorsten; DeAngelis, Donald L.

2005-11-01

Agent-based complex systems are dynamic networks of many interacting agents; examples include ecosystems, financial markets, and cities. The search for general principles underlying the internal organization of such systems often uses bottom-up simulation models such as cellular automata and agent-based models. No general framework for designing, testing, and analyzing bottom-up models has yet been established, but recent advances in ecological modeling have come together in a general strategy we call pattern-oriented modeling. This strategy provides a unifying framework for decoding the internal organization of agent-based complex systems and may lead toward unifying algorithmic theories of the relation between adaptive behavior and system complexity.

Structure-based control of complex networks with nonlinear dynamics.

PubMed

Zañudo, Jorge Gomez Tejeda; Yang, Gang; Albert, Réka

2017-07-11

What can we learn about controlling a system solely from its underlying network structure? Here we adapt a recently developed framework for control of networks governed by a broad class of nonlinear dynamics that includes the major dynamic models of biological, technological, and social processes. This feedback-based framework provides realizable node overrides that steer a system toward any of its natural long-term dynamic behaviors, regardless of the specific functional forms and system parameters. We use this framework on several real networks, identify the topological characteristics that underlie the predicted node overrides, and compare its predictions to those of structural controllability in control theory. Finally, we demonstrate this framework's applicability in dynamic models of gene regulatory networks and identify nodes whose override is necessary for control in the general case but not in specific model instances.

NoSQL Based 3D City Model Management System

NASA Astrophysics Data System (ADS)

Mao, B.; Harrie, L.; Cao, J.; Wu, Z.; Shen, J.

2014-04-01

To manage increasingly complicated 3D city models, a framework based on NoSQL database is proposed in this paper. The framework supports import and export of 3D city model according to international standards such as CityGML, KML/COLLADA and X3D. We also suggest and implement 3D model analysis and visualization in the framework. For city model analysis, 3D geometry data and semantic information (such as name, height, area, price and so on) are stored and processed separately. We use a Map-Reduce method to deal with the 3D geometry data since it is more complex, while the semantic analysis is mainly based on database query operation. For visualization, a multiple 3D city representation structure CityTree is implemented within the framework to support dynamic LODs based on user viewpoint. Also, the proposed framework is easily extensible and supports geoindexes to speed up the querying. Our experimental results show that the proposed 3D city management system can efficiently fulfil the analysis and visualization requirements.

Creating an outcomes framework.

PubMed

Doerge, J B

2000-01-01

Four constructs used to build a framework for outcomes management for a large midwestern tertiary hospital are described in this article. A system framework outlining a model of clinical integration and population management based in Steven Shortell's work is discussed. This framework includes key definitions of high-risk patients, target groups, populations and community. Roles for each level of population management and how they were implemented in the health care system are described. A point of service framework centered on seven dimensions of care is the next construct applied on each nursing unit. The third construct outlines the framework for role development. Three roles for nursing were created to implement strategies for target groups that are strategic disease categories; two of those roles are described in depth. The philosophy of nursing practice is centered on caring and existential advocacy. The final construct is the modification of the Dartmouth model as a common framework for outcomes. System applications of the scorecard and lessons learned in the 2-year process of implementation are shared

Persistent model order reduction for complex dynamical systems using smooth orthogonal decomposition

NASA Astrophysics Data System (ADS)

Ilbeigi, Shahab; Chelidze, David

2017-11-01

Full-scale complex dynamic models are not effective for parametric studies due to the inherent constraints on available computational power and storage resources. A persistent reduced order model (ROM) that is robust, stable, and provides high-fidelity simulations for a relatively wide range of parameters and operating conditions can provide a solution to this problem. The fidelity of a new framework for persistent model order reduction of large and complex dynamical systems is investigated. The framework is validated using several numerical examples including a large linear system and two complex nonlinear systems with material and geometrical nonlinearities. While the framework is used for identifying the robust subspaces obtained from both proper and smooth orthogonal decompositions (POD and SOD, respectively), the results show that SOD outperforms POD in terms of stability, accuracy, and robustness.

Design tool for estimating chemical hydrogen storage system characteristics for light-duty fuel cell vehicles

DOE PAGES

Brooks, Kriston P.; Sprik, Samuel J.; Tamburello, David A.; ...

2018-04-07

The U.S. Department of Energy (DOE) developed a vehicle Framework model to simulate fuel cell-based light-duty vehicle operation for various hydrogen storage systems. This transient model simulates the performance of the storage system, fuel cell, and vehicle for comparison to Technical Targets established by DOE for four drive cycles/profiles. Chemical hydrogen storage models have been developed for the Framework for both exothermic and endothermic materials. Despite the utility of such models, they require that material researchers input system design specifications that cannot be estimated easily. To address this challenge, a design tool has been developed that allows researchers to directlymore » enter kinetic and thermodynamic chemical hydrogen storage material properties into a simple sizing module that then estimates system parameters required to run the storage system model. Additionally, the design tool can be used as a standalone executable file to estimate the storage system mass and volume outside of the Framework model. Here, these models will be explained and exercised with the representative hydrogen storage materials exothermic ammonia borane (NH 3BH 3) and endothermic alane (AlH 3).« less

Design tool for estimating chemical hydrogen storage system characteristics for light-duty fuel cell vehicles

DOE Office of Scientific and Technical Information (OSTI.GOV)

Brooks, Kriston P.; Sprik, Samuel J.; Tamburello, David A.

The U.S. Department of Energy (DOE) developed a vehicle Framework model to simulate fuel cell-based light-duty vehicle operation for various hydrogen storage systems. This transient model simulates the performance of the storage system, fuel cell, and vehicle for comparison to Technical Targets established by DOE for four drive cycles/profiles. Chemical hydrogen storage models have been developed for the Framework for both exothermic and endothermic materials. Despite the utility of such models, they require that material researchers input system design specifications that cannot be estimated easily. To address this challenge, a design tool has been developed that allows researchers to directlymore » enter kinetic and thermodynamic chemical hydrogen storage material properties into a simple sizing module that then estimates system parameters required to run the storage system model. Additionally, the design tool can be used as a standalone executable file to estimate the storage system mass and volume outside of the Framework model. Here, these models will be explained and exercised with the representative hydrogen storage materials exothermic ammonia borane (NH 3BH 3) and endothermic alane (AlH 3).« less

A Community Framework for Integrative, Coupled Modeling of Human-Earth Systems

NASA Astrophysics Data System (ADS)

Barton, C. M.; Nelson, G. C.; Tucker, G. E.; Lee, A.; Porter, C.; Ullah, I.; Hutton, E.; Hoogenboom, G.; Rogers, K. G.; Pritchard, C.

2017-12-01

We live today in a humanized world, where critical zone dynamics are driven by coupled human and biophysical processes. First generation modeling platforms have been invaluable in providing insight into dynamics of biophysical systems and social systems. But to understand today's humanized planet scientifically and to manage it sustainably, we need integrative modeling of this coupled human-Earth system. To address both scientific and policy questions, we also need modeling that can represent variable combinations of human-Earth system processes at multiple scales. Simply adding more code needed to do this to large, legacy first generation models is impractical, expensive, and will make them even more difficult to evaluate or understand. We need an approach to modeling that mirrors and benefits from the architecture of the complexly coupled systems we hope to model. Building on a series of international workshops over the past two years, we present a community framework to enable and support an ecosystem of diverse models as components that can be interconnected as needed to facilitate understanding of a range of complex human-earth systems interactions. Models are containerized in Docker to make them platform independent. A Basic Modeling Interface and Standard Names ontology (developed by the Community Surface Dynamics Modeling System) is applied to make them interoperable. They are then transformed into RESTful micro-services to allow them to be connected and run in a browser environment. This enables a flexible, multi-scale modeling environment to help address diverse issues with combinations of smaller, focused, component models that are easier to understand and evaluate. We plan to develop, deploy, and maintain this framework for integrated, coupled modeling in an open-source collaborative development environment that can democratize access to advanced technology and benefit from diverse global participation in model development. We also present an initial proof-of-concept of this framework, coupling a widely used agricultural crop model (DSSAT) with a widely used hydrology model (TopoFlow).

Metadata mapping and reuse in caBIG.

PubMed

Kunz, Isaac; Lin, Ming-Chin; Frey, Lewis

2009-02-05

This paper proposes that interoperability across biomedical databases can be improved by utilizing a repository of Common Data Elements (CDEs), UML model class-attributes and simple lexical algorithms to facilitate the building domain models. This is examined in the context of an existing system, the National Cancer Institute (NCI)'s cancer Biomedical Informatics Grid (caBIG). The goal is to demonstrate the deployment of open source tools that can be used to effectively map models and enable the reuse of existing information objects and CDEs in the development of new models for translational research applications. This effort is intended to help developers reuse appropriate CDEs to enable interoperability of their systems when developing within the caBIG framework or other frameworks that use metadata repositories. The Dice (di-grams) and Dynamic algorithms are compared and both algorithms have similar performance matching UML model class-attributes to CDE class object-property pairs. With algorithms used, the baselines for automatically finding the matches are reasonable for the data models examined. It suggests that automatic mapping of UML models and CDEs is feasible within the caBIG framework and potentially any framework that uses a metadata repository. This work opens up the possibility of using mapping algorithms to reduce cost and time required to map local data models to a reference data model such as those used within caBIG. This effort contributes to facilitating the development of interoperable systems within caBIG as well as other metadata frameworks. Such efforts are critical to address the need to develop systems to handle enormous amounts of diverse data that can be leveraged from new biomedical methodologies.

Modelling biological behaviours with the unified modelling language: an immunological case study and critique.

PubMed

Read, Mark; Andrews, Paul S; Timmis, Jon; Kumar, Vipin

2014-10-06

We present a framework to assist the diagrammatic modelling of complex biological systems using the unified modelling language (UML). The framework comprises three levels of modelling, ranging in scope from the dynamics of individual model entities to system-level emergent properties. By way of an immunological case study of the mouse disease experimental autoimmune encephalomyelitis, we show how the framework can be used to produce models that capture and communicate the biological system, detailing how biological entities, interactions and behaviours lead to higher-level emergent properties observed in the real world. We demonstrate how the UML can be successfully applied within our framework, and provide a critique of UML's ability to capture concepts fundamental to immunology and biology more generally. We show how specialized, well-explained diagrams with less formal semantics can be used where no suitable UML formalism exists. We highlight UML's lack of expressive ability concerning cyclic feedbacks in cellular networks, and the compounding concurrency arising from huge numbers of stochastic, interacting agents. To compensate for this, we propose several additional relationships for expressing these concepts in UML's activity diagram. We also demonstrate the ambiguous nature of class diagrams when applied to complex biology, and question their utility in modelling such dynamic systems. Models created through our framework are non-executable, and expressly free of simulation implementation concerns. They are a valuable complement and precursor to simulation specifications and implementations, focusing purely on thoroughly exploring the biology, recording hypotheses and assumptions, and serve as a communication medium detailing exactly how a simulation relates to the real biology.

Modelling biological behaviours with the unified modelling language: an immunological case study and critique

PubMed Central

Read, Mark; Andrews, Paul S.; Timmis, Jon; Kumar, Vipin

2014-01-01

We present a framework to assist the diagrammatic modelling of complex biological systems using the unified modelling language (UML). The framework comprises three levels of modelling, ranging in scope from the dynamics of individual model entities to system-level emergent properties. By way of an immunological case study of the mouse disease experimental autoimmune encephalomyelitis, we show how the framework can be used to produce models that capture and communicate the biological system, detailing how biological entities, interactions and behaviours lead to higher-level emergent properties observed in the real world. We demonstrate how the UML can be successfully applied within our framework, and provide a critique of UML's ability to capture concepts fundamental to immunology and biology more generally. We show how specialized, well-explained diagrams with less formal semantics can be used where no suitable UML formalism exists. We highlight UML's lack of expressive ability concerning cyclic feedbacks in cellular networks, and the compounding concurrency arising from huge numbers of stochastic, interacting agents. To compensate for this, we propose several additional relationships for expressing these concepts in UML's activity diagram. We also demonstrate the ambiguous nature of class diagrams when applied to complex biology, and question their utility in modelling such dynamic systems. Models created through our framework are non-executable, and expressly free of simulation implementation concerns. They are a valuable complement and precursor to simulation specifications and implementations, focusing purely on thoroughly exploring the biology, recording hypotheses and assumptions, and serve as a communication medium detailing exactly how a simulation relates to the real biology. PMID:25142524

A beamline systems model for Accelerator-Driven Transmutation Technology (ADTT) facilities

DOE Office of Scientific and Technical Information (OSTI.GOV)

Todd, A.M.M.; Paulson, C.C.; Peacock, M.A.

1995-10-01

A beamline systems code, that is being developed for Accelerator-Driven Transmutation Technology (ADTT) facility trade studies, is described. The overall program is a joint Grumman, G.H. Gillespie Associates (GHGA) and Los Alamos National Laboratory effort. The GHGA Accelerator Systems Model (ASM) has been adopted as the framework on which this effort is based. Relevant accelerator and beam transport models from earlier Grumman systems codes are being adapted to this framework. Preliminary physics and engineering models for each ADTT beamline component have been constructed. Examples noted include a Bridge Coupled Drift Tube Linac (BCDTL) and the accelerator thermal system. A decisionmore » has been made to confine the ASM framework principally to beamline modeling, while detailed target/blanket, balance-of-plant and facility costing analysis will be performed externally. An interfacing external balance-of-plant and facility costing model, which will permit the performance of iterative facility trade studies, is under separate development. An ABC (Accelerator Based Conversion) example is used to highlight the present models and capabilities.« less

A beamline systems model for Accelerator-Driven Transmutation Technology (ADTT) facilities

DOE Office of Scientific and Technical Information (OSTI.GOV)

Todd, Alan M. M.; Paulson, C. C.; Peacock, M. A.

1995-09-15

A beamline systems code, that is being developed for Accelerator-Driven Transmutation Technology (ADTT) facility trade studies, is described. The overall program is a joint Grumman, G. H. Gillespie Associates (GHGA) and Los Alamos National Laboratory effort. The GHGA Accelerator Systems Model (ASM) has been adopted as the framework on which this effort is based. Relevant accelerator and beam transport models from earlier Grumman systems codes are being adapted to this framework. Preliminary physics and engineering models for each ADTT beamline component have been constructed. Examples noted include a Bridge Coupled Drift Tube Linac (BCDTL) and the accelerator thermal system. Amore » decision has been made to confine the ASM framework principally to beamline modeling, while detailed target/blanket, balance-of-plant and facility costing analysis will be performed externally. An interfacing external balance-of-plant and facility costing model, which will permit the performance of iterative facility trade studies, is under separate development. An ABC (Accelerator Based Conversion) example is used to highlight the present models and capabilities.« less

DoD Lead System Integrator (LSI) Transformation - Creating a Model Based Acquisition Framework (MBAF)

DTIC Science & Technology

2014-04-30

cost to acquire systems as design maturity could be verified incrementally as the system was developed vice waiting for specific large “ big bang ...Framework (MBAF) be applied to simulate or optimize process variations on programs? LSI Roles and Responsibilities A review of the roles and...the model/process optimization process. It is the current intent that NAVAIR will use the model to run simulations on process changes in an attempt to

A modular approach to addressing model design, scale, and parameter estimation issues in distributed hydrological modelling

USGS Publications Warehouse

Leavesley, G.H.; Markstrom, S.L.; Restrepo, Pedro J.; Viger, R.J.

2002-01-01

A modular approach to model design and construction provides a flexible framework in which to focus the multidisciplinary research and operational efforts needed to facilitate the development, selection, and application of the most robust distributed modelling methods. A variety of modular approaches have been developed, but with little consideration for compatibility among systems and concepts. Several systems are proprietary, limiting any user interaction. The US Geological Survey modular modelling system (MMS) is a modular modelling framework that uses an open source software approach to enable all members of the scientific community to address collaboratively the many complex issues associated with the design, development, and application of distributed hydrological and environmental models. Implementation of a common modular concept is not a trivial task. However, it brings the resources of a larger community to bear on the problems of distributed modelling, provides a framework in which to compare alternative modelling approaches objectively, and provides a means of sharing the latest modelling advances. The concepts and components of the MMS are described and an example application of the MMS, in a decision-support system context, is presented to demonstrate current system capabilities. Copyright ?? 2002 John Wiley and Sons, Ltd.

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.

Towards a Decision Support System for Space Flight Operations

NASA Technical Reports Server (NTRS)

Meshkat, Leila; Hogle, Charles; Ruszkowski, James

2013-01-01

The Mission Operations Directorate (MOD) at the Johnson Space Center (JSC) has put in place a Model Based Systems Engineering (MBSE) technological framework for the development and execution of the Flight Production Process (FPP). This framework has provided much added value and return on investment to date. This paper describes a vision for a model based Decision Support System (DSS) for the development and execution of the FPP and its design and development process. The envisioned system extends the existing MBSE methodology and technological framework which is currently in use. The MBSE technological framework currently in place enables the systematic collection and integration of data required for building an FPP model for a diverse set of missions. This framework includes the technology, people and processes required for rapid development of architectural artifacts. It is used to build a feasible FPP model for the first flight of spacecraft and for recurrent flights throughout the life of the program. This model greatly enhances our ability to effectively engage with a new customer. It provides a preliminary work breakdown structure, data flow information and a master schedule based on its existing knowledge base. These artifacts are then refined and iterated upon with the customer for the development of a robust end-to-end, high-level integrated master schedule and its associated dependencies. The vision is to enhance this framework to enable its application for uncertainty management, decision support and optimization of the design and execution of the FPP by the program. Furthermore, this enhanced framework will enable the agile response and redesign of the FPP based on observed system behavior. The discrepancy of the anticipated system behavior and the observed behavior may be due to the processing of tasks internally, or due to external factors such as changes in program requirements or conditions associated with other organizations that are outside of MOD. The paper provides a roadmap for the three increments of this vision. These increments include (1) hardware and software system components and interfaces with the NASA ground system, (2) uncertainty management and (3) re-planning and automated execution. Each of these increments provide value independently; but some may also enable building of a subsequent increment.

ESPC Common Model Architecture Earth System Modeling Framework (ESMF) Software and Application Development

DTIC Science & Technology

2015-09-30

originate from NASA , NOAA , and community modeling efforts, and support for creation of the suite was shared by sponsors from other agencies. ESPS...Framework (ESMF) Software and Application Development Cecelia Deluca NESII/CIRES/ NOAA Earth System Research Laboratory 325 Broadway Boulder, CO...Capability (NUOPC) was established between NOAA and Navy to develop a common software architecture for easy and efficient interoperability. The

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...

[Computer aided design and rapid manufacturing of removable partial denture frameworks].

PubMed

Han, Jing; Lü, Pei-jun; Wang, Yong

2010-08-01

To introduce a method of digital modeling and fabricating removable partial denture (RPD) frameworks using self-developed software for RPD design and rapid manufacturing system. The three-dimensional data of two partially dentate dental casts were obtained using a three-dimensional crossing section scanner. Self-developed software package for RPD design was used to decide the path of insertion and to design different components of RPD frameworks. The components included occlusal rest, clasp, lingual bar, polymeric retention framework and maxillary major connector. The design procedure for the components was as following: first, determine the outline of the component. Second, build the tissue surface of the component using the scanned data within the outline. Third, preset cross section was used to produce the polished surface. Finally, different RPD components were modeled respectively and connected by minor connectors to form an integrated RPD framework. The finished data were imported into a self-developed selective laser melting (SLM) machine and metal frameworks were fabricated directly. RPD frameworks for the two scanned dental casts were modeled with this self-developed program and metal RPD frameworks were successfully fabricated using SLM method. The finished metal frameworks fit well on the plaster models. The self-developed computer aided design and computer aided manufacture (CAD-CAM) system for RPD design and fabrication has completely independent intellectual property rights. It provides a new method of manufacturing metal RPD frameworks.

A Data Analytical Framework for Improving Real-Time, Decision Support Systems in Healthcare

ERIC Educational Resources Information Center

Yahav, Inbal

2010-01-01

In this dissertation we develop a framework that combines data mining, statistics and operations research methods for improving real-time decision support systems in healthcare. Our approach consists of three main concepts: data gathering and preprocessing, modeling, and deployment. We introduce the notion of offline and semi-offline modeling to…

Approximation Methods for Inverse Problems Governed by Nonlinear Parabolic Systems

DTIC Science & Technology

1999-12-17

We present a rigorous theoretical framework for approximation of nonlinear parabolic systems with delays in the context of inverse least squares...numerical results demonstrating the convergence are given for a model of dioxin uptake and elimination in a distributed liver model that is a special case of the general theoretical framework .

Architectural frameworks: defining the structures for implementing learning health systems.

PubMed

Lessard, Lysanne; Michalowski, Wojtek; Fung-Kee-Fung, Michael; Jones, Lori; Grudniewicz, Agnes

2017-06-23

The vision of transforming health systems into learning health systems (LHSs) that rapidly and continuously transform knowledge into improved health outcomes at lower cost is generating increased interest in government agencies, health organizations, and health research communities. While existing initiatives demonstrate that different approaches can succeed in making the LHS vision a reality, they are too varied in their goals, focus, and scale to be reproduced without undue effort. Indeed, the structures necessary to effectively design and implement LHSs on a larger scale are lacking. In this paper, we propose the use of architectural frameworks to develop LHSs that adhere to a recognized vision while being adapted to their specific organizational context. Architectural frameworks are high-level descriptions of an organization as a system; they capture the structure of its main components at varied levels, the interrelationships among these components, and the principles that guide their evolution. Because these frameworks support the analysis of LHSs and allow their outcomes to be simulated, they act as pre-implementation decision-support tools that identify potential barriers and enablers of system development. They thus increase the chances of successful LHS deployment. We present an architectural framework for LHSs that incorporates five dimensions-goals, scientific, social, technical, and ethical-commonly found in the LHS literature. The proposed architectural framework is comprised of six decision layers that model these dimensions. The performance layer models goals, the scientific layer models the scientific dimension, the organizational layer models the social dimension, the data layer and information technology layer model the technical dimension, and the ethics and security layer models the ethical dimension. We describe the types of decisions that must be made within each layer and identify methods to support decision-making. In this paper, we outline a high-level architectural framework grounded in conceptual and empirical LHS literature. Applying this architectural framework can guide the development and implementation of new LHSs and the evolution of existing ones, as it allows for clear and critical understanding of the types of decisions that underlie LHS operations. Further research is required to assess and refine its generalizability and methods.

Control of Distributed Parameter Systems

DTIC Science & Technology

1990-08-01

vari- ant of the general Lotka - Volterra model for interspecific competition. The variant described the emergence of one subpopulation from another as a...distribut ion unlimited. I&. ARSTRACT (MAUMUnw2O1 A unified arioroximation framework for Parameter estimation In general linear POE models has been completed...unified approximation framework for parameter estimation in general linear PDE models. This framework has provided the theoretical basis for a number of

Modeling the Earth System, volume 3

NASA Technical Reports Server (NTRS)

Ojima, Dennis (Editor)

1992-01-01

The topics covered fall under the following headings: critical gaps in the Earth system conceptual framework; development needs for simplified models; and validating Earth system models and their subcomponents.

Dynamically analyzing cell interactions in biological environments using multiagent social learning framework.

PubMed

Zhang, Chengwei; Li, Xiaohong; Li, Shuxin; Feng, Zhiyong

2017-09-20

Biological environment is uncertain and its dynamic is similar to the multiagent environment, thus the research results of the multiagent system area can provide valuable insights to the understanding of biology and are of great significance for the study of biology. Learning in a multiagent environment is highly dynamic since the environment is not stationary anymore and each agent's behavior changes adaptively in response to other coexisting learners, and vice versa. The dynamics becomes more unpredictable when we move from fixed-agent interaction environments to multiagent social learning framework. Analytical understanding of the underlying dynamics is important and challenging. In this work, we present a social learning framework with homogeneous learners (e.g., Policy Hill Climbing (PHC) learners), and model the behavior of players in the social learning framework as a hybrid dynamical system. By analyzing the dynamical system, we obtain some conditions about convergence or non-convergence. We experimentally verify the predictive power of our model using a number of representative games. Experimental results confirm the theoretical analysis. Under multiagent social learning framework, we modeled the behavior of agent in biologic environment, and theoretically analyzed the dynamics of the model. We present some sufficient conditions about convergence or non-convergence and prove them theoretically. It can be used to predict the convergence of the system.

Proposed evaluation framework for assessing operator performance with multisensor displays

NASA Technical Reports Server (NTRS)

Foyle, David C.

1992-01-01

Despite aggressive work on the development of sensor fusion algorithms and techniques, no formal evaluation procedures have been proposed. Based on existing integration models in the literature, an evaluation framework is developed to assess an operator's ability to use multisensor, or sensor fusion, displays. The proposed evaluation framework for evaluating the operator's ability to use such systems is a normative approach: The operator's performance with the sensor fusion display can be compared to the models' predictions based on the operator's performance when viewing the original sensor displays prior to fusion. This allows for the determination as to when a sensor fusion system leads to: 1) poorer performance than one of the original sensor displays (clearly an undesirable system in which the fused sensor system causes some distortion or interference); 2) better performance than with either single sensor system alone, but at a sub-optimal (compared to the model predictions) level; 3) optimal performance (compared to model predictions); or, 4) super-optimal performance, which may occur if the operator were able to use some highly diagnostic 'emergent features' in the sensor fusion display, which were unavailable in the original sensor displays. An experiment demonstrating the usefulness of the proposed evaluation framework is discussed.

The GBT Dynamic Scheduling System: Powered by the Web

NASA Astrophysics Data System (ADS)

Marganian, P.; Clark, M.; McCarty, M.; Sessoms, E.; Shelton, A.

2009-09-01

The web technologies utilized for the Robert C. Byrd Green Bank Telescope's (GBT) new Dynamic Scheduling System are discussed, focusing on languages, frameworks, and tools. We use a popular Python web framework, TurboGears, to take advantage of the extensive web services the system provides. TurboGears is a model-view-controller framework, which aggregates SQLAlchemy, Genshi, and CherryPy respectively. On top of this framework, Javascript (Prototype, script.aculo.us, and JQuery) and cascading style sheets (Blueprint) are used for desktop-quality web pages.

IEA Wind Task 37: Systems Modeling Framework and Ontology for Wind Turbines and Plants

DOE Office of Scientific and Technical Information (OSTI.GOV)

Dykes, Katherine L; Zahle, Frederik; Merz, Karl

This presentation will provide an overview of progress to date in the development of a system modeling framework and ontology for wind turbines and plants as part of the larger IEA Wind Task 37 on wind energy systems engineering. The goals of the effort are to create a set of guidelines for a common conceptual architecture for wind turbines and plants so that practitioners can more easily share descriptions of wind turbines and plants across multiple parties and reduce the effort for translating descriptions between models; integrate different models together and collaborate on model development; and translate models among differentmore » levels of fidelity in the system.« less

A hybrid model of cell cycle in mammals.

PubMed

Behaegel, Jonathan; Comet, Jean-Paul; Bernot, Gilles; Cornillon, Emilien; Delaunay, Franck

2016-02-01

Time plays an essential role in many biological systems, especially in cell cycle. Many models of biological systems rely on differential equations, but parameter identification is an obstacle to use differential frameworks. In this paper, we present a new hybrid modeling framework that extends René Thomas' discrete modeling. The core idea is to associate with each qualitative state "celerities" allowing us to compute the time spent in each state. This hybrid framework is illustrated by building a 5-variable model of the mammalian cell cycle. Its parameters are determined by applying formal methods on the underlying discrete model and by constraining parameters using timing observations on the cell cycle. This first hybrid model presents the most important known behaviors of the cell cycle, including quiescent phase and endoreplication.

A 3D Human-Machine Integrated Design and Analysis Framework for Squat Exercises with a Smith Machine.

PubMed

Lee, Haerin; Jung, Moonki; Lee, Ki-Kwang; Lee, Sang Hun

2017-02-06

In this paper, we propose a three-dimensional design and evaluation framework and process based on a probabilistic-based motion synthesis algorithm and biomechanical analysis system for the design of the Smith machine and squat training programs. Moreover, we implemented a prototype system to validate the proposed framework. The framework consists of an integrated human-machine-environment model as well as a squat motion synthesis system and biomechanical analysis system. In the design and evaluation process, we created an integrated model in which interactions between a human body and machine or the ground are modeled as joints with constraints at contact points. Next, we generated Smith squat motion using the motion synthesis program based on a Gaussian process regression algorithm with a set of given values for independent variables. Then, using the biomechanical analysis system, we simulated joint moments and muscle activities from the input of the integrated model and squat motion. We validated the model and algorithm through physical experiments measuring the electromyography (EMG) signals, ground forces, and squat motions as well as through a biomechanical simulation of muscle forces. The proposed approach enables the incorporation of biomechanics in the design process and reduces the need for physical experiments and prototypes in the development of training programs and new Smith machines.

A 3D Human-Machine Integrated Design and Analysis Framework for Squat Exercises with a Smith Machine

PubMed Central

Lee, Haerin; Jung, Moonki; Lee, Ki-Kwang; Lee, Sang Hun

2017-01-01

In this paper, we propose a three-dimensional design and evaluation framework and process based on a probabilistic-based motion synthesis algorithm and biomechanical analysis system for the design of the Smith machine and squat training programs. Moreover, we implemented a prototype system to validate the proposed framework. The framework consists of an integrated human–machine–environment model as well as a squat motion synthesis system and biomechanical analysis system. In the design and evaluation process, we created an integrated model in which interactions between a human body and machine or the ground are modeled as joints with constraints at contact points. Next, we generated Smith squat motion using the motion synthesis program based on a Gaussian process regression algorithm with a set of given values for independent variables. Then, using the biomechanical analysis system, we simulated joint moments and muscle activities from the input of the integrated model and squat motion. We validated the model and algorithm through physical experiments measuring the electromyography (EMG) signals, ground forces, and squat motions as well as through a biomechanical simulation of muscle forces. The proposed approach enables the incorporation of biomechanics in the design process and reduces the need for physical experiments and prototypes in the development of training programs and new Smith machines. PMID:28178184

Conceptual Model-Based Systems Biology: Mapping Knowledge and Discovering Gaps in the mRNA Transcription Cycle

PubMed Central

Somekh, Judith; Choder, Mordechai; Dori, Dov

2012-01-01

We propose a Conceptual Model-based Systems Biology framework for qualitative modeling, executing, and eliciting knowledge gaps in molecular biology systems. The framework is an adaptation of Object-Process Methodology (OPM), a graphical and textual executable modeling language. OPM enables concurrent representation of the system's structure—the objects that comprise the system, and behavior—how processes transform objects over time. Applying a top-down approach of recursively zooming into processes, we model a case in point—the mRNA transcription cycle. Starting with this high level cell function, we model increasingly detailed processes along with participating objects. Our modeling approach is capable of modeling molecular processes such as complex formation, localization and trafficking, molecular binding, enzymatic stimulation, and environmental intervention. At the lowest level, similar to the Gene Ontology, all biological processes boil down to three basic molecular functions: catalysis, binding/dissociation, and transporting. During modeling and execution of the mRNA transcription model, we discovered knowledge gaps, which we present and classify into various types. We also show how model execution enhances a coherent model construction. Identification and pinpointing knowledge gaps is an important feature of the framework, as it suggests where research should focus and whether conjectures about uncertain mechanisms fit into the already verified model. PMID:23308089

Integrating human and natural systems in community psychology: an ecological model of stewardship behavior.

PubMed

Moskell, Christine; Allred, Shorna Broussard

2013-03-01

Community psychology (CP) research on the natural environment lacks a theoretical framework for analyzing the complex relationship between human systems and the natural world. We introduce other academic fields concerned with the interactions between humans and the natural environment, including environmental sociology and coupled human and natural systems. To demonstrate how the natural environment can be included within CP's ecological framework, we propose an ecological model of urban forest stewardship action. Although ecological models of behavior in CP have previously modeled health behaviors, we argue that these frameworks are also applicable to actions that positively influence the natural environment. We chose the environmental action of urban forest stewardship because cities across the United States are planting millions of trees and increased citizen participation in urban tree planting and stewardship will be needed to sustain the benefits provided by urban trees. We used the framework of an ecological model of behavior to illustrate multiple levels of factors that may promote or hinder involvement in urban forest stewardship actions. The implications of our model for the development of multi-level ecological interventions to foster stewardship actions are discussed, as well as directions for future research to further test and refine the model.

A Bayesian framework for adaptive selection, calibration, and validation of coarse-grained models of atomistic systems

NASA Astrophysics Data System (ADS)

Farrell, Kathryn; Oden, J. Tinsley; Faghihi, Danial

2015-08-01

A general adaptive modeling algorithm for selection and validation of coarse-grained models of atomistic systems is presented. A Bayesian framework is developed to address uncertainties in parameters, data, and model selection. Algorithms for computing output sensitivities to parameter variances, model evidence and posterior model plausibilities for given data, and for computing what are referred to as Occam Categories in reference to a rough measure of model simplicity, make up components of the overall approach. Computational results are provided for representative applications.

Automated numerical simulation of biological pattern formation based on visual feedback simulation framework

PubMed Central

Sun, Mingzhu; Xu, Hui; Zeng, Xingjuan; Zhao, Xin

2017-01-01

There are various fantastic biological phenomena in biological pattern formation. Mathematical modeling using reaction-diffusion partial differential equation systems is employed to study the mechanism of pattern formation. However, model parameter selection is both difficult and time consuming. In this paper, a visual feedback simulation framework is proposed to calculate the parameters of a mathematical model automatically based on the basic principle of feedback control. In the simulation framework, the simulation results are visualized, and the image features are extracted as the system feedback. Then, the unknown model parameters are obtained by comparing the image features of the simulation image and the target biological pattern. Considering two typical applications, the visual feedback simulation framework is applied to fulfill pattern formation simulations for vascular mesenchymal cells and lung development. In the simulation framework, the spot, stripe, labyrinthine patterns of vascular mesenchymal cells, the normal branching pattern and the branching pattern lacking side branching for lung branching are obtained in a finite number of iterations. The simulation results indicate that it is easy to achieve the simulation targets, especially when the simulation patterns are sensitive to the model parameters. Moreover, this simulation framework can expand to other types of biological pattern formation. PMID:28225811

Automated numerical simulation of biological pattern formation based on visual feedback simulation framework.

PubMed

Sun, Mingzhu; Xu, Hui; Zeng, Xingjuan; Zhao, Xin

2017-01-01

There are various fantastic biological phenomena in biological pattern formation. Mathematical modeling using reaction-diffusion partial differential equation systems is employed to study the mechanism of pattern formation. However, model parameter selection is both difficult and time consuming. In this paper, a visual feedback simulation framework is proposed to calculate the parameters of a mathematical model automatically based on the basic principle of feedback control. In the simulation framework, the simulation results are visualized, and the image features are extracted as the system feedback. Then, the unknown model parameters are obtained by comparing the image features of the simulation image and the target biological pattern. Considering two typical applications, the visual feedback simulation framework is applied to fulfill pattern formation simulations for vascular mesenchymal cells and lung development. In the simulation framework, the spot, stripe, labyrinthine patterns of vascular mesenchymal cells, the normal branching pattern and the branching pattern lacking side branching for lung branching are obtained in a finite number of iterations. The simulation results indicate that it is easy to achieve the simulation targets, especially when the simulation patterns are sensitive to the model parameters. Moreover, this simulation framework can expand to other types of biological pattern formation.

On accommodating spatial interactions in a Generalized Heterogeneous Data Model (GHDM) of mixed types of dependent variables.

DOT National Transportation Integrated Search

2015-12-01

We develop an econometric framework for incorporating spatial dependence in integrated model systems of latent variables and multidimensional mixed data outcomes. The framework combines Bhats Generalized Heterogeneous Data Model (GHDM) with a spat...

Framework Programmable Platform for the Advanced Software Development Workstation: Preliminary system design document

NASA Technical Reports Server (NTRS)

Mayer, Richard J.; Blinn, Thomas M.; Mayer, Paula S. D.; Ackley, Keith A.; Crump, John W., IV; Henderson, Richard; Futrell, Michael T.

1991-01-01

The Framework Programmable Software Development Platform (FPP) is a project aimed at combining effective tool and data integration mechanisms with a model of the software development process in an intelligent integrated software environment. Guided by the model, this system development framework will take advantage of an integrated operating environment to automate effectively the management of the software development process so that costly mistakes during the development phase can be eliminated. The focus here is on the design of components that make up the FPP. These components serve as supporting systems for the Integration Mechanism and the Framework Processor and provide the 'glue' that ties the FPP together. Also discussed are the components that allow the platform to operate in a distributed, heterogeneous environment and to manage the development and evolution of software system artifacts.

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…

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...

The water-energy nexus at water supply and its implications on the integrated water and energy management.

PubMed

Khalkhali, Masoumeh; Westphal, Kirk; Mo, Weiwei

2018-09-15

Water and energy are highly interdependent in the modern world, and hence, it is important to understand their constantly changing and nonlinear interconnections to inform the integrated management of water and energy. In this study, a hydrologic model, a water systems model, and an energy model were developed and integrated into a system dynamics modeling framework. This framework was then applied to a water supply system in the northeast US to capture its water-energy interactions under a set of future population, climate, and system operation scenarios. A hydrologic model was first used to simulate the system's hydrologic inflows and outflows under temperature and precipitation changes on a weekly-basis. A water systems model that combines the hydrologic model and management rules (e.g., water release and transfer) was then developed to dynamically simulate the system's water storage and water head. Outputs from the water systems model were used in the energy model to estimate hydropower generation. It was found that critical water-energy synergies and tradeoffs exist, and there is a possibility for integrated water and energy management to achieve better outcomes. This analysis also shows the importance of a holistic understanding of the systems as a whole, which would allow utility managers to make proactive long-term management decisions. The modeling framework is generalizable to other water supply systems with hydropower generation capacities to inform the integrated management of water and energy resources. Copyright © 2018 Elsevier B.V. All rights reserved.

An option space for early neural evolution.

PubMed

Jékely, Gáspár; Keijzer, Fred; Godfrey-Smith, Peter

2015-12-19

The origin of nervous systems has traditionally been discussed within two conceptual frameworks. Input-output models stress the sensory-motor aspects of nervous systems, while internal coordination models emphasize the role of nervous systems in coordinating multicellular activity, especially muscle-based motility. Here we consider both frameworks and apply them to describe aspects of each of three main groups of phenomena that nervous systems control: behaviour, physiology and development. We argue that both frameworks and all three aspects of nervous system function need to be considered for a comprehensive discussion of nervous system origins. This broad mapping of the option space enables an overview of the many influences and constraints that may have played a role in the evolution of the first nervous systems. © 2015 The Author(s).

Model Diagnostics for the Department of Energy's Accelerated Climate Modeling for Energy (ACME) Project

NASA Astrophysics Data System (ADS)

Smith, B.

2015-12-01

In 2014, eight Department of Energy (DOE) national laboratories, four academic institutions, one company, and the National Centre for Atmospheric Research combined forces in a project called Accelerated Climate Modeling for Energy (ACME) with the goal to speed Earth system model development for climate and energy. Over the planned 10-year span, the project will conduct simulations and modeling on DOE's most powerful high-performance computing systems at Oak Ridge, Argonne, and Lawrence Berkeley Leadership Compute Facilities. A key component of the ACME project is the development of an interactive test bed for the advanced Earth system model. Its execution infrastructure will accelerate model development and testing cycles. The ACME Workflow Group is leading the efforts to automate labor-intensive tasks, provide intelligent support for complex tasks and reduce duplication of effort through collaboration support. As part of this new workflow environment, we have created a diagnostic, metric, and intercomparison Python framework, called UVCMetrics, to aid in the testing-to-production execution of the ACME model. The framework exploits similarities among different diagnostics to compactly support diagnosis of new models. It presently focuses on atmosphere and land but is designed to support ocean and sea ice model components as well. This framework is built on top of the existing open-source software framework known as the Ultrascale Visualization Climate Data Analysis Tools (UV-CDAT). Because of its flexible framework design, scientists and modelers now can generate thousands of possible diagnostic outputs. These diagnostics can compare model runs, compare model vs. observation, or simply verify a model is physically realistic. Additional diagnostics are easily integrated into the framework, and our users have already added several. Diagnostics can be generated, viewed, and manipulated from the UV-CDAT graphical user interface, Python command line scripts and programs, and web browsers. The framework is designed to be scalable to large datasets, yet easy to use and familiar to scientists using previous tools. Integration in the ACME overall user interface facilitates data publication, further analysis, and quick feedback to model developers and scientists making component or coupled model runs.

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

DOE Office of Scientific and Technical Information (OSTI.GOV)

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

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

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

Multimedia-modeling integration development environment

DOE Office of Scientific and Technical Information (OSTI.GOV)

Pelton, Mitchell A.; Hoopes, Bonnie L.

2002-09-02

There are many framework systems available; however, the purpose of the framework presented here is to capitalize on the successes of the Framework for Risk Analysis in Multimedia Environmental Systems (FRAMES) and Multi-media Multi-pathway Multi-receptor Risk Assessment (3MRA) methodology as applied to the Hazardous Waste Identification Rule (HWIR) while focusing on the development of software tools to simplify the module developer?s effort of integrating a module into the framework.

A Model Independent S/W Framework for Search-Based Software Testing

PubMed Central

Baik, Jongmoon

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. PMID:25302314

Rule-based graph theory to enable exploration of the space system architecture design space

NASA Astrophysics Data System (ADS)

Arney, Dale Curtis

The primary goal of this research is to improve upon system architecture modeling in order to enable the exploration of design space options. A system architecture is the description of the functional and physical allocation of elements and the relationships, interactions, and interfaces between those elements necessary to satisfy a set of constraints and requirements. The functional allocation defines the functions that each system (element) performs, and the physical allocation defines the systems required to meet those functions. Trading the functionality between systems leads to the architecture-level design space that is available to the system architect. The research presents a methodology that enables the modeling of complex space system architectures using a mathematical framework. To accomplish the goal of improved architecture modeling, the framework meets five goals: technical credibility, adaptability, flexibility, intuitiveness, and exhaustiveness. The framework is technically credible, in that it produces an accurate and complete representation of the system architecture under consideration. The framework is adaptable, in that it provides the ability to create user-specified locations, steady states, and functions. The framework is flexible, in that it allows the user to model system architectures to multiple destinations without changing the underlying framework. The framework is intuitive for user input while still creating a comprehensive mathematical representation that maintains the necessary information to completely model complex system architectures. Finally, the framework is exhaustive, in that it provides the ability to explore the entire system architecture design space. After an extensive search of the literature, graph theory presents a valuable mechanism for representing the flow of information or vehicles within a simple mathematical framework. Graph theory has been used in developing mathematical models of many transportation and network flow problems in the past, where nodes represent physical locations and edges represent the means by which information or vehicles travel between those locations. In space system architecting, expressing the physical locations (low-Earth orbit, low-lunar orbit, etc.) and steady states (interplanetary trajectory) as nodes and the different means of moving between the nodes (propulsive maneuvers, etc.) as edges formulates a mathematical representation of this design space. The selection of a given system architecture using graph theory entails defining the paths that the systems take through the space system architecture graph. A path through the graph is defined as a list of edges that are traversed, which in turn defines functions performed by the system. A structure to compactly represent this information is a matrix, called the system map, in which the column indices are associated with the systems that exist and row indices are associated with the edges, or functions, to which each system has access. Several contributions have been added to the state of the art in space system architecture analysis. The framework adds the capability to rapidly explore the design space without the need to limit trade options or the need for user interaction during the exploration process. The unique mathematical representation of a system architecture, through the use of the adjacency, incidence, and system map matrices, enables automated design space exploration using stochastic optimization processes. The innovative rule-based graph traversal algorithm ensures functional feasibility of each system architecture that is analyzed, and the automatic generation of the system hierarchy eliminates the need for the user to manually determine the relationships between systems during or before the design space exploration process. Finally, the rapid evaluation of system architectures for various mission types enables analysis of the system architecture design space for multiple destinations within an evolutionary exploration program. (Abstract shortened by UMI.).

Computational Model for Ethnographically Informed Systems Design

NASA Astrophysics Data System (ADS)

Iqbal, Rahat; James, Anne; Shah, Nazaraf; Terken, Jacuqes

This paper presents a computational model for ethnographically informed systems design that can support complex and distributed cooperative activities. This model is based on an ethnographic framework consisting of three important dimensions (e.g., distributed coordination, awareness of work and plans and procedure), and the BDI (Belief, Desire and Intention) model of intelligent agents. The ethnographic framework is used to conduct ethnographic analysis and to organise ethnographically driven information into three dimensions, whereas the BDI model allows such information to be mapped upon the underlying concepts of multi-agent systems. The advantage of this model is that it is built upon an adaptation of existing mature and well-understood techniques. By the use of this model, we also address the cognitive aspects of systems design.

A Qualitative Simulation Framework in Smalltalk Based on Fuzzy Arithmetic

Treesearch

Richard L. Olson; Daniel L. Schmoldt; David L. Peterson

1996-01-01

For many systems, it is not practical to collect and correlate empirical data necessary to formulate a mathematical model. However, it is often sufficient to predict qualitative dynamics effects (as opposed to system quantities), especially for research purposes. In this effort, an object-oriented application framework (AF) was developed for the qualitative modeling of...

Predictive Models and Computational Embryology

EPA Science Inventory

EPA’s ‘virtual embryo’ project is building an integrative systems biology framework for predictive models of developmental toxicity. One schema involves a knowledge-driven adverse outcome pathway (AOP) framework utilizing information from public databases, standardized ontologies...

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, time interpolators and unit converters) as necessary to mediate the differences between them so they can work together. This talk will first review two key products of the CSDMS project, namely a standardized model interface called the Basic Model Interface (BMI) and the CSDMS Standard Names. The standard names are used in conjunction with BMI to provide a semantic matching mechanism that allows output variables from one process model or data set to be reliably used as input variables to other process models in a collection. They include not just a standardized naming scheme for model variables, but also a standardized set of terms for describing the attributes and assumptions of a given model. Recent efforts to bring powerful uncertainty analysis and inverse modeling toolkits such as DAKOTA into modeling frameworks will also be described. This talk will conclude with an overview of several related modeling projects that have been funded by NSF's EarthCube initiative, namely the Earth System Bridge, OntoSoft and GeoSemantics projects.

Metadata mapping and reuse in caBIG™

PubMed Central

Kunz, Isaac; Lin, Ming-Chin; Frey, Lewis

2009-01-01

Background This paper proposes that interoperability across biomedical databases can be improved by utilizing a repository of Common Data Elements (CDEs), UML model class-attributes and simple lexical algorithms to facilitate the building domain models. This is examined in the context of an existing system, the National Cancer Institute (NCI)'s cancer Biomedical Informatics Grid (caBIG™). The goal is to demonstrate the deployment of open source tools that can be used to effectively map models and enable the reuse of existing information objects and CDEs in the development of new models for translational research applications. This effort is intended to help developers reuse appropriate CDEs to enable interoperability of their systems when developing within the caBIG™ framework or other frameworks that use metadata repositories. Results The Dice (di-grams) and Dynamic algorithms are compared and both algorithms have similar performance matching UML model class-attributes to CDE class object-property pairs. With algorithms used, the baselines for automatically finding the matches are reasonable for the data models examined. It suggests that automatic mapping of UML models and CDEs is feasible within the caBIG™ framework and potentially any framework that uses a metadata repository. Conclusion This work opens up the possibility of using mapping algorithms to reduce cost and time required to map local data models to a reference data model such as those used within caBIG™. This effort contributes to facilitating the development of interoperable systems within caBIG™ as well as other metadata frameworks. Such efforts are critical to address the need to develop systems to handle enormous amounts of diverse data that can be leveraged from new biomedical methodologies. PMID:19208192

Learning to learn causal models.

PubMed

Kemp, Charles; Goodman, Noah D; Tenenbaum, Joshua B

2010-09-01

Learning to understand a single causal system can be an achievement, but humans must learn about multiple causal systems over the course of a lifetime. We present a hierarchical Bayesian framework that helps to explain how learning about several causal systems can accelerate learning about systems that are subsequently encountered. Given experience with a set of objects, our framework learns a causal model for each object and a causal schema that captures commonalities among these causal models. The schema organizes the objects into categories and specifies the causal powers and characteristic features of these categories and the characteristic causal interactions between categories. A schema of this kind allows causal models for subsequent objects to be rapidly learned, and we explore this accelerated learning in four experiments. Our results confirm that humans learn rapidly about the causal powers of novel objects, and we show that our framework accounts better for our data than alternative models of causal learning. Copyright © 2010 Cognitive Science Society, Inc.

Modeling formalisms in Systems Biology

PubMed Central

2011-01-01

Systems Biology has taken advantage of computational tools and high-throughput experimental data to model several biological processes. These include signaling, gene regulatory, and metabolic networks. However, most of these models are specific to each kind of network. Their interconnection demands a whole-cell modeling framework for a complete understanding of cellular systems. We describe the features required by an integrated framework for modeling, analyzing and simulating biological processes, and review several modeling formalisms that have been used in Systems Biology including Boolean networks, Bayesian networks, Petri nets, process algebras, constraint-based models, differential equations, rule-based models, interacting state machines, cellular automata, and agent-based models. We compare the features provided by different formalisms, and discuss recent approaches in the integration of these formalisms, as well as possible directions for the future. PMID:22141422

A Model-based Framework for Risk Assessment in Human-Computer Controlled Systems

NASA Technical Reports Server (NTRS)

Hatanaka, Iwao

2000-01-01

The rapid growth of computer technology and innovation has played a significant role in the rise of computer automation of human tasks in modem production systems across all industries. Although the rationale for automation has been to eliminate "human error" or to relieve humans from manual repetitive tasks, various computer-related hazards and accidents have emerged as a direct result of increased system complexity attributed to computer automation. The risk assessment techniques utilized for electromechanical systems are not suitable for today's software-intensive systems or complex human-computer controlled systems. This thesis will propose a new systemic model-based framework for analyzing risk in safety-critical systems where both computers and humans are controlling safety-critical functions. A new systems accident model will be developed based upon modem systems theory and human cognitive processes to better characterize system accidents, the role of human operators, and the influence of software in its direct control of significant system functions. Better risk assessments will then be achievable through the application of this new framework to complex human-computer controlled systems.

Using an Integrated, Multi-disciplinary Framework to Support Quantitative Microbial Risk Assessments

EPA Science Inventory

The Framework for Risk Analysis in Multimedia Environmental Systems (FRAMES) provides the infrastructure to link disparate models and databases seamlessly, giving an assessor the ability to construct an appropriate conceptual site model from a host of modeling choices, so a numbe...

A Framework for Curriculum Research.

ERIC Educational Resources Information Center

Kimpston, Richard D.; Rogers, Karen B.

1986-01-01

A framework for generating curriculum research is proposed from a synthesis of Dunkin and Biddle's model of teaching variables with Beauchamp's "curriculum system" planning functions. The framework systematically defines variables that delineate curriculum planning processes. (CJH)

Numerical Coupling and Simulation of Point-Mass System with the Turbulent Fluid Flow

NASA Astrophysics Data System (ADS)

Gao, Zheng

A computational framework that combines the Eulerian description of the turbulence field with a Lagrangian point-mass ensemble is proposed in this dissertation. Depending on the Reynolds number, the turbulence field is simulated using Direct Numerical Simulation (DNS) or eddy viscosity model. In the meanwhile, the particle system, such as spring-mass system and cloud droplets, are modeled using the ordinary differential system, which is stiff and hence poses a challenge to the stability of the entire system. This computational framework is applied to the numerical study of parachute deceleration and cloud microphysics. These two distinct problems can be uniformly modeled with Partial Differential Equations (PDEs) and Ordinary Differential Equations (ODEs), and numerically solved in the same framework. For the parachute simulation, a novel porosity model is proposed to simulate the porous effects of the parachute canopy. This model is easy to implement with the projection method and is able to reproduce Darcy's law observed in the experiment. Moreover, the impacts of using different versions of k-epsilon turbulence model in the parachute simulation have been investigated and conclude that the standard and Re-Normalisation Group (RNG) model may overestimate the turbulence effects when Reynolds number is small while the Realizable model has a consistent performance with both large and small Reynolds number. For another application, cloud microphysics, the cloud entrainment-mixing problem is studied in the same numerical framework. Three sets of DNS are carried out with both decaying and forced turbulence. The numerical result suggests a new way parameterize the cloud mixing degree using the dynamical measures. The numerical experiments also verify the negative relationship between the droplets number concentration and the vorticity field. The results imply that the gravity has fewer impacts on the forced turbulence than the decaying turbulence. In summary, the proposed framework can be used to solve a physics problem that involves turbulence field and point-mass system, and therefore has a broad application.

Understanding Illinois Principals' Concerns Implementing Charlotte Danielson's Framework for Teaching as a Model for Evaluation

ERIC Educational Resources Information Center

Mckenna, George Tucker

2017-01-01

The purpose of this study is to determine the levels of concern of Illinois principals regarding the adoption of an evaluation system modeled after Charlotte Danielson's Framework for Teaching. Principal demographics and involvement in the use of and professional development surrounding Charlotte Danielson's Framework for Teaching were studied for…

Threat driven modeling framework using petri nets for e-learning system.

PubMed

Khamparia, Aditya; Pandey, Babita

2016-01-01

Vulnerabilities at various levels are main cause of security risks in e-learning system. This paper presents a modified threat driven modeling framework, to identify the threats after risk assessment which requires mitigation and how to mitigate those threats. To model those threat mitigations aspects oriented stochastic petri nets are used. This paper included security metrics based on vulnerabilities present in e-learning system. The Common Vulnerability Scoring System designed to provide a normalized method for rating vulnerabilities which will be used as basis in metric definitions and calculations. A case study has been also proposed which shows the need and feasibility of using aspect oriented stochastic petri net models for threat modeling which improves reliability, consistency and robustness of the e-learning system.

A Flexible framework for forward and inverse modeling of stormwater control measures

NASA Astrophysics Data System (ADS)

Aflaki, S.; Massoudieh, A.

2016-12-01

Models that allow for design considerations of green infrastructure (GI) practices to control stormwater runoff and associated contaminants have received considerable attention in recent years. While popular, generally, the GI models are relatively simplistic. However, GI model predictions are being relied upon by many municipalities and State/Local agencies to make decisions about grey vs. green infrastructure improvement planning. Adding complexity to GI modeling frameworks may preclude their use in simpler urban planning situations. Therefore, the goal here was to develop a sophisticated, yet flexible tool that could be used by design engineers and researchers to capture and explore the effect of design factors and properties of the media used in the performance of GI systems at a relatively small scale. We deemed it essential to have a flexible GI modeling tool that is capable of simulating GI system components and specific biophysical processes affecting contaminants such as reactions, and particle-associated transport accurately while maintaining a high degree of flexibly to account for the myriad of GI alternatives. The mathematical framework for a stand-alone GI performance assessment tool has been developed and will be demonstrated. The process-based model framework developed here can be used to model a diverse range of GI practices such as green roof, retention pond, bioretention, infiltration trench, permeable pavement and other custom-designed combinatory systems. Four demonstration applications covering a diverse range of systems will be presented. The example applications include a evaluating hydraulic performance of a complex bioretention system, hydraulic analysis of porous pavement system, flow colloid-facilitated transport, reactive transport and groundwater recharge underneath an infiltration pond and finally reactive transport and bed-sediment interactions in a wetland system will be presented.

A novel framework of tissue membrane systems for image fusion.

PubMed

Zhang, Zulin; Yi, Xinzhong; Peng, Hong

2014-01-01

This paper proposes a tissue membrane system-based framework to deal with the optimal image fusion problem. A spatial domain fusion algorithm is given, and a tissue membrane system of multiple cells is used as its computing framework. Based on the multicellular structure and inherent communication mechanism of the tissue membrane system, an improved velocity-position model is developed. The performance of the fusion framework is studied with comparison of several traditional fusion methods as well as genetic algorithm (GA)-based and differential evolution (DE)-based spatial domain fusion methods. Experimental results show that the proposed fusion framework is superior or comparable to the other methods and can be efficiently used for image fusion.

An ontology for component-based models of water resource systems

NASA Astrophysics Data System (ADS)

Elag, Mostafa; Goodall, Jonathan L.

2013-08-01

Component-based modeling is an approach for simulating water resource systems where a model is composed of a set of components, each with a defined modeling objective, interlinked through data exchanges. Component-based modeling frameworks are used within the hydrologic, atmospheric, and earth surface dynamics modeling communities. While these efforts have been advancing, it has become clear that the water resources modeling community in particular, and arguably the larger earth science modeling community as well, faces a challenge of fully and precisely defining the metadata for model components. The lack of a unified framework for model component metadata limits interoperability between modeling communities and the reuse of models across modeling frameworks due to ambiguity about the model and its capabilities. To address this need, we propose an ontology for water resources model components that describes core concepts and relationships using the Web Ontology Language (OWL). The ontology that we present, which is termed the Water Resources Component (WRC) ontology, is meant to serve as a starting point that can be refined over time through engagement by the larger community until a robust knowledge framework for water resource model components is achieved. This paper presents the methodology used to arrive at the WRC ontology, the WRC ontology itself, and examples of how the ontology can aid in component-based water resources modeling by (i) assisting in identifying relevant models, (ii) encouraging proper model coupling, and (iii) facilitating interoperability across earth science modeling frameworks.

Design of the HELICS High-Performance Transmission-Distribution-Communication-Market Co-Simulation Framework

DOE Office of Scientific and Technical Information (OSTI.GOV)

Palmintier, Bryan S; Krishnamurthy, Dheepak; Top, Philip

This paper describes the design rationale for a new cyber-physical-energy co-simulation framework for electric power systems. This new framework will support very large-scale (100,000+ federates) co-simulations with off-the-shelf power-systems, communication, and end-use models. Other key features include cross-platform operating system support, integration of both event-driven (e.g. packetized communication) and time-series (e.g. power flow) simulation, and the ability to co-iterate among federates to ensure model convergence at each time step. After describing requirements, we begin by evaluating existing co-simulation frameworks, including HLA and FMI, and conclude that none provide the required features. Then we describe the design for the new layeredmore » co-simulation architecture.« less

Design of the HELICS High-Performance Transmission-Distribution-Communication-Market Co-Simulation Framework: Preprint

DOE Office of Scientific and Technical Information (OSTI.GOV)

Palmintier, Bryan S; Krishnamurthy, Dheepak; Top, Philip

This paper describes the design rationale for a new cyber-physical-energy co-simulation framework for electric power systems. This new framework will support very large-scale (100,000+ federates) co-simulations with off-the-shelf power-systems, communication, and end-use models. Other key features include cross-platform operating system support, integration of both event-driven (e.g. packetized communication) and time-series (e.g. power flow) simulation, and the ability to co-iterate among federates to ensure model convergence at each time step. After describing requirements, we begin by evaluating existing co-simulation frameworks, including HLA and FMI, and conclude that none provide the required features. Then we describe the design for the new layeredmore » co-simulation architecture.« less

Using a systems orientation and foundational theory to enhance theory-driven human service program evaluations.

PubMed

Wasserman, Deborah L

2010-05-01

This paper offers a framework for using a systems orientation and "foundational theory" to enhance theory-driven evaluations and logic models. The framework guides the process of identifying and explaining operative relationships and perspectives within human service program systems. Self-Determination Theory exemplifies how a foundational theory can be used to support the framework in a wide range of program evaluations. Two examples illustrate how applications of the framework have improved the evaluators' abilities to observe and explain program effect. In both exemplars improvements involved addressing and organizing into a single logic model heretofore seemingly disparate evaluation issues regarding valuing (by whose values); the role of organizational and program context; and evaluation anxiety and utilization. Copyright 2009 Elsevier Ltd. All rights reserved.

A Framework to Learn Physics from Atomically Resolved Images

DOE Office of Scientific and Technical Information (OSTI.GOV)

Vlcek, L.; Maksov, A.; Pan, M.

Here, we present a generalized framework for physics extraction, i.e., knowledge, from atomically resolved images, and show its utility by applying it to a model system of segregation of chalcogen atoms in an FeSe 0.45Te 0.55 superconductor system. We emphasize that the framework can be used for any imaging data for which a generative physical model exists. Consider that a generative physical model can produce a very large number of configurations, not all of which are observable. By applying a microscope function to a sub-set of this generated data, we form a simulated dataset on which statistics can be computed.

Predictive Models and Computational Toxicology (II IBAMTOX)

EPA Science Inventory

EPA’s ‘virtual embryo’ project is building an integrative systems biology framework for predictive models of developmental toxicity. One schema involves a knowledge-driven adverse outcome pathway (AOP) framework utilizing information from public databases, standardized ontologies...

Holistic uncertainty analysis in river basin modeling for climate vulnerability assessment

NASA Astrophysics Data System (ADS)

Taner, M. U.; Wi, S.; Brown, C.

2017-12-01

The challenges posed by uncertain future climate are a prominent concern for water resources managers. A number of frameworks exist for assessing the impacts of climate-related uncertainty, including internal climate variability and anthropogenic climate change, such as scenario-based approaches and vulnerability-based approaches. While in many cases climate uncertainty may be dominant, other factors such as future evolution of the river basin, hydrologic response and reservoir operations are potentially significant sources of uncertainty. While uncertainty associated with modeling hydrologic response has received attention, very little attention has focused on the range of uncertainty and possible effects of the water resources infrastructure and management. This work presents a holistic framework that allows analysis of climate, hydrologic and water management uncertainty in water resources systems analysis with the aid of a water system model designed to integrate component models for hydrology processes and water management activities. The uncertainties explored include those associated with climate variability and change, hydrologic model parameters, and water system operation rules. A Bayesian framework is used to quantify and model the uncertainties at each modeling steps in integrated fashion, including prior and the likelihood information about model parameters. The framework is demonstrated in a case study for the St. Croix Basin located at border of United States and Canada.

High-Performance Computer Modeling of the Cosmos-Iridium Collision

DOE Office of Scientific and Technical Information (OSTI.GOV)

Olivier, S; Cook, K; Fasenfest, B

2009-08-28

This paper describes the application of a new, integrated modeling and simulation framework, encompassing the space situational awareness (SSA) enterprise, to the recent Cosmos-Iridium collision. This framework is based on a flexible, scalable architecture to enable efficient 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, high-performance computer systems available, for example, at Lawrence Livermore National Laboratory. We will describe the application of this framework to the recent collision of the Cosmos and Iridium satellites, including (1) detailed hydrodynamic modeling of the satellitemore » collision and resulting debris generation, (2) orbital propagation of the simulated debris and analysis of the increased risk to other satellites (3) calculation of the radar and optical signatures of the simulated debris and modeling of debris detection with space surveillance radar and optical systems (4) determination of simulated debris orbits from modeled space surveillance observations and analysis of the resulting orbital accuracy, (5) comparison of these modeling and simulation results with Space Surveillance Network observations. We will also discuss the use of this integrated modeling and simulation framework to analyze the risks and consequences of future satellite collisions and to assess strategies for mitigating or avoiding future incidents, including the addition of new sensor systems, used in conjunction with the Space Surveillance Network, for improving space situational awareness.« less

When 1+1 can be >2: Uncertainties compound when simulating climate, fisheries and marine ecosystems

NASA Astrophysics Data System (ADS)

Evans, Karen; Brown, Jaclyn N.; Sen Gupta, Alex; Nicol, Simon J.; Hoyle, Simon; Matear, Richard; Arrizabalaga, Haritz

2015-03-01

Multi-disciplinary approaches that combine oceanographic, biogeochemical, ecosystem, fisheries population and socio-economic models are vital tools for modelling whole ecosystems. Interpreting the outputs from such complex models requires an appreciation of the many different types of modelling frameworks being used and their associated limitations and uncertainties. Both users and developers of particular model components will often have little involvement or understanding of other components within such modelling frameworks. Failure to recognise limitations and uncertainties associated with components and how these uncertainties might propagate throughout modelling frameworks can potentially result in poor advice for resource management. Unfortunately, many of the current integrative frameworks do not propagate the uncertainties of their constituent parts. In this review, we outline the major components of a generic whole of ecosystem modelling framework incorporating the external pressures of climate and fishing. We discuss the limitations and uncertainties associated with each component of such a modelling system, along with key research gaps. Major uncertainties in modelling frameworks are broadly categorised into those associated with (i) deficient knowledge in the interactions of climate and ocean dynamics with marine organisms and ecosystems; (ii) lack of observations to assess and advance modelling efforts and (iii) an inability to predict with confidence natural ecosystem variability and longer term changes as a result of external drivers (e.g. greenhouse gases, fishing effort) and the consequences for marine ecosystems. As a result of these uncertainties and intrinsic differences in the structure and parameterisation of models, users are faced with considerable challenges associated with making appropriate choices on which models to use. We suggest research directions required to address these uncertainties, and caution against overconfident predictions. Understanding the full impact of uncertainty makes it clear that full comprehension and robust certainty about the systems themselves are not feasible. A key research direction is the development of management systems that are robust to this unavoidable uncertainty.

Hybrid modeling in biochemical systems theory by means of functional petri nets.

PubMed

Wu, Jialiang; Voit, Eberhard

2009-02-01

Many biological systems are genuinely hybrids consisting of interacting discrete and continuous components and processes that often operate at different time scales. It is therefore desirable to create modeling frameworks capable of combining differently structured processes and permitting their analysis over multiple time horizons. During the past 40 years, Biochemical Systems Theory (BST) has been a very successful approach to elucidating metabolic, gene regulatory, and signaling systems. However, its foundation in ordinary differential equations has precluded BST from directly addressing problems containing switches, delays, and stochastic effects. In this study, we extend BST to hybrid modeling within the framework of Hybrid Functional Petri Nets (HFPN). First, we show how the canonical GMA and S-system models in BST can be directly implemented in a standard Petri Net framework. In a second step we demonstrate how to account for different types of time delays as well as for discrete, stochastic, and switching effects. Using representative test cases, we validate the hybrid modeling approach through comparative analyses and simulations with other approaches and highlight the feasibility, quality, and efficiency of the hybrid method.

High Spatial Resolution Multi-Organ Finite Element Modeling of Ventricular-Arterial Coupling

PubMed Central

Shavik, Sheikh Mohammad; Jiang, Zhenxiang; Baek, Seungik; Lee, Lik Chuan

2018-01-01

While it has long been recognized that bi-directional interaction between the heart and the vasculature plays a critical role in the proper functioning of the cardiovascular system, a comprehensive study of this interaction has largely been hampered by a lack of modeling framework capable of simultaneously accommodating high-resolution models of the heart and vasculature. Here, we address this issue and present a computational modeling framework that couples finite element (FE) models of the left ventricle (LV) and aorta to elucidate ventricular—arterial coupling in the systemic circulation. We show in a baseline simulation that the framework predictions of (1) LV pressure—volume loop, (2) aorta pressure—diameter relationship, (3) pressure—waveforms of the aorta, LV, and left atrium (LA) over the cardiac cycle are consistent with the physiological measurements found in healthy human. To develop insights of ventricular-arterial interactions, the framework was then used to simulate how alterations in the geometrical or, material parameter(s) of the aorta affect the LV and vice versa. We show that changing the geometry and microstructure of the aorta model in the framework led to changes in the functional behaviors of both LV and aorta that are consistent with experimental observations. On the other hand, changing contractility and passive stiffness of the LV model in the framework also produced changes in both the LV and aorta functional behaviors that are consistent with physiology principles. PMID:29551977

Public Management Information Systems: Theory and Prescription.

ERIC Educational Resources Information Center

Bozeman, Barry; Bretschneider, Stuart

1986-01-01

The existing theoretical framework for research in management information systems (MIS) is criticized for its lack of attention to the external environment of organizations, and a new framework is developed which better accommodates MIS in public organizations: public management information systems. Four models of publicness that reflect external…

Methodology Evaluation Framework for Component-Based System Development.

ERIC Educational Resources Information Center

Dahanayake, Ajantha; Sol, Henk; Stojanovic, Zoran

2003-01-01

Explains component-based development (CBD) for distributed information systems and presents an evaluation framework, which highlights the extent to which a methodology is component oriented. Compares prominent CBD methods, discusses ways of modeling, and suggests that this is a first step towards a components-oriented systems development…

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.

Feature-based component model for design of embedded systems

NASA Astrophysics Data System (ADS)

Zha, Xuan Fang; Sriram, Ram D.

2004-11-01

An embedded system is a hybrid of hardware and software, which combines software's flexibility and hardware real-time performance. Embedded systems can be considered as assemblies of hardware and software components. An Open Embedded System Model (OESM) is currently being developed at NIST to provide a standard representation and exchange protocol for embedded systems and system-level design, simulation, and testing information. This paper proposes an approach to representing an embedded system feature-based model in OESM, i.e., Open Embedded System Feature Model (OESFM), addressing models of embedded system artifacts, embedded system components, embedded system features, and embedded system configuration/assembly. The approach provides an object-oriented UML (Unified Modeling Language) representation for the embedded system feature model and defines an extension to the NIST Core Product Model. The model provides a feature-based component framework allowing the designer to develop a virtual embedded system prototype through assembling virtual components. The framework not only provides a formal precise model of the embedded system prototype but also offers the possibility of designing variation of prototypes whose members are derived by changing certain virtual components with different features. A case study example is discussed to illustrate the embedded system model.

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.

A Biophysical Modeling Framework for Assessing the Environmental Impact of Biofuel Production

NASA Astrophysics Data System (ADS)

Zhang, X.; Izaurradle, C.; Manowitz, D.; West, T. O.; Post, W. M.; Thomson, A. M.; Nichols, J.; Bandaru, V.; Williams, J. R.

2009-12-01

Long-term sustainability of a biofuel economy necessitates environmentally friendly biofuel production systems. We describe a biophysical modeling framework developed to understand and quantify the environmental value and impact (e.g. water balance, nutrients balance, carbon balance, and soil quality) of different biomass cropping systems. This modeling framework consists of three major components: 1) a Geographic Information System (GIS) based data processing system, 2) a spatially-explicit biophysical modeling approach, and 3) a user friendly information distribution system. First, we developed a GIS to manage the large amount of geospatial data (e.g. climate, land use, soil, and hydrograhy) and extract input information for the biophysical model. Second, the Environmental Policy Integrated Climate (EPIC) biophysical model is used to predict the impact of various cropping systems and management intensities on productivity, water balance, and biogeochemical variables. Finally, a geo-database is developed to distribute the results of ecosystem service variables (e.g. net primary productivity, soil carbon balance, soil erosion, nitrogen and phosphorus losses, and N2O fluxes) simulated by EPIC for each spatial modeling unit online using PostgreSQL. We applied this framework in a Regional Intensive Management Area (RIMA) of 9 counties in Michigan. A total of 4,833 spatial units with relatively homogeneous biophysical properties were derived using SSURGO, Crop Data Layer, County, and 10-digit watershed boundaries. For each unit, EPIC was executed from 1980 to 2003 under 54 cropping scenarios (eg. corn, switchgrass, and hybrid poplar). The simulation results were compared with historical crop yields from USDA NASS. Spatial mapping of the results show high variability among different cropping scenarios in terms of the simulated ecosystem services variables. Overall, the framework developed in this study enables the incorporation of environmental factors into economic and life-cycle analysis in order to optimize biomass cropping production scenarios.

Multitask TSK fuzzy system modeling by mining intertask common hidden structure.

PubMed

Jiang, Yizhang; Chung, Fu-Lai; Ishibuchi, Hisao; Deng, Zhaohong; Wang, Shitong

2015-03-01

The classical fuzzy system modeling methods implicitly assume data generated from a single task, which is essentially not in accordance with many practical scenarios where data can be acquired from the perspective of multiple tasks. Although one can build an individual fuzzy system model for each task, the result indeed tells us that the individual modeling approach will get poor generalization ability due to ignoring the intertask hidden correlation. In order to circumvent this shortcoming, we consider a general framework for preserving the independent information among different tasks and mining hidden correlation information among all tasks in multitask fuzzy modeling. In this framework, a low-dimensional subspace (structure) is assumed to be shared among all tasks and hence be the hidden correlation information among all tasks. Under this framework, a multitask Takagi-Sugeno-Kang (TSK) fuzzy system model called MTCS-TSK-FS (TSK-FS for multiple tasks with common hidden structure), based on the classical L2-norm TSK fuzzy system, is proposed in this paper. The proposed model can not only take advantage of independent sample information from the original space for each task, but also effectively use the intertask common hidden structure among multiple tasks to enhance the generalization performance of the built fuzzy systems. Experiments on synthetic and real-world datasets demonstrate the applicability and distinctive performance of the proposed multitask fuzzy system model in multitask regression learning scenarios.

Multi-Scale Multi-Domain Model | Transportation Research | NREL

Science.gov Websites

framework for NREL's MSMD model. NREL's MSMD model quantifies the impacts of electrical/thermal pathway : NREL Macroscopic design factors and highly dynamic environmental conditions significantly influence the design of affordable, long-lasting, high-performing, and safe large battery systems. The MSMD framework

Health level 7 development framework for medication administration.

PubMed

Kim, Hwa Sun; Cho, Hune

2009-01-01

We propose the creation of a standard data model for medication administration activities through the development of a clinical document architecture using the Health Level 7 Development Framework process based on an object-oriented analysis and the development method of Health Level 7 Version 3. Medication administration is the most common activity performed by clinical professionals in healthcare settings. A standardized information model and structured hospital information system are necessary to achieve evidence-based clinical activities. A virtual scenario is used to demonstrate the proposed method of administering medication. We used the Health Level 7 Development Framework and other tools to create the clinical document architecture, which allowed us to illustrate each step of the Health Level 7 Development Framework in the administration of medication. We generated an information model of the medication administration process as one clinical activity. It should become a fundamental conceptual model for understanding international-standard methodology by healthcare professionals and nursing practitioners with the objective of modeling healthcare information systems.

Authentic scientific data collection in support of an integrative model-based class: A framework for student engagement in the classroom

NASA Astrophysics Data System (ADS)

Sorensen, A. E.; Dauer, J. M.; Corral, L.; Fontaine, J. J.

2017-12-01

A core component of public scientific literacy, and thereby informed decision-making, is the ability of individuals to reason about complex systems. In response to students having difficulty learning about complex systems, educational research suggests that conceptual representations, or mental models, may help orient student thinking. Mental models provide a framework to support students in organizing and developing ideas. The PMC-2E model is a productive tool in teaching ideas of modeling complex systems in the classroom because the conceptual representation framework allows for self-directed learning where students can externalize systems thinking. Beyond mental models, recent work emphasizes the importance of facilitating integration of authentic science into the formal classroom. To align these ideas, a university class was developed around the theme of carnivore ecology, founded on PMC-2E framework and authentic scientific data collection. Students were asked to develop a protocol, collect, and analyze data around a scientific question in partnership with a scientist, and then use data to inform their own learning about the system through the mental model process. We identified two beneficial outcomes (1) scientific data is collected to address real scientific questions at a larger scale and (2) positive outcomes for student learning and views of science. After participating in the class, students report enjoying class structure, increased support for public understanding of science, and shifts in nature of science and interest in pursuing science metrics on post-assessments. Further work is ongoing investigating the linkages between engaging in authentic scientific practices that inform student mental models, and how it might promote students' systems-thinking skills, implications for student views of nature of science, and development of student epistemic practices.

Structure-based control of complex networks with nonlinear dynamics

NASA Astrophysics Data System (ADS)

Zanudo, Jorge G. T.; Yang, Gang; Albert, Reka

What can we learn about controlling a system solely from its underlying network structure? Here we use a framework for control of networks governed by a broad class of nonlinear dynamics that includes the major dynamic models of biological, technological, and social processes. This feedback-based framework provides realizable node overrides that steer a system towards any of its natural long term dynamic behaviors, regardless of the dynamic details and system parameters. We use this framework on several real networks, identify the topological characteristics that underlie the predicted node overrides, and compare its predictions to those of classical structural control theory. Finally, we demonstrate this framework's applicability in dynamic models of gene regulatory networks and identify nodes whose override is necessary for control in the general case, but not in specific model instances. This work was supported by NSF Grants PHY 1205840 and IIS 1160995. JGTZ is a recipient of a Stand Up To Cancer - The V Foundation Convergence Scholar Award.

A Computational Framework for Bioimaging Simulation.

PubMed

Watabe, Masaki; Arjunan, Satya N V; Fukushima, Seiya; Iwamoto, Kazunari; Kozuka, Jun; Matsuoka, Satomi; Shindo, Yuki; Ueda, Masahiro; Takahashi, Koichi

2015-01-01

Using bioimaging technology, biologists have attempted to identify and document analytical interpretations that underlie biological phenomena in biological cells. Theoretical biology aims at distilling those interpretations into knowledge in the mathematical form of biochemical reaction networks and understanding how higher level functions emerge from the combined action of biomolecules. However, there still remain formidable challenges in bridging the gap between bioimaging and mathematical modeling. Generally, measurements using fluorescence microscopy systems are influenced by systematic effects that arise from stochastic nature of biological cells, the imaging apparatus, and optical physics. Such systematic effects are always present in all bioimaging systems and hinder quantitative comparison between the cell model and bioimages. Computational tools for such a comparison are still unavailable. Thus, in this work, we present a computational framework for handling the parameters of the cell models and the optical physics governing bioimaging systems. Simulation using this framework can generate digital images of cell simulation results after accounting for the systematic effects. We then demonstrate that such a framework enables comparison at the level of photon-counting units.

Watershed System Model: The Essentials to Model Complex Human-Nature System at the River Basin Scale

NASA Astrophysics Data System (ADS)

Li, Xin; Cheng, Guodong; Lin, Hui; Cai, Ximing; Fang, Miao; Ge, Yingchun; Hu, Xiaoli; Chen, Min; Li, Weiyue

2018-03-01

Watershed system models are urgently needed to understand complex watershed systems and to support integrated river basin management. Early watershed modeling efforts focused on the representation of hydrologic processes, while the next-generation watershed models should represent the coevolution of the water-land-air-plant-human nexus in a watershed and provide capability of decision-making support. We propose a new modeling framework and discuss the know-how approach to incorporate emerging knowledge into integrated models through data exchange interfaces. We argue that the modeling environment is a useful tool to enable effective model integration, as well as create domain-specific models of river basin systems. The grand challenges in developing next-generation watershed system models include but are not limited to providing an overarching framework for linking natural and social sciences, building a scientifically based decision support system, quantifying and controlling uncertainties, and taking advantage of new technologies and new findings in the various disciplines of watershed science. The eventual goal is to build transdisciplinary, scientifically sound, and scale-explicit watershed system models that are to be codesigned by multidisciplinary communities.

Oral health disparities and the workforce: a framework to guide innovation.

PubMed

Hilton, Irene V; Lester, Arlene M

2010-06-01

Oral health disparities currently exist in the United States, and workforce innovations have been proposed as one strategy to address these disparities. A framework is needed to logically assess the possible role of workforce as a contributor to and to analyze workforce strategies addressing the issue of oral health disparities. Using an existing framework, A Strategic Framework for Improving Racial/Ethnic Minority Health and Eliminating Racial/Ethnic Health Disparities, workforce was sequentially applied across individual, environmental/community, and system levels to identify long-term problems, contributing factors, strategies/innovation, measurable outcomes/impacts, and long-term goals. Examples of current workforce innovations were applied to the framework. Contributing factors to oral health disparities included lack of racial/ethnic diversity of the workforce, lack of appropriate training, provider distribution, and a nonuser-centered system. The framework was applied to selected workforce innovation models delineating the potential impact on contributing factors across the individual, environmental/community, and system levels. The framework helps to define expected outcomes from workforce models that would contribute to the goal of reducing oral health disparities and examine impacts across multiple levels. However, the contributing factors to oral health disparities cannot be addressed by workforce innovation alone. The Strategic Framework is a logical approach to guide workforce innovation, solutions, and identification of other aspects of the oral healthcare delivery system that need innovation in order to reduce oral health disparities.

Enterprise and system of systems capability development life-cycle processes.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Beck, David Franklin

2014-08-01

This report and set of appendices are a collection of memoranda originally drafted circa 2007-2009 for the purpose of describing and detailing a models-based systems engineering approach for satisfying enterprise and system-of-systems life cycle process requirements. At the time there was interest and support to move from Capability Maturity Model Integration (CMMI) Level One (ad hoc processes) to Level Three. The main thrust of the material presents a rational exposâe of a structured enterprise development life cycle that uses the scientific method as a framework, with further rigor added from adapting relevant portions of standard systems engineering processes. While themore » approach described invokes application of the Department of Defense Architectural Framework (DoDAF), it is suitable for use with other architectural description frameworks.« less

A flexible framework for process-based hydraulic and water ...

EPA Pesticide Factsheets

Background Models that allow for design considerations of green infrastructure (GI) practices to control stormwater runoff and associated contaminants have received considerable attention in recent years. While popular, generally, the GI models are relatively simplistic. However, GI model predictions are being relied upon by many municipalities and State/Local agencies to make decisions about grey vs. green infrastructure improvement planning. Adding complexity to GI modeling frameworks may preclude their use in simpler urban planning situations. Therefore, the goal here was to develop a sophisticated, yet flexible tool that could be used by design engineers and researchers to capture and explore the effect of design factors and properties of the media used in the performance of GI systems at a relatively small scale. We deemed it essential to have a flexible GI modeling tool that is capable of simulating GI system components and specific biophysical processes affecting contaminants such as reactions, and particle-associated transport accurately while maintaining a high degree of flexibly to account for the myriad of GI alternatives. The mathematical framework for a stand-alone GI performance assessment tool has been developed and will be demonstrated.Framework Features The process-based model framework developed here can be used to model a diverse range of GI practices such as green roof, retention pond, bioretention, infiltration trench, permeable pavement and

A framework to analyze emissions implications of ...

EPA Pesticide Factsheets

Future year emissions depend highly on the evolution of the economy, technology and current and future regulatory drivers. A scenario framework was adopted to analyze various technology development pathways and societal change while considering existing regulations and future uncertainty in regulations and evaluate resulting emissions growth patterns. The framework integrates EPA’s energy systems model with an economic Input-Output (I/O) Life Cycle Assessment model. The EPAUS9r MARKAL database is assembled from a set of technologies to represent the U.S. energy system within MARKAL bottom-up technology rich energy modeling framework. The general state of the economy and consequent demands for goods and services from these sectors are taken exogenously in MARKAL. It is important to characterize exogenous inputs about the economy to appropriately represent the industrial sector outlook for each of the scenarios and case studies evaluated. An economic input-output (I/O) model of the US economy is constructed to link up with MARKAL. The I/O model enables user to change input requirements (e.g. energy intensity) for different sectors or the share of consumer income expended on a given good. This gives end-users a mechanism for modeling change in the two dimensions of technological progress and consumer preferences that define the future scenarios. The framework will then be extended to include environmental I/O framework to track life cycle emissions associated

Carbon dioxide capture using covalent organic frameworks (COFs) type material-a theoretical investigation.

PubMed

Dash, Bibek

2018-04-26

The present work deals with a density functional theory (DFT) study of porous organic framework materials containing - groups for CO 2 capture. In this study, first principle calculations were performed for CO 2 adsorption using N-containing covalent organic framework (COFs) models. Ab initio and DFT-based methods were used to characterize the N-containing porous model system based on their interaction energies upon complexing with CO 2 and nitrogen gas. Binding energies (BEs) of CO 2 and N 2 molecules with the polymer framework were calculated with DFT methods. Hybrid B3LYP and second order MP2 methods combined with of Pople 6-31G(d,p) and correlation consistent basis sets cc-pVDZ, cc-pVTZ and aug-ccVDZ were used to calculate BEs. The effect of linker groups in the designed covalent organic framework model system on the CO 2 and N 2 interactions was studied using quantum calculations.

Modeling and simulation of an unmanned ground vehicle power system

NASA Astrophysics Data System (ADS)

Broderick, John; Hartner, Jack; Tilbury, Dawn M.; Atkins, Ella M.

2014-06-01

Long-duration missions challenge ground robot systems with respect to energy storage and efficient conversion to power on demand. Ground robot systems can contain multiple power sources such as fuel cell, battery and/or ultra-capacitor. This paper presents a hybrid systems framework for collectively modeling the dynamics and switching between these different power components. The hybrid system allows modeling power source on/off switching and different regimes of operation, together with continuous parameters such as state of charge, temperature, and power output. We apply this modeling framework to a fuel cell/battery power system applicable to unmanned ground vehicles such as Packbot or TALON. A simulation comparison of different control strategies is presented. These strategies are compared based on maximizing energy efficiency and meeting thermal constraints.

Genetic Programming for Automatic Hydrological Modelling

NASA Astrophysics Data System (ADS)

Chadalawada, Jayashree; Babovic, Vladan

2017-04-01

One of the recent challenges for the hydrologic research community is the need for the development of coupled systems that involves the integration of hydrologic, atmospheric and socio-economic relationships. This poses a requirement for novel modelling frameworks that can accurately represent complex systems, given, the limited understanding of underlying processes, increasing volume of data and high levels of uncertainity. Each of the existing hydrological models vary in terms of conceptualization and process representation and is the best suited to capture the environmental dynamics of a particular hydrological system. Data driven approaches can be used in the integration of alternative process hypotheses in order to achieve a unified theory at catchment scale. The key steps in the implementation of integrated modelling framework that is influenced by prior understanding and data, include, choice of the technique for the induction of knowledge from data, identification of alternative structural hypotheses, definition of rules, constraints for meaningful, intelligent combination of model component hypotheses and definition of evaluation metrics. This study aims at defining a Genetic Programming based modelling framework that test different conceptual model constructs based on wide range of objective functions and evolves accurate and parsimonious models that capture dominant hydrological processes at catchment scale. In this paper, GP initializes the evolutionary process using the modelling decisions inspired from the Superflex framework [Fenicia et al., 2011] and automatically combines them into model structures that are scrutinized against observed data using statistical, hydrological and flow duration curve based performance metrics. The collaboration between data driven and physical, conceptual modelling paradigms improves the ability to model and manage hydrologic systems. Fenicia, F., D. Kavetski, and H. H. Savenije (2011), Elements of a flexible approach for conceptual hydrological modeling: 1. Motivation and theoretical development, Water Resources Research, 47(11).

Modelling the protocol stack in NCS with deterministic and stochastic petri net

NASA Astrophysics Data System (ADS)

Hui, Chen; Chunjie, Zhou; Weifeng, Zhu

2011-06-01

Protocol stack is the basis of the networked control systems (NCS). Full or partial reconfiguration of protocol stack offers both optimised communication service and system performance. Nowadays, field testing is unrealistic to determine the performance of reconfigurable protocol stack; and the Petri net formal description technique offers the best combination of intuitive representation, tool support and analytical capabilities. Traditionally, separation between the different layers of the OSI model has been a common practice. Nevertheless, such a layered modelling analysis framework of protocol stack leads to the lack of global optimisation for protocol reconfiguration. In this article, we proposed a general modelling analysis framework for NCS based on the cross-layer concept, which is to establish an efficiency system scheduling model through abstracting the time constraint, the task interrelation, the processor and the bus sub-models from upper and lower layers (application, data link and physical layer). Cross-layer design can help to overcome the inadequacy of global optimisation based on information sharing between protocol layers. To illustrate the framework, we take controller area network (CAN) as a case study. The simulation results of deterministic and stochastic Petri-net (DSPN) model can help us adjust the message scheduling scheme and obtain better system performance.

A Flexible Electronic Commerce Recommendation System

NASA Astrophysics Data System (ADS)

Gong, Songjie

Recommendation systems have become very popular in E-commerce websites. Many of the largest commerce websites are already using recommender technologies to help their customers find products to purchase. An electronic commerce recommendation system learns from a customer and recommends products that the customer will find most valuable from among the available products. But most recommendation methods are hard-wired into the system and they support only fixed recommendations. This paper presented a framework of flexible electronic commerce recommendation system. The framework is composed by user model interface, recommendation engine, recommendation strategy model, recommendation technology group, user interest model and database interface. In the recommender strategy model, the method can be collaborative filtering, content-based filtering, mining associate rules method, knowledge-based filtering method or the mixed method. The system mapped the implementation and demand through strategy model, and the whole system would be design as standard parts to adapt to the change of the recommendation strategy.

A framework for modelling the complexities of food and water security under globalisation

NASA Astrophysics Data System (ADS)

Dermody, Brian J.; Sivapalan, Murugesu; Stehfest, Elke; van Vuuren, Detlef P.; Wassen, Martin J.; Bierkens, Marc F. P.; Dekker, Stefan C.

2018-01-01

We present a new framework for modelling the complexities of food and water security under globalisation. The framework sets out a method to capture regional and sectoral interdependencies and cross-scale feedbacks within the global food system that contribute to emergent water use patterns. The framework integrates aspects of existing models and approaches in the fields of hydrology and integrated assessment modelling. The core of the framework is a multi-agent network of city agents connected by infrastructural trade networks. Agents receive socio-economic and environmental constraint information from integrated assessment models and hydrological models respectively and simulate complex, socio-environmental dynamics that operate within those constraints. The emergent changes in food and water resources are aggregated and fed back to the original models with minimal modification of the structure of those models. It is our conviction that the framework presented can form the basis for a new wave of decision tools that capture complex socio-environmental change within our globalised world. In doing so they will contribute to illuminating pathways towards a sustainable future for humans, ecosystems and the water they share.

Integration of agricultural and energy system models for biofuel assessment

EPA Science Inventory

This paper presents a coupled modeling framework to capture the dynamic linkages between agricultural and energy markets that have been enhanced through the expansion of biofuel production, as well as the environmental impacts resulting from this expansion. The framework incorpor...

A post-Bertalanffy Systemics Healthcare Competitive Framework Proposal.

PubMed

Fiorini, Rodolfo A; Santacroce, Giulia F

2014-01-01

Health Information community can take advantage of a new evolutive categorization cybernetic framework. A systemic concept of principles organizing nature is proposed. It can be used as a multiscaling reference framework to develop successful and competitive antifragile system and new HRO information management strategies in advanced healthcare organization (HO) and high reliability organization (HRO) conveniently. Expected impacts are multifarious and quite articulated at different system scale level: major one is that, for the first time, Biomedical Engineering ideal system categorization levels can be matched exactly to practical system modeling interaction styles, with no paradigmatic operational ambiguity and information loss.

Extending MAM5 Meta-Model and JaCalIV E Framework to Integrate Smart Devices from Real Environments.

PubMed

Rincon, J A; Poza-Lujan, Jose-Luis; Julian, V; Posadas-Yagüe, Juan-Luis; Carrascosa, C

2016-01-01

This paper presents the extension of a meta-model (MAM5) and a framework based on the model (JaCalIVE) for developing intelligent virtual environments. The goal of this extension is to develop augmented mirror worlds that represent a real and virtual world coupled, so that the virtual world not only reflects the real one, but also complements it. A new component called a smart resource artifact, that enables modelling and developing devices to access the real physical world, and a human in the loop agent to place a human in the system have been included in the meta-model and framework. The proposed extension of MAM5 has been tested by simulating a light control system where agents can access both virtual and real sensor/actuators through the smart resources developed. The results show that the use of real environment interactive elements (smart resource artifacts) in agent-based simulations allows to minimize the error between simulated and real system.

Extending MAM5 Meta-Model and JaCalIV E Framework to Integrate Smart Devices from Real Environments

PubMed Central

2016-01-01

This paper presents the extension of a meta-model (MAM5) and a framework based on the model (JaCalIVE) for developing intelligent virtual environments. The goal of this extension is to develop augmented mirror worlds that represent a real and virtual world coupled, so that the virtual world not only reflects the real one, but also complements it. A new component called a smart resource artifact, that enables modelling and developing devices to access the real physical world, and a human in the loop agent to place a human in the system have been included in the meta-model and framework. The proposed extension of MAM5 has been tested by simulating a light control system where agents can access both virtual and real sensor/actuators through the smart resources developed. The results show that the use of real environment interactive elements (smart resource artifacts) in agent-based simulations allows to minimize the error between simulated and real system. PMID:26926691

Observing System Simulation Experiments for Fun and Profit

NASA Technical Reports Server (NTRS)

Prive, Nikki C.

2015-01-01

Observing System Simulation Experiments can be powerful tools for evaluating and exploring both the behavior of data assimilation systems and the potential impacts of future observing systems. With great power comes great responsibility - given a pure modeling framework, how can we be sure our results are meaningful? The challenges and pitfalls of OSSE calibration and validation will be addressed, as well as issues of incestuousness, selection of appropriate metrics, and experiment design. The use of idealized observational networks to investigate theoretical ideas in a fully complex modeling framework will also be discussed

Automated Analysis of Stateflow Models

NASA Technical Reports Server (NTRS)

Bourbouh, Hamza; Garoche, Pierre-Loic; Garion, Christophe; Gurfinkel, Arie; Kahsaia, Temesghen; Thirioux, Xavier

2017-01-01

Stateflow is a widely used modeling framework for embedded and cyber physical systems where control software interacts with physical processes. In this work, we present a framework a fully automated safety verification technique for Stateflow models. Our approach is two-folded: (i) we faithfully compile Stateflow models into hierarchical state machines, and (ii) we use automated logic-based verification engine to decide the validity of safety properties. The starting point of our approach is a denotational semantics of State flow. We propose a compilation process using continuation-passing style (CPS) denotational semantics. Our compilation technique preserves the structural and modal behavior of the system. The overall approach is implemented as an open source toolbox that can be integrated into the existing Mathworks Simulink Stateflow modeling framework. We present preliminary experimental evaluations that illustrate the effectiveness of our approach in code generation and safety verification of industrial scale Stateflow models.

Self, System, Synergy: A Career-Life Development Framework for Individuals and Organizations.

ERIC Educational Resources Information Center

Gelatt, H. B.

1998-01-01

The Self-System-Synergy model provides the philosophical framework for the concept of career resiliency, which has become the basis for many organizational initiatives. The three elements are self-reliance (the power of personal beliefs), interdependence (the connectedness of multiple systems), and self-renewal through continuous learning. (JOW)

MIS Development in Higher Education: A Framework for Systems Planning.

ERIC Educational Resources Information Center

St. John, Edward P.

An institutional management systems development study examined the Management Information Systems (MIS) needs of 23 public institutions of higher education in Missouri. The result was a model framework for other institutions to develop MIS appropriate to their needs. One of five distinct structural development phases could be related to all…

A Survey of Statistical Models for Reverse Engineering Gene Regulatory Networks

PubMed Central

Huang, Yufei; Tienda-Luna, Isabel M.; Wang, Yufeng

2009-01-01

Statistical models for reverse engineering gene regulatory networks are surveyed in this article. To provide readers with a system-level view of the modeling issues in this research, a graphical modeling framework is proposed. This framework serves as the scaffolding on which the review of different models can be systematically assembled. Based on the framework, we review many existing models for many aspects of gene regulation; the pros and cons of each model are discussed. In addition, network inference algorithms are also surveyed under the graphical modeling framework by the categories of point solutions and probabilistic solutions and the connections and differences among the algorithms are provided. This survey has the potential to elucidate the development and future of reverse engineering GRNs and bring statistical signal processing closer to the core of this research. PMID:20046885

Sequential state estimation of nonlinear/non-Gaussian systems with stochastic input for turbine degradation estimation

NASA Astrophysics Data System (ADS)

Hanachi, Houman; Liu, Jie; Banerjee, Avisekh; Chen, Ying

2016-05-01

Health state estimation of inaccessible components in complex systems necessitates effective state estimation techniques using the observable variables of the system. The task becomes much complicated when the system is nonlinear/non-Gaussian and it receives stochastic input. In this work, a novel sequential state estimation framework is developed based on particle filtering (PF) scheme for state estimation of general class of nonlinear dynamical systems with stochastic input. Performance of the developed framework is then validated with simulation on a Bivariate Non-stationary Growth Model (BNGM) as a benchmark. In the next step, three-year operating data of an industrial gas turbine engine (GTE) are utilized to verify the effectiveness of the developed framework. A comprehensive thermodynamic model for the GTE is therefore developed to formulate the relation of the observable parameters and the dominant degradation symptoms of the turbine, namely, loss of isentropic efficiency and increase of the mass flow. The results confirm the effectiveness of the developed framework for simultaneous estimation of multiple degradation symptoms in complex systems with noisy measured inputs.

Dyadic brain modelling, mirror systems and the ontogenetic ritualization of ape gesture

PubMed Central

Arbib, Michael; Ganesh, Varsha; Gasser, Brad

2014-01-01

The paper introduces dyadic brain modelling, offering both a framework for modelling the brains of interacting agents and a general framework for simulating and visualizing the interactions generated when the brains (and the two bodies) are each coded up in computational detail. It models selected neural mechanisms in ape brains supportive of social interactions, including putative mirror neuron systems inspired by macaque neurophysiology but augmented by increased access to proprioceptive state. Simulation results for a reduced version of the model show ritualized gesture emerging from interactions between a simulated child and mother ape. PMID:24778382

Dyadic brain modelling, mirror systems and the ontogenetic ritualization of ape gesture.

PubMed

Arbib, Michael; Ganesh, Varsha; Gasser, Brad

2014-01-01

The paper introduces dyadic brain modelling, offering both a framework for modelling the brains of interacting agents and a general framework for simulating and visualizing the interactions generated when the brains (and the two bodies) are each coded up in computational detail. It models selected neural mechanisms in ape brains supportive of social interactions, including putative mirror neuron systems inspired by macaque neurophysiology but augmented by increased access to proprioceptive state. Simulation results for a reduced version of the model show ritualized gesture emerging from interactions between a simulated child and mother ape.

An RFID-Based Manufacturing Control Framework for Loosely Coupled Distributed Manufacturing System Supporting Mass Customization

NASA Astrophysics Data System (ADS)

Chen, Ruey-Shun; Tsai, Yung-Shun; Tu, Arthur

In this study we propose a manufacturing control framework based on radio-frequency identification (RFID) technology and a distributed information system to construct a mass-customization production process in a loosely coupled shop-floor control environment. On the basis of this framework, we developed RFID middleware and an integrated information system for tracking and controlling the manufacturing process flow. A bicycle manufacturer was used to demonstrate the prototype system. The findings of this study were that the proposed framework can improve the visibility and traceability of the manufacturing process as well as enhance process quality control and real-time production pedigree access. Using this framework, an enterprise can easily integrate an RFID-based system into its manufacturing environment to facilitate mass customization and a just-in-time production model.

An Agent-Based Optimization Framework for Engineered Complex Adaptive Systems with Application to Demand Response in Electricity Markets

NASA Astrophysics Data System (ADS)

Haghnevis, Moeed

The main objective of this research is to develop an integrated method to study emergent behavior and consequences of evolution and adaptation in engineered complex adaptive systems (ECASs). A multi-layer conceptual framework and modeling approach including behavioral and structural aspects is provided to describe the structure of a class of engineered complex systems and predict their future adaptive patterns. The approach allows the examination of complexity in the structure and the behavior of components as a result of their connections and in relation to their environment. This research describes and uses the major differences of natural complex adaptive systems (CASs) with artificial/engineered CASs to build a framework and platform for ECAS. While this framework focuses on the critical factors of an engineered system, it also enables one to synthetically employ engineering and mathematical models to analyze and measure complexity in such systems. In this way concepts of complex systems science are adapted to management science and system of systems engineering. In particular an integrated consumer-based optimization and agent-based modeling (ABM) platform is presented that enables managers to predict and partially control patterns of behaviors in ECASs. Demonstrated on the U.S. electricity markets, ABM is integrated with normative and subjective decision behavior recommended by the U.S. Department of Energy (DOE) and Federal Energy Regulatory Commission (FERC). The approach integrates social networks, social science, complexity theory, and diffusion theory. Furthermore, it has unique and significant contribution in exploring and representing concrete managerial insights for ECASs and offering new optimized actions and modeling paradigms in agent-based simulation.

A generalized reconstruction framework for unconventional PET systems

DOE Office of Scientific and Technical Information (OSTI.GOV)

Mathews, Aswin John, E-mail: amathews@wustl.edu; Li, Ke; O’Sullivan, Joseph A.

2015-08-15

Purpose: Quantitative estimation of the radionuclide activity concentration in positron emission tomography (PET) requires precise modeling of PET physics. The authors are focused on designing unconventional PET geometries for specific applications. This work reports the creation of a generalized reconstruction framework, capable of reconstructing tomographic PET data for systems that use right cuboidal detector elements positioned at arbitrary geometry using a regular Cartesian grid of image voxels. Methods: The authors report on a variety of design choices and optimization for the creation of the generalized framework. The image reconstruction algorithm is maximum likelihood-expectation–maximization. System geometry can be specified using amore » simple script. Given the geometry, a symmetry seeking algorithm finds existing symmetry in the geometry with respect to the image grid to improve the memory usage/speed. Normalization is approached from a geometry independent perspective. The system matrix is computed using the Siddon’s algorithm and subcrystal approach. The program is parallelized through open multiprocessing and message passing interface libraries. A wide variety of systems can be modeled using the framework. This is made possible by modeling the underlying physics and data correction, while generalizing the geometry dependent features. Results: Application of the framework for three novel PET systems, each designed for a specific application, is presented to demonstrate the robustness of the framework in modeling PET systems of unconventional geometry. Three PET systems of unconventional geometry are studied. (1) Virtual-pinhole half-ring insert integrated into Biograph-40: although the insert device improves image quality over conventional whole-body scanner, the image quality varies depending on the position of the insert and the object. (2) Virtual-pinhole flat-panel insert integrated into Biograph-40: preliminary results from an investigation into a modular flat-panel insert are presented. (3) Plant PET system: a reconfigurable PET system for imaging plants, with resolution of greater than 3.3 mm, is shown. Using the automated symmetry seeking algorithm, the authors achieved a compression ratio of the storage and memory requirement by a factor of approximately 50 for the half-ring and flat-panel systems. For plant PET system, the compression ratio is approximately five. The ratio depends on the level of symmetry that exists in different geometries. Conclusions: This work brings the field closer to arbitrary geometry reconstruction. A generalized reconstruction framework can be used to validate multiple hypotheses and the effort required to investigate each system is reduced. Memory usage/speed can be improved with certain optimizations.« less

A generalized reconstruction framework for unconventional PET systems.

PubMed

Mathews, Aswin John; Li, Ke; Komarov, Sergey; Wang, Qiang; Ravindranath, Bosky; O'Sullivan, Joseph A; Tai, Yuan-Chuan

2015-08-01

Quantitative estimation of the radionuclide activity concentration in positron emission tomography (PET) requires precise modeling of PET physics. The authors are focused on designing unconventional PET geometries for specific applications. This work reports the creation of a generalized reconstruction framework, capable of reconstructing tomographic PET data for systems that use right cuboidal detector elements positioned at arbitrary geometry using a regular Cartesian grid of image voxels. The authors report on a variety of design choices and optimization for the creation of the generalized framework. The image reconstruction algorithm is maximum likelihood-expectation-maximization. System geometry can be specified using a simple script. Given the geometry, a symmetry seeking algorithm finds existing symmetry in the geometry with respect to the image grid to improve the memory usage/speed. Normalization is approached from a geometry independent perspective. The system matrix is computed using the Siddon's algorithm and subcrystal approach. The program is parallelized through open multiprocessing and message passing interface libraries. A wide variety of systems can be modeled using the framework. This is made possible by modeling the underlying physics and data correction, while generalizing the geometry dependent features. Application of the framework for three novel PET systems, each designed for a specific application, is presented to demonstrate the robustness of the framework in modeling PET systems of unconventional geometry. Three PET systems of unconventional geometry are studied. (1) Virtual-pinhole half-ring insert integrated into Biograph-40: although the insert device improves image quality over conventional whole-body scanner, the image quality varies depending on the position of the insert and the object. (2) Virtual-pinhole flat-panel insert integrated into Biograph-40: preliminary results from an investigation into a modular flat-panel insert are presented. (3) Plant PET system: a reconfigurable PET system for imaging plants, with resolution of greater than 3.3 mm, is shown. Using the automated symmetry seeking algorithm, the authors achieved a compression ratio of the storage and memory requirement by a factor of approximately 50 for the half-ring and flat-panel systems. For plant PET system, the compression ratio is approximately five. The ratio depends on the level of symmetry that exists in different geometries. This work brings the field closer to arbitrary geometry reconstruction. A generalized reconstruction framework can be used to validate multiple hypotheses and the effort required to investigate each system is reduced. Memory usage/speed can be improved with certain optimizations.

A generalized reconstruction framework for unconventional PET systems

PubMed Central

Mathews, Aswin John; Li, Ke; Komarov, Sergey; Wang, Qiang; Ravindranath, Bosky; O’Sullivan, Joseph A.; Tai, Yuan-Chuan

2015-01-01

Purpose: Quantitative estimation of the radionuclide activity concentration in positron emission tomography (PET) requires precise modeling of PET physics. The authors are focused on designing unconventional PET geometries for specific applications. This work reports the creation of a generalized reconstruction framework, capable of reconstructing tomographic PET data for systems that use right cuboidal detector elements positioned at arbitrary geometry using a regular Cartesian grid of image voxels. Methods: The authors report on a variety of design choices and optimization for the creation of the generalized framework. The image reconstruction algorithm is maximum likelihood-expectation–maximization. System geometry can be specified using a simple script. Given the geometry, a symmetry seeking algorithm finds existing symmetry in the geometry with respect to the image grid to improve the memory usage/speed. Normalization is approached from a geometry independent perspective. The system matrix is computed using the Siddon’s algorithm and subcrystal approach. The program is parallelized through open multiprocessing and message passing interface libraries. A wide variety of systems can be modeled using the framework. This is made possible by modeling the underlying physics and data correction, while generalizing the geometry dependent features. Results: Application of the framework for three novel PET systems, each designed for a specific application, is presented to demonstrate the robustness of the framework in modeling PET systems of unconventional geometry. Three PET systems of unconventional geometry are studied. (1) Virtual-pinhole half-ring insert integrated into Biograph-40: although the insert device improves image quality over conventional whole-body scanner, the image quality varies depending on the position of the insert and the object. (2) Virtual-pinhole flat-panel insert integrated into Biograph-40: preliminary results from an investigation into a modular flat-panel insert are presented. (3) Plant PET system: a reconfigurable PET system for imaging plants, with resolution of greater than 3.3 mm, is shown. Using the automated symmetry seeking algorithm, the authors achieved a compression ratio of the storage and memory requirement by a factor of approximately 50 for the half-ring and flat-panel systems. For plant PET system, the compression ratio is approximately five. The ratio depends on the level of symmetry that exists in different geometries. Conclusions: This work brings the field closer to arbitrary geometry reconstruction. A generalized reconstruction framework can be used to validate multiple hypotheses and the effort required to investigate each system is reduced. Memory usage/speed can be improved with certain optimizations. PMID:26233187

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.

Anatomy and Physiology of Multiscale Modeling and Simulation in Systems Medicine.

PubMed

Mizeranschi, Alexandru; Groen, Derek; Borgdorff, Joris; Hoekstra, Alfons G; Chopard, Bastien; Dubitzky, Werner

2016-01-01

Systems medicine is the application of systems biology concepts, methods, and tools to medical research and practice. It aims to integrate data and knowledge from different disciplines into biomedical models and simulations for the understanding, prevention, cure, and management of complex diseases. Complex diseases arise from the interactions among disease-influencing factors across multiple levels of biological organization from the environment to molecules. To tackle the enormous challenges posed by complex diseases, we need a modeling and simulation framework capable of capturing and integrating information originating from multiple spatiotemporal and organizational scales. Multiscale modeling and simulation in systems medicine is an emerging methodology and discipline that has already demonstrated its potential in becoming this framework. The aim of this chapter is to present some of the main concepts, requirements, and challenges of multiscale modeling and simulation in systems medicine.

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...

POLARIS: Agent-based modeling framework development and implementation for integrated travel demand and network and operations simulations

DOE Office of Scientific and Technical Information (OSTI.GOV)

Auld, Joshua; Hope, Michael; Ley, Hubert

This paper discusses the development of an agent-based modelling software development kit, and the implementation and validation of a model using it that integrates dynamic simulation of travel demand, network supply and network operations. A description is given of the core utilities in the kit: a parallel discrete event engine, interprocess exchange engine, and memory allocator, as well as a number of ancillary utilities: visualization library, database IO library, and scenario manager. The overall framework emphasizes the design goals of: generality, code agility, and high performance. This framework allows the modeling of several aspects of transportation system that are typicallymore » done with separate stand-alone software applications, in a high-performance and extensible manner. The issue of integrating such models as dynamic traffic assignment and disaggregate demand models has been a long standing issue for transportation modelers. The integrated approach shows a possible way to resolve this difficulty. The simulation model built from the POLARIS framework is a single, shared-memory process for handling all aspects of the integrated urban simulation. The resulting gains in computational efficiency and performance allow planning models to be extended to include previously separate aspects of the urban system, enhancing the utility of such models from the planning perspective. Initial tests with case studies involving traffic management center impacts on various network events such as accidents, congestion and weather events, show the potential of the system.« less

Kinetic Framework for the Magnetosphere-Ionosphere-Plasmasphere-Polar Wind System: Modeling Ion Outflow

NASA Astrophysics Data System (ADS)

Schunk, R. W.; Barakat, A. R.; Eccles, V.; Karimabadi, H.; Omelchenko, Y.; Khazanov, G. V.; Glocer, A.; Kistler, L. M.

2014-12-01

A Kinetic Framework for the Magnetosphere-Ionosphere-Plasmasphere-Polar Wind System is being developed in order to provide a rigorous approach to modeling the interaction of hot and cold particle interactions. The framework will include ion and electron kinetic species in the ionosphere, plasmasphere and polar wind, and kinetic ion, super-thermal electron and fluid electron species in the magnetosphere. The framework is ideally suited to modeling ion outflow from the ionosphere and plasmasphere, where a wide range for fluid and kinetic processes are important. These include escaping ion interactions with (1) photoelectrons, (2) cusp/auroral waves, double layers, and field-aligned currents, (3) double layers in the polar cap due to the interaction of cold ionospheric and hot magnetospheric electrons, (4) counter-streaming ions, and (5) electromagnetic wave turbulence. The kinetic ion interactions are particularly strong during geomagnetic storms and substorms. The presentation will provide a brief description of the models involved and discuss the effect that kinetic processes have on the ion outflow.

A Hierarchical Learning Control Framework for an Aerial Manipulation System

NASA Astrophysics Data System (ADS)

Ma, Le; Chi, yanxun; Li, Jiapeng; Li, Zhongsheng; Ding, Yalei; Liu, Lixing

2017-07-01

A hierarchical learning control framework for an aerial manipulation system is proposed. Firstly, the mechanical design of aerial manipulation system is introduced and analyzed, and the kinematics and the dynamics based on Newton-Euler equation are modeled. Secondly, the framework of hierarchical learning for this system is presented, in which flight platform and manipulator are controlled by different controller respectively. The RBF (Radial Basis Function) neural networks are employed to estimate parameters and control. The Simulation and experiment demonstrate that the methods proposed effective and advanced.

Vulnerability Assessment of Water Supply Systems: Status, Gaps and Opportunities

NASA Astrophysics Data System (ADS)

Wheater, H. S.

2015-12-01

Conventional frameworks for assessing the impacts of climate change on water resource systems use cascades of climate and hydrological models to provide 'top-down' projections of future water availability, but these are subject to high uncertainty and are model and scenario-specific. Hence there has been recent interest in 'bottom-up' frameworks, which aim to evaluate system vulnerability to change in the context of possible future climate and/or hydrological conditions. Such vulnerability assessments are generic, and can be combined with updated information from top-down assessments as they become available. While some vulnerability methods use hydrological models to estimate water availability, fully bottom-up schemes have recently been proposed that directly map system vulnerability as a function of feasible changes in water supply characteristics. These use stochastic algorithms, based on reconstruction or reshuffling methods, by which multiple water supply realizations can be generated under feasible ranges of change in water supply conditions. The paper reports recent successes, and points to areas of future improvement. Advances in stochastic modeling and optimization can address some technical limitations in flow reconstruction, while various data mining and system identification techniques can provide possibilities to better condition realizations for consistency with top-down scenarios. Finally, we show that probabilistic and Bayesian frameworks together can provide a potential basis to combine information obtained from fully bottom-up analyses with projections available from climate and/or hydrological models in a fully integrated risk assessment framework for deep uncertainty.

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 service components as necessary to mediate the differences between the coupled models. This talk will first review two key products of the CSDMS project, namely a standardized model interface called the Basic Model Interface (BMI) and the CSDMS Standard Names. The standard names are used in conjunction with BMI to provide a semantic matching mechanism that allows output variables from one process model to be reliably used as input variables to other process models in a collection. They include not just a standardized naming scheme for model variables, but also a standardized set of terms for describing the attributes and assumptions of a given model. To illustrate the power of standardized model interfaces and metadata, a smart, light-weight modeling framework written in Python will be introduced that can automatically (without user intervention) couple a set of BMI-enabled hydrologic process components together to create a spatial hydrologic model. The same mechanisms could also be used to provide seamless integration (import/export) of data and models.

A framework for service enterprise workflow simulation with multi-agents cooperation

NASA Astrophysics Data System (ADS)

Tan, Wenan; Xu, Wei; Yang, Fujun; Xu, Lida; Jiang, Chuanqun

2013-11-01

Process dynamic modelling for service business is the key technique for Service-Oriented information systems and service business management, and the workflow model of business processes is the core part of service systems. Service business workflow simulation is the prevalent approach to be used for analysis of service business process dynamically. Generic method for service business workflow simulation is based on the discrete event queuing theory, which is lack of flexibility and scalability. In this paper, we propose a service workflow-oriented framework for the process simulation of service businesses using multi-agent cooperation to address the above issues. Social rationality of agent is introduced into the proposed framework. Adopting rationality as one social factor for decision-making strategies, a flexible scheduling for activity instances has been implemented. A system prototype has been developed to validate the proposed simulation framework through a business case study.

Geometry of behavioral spaces: A computational approach to analysis and understanding of agent based models and agent behaviors

NASA Astrophysics Data System (ADS)

Cenek, Martin; Dahl, Spencer K.

2016-11-01

Systems with non-linear dynamics frequently exhibit emergent system behavior, which is important to find and specify rigorously to understand the nature of the modeled phenomena. Through this analysis, it is possible to characterize phenomena such as how systems assemble or dissipate and what behaviors lead to specific final system configurations. Agent Based Modeling (ABM) is one of the modeling techniques used to study the interaction dynamics between a system's agents and its environment. Although the methodology of ABM construction is well understood and practiced, there are no computational, statistically rigorous, comprehensive tools to evaluate an ABM's execution. Often, a human has to observe an ABM's execution in order to analyze how the ABM functions, identify the emergent processes in the agent's behavior, or study a parameter's effect on the system-wide behavior. This paper introduces a new statistically based framework to automatically analyze agents' behavior, identify common system-wide patterns, and record the probability of agents changing their behavior from one pattern of behavior to another. We use network based techniques to analyze the landscape of common behaviors in an ABM's execution. Finally, we test the proposed framework with a series of experiments featuring increasingly emergent behavior. The proposed framework will allow computational comparison of ABM executions, exploration of a model's parameter configuration space, and identification of the behavioral building blocks in a model's dynamics.

Geometry of behavioral spaces: A computational approach to analysis and understanding of agent based models and agent behaviors.

PubMed

Cenek, Martin; Dahl, Spencer K

2016-11-01

Systems with non-linear dynamics frequently exhibit emergent system behavior, which is important to find and specify rigorously to understand the nature of the modeled phenomena. Through this analysis, it is possible to characterize phenomena such as how systems assemble or dissipate and what behaviors lead to specific final system configurations. Agent Based Modeling (ABM) is one of the modeling techniques used to study the interaction dynamics between a system's agents and its environment. Although the methodology of ABM construction is well understood and practiced, there are no computational, statistically rigorous, comprehensive tools to evaluate an ABM's execution. Often, a human has to observe an ABM's execution in order to analyze how the ABM functions, identify the emergent processes in the agent's behavior, or study a parameter's effect on the system-wide behavior. This paper introduces a new statistically based framework to automatically analyze agents' behavior, identify common system-wide patterns, and record the probability of agents changing their behavior from one pattern of behavior to another. We use network based techniques to analyze the landscape of common behaviors in an ABM's execution. Finally, we test the proposed framework with a series of experiments featuring increasingly emergent behavior. The proposed framework will allow computational comparison of ABM executions, exploration of a model's parameter configuration space, and identification of the behavioral building blocks in a model's dynamics.

Integrated modeling of land-use change: the role of coupling, interactions and feedbacks between the human and Earth systems

NASA Astrophysics Data System (ADS)

Monier, E.; Kicklighter, D. W.; Ejaz, Q.; Winchester, N.; Paltsev, S.; Reilly, J. M.

2016-12-01

Land-use change integrates a large number of components of the human and Earth systems, including climate, energy, water, and land. These complex coupling elements, interactions and feedbacks take place on a variety of space and time scales, thus increasing the complexity of land-use change modeling frameworks. In this study, we aim to identify which coupling elements, interactions and feedbacks are important for modeling land-use change, both at the global and regional level. First, we review the existing land-use change modeling framework used to develop land-use change projections for the Representative Concentration Pathways (RCP) scenarios. In such framework, land-use change is simulated by Integrated Assessment Models (IAMs) and mainly influenced by economic, energy, demographic and policy drivers. IAMs focus on representing the demand for agriculture and forestry goods (crops for food and bioenergy, forest products for construction and bioenergy), the interactions with other sectors of the economy and trade between various regions of the world. Then, we investigate how important various coupling elements and feedbacks with the Earth system are for projections of land-use change at the global and regional level. We focus on the following: i) the climate impacts on land productivity and greenhouse gas emissions, which requires climate change information and coupling to a terrestrial ecosystem model/crop model; ii) the climate and economic impacts on irrigation availability, which requires coupling the LUC modeling framework to a water resources management model and disaggregating rainfed and irrigated croplands; iii) the feedback of land-use change on the global and regional climate system through land-use change emissions and changes in the surface albedo and hydrology, which requires coupling to an Earth system model. Finally, we conclude our study by highlighting the current lack of clarity in how various components of the human and Earth systems are coupled in IAMs , and the need for a lexicon that is agreed upon by the IAM community.

The Estimation Theory Framework of Data Assimilation

NASA Technical Reports Server (NTRS)

Cohn, S.; Atlas, Robert (Technical Monitor)

2002-01-01

Lecture 1. The Estimation Theory Framework of Data Assimilation: 1. The basic framework: dynamical and observation models; 2. Assumptions and approximations; 3. The filtering, smoothing, and prediction problems; 4. Discrete Kalman filter and smoother algorithms; and 5. Example: A retrospective data assimilation system

Structure, function, and behaviour of computational models in systems biology

PubMed Central

2013-01-01

Background Systems Biology develops computational models in order to understand biological phenomena. The increasing number and complexity of such “bio-models” necessitate computer support for the overall modelling task. Computer-aided modelling has to be based on a formal semantic description of bio-models. But, even if computational bio-models themselves are represented precisely in terms of mathematical expressions their full meaning is not yet formally specified and only described in natural language. Results We present a conceptual framework – the meaning facets – which can be used to rigorously specify the semantics of bio-models. A bio-model has a dual interpretation: On the one hand it is a mathematical expression which can be used in computational simulations (intrinsic meaning). On the other hand the model is related to the biological reality (extrinsic meaning). We show that in both cases this interpretation should be performed from three perspectives: the meaning of the model’s components (structure), the meaning of the model’s intended use (function), and the meaning of the model’s dynamics (behaviour). In order to demonstrate the strengths of the meaning facets framework we apply it to two semantically related models of the cell cycle. Thereby, we make use of existing approaches for computer representation of bio-models as much as possible and sketch the missing pieces. Conclusions The meaning facets framework provides a systematic in-depth approach to the semantics of bio-models. It can serve two important purposes: First, it specifies and structures the information which biologists have to take into account if they build, use and exchange models. Secondly, because it can be formalised, the framework is a solid foundation for any sort of computer support in bio-modelling. The proposed conceptual framework establishes a new methodology for modelling in Systems Biology and constitutes a basis for computer-aided collaborative research. PMID:23721297

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.

Study on the influence of supplying compressed air channels and evicting channels on pneumatical oscillation systems for vibromooshing

NASA Astrophysics Data System (ADS)

Glăvan, D. O.; Radu, I.; Babanatsas, T.; Babanatis Merce, R. M.; Kiss, I.; Gaspar, M. C.

2018-01-01

The paper presents a pneumatic system with two oscillating masses. The system is composed of a cylinder (framework) with mass m1, which has a piston with mass m2 inside. The cylinder (framework system) has one supplying channel for compressed air and one evicting channel for each work chamber (left and right of the piston). Functionality of the piston position comparatively with the cylinder (framework) is possible through the supplying or evicting of compressed air. The variable force that keeps the movement depends on variation of the pressure that is changing depending on the piston position according to the cylinder (framework) and to the section form that is supplying and evicting channels with compressed air. The paper presents the physical model/pattern, the mathematical model/pattern (differential equations) and numerical solution of the differential equations in hypothesis with the section form of supplying and evicting channels with compressed air is rectangular (variation linear) or circular (variation nonlinear).

Systemic risk in a unifying framework for cascading processes on networks

NASA Astrophysics Data System (ADS)

Lorenz, J.; Battiston, S.; Schweitzer, F.

2009-10-01

We introduce a general framework for models of cascade and contagion processes on networks, to identify their commonalities and differences. In particular, models of social and financial cascades, as well as the fiber bundle model, the voter model, and models of epidemic spreading are recovered as special cases. To unify their description, we define the net fragility of a node, which is the difference between its fragility and the threshold that determines its failure. Nodes fail if their net fragility grows above zero and their failure increases the fragility of neighbouring nodes, thus possibly triggering a cascade. In this framework, we identify three classes depending on the way the fragility of a node is increased by the failure of a neighbour. At the microscopic level, we illustrate with specific examples how the failure spreading pattern varies with the node triggering the cascade, depending on its position in the network and its degree. At the macroscopic level, systemic risk is measured as the final fraction of failed nodes, X*, and for each of the three classes we derive a recursive equation to compute its value. The phase diagram of X* as a function of the initial conditions, thus allows for a prediction of the systemic risk as well as a comparison of the three different model classes. We could identify which model class leads to a first-order phase transition in systemic risk, i.e. situations where small changes in the initial conditions determine a global failure. Eventually, we generalize our framework to encompass stochastic contagion models. This indicates the potential for further generalizations.

Development of a software framework for data assimilation and its applications for streamflow forecasting in Japan

NASA Astrophysics Data System (ADS)

Noh, S. J.; Tachikawa, Y.; Shiiba, M.; Yorozu, K.; Kim, S.

2012-04-01

Data assimilation methods have received increased attention to accomplish uncertainty assessment and enhancement of forecasting capability in various areas. Despite of their potentials, applicable software frameworks to probabilistic approaches and data assimilation are still limited because the most of hydrologic modeling software are based on a deterministic approach. In this study, we developed a hydrological modeling framework for sequential data assimilation, so called MPI-OHyMoS. MPI-OHyMoS allows user to develop his/her own element models and to easily build a total simulation system model for hydrological simulations. Unlike process-based modeling framework, this software framework benefits from its object-oriented feature to flexibly represent hydrological processes without any change of the main library. Sequential data assimilation based on the particle filters is available for any hydrologic models based on MPI-OHyMoS considering various sources of uncertainty originated from input forcing, parameters and observations. The particle filters are a Bayesian learning process in which the propagation of all uncertainties is carried out by a suitable selection of randomly generated particles without any assumptions about the nature of the distributions. In MPI-OHyMoS, ensemble simulations are parallelized, which can take advantage of high performance computing (HPC) system. We applied this software framework for short-term streamflow forecasting of several catchments in Japan using a distributed hydrologic model. Uncertainty of model parameters and remotely-sensed rainfall data such as X-band or C-band radar is estimated and mitigated in the sequential data assimilation.

Developing a performance measurement framework and indicators for community health service facilities in urban China.

PubMed

Wong, Sabrina T; Yin, Delu; Bhattacharyya, Onil; Wang, Bin; Liu, Liqun; Chen, Bowen

2010-11-18

China has had no effective and systematic information system to provide guidance for strengthening PHC (Primary Health Care) or account to citizens on progress. We report on the development of the China results-based Logic Model for Community Health Facilities and Stations (CHS) and a set of relevant PHC indicators intended to measure CHS priorities. We adapted the PHC Results Based Logic Model developed in Canada and current work conducted in the community health system in China to create the China CHS Logic Model framework. We used a staged approach by first constructing the framework and indicators and then validating their content through an interactive process involving policy analysis, critical review of relevant literature and multiple stakeholder consultation. The China CHS Logic Model includes inputs, activities, outputs and outcomes with a total of 287 detailed performance indicators. In these indicators, 31 indicators measure inputs, 64 measure activities, 105 measure outputs, and 87 measure immediate (n = 65), intermediate (n = 15), or final (n = 7) outcomes. A Logic Model framework can be useful in planning, implementation, analysis and evaluation of PHC at a system and service level. The development and content validation of the China CHS Logic Model and subsequent indicators provides a means for stronger accountability and a clearer sense of overall direction and purpose needed to renew and strengthen the PHC system in China. Moreover, this work will be useful in moving towards developing a PHC information system and performance measurement across districts in urban China, and guiding the pursuit of quality in PHC.

Developing a Performance Measurement Framework and Indicators for Community Health Service Facilities in Urban China

PubMed Central

2010-01-01

Background China has had no effective and systematic information system to provide guidance for strengthening PHC (Primary Health Care) or account to citizens on progress. We report on the development of the China results-based Logic Model for Community Health Facilities and Stations (CHS) and a set of relevant PHC indicators intended to measure CHS priorities. Methods We adapted the PHC Results Based Logic Model developed in Canada and current work conducted in the community health system in China to create the China CHS Logic Model framework. We used a staged approach by first constructing the framework and indicators and then validating their content through an interactive process involving policy analysis, critical review of relevant literature and multiple stakeholder consultation. Results The China CHS Logic Model includes inputs, activities, outputs and outcomes with a total of 287 detailed performance indicators. In these indicators, 31 indicators measure inputs, 64 measure activities, 105 measure outputs, and 87 measure immediate (n = 65), intermediate (n = 15), or final (n = 7) outcomes. Conclusion A Logic Model framework can be useful in planning, implementation, analysis and evaluation of PHC at a system and service level. The development and content validation of the China CHS Logic Model and subsequent indicators provides a means for stronger accountability and a clearer sense of overall direction and purpose needed to renew and strengthen the PHC system in China. Moreover, this work will be useful in moving towards developing a PHC information system and performance measurement across districts in urban China, and guiding the pursuit of quality in PHC. PMID:21087516

Implementation of the US EPA (United States Environmental Protection Agency) Regional Oxidant Modeling System

DOE Office of Scientific and Technical Information (OSTI.GOV)

Novak, J.H.

1984-05-01

Model design, implementation and quality assurance procedures can have a significant impact on the effectiveness of long term utility of any modeling approach. The Regional Oxidant Modeling System (ROMS) is exceptionally complex because it treats all chemical and physical processes thought to affect ozone concentration on a regional scale. Thus, to effectively illustrate useful design and implementation techniques, this paper describes the general modeling framework which forms the basis of the ROMS. This framework is flexible enough to allow straightforward update or replacement of the chemical kinetics mechanism and/or any theoretical formulations of the physical processes. Use of the Jacksonmore » Structured Programming (JSP) method to implement this modeling framework has not only increased programmer productivity and quality of the resulting programs, but also has provided standardized program design, dynamic documentation, and easily maintainable and transportable code. A summary of the JSP method is presented to encourage modelers to pursue this technique in their own model development efforts. In addition, since data preparation is such an integral part of a successful modeling system, the ROMS processor network is described with emphasis on the internal quality control techniques.« less

An overview of the model integration process: From pre ...

EPA Pesticide Factsheets

Integration of models requires linking models which can be developed using different tools, methodologies, and assumptions. We performed a literature review with the aim of improving our understanding of model integration process, and also presenting better strategies for building integrated modeling systems. We identified five different phases to characterize integration process: pre-integration assessment, preparation of models for integration, orchestration of models during simulation, data interoperability, and testing. Commonly, there is little reuse of existing frameworks beyond the development teams and not much sharing of science components across frameworks. We believe this must change to enable researchers and assessors to form complex workflows that leverage the current environmental science available. In this paper, we characterize the model integration process and compare integration practices of different groups. We highlight key strategies, features, standards, and practices that can be employed by developers to increase reuse and interoperability of science software components and systems. The paper provides a review of the literature regarding techniques and methods employed by various modeling system developers to facilitate science software interoperability. The intent of the paper is to illustrate the wide variation in methods and the limiting effect the variation has on inter-framework reuse and interoperability. A series of recommendation

Communication: Introducing prescribed biases in out-of-equilibrium Markov models

NASA Astrophysics Data System (ADS)

Dixit, Purushottam D.

2018-03-01

Markov models are often used in modeling complex out-of-equilibrium chemical and biochemical systems. However, many times their predictions do not agree with experiments. We need a systematic framework to update existing Markov models to make them consistent with constraints that are derived from experiments. Here, we present a framework based on the principle of maximum relative path entropy (minimum Kullback-Leibler divergence) to update Markov models using stationary state and dynamical trajectory-based constraints. We illustrate the framework using a biochemical model network of growth factor-based signaling. We also show how to find the closest detailed balanced Markov model to a given Markov model. Further applications and generalizations are discussed.

Load Model Verification, Validation and Calibration Framework by Statistical Analysis on Field Data

NASA Astrophysics Data System (ADS)

Jiao, Xiangqing; Liao, Yuan; Nguyen, Thai

2017-11-01

Accurate load models are critical for power system analysis and operation. A large amount of research work has been done on load modeling. Most of the existing research focuses on developing load models, while little has been done on developing formal load model verification and validation (V&V) methodologies or procedures. Most of the existing load model validation is based on qualitative rather than quantitative analysis. In addition, not all aspects of model V&V problem have been addressed by the existing approaches. To complement the existing methods, this paper proposes a novel load model verification and validation framework that can systematically and more comprehensively examine load model's effectiveness and accuracy. Statistical analysis, instead of visual check, quantifies the load model's accuracy, and provides a confidence level of the developed load model for model users. The analysis results can also be used to calibrate load models. The proposed framework can be used as a guidance to systematically examine load models for utility engineers and researchers. The proposed method is demonstrated through analysis of field measurements collected from a utility system.

A coupled modeling framework of the co-evolution of humans and water: case study of Tarim River Basin, western China

NASA Astrophysics Data System (ADS)

Liu, D.; Tian, F.; Lin, M.; Sivapalan, M.

2014-04-01

The complex interactions and feedbacks between humans and water are very essential issues but are poorly understood in the newly proposed discipline of socio-hydrology (Sivapalan et al., 2012). An exploratory model with the appropriate level of simplification can be valuable to improve our understanding of the co-evolution and self-organization of socio-hydrological systems driven by interactions and feedbacks operating at different scales. In this study, a simple coupled modeling framework for socio-hydrology co-evolution is developed for the Tarim River Basin in Western China, and is used to illustrate the explanatory power of such a model. The study area is the mainstream of the Tarim River, which is divided into two modeling units. The socio-hydrological system is composed of four parts, i.e. social sub-system, economic sub-system, ecological sub-system, and hydrological sub-system. In each modeling unit, four coupled ordinary differential equations are used to simulate the dynamics of the social sub-system represented by human population, the economic sub-system represented by irrigated crop area, the ecological sub-system represented by natural vegetation cover and the hydrological sub-system represented by stream discharge. The coupling and feedback processes of the four dominant sub-systems (and correspondingly four state variables) are integrated into several internal system characteristics interactively and jointly determined by themselves and by other coupled systems. For example, the stream discharge is coupled to the irrigated crop area by the colonization rate and mortality rate of the irrigated crop area in the upper reach and the irrigated area is coupled to stream discharge through irrigation water consumption. In a similar way, the stream discharge and natural vegetation cover are coupled together. The irrigated crop area is coupled to human population by the colonization rate and mortality rate of the population. The inflow of the lower reach is determined by the outflow from the upper reach. The natural vegetation cover in the lower reach is coupled to the outflow from the upper reach and governed by regional water resources management policy. The co-evolution of the Tarim socio-hydrological system is then analyzed within this modeling framework to gain insights into the overall system dynamics and its sensitivity to the external drivers and internal system variables. In the modeling framework, the state of each subsystem is holistically described by one state variable and the framework is flexible enough to comprise more processes and constitutive relationships if they are needed to illustrate the interaction and feedback mechanisms of the human-water system.

The blackboard model - A framework for integrating multiple cooperating expert systems

NASA Technical Reports Server (NTRS)

Erickson, W. K.

1985-01-01

The use of an artificial intelligence (AI) architecture known as the blackboard model is examined as a framework for designing and building distributed systems requiring the integration of multiple cooperating expert systems (MCXS). Aerospace vehicles provide many examples of potential systems, ranging from commercial and military aircraft to spacecraft such as satellites, the Space Shuttle, and the Space Station. One such system, free-flying, spaceborne telerobots to be used in construction, servicing, inspection, and repair tasks around NASA's Space Station, is examined. The major difficulties found in designing and integrating the individual expert system components necessary to implement such a robot are outlined. The blackboard model, a general expert system architecture which seems to address many of the problems found in designing and building such a system, is discussed. A progress report on a prototype system under development called DBB (Distributed BlackBoard model) is given. The prototype will act as a testbed for investigating the feasibility, utility, and efficiency of MCXS-based designs developed under the blackboard model.

Toward improved calibration of watershed models: multisite many objective measures of information

USDA-ARS?s Scientific Manuscript database

This paper presents a computational framework for incorporation of disparate information from observed hydrologic responses at multiple locations into the calibration of watershed models. The framework consists of four components: (i) an a-priori characterization of system behavior; (ii) a formal an...

Modeling Framework and Validation of a Smart Grid and Demand Response System for Wind Power Integration

DOE Office of Scientific and Technical Information (OSTI.GOV)

Broeer, Torsten; Fuller, Jason C.; Tuffner, Francis K.

2014-01-31

Electricity generation from wind power and other renewable energy sources is increasing, and their variability introduces new challenges to the power system. The emergence of smart grid technologies in recent years has seen a paradigm shift in redefining the electrical system of the future, in which controlled response of the demand side is used to balance fluctuations and intermittencies from the generation side. This paper presents a modeling framework for an integrated electricity system where loads become an additional resource. The agent-based model represents a smart grid power system integrating generators, transmission, distribution, loads and market. The model incorporates generatormore » and load controllers, allowing suppliers and demanders to bid into a Real-Time Pricing (RTP) electricity market. The modeling framework is applied to represent a physical demonstration project conducted on the Olympic Peninsula, Washington, USA, and validation simulations are performed using actual dynamic data. Wind power is then introduced into the power generation mix illustrating the potential of demand response to mitigate the impact of wind power variability, primarily through thermostatically controlled loads. The results also indicate that effective implementation of Demand Response (DR) to assist integration of variable renewable energy resources requires a diversity of loads to ensure functionality of the overall system.« less

Integration of a CAD System Into an MDO Framework

NASA Technical Reports Server (NTRS)

Townsend, J. C.; Samareh, J. A.; Weston, R. P.; Zorumski, W. E.

1998-01-01

NASA Langley has developed a heterogeneous distributed computing environment, called the Framework for Inter-disciplinary Design Optimization, or FIDO. Its purpose has been to demonstrate framework technical feasibility and usefulness for optimizing the preliminary design of complex systems and to provide a working environment for testing optimization schemes. Its initial implementation has been for a simplified model of preliminary design of a high-speed civil transport. Upgrades being considered for the FIDO system include a more complete geometry description, required by high-fidelity aerodynamics and structures codes and based on a commercial Computer Aided Design (CAD) system. This report presents the philosophy behind some of the decisions that have shaped the FIDO system and gives a brief case study of the problems and successes encountered in integrating a CAD system into the FEDO framework.

Advanced Information Technology in Simulation Based Life Cycle Design

NASA Technical Reports Server (NTRS)

Renaud, John E.

2003-01-01

In this research a Collaborative Optimization (CO) approach for multidisciplinary systems design is used to develop a decision based design framework for non-deterministic optimization. To date CO strategies have been developed for use in application to deterministic systems design problems. In this research the decision based design (DBD) framework proposed by Hazelrigg is modified for use in a collaborative optimization framework. The Hazelrigg framework as originally proposed provides a single level optimization strategy that combines engineering decisions with business decisions in a single level optimization. By transforming this framework for use in collaborative optimization one can decompose the business and engineering decision making processes. In the new multilevel framework of Decision Based Collaborative Optimization (DBCO) the business decisions are made at the system level. These business decisions result in a set of engineering performance targets that disciplinary engineering design teams seek to satisfy as part of subspace optimizations. The Decision Based Collaborative Optimization framework more accurately models the existing relationship between business and engineering in multidisciplinary systems design.

OpenDanubia - An integrated, modular simulation system to support regional water resource management

NASA Astrophysics Data System (ADS)

Muerth, M.; Waldmann, D.; Heinzeller, C.; Hennicker, R.; Mauser, W.

2012-04-01

The already completed, multi-disciplinary research project GLOWA-Danube has developed a regional scale, integrated modeling system, which was successfully applied on the 77,000 km2 Upper Danube basin to investigate the impact of Global Change on both the natural and anthropogenic water cycle. At the end of the last project phase, the integrated modeling system was transferred into the open source project OpenDanubia, which now provides both the core system as well as all major model components to the general public. First, this will enable decision makers from government, business and management to use OpenDanubia as a tool for proactive management of water resources in the context of global change. Secondly, the model framework to support integrated simulations and all simulation models developed for OpenDanubia in the scope of GLOWA-Danube are further available for future developments and research questions. OpenDanubia allows for the investigation of water-related scenarios considering different ecological and economic aspects to support both scientists and policy makers to design policies for sustainable environmental management. OpenDanubia is designed as a framework-based, distributed system. The model system couples spatially distributed physical and socio-economic process during run-time, taking into account their mutual influence. To simulate the potential future impacts of Global Change on agriculture, industrial production, water supply, households and tourism businesses, so-called deep actor models are implemented in OpenDanubia. All important water-related fluxes and storages in the natural environment are implemented in OpenDanubia as spatially explicit, process-based modules. This includes the land surface water and energy balance, dynamic plant water uptake, ground water recharge and flow as well as river routing and reservoirs. Although the complete system is relatively demanding on data requirements and hardware requirements, the modular structure and the generic core system (Core Framework, Actor Framework) allows the application in new regions and the selection of a reduced number of modules for simulation. As part of the Open Source Initiative in GLOWA-Danube (opendanubia.glowa-danube.de) a comprehensive documentation for the system installation was created and both the program code of the framework and of all major components is licensed under the GNU General Public License. In addition, some helpful programs and scripts necessary for the operation and processing of input and result data sets are provided.

Ontological Problem-Solving Framework for Assigning Sensor Systems and Algorithms to High-Level Missions

PubMed Central

Qualls, Joseph; Russomanno, David J.

2011-01-01

The lack of knowledge models to represent sensor systems, algorithms, and missions makes opportunistically discovering a synthesis of systems and algorithms that can satisfy high-level mission specifications impractical. A novel ontological problem-solving framework has been designed that leverages knowledge models describing sensors, algorithms, and high-level missions to facilitate automated inference of assigning systems to subtasks that may satisfy a given mission specification. To demonstrate the efficacy of the ontological problem-solving architecture, a family of persistence surveillance sensor systems and algorithms has been instantiated in a prototype environment to demonstrate the assignment of systems to subtasks of high-level missions. PMID:22164081

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hartmann, Anja, E-mail: hartmann@ipk-gatersleben.de; Schreiber, Falk; Martin-Luther-University Halle-Wittenberg, Halle

The characterization of biological systems with respect to their behavior and functionality based on versatile biochemical interactions is a major challenge. To understand these complex mechanisms at systems level modeling approaches are investigated. Different modeling formalisms allow metabolic models to be analyzed depending on the question to be solved, the biochemical knowledge and the availability of experimental data. Here, we describe a method for an integrative analysis of the structure and dynamics represented by qualitative and quantitative metabolic models. Using various formalisms, the metabolic model is analyzed from different perspectives. Determined structural and dynamic properties are visualized in the contextmore » of the metabolic model. Interaction techniques allow the exploration and visual analysis thereby leading to a broader understanding of the behavior and functionality of the underlying biological system. The System Biology Metabolic Model Framework (SBM{sup 2} – Framework) implements the developed method and, as an example, is applied for the integrative analysis of the crop plant potato.« less

On domain modelling of the service system with its application to enterprise information systems

NASA Astrophysics Data System (ADS)

Wang, J. W.; Wang, H. F.; Ding, J. L.; Furuta, K.; Kanno, T.; Ip, W. H.; Zhang, W. J.

2016-01-01

Information systems are a kind of service systems and they are throughout every element of a modern industrial and business system, much like blood in our body. Types of information systems are heterogeneous because of extreme uncertainty in changes in modern industrial and business systems. To effectively manage information systems, modelling of the work domain (or domain) of information systems is necessary. In this paper, a domain modelling framework for the service system is proposed and its application to the enterprise information system is outlined. The framework is defined based on application of a general domain modelling tool called function-context-behaviour-principle-state-structure (FCBPSS). The FCBPSS is based on a set of core concepts, namely: function, context, behaviour, principle, state and structure and system decomposition. Different from many other applications of FCBPSS in systems engineering, the FCBPSS is applied to both infrastructure and substance systems, which is novel and effective to modelling of service systems including enterprise information systems. It is to be noted that domain modelling of systems (e.g. enterprise information systems) is a key to integration of heterogeneous systems and to coping with unanticipated situations facing to systems.

Operationalizing the Learning Health Care System in an Integrated Delivery System

PubMed Central

Psek, Wayne A.; Stametz, Rebecca A.; Bailey-Davis, Lisa D.; Davis, Daniel; Darer, Jonathan; Faucett, William A.; Henninger, Debra L.; Sellers, Dorothy C.; Gerrity, Gloria

2015-01-01

Introduction: The Learning Health Care System (LHCS) model seeks to utilize sophisticated technologies and competencies to integrate clinical operations, research and patient participation in order to continuously generate knowledge, improve care, and deliver value. Transitioning from concept to practical application of an LHCS presents many challenges but can yield opportunities for continuous improvement. There is limited literature and practical experience available in operationalizing the LHCS in the context of an integrated health system. At Geisinger Health System (GHS) a multi-stakeholder group is undertaking to enhance organizational learning and develop a plan for operationalizing the LHCS system-wide. We present a framework for operationalizing continuous learning across an integrated delivery system and lessons learned through the ongoing planning process. Framework: The framework focuses attention on nine key LHCS operational components: Data and Analytics; People and Partnerships; Patient and Family Engagement; Ethics and Oversight; Evaluation and Methodology; Funding; Organization; Prioritization; and Deliverables. Definitions, key elements and examples for each are presented. The framework is purposefully broad for application across different organizational contexts. Conclusion: A realistic assessment of the culture, resources and capabilities of the organization related to learning is critical to defining the scope of operationalization. Engaging patients in clinical care and discovery, including quality improvement and comparative effectiveness research, requires a defensible ethical framework that undergirds a system of strong but flexible oversight. Leadership support is imperative for advancement of the LHCS model. Findings from our ongoing work within the proposed framework may inform other organizations considering a transition to an LHCS. PMID:25992388

eClims: An Extensible and Dynamic Integration Framework for Biomedical Information Systems.

PubMed

Savonnet, Marinette; Leclercq, Eric; Naubourg, Pierre

2016-11-01

Biomedical information systems (BIS) require consideration of three types of variability: data variability induced by new high throughput technologies, schema or model variability induced by large scale studies or new fields of research, and knowledge variability resulting from new discoveries. Beyond data heterogeneity, managing variabilities in the context of BIS requires extensible and dynamic integration process. In this paper, we focus on data and schema variabilities and we propose an integration framework based on ontologies, master data, and semantic annotations. The framework addresses issues related to: 1) collaborative work through a dynamic integration process; 2) variability among studies using an annotation mechanism; and 3) quality control over data and semantic annotations. Our approach relies on two levels of knowledge: BIS-related knowledge is modeled using an application ontology coupled with UML models that allow controlling data completeness and consistency, and domain knowledge is described by a domain ontology, which ensures data coherence. A system build with the eClims framework has been implemented and evaluated in the context of a proteomic platform.

Predictor-corrector framework for the sequential assembly of optical systems based on wavefront sensing.

PubMed

Schindlbeck, Christopher; Pape, Christian; Reithmeier, Eduard

2018-04-16

Alignment of optical components is crucial for the assembly of optical systems to ensure their full functionality. In this paper we present a novel predictor-corrector framework for the sequential assembly of serial optical systems. Therein, we use a hybrid optical simulation model that comprises virtual and identified component positions. The hybrid model is constantly adapted throughout the assembly process with the help of nonlinear identification techniques and wavefront measurements. This enables prediction of the future wavefront at the detector plane and therefore allows for taking corrective measures accordingly during the assembly process if a user-defined tolerance on the wavefront error is violated. We present a novel notation for the so-called hybrid model and outline the work flow of the presented predictor-corrector framework. A beam expander is assembled as demonstrator for experimental verification of the framework. The optical setup consists of a laser, two bi-convex spherical lenses each mounted to a five degree-of-freedom stage to misalign and correct components, and a Shack-Hartmann sensor for wavefront measurements.

A Computational Framework for Bioimaging Simulation

PubMed Central

Watabe, Masaki; Arjunan, Satya N. V.; Fukushima, Seiya; Iwamoto, Kazunari; Kozuka, Jun; Matsuoka, Satomi; Shindo, Yuki; Ueda, Masahiro; Takahashi, Koichi

2015-01-01

Using bioimaging technology, biologists have attempted to identify and document analytical interpretations that underlie biological phenomena in biological cells. Theoretical biology aims at distilling those interpretations into knowledge in the mathematical form of biochemical reaction networks and understanding how higher level functions emerge from the combined action of biomolecules. However, there still remain formidable challenges in bridging the gap between bioimaging and mathematical modeling. Generally, measurements using fluorescence microscopy systems are influenced by systematic effects that arise from stochastic nature of biological cells, the imaging apparatus, and optical physics. Such systematic effects are always present in all bioimaging systems and hinder quantitative comparison between the cell model and bioimages. Computational tools for such a comparison are still unavailable. Thus, in this work, we present a computational framework for handling the parameters of the cell models and the optical physics governing bioimaging systems. Simulation using this framework can generate digital images of cell simulation results after accounting for the systematic effects. We then demonstrate that such a framework enables comparison at the level of photon-counting units. PMID:26147508

Conceptual Models, Choices, and Benchmarks for Building Quality Work Cultures.

ERIC Educational Resources Information Center

Acker-Hocevar, Michele

1996-01-01

The two models in Florida's Educational Quality Benchmark System represent a new way of thinking about developing schools' work culture. The Quality Performance System Model identifies nine dimensions of work within a quality system. The Change Process Model provides a theoretical framework for changing existing beliefs, attitudes, and behaviors…

A proposed analytic framework for determining the impact of an antimicrobial resistance intervention.

PubMed

Grohn, Yrjo T; Carson, Carolee; Lanzas, Cristina; Pullum, Laura; Stanhope, Michael; Volkova, Victoriya

2017-06-01

Antimicrobial use (AMU) is increasingly threatened by antimicrobial resistance (AMR). The FDA is implementing risk mitigation measures promoting prudent AMU in food animals. Their evaluation is crucial: the AMU/AMR relationship is complex; a suitable framework to analyze interventions is unavailable. Systems science analysis, depicting variables and their associations, would help integrate mathematics/epidemiology to evaluate the relationship. This would identify informative data and models to evaluate interventions. This National Institute for Mathematical and Biological Synthesis AMR Working Group's report proposes a system framework to address the methodological gap linking livestock AMU and AMR in foodborne bacteria. It could evaluate how AMU (and interventions) impact AMR. We will evaluate pharmacokinetic/dynamic modeling techniques for projecting AMR selection pressure on enteric bacteria. We study two methods to model phenotypic AMR changes in bacteria in the food supply and evolutionary genotypic analyses determining molecular changes in phenotypic AMR. Systems science analysis integrates the methods, showing how resistance in the food supply is explained by AMU and concurrent factors influencing the whole system. This process is updated with data and techniques to improve prediction and inform improvements for AMU/AMR surveillance. Our proposed framework reflects both the AMR system's complexity, and desire for simple, reliable conclusions.

Advanced error diagnostics of the CMAQ and Chimere modelling systems within the AQMEII3 model evaluation framework

EPA Science Inventory

The work here complements the overview analysis of the modelling systems participating in the third phase of the Air Quality Model Evaluation International Initiative (AQMEII3) by focusing on the performance for hourly surface ozone by two modelling systems, Chimere for Europe an...

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hansen, Jacob; Edgar, Thomas W.; Daily, Jeffrey A.

With an ever-evolving power grid, concerns regarding how to maintain system stability, efficiency, and reliability remain constant because of increasing uncertainties and decreasing rotating inertia. To alleviate some of these concerns, demand response represents a viable solution and is virtually an untapped resource in the current power grid. This work describes a hierarchical control framework that allows coordination between distributed energy resources and demand response. This control framework is composed of two control layers: a coordination layer that ensures aggregations of resources are coordinated to achieve system objectives and a device layer that controls individual resources to assure the predeterminedmore » power profile is tracked in real time. Large-scale simulations are executed to study the hierarchical control, requiring advancements in simulation capabilities. Technical advancements necessary to investigate and answer control interaction questions, including the Framework for Network Co-Simulation platform and Arion modeling capability, are detailed. Insights into the interdependencies of controls across a complex system and how they must be tuned, as well as validation of the effectiveness of the proposed control framework, are yielded using a large-scale integrated transmission system model coupled with multiple distribution systems.« less

A framework for optimization and quantification of uncertainty and sensitivity for developing carbon capture systems

DOE PAGES

Eslick, John C.; Ng, Brenda; Gao, Qianwen; ...

2014-12-31

Under the auspices of the U.S. Department of Energy’s Carbon Capture Simulation Initiative (CCSI), a Framework for Optimization and Quantification of Uncertainty and Sensitivity (FOQUS) has been developed. This tool enables carbon capture systems to be rapidly synthesized and rigorously optimized, in an environment that accounts for and propagates uncertainties in parameters and models. FOQUS currently enables (1) the development of surrogate algebraic models utilizing the ALAMO algorithm, which can be used for superstructure optimization to identify optimal process configurations, (2) simulation-based optimization utilizing derivative free optimization (DFO) algorithms with detailed black-box process models, and (3) rigorous uncertainty quantification throughmore » PSUADE. FOQUS utilizes another CCSI technology, the Turbine Science Gateway, to manage the thousands of simulated runs necessary for optimization and UQ. Thus, this computational framework has been demonstrated for the design and analysis of a solid sorbent based carbon capture system.« less

Decision support system based on DPSIR framework for a low flow Mediterranean river basin

NASA Astrophysics Data System (ADS)

Bangash, Rubab Fatima; Kumar, Vikas; Schuhmacher, Marta

2013-04-01

The application of decision making practices are effectively enhanced by adopting a procedural approach setting out a general methodological framework within which specific methods, models and tools can be integrated. Integrated Catchment Management is a process that recognizes the river catchment as a basic organizing unit for understanding and managing ecosystem process. Decision support system becomes more complex by considering unavoidable human activities within a catchment that are motivated by multiple and often competing criteria and/or constraints. DPSIR is a causal framework for describing the interactions between society and the environment. This framework has been adopted by the European Environment Agency and the components of this model are: Driving forces, Pressures, States, Impacts and Responses. The proposed decision support system is a two step framework based on DPSIR. Considering first three component of DPSIR, Driving forces, Pressures and States, hydrological and ecosystem services models are developed. The last two components, Impact and Responses, helped to develop Bayesian Network to integrate the models. This decision support system also takes account of social, economic and environmental aspects. A small river of Catalonia (Northeastern Spain), Francoli River with a low flow (~2 m3/s) is selected for integration of catchment assessment models and to improve knowledge transfer from research to the stakeholders with a view to improve decision making process. DHI's MIKE BASIN software is used to evaluate the low-flow Francolí River with respect to the water bodies' characteristics and also to assess the impact of human activities aiming to achieve good water status for all waters to comply with the WFD's River Basin Management Plan. Based on ArcGIS, MIKE BASIN is a versatile decision support tool that provides a simple and powerful framework for managers and stakeholders to address multisectoral allocation and environmental issues in river basins. While InVEST is a spatially explicit tool, used to model and map a suite of ecosystem services caused by land cover changes or climate change impacts. Moreover, results obtained from low-flow hydrological simulation and ecosystem services models serves as useful tools to develop decision support system based on DPSIR framework by integrating models. Bayesian Networks is used as a knowledge integration and visualization tool to summarize the outcomes of hydrological and ecosystem services models at the "Response" stage of DPSIR. Bayesian Networks provide a framework for modelling the logical relationship between catchment variables and decision objectives by quantifying the strength of these relationships using conditional probabilities. Participatory nature of this framework can provide better communication of water research, particularly in the context of a perceived lack of future awareness-raising with the public that helps to develop more sustainable water management strategies. Acknowledgements The present study was financially supported by Spanish Ministry of Economy and Competitiveness for its financial support through the project SCARCE (Consolider-Ingenio 2010 CSD2009-00065). R. F. Bangash also received PhD fellowship from AGAUR (Commissioner for Universities and Research of the Department of Innovation, Universities and Enterprise of the "Generalitat de Catalunya" and the European Social Fund).

A Bayesian framework based on a Gaussian mixture model and radial-basis-function Fisher discriminant analysis (BayGmmKda V1.1) for spatial prediction of floods

NASA Astrophysics Data System (ADS)

Tien Bui, Dieu; Hoang, Nhat-Duc

2017-09-01

In this study, a probabilistic model, named as BayGmmKda, is proposed for flood susceptibility assessment in a study area in central Vietnam. The new model is a Bayesian framework constructed by a combination of a Gaussian mixture model (GMM), radial-basis-function Fisher discriminant analysis (RBFDA), and a geographic information system (GIS) database. In the Bayesian framework, GMM is used for modeling the data distribution of flood-influencing factors in the GIS database, whereas RBFDA is utilized to construct a latent variable that aims at enhancing the model performance. As a result, the posterior probabilistic output of the BayGmmKda model is used as flood susceptibility index. Experiment results showed that the proposed hybrid framework is superior to other benchmark models, including the adaptive neuro-fuzzy inference system and the support vector machine. To facilitate the model implementation, a software program of BayGmmKda has been developed in MATLAB. The BayGmmKda program can accurately establish a flood susceptibility map for the study region. Accordingly, local authorities can overlay this susceptibility map onto various land-use maps for the purpose of land-use planning or management.

The Foundations Framework for Developing and Reporting New Models of Care for Multimorbidity

PubMed Central

Stokes, Jonathan; Man, Mei-See; Guthrie, Bruce; Mercer, Stewart W.; Salisbury, Chris; Bower, Peter

2017-01-01

PURPOSE Multimorbidity challenges health systems globally. New models of care are urgently needed to better manage patients with multimorbidity; however, there is no agreed framework for designing and reporting models of care for multimorbidity and their evaluation. METHODS Based on findings from a literature search to identify models of care for multimorbidity, we developed a framework to describe these models. We illustrate the application of the framework by identifying the focus and gaps in current models of care, and by describing the evolution of models over time. RESULTS Our framework describes each model in terms of its theoretical basis and target population (the foundations of the model) and of the elements of care implemented to deliver the model. We categorized elements of care into 3 types: (1) clinical focus, (2) organization of care, (3) support for model delivery. Application of the framework identified a limited use of theory in model design and a strong focus on some patient groups (elderly, high users) more than others (younger patients, deprived populations). We found changes in elements with time, with a decrease in models implementing home care and an increase in models offering extended appointments. CONCLUSIONS By encouragin greater clarity about the underpinning theory and target population, and by categorizing the wide range of potentially important elements of an intervention to improve care for patients with multimorbidity, the framework may be useful in designing and reporting models of care and help advance the currently limited evidence base. PMID:29133498

Positive Youth Development and Nutrition: Interdisciplinary Strategies to Enhance Student Outcomes

ERIC Educational Resources Information Center

Edwards, Oliver W.; Cheeley, Taylor

2016-01-01

Educational policies require the use of data and progress monitoring frameworks to guide instruction and intervention in schools. As a result, different problem-solving models such as multitiered systems of supports (MTSS) have emerged that use these frameworks to improve student outcomes. However, problem-focused models emphasize negative…

Theories, models and frameworks used in capacity building interventions relevant to public health: a systematic review.

PubMed

Bergeron, Kim; Abdi, Samiya; DeCorby, Kara; Mensah, Gloria; Rempel, Benjamin; Manson, Heather

2017-11-28

There is limited research on capacity building interventions that include theoretical foundations. The purpose of this systematic review is to identify underlying theories, models and frameworks used to support capacity building interventions relevant to public health practice. The aim is to inform and improve capacity building practices and services offered by public health organizations. Four search strategies were used: 1) electronic database searching; 2) reference lists of included papers; 3) key informant consultation; and 4) grey literature searching. Inclusion and exclusion criteria are outlined with included papers focusing on capacity building, learning plans, professional development plans in combination with tools, resources, processes, procedures, steps, model, framework, guideline, described in a public health or healthcare setting, or non-government, government, or community organizations as they relate to healthcare, and explicitly or implicitly mention a theory, model and/or framework that grounds the type of capacity building approach developed. Quality assessment were performed on all included articles. Data analysis included a process for synthesizing, analyzing and presenting descriptive summaries, categorizing theoretical foundations according to which theory, model and/or framework was used and whether or not the theory, model or framework was implied or explicitly identified. Nineteen articles were included in this review. A total of 28 theories, models and frameworks were identified. Of this number, two theories (Diffusion of Innovations and Transformational Learning), two models (Ecological and Interactive Systems Framework for Dissemination and Implementation) and one framework (Bloom's Taxonomy of Learning) were identified as the most frequently cited. This review identifies specific theories, models and frameworks to support capacity building interventions relevant to public health organizations. It provides public health practitioners with a menu of potentially usable theories, models and frameworks to support capacity building efforts. The findings also support the need for the use of theories, models or frameworks to be intentional, explicitly identified, referenced and for it to be clearly outlined how they were applied to the capacity building intervention.

A surety engineering framework to reduce cognitive systems risks.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Caudell, Thomas P.; Peercy, David Eugene; Caldera, Eva O.

Cognitive science research investigates the advancement of human cognition and neuroscience capabilities. Addressing risks associated with these advancements can counter potential program failures, legal and ethical issues, constraints to scientific research, and product vulnerabilities. Survey results, focus group discussions, cognitive science experts, and surety researchers concur technical risks exist that could impact cognitive science research in areas such as medicine, privacy, human enhancement, law and policy, military applications, and national security (SAND2006-6895). This SAND report documents a surety engineering framework and a process for identifying cognitive system technical, ethical, legal and societal risks and applying appropriate surety methods to reducemore » such risks. The framework consists of several models: Specification, Design, Evaluation, Risk, and Maturity. Two detailed case studies are included to illustrate the use of the process and framework. Several Appendices provide detailed information on existing cognitive system architectures; ethical, legal, and societal risk research; surety methods and technologies; and educing information research with a case study vignette. The process and framework provide a model for how cognitive systems research and full-scale product development can apply surety engineering to reduce perceived and actual risks.« less

Information of Complex Systems and Applications in Agent Based Modeling.

PubMed

Bao, Lei; Fritchman, Joseph C

2018-04-18

Information about a system's internal interactions is important to modeling the system's dynamics. This study examines the finer categories of the information definition and explores the features of a type of local information that describes the internal interactions of a system. Based on the results, a dual-space agent and information modeling framework (AIM) is developed by explicitly distinguishing an information space from the material space. The two spaces can evolve both independently and interactively. The dual-space framework can provide new analytic methods for agent based models (ABMs). Three examples are presented including money distribution, individual's economic evolution, and artificial stock market. The results are analyzed in the dual-space, which more clearly shows the interactions and evolutions within and between the information and material spaces. The outcomes demonstrate the wide-ranging applicability of using the dual-space AIMs to model and analyze a broad range of interactive and intelligent systems.

IGMS: An Integrated ISO-to-Appliance Scale Grid Modeling System

DOE Office of Scientific and Technical Information (OSTI.GOV)

Palmintier, Bryan; Hale, Elaine; Hansen, Timothy M.

This paper describes the Integrated Grid Modeling System (IGMS), a novel electric power system modeling platform for integrated transmission-distribution analysis that co-simulates off-the-shelf tools on high performance computing (HPC) platforms to offer unprecedented resolution from ISO markets down to appliances and other end uses. Specifically, the system simultaneously models hundreds or thousands of distribution systems in co-simulation with detailed Independent System Operator (ISO) markets and AGC-level reserve deployment. IGMS uses a new MPI-based hierarchical co-simulation framework to connect existing sub-domain models. Our initial efforts integrate opensource tools for wholesale markets (FESTIV), bulk AC power flow (MATPOWER), and full-featured distribution systemsmore » including physics-based end-use and distributed generation models (many instances of GridLAB-D[TM]). The modular IGMS framework enables tool substitution and additions for multi-domain analyses. This paper describes the IGMS tool, characterizes its performance, and demonstrates the impacts of the coupled simulations for analyzing high-penetration solar PV and price responsive load scenarios.« less

Automatic classification of animal vocalizations

NASA Astrophysics Data System (ADS)

Clemins, Patrick J.

2005-11-01

Bioacoustics, the study of animal vocalizations, has begun to use increasingly sophisticated analysis techniques in recent years. Some common tasks in bioacoustics are repertoire determination, call detection, individual identification, stress detection, and behavior correlation. Each research study, however, uses a wide variety of different measured variables, called features, and classification systems to accomplish these tasks. The well-established field of human speech processing has developed a number of different techniques to perform many of the aforementioned bioacoustics tasks. Melfrequency cepstral coefficients (MFCCs) and perceptual linear prediction (PLP) coefficients are two popular feature sets. The hidden Markov model (HMM), a statistical model similar to a finite autonoma machine, is the most commonly used supervised classification model and is capable of modeling both temporal and spectral variations. This research designs a framework that applies models from human speech processing for bioacoustic analysis tasks. The development of the generalized perceptual linear prediction (gPLP) feature extraction model is one of the more important novel contributions of the framework. Perceptual information from the species under study can be incorporated into the gPLP feature extraction model to represent the vocalizations as the animals might perceive them. By including this perceptual information and modifying parameters of the HMM classification system, this framework can be applied to a wide range of species. The effectiveness of the framework is shown by analyzing African elephant and beluga whale vocalizations. The features extracted from the African elephant data are used as input to a supervised classification system and compared to results from traditional statistical tests. The gPLP features extracted from the beluga whale data are used in an unsupervised classification system and the results are compared to labels assigned by experts. The development of a framework from which to build animal vocalization classifiers will provide bioacoustics researchers with a consistent platform to analyze and classify vocalizations. A common framework will also allow studies to compare results across species and institutions. In addition, the use of automated classification techniques can speed analysis and uncover behavioral correlations not readily apparent using traditional techniques.

Expertise, Task Complexity, and Artificial Intelligence: A Conceptual Framework.

ERIC Educational Resources Information Center

Buckland, Michael K.; Florian, Doris

1991-01-01

Examines the relationship between users' expertise, task complexity of information system use, and artificial intelligence to provide the basis for a conceptual framework for considering the role that artificial intelligence might play in information systems. Cognitive and conceptual models are discussed, and cost effectiveness is considered. (27…

Teaching to the Brain's Natural Learning Systems.

ERIC Educational Resources Information Center

Given, Barbara K.

This book investigates brain structures and functions of the brain's five major systems (emotional, social, cognitive, physical, and reflective), applying findings from neuro-biology to education. It translates neuroscience into an educational framework for lesson planning and teaching. This framework can serve as a mental model for an ongoing…

Using Evidence-Centered Design to Create a Special Educator Observation System

ERIC Educational Resources Information Center

Johnson, Evelyn S.; Crawford, Angela R.; Moylan, Laura A.; Zheng, Yuzhu

2018-01-01

The Evidence-Centered Design (ECD) framework was used to create a special education teacher observation system, Recognizing Effective Special Education Teachers (RESET). Extensive reviews of research informed the domain analysis and modeling stages, and led to the conceptual framework in which effective special education teaching is…

Modular System for Shelves and Coasts (MOSSCO v1.0) - a flexible and multi-component framework for coupled coastal ocean ecosystem modelling

NASA Astrophysics Data System (ADS)

Lemmen, Carsten; Hofmeister, Richard; Klingbeil, Knut; Hassan Nasermoaddeli, M.; Kerimoglu, Onur; Burchard, Hans; Kösters, Frank; Wirtz, Kai W.

2018-03-01

Shelf and coastal sea processes extend from the atmosphere through the water column and into the seabed. These processes reflect intimate interactions between physical, chemical, and biological states on multiple scales. As a consequence, coastal system modelling requires a high and flexible degree of process and domain integration; this has so far hardly been achieved by current model systems. The lack of modularity and flexibility in integrated models hinders the exchange of data and model components and has historically imposed the supremacy of specific physical driver models. We present the Modular System for Shelves and Coasts (MOSSCO; http://www.mossco.de), a novel domain and process coupling system tailored but not limited to the coupling challenges of and applications in the coastal ocean. MOSSCO builds on the Earth System Modeling Framework (ESMF) and on the Framework for Aquatic Biogeochemical Models (FABM). It goes beyond existing technologies by creating a unique level of modularity in both domain and process coupling, including a clear separation of component and basic model interfaces, flexible scheduling of several tens of models, and facilitation of iterative development at the lab and the station and on the coastal ocean scale. MOSSCO is rich in metadata and its concepts are also applicable outside the coastal domain. For coastal modelling, it contains dozens of example coupling configurations and tested set-ups for coupled applications. Thus, MOSSCO addresses the technology needs of a growing marine coastal Earth system community that encompasses very different disciplines, numerical tools, and research questions.

Ecosystem Services and Climate Change Considerations for ...

EPA Pesticide Factsheets

Freshwater habitats provide fishable, swimmable and drinkable resources and are a nexus of geophysical and biological processes. These processes in turn influence the persistence and sustainability of populations, communities and ecosystems. Climate change and landuse change encompass numerous stressors of potential exposure, including the introduction of toxic contaminants, invasive species, and disease in addition to physical drivers such as temperature and hydrologic regime. A systems approach that includes the scientific and technologic basis of assessing the health of ecosystems is needed to effectively protect human health and the environment. The Integrated Environmental Modeling Framework “iemWatersheds” has been developed as a consistent and coherent means of forecasting the cumulative impact of co-occurring stressors. The Framework consists of three facilitating technologies: Data for Environmental Modeling (D4EM) that automates the collection and standardization of input data; the Framework for Risk Assessment of Multimedia Environmental Systems (FRAMES) that manages the flow of information between linked models; and the Supercomputer for Model Uncertainty and Sensitivity Evaluation (SuperMUSE) that provides post-processing and analysis of model outputs, including uncertainty and sensitivity analysis. Five models are linked within the Framework to provide multimedia simulation capabilities for hydrology and water quality processes: the Soil Water

Modeling framework for representing long-term effectiveness of best management practices in addressing hydrology and water quality problems: Framework development and demonstration using a Bayesian method

NASA Astrophysics Data System (ADS)

Liu, Yaoze; Engel, Bernard A.; Flanagan, Dennis C.; Gitau, Margaret W.; McMillan, Sara K.; Chaubey, Indrajeet; Singh, Shweta

2018-05-01

Best management practices (BMPs) are popular approaches used to improve hydrology and water quality. Uncertainties in BMP effectiveness over time may result in overestimating long-term efficiency in watershed planning strategies. To represent varying long-term BMP effectiveness in hydrologic/water quality models, a high level and forward-looking modeling framework was developed. The components in the framework consist of establishment period efficiency, starting efficiency, efficiency for each storm event, efficiency between maintenance, and efficiency over the life cycle. Combined, they represent long-term efficiency for a specific type of practice and specific environmental concern (runoff/pollutant). An approach for possible implementation of the framework was discussed. The long-term impacts of grass buffer strips (agricultural BMP) and bioretention systems (urban BMP) in reducing total phosphorus were simulated to demonstrate the framework. Data gaps were captured in estimating the long-term performance of the BMPs. A Bayesian method was used to match the simulated distribution of long-term BMP efficiencies with the observed distribution with the assumption that the observed data represented long-term BMP efficiencies. The simulated distribution matched the observed distribution well with only small total predictive uncertainties. With additional data, the same method can be used to further improve the simulation results. The modeling framework and results of this study, which can be adopted in hydrologic/water quality models to better represent long-term BMP effectiveness, can help improve decision support systems for creating long-term stormwater management strategies for watershed management projects.

The Genome-based Knowledge Management in Cycles model: a complex adaptive systems framework for implementation of genomic applications.

PubMed

Arar, Nedal; Knight, Sara J; Modell, Stephen M; Issa, Amalia M

2011-03-01

The main mission of the Genomic Applications in Practice and Prevention Network™ is to advance collaborative efforts involving partners from across the public health sector to realize the promise of genomics in healthcare and disease prevention. We introduce a new framework that supports the Genomic Applications in Practice and Prevention Network mission and leverages the characteristics of the complex adaptive systems approach. We call this framework the Genome-based Knowledge Management in Cycles model (G-KNOMIC). G-KNOMIC proposes that the collaborative work of multidisciplinary teams utilizing genome-based applications will enhance translating evidence-based genomic findings by creating ongoing knowledge management cycles. Each cycle consists of knowledge synthesis, knowledge evaluation, knowledge implementation and knowledge utilization. Our framework acknowledges that all the elements in the knowledge translation process are interconnected and continuously changing. It also recognizes the importance of feedback loops, and the ability of teams to self-organize within a dynamic system. We demonstrate how this framework can be used to improve the adoption of genomic technologies into practice using two case studies of genomic uptake.

A system for environmental model coupling and code reuse: The Great Rivers Project

NASA Astrophysics Data System (ADS)

Eckman, B.; Rice, J.; Treinish, L.; Barford, C.

2008-12-01

As part of the Great Rivers Project, IBM is collaborating with The Nature Conservancy and the Center for Sustainability and the Global Environment (SAGE) at the University of Wisconsin, Madison to build a Modeling Framework and Decision Support System (DSS) designed to help policy makers and a variety of stakeholders (farmers, fish & wildlife managers, hydropower operators, et al.) to assess, come to consensus, and act on land use decisions representing effective compromises between human use and ecosystem preservation/restoration. Initially focused on Brazil's Paraguay-Parana, China's Yangtze, and the Mississippi Basin in the US, the DSS integrates data and models from a wide variety of environmental sectors, including water balance, water quality, carbon balance, crop production, hydropower, and biodiversity. In this presentation we focus on the modeling framework aspect of this project. In our approach to these and other environmental modeling projects, we see a flexible, extensible modeling framework infrastructure for defining and running multi-step analytic simulations as critical. In this framework, we divide monolithic models into atomic components with clearly defined semantics encoded via rich metadata representation. Once models and their semantics and composition rules have been registered with the system by their authors or other experts, non-expert users may construct simulations as workflows of these atomic model components. A model composition engine enforces rules/constraints for composing model components into simulations, to avoid the creation of Frankenmodels, models that execute but produce scientifically invalid results. A common software environment and common representations of data and models are required, as well as an adapter strategy for code written in e.g., Fortran or python, that still enables efficient simulation runs, including parallelization. Since each new simulation, as a new composition of model components, requires calibration of parameters (fudge factors) to produce scientifically valid results, we are also developing an autocalibration engine. Finally, visualization is a key element of this modeling framework strategy, both to convey complex scientific data effectively, and also to enable non-expert users to make full use of the relevant features of the framework. We are developing a visualization environment with a strong data model, to enable visualizations, model results, and data all to be handled similarly.

Framework for Architecture Trade Study Using MBSE and Performance Simulation

NASA Technical Reports Server (NTRS)

Ryan, Jessica; Sarkani, Shahram; Mazzuchim, Thomas

2012-01-01

Increasing complexity in modern systems as well as cost and schedule constraints require a new paradigm of system engineering to fulfill stakeholder needs. Challenges facing efficient trade studies include poor tool interoperability, lack of simulation coordination (design parameters) and requirements flowdown. A recent trend toward Model Based System Engineering (MBSE) includes flexible architecture definition, program documentation, requirements traceability and system engineering reuse. As a new domain MBSE still lacks governing standards and commonly accepted frameworks. This paper proposes a framework for efficient architecture definition using MBSE in conjunction with Domain Specific simulation to evaluate trade studies. A general framework is provided followed with a specific example including a method for designing a trade study, defining candidate architectures, planning simulations to fulfill requirements and finally a weighted decision analysis to optimize system objectives.

Ontological Problem-Solving Framework for Dynamically Configuring Sensor Systems and Algorithms

PubMed Central

Qualls, Joseph; Russomanno, David J.

2011-01-01

The deployment of ubiquitous sensor systems and algorithms has led to many challenges, such as matching sensor systems to compatible algorithms which are capable of satisfying a task. Compounding the challenges is the lack of the requisite knowledge models needed to discover sensors and algorithms and to subsequently integrate their capabilities to satisfy a specific task. A novel ontological problem-solving framework has been designed to match sensors to compatible algorithms to form synthesized systems, which are capable of satisfying a task and then assigning the synthesized systems to high-level missions. The approach designed for the ontological problem-solving framework has been instantiated in the context of a persistence surveillance prototype environment, which includes profiling sensor systems and algorithms to demonstrate proof-of-concept principles. Even though the problem-solving approach was instantiated with profiling sensor systems and algorithms, the ontological framework may be useful with other heterogeneous sensing-system environments. PMID:22163793

A coupled modeling framework for sustainable watershed management in transboundary river basins

NASA Astrophysics Data System (ADS)

Furqan Khan, Hassaan; Yang, Y. C. Ethan; Xie, Hua; Ringler, Claudia

2017-12-01

There is a growing recognition among water resource managers that sustainable watershed management needs to not only account for the diverse ways humans benefit from the environment, but also incorporate the impact of human actions on the natural system. Coupled natural-human system modeling through explicit modeling of both natural and human behavior can help reveal the reciprocal interactions and co-evolution of the natural and human systems. This study develops a spatially scalable, generalized agent-based modeling (ABM) framework consisting of a process-based semi-distributed hydrologic model (SWAT) and a decentralized water system model to simulate the impacts of water resource management decisions that affect the food-water-energy-environment (FWEE) nexus at a watershed scale. Agents within a river basin are geographically delineated based on both political and watershed boundaries and represent key stakeholders of ecosystem services. Agents decide about the priority across three primary water uses: food production, hydropower generation and ecosystem health within their geographical domains. Agents interact with the environment (streamflow) through the SWAT model and interact with other agents through a parameter representing willingness to cooperate. The innovative two-way coupling between the water system model and SWAT enables this framework to fully explore the feedback of human decisions on the environmental dynamics and vice versa. To support non-technical stakeholder interactions, a web-based user interface has been developed that allows for role-play and participatory modeling. The generalized ABM framework is also tested in two key transboundary river basins, the Mekong River basin in Southeast Asia and the Niger River basin in West Africa, where water uses for ecosystem health compete with growing human demands on food and energy resources. We present modeling results for crop production, energy generation and violation of eco-hydrological indicators at both the agent and basin-wide levels to shed light on holistic FWEE management policies in these two basins.

Water and Power Systems Co-optimization under a High Performance Computing Framework

NASA Astrophysics Data System (ADS)

Xuan, Y.; Arumugam, S.; DeCarolis, J.; Mahinthakumar, K.

2016-12-01

Water and energy systems optimizations are traditionally being treated as two separate processes, despite their intrinsic interconnections (e.g., water is used for hydropower generation, and thermoelectric cooling requires a large amount of water withdrawal). Given the challenges of urbanization, technology uncertainty and resource constraints, and the imminent threat of climate change, a cyberinfrastructure is needed to facilitate and expedite research into the complex management of these two systems. To address these issues, we developed a High Performance Computing (HPC) framework for stochastic co-optimization of water and energy resources to inform water allocation and electricity demand. The project aims to improve conjunctive management of water and power systems under climate change by incorporating improved ensemble forecast models of streamflow and power demand. First, by downscaling and spatio-temporally disaggregating multimodel climate forecasts from General Circulation Models (GCMs), temperature and precipitation forecasts are obtained and input into multi-reservoir and power systems models. Extended from Optimus (Optimization Methods for Universal Simulators), the framework drives the multi-reservoir model and power system model, Temoa (Tools for Energy Model Optimization and Analysis), and uses Particle Swarm Optimization (PSO) algorithm to solve high dimensional stochastic problems. The utility of climate forecasts on the cost of water and power systems operations is assessed and quantified based on different forecast scenarios (i.e., no-forecast, multimodel forecast and perfect forecast). Analysis of risk management actions and renewable energy deployments will be investigated for the Catawba River basin, an area with adequate hydroclimate predicting skill and a critical basin with 11 reservoirs that supplies water and generates power for both North and South Carolina. Further research using this scalable decision supporting framework will provide understanding and elucidate the intricate and interdependent relationship between water and energy systems and enhance the security of these two critical public infrastructures.

Comparison of L-system applications towards plant modelling, music rendering and score generation using visual language programming

NASA Astrophysics Data System (ADS)

Lim, Chen Kim; Tan, Kian Lam; Yusran, Hazwanni; Suppramaniam, Vicknesh

2017-10-01

Visual language or visual representation has been used in the past few years in order to express the knowledge in graphic. One of the important graphical elements is fractal and L-Systems is a mathematic-based grammatical model for modelling cell development and plant topology. From the plant model, L-Systems can be interpreted as music sound and score. In this paper, LSound which is a Visual Language Programming (VLP) framework has been developed to model plant to music sound and generate music score and vice versa. The objectives of this research has three folds: (i) To expand the grammar dictionary of L-Systems music based on visual programming, (ii) To design and produce a user-friendly and icon based visual language framework typically for L-Systems musical score generation which helps the basic learners in musical field and (iii) To generate music score from plant models and vice versa using L-Systems method. This research undergoes a four phases methodology where the plant is first modelled, then the music is interpreted, followed by the output of music sound through MIDI and finally score is generated. LSound is technically compared to other existing applications in the aspects of the capability of modelling the plant, rendering the music and generating the sound. It has been found that LSound is a flexible framework in which the plant can be easily altered through arrow-based programming and the music score can be altered through the music symbols and notes. This work encourages non-experts to understand L-Systems and music hand-in-hand.

Information-Theoretic Approach May Shed a Light to a Better Understanding and Sustaining the Integrity of Ecological-Societal Systems under Changing Climate

NASA Astrophysics Data System (ADS)

Kim, J.

2016-12-01

Considering high levels of uncertainty, epistemological conflicts over facts and values, and a sense of urgency, normal paradigm-driven science will be insufficient to mobilize people and nation toward sustainability. The conceptual framework to bridge the societal system dynamics with that of natural ecosystems in which humanity operates remains deficient. The key to understanding their coevolution is to understand `self-organization.' Information-theoretic approach may shed a light to provide a potential framework which enables not only to bridge human and nature but also to generate useful knowledge for understanding and sustaining the integrity of ecological-societal systems. How can information theory help understand the interface between ecological systems and social systems? How to delineate self-organizing processes and ensure them to fulfil sustainability? How to evaluate the flow of information from data through models to decision-makers? These are the core questions posed by sustainability science in which visioneering (i.e., the engineering of vision) is an essential framework. Yet, visioneering has neither quantitative measure nor information theoretic framework to work with and teach. This presentation is an attempt to accommodate the framework of self-organizing hierarchical open systems with visioneering into a common information-theoretic framework. A case study is presented with the UN/FAO's communal vision of climate-smart agriculture (CSA) which pursues a trilemma of efficiency, mitigation, and resilience. Challenges of delineating and facilitating self-organizing systems are discussed using transdisciplinary toold such as complex systems thinking, dynamic process network analysis and multi-agent systems modeling. Acknowledgments: This study was supported by the Korea Meteorological Administration Research and Development Program under Grant KMA-2012-0001-A (WISE project).

System analysis through bond graph modeling

NASA Astrophysics Data System (ADS)

McBride, Robert Thomas

2005-07-01

Modeling and simulation form an integral role in the engineering design process. An accurate mathematical description of a system provides the design engineer the flexibility to perform trade studies quickly and accurately to expedite the design process. Most often, the mathematical model of the system contains components of different engineering disciplines. A modeling methodology that can handle these types of systems might be used in an indirect fashion to extract added information from the model. This research examines the ability of a modeling methodology to provide added insight into system analysis and design. The modeling methodology used is bond graph modeling. An investigation into the creation of a bond graph model using the Lagrangian of the system is provided. Upon creation of the bond graph, system analysis is performed. To aid in the system analysis, an object-oriented approach to bond graph modeling is introduced. A framework is provided to simulate the bond graph directly. Through object-oriented simulation of a bond graph, the information contained within the bond graph can be exploited to create a measurement of system efficiency. A definition of system efficiency is given. This measurement of efficiency is used in the design of different controllers of varying architectures. Optimal control of a missile autopilot is discussed within the framework of the calculated system efficiency.

Distributed parallel computing in stochastic modeling of groundwater systems.

PubMed

Dong, Yanhui; Li, Guomin; Xu, Haizhen

2013-03-01

Stochastic modeling is a rapidly evolving, popular approach to the study of the uncertainty and heterogeneity of groundwater systems. However, the use of Monte Carlo-type simulations to solve practical groundwater problems often encounters computational bottlenecks that hinder the acquisition of meaningful results. To improve the computational efficiency, a system that combines stochastic model generation with MODFLOW-related programs and distributed parallel processing is investigated. The distributed computing framework, called the Java Parallel Processing Framework, is integrated into the system to allow the batch processing of stochastic models in distributed and parallel systems. As an example, the system is applied to the stochastic delineation of well capture zones in the Pinggu Basin in Beijing. Through the use of 50 processing threads on a cluster with 10 multicore nodes, the execution times of 500 realizations are reduced to 3% compared with those of a serial execution. Through this application, the system demonstrates its potential in solving difficult computational problems in practical stochastic modeling. © 2012, The Author(s). Groundwater © 2012, National Ground Water Association.

A geographic data model for representing ground water systems.

PubMed

Strassberg, Gil; Maidment, David R; Jones, Norm L

2007-01-01

The Arc Hydro ground water data model is a geographic data model for representing spatial and temporal ground water information within a geographic information system (GIS). The data model is a standardized representation of ground water systems within a spatial database that provides a public domain template for GIS users to store, document, and analyze commonly used spatial and temporal ground water data sets. This paper describes the data model framework, a simplified version of the complete ground water data model that includes two-dimensional and three-dimensional (3D) object classes for representing aquifers, wells, and borehole data, and the 3D geospatial context in which these data exist. The framework data model also includes tabular objects for representing temporal information such as water levels and water quality samples that are related with spatial features.

Software Engineering Support of the Third Round of Scientific Grand Challenge Investigations: An Earth Modeling System Software Framework Strawman Design that Integrates Cactus and UCLA/UCB Distributed Data Broker

NASA Technical Reports Server (NTRS)

Talbot, Bryan; Zhou, Shu-Jia; Higgins, Glenn

2002-01-01

One of the most significant challenges in large-scale climate modeling, as well as in high-performance computing in other scientific fields, is that of effectively integrating many software models from multiple contributors. A software framework facilitates the integration task. both in the development and runtime stages of the simulation. Effective software frameworks reduce the programming burden for the investigators, freeing them to focus more on the science and less on the parallel communication implementation, while maintaining high performance across numerous supercomputer and workstation architectures. This document proposes a strawman framework design for the climate community based on the integration of Cactus, from the relativistic physics community, and UCLA/UCB Distributed Data Broker (DDB) from the climate community. This design is the result of an extensive survey of climate models and frameworks in the climate community as well as frameworks from many other scientific communities. The design addresses fundamental development and runtime needs using Cactus, a framework with interfaces for FORTRAN and C-based languages, and high-performance model communication needs using DDB. This document also specifically explores object-oriented design issues in the context of climate modeling as well as climate modeling issues in terms of object-oriented design.

Fully Associative, Nonisothermal, Potential-Based Unified Viscoplastic Model for Titanium-Based Matrices

NASA Technical Reports Server (NTRS)

2005-01-01

A number of titanium matrix composite (TMC) systems are currently being investigated for high-temperature air frame and propulsion system applications. As a result, numerous computational methodologies for predicting both deformation and life for this class of materials are under development. An integral part of these methodologies is an accurate and computationally efficient constitutive model for the metallic matrix constituent. Furthermore, because these systems are designed to operate at elevated temperatures, the required constitutive models must account for both time-dependent and time-independent deformations. To accomplish this, the NASA Lewis Research Center is employing a recently developed, complete, potential-based framework. This framework, which utilizes internal state variables, was put forth for the derivation of reversible and irreversible constitutive equations. The framework, and consequently the resulting constitutive model, is termed complete because the existence of the total (integrated) form of the Gibbs complementary free energy and complementary dissipation potentials are assumed a priori. The specific forms selected here for both the Gibbs and complementary dissipation potentials result in a fully associative, multiaxial, nonisothermal, unified viscoplastic model with nonlinear kinematic hardening. This model constitutes one of many models in the Generalized Viscoplasticity with Potential Structure (GVIPS) class of inelastic constitutive equations.

Modelling Spread of Oncolytic Viruses in Heterogeneous Cell Populations

NASA Astrophysics Data System (ADS)

Ellis, Michael; Dobrovolny, Hana

2014-03-01

One of the most promising areas in current cancer research and treatment is the use of viruses to attack cancer cells. A number of oncolytic viruses have been identified to date that possess the ability to destroy or neutralize cancer cells while inflicting minimal damage upon healthy cells. Formulation of predictive models that correctly describe the evolution of infected tumor systems is critical to the successful application of oncolytic virus therapy. A number of different models have been proposed for analysis of the oncolytic virus-infected tumor system, with approaches ranging from traditional coupled differential equations such as the Lotka-Volterra predator-prey models, to contemporary modeling frameworks based on neural networks and cellular automata. Existing models are focused on tumor cells and the effects of virus infection, and offer the potential for improvement by including effects upon normal cells. We have recently extended the traditional framework to a 2-cell model addressing the full cellular system including tumor cells, normal cells, and the impacts of viral infection upon both populations. Analysis of the new framework reveals complex interaction between the populations and potential inability to simultaneously eliminate the virus and tumor populations.

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.

Measures and Metrics of Information Processing in Complex Systems: A Rope of Sand

ERIC Educational Resources Information Center

James, Ryan Gregory

2013-01-01

How much information do natural systems store and process? In this work we attempt to answer this question in multiple ways. We first establish a mathematical framework where natural systems are represented by a canonical form of edge-labeled hidden fc models called e-machines. Then, utilizing this framework, a variety of measures are defined and…

The Development of a Framework for and a Model Teaching-Learning System in Electronics Technology for the Elementary School.

ERIC Educational Resources Information Center

Inaba, Lawrence Akio

Developing a rationale and a structure of knowledge as the basis for an instructional system in electronics technology and designing and developing a packaged instructional system in electronics technology for the sixth grade is the two-fold purpose of this study. The study identifies electronics technology within the broad framework of industrial…

Nemesis Autonomous Test System

NASA Technical Reports Server (NTRS)

Barltrop, Kevin J.; Lee, Cin-Young; Horvath, Gregory A,; Clement, Bradley J.

2012-01-01

A generalized framework has been developed for systems validation that can be applied to both traditional and autonomous systems. The framework consists of an automated test case generation and execution system called Nemesis that rapidly and thoroughly identifies flaws or vulnerabilities within a system. By applying genetic optimization and goal-seeking algorithms on the test equipment side, a "war game" is conducted between a system and its complementary nemesis. The end result of the war games is a collection of scenarios that reveals any undesirable behaviors of the system under test. The software provides a reusable framework to evolve test scenarios using genetic algorithms using an operation model of the system under test. It can automatically generate and execute test cases that reveal flaws in behaviorally complex systems. Genetic algorithms focus the exploration of tests on the set of test cases that most effectively reveals the flaws and vulnerabilities of the system under test. It leverages advances in state- and model-based engineering, which are essential in defining the behavior of autonomous systems. It also uses goal networks to describe test scenarios.

Amelie: A Recombinant Computing Framework for Ambient Awareness

NASA Astrophysics Data System (ADS)

Metaxas, Georgios; Markopoulos, Panos; Aarts, Emile

This paper presents Amelie, a service oriented framework that supports the implementation of awareness systems. Amelie adopts the tenets of Recombinant computing to address an important non-functional requirement for Ambient Intelligence software, namely the heterogeneous combination of services and components. Amelie is founded upon FN-AAR an abstract model of Awareness Systems which enables the immediate expression and implementation of socially salient requirements, such as symmetry and social translucence. We discuss the framework and show how system behaviours can be specified using the Awareness Mark-up Language AML.

Dshell++: A Component Based, Reusable Space System Simulation Framework

NASA Technical Reports Server (NTRS)

Lim, Christopher S.; Jain, Abhinandan

2009-01-01

This paper describes the multi-mission Dshell++ simulation framework for high fidelity, physics-based simulation of spacecraft, robotic manipulation and mobility systems. Dshell++ is a C++/Python library which uses modern script driven object-oriented techniques to allow component reuse and a dynamic run-time interface for complex, high-fidelity simulation of spacecraft and robotic systems. The goal of the Dshell++ architecture is to manage the inherent complexity of physicsbased simulations while supporting component model reuse across missions. The framework provides several features that support a large degree of simulation configurability and usability.

Using Uncertainty Quantification to Guide Development and Improvements of a Regional-Scale Model of the Coastal Lowlands Aquifer System Spanning Texas, Louisiana, Mississippi, Alabama and Florida

NASA Astrophysics Data System (ADS)

Foster, L. K.; Clark, B. R.; Duncan, L. L.; Tebo, D. T.; White, J.

2017-12-01

Several historical groundwater models exist within the Coastal Lowlands Aquifer System (CLAS), which spans the Gulf Coastal Plain in Texas, Louisiana, Mississippi, Alabama, and Florida. The largest of these models, called the Gulf Coast Regional Aquifer System Analysis (RASA) model, has been brought into a new framework using the Newton formulation for MODFLOW-2005 (MODFLOW-NWT) and serves as the starting point of a new investigation underway by the U.S. Geological Survey to improve understanding of the CLAS and provide predictions of future groundwater availability within an uncertainty quantification (UQ) framework. The use of an UQ framework will not only provide estimates of water-level observation worth, hydraulic parameter uncertainty, boundary-condition uncertainty, and uncertainty of future potential predictions, but it will also guide the model development process. Traditionally, model development proceeds from dataset construction to the process of deterministic history matching, followed by deterministic predictions using the model. This investigation will combine the use of UQ with existing historical models of the study area to assess in a quantitative framework the effect model package and property improvements have on the ability to represent past-system states, as well as the effect on the model's ability to make certain predictions of water levels, water budgets, and base-flow estimates. Estimates of hydraulic property information and boundary conditions from the existing models and literature, forming the prior, will be used to make initial estimates of model forecasts and their corresponding uncertainty, along with an uncalibrated groundwater model run within an unconstrained Monte Carlo analysis. First-Order Second-Moment (FOSM) analysis will also be used to investigate parameter and predictive uncertainty, and guide next steps in model development prior to rigorous history matching by using PEST++ parameter estimation code.

Reconstructing Mammalian Sleep Dynamics with Data Assimilation

PubMed Central

Sedigh-Sarvestani, Madineh; Schiff, Steven J.; Gluckman, Bruce J.

2012-01-01

Data assimilation is a valuable tool in the study of any complex system, where measurements are incomplete, uncertain, or both. It enables the user to take advantage of all available information including experimental measurements and short-term model forecasts of a system. Although data assimilation has been used to study other biological systems, the study of the sleep-wake regulatory network has yet to benefit from this toolset. We present a data assimilation framework based on the unscented Kalman filter (UKF) for combining sparse measurements together with a relatively high-dimensional nonlinear computational model to estimate the state of a model of the sleep-wake regulatory system. We demonstrate with simulation studies that a few noisy variables can be used to accurately reconstruct the remaining hidden variables. We introduce a metric for ranking relative partial observability of computational models, within the UKF framework, that allows us to choose the optimal variables for measurement and also provides a methodology for optimizing framework parameters such as UKF covariance inflation. In addition, we demonstrate a parameter estimation method that allows us to track non-stationary model parameters and accommodate slow dynamics not included in the UKF filter model. Finally, we show that we can even use observed discretized sleep-state, which is not one of the model variables, to reconstruct model state and estimate unknown parameters. Sleep is implicated in many neurological disorders from epilepsy to schizophrenia, but simultaneous observation of the many brain components that regulate this behavior is difficult. We anticipate that this data assimilation framework will enable better understanding of the detailed interactions governing sleep and wake behavior and provide for better, more targeted, therapies. PMID:23209396

Surface Pressure Dependencies in the GEOS-Chem-Adjoint System and the Impact of the GEOS-5 Surface Pressure on CO2 Model Forecast

NASA Technical Reports Server (NTRS)

Lee, Meemong; Weidner, Richard

2016-01-01

In the GEOS-Chem Adjoint (GCA) system, the total (wet) surface pressure of the GEOS meteorology is employed as dry surface pressure, ignoring the presence of water vapor. The Jet Propulsion Laboratory (JPL) Carbon Monitoring System (CMS) research team has been evaluating the impact of the above discrepancy on the CO2 model forecast and the CO2 flux inversion. The JPL CMS research utilizes a multi-mission assimilation framework developed by the Multi-Mission Observation Operator (M2O2) research team at JPL extending the GCA system. The GCA-M2O2 framework facilitates mission-generic 3D and 4D-variational assimilations streamlining the interfaces to the satellite data products and prior emission inventories. The GCA-M2O2 framework currently integrates the GCA system version 35h and provides a dry surface pressure setup to allow the CO2 model forecast to be performed with the GEOS-5 surface pressure directly or after converting it to dry surface pressure.

Surface Pressure Dependencies in the Geos-Chem-Adjoint System and the Impact of the GEOS-5 Surface Pressure on CO2 Model Forecast

NASA Technical Reports Server (NTRS)

Lee, Meemong; Weidner, Richard

2016-01-01

In the GEOS-Chem Adjoint (GCA) system, the total (wet) surface pressure of the GEOS meteorology is employed as dry surface pressure, ignoring the presence of water vapor. The Jet Propulsion Laboratory (JPL) Carbon Monitoring System (CMS) research team has been evaluating the impact of the above discrepancy on the CO2 model forecast and the CO2 flux inversion. The JPL CMS research utilizes a multi-mission assimilation framework developed by the Multi-Mission Observation Operator (M2O2) research team at JPL extending the GCA system. The GCA-M2O2 framework facilitates mission-generic 3D and 4D-variational assimilations streamlining the interfaces to the satellite data products and prior emission inventories. The GCA-M2O2 framework currently integrates the GCA system version 35h and provides a dry surface pressure setup to allow the CO2 model forecast to be performed with the GEOS-5 surface pressure directly or after converting it to dry surface pressure.

An Illustrative Guide to the Minerva Framework

NASA Astrophysics Data System (ADS)

Flom, Erik; Leonard, Patrick; Hoeffel, Udo; Kwak, Sehyun; Pavone, Andrea; Svensson, Jakob; Krychowiak, Maciej; Wendelstein 7-X Team Collaboration

2017-10-01

Modern phsyics experiments require tracking and modelling data and their associated uncertainties on a large scale, as well as the combined implementation of multiple independent data streams for sophisticated modelling and analysis. The Minerva Framework offers a centralized, user-friendly method of large-scale physics modelling and scientific inference. Currently used by teams at multiple large-scale fusion experiments including the Joint European Torus (JET) and Wendelstein 7-X (W7-X), the Minerva framework provides a forward-model friendly architecture for developing and implementing models for large-scale experiments. One aspect of the framework involves so-called data sources, which are nodes in the graphical model. These nodes are supplied with engineering and physics parameters. When end-user level code calls a node, it is checked network-wide against its dependent nodes for changes since its last implementation and returns version-specific data. Here, a filterscope data node is used as an illustrative example of the Minerva Framework's data management structure and its further application to Bayesian modelling of complex systems. This work has been carried out within the framework of the EUROfusion Consortium and has received funding from the Euratom research and training programme 2014-2018 under Grant Agreement No. 633053.

An Efficient Model-based Diagnosis Engine for Hybrid Systems Using Structural Model Decomposition

NASA Technical Reports Server (NTRS)

Bregon, Anibal; Narasimhan, Sriram; Roychoudhury, Indranil; Daigle, Matthew; Pulido, Belarmino

2013-01-01

Complex hybrid systems are present in a large range of engineering applications, like mechanical systems, electrical circuits, or embedded computation systems. The behavior of these systems is made up of continuous and discrete event dynamics that increase the difficulties for accurate and timely online fault diagnosis. The Hybrid Diagnosis Engine (HyDE) offers flexibility to the diagnosis application designer to choose the modeling paradigm and the reasoning algorithms. The HyDE architecture supports the use of multiple modeling paradigms at the component and system level. However, HyDE faces some problems regarding performance in terms of complexity and time. Our focus in this paper is on developing efficient model-based methodologies for online fault diagnosis in complex hybrid systems. To do this, we propose a diagnosis framework where structural model decomposition is integrated within the HyDE diagnosis framework to reduce the computational complexity associated with the fault diagnosis of hybrid systems. As a case study, we apply our approach to a diagnostic testbed, the Advanced Diagnostics and Prognostics Testbed (ADAPT), using real data.

The Parallel System for Integrating Impact Models and Sectors (pSIMS)

NASA Technical Reports Server (NTRS)

Elliott, Joshua; Kelly, David; Chryssanthacopoulos, James; Glotter, Michael; Jhunjhnuwala, Kanika; Best, Neil; Wilde, Michael; Foster, Ian

2014-01-01

We present a framework for massively parallel climate impact simulations: the parallel System for Integrating Impact Models and Sectors (pSIMS). This framework comprises a) tools for ingesting and converting large amounts of data to a versatile datatype based on a common geospatial grid; b) tools for translating this datatype into custom formats for site-based models; c) a scalable parallel framework for performing large ensemble simulations, using any one of a number of different impacts models, on clusters, supercomputers, distributed grids, or clouds; d) tools and data standards for reformatting outputs to common datatypes for analysis and visualization; and e) methodologies for aggregating these datatypes to arbitrary spatial scales such as administrative and environmental demarcations. By automating many time-consuming and error-prone aspects of large-scale climate impacts studies, pSIMS accelerates computational research, encourages model intercomparison, and enhances reproducibility of simulation results. We present the pSIMS design and use example assessments to demonstrate its multi-model, multi-scale, and multi-sector versatility.

Validation of the SWMF Magnetosphere: Fields and Particles

NASA Astrophysics Data System (ADS)

Welling, D. T.; Ridley, A. J.

2009-05-01

The Space Weather Modeling Framework has been developed at the University of Michigan to allow many independent space environment numerical models to be executed simultaneously and coupled together to create a more accurate, all-encompassing system. This work explores the capabilities of the framework when using the BATS-R-US MHD code, Rice Convection Model (RCM), the Ridley Ionosphere Model (RIM), and the Polar Wind Outflow Model (PWOM). Ten space weather events, ranging from quiet to extremely stormy periods, are modeled by the framework. All simulations are executed in a manner that mimics an operational environment where fewer resources are available and predictions are required in a timely manner. The results are compared against in-situ measurements of magnetic fields from GOES, Polar, Geotail, and Cluster satellites as well as MPA particle measurements from the LANL geosynchronous spacecraft. Various metrics are calculated to quantify performance. Results when using only two to all four components are compared to evaluate the increase in performance as new physics are included in the system.

Automatising the analysis of stochastic biochemical time-series

PubMed Central

2015-01-01

Background Mathematical and computational modelling of biochemical systems has seen a lot of effort devoted to the definition and implementation of high-performance mechanistic simulation frameworks. Within these frameworks it is possible to analyse complex models under a variety of configurations, eventually selecting the best setting of, e.g., parameters for a target system. Motivation This operational pipeline relies on the ability to interpret the predictions of a model, often represented as simulation time-series. Thus, an efficient data analysis pipeline is crucial to automatise time-series analyses, bearing in mind that errors in this phase might mislead the modeller's conclusions. Results For this reason we have developed an intuitive framework-independent Python tool to automate analyses common to a variety of modelling approaches. These include assessment of useful non-trivial statistics for simulation ensembles, e.g., estimation of master equations. Intuitive and domain-independent batch scripts will allow the researcher to automatically prepare reports, thus speeding up the usual model-definition, testing and refinement pipeline. PMID:26051821

Framework programmable platform for the advanced software development workstation. Integration mechanism design document

NASA Technical Reports Server (NTRS)

Mayer, Richard J.; Blinn, Thomas M.; Mayer, Paula S. D.; Reddy, Uday; Ackley, Keith; Futrell, Mike

1991-01-01

The Framework Programmable Software Development Platform (FPP) is a project aimed at combining effective tool and data integration mechanisms with a model of the software development process in an intelligent integrated software development environment. Guided by this model, this system development framework will take advantage of an integrated operating environment to automate effectively the management of the software development process so that costly mistakes during the development phase can be eliminated.

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

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.

Modeling of Water-Breathing Propulsion Systems Utilizing the Aluminum-Seawater Reaction and Solid-Oxide Fuel Cells

DTIC Science & Technology

2011-01-01

ABSTRACT Title of Document: MODELING OF WATER-BREATHING PROPULSION SYSTEMS UTILIZING THE ALUMINUM-SEAWATER REACTION AND SOLID...Hybrid Aluminum Combustor (HAC): a novel underwater power system based on the exothermic reaction of aluminum with seawater. The system is modeled ...using a NASA-developed framework called Numerical Propulsion System Simulation (NPSS) by assembling thermodynamic models developed for each component

Care delivery for Filipino Americans using the Neuman systems model.

PubMed

Angosta, Alona D; Ceria-Ulep, Clementina D; Tse, Alice M

2014-04-01

Filipino Americans are at risk of coronary heart disease due to the presence of multiple cardiometabolic factors. Selecting a framework that addresses the factors leading to coronary heart disease is vital when providing care for this population. The Neuman systems model is a comprehensive and wholistic framework that offers an innovative method of viewing clients, their families, and the healthcare system across multiple dimensions. Using the Neuman systems model, advanced practice nurses can develop and implement interventions that will help reduce the potential cardiovascular problems of clients with multiple risk factors. The authors in this article provides insight into the cardiovascular health of Filipino Americans and has implications for nurses and other healthcare providers working with various Southeast Asian groups in the United States.

A FEniCS-based programming framework for modeling turbulent flow by the Reynolds-averaged Navier-Stokes equations

NASA Astrophysics Data System (ADS)

Mortensen, Mikael; Langtangen, Hans Petter; Wells, Garth N.

2011-09-01

Finding an appropriate turbulence model for a given flow case usually calls for extensive experimentation with both models and numerical solution methods. This work presents the design and implementation of a flexible, programmable software framework for assisting with numerical experiments in computational turbulence. The framework targets Reynolds-averaged Navier-Stokes models, discretized by finite element methods. The novel implementation makes use of Python and the FEniCS package, the combination of which leads to compact and reusable code, where model- and solver-specific code resemble closely the mathematical formulation of equations and algorithms. The presented ideas and programming techniques are also applicable to other fields that involve systems of nonlinear partial differential equations. We demonstrate the framework in two applications and investigate the impact of various linearizations on the convergence properties of nonlinear solvers for a Reynolds-averaged Navier-Stokes model.

Whole systems shared governance: a model for the integrated health system.

PubMed

Evan, K; Aubry, K; Hawkins, M; Curley, T A; Porter-O'Grady, T

1995-05-01

The healthcare system is under renovation and renewal. In the process, roles and structures are shifting to support a subscriber-based continuum of care. Alliances and partnerships are emerging as the models of integration for the future. But how do we structure to support these emerging integrated partnerships? As the nurse executive expands the role and assumes increasing responsibility for creating new frameworks for care, a structure that sustains the point-of-care innovations and interdisciplinary relationships must be built. Whole systems models of organization, such as shared governance, are expanding as demand grows for a sustainable structure for horizontal and partnered systems of healthcare delivery. The executive will have to apply these newer frameworks to the delivery of care to provide adequate support for the clinically integrated environment.

CEOS SEO and GISS Meeting

NASA Technical Reports Server (NTRS)

Killough, Brian; Stover, Shelley

2008-01-01

The Committee on Earth Observation Satellites (CEOS) provides a brief to the Goddard Institute for Space Studies (GISS) regarding the CEOS Systems Engineering Office (SEO) and current work on climate requirements and analysis. A "system framework" is provided for the Global Earth Observation System of Systems (GEOSS). SEO climate-related tasks are outlined including the assessment of essential climate variable (ECV) parameters, use of the "systems framework" to determine relevant informational products and science models and the performance of assessments and gap analyses of measurements and missions for each ECV. Climate requirements, including instruments and missions, measurements, knowledge and models, and decision makers, are also outlined. These requirements would establish traceability from instruments to products and services allowing for benefit evaluation of instruments and measurements. Additionally, traceable climate requirements would provide a better understanding of global climate models.

Framework for modelling the cost-effectiveness of systemic interventions aimed to reduce youth delinquency.

PubMed

Schawo, Saskia J; van Eeren, Hester; Soeteman, Djira I; van der Veldt, Marie-Christine; Noom, Marc J; Brouwer, Werner; Busschbach, Jan J V; Hakkaart, Leona

2012-12-01

Many interventions initiated within and financed from the health care sector are not necessarily primarily aimed at improving health. This poses important questions regarding the operationalisation of economic evaluations in such contexts. We investigated whether assessing cost-effectiveness using state-of-the-art methods commonly applied in health care evaluations is feasible and meaningful when evaluating interventions aimed at reducing youth delinquency. A probabilistic Markov model was constructed to create a framework for the assessment of the cost-effectiveness of systemic interventions in delinquent youth. For illustrative purposes, Functional Family Therapy (FFT), a systemic intervention aimed at improving family functioning and, primarily, reducing delinquent activity in youths, was compared to Treatment as Usual (TAU). "Criminal activity free years" (CAFYs) were introduced as central outcome measure. Criminal activity may e.g. be based on police contacts or committed crimes. In absence of extensive data and for illustrative purposes the current study based criminal activity on available literature on recidivism. Furthermore, a literature search was performed to deduce the model's structure and parameters. Common cost-effectiveness methodology could be applied to interventions for youth delinquency. Model characteristics and parameters were derived from literature and ongoing trial data. The model resulted in an estimate of incremental costs/CAFY and included long-term effects. Illustrative model results point towards dominance of FFT compared to TAU. Using a probabilistic model and the CAFY outcome measure to assess cost-effectiveness of systemic interventions aimed to reduce delinquency is feasible. However, the model structure is limited to three states and the CAFY measure was defined rather crude. Moreover, as the model parameters are retrieved from literature the model results are illustrative in the absence of empirical data. The current model provides a framework to assess the cost-effectiveness of systemic interventions, while taking into account parameter uncertainty and long-term effectiveness. The framework of the model could be used to assess the cost-effectiveness of systemic interventions alongside (clinical) trial data. Consequently, it is suitable to inform reimbursement decisions, since the value for money of systemic interventions can be demonstrated using a decision analytic model. Future research could be focussed on testing the current model based on extensive empirical data, improving the outcome measure and finding appropriate values for that outcome.

Hierarchical control and performance evaluation of multi-vehicle autonomous systems

NASA Astrophysics Data System (ADS)

Balakirsky, Stephen; Scrapper, Chris; Messina, Elena

2005-05-01

This paper will describe how the Mobility Open Architecture Tools and Simulation (MOAST) framework can facilitate performance evaluations of RCS compliant multi-vehicle autonomous systems. This framework provides an environment that allows for simulated and real architectural components to function seamlessly together. By providing repeatable environmental conditions, this framework allows for the development of individual components as well as component performance metrics. MOAST is composed of high-fidelity and low-fidelity simulation systems, a detailed model of real-world terrain, actual hardware components, a central knowledge repository, and architectural glue to tie all of the components together. This paper will describe the framework"s components in detail and provide an example that illustrates how the framework can be utilized to develop and evaluate a single architectural component through the use of repeatable trials and experimentation that includes both virtual and real components functioning together

Stochastic Radiative Transfer Model for Contaminated Rough Surfaces: A Framework for Detection System Design

DTIC Science & Technology

2013-11-01

STOCHASTIC RADIATIVE TRANSFER MODEL FOR CONTAMINATED ROUGH SURFACES: A...of law, no person shall be subject to any penalty for failing to comply with a collection of information if it does not display a currently valid ...COVERED (From - To) Jan 2013 - Sep 2013 4. TITLE AND SUBTITLE Stochastic Radiative Transfer Model for Contaminated Rough Surfaces: A Framework for

Toward Multi-Model Frameworks Addressing Multi-Sector Dynamics, Risks, and Resiliency

NASA Astrophysics Data System (ADS)

Moss, R. H.; Fisher-Vanden, K.; Barrett, C.; Kraucunas, I.; Rice, J.; Sue Wing, I.; Bhaduri, B. L.; Reed, P. M.

2016-12-01

This presentation will report on the findings of recent modeling studies and a series of workshops and other efforts convened under the auspices of the US Global Change Research Program (USGCRP) to improve integration of critical infrastructure, natural resources, integrated assessment, and human systems modeling. The focus is issues related to drought and increased variability of water supply at the energy-water-land nexus. One motivation for the effort is the potential for impact cascades across coupled built, natural, and socioeconomic systems stressed by social and environmental change. The design is for an adaptable modeling framework that will includes a repository of independently-developed modeling tools of varying complexity - from coarser grid, longer time-horizon to higher-resolution shorter-term models of socioeconomic systems, infrastructure, and natural resources. The models draw from three interlocking research communities: Earth system, impacts/adaptation/vulnerability, and integrated assessment. A key lesson will be explored, namely the importance of defining a clear use perspective to limit dimensionality, focus modeling, and facilitate uncertainty characterization and communication.

A Customizable Language Learning Support System Using Ontology-Driven Engine

ERIC Educational Resources Information Center

Wang, Jingyun; Mendori, Takahiko; Xiong, Juan

2013-01-01

This paper proposes a framework for web-based language learning support systems designed to provide customizable pedagogical procedures based on the analysis of characteristics of both learner and course. This framework employs a course-centered ontology and a teaching method ontology as the foundation for the student model, which includes learner…

A general theoretical framework for decoherence in open and closed systems

NASA Astrophysics Data System (ADS)

Castagnino, Mario; Fortin, Sebastian; Laura, Roberto; Lombardi, Olimpia

2008-08-01

A general theoretical framework for decoherence is proposed, which encompasses formalisms originally devised to deal just with open or closed systems. The conditions for decoherence are clearly stated and the relaxation and decoherence times are compared. Finally, the spin-bath model is developed in detail from the new perspective.

An integrated conceptual framework for long-term social-ecological research

Treesearch

S.L. Collins; S.R. Carpenter; S.M. Swinton; D.E. Orenstein; D.L. Childers; T.L. Gragson; N.B. Grimm; J.M. Grove; S.L. Harlan; J.P. Kaye; A.K. Knapp; G.P. Kofinas; J.J. Magnuson; W.H. McDowell; J.M. Melack; L.A. Ogden; G.P. Robertson; M.D. Smith; A.C. Whitmer

2010-01-01

The global reach of human activities affects all natural ecosystems, so that the environment is best viewed as a social-ecological system. Consequently, a more integrative approach to environmental science, one that bridges the biophysical and social domains, is sorely needed. Although models and frameworks for social-ecological systems exist, few are explicitly...

Reengineering Framework for Systems in Education

ERIC Educational Resources Information Center

Choquet, Christophe; Corbiere, Alain

2006-01-01

Specifications recently proposed as standards in the domain of Technology Enhanced Learning (TEL), question the designers of TEL systems on how to put them into practice. Recent studies in Model Driven Engineering have highlighted the need for a framework which could formalize the use of these specifications as well as enhance the quality of the…

Sensor fusion display evaluation using information integration models in enhanced/synthetic vision applications

NASA Technical Reports Server (NTRS)

Foyle, David C.

1993-01-01

Based on existing integration models in the psychological literature, an evaluation framework is developed to assess sensor fusion displays as might be implemented in an enhanced/synthetic vision system. The proposed evaluation framework for evaluating the operator's ability to use such systems is a normative approach: The pilot's performance with the sensor fusion image is compared to models' predictions based on the pilot's performance when viewing the original component sensor images prior to fusion. This allows for the determination as to when a sensor fusion system leads to: poorer performance than one of the original sensor displays, clearly an undesirable system in which the fused sensor system causes some distortion or interference; better performance than with either single sensor system alone, but at a sub-optimal level compared to model predictions; optimal performance compared to model predictions; or, super-optimal performance, which may occur if the operator were able to use some highly diagnostic 'emergent features' in the sensor fusion display, which were unavailable in the original sensor displays.

A Regularized Volumetric Fusion Framework for Large-Scale 3D Reconstruction

NASA Astrophysics Data System (ADS)

Rajput, Asif; Funk, Eugen; Börner, Anko; Hellwich, Olaf

2018-07-01

Modern computational resources combined with low-cost depth sensing systems have enabled mobile robots to reconstruct 3D models of surrounding environments in real-time. Unfortunately, low-cost depth sensors are prone to produce undesirable estimation noise in depth measurements which result in either depth outliers or introduce surface deformations in the reconstructed model. Conventional 3D fusion frameworks integrate multiple error-prone depth measurements over time to reduce noise effects, therefore additional constraints such as steady sensor movement and high frame-rates are required for high quality 3D models. In this paper we propose a generic 3D fusion framework with controlled regularization parameter which inherently reduces noise at the time of data fusion. This allows the proposed framework to generate high quality 3D models without enforcing additional constraints. Evaluation of the reconstructed 3D models shows that the proposed framework outperforms state of art techniques in terms of both absolute reconstruction error and processing time.

Connections Matter: Social Networks and Lifespan Health in Primate Translational Models

PubMed Central

McCowan, Brenda; Beisner, Brianne; Bliss-Moreau, Eliza; Vandeleest, Jessica; Jin, Jian; Hannibal, Darcy; Hsieh, Fushing

2016-01-01

Humans live in societies full of rich and complex relationships that influence health. The ability to improve human health requires a detailed understanding of the complex interplay of biological systems that contribute to disease processes, including the mechanisms underlying the influence of social contexts on these biological systems. A longitudinal computational systems science approach provides methods uniquely suited to elucidate the mechanisms by which social systems influence health and well-being by investigating how they modulate the interplay among biological systems across the lifespan. In the present report, we argue that nonhuman primate social systems are sufficiently complex to serve as model systems allowing for the development and refinement of both analytical and theoretical frameworks linking social life to health. Ultimately, developing systems science frameworks in nonhuman primate models will speed discovery of the mechanisms that subserve the relationship between social life and human health. PMID:27148103

Tailored motivational message generation: A model and practical framework for real-time physical activity coaching.

PubMed

Op den Akker, Harm; Cabrita, Miriam; Op den Akker, Rieks; Jones, Valerie M; Hermens, Hermie J

2015-06-01

This paper presents a comprehensive and practical framework for automatic generation of real-time tailored messages in behavior change applications. Basic aspects of motivational messages are time, intention, content and presentation. Tailoring of messages to the individual user may involve all aspects of communication. A linear modular system is presented for generating such messages. It is explained how properties of user and context are taken into account in each of the modules of the system and how they affect the linguistic presentation of the generated messages. The model of motivational messages presented is based on an analysis of existing literature as well as the analysis of a corpus of motivational messages used in previous studies. The model extends existing 'ontology-based' approaches to message generation for real-time coaching systems found in the literature. Practical examples are given on how simple tailoring rules can be implemented throughout the various stages of the framework. Such examples can guide further research by clarifying what it means to use e.g. user targeting to tailor a message. As primary example we look at the issue of promoting daily physical activity. Future work is pointed out in applying the present model and framework, defining efficient ways of evaluating individual tailoring components, and improving effectiveness through the creation of accurate and complete user- and context models. Copyright © 2015 Elsevier Inc. All rights reserved.

Engaging Youth Through Spatial Socio-Technical Storytelling, Participatory GIS, Agent-Based Modeling, Online Geogames and Action Projects

NASA Astrophysics Data System (ADS)

Poplin, A.; Shenk, L.; Krejci, C.; Passe, U.

2017-09-01

The main goal of this paper is to present the conceptual framework for engaging youth in urban planning activities that simultaneously create locally meaningful positive change. The framework for engaging youth interlinks the use of IT tools such as geographic information systems (GIS), agent-based modelling (ABM), online serious games, and mobile participatory geographic information systems with map-based storytelling and action projects. We summarize the elements of our framework and the first results gained in the program Community Growers established in a neighbourhood community of Des Moines, the capital of Iowa, USA. We conclude the paper with a discussion and future research directions.

Selecting effective incentive structures in health care: A decision framework to support health care purchasers in finding the right incentives to drive performance

PubMed Central

Custers, Thomas; Hurley, Jeremiah; Klazinga, Niek S; Brown, Adalsteinn D

2008-01-01

Background The Ontario health care system is devolving planning and funding authority to community based organizations and moving from steering through rules and regulations to steering on performance. As part of this transformation, the Ontario Ministry of Health and Long-Term Care (MOHLTC) are interested in using incentives as a strategy to ensure alignment – that is, health service providers' goals are in accord with the goals of the health system. The objective of the study was to develop a decision framework to assist policymakers in choosing and designing effective incentive systems. Methods The first part of the study was an extensive review of the literature to identify incentives models that are used in the various health care systems and their effectiveness. The second part was the development of policy principles to ensure that the used incentive models are congruent with the values of the Ontario health care system. The principles were developed by reviewing the Ontario policy documents and through discussions with policymakers. The validation of the principles and the suggested incentive models for use in Ontario took place at two meetings. The first meeting was with experts from the research and policy community, the second with senior policymakers from the MOHLTC. Based on the outcome of those two meetings, the researchers built a decision framework for incentives. The framework was send to the participants of both meetings and four additional experts for validation. Results We identified several models that have proven, with a varying degree of evidence, to be effective in changing or enabling a health provider's performance. Overall, the literature suggests that there is no single best approach to create incentives yet and the ability of financial and non-financial incentives to achieve results depends on a number of contextual elements. After assessing the initial set of incentive models on their congruence with the four policy principles we defined nine incentive models to be appropriate for use in Ontario and potentially other health care systems that want to introduce incentives to improve performance. Subsequently, the models were incorporated in the resulting decision framework. Conclusion The design of an incentive must reflect the values and goals of the health care system, be well matched to the performance objectives and reflect a range of contextual factors that can influence the effectiveness of even well-designed incentives. As a consequence, a single policy recommendation around incentives is inappropriate. The decision framework provides health care policymakers and purchasers with a tool to support the selection of an incentive model that is the most appropriate to improve the targeted performance. PMID:18371198

Performance and Evaluation of the Global Modeling and Assimilation Office Observing System Simulation Experiment

NASA Technical Reports Server (NTRS)

Prive, Nikki; Errico, R. M.; Carvalho, D.

2018-01-01

The National Aeronautics and Space Administration Global Modeling and Assimilation Office (NASA/GMAO) has spent more than a decade developing and implementing a global Observing System Simulation Experiment framework for use in evaluting both new observation types as well as the behavior of data assimilation systems. The NASA/GMAO OSSE has constantly evolved to relect changes in the Gridpoint Statistical Interpolation data assimiation system, the Global Earth Observing System model, version 5 (GEOS-5), and the real world observational network. Software and observational datasets for the GMAO OSSE are publicly available, along with a technical report. Substantial modifications have recently been made to the NASA/GMAO OSSE framework, including the character of synthetic observation errors, new instrument types, and more sophisticated atmospheric wind vectors. These improvements will be described, along with the overall performance of the current OSSE. Lessons learned from investigations into correlated errors and model error will be discussed.

A Framework for Evaluating Regional-Scale Numerical Photochemical Modeling Systems

EPA Science Inventory

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 li...

An Uncertainty Quantification Framework for Prognostics and Condition-Based Monitoring

NASA Technical Reports Server (NTRS)

Sankararaman, Shankar; Goebel, Kai

2014-01-01

This paper presents a computational framework for uncertainty quantification in prognostics in the context of condition-based monitoring of aerospace systems. The different sources of uncertainty and the various uncertainty quantification activities in condition-based prognostics are outlined in detail, and it is demonstrated that the Bayesian subjective approach is suitable for interpreting uncertainty in online monitoring. A state-space model-based framework for prognostics, that can rigorously account for the various sources of uncertainty, is presented. Prognostics consists of two important steps. First, the state of the system is estimated using Bayesian tracking, and then, the future states of the system are predicted until failure, thereby computing the remaining useful life of the system. The proposed framework is illustrated using the power system of a planetary rover test-bed, which is being developed and studied at NASA Ames Research Center.

A General Cross-Layer Cloud Scheduling Framework for Multiple IoT Computer Tasks.

PubMed

Wu, Guanlin; Bao, Weidong; Zhu, Xiaomin; Zhang, Xiongtao

2018-05-23

The diversity of IoT services and applications brings enormous challenges to improving the performance of multiple computer tasks' scheduling in cross-layer cloud computing systems. Unfortunately, the commonly-employed frameworks fail to adapt to the new patterns on the cross-layer cloud. To solve this issue, we design a new computer task scheduling framework for multiple IoT services in cross-layer cloud computing systems. Specifically, we first analyze the features of the cross-layer cloud and computer tasks. Then, we design the scheduling framework based on the analysis and present detailed models to illustrate the procedures of using the framework. With the proposed framework, the IoT services deployed in cross-layer cloud computing systems can dynamically select suitable algorithms and use resources more effectively to finish computer tasks with different objectives. Finally, the algorithms are given based on the framework, and extensive experiments are also given to validate its effectiveness, as well as its superiority.

How ecology shapes exploitation: a framework to predict the behavioural response of human and animal foragers along exploration-exploitation trade-offs.

PubMed

Monk, Christopher T; Barbier, Matthieu; Romanczuk, Pawel; Watson, James R; Alós, Josep; Nakayama, Shinnosuke; Rubenstein, Daniel I; Levin, Simon A; Arlinghaus, Robert

2018-06-01

Understanding how humans and other animals behave in response to changes in their environments is vital for predicting population dynamics and the trajectory of coupled social-ecological systems. Here, we present a novel framework for identifying emergent social behaviours in foragers (including humans engaged in fishing or hunting) in predator-prey contexts based on the exploration difficulty and exploitation potential of a renewable natural resource. A qualitative framework is introduced that predicts when foragers should behave territorially, search collectively, act independently or switch among these states. To validate it, we derived quantitative predictions from two models of different structure: a generic mathematical model, and a lattice-based evolutionary model emphasising exploitation and exclusion costs. These models independently identified that the exploration difficulty and exploitation potential of the natural resource controls the social behaviour of resource exploiters. Our theoretical predictions were finally compared to a diverse set of empirical cases focusing on fisheries and aquatic organisms across a range of taxa, substantiating the framework's predictions. Understanding social behaviour for given social-ecological characteristics has important implications, particularly for the design of governance structures and regulations to move exploited systems, such as fisheries, towards sustainability. Our framework provides concrete steps in this direction. © 2018 John Wiley & Sons Ltd/CNRS.

A College Administrator's Framework to Assess Compliance with Accreditation Mandates

ERIC Educational Resources Information Center

Davis†, Jerry M.; Rivera, John-Juan

2014-01-01

A framework to assess the impact of complying with college accreditation mandates is developed based on North's (1996) concepts of transaction costs, property rights, and institutions; Clayton's (1999) Systems Alignment Model; and the educational production function described by Hanushek (2007). The framework demonstrates how sought…

Comprehensive Assessment of Models and Events based on Library tools (CAMEL)

NASA Astrophysics Data System (ADS)

Rastaetter, L.; Boblitt, J. M.; DeZeeuw, D.; Mays, M. L.; Kuznetsova, M. M.; Wiegand, C.

2017-12-01

At the Community Coordinated Modeling Center (CCMC), the assessment of modeling skill using a library of model-data comparison metrics is taken to the next level by fully integrating the ability to request a series of runs with the same model parameters for a list of events. The CAMEL framework initiates and runs a series of selected, pre-defined simulation settings for participating models (e.g., WSA-ENLIL, SWMF-SC+IH for the heliosphere, SWMF-GM, OpenGGCM, LFM, GUMICS for the magnetosphere) and performs post-processing using existing tools for a host of different output parameters. The framework compares the resulting time series data with respective observational data and computes a suite of metrics such as Prediction Efficiency, Root Mean Square Error, Probability of Detection, Probability of False Detection, Heidke Skill Score for each model-data pair. The system then plots scores by event and aggregated over all events for all participating models and run settings. We are building on past experiences with model-data comparisons of magnetosphere and ionosphere model outputs in GEM2008, GEM-CEDAR CETI2010 and Operational Space Weather Model challenges (2010-2013). We can apply the framework also to solar-heliosphere as well as radiation belt models. The CAMEL framework takes advantage of model simulations described with Space Physics Archive Search and Extract (SPASE) metadata and a database backend design developed for a next-generation Run-on-Request system at the CCMC.

Integration of a three-dimensional process-based hydrological model into the Object Modeling System

USDA-ARS?s Scientific Manuscript database

The integration of a spatial process model into an environmental modelling framework can enhance the model’s capabilities. We present the integration of the GEOtop model into the Object Modeling System (OMS) version 3.0 and illustrate its application in a small watershed. GEOtop is a physically base...

Use of Annotations for Component and Framework Interoperability

NASA Astrophysics Data System (ADS)

David, O.; Lloyd, W.; Carlson, J.; Leavesley, G. H.; Geter, F.

2009-12-01

The popular programming languages Java and C# provide annotations, a form of meta-data construct. Software frameworks for web integration, web services, database access, and unit testing now take advantage of annotations to reduce the complexity of APIs and the quantity of integration code between the application and framework infrastructure. Adopting annotation features in frameworks has been observed to lead to cleaner and leaner application code. The USDA Object Modeling System (OMS) version 3.0 fully embraces the annotation approach and additionally defines a meta-data standard for components and models. In version 3.0 framework/model integration previously accomplished using API calls is now achieved using descriptive annotations. This enables the framework to provide additional functionality non-invasively such as implicit multithreading, and auto-documenting capabilities while achieving a significant reduction in the size of the model source code. Using a non-invasive methodology leads to models and modeling components with only minimal dependencies on the modeling framework. Since models and modeling components are not directly bound to framework by the use of specific APIs and/or data types they can more easily be reused both within the framework as well as outside of it. To study the effectiveness of an annotation based framework approach with other modeling frameworks, a framework-invasiveness study was conducted to evaluate the effects of framework design on model code quality. A monthly water balance model was implemented across several modeling frameworks and several software metrics were collected. The metrics selected were measures of non-invasive design methods for modeling frameworks from a software engineering perspective. It appears that the use of annotations positively impacts several software quality measures. In a next step, the PRMS model was implemented in OMS 3.0 and is currently being implemented for water supply forecasting in the western United States at the USDA NRCS National Water and Climate Center. PRMS is a component based modular precipitation-runoff model developed to evaluate the impacts of various combinations of precipitation, climate, and land use on streamflow and general basin hydrology. The new OMS 3.0 PRMS model source code is more concise and flexible as a result of using the new framework’s annotation based approach. The fully annotated components are now providing information directly for (i) model assembly and building, (ii) dataflow analysis for implicit multithreading, (iii) automated and comprehensive model documentation of component dependencies, physical data properties, (iv) automated model and component testing, and (v) automated audit-traceability to account for all model resources leading to a particular simulation result. Experience to date has demonstrated the multi-purpose value of using annotations. Annotations are also a feasible and practical method to enable interoperability among models and modeling frameworks. As a prototype example, model code annotations were used to generate binding and mediation code to allow the use of OMS 3.0 model components within the OpenMI context.

Antecedences to Continued Intentions of Adopting E-Learning System in Blended Learning Instruction: A Contingency Framework Based on Models of Information System Success and Task-Technology Fit

ERIC Educational Resources Information Center

Lin, Wen-Shan; Wang, Chun-Hsien

2012-01-01

The objective of this study is to propose a research framework that investigates the relation between perceived fit and system factors that can motivate learners in continuing utilizing an e-learning system in blended learning instruction. As learners have the face-to-face learning opportunity in interacting with lecturers, the study aims at…

The TEF modeling and analysis approach to advance thermionic space power technology

NASA Astrophysics Data System (ADS)

Marshall, Albert C.

1997-01-01

Thermionics space power systems have been proposed as advanced power sources for future space missions that require electrical power levels significantly above the capabilities of current space power systems. The Defense Special Weapons Agency's (DSWA) Thermionic Evaluation Facility (TEF) is carrying out both experimental and analytical research to advance thermionic space power technology to meet this expected need. A Modeling and Analysis (M&A) project has been created at the TEF to develop analysis tools, evaluate concepts, and guide research. M&A activities are closely linked to the TEF experimental program, providing experiment support and using experimental data to validate models. A planning exercise has been completed for the M&A project, and a strategy for implementation was developed. All M&A activities will build on a framework provided by a system performance model for a baseline Thermionic Fuel Element (TFE) concept. The system model is composed of sub-models for each of the system components and sub-systems. Additional thermionic component options and model improvements will continue to be incorporated in the basic system model during the course of the program. All tasks are organized into four focus areas: 1) system models, 2) thermionic research, 3) alternative concepts, and 4) documentation and integration. The M&A project will provide a solid framework for future thermionic system development.

Connecting heterogeneous single slip to diffraction peak evolution in high-energy monochromatic X-ray experiments

PubMed Central

Pagan, Darren C.; Miller, Matthew P.

2014-01-01

A forward modeling diffraction framework is introduced and employed to identify slip system activity in high-energy diffraction microscopy (HEDM) experiments. In the framework, diffraction simulations are conducted on virtual mosaic crystals with orientation gradients consistent with Nye’s model of heterogeneous single slip. Simulated diffraction peaks are then compared against experimental measurements to identify slip system activity. Simulation results compared against diffraction data measured in situ from a silicon single-crystal specimen plastically deformed under single-slip conditions indicate that slip system activity can be identified during HEDM experiments. PMID:24904242

Framework for the mapping of the monthly average daily solar radiation using an advanced case-based reasoning and a geostatistical technique.

PubMed

Lee, Minhyun; Koo, Choongwan; Hong, Taehoon; Park, Hyo Seon

2014-04-15

For the effective photovoltaic (PV) system, it is necessary to accurately determine the monthly average daily solar radiation (MADSR) and to develop an accurate MADSR map, which can simplify the decision-making process for selecting the suitable location of the PV system installation. Therefore, this study aimed to develop a framework for the mapping of the MADSR using an advanced case-based reasoning (CBR) and a geostatistical technique. The proposed framework consists of the following procedures: (i) the geographic scope for the mapping of the MADSR is set, and the measured MADSR and meteorological data in the geographic scope are collected; (ii) using the collected data, the advanced CBR model is developed; (iii) using the advanced CBR model, the MADSR at unmeasured locations is estimated; and (iv) by applying the measured and estimated MADSR data to the geographic information system, the MADSR map is developed. A practical validation was conducted by applying the proposed framework to South Korea. It was determined that the MADSR map developed through the proposed framework has been improved in terms of accuracy. The developed MADSR map can be used for estimating the MADSR at unmeasured locations and for determining the optimal location for the PV system installation.

Knowledge acquisition in the fuzzy knowledge representation framework of a medical consultation system.

PubMed

Boegl, Karl; Adlassnig, Klaus-Peter; Hayashi, Yoichi; Rothenfluh, Thomas E; Leitich, Harald

2004-01-01

This paper describes the fuzzy knowledge representation framework of the medical computer consultation system MedFrame/CADIAG-IV as well as the specific knowledge acquisition techniques that have been developed to support the definition of knowledge concepts and inference rules. As in its predecessor system CADIAG-II, fuzzy medical knowledge bases are used to model the uncertainty and the vagueness of medical concepts and fuzzy logic reasoning mechanisms provide the basic inference processes. The elicitation and acquisition of medical knowledge from domain experts has often been described as the most difficult and time-consuming task in knowledge-based system development in medicine. It comes as no surprise that this is even more so when unfamiliar representations like fuzzy membership functions are to be acquired. From previous projects we have learned that a user-centered approach is mandatory in complex and ill-defined knowledge domains such as internal medicine. This paper describes the knowledge acquisition framework that has been developed in order to make easier and more accessible the three main tasks of: (a) defining medical concepts; (b) providing appropriate interpretations for patient data; and (c) constructing inferential knowledge in a fuzzy knowledge representation framework. Special emphasis is laid on the motivations for some system design and data modeling decisions. The theoretical framework has been implemented in a software package, the Knowledge Base Builder Toolkit. The conception and the design of this system reflect the need for a user-centered, intuitive, and easy-to-handle tool. First results gained from pilot studies have shown that our approach can be successfully implemented in the context of a complex fuzzy theoretical framework. As a result, this critical aspect of knowledge-based system development can be accomplished more easily.

Vulnerability assessment of water resources - Translating a theoretical concept to an operational framework using systems thinking approach in a changing climate: Case study in Ogallala Aquifer

NASA Astrophysics Data System (ADS)

Anandhi, Aavudai; Kannan, Narayanan

2018-02-01

Water is an essential natural resource. Among many stressors, altered climate is exerting pressure on water resource systems, increasing its demand and creating a need for vulnerability assessments. The overall objective of this study was to develop a novel tool that can translate a theoretical concept (vulnerability of water resources (VWR)) to an operational framework mainly under altered temperature and precipitation, as well as for population change (smaller extent). The developed tool had three stages and utilized a novel systems thinking approach. Stage-1: Translating theoretical concept to characteristics identified from studies; Stage-2: Operationalizing characteristics to methodology in VWR; Stage-3: Utilizing the methodology for development of a conceptual modeling tool for VWR: WR-VISTA (Water Resource Vulnerability assessment conceptual model using Indicators selected by System's Thinking Approach). The specific novelties were: 1) The important characteristics in VWR were identified in Stage-1 (target system, system components, scale, level of detail, data source, frameworks, and indicator); 2) WR-VISTA combined two vulnerability assessments frameworks: the European's Driver-Pressure-State-Impact-Response framework (DPSIR) and the Intergovernmental Panel on Climate Change's framework (IPCC's); and 3) used systems thinking approaches in VWR for indicator selection. The developed application was demonstrated in Kansas (overlying the High Plains region/Ogallala Aquifer, considered the "breadbasket of the world"), using 26 indicators with intermediate level of detail. Our results indicate that the western part of the state is vulnerable from agricultural water use and the eastern part from urban water use. The developed tool can be easily replicated to other regions within and outside the US.

Adaptive and neuroadaptive control for nonnegative and compartmental dynamical systems

NASA Astrophysics Data System (ADS)

Volyanskyy, Kostyantyn Y.

Neural networks have been extensively used for adaptive system identification as well as adaptive and neuroadaptive control of highly uncertain systems. The goal of adaptive and neuroadaptive control is to achieve system performance without excessive reliance on system models. To improve robustness and the speed of adaptation of adaptive and neuroadaptive controllers several controller architectures have been proposed in the literature. In this dissertation, we develop a new neuroadaptive control architecture for nonlinear uncertain dynamical systems. The proposed framework involves a novel controller architecture with additional terms in the update laws that are constructed using a moving window of the integrated system uncertainty. These terms can be used to identify the ideal system weights of the neural network as well as effectively suppress system uncertainty. Linear and nonlinear parameterizations of the system uncertainty are considered and state and output feedback neuroadaptive controllers are developed. Furthermore, we extend the developed framework to discrete-time dynamical systems. To illustrate the efficacy of the proposed approach we apply our results to an aircraft model with wing rock dynamics, a spacecraft model with unknown moment of inertia, and an unmanned combat aerial vehicle undergoing actuator failures, and compare our results with standard neuroadaptive control methods. Nonnegative systems are essential in capturing the behavior of a wide range of dynamical systems involving dynamic states whose values are nonnegative. A sub-class of nonnegative dynamical systems are compartmental systems. These systems are derived from mass and energy balance considerations and are comprised of homogeneous interconnected microscopic subsystems or compartments which exchange variable quantities of material via intercompartmental flow laws. In this dissertation, we develop direct adaptive and neuroadaptive control framework for stabilization, disturbance rejection and noise suppression for nonnegative and compartmental dynamical systems with noise and exogenous system disturbances. We then use the developed framework to control the infusion of the anesthetic drug propofol for maintaining a desired constant level of depth of anesthesia for surgery in the face of continuing hemorrhage and hemodilution. Critical care patients, whether undergoing surgery or recovering in intensive care units, require drug administration to regulate physiological variables such as blood pressure, cardiac output, heart rate, and degree of consciousness. The rate of infusion of each administered drug is critical, requiring constant monitoring and frequent adjustments. In this dissertation, we develop a neuroadaptive output feedback control framework for nonlinear uncertain nonnegative and compartmental systems with nonnegative control inputs and noisy measurements. The proposed framework is Lyapunov-based and guarantees ultimate boundedness of the error signals. In addition, the neuroadaptive controller guarantees that the physical system states remain in the nonnegative orthant of the state space. Finally, the developed approach is used to control the infusion of the anesthetic drug propofol for maintaining a desired constant level of depth of anesthesia for surgery in the face of noisy electroencephalographic (EEG) measurements. Clinical trials demonstrate excellent regulation of unconsciousness allowing for a safe and effective administration of the anesthetic agent propofol. Furthermore, a neuroadaptive output feedback control architecture for nonlinear nonnegative dynamical systems with input amplitude and integral constraints is developed. Specifically, the neuroadaptive controller guarantees that the imposed amplitude and integral input constraints are satisfied and the physical system states remain in the nonnegative orthant of the state space. The proposed approach is used to control the infusion of the anesthetic drug propofol for maintaining a desired constant level of depth of anesthesia for noncardiac surgery in the face of infusion rate constraints and a drug dosing constraint over a specified period. In addition, the aforementioned control architecture is used to control lung volume and minute ventilation with input pressure constraints that also accounts for spontaneous breathing by the patient. Specifically, we develop a pressure- and work-limited neuroadaptive controller for mechanical ventilation based on a nonlinear multi-compartmental lung model. The control framework does not rely on any averaged data and is designed to automatically adjust the input pressure to the patient's physiological characteristics capturing lung resistance and compliance modeling uncertainty. Moreover, the controller accounts for input pressure constraints as well as work of breathing constraints. The effect of spontaneous breathing is incorporated within the lung model and the control framework. Finally, a neural network hybrid adaptive control framework for nonlinear uncertain hybrid dynamical systems is developed. The proposed hybrid adaptive control framework is Lyapunov-based and guarantees partial asymptotic stability of the closed-loop hybrid system; that is, asymptotic stability with respect to part of the closed-loop system states associated with the hybrid plant states. A numerical example is provided to demonstrate the efficacy of the proposed hybrid adaptive stabilization approach.

Data-Adaptable Modeling and Optimization for Runtime Adaptable Systems

DTIC Science & Technology

2016-06-08

execution scenarios e . Enables model -guided optimization algorithms that outperform state-of-the-art f. Understands the overhead of system...the Data-Adaptable System Model (DASM), that facilitates design by enabling the designer to: 1) specify both an application’s task flow as well as...systems. The MILAN [3] framework specializes in the design, simulation , and synthesis of System On Chip (SoC) applications using model -based techniques

A Conceptual Framework for SAHRA Integrated Multi-resolution Modeling in the Rio Grande Basin

NASA Astrophysics Data System (ADS)

Liu, Y.; Gupta, H.; Springer, E.; Wagener, T.; Brookshire, D.; Duffy, C.

2004-12-01

The sustainable management of water resources in a river basin requires an integrated analysis of the social, economic, environmental and institutional dimensions of the problem. Numerical models are commonly used for integration of these dimensions and for communication of the analysis results to stakeholders and policy makers. The National Science Foundation Science and Technology Center for Sustainability of semi-Arid Hydrology and Riparian Areas (SAHRA) has been developing integrated multi-resolution models to assess impacts of climate variability and land use change on water resources in the Rio Grande Basin. These models not only couple natural systems such as surface and ground waters, but will also include engineering, economic and social components that may be involved in water resources decision-making processes. This presentation will describe the conceptual framework being developed by SAHRA to guide and focus the multiple modeling efforts and to assist the modeling team in planning, data collection and interpretation, communication, evaluation, etc. One of the major components of this conceptual framework is a Conceptual Site Model (CSM), which describes the basin and its environment based on existing knowledge and identifies what additional information must be collected to develop technically sound models at various resolutions. The initial CSM is based on analyses of basin profile information that has been collected, including a physical profile (e.g., topographic and vegetative features), a man-made facility profile (e.g., dams, diversions, and pumping stations), and a land use and ecological profile (e.g., demographics, natural habitats, and endangered species). Based on the initial CSM, a Conceptual Physical Model (CPM) is developed to guide and evaluate the selection of a model code (or numerical model) for each resolution to conduct simulations and predictions. A CPM identifies, conceptually, all the physical processes and engineering and socio-economic activities occurring (or to occur) in the real system that the corresponding numerical models are required to address, such as riparian evapotranspiration responses to vegetation change and groundwater pumping impacts on soil moisture contents. Simulation results from different resolution models and observations of the real system will then be compared to evaluate the consistency among the CSM, the CPMs, and the numerical models, and feedbacks will be used to update the models. In a broad sense, the evaluation of the models (conceptual or numerical), as well as the linkages between them, can be viewed as a part of the overall conceptual framework. As new data are generated and understanding improves, the models will evolve, and the overall conceptual framework is refined. The development of the conceptual framework becomes an on-going process. We will describe the current state of this framework and the open questions that have to be addressed in the future.

MOCASSIM - an operational forecast system for the Portuguese coastal waters.

NASA Astrophysics Data System (ADS)

Vitorino, J.; Soares, C.; Almeida, S.; Rusu, E.; Pinto, J.

2003-04-01

An operational system for the forecast of oceanographic conditions off the Portuguese coast is presently being implemented at Instituto Hidrográfico (IH), in the framework of project MOCASSIM. The system is planned to use a broad range of observations provided both from IH observational networks (wave buoys, tidal gauges) and programs (hydrographic surveys, moorings) as well as from external sources. The MOCASSIM system integrates several numerical models which, combined, are intended to cover the relevant physical processes observed in the geographical areas of interest. At the present stage of development the system integrates a circulation module and a wave module. The circulation module is based on the Harvard Ocean Prediction System (HOPS), a primitive equation model formulated under the rigid lid assumption, which includes a data assimilation module. The wave module is based on the WaveWatch3 (WW3) model, which provides wave conditions in the North Atlantic basin, and on the SWAN model which is used to improve the wave forecasts on coastal or other specific areas of interest. The models use the meteorological forcing fields of a limited area model (ALADIN model) covering the Portuguese area, which are being provided in the framework of a close colaboration with Instituto de Meteorologia. Although still under devellopment, the MOCASSIM system has already been used in several operationnal contexts. These included the operational environmental assessment during both national and NATO navy exercises and, more recently, the monitoring of the oceanographic conditions in the NW Iberian area affected by the oil spill of MV "Prestige". The system is also a key component of ongoing research on the oceanography of the Portuguese continental margin, which is presently being conducted at IH in the framework of national and European funded projects.

Physiome-model-based state-space framework for cardiac deformation recovery.

PubMed

Wong, Ken C L; Zhang, Heye; Liu, Huafeng; Shi, Pengcheng

2007-11-01

To more reliably recover cardiac information from noise-corrupted, patient-specific measurements, it is essential to employ meaningful constraining models and adopt appropriate optimization criteria to couple the models with the measurements. Although biomechanical models have been extensively used for myocardial motion recovery with encouraging results, the passive nature of such constraints limits their ability to fully count for the deformation caused by active forces of the myocytes. To overcome such limitations, we propose to adopt a cardiac physiome model as the prior constraint for cardiac motion analysis. The cardiac physiome model comprises an electric wave propagation model, an electromechanical coupling model, and a biomechanical model, which are connected through a cardiac system dynamics for a more complete description of the macroscopic cardiac physiology. Embedded within a multiframe state-space framework, the uncertainties of the model and the patient's measurements are systematically dealt with to arrive at optimal cardiac kinematic estimates and possibly beyond. Experiments have been conducted to compare our proposed cardiac-physiome-model-based framework with the solely biomechanical model-based framework. The results show that our proposed framework recovers more accurate cardiac deformation from synthetic data and obtains more sensible estimates from real magnetic resonance image sequences. With the active components introduced by the cardiac physiome model, cardiac deformations recovered from patient's medical images are more physiologically plausible.

Understanding Universities in Ontario, Canada: An Industry Analysis Using Porter's Five Forces Framework

ERIC Educational Resources Information Center

Pringle, James; Huisman, Jeroen

2011-01-01

In analyses of higher education systems, many models and frameworks are based on governance, steering, or coordination models. Although much can be gained by such analyses, we argue that the language used in the present-day policy documents (knowledge economy, competitive position, etc.) calls for an analysis of higher education as an industry. In…

RESEARCH: Conceptualizing Environmental Stress: A Stress-Response Model of Coastal Sandy Barriers.

PubMed

Gabriel; Kreutzwiser

2000-01-01

/ The purpose of this paper is to develop and apply a conceptual framework of environmental stress-response for a geomorphic system. Constructs and methods generated from the literature were applied in the development of an integrative stress-response framework using existing environmental assessment techniques: interaction matrices and a systems diagram. Emphasis is on the interaction between environmental stress and the geomorphic environment of a sandy barrier system. The model illustrates a number of stress concepts pertinent to modeling environmental stress-response, including those related to stress-dependency, frequency-recovery relationships, environmental heterogeneity, spatial hierarchies and linkages, and temporal change. Sandy barrier stress-response and recovery are greatly impacted by fluctuating water levels, stress intensity and frequency, as well as environmental gradients such as differences in sediment storage and supply. Aspects of these stress-response variables are articulated in terms of three main challenges to management: dynamic stability, spatial integrity, and temporal variability. These in turn form the framework for evaluative principles that may be applied to assess how policies and management practices reflect key biophysical processes and human stresses identified by the model.

Object-oriented models of cognitive processing.

PubMed

Mather, G

2001-05-01

Information-processing models of vision and cognition are inspired by procedural programming languages. Models that emphasize object-based representations are closely related to object-oriented programming languages. The concepts underlying object-oriented languages provide a theoretical framework for cognitive processing that differs markedly from that offered by procedural languages. This framework is well-suited to a system designed to deal flexibly with discrete objects and unpredictable events in the world.

Application of an Integrated HPC Reliability Prediction Framework to HMMWV Suspension System

DTIC Science & Technology

2010-09-13

model number M966 (TOW Missle Carrier, Basic Armor without weapons), since they were available. Tires used for all simulations were the bias-type...vehicle fleet, including consideration of all kinds of uncertainty, especially including model uncertainty. The end result will be a tool to use...building an adequate vehicle reliability prediction framework for military vehicles is the accurate modeling of the integration of various types of

Colaborated Architechture Framework for Composition UML 2.0 in Zachman Framework

NASA Astrophysics Data System (ADS)

Hermawan; Hastarista, Fika

2016-01-01

Zachman Framework (ZF) is the framework of enterprise architechture that most widely adopted in the Enterprise Information System (EIS) development. In this study, has been developed Colaborated Architechture Framework (CAF) to collaborate ZF with Unified Modeling Language (UML) 2.0 modeling. The CAF provides the composition of ZF matrix that each cell is consist of the Model Driven architechture (MDA) from the various UML models and many Software Requirement Specification (SRS) documents. Implementation of this modeling is used to develops Enterprise Resource Planning (ERP). Because ERP have a coverage of applications in large numbers and complexly relations, it is necessary to use Agile Model Driven Design (AMDD) approach as an advanced method to transforms MDA into components of application modules with efficiently and accurately. Finally, through the using of the CAF, give good achievement in fullfilment the needs from all stakeholders that are involved in the overall process stage of Rational Unified Process (RUP), and also obtaining a high satisfaction to fullfiled the functionality features of the ERP software in PT. Iglas (Persero) Gresik.

Generating action descriptions from statistically integrated representations of human motions and sentences.

PubMed

Takano, Wataru; Kusajima, Ikuo; Nakamura, Yoshihiko

2016-08-01

It is desirable for robots to be able to linguistically understand human actions during human-robot interactions. Previous research has developed frameworks for encoding human full body motion into model parameters and for classifying motion into specific categories. For full understanding, the motion categories need to be connected to the natural language such that the robots can interpret human motions as linguistic expressions. This paper proposes a novel framework for integrating observation of human motion with that of natural language. This framework consists of two models; the first model statistically learns the relations between motions and their relevant words, and the second statistically learns sentence structures as word n-grams. Integration of these two models allows robots to generate sentences from human motions by searching for words relevant to the motion using the first model and then arranging these words in appropriate order using the second model. This allows making sentences that are the most likely to be generated from the motion. The proposed framework was tested on human full body motion measured by an optical motion capture system. In this, descriptive sentences were manually attached to the motions, and the validity of the system was demonstrated. Copyright © 2016 Elsevier Ltd. All rights reserved.

An integrated framework for detecting suspicious behaviors in video surveillance

NASA Astrophysics Data System (ADS)

Zin, Thi Thi; Tin, Pyke; Hama, Hiromitsu; Toriu, Takashi

2014-03-01

In this paper, we propose an integrated framework for detecting suspicious behaviors in video surveillance systems which are established in public places such as railway stations, airports, shopping malls and etc. Especially, people loitering in suspicion, unattended objects left behind and exchanging suspicious objects between persons are common security concerns in airports and other transit scenarios. These involve understanding scene/event, analyzing human movements, recognizing controllable objects, and observing the effect of the human movement on those objects. In the proposed framework, multiple background modeling technique, high level motion feature extraction method and embedded Markov chain models are integrated for detecting suspicious behaviors in real time video surveillance systems. Specifically, the proposed framework employs probability based multiple backgrounds modeling technique to detect moving objects. Then the velocity and distance measures are computed as the high level motion features of the interests. By using an integration of the computed features and the first passage time probabilities of the embedded Markov chain, the suspicious behaviors in video surveillance are analyzed for detecting loitering persons, objects left behind and human interactions such as fighting. The proposed framework has been tested by using standard public datasets and our own video surveillance scenarios.

Model and Interoperability using Meta Data Annotations

NASA Astrophysics Data System (ADS)

David, O.

2011-12-01

Software frameworks and architectures are in need for meta data to efficiently support model integration. Modelers have to know the context of a model, often stepping into modeling semantics and auxiliary information usually not provided in a concise structure and universal format, consumable by a range of (modeling) tools. XML often seems the obvious solution for capturing meta data, but its wide adoption to facilitate model interoperability is limited by XML schema fragmentation, complexity, and verbosity outside of a data-automation process. Ontologies seem to overcome those shortcomings, however the practical significance of their use remains to be demonstrated. OMS version 3 took a different approach for meta data representation. The fundamental building block of a modular model in OMS is a software component representing a single physical process, calibration method, or data access approach. Here, programing language features known as Annotations or Attributes were adopted. Within other (non-modeling) frameworks it has been observed that annotations lead to cleaner and leaner application code. Framework-supported model integration, traditionally accomplished using Application Programming Interfaces (API) calls is now achieved using descriptive code annotations. Fully annotated components for various hydrological and Ag-system models now provide information directly for (i) model assembly and building, (ii) data flow analysis for implicit multi-threading or visualization, (iii) automated and comprehensive model documentation of component dependencies, physical data properties, (iv) automated model and component testing, calibration, and optimization, and (v) automated audit-traceability to account for all model resources leading to a particular simulation result. Such a non-invasive methodology leads to models and modeling components with only minimal dependencies on the modeling framework but a strong reference to its originating code. Since models and modeling components are not directly bound to framework by the use of specific APIs and/or data types they can more easily be reused both within the framework as well as outside. While providing all those capabilities, a significant reduction in the size of the model source code was achieved. To support the benefit of annotations for a modeler, studies were conducted to evaluate the effectiveness of an annotation based framework approach with other modeling frameworks and libraries, a framework-invasiveness study was conducted to evaluate the effects of framework design on model code quality. A typical hydrological model was implemented across several modeling frameworks and several software metrics were collected. The metrics selected were measures of non-invasive design methods for modeling frameworks from a software engineering perspective. It appears that the use of annotations positively impacts several software quality measures. Experience to date has demonstrated the multi-purpose value of using annotations. Annotations are also a feasible and practical method to enable interoperability among models and modeling frameworks.

Analytical method of waste allocation in waste management systems: Concept, method and case study

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bergeron, Francis C., E-mail: francis.b.c@videotron.ca

Waste is not a rejected item to dispose anymore but increasingly a secondary resource to exploit, influencing waste allocation among treatment operations in a waste management (WM) system. The aim of this methodological paper is to present a new method for the assessment of the WM system, the “analytical method of the waste allocation process” (AMWAP), based on the concept of the “waste allocation process” defined as the aggregation of all processes of apportioning waste among alternative waste treatment operations inside or outside the spatial borders of a WM system. AMWAP contains a conceptual framework and an analytical approach. Themore » conceptual framework includes, firstly, a descriptive model that focuses on the description and classification of the WM system. It includes, secondly, an explanatory model that serves to explain and to predict the operation of the WM system. The analytical approach consists of a step-by-step analysis for the empirical implementation of the conceptual framework. With its multiple purposes, AMWAP provides an innovative and objective modular method to analyse a WM system which may be integrated in the framework of impact assessment methods and environmental systems analysis tools. Its originality comes from the interdisciplinary analysis of the WAP and to develop the conceptual framework. AMWAP is applied in the framework of an illustrative case study on the household WM system of Geneva (Switzerland). It demonstrates that this method provides an in-depth and contextual knowledge of WM. - Highlights: • The study presents a new analytical method based on the waste allocation process. • The method provides an in-depth and contextual knowledge of the waste management system. • The paper provides a reproducible procedure for professionals, experts and academics. • It may be integrated into impact assessment or environmental system analysis tools. • An illustrative case study is provided based on household waste management in Geneva.« less

Framework for Risk Analysis in Multimedia Environmental Systems: Modeling Individual Steps of a Risk Assessment Process

DOE Office of Scientific and Technical Information (OSTI.GOV)

Shah, Anuj; Castleton, Karl J.; Hoopes, Bonnie L.

2004-06-01

The study of the release and effects of chemicals in the environment and their associated risks to humans is central to public and private decision making. FRAMES 1.X, Framework for Risk Analysis in Multimedia Environmental Systems, is a systems modeling software platform, developed by PNNL, Pacific Northwest National Laboratory, that helps scientists study the release and effects of chemicals on a source to outcome basis, create environmental models for similar risk assessment and management problems. The unique aspect of FRAMES is to dynamically introduce software modules representing individual components of a risk assessment (e.g., source release of contaminants, fate andmore » transport in various environmental media, exposure, etc.) within a software framework, manipulate their attributes and run simulations to obtain results. This paper outlines the fundamental constituents of FRAMES 2.X, an enhanced version of FRAMES 1.X, that greatly improve the ability of the module developers to “plug” their self-developed software modules into the system. The basic design, the underlying principles and a discussion of the guidelines for module developers are presented.« less

Systematizing Web Search through a Meta-Cognitive, Systems-Based, Information Structuring Model (McSIS)

ERIC Educational Resources Information Center

Abuhamdieh, Ayman H.; Harder, Joseph T.

2015-01-01

This paper proposes a meta-cognitive, systems-based, information structuring model (McSIS) to systematize online information search behavior based on literature review of information-seeking models. The General Systems Theory's (GST) prepositions serve as its framework. Factors influencing information-seekers, such as the individual learning…

MODELS-3 (CMAQ). NARSTO NEWS (VOL. 3, NO. 2, SUMMER/FALL 1999)

EPA Science Inventory

A revised version of the U.S. EPA's Models-3/CMAQ system was released on June 30, 1999. Models-3 consists of a sophisticated computational framework for environmental models allowing for much flexibility in the communications between component parts of the system, in updating or ...

Adaptive Automation Design and Implementation

DTIC Science & Technology

2015-09-17

Study : Space Navigator This section demonstrates the player modeling paradigm, focusing specifically on the response generation section of the player ...human-machine system, a real-time player modeling framework for imitating a specific person’s task performance, and the Adaptive Automation System...Model . . . . . . . . . . . . . . . . . . . . . . . 13 Clustering-Based Real-Time Player Modeling . . . . . . . . . . . . . . . . . . . . . . 15 An

A multi-level simulation platform of natural gas internal reforming solid oxide fuel cell-gas turbine hybrid generation system - Part II. Balancing units model library and system simulation

NASA Astrophysics Data System (ADS)

Bao, Cheng; Cai, Ningsheng; Croiset, Eric

2011-10-01

Following our integrated hierarchical modeling framework of natural gas internal reforming solid oxide fuel cell (IRSOFC), this paper firstly introduces the model libraries of main balancing units, including some state-of-the-art achievements and our specific work. Based on gPROMS programming code, flexible configuration and modular design are fully realized by specifying graphically all unit models in each level. Via comparison with the steady-state experimental data of Siemens-Westinghouse demonstration system, the in-house multi-level SOFC-gas turbine (GT) simulation platform is validated to be more accurate than the advanced power system analysis tool (APSAT). Moreover, some units of the demonstration system are designed reversely for analysis of a typically part-load transient process. The framework of distributed and dynamic modeling in most of units is significant for the development of control strategies in the future.

LISA Framework for Enhancing Gravitational Wave Signal Extraction Techniques

NASA Technical Reports Server (NTRS)

Thompson, David E.; Thirumalainambi, Rajkumar

2006-01-01

This paper describes the development of a Framework for benchmarking and comparing signal-extraction and noise-interference-removal methods that are applicable to interferometric Gravitational Wave detector systems. The primary use is towards comparing signal and noise extraction techniques at LISA frequencies from multiple (possibly confused) ,gravitational wave sources. The Framework includes extensive hybrid learning/classification algorithms, as well as post-processing regularization methods, and is based on a unique plug-and-play (component) architecture. Published methods for signal extraction and interference removal at LISA Frequencies are being encoded, as well as multiple source noise models, so that the stiffness of GW Sensitivity Space can be explored under each combination of methods. Furthermore, synthetic datasets and source models can be created and imported into the Framework, and specific degraded numerical experiments can be run to test the flexibility of the analysis methods. The Framework also supports use of full current LISA Testbeds, Synthetic data systems, and Simulators already in existence through plug-ins and wrappers, thus preserving those legacy codes and systems in tact. Because of the component-based architecture, all selected procedures can be registered or de-registered at run-time, and are completely reusable, reconfigurable, and modular.

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.

An Overview of Atmospheric Composition OSSE Activities at NASA's Global Modeling and Assimilation Office

NASA Technical Reports Server (NTRS)

daSilva, Arlinda

2012-01-01

A model-based Observing System Simulation Experiment (OSSE) is a framework for numerical experimentation in which observables are simulated from fields generated by an earth system model, including a parameterized description of observational error characteristics. Simulated observations can be used for sampling studies, quantifying errors in analysis or retrieval algorithms, and ultimately being a planning tool for designing new observing missions. While this framework has traditionally been used to assess the impact of observations on numerical weather prediction, it has a much broader applicability, in particular to aerosols and chemical constituents. In this talk we will give a general overview of Observing System Simulation Experiments (OSSE) activities at NASA's Global Modeling and Assimilation Office, with focus on its emerging atmospheric composition component.

Data Management System for the National Energy-Water System (NEWS) Assessment Framework

NASA Astrophysics Data System (ADS)

Corsi, F.; Prousevitch, A.; Glidden, S.; Piasecki, M.; Celicourt, P.; Miara, A.; Fekete, B. M.; Vorosmarty, C. J.; Macknick, J.; Cohen, S. M.

2015-12-01

Aiming at providing a comprehensive assessment of the water-energy nexus, the National Energy-Water System (NEWS) project requires the integration of data to support a modeling framework that links climate, hydrological, power production, transmission, and economical models. Large amounts of Georeferenced data has to be streamed to the components of the inter-disciplinary model to explore future challenges and tradeoffs in the US power production, based on climate scenarios, power plant locations and technologies, available water resources, ecosystem sustainability, and economic demand. We used open source and in-house build software components to build a system that addresses two major data challenges: On-the-fly re-projection, re-gridding, interpolation, extrapolation, nodata patching, merging, temporal and spatial aggregation, of static and time series datasets in virtually any file formats and file structures, and any geographic extent for the models I/O, directly at run time; Comprehensive data management based on metadata cataloguing and discovery in repositories utilizing the MAGIC Table (Manipulation and Geographic Inquiry Control database). This innovative concept allows models to access data on-the-fly by data ID, irrespective of file path, file structure, file format and regardless its GIS specifications. In addition, a web-based information and computational system is being developed to control the I/O of spatially distributed Earth system, climate, and hydrological, power grid, and economical data flow within the NEWS framework. The system allows scenario building, data exploration, visualization, querying, and manipulation any loaded gridded, point, and vector polygon dataset. The system has demonstrated its potential for applications in other fields of Earth science modeling, education, and outreach. Over time, this implementation of the system will provide near real-time assessment of various current and future scenarios of the water-energy nexus.

Abstraction and Assume-Guarantee Reasoning for Automated Software Verification

NASA Technical Reports Server (NTRS)

Chaki, S.; Clarke, E.; Giannakopoulou, D.; Pasareanu, C. S.

2004-01-01

Compositional verification and abstraction are the key techniques to address the state explosion problem associated with model checking of concurrent software. A promising compositional approach is to prove properties of a system by checking properties of its components in an assume-guarantee style. This article proposes a framework for performing abstraction and assume-guarantee reasoning of concurrent C code in an incremental and fully automated fashion. The framework uses predicate abstraction to extract and refine finite state models of software and it uses an automata learning algorithm to incrementally construct assumptions for the compositional verification of the abstract models. The framework can be instantiated with different assume-guarantee rules. We have implemented our approach in the COMFORT reasoning framework and we show how COMFORT out-performs several previous software model checking approaches when checking safety properties of non-trivial concurrent programs.

Complex multidisciplinary system composition for aerospace vehicle conceptual design

NASA Astrophysics Data System (ADS)

Gonzalez, Lex

Although, there exists a vast amount of work concerning the analysis, design, integration of aerospace vehicle systems, there is no standard for how this data and knowledge should be combined in order to create a synthesis system. Each institution creating a synthesis system has in house vehicle and hardware components they are attempting to model and proprietary methods with which to model them. This leads to the fact that synthesis systems begin as one-off creations meant to answer a specific problem. As the scope of the synthesis system grows to encompass more and more problems, so does its size and complexity; in order for a single synthesis system to answer multiple questions the number of methods and method interface must increase. As a means to curtail the requirement that the increase of an aircraft synthesis systems capability leads to an increase in its size and complexity, this research effort focuses on the idea that each problem in aerospace requires its own analysis framework. By focusing on the creation of a methodology which centers on the matching of an analysis framework towards the problem being solved, the complexity of the analysis framework is decoupled from the complexity of the system that creates it. The derived methodology allows for the composition of complex multi-disciplinary systems (CMDS) through the automatic creation and implementation of system and disciplinary method interfaces. The CMDS Composition process follows a four step methodology meant to take a problem definition and progress towards the creation of an analysis framework meant to answer said problem. The unique implementation of the CMDS Composition process take user selected disciplinary analysis methods and automatically integrates them, together in order to create a syntactically composable analysis framework. As a means of assessing the validity of the CMDS Composition process a prototype system (AVDDBMS) has been developed. AVD DBMS has been used to model the Generic Hypersonic Vehicle (GHV), an open source family of hypersonic vehicles originating from the Air Force Research Laboratory. AVDDBMS has been applied in three different ways in order to assess its validity: Verification using GHV disciplinary data, Validation using selected disciplinary analysis methods, and Application of the CMDS Composition Process to assess the design solution space for the GHV hardware. The research demonstrates the holistic effect that selection of individual disciplinary analysis methods has on the structure and integration of the analysis framework.

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

Care Delivery for Filipino Americans Using the Neuman Systems Model

PubMed Central

Angosta, Alona D.; Ceria-Ulep, Clementina D.; Tse, Alice M.

2016-01-01

Filipino Americans are at risk of coronary heart disease due to the presence of multiple cardiometabolic factors. Selecting a framework that addresses the factors leading to coronary heart disease is vital when providing care for this population. The Neuman systems model is a comprehensive and wholistic framework that offers an innovative method of viewing clients, their families, and the healthcare system across multiple dimensions. Using the Neuman systems model, advanced practice nurses can develop and implement interventions that will help reduce the potential cardiovascular problems of clients with multiple risk factors. The authors in this article provides insight into the cardiovascular health of Filipino Americans and has implications for nurses and other healthcare providers working with various Southeast Asian groups in the United States. PMID:24740949

Toward a consistent modeling framework to assess multi-sectoral climate impacts.

PubMed

Monier, Erwan; Paltsev, Sergey; Sokolov, Andrei; Chen, Y-H Henry; Gao, Xiang; Ejaz, Qudsia; Couzo, Evan; Schlosser, C Adam; Dutkiewicz, Stephanie; Fant, Charles; Scott, Jeffery; Kicklighter, David; Morris, Jennifer; Jacoby, Henry; Prinn, Ronald; Haigh, Martin

2018-02-13

Efforts to estimate the physical and economic impacts of future climate change face substantial challenges. To enrich the currently popular approaches to impact analysis-which involve evaluation of a damage function or multi-model comparisons based on a limited number of standardized scenarios-we propose integrating a geospatially resolved physical representation of impacts into a coupled human-Earth system modeling framework. Large internationally coordinated exercises cannot easily respond to new policy targets and the implementation of standard scenarios across models, institutions and research communities can yield inconsistent estimates. Here, we argue for a shift toward the use of a self-consistent integrated modeling framework to assess climate impacts, and discuss ways the integrated assessment modeling community can move in this direction. We then demonstrate the capabilities of such a modeling framework by conducting a multi-sectoral assessment of climate impacts under a range of consistent and integrated economic and climate scenarios that are responsive to new policies and business expectations.

Design of Knowledge Management System for Diabetic Complication Diseases

NASA Astrophysics Data System (ADS)

Fiarni, Cut

2017-01-01

This paper examines how to develop a Model for Knowledge Management System (KMS) for diabetes complication diseases. People with diabetes have a higher risk of developing a series of serious health problems. Each patient has different condition that could lead to different disease and health problem. But, with the right information, patient could have early detection so the health risk could be minimized and avoided. Hence, the objective of this research is to propose a conceptual framework that integrates social network model, Knowledge Management activities, and content based reasoning (CBR) for designing such a diabetes health and complication disease KMS. The framework indicates that the critical knowledge management activities are in the process to find similar case and the index table for algorithm to fit the framework for the social media. With this framework, KMS developers can work with healthcare provider to easily identify the suitable IT associated with the CBR process when developing a diabetes KMS.

Integration of RAM-SCB into the Space Weather Modeling Framework

DOE PAGES

Welling, Daniel; Toth, Gabor; Jordanova, Vania Koleva; ...

2018-02-07

We present that numerical simulations of the ring current are a challenging endeavor. They require a large set of inputs, including electric and magnetic fields and plasma sheet fluxes. Because the ring current broadly affects the magnetosphere-ionosphere system, the input set is dependent on the ring current region itself. This makes obtaining a set of inputs that are self-consistent with the ring current difficult. To overcome this challenge, researchers have begun coupling ring current models to global models of the magnetosphere-ionosphere system. This paper describes the coupling between the Ring current Atmosphere interaction Model with Self-Consistent Magnetic field (RAM-SCB) tomore » the models within the Space Weather Modeling Framework. Full details on both previously introduced and new coupling mechanisms are defined. Finally, the impact of self-consistently including the ring current on the magnetosphere-ionosphere system is illustrated via a set of example simulations.« less

Integration of RAM-SCB into the Space Weather Modeling Framework

DOE Office of Scientific and Technical Information (OSTI.GOV)

Welling, Daniel; Toth, Gabor; Jordanova, Vania Koleva

We present that numerical simulations of the ring current are a challenging endeavor. They require a large set of inputs, including electric and magnetic fields and plasma sheet fluxes. Because the ring current broadly affects the magnetosphere-ionosphere system, the input set is dependent on the ring current region itself. This makes obtaining a set of inputs that are self-consistent with the ring current difficult. To overcome this challenge, researchers have begun coupling ring current models to global models of the magnetosphere-ionosphere system. This paper describes the coupling between the Ring current Atmosphere interaction Model with Self-Consistent Magnetic field (RAM-SCB) tomore » the models within the Space Weather Modeling Framework. Full details on both previously introduced and new coupling mechanisms are defined. Finally, the impact of self-consistently including the ring current on the magnetosphere-ionosphere system is illustrated via a set of example simulations.« less

A discrete model to study reaction-diffusion-mechanics systems.

PubMed

Weise, Louis D; Nash, Martyn P; Panfilov, Alexander V

2011-01-01

This article introduces a discrete reaction-diffusion-mechanics (dRDM) model to study the effects of deformation on reaction-diffusion (RD) processes. The dRDM framework employs a FitzHugh-Nagumo type RD model coupled to a mass-lattice model, that undergoes finite deformations. The dRDM model describes a material whose elastic properties are described by a generalized Hooke's law for finite deformations (Seth material). Numerically, the dRDM approach combines a finite difference approach for the RD equations with a Verlet integration scheme for the equations of the mass-lattice system. Using this framework results were reproduced on self-organized pacemaking activity that have been previously found with a continuous RD mechanics model. Mechanisms that determine the period of pacemakers and its dependency on the medium size are identified. Finally it is shown how the drift direction of pacemakers in RDM systems is related to the spatial distribution of deformation and curvature effects.

A Discrete Model to Study Reaction-Diffusion-Mechanics Systems

PubMed Central

Weise, Louis D.; Nash, Martyn P.; Panfilov, Alexander V.

2011-01-01

This article introduces a discrete reaction-diffusion-mechanics (dRDM) model to study the effects of deformation on reaction-diffusion (RD) processes. The dRDM framework employs a FitzHugh-Nagumo type RD model coupled to a mass-lattice model, that undergoes finite deformations. The dRDM model describes a material whose elastic properties are described by a generalized Hooke's law for finite deformations (Seth material). Numerically, the dRDM approach combines a finite difference approach for the RD equations with a Verlet integration scheme for the equations of the mass-lattice system. Using this framework results were reproduced on self-organized pacemaking activity that have been previously found with a continuous RD mechanics model. Mechanisms that determine the period of pacemakers and its dependency on the medium size are identified. Finally it is shown how the drift direction of pacemakers in RDM systems is related to the spatial distribution of deformation and curvature effects. PMID:21804911

A unified structural/terminological interoperability framework based on LexEVS: application to TRANSFoRm.

PubMed

Ethier, Jean-François; Dameron, Olivier; Curcin, Vasa; McGilchrist, Mark M; Verheij, Robert A; Arvanitis, Theodoros N; Taweel, Adel; Delaney, Brendan C; Burgun, Anita

2013-01-01

Biomedical research increasingly relies on the integration of information from multiple heterogeneous data sources. Despite the fact that structural and terminological aspects of interoperability are interdependent and rely on a common set of requirements, current efforts typically address them in isolation. We propose a unified ontology-based knowledge framework to facilitate interoperability between heterogeneous sources, and investigate if using the LexEVS terminology server is a viable implementation method. We developed a framework based on an ontology, the general information model (GIM), to unify structural models and terminologies, together with relevant mapping sets. This allowed a uniform access to these resources within LexEVS to facilitate interoperability by various components and data sources from implementing architectures. Our unified framework has been tested in the context of the EU Framework Program 7 TRANSFoRm project, where it was used to achieve data integration in a retrospective diabetes cohort study. The GIM was successfully instantiated in TRANSFoRm as the clinical data integration model, and necessary mappings were created to support effective information retrieval for software tools in the project. We present a novel, unifying approach to address interoperability challenges in heterogeneous data sources, by representing structural and semantic models in one framework. Systems using this architecture can rely solely on the GIM that abstracts over both the structure and coding. Information models, terminologies and mappings are all stored in LexEVS and can be accessed in a uniform manner (implementing the HL7 CTS2 service functional model). The system is flexible and should reduce the effort needed from data sources personnel for implementing and managing the integration.

A unified structural/terminological interoperability framework based on LexEVS: application to TRANSFoRm

PubMed Central

Ethier, Jean-François; Dameron, Olivier; Curcin, Vasa; McGilchrist, Mark M; Verheij, Robert A; Arvanitis, Theodoros N; Taweel, Adel; Delaney, Brendan C; Burgun, Anita

2013-01-01

Objective Biomedical research increasingly relies on the integration of information from multiple heterogeneous data sources. Despite the fact that structural and terminological aspects of interoperability are interdependent and rely on a common set of requirements, current efforts typically address them in isolation. We propose a unified ontology-based knowledge framework to facilitate interoperability between heterogeneous sources, and investigate if using the LexEVS terminology server is a viable implementation method. Materials and methods We developed a framework based on an ontology, the general information model (GIM), to unify structural models and terminologies, together with relevant mapping sets. This allowed a uniform access to these resources within LexEVS to facilitate interoperability by various components and data sources from implementing architectures. Results Our unified framework has been tested in the context of the EU Framework Program 7 TRANSFoRm project, where it was used to achieve data integration in a retrospective diabetes cohort study. The GIM was successfully instantiated in TRANSFoRm as the clinical data integration model, and necessary mappings were created to support effective information retrieval for software tools in the project. Conclusions We present a novel, unifying approach to address interoperability challenges in heterogeneous data sources, by representing structural and semantic models in one framework. Systems using this architecture can rely solely on the GIM that abstracts over both the structure and coding. Information models, terminologies and mappings are all stored in LexEVS and can be accessed in a uniform manner (implementing the HL7 CTS2 service functional model). The system is flexible and should reduce the effort needed from data sources personnel for implementing and managing the integration. PMID:23571850

Incident Management in Academic Information System using ITIL Framework

NASA Astrophysics Data System (ADS)

Palilingan, V. R.; Batmetan, J. R.

2018-02-01

Incident management is very important in order to ensure the continuity of a system. Information systems require incident management to ensure information systems can provide maximum service according to the service provided. Many of the problems that arise in academic information systems come from incidents that are not properly handled. The objective of this study aims to find the appropriate way of incident management. The incident can be managed so it will not be a big problem. This research uses the ITIL framework to solve incident problems. The technique used in this study is a technique adopted and developed from the service operations section of the ITIL framework. The results of this research found that 84.5% of incidents appearing in academic information systems can be handled quickly and appropriately. 15.5% incidents can be escalated so as to not cause any new problems. The model of incident management applied to make academic information system can run quickly in providing academic service in a good and efficient. The incident management model implemented in this research is able to manage resources appropriately so as to quickly and easily manage incidents.

From complexity to reality: providing useful frameworks for defining systems of care.

PubMed

Levison-Johnson, Jody; Wenz-Gross, Melodie

2010-02-01

Because systems of care are not uniform across communities, there is a need to better document the process of system development, define the complexity, and describe the development of the structures, processes, and relationships within communities engaged in system transformation. By doing so, we begin to identify the necessary and sufficient components that, at minimum, move us from usual care within a naturally occurring system to a true system of care. Further, by documenting and measuring the degree to which key components are operating, we may be able to identify the most successful strategies in creating system reform. The theory of change and logic model offer a useful framework for communities to begin the adaptive work necessary to effect true transformation. Using the experience of two system of care communities, this new definition and the utility of a theory of change and logic model framework for defining local system transformation efforts will be discussed. Implications for the field, including the need to further examine the natural progression of systems change and to create quantifiable measures of transformation, will be raised as new challenges for the evolving system of care movement.

Framework Programmable Platform for the Advanced Software Development Workstation (FPP/ASDW). Demonstration framework document. Volume 1: Concepts and activity descriptions

NASA Technical Reports Server (NTRS)

Mayer, Richard J.; Blinn, Thomas M.; Dewitte, Paul S.; Crump, John W.; Ackley, Keith A.

1992-01-01

The Framework Programmable Software Development Platform (FPP) is a project aimed at effectively combining tool and data integration mechanisms with a model of the software development process to provide an intelligent integrated software development environment. Guided by the model, this system development framework will take advantage of an integrated operating environment to automate effectively the management of the software development process so that costly mistakes during the development phase can be eliminated. The Advanced Software Development Workstation (ASDW) program is conducting research into development of advanced technologies for Computer Aided Software Engineering (CASE).

Interactive classification and content-based retrieval of tissue images

NASA Astrophysics Data System (ADS)

Aksoy, Selim; Marchisio, Giovanni B.; Tusk, Carsten; Koperski, Krzysztof

2002-11-01

We describe a system for interactive classification and retrieval of microscopic tissue images. Our system models tissues in pixel, region and image levels. Pixel level features are generated using unsupervised clustering of color and texture values. Region level features include shape information and statistics of pixel level feature values. Image level features include statistics and spatial relationships of regions. To reduce the gap between low-level features and high-level expert knowledge, we define the concept of prototype regions. The system learns the prototype regions in an image collection using model-based clustering and density estimation. Different tissue types are modeled using spatial relationships of these regions. Spatial relationships are represented by fuzzy membership functions. The system automatically selects significant relationships from training data and builds models which can also be updated using user relevance feedback. A Bayesian framework is used to classify tissues based on these models. Preliminary experiments show that the spatial relationship models we developed provide a flexible and powerful framework for classification and retrieval of tissue images.

An Education for Peace Model That Centres on Belief Systems: The Theory behind The Model

ERIC Educational Resources Information Center

Willis, Alison

2017-01-01

The education for peace model (EFPM) presented in this paper was developed within a theoretical framework of complexity science and critical theory and was derived from a review of an empirical research project conducted in a conflict affected environment. The model positions belief systems at the centre and is socioecologically systemic in design…

Surrogate assisted multidisciplinary design optimization for an all-electric GEO satellite

NASA Astrophysics Data System (ADS)

Shi, Renhe; Liu, Li; Long, Teng; Liu, Jian; Yuan, Bin

2017-09-01

State-of-the-art all-electric geostationary earth orbit (GEO) satellites use electric thrusters to execute all propulsive duties, which significantly differ from the traditional all-chemical ones in orbit-raising, station-keeping, radiation damage protection, and power budget, etc. Design optimization task of an all-electric GEO satellite is therefore a complex multidisciplinary design optimization (MDO) problem involving unique design considerations. However, solving the all-electric GEO satellite MDO problem faces big challenges in disciplinary modeling techniques and efficient optimization strategy. To address these challenges, we presents a surrogate assisted MDO framework consisting of several modules, i.e., MDO problem definition, multidisciplinary modeling, multidisciplinary analysis (MDA), and surrogate assisted optimizer. Based on the proposed framework, the all-electric GEO satellite MDO problem is formulated to minimize the total mass of the satellite system under a number of practical constraints. Then considerable efforts are spent on multidisciplinary modeling involving geosynchronous transfer, GEO station-keeping, power, thermal control, attitude control, and structure disciplines. Since orbit dynamics models and finite element structural model are computationally expensive, an adaptive response surface surrogate based optimizer is incorporated in the proposed framework to solve the satellite MDO problem with moderate computational cost, where a response surface surrogate is gradually refined to represent the computationally expensive MDA process. After optimization, the total mass of the studied GEO satellite is decreased by 185.3 kg (i.e., 7.3% of the total mass). Finally, the optimal design is further discussed to demonstrate the effectiveness of our proposed framework to cope with the all-electric GEO satellite system design optimization problems. This proposed surrogate assisted MDO framework can also provide valuable references for other all-electric spacecraft system design.

Dealing with equality and benefit for water allocation in a lake watershed: A Gini-coefficient based stochastic optimization approach

NASA Astrophysics Data System (ADS)

Dai, C.; Qin, X. S.; Chen, Y.; Guo, H. C.

2018-06-01

A Gini-coefficient based stochastic optimization (GBSO) model was developed by integrating the hydrological model, water balance model, Gini coefficient and chance-constrained programming (CCP) into a general multi-objective optimization modeling framework for supporting water resources allocation at a watershed scale. The framework was advantageous in reflecting the conflicting equity and benefit objectives for water allocation, maintaining the water balance of watershed, and dealing with system uncertainties. GBSO was solved by the non-dominated sorting Genetic Algorithms-II (NSGA-II), after the parameter uncertainties of the hydrological model have been quantified into the probability distribution of runoff as the inputs of CCP model, and the chance constraints were converted to the corresponding deterministic versions. The proposed model was applied to identify the Pareto optimal water allocation schemes in the Lake Dianchi watershed, China. The optimal Pareto-front results reflected the tradeoff between system benefit (αSB) and Gini coefficient (αG) under different significance levels (i.e. q) and different drought scenarios, which reveals the conflicting nature of equity and efficiency in water allocation problems. A lower q generally implies a lower risk of violating the system constraints and a worse drought intensity scenario corresponds to less available water resources, both of which would lead to a decreased system benefit and a less equitable water allocation scheme. Thus, the proposed modeling framework could help obtain the Pareto optimal schemes under complexity and ensure that the proposed water allocation solutions are effective for coping with drought conditions, with a proper tradeoff between system benefit and water allocation equity.

A computational framework for prime implicants identification in noncoherent dynamic systems.

PubMed

Di Maio, Francesco; Baronchelli, Samuele; Zio, Enrico

2015-01-01

Dynamic reliability methods aim at complementing the capability of traditional static approaches (e.g., event trees [ETs] and fault trees [FTs]) by accounting for the system dynamic behavior and its interactions with the system state transition process. For this, the system dynamics is here described by a time-dependent model that includes the dependencies with the stochastic transition events. In this article, we present a novel computational framework for dynamic reliability analysis whose objectives are i) accounting for discrete stochastic transition events and ii) identifying the prime implicants (PIs) of the dynamic system. The framework entails adopting a multiple-valued logic (MVL) to consider stochastic transitions at discretized times. Then, PIs are originally identified by a differential evolution (DE) algorithm that looks for the optimal MVL solution of a covering problem formulated for MVL accident scenarios. For testing the feasibility of the framework, a dynamic noncoherent system composed of five components that can fail at discretized times has been analyzed, showing the applicability of the framework to practical cases. © 2014 Society for Risk Analysis.

Three-dimensional hydrogeologic framework model of the Rio Grande transboundary region of New Mexico and Texas, USA, and northern Chihuahua, Mexico

USGS Publications Warehouse

Sweetkind, Donald S.

2017-09-08

As part of a U.S. Geological Survey study in cooperation with the Bureau of Reclamation, a digital three-dimensional hydrogeologic framework model was constructed for the Rio Grande transboundary region of New Mexico and Texas, USA, and northern Chihuahua, Mexico. This model was constructed to define the aquifer system geometry and subsurface lithologic characteristics and distribution for use in a regional numerical hydrologic model. The model includes five hydrostratigraphic units: river channel alluvium, three informal subdivisions of Santa Fe Group basin fill, and an undivided pre-Santa Fe Group bedrock unit. Model input data were compiled from published cross sections, well data, structure contour maps, selected geophysical data, and contiguous compilations of surficial geology and structural features in the study area. These data were used to construct faulted surfaces that represent the upper and lower subsurface hydrostratigraphic unit boundaries. The digital three-dimensional hydrogeologic framework model is constructed through combining faults, the elevation of the tops of each hydrostratigraphic unit, and boundary lines depicting the subsurface extent of each hydrostratigraphic unit. The framework also compiles a digital representation of the distribution of sedimentary facies within each hydrostratigraphic unit. The digital three-dimensional hydrogeologic model reproduces with reasonable accuracy the previously published subsurface hydrogeologic conceptualization of the aquifer system and represents the large-scale geometry of the subsurface aquifers. The model is at a scale and resolution appropriate for use as the foundation for a numerical hydrologic model of the study area.

Health systems frameworks in their political context: framing divergent agendas

PubMed Central

2012-01-01

Background Despite the mounting attention for health systems and health systems theories, there is a persisting lack of consensus on their conceptualisation and strengthening. This paper contributes to structuring the debate, presenting landmarks in the development of health systems thinking against the backdrop of the policy context and its dominant actors. We argue that frameworks on health systems are products of their time, emerging from specific discourses. They are purposive, not neutrally descriptive, and are shaped by the agendas of their authors. Discussion The evolution of thinking over time does not reflect a progressive accumulation of insights. Instead, theories and frameworks seem to develop in reaction to one another, partly in line with prevailing paradigms and partly as a response to the very different needs of their developers. The reform perspective considering health systems as projects to be engineered is fundamentally different from the organic view that considers a health system as a mirror of society. The co-existence of health systems and disease-focused approaches indicates that different frameworks are complementary but not synthetic. The contestation of theories and methods for health systems relates almost exclusively to low income countries. At the global level, health system strengthening is largely narrowed down to its instrumental dimension, whereby well-targeted and specific interventions are supposed to strengthen health services and systems or, more selectively, specific core functions essential to programmes. This is in contrast to a broader conceptualization of health systems as social institutions. Summary Health systems theories and frameworks frame health, health systems and policies in particular political and public health paradigms. While there is a clear trend to try to understand the complexity of and dynamic relationships between elements of health systems, there is also a demand to provide frameworks that distinguish between health system interventions, and that allow mapping with a view of analysing their returns. The choice for a particular health system model to guide discussions and work should fit the purpose. The understanding of the underlying rationale of a chosen model facilitates an open dialogue about purpose and strategy. PMID:22971107

A Source-Term Based Boundary Layer Bleed/Effusion Model for Passive Shock Control

NASA Technical Reports Server (NTRS)

Baurle, Robert A.; Norris, Andrew T.

2011-01-01

A modeling framework for boundary layer effusion has been developed based on the use of source (or sink) terms instead of the usual practice of specifying bleed directly as a boundary condition. This framework allows the surface boundary condition (i.e. isothermal wall, adiabatic wall, slip wall, etc.) to remain unaltered in the presence of bleed. This approach also lends itself to easily permit the addition of empirical models for second order effects that are not easily accounted for by simply defining effective transpiration values. Two effusion models formulated for supersonic flows have been implemented into this framework; the Doerffer/Bohning law and the Slater formulation. These models were applied to unit problems that contain key aspects of the flow physics applicable to bleed systems designed for hypersonic air-breathing propulsion systems. The ability of each model to predict bulk bleed properties was assessed, as well as the response of the boundary layer as it passes through and downstream of a porous bleed system. The model assessment was performed with and without the presence of shock waves. Three-dimensional CFD simulations that included the geometric details of the porous plate bleed systems were also carried out to supplement the experimental data, and provide additional insights into the bleed flow physics. Overall, both bleed formulations fared well for the tests performed in this study. However, the sample of test problems considered in this effort was not large enough to permit a comprehensive validation of the models.

Protein solubility modeling

NASA Technical Reports Server (NTRS)

Agena, S. M.; Pusey, M. L.; Bogle, I. D.

1999-01-01

A thermodynamic framework (UNIQUAC model with temperature dependent parameters) is applied to model the salt-induced protein crystallization equilibrium, i.e., protein solubility. The framework introduces a term for the solubility product describing protein transfer between the liquid and solid phase and a term for the solution behavior describing deviation from ideal solution. Protein solubility is modeled as a function of salt concentration and temperature for a four-component system consisting of a protein, pseudo solvent (water and buffer), cation, and anion (salt). Two different systems, lysozyme with sodium chloride and concanavalin A with ammonium sulfate, are investigated. Comparison of the modeled and experimental protein solubility data results in an average root mean square deviation of 5.8%, demonstrating that the model closely follows the experimental behavior. Model calculations and model parameters are reviewed to examine the model and protein crystallization process. Copyright 1999 John Wiley & Sons, Inc.

Integrative systems modeling and multi-objective optimization

EPA Science Inventory

This presentation presents a number of algorithms, tools, and methods for utilizing multi-objective optimization within integrated systems modeling frameworks. We first present innovative methods using a genetic algorithm to optimally calibrate the VELMA and SWAT ecohydrological ...

Quantifying and reducing model-form uncertainties in Reynolds-averaged Navier–Stokes simulations: A data-driven, physics-informed Bayesian approach

DOE Office of Scientific and Technical Information (OSTI.GOV)

Xiao, H., E-mail: hengxiao@vt.edu; Wu, J.-L.; Wang, J.-X.

Despite their well-known limitations, Reynolds-Averaged Navier–Stokes (RANS) models are still the workhorse tools for turbulent flow simulations in today's engineering analysis, design and optimization. While the predictive capability of RANS models depends on many factors, for many practical flows the turbulence models are by far the largest source of uncertainty. As RANS models are used in the design and safety evaluation of many mission-critical systems such as airplanes and nuclear power plants, quantifying their model-form uncertainties has significant implications in enabling risk-informed decision-making. In this work we develop a data-driven, physics-informed Bayesian framework for quantifying model-form uncertainties in RANS simulations.more » Uncertainties are introduced directly to the Reynolds stresses and are represented with compact parameterization accounting for empirical prior knowledge and physical constraints (e.g., realizability, smoothness, and symmetry). An iterative ensemble Kalman method is used to assimilate the prior knowledge and observation data in a Bayesian framework, and to propagate them to posterior distributions of velocities and other Quantities of Interest (QoIs). We use two representative cases, the flow over periodic hills and the flow in a square duct, to evaluate the performance of the proposed framework. Both cases are challenging for standard RANS turbulence models. Simulation results suggest that, even with very sparse observations, the obtained posterior mean velocities and other QoIs have significantly better agreement with the benchmark data compared to the baseline results. At most locations the posterior distribution adequately captures the true model error within the developed model form uncertainty bounds. The framework is a major improvement over existing black-box, physics-neutral methods for model-form uncertainty quantification, where prior knowledge and details of the models are not exploited. This approach has potential implications in many fields in which the governing equations are well understood but the model uncertainty comes from unresolved physical processes. - Highlights: • Proposed a physics–informed framework to quantify uncertainty in RANS simulations. • Framework incorporates physical prior knowledge and observation data. • Based on a rigorous Bayesian framework yet fully utilizes physical model. • Applicable for many complex physical systems beyond turbulent flows.« less

Model-free inference of direct network interactions from nonlinear collective dynamics.

PubMed

Casadiego, Jose; Nitzan, Mor; Hallerberg, Sarah; Timme, Marc

2017-12-19

The topology of interactions in network dynamical systems fundamentally underlies their function. Accelerating technological progress creates massively available data about collective nonlinear dynamics in physical, biological, and technological systems. Detecting direct interaction patterns from those dynamics still constitutes a major open problem. In particular, current nonlinear dynamics approaches mostly require to know a priori a model of the (often high dimensional) system dynamics. Here we develop a model-independent framework for inferring direct interactions solely from recording the nonlinear collective dynamics generated. Introducing an explicit dependency matrix in combination with a block-orthogonal regression algorithm, the approach works reliably across many dynamical regimes, including transient dynamics toward steady states, periodic and non-periodic dynamics, and chaos. Together with its capabilities to reveal network (two point) as well as hypernetwork (e.g., three point) interactions, this framework may thus open up nonlinear dynamics options of inferring direct interaction patterns across systems where no model is known.

Modelling Biogeochemistry Across Domains with The Modular System for Shelves and Coasts (MOSSCO)

NASA Astrophysics Data System (ADS)

Burchard, H.; Lemmen, C.; Hofmeister, R.; Knut, K.; Nasermoaddeli, M. H.; Kerimoglu, O.; Koesters, F.; Wirtz, K.

2016-02-01

Coastal biogeochemical processes extend from the atmosphere through the water column and the epibenthos into the ocean floor, laterally they are determined by freshwater inflows and open water exchange, and in situ they are mediated by physical, chemical and biological interactions. We use the new Modular System for Shelves and Coasts (MOSSCO, http://www.mossco.de) to obtain an integrated view of coastal biogeochemistry. MOSSCO is a coupling framework that builds on existing coupling technologies like the Earth System Modeling Framework (ESMF, for domain-coupling) and the Framework for Aquatic Biogeochemistry (FABM, for process coupling). MOSSCO facilitates the communication about and the integration of existing and of new process models into a threedimensional regional coastal modelling context. In the MOSSCO concept, the integrating framework imposes very few restrictions on contributed data or models; in fact, there is no distinction made between data and models. The few requirements are: (1) principle coupleability, i.e. access to I/O and timing information in submodels, which has recently been referred to as the Basic Model Interface (BMI) (2) open source/open data access and licencing and (3) communication of metadata, such as spatiotemporal information, naming conventions, and physical units. These requirements suffice to integrate different models and data sets into the MOSSCO infrastructure and subsequently built a modular integrated modeling tool that can span a diversity of processes and domains. Here, we demonstrate a MOSSCO application for the southern North Sea, where atmospheric deposition, biochemical processing in the water column and the ocean floor, lateral nutrient replenishment, and wave- and current-dependent remobilization from sediments are accounted for by modular components. A multi-annual simulation yields realistic succession of the spatial gradients of dissolved nutrients, of chlorophyll variability and gross primary production rates and of benthic denitrification rates for this intriguing coastal system.

A framework for evolutionary systems biology

PubMed Central

Loewe, Laurence

2009-01-01

Background Many difficult problems in evolutionary genomics are related to mutations that have weak effects on fitness, as the consequences of mutations with large effects are often simple to predict. Current systems biology has accumulated much data on mutations with large effects and can predict the properties of knockout mutants in some systems. However experimental methods are too insensitive to observe small effects. Results Here I propose a novel framework that brings together evolutionary theory and current systems biology approaches in order to quantify small effects of mutations and their epistatic interactions in silico. Central to this approach is the definition of fitness correlates that can be computed in some current systems biology models employing the rigorous algorithms that are at the core of much work in computational systems biology. The framework exploits synergies between the realism of such models and the need to understand real systems in evolutionary theory. This framework can address many longstanding topics in evolutionary biology by defining various 'levels' of the adaptive landscape. Addressed topics include the distribution of mutational effects on fitness, as well as the nature of advantageous mutations, epistasis and robustness. Combining corresponding parameter estimates with population genetics models raises the possibility of testing evolutionary hypotheses at a new level of realism. Conclusion EvoSysBio is expected to lead to a more detailed understanding of the fundamental principles of life by combining knowledge about well-known biological systems from several disciplines. This will benefit both evolutionary theory and current systems biology. Understanding robustness by analysing distributions of mutational effects and epistasis is pivotal for drug design, cancer research, responsible genetic engineering in synthetic biology and many other practical applications. PMID:19239699

Using an Interactive Systems Framework to Expand Telepsychology Innovations in Underserved Communities

PubMed Central

Alaniz, Angela B.

2016-01-01

Literature indicates that the use of promising innovations in mental health care can be improved. The advancement of telepsychology is one innovation that has been utilized as a method to reduce rural health disparities and increase the number of people with access to mental health services. This paper describes a successful pilot telepsychology program implemented in a rural community to increase access to mental health services and the model's replication and expansion into four additional communities using concepts described in an Interactive Systems Framework. The Interactive Systems Framework highlights how building local capacity specific to organizational functioning and innovations are necessary to support, deliver, and disseminate innovations within new settings. Based on the knowledge gained from this telepsychology innovation, the application of an Interactive Systems Framework and funding mechanisms are discussed. PMID:27403374

Shared mental models of integrated care: aligning multiple stakeholder perspectives.

PubMed

Evans, Jenna M; Baker, G Ross

2012-01-01

Health service organizations and professionals are under increasing pressure to work together to deliver integrated patient care. A common understanding of integration strategies may facilitate the delivery of integrated care across inter-organizational and inter-professional boundaries. This paper aims to build a framework for exploring and potentially aligning multiple stakeholder perspectives of systems integration. The authors draw from the literature on shared mental models, strategic management and change, framing, stakeholder management, and systems theory to develop a new construct, Mental Models of Integrated Care (MMIC), which consists of three types of mental models, i.e. integration-task, system-role, and integration-belief. The MMIC construct encompasses many of the known barriers and enablers to integrating care while also providing a comprehensive, theory-based framework of psychological factors that may influence inter-organizational and inter-professional relations. While the existing literature on integration focuses on optimizing structures and processes, the MMIC construct emphasizes the convergence and divergence of stakeholders' knowledge and beliefs, and how these underlying cognitions influence interactions (or lack thereof) across the continuum of care. MMIC may help to: explain what differentiates effective from ineffective integration initiatives; determine system readiness to integrate; diagnose integration problems; and develop interventions for enhancing integrative processes and ultimately the delivery of integrated care. Global interest and ongoing challenges in integrating care underline the need for research on the mental models that characterize the behaviors of actors within health systems; the proposed framework offers a starting point for applying a cognitive perspective to health systems integration.

Risk-Informed Safety Assurance and Probabilistic Assessment of Mission-Critical Software-Intensive Systems

NASA Technical Reports Server (NTRS)

Guarro, Sergio B.

2010-01-01

This report validates and documents the detailed features and practical application of the framework for software intensive digital systems risk assessment and risk-informed safety assurance presented in the NASA PRA Procedures Guide for Managers and Practitioner. This framework, called herein the "Context-based Software Risk Model" (CSRM), enables the assessment of the contribution of software and software-intensive digital systems to overall system risk, in a manner which is entirely compatible and integrated with the format of a "standard" Probabilistic Risk Assessment (PRA), as currently documented and applied for NASA missions and applications. The CSRM also provides a risk-informed path and criteria for conducting organized and systematic digital system and software testing so that, within this risk-informed paradigm, the achievement of a quantitatively defined level of safety and mission success assurance may be targeted and demonstrated. The framework is based on the concept of context-dependent software risk scenarios and on the modeling of such scenarios via the use of traditional PRA techniques - i.e., event trees and fault trees - in combination with more advanced modeling devices such as the Dynamic Flowgraph Methodology (DFM) or other dynamic logic-modeling representations. The scenarios can be synthesized and quantified in a conditional logic and probabilistic formulation. The application of the CSRM method documented in this report refers to the MiniAERCam system designed and developed by the NASA Johnson Space Center.

V&V framework

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hills, Richard G.; Maniaci, David Charles; Naughton, Jonathan W.

2015-09-01

A Verification and Validation (V&V) framework is presented for the development and execution of coordinated modeling and experimental program s to assess the predictive capability of computational models of complex systems through focused, well structured, and formal processes.The elements of the framework are based on established V&V methodology developed by various organizations including the Department of Energy, National Aeronautics and Space Administration, the American Institute of Aeronautics and Astronautics, and the American Society of Mechanical Engineers. Four main topics are addressed: 1) Program planning based on expert elicitation of the modeling physics requirements, 2) experimental design for model assessment, 3)more » uncertainty quantification for experimental observations and computational model simulations, and 4) assessment of the model predictive capability. The audience for this document includes program planners, modelers, experimentalist, V &V specialist, and customers of the modeling results.« less

A hydroeconomic modeling framework for optimal integrated management of forest and water

NASA Astrophysics Data System (ADS)

Garcia-Prats, Alberto; del Campo, Antonio D.; Pulido-Velazquez, Manuel

2016-10-01

Forests play a determinant role in the hydrologic cycle, with water being the most important ecosystem service they provide in semiarid regions. However, this contribution is usually neither quantified nor explicitly valued. The aim of this study is to develop a novel hydroeconomic modeling framework for assessing and designing the optimal integrated forest and water management for forested catchments. The optimization model explicitly integrates changes in water yield in the stands (increase in groundwater recharge) induced by forest management and the value of the additional water provided to the system. The model determines the optimal schedule of silvicultural interventions in the stands of the catchment in order to maximize the total net benefit in the system. Canopy cover and biomass evolution over time were simulated using growth and yield allometric equations specific for the species in Mediterranean conditions. Silvicultural operation costs according to stand density and canopy cover were modeled using local cost databases. Groundwater recharge was simulated using HYDRUS, calibrated and validated with data from the experimental plots. In order to illustrate the presented modeling framework, a case study was carried out in a planted pine forest (Pinus halepensis Mill.) located in south-western Valencia province (Spain). The optimized scenario increased groundwater recharge. This novel modeling framework can be used in the design of a "payment for environmental services" scheme in which water beneficiaries could contribute to fund and promote efficient forest management operations.

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 using FSPMs. This structure can accommodate both previously developed models for individual aspects of pathosystems and new ones. Complex models are deconstructed into separate ‘knowledge sources’ originating from different specialist areas of expertise and these can be shared and reassembled into multidisciplinary models. The framework thus provides a beneficial tool for a potential diverse and dynamic research community. PMID:24925323

Transitioning from learning healthcare systems to learning health care communities.

PubMed

Mullins, C Daniel; Wingate, La'Marcus T; Edwards, Hillary A; Tofade, Toyin; Wutoh, Anthony

2018-02-26

The learning healthcare system (LHS) model framework has three core, foundational components. These include an infrastructure for health-related data capture, care improvement targets and a supportive policy environment. Despite progress in advancing and implementing LHS approaches, low levels of participation from patients and the public have hampered the transformational potential of the LHS model. An enhanced vision of a community-engaged LHS redesign would focus on the provision of health care from the patient and community perspective to complement the healthcare system as the entity that provides the environment for care. Addressing the LHS framework implementation challenges and utilizing community levers are requisite components of a learning health care community model, version two of the LHS archetype.

Off-Road Mobility Research

DTIC Science & Technology

1967-09-01

Lewandowski, Thomas R. Magorian, H. T. McAdams, James N. Naylor, Walter F. Wood -ii- VJ-2330-G-2 Section 6 Stephen C. Cowin, Vito De Palma, Patrick M. Miller...providing detailed inputs to a)). 2. The establishing of the general framework for the Phenomenological Model. 3. A prelim.na ry methodology study using the...of current practice in mathematical modeling of vehicle-terrain systems. 2) The establishing of the framework for a vehicle-terrain dynamics model as

Counseling Female Offenders and Victims: A Strengths-Restorative Approach. Springer Series on Family Violence.

ERIC Educational Resources Information Center

van Wormer, Katherine

This books considers the many aspects of how the criminal justice system can be reshaped to address the needs of victims of violence and offenders who themselves are often the victims of abuse. It presents a new model that offers an integrated framework to combine tenets of social work's strengths framework with the restorative justice model. It…

Towards a cyber-physical era: soft computing framework based multi-sensor array for water quality monitoring

NASA Astrophysics Data System (ADS)

Bhardwaj, Jyotirmoy; Gupta, Karunesh K.; Gupta, Rajiv

2018-02-01

New concepts and techniques are replacing traditional methods of water quality parameter measurement systems. This paper introduces a cyber-physical system (CPS) approach for water quality assessment in a distribution network. Cyber-physical systems with embedded sensors, processors and actuators can be designed to sense and interact with the water environment. The proposed CPS is comprised of sensing framework integrated with five different water quality parameter sensor nodes and soft computing framework for computational modelling. Soft computing framework utilizes the applications of Python for user interface and fuzzy sciences for decision making. Introduction of multiple sensors in a water distribution network generates a huge number of data matrices, which are sometimes highly complex, difficult to understand and convoluted for effective decision making. Therefore, the proposed system framework also intends to simplify the complexity of obtained sensor data matrices and to support decision making for water engineers through a soft computing framework. The target of this proposed research is to provide a simple and efficient method to identify and detect presence of contamination in a water distribution network using applications of CPS.

Understanding Global Change (UGC) as a Unifying Conceptual Framework for Teaching Ecology: Using UGC in a High School Biology Program to Integrate Earth Science and Biology, and to Demonstrate the Value of Modeling Global Systems in Promoting Conceptual Learning

NASA Astrophysics Data System (ADS)

Levine, J.; Bean, J. R.

2017-12-01

Global change science is ideal for NGSS-informed teaching, but presents a serious challenge to K-12 educators because it is complex and interdisciplinary- combining earth science, biology, chemistry, and physics. Global systems are themselves complex. Adding anthropogenic influences on those systems creates a formidable list of topics - greenhouse effect, climate change, nitrogen enrichment, introduced species, land-use change among them - which are often presented as a disconnected "laundry list" of "facts." This complexity, combined with public and mass-media scientific illiteracy, leaves global change science vulnerable to misrepresentation and politicization, creating additional challenges to teachers in public schools. Ample stand-alone, one-off, online resources, many of them excellent, are (to date) underutilized by teachers in the high school science course taken by most students: biology. The Understanding Global Change project (UGC) from the UC Berkeley Museum of Paleontology has created a conceptual framework that organizes, connects, and explains global systems, human and non-human drivers of change in those systems, and measurable changes in those systems. This organization and framework employ core ideas, crosscutting concepts, structure/function relationships, and system models in a unique format that facilitates authentic understanding, rather than memorization. This system serves as an organizing framework for the entire ecology unit of a forthcoming mainstream high school biology program. The UGC system model is introduced up front with its core informational graphic. The model is elaborated, step by step, by adding concepts and processes as they are introduced and explained in each chapter. The informational graphic is thus used in several ways: to organize material as it is presented, to summarize topics in each chapter and put them in perspective, and for review and critical thinking exercises that supplement the usual end-of-chapter lists of key terms.

A business rules design framework for a pharmaceutical validation and alert system.

PubMed

Boussadi, A; Bousquet, C; Sabatier, B; Caruba, T; Durieux, P; Degoulet, P

2011-01-01

Several alert systems have been developed to improve the patient safety aspects of clinical information systems (CIS). Most studies have focused on the evaluation of these systems, with little information provided about the methodology leading to system implementation. We propose here an 'agile' business rule design framework (BRDF) supporting both the design of alerts for the validation of drug prescriptions and the incorporation of the end user into the design process. We analyzed the unified process (UP) design life cycle and defined the activities, subactivities, actors and UML artifacts that could be used to enhance the agility of the proposed framework. We then applied the proposed framework to two different sets of data in the context of the Georges Pompidou University Hospital (HEGP) CIS. We introduced two new subactivities into UP: business rule specification and business rule instantiation activity. The pharmacist made an effective contribution to five of the eight BRDF design activities. Validation of the two new subactivities was effected in the context of drug dosage adaption to the patients' clinical and biological contexts. Pilot experiment shows that business rules modeled with BRDF and implemented as an alert system triggered an alert for 5824 of the 71,413 prescriptions considered (8.16%). A business rule design framework approach meets one of the strategic objectives for decision support design by taking into account three important criteria posing a particular challenge to system designers: 1) business processes, 2) knowledge modeling of the context of application, and 3) the agility of the various design steps.

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…

Stochastic Robust Mathematical Programming Model for Power System Optimization

DOE Office of Scientific and Technical Information (OSTI.GOV)

Liu, Cong; Changhyeok, Lee; Haoyong, Chen

2016-01-01

This paper presents a stochastic robust framework for two-stage power system optimization problems with uncertainty. The model optimizes the probabilistic expectation of different worst-case scenarios with ifferent uncertainty sets. A case study of unit commitment shows the effectiveness of the proposed model and algorithms.

Parameterized post-Newtonian cosmology

NASA Astrophysics Data System (ADS)

Sanghai, Viraj A. A.; Clifton, Timothy

2017-03-01

Einstein’s theory of gravity has been extensively tested on solar system scales, and for isolated astrophysical systems, using the perturbative framework known as the parameterized post-Newtonian (PPN) formalism. This framework is designed for use in the weak-field and slow-motion limit of gravity, and can be used to constrain a large class of metric theories of gravity with data collected from the aforementioned systems. Given the potential of future surveys to probe cosmological scales to high precision, it is a topic of much contemporary interest to construct a similar framework to link Einstein’s theory of gravity and its alternatives to observations on cosmological scales. Our approach to this problem is to adapt and extend the existing PPN formalism for use in cosmology. We derive a set of equations that use the same parameters to consistently model both weak fields and cosmology. This allows us to parameterize a large class of modified theories of gravity and dark energy models on cosmological scales, using just four functions of time. These four functions can be directly linked to the background expansion of the universe, first-order cosmological perturbations, and the weak-field limit of the theory. They also reduce to the standard PPN parameters on solar system scales. We illustrate how dark energy models and scalar-tensor and vector-tensor theories of gravity fit into this framework, which we refer to as ‘parameterized post-Newtonian cosmology’ (PPNC).

Performance measurement integrated information framework in e-Manufacturing

NASA Astrophysics Data System (ADS)

Teran, Hilaida; Hernandez, Juan Carlos; Vizán, Antonio; Ríos, José

2014-11-01

The implementation of Internet technologies has led to e-Manufacturing technologies becoming more widely used and to the development of tools for compiling, transforming and synchronising manufacturing data through the Web. In this context, a potential area for development is the extension of virtual manufacturing to performance measurement (PM) processes, a critical area for decision making and implementing improvement actions in manufacturing. This paper proposes a PM information framework to integrate decision support systems in e-Manufacturing. Specifically, the proposed framework offers a homogeneous PM information exchange model that can be applied through decision support in e-Manufacturing environment. Its application improves the necessary interoperability in decision-making data processing tasks. It comprises three sub-systems: a data model, a PM information platform and PM-Web services architecture. A practical example of data exchange for measurement processes in the area of equipment maintenance is shown to demonstrate the utility of the model.

Modelling runway incursion severity.

PubMed

Wilke, Sabine; Majumdar, Arnab; Ochieng, Washington Y

2015-06-01

Analysis of the causes underlying runway incursions is fundamental for the development of effective mitigation measures. However, there are significant weaknesses in the current methods to model these factors. This paper proposes a structured framework for modelling causal factors and their relationship to severity, which includes a description of the airport surface system architecture, establishment of terminological definitions, the determination and collection of appropriate data, the analysis of occurrences for severity and causes, and the execution of a statistical analysis framework. It is implemented in the context of U.S. airports, enabling the identification of a number of priority interventions, including the need for better investigation and causal factor capture, recommendations for airfield design, operating scenarios and technologies, and better training for human operators in the system. The framework is recommended for the analysis of runway incursions to support safety improvements and the methodology is transferable to other areas of aviation safety risk analysis. Copyright © 2015 Elsevier Ltd. All rights reserved.

IDEA: Planning at the Core of Autonomous Reactive Agents

NASA Technical Reports Server (NTRS)

Muscettola, Nicola; Dorais, Gregory A.; Fry, Chuck; Levinson, Richard; Plaunt, Christian; Clancy, Daniel (Technical Monitor)

2002-01-01

Several successful autonomous systems are separated into technologically diverse functional layers operating at different levels of abstraction. This diversity makes them difficult to implement and validate. In this paper, we present IDEA (Intelligent Distributed Execution Architecture), a unified planning and execution framework. In IDEA a layered system can be implemented as separate agents, one per layer, each representing its interactions with the world in a model. At all levels, the model representation primitives and their semantics is the same. Moreover, each agent relies on a single model, plan database, plan runner and on a variety of planners, both reactive and deliberative. The framework allows the specification of agents that operate, within a guaranteed reaction time and supports flexible specification of reactive vs. deliberative agent behavior. Within the IDEA framework we are working to fully duplicate the functionalities of the DS1 Remote Agent and extend it to domains of higher complexity than autonomous spacecraft control.

Integrated modelling of ecosystem services and energy systems research

NASA Astrophysics Data System (ADS)

Agarwala, Matthew; Lovett, Andrew; Bateman, Ian; Day, Brett; Agnolucci, Paolo; Ziv, Guy

2016-04-01

The UK Government is formally committed to reducing carbon emissions and protecting and improving natural capital and the environment. However, actually delivering on these objectives requires an integrated approach to addressing two parallel challenges: de-carbonising future energy system pathways; and safeguarding natural capital to ensure the continued flow of ecosystem services. Although both emphasise benefiting from natural resources, efforts to connect natural capital and energy systems research have been limited, meaning opportunities to improve management of natural resources and meet society's energy needs could be missed. The ecosystem services paradigm provides a consistent conceptual framework that applies in multiple disciplines across the natural and economic sciences, and facilitates collaboration between them. At the forefront of the field, integrated ecosystem service - economy models have guided public- and private-sector decision making at all levels. Models vary in sophistication from simple spreadsheet tools to complex software packages integrating biophysical, GIS and economic models and draw upon many fields, including ecology, hydrology, geography, systems theory, economics and the social sciences. They also differ in their ability to value changes in natural capital and ecosystem services at various spatial and temporal scales. Despite these differences, current models share a common feature: their treatment of energy systems is superficial at best. In contrast, energy systems research has no widely adopted, unifying conceptual framework that organises thinking about key system components and interactions. Instead, the literature is organised around modelling approaches, including life cycle analyses, econometric investigations, linear programming and computable general equilibrium models. However, some consistencies do emerge. First, often contain a linear set of steps, from exploration to resource supply, fuel processing, conversion/generation, transmission, distribution, and finally, end energy use. Although each step clearly impacts upon natural capital, links to the natural environment are rarely identified or quantified within energy research. In short, the respective conceptual frameworks guiding ecosystem service and energy research are not well integrated. Major knowledge and research gaps appear at the system boundaries: while energy models may mention flows of residuals, exploring where exactly these flows enter the environment, and how they impact ecosystems and natural capital is often considered to be 'outside the system boundary'. While integrated modelling represents the frontier of ecosystem service research, current efforts largely ignore the future energy pathways set out by energy systems models and government carbon targets. This disconnect means that policy-oriented research on how best to (i) maintain natural capital and (ii) meet specific climate targets may be poorly aligned, or worse, offer conflicting advice. We present a re-imagined version of the ecosystem services conceptual framework, in which emphasis is placed on interactions between energy systems and the natural environment. Using the UK as a case study, we employ a recent integrated environmental-economic ecosystem service model, TIM, developed by Bateman et al (2014) and energy pathways developed by the UK Energy Research Centre and the UK Government Committee on Climate Change to illustrate how the new conceptual framework might apply in real world applications.

Baldrige Theory into Practice: A Generic Model

ERIC Educational Resources Information Center

Arif, Mohammed

2007-01-01

Purpose: The education system globally has moved from a push-based or producer-centric system to a pull-based or customer centric system. Malcolm Baldrige Quality Award (MBQA) model happens to be one of the latest additions to the pull based models. The purpose of this paper is to develop a generic framework for MBQA that can be used by…

New ARCH: Future Generation Internet Architecture

DTIC Science & Technology

2004-08-01

a vocabulary to talk about a system . This provides a framework ( a “reference model ...layered model Modularity and abstraction are central tenets of Computer Science thinking. Modularity breaks a system into parts, normally to permit...this complexity is hidden. Abstraction suggests a structure for the system . A popular and simple structure is a layered model : lower layer

Development of an Electronic Portfolio System Success Model: An Information Systems Approach

ERIC Educational Resources Information Center

Balaban, Igor; Mu, Enrique; Divjak, Blazenka

2013-01-01

This research has two main goals: to develop an instrument for assessing Electronic Portfolio (ePortfolio) success and to build a corresponding ePortfolio success model using DeLone and McLean's information systems success model as the theoretical framework. For this purpose, we developed an ePortfolio success measurement instrument and structural…

Simulation, identification and statistical variation in cardiovascular analysis (SISCA) - A software framework for multi-compartment lumped modeling.

PubMed

Huttary, Rudolf; Goubergrits, Leonid; Schütte, Christof; Bernhard, Stefan

2017-08-01

It has not yet been possible to obtain modeling approaches suitable for covering a wide range of real world scenarios in cardiovascular physiology because many of the system parameters are uncertain or even unknown. Natural variability and statistical variation of cardiovascular system parameters in healthy and diseased conditions are characteristic features for understanding cardiovascular diseases in more detail. This paper presents SISCA, a novel software framework for cardiovascular system modeling and its MATLAB implementation. The framework defines a multi-model statistical ensemble approach for dimension reduced, multi-compartment models and focuses on statistical variation, system identification and patient-specific simulation based on clinical data. We also discuss a data-driven modeling scenario as a use case example. The regarded dataset originated from routine clinical examinations and comprised typical pre and post surgery clinical data from a patient diagnosed with coarctation of aorta. We conducted patient and disease specific pre/post surgery modeling by adapting a validated nominal multi-compartment model with respect to structure and parametrization using metadata and MRI geometry. In both models, the simulation reproduced measured pressures and flows fairly well with respect to stenosis and stent treatment and by pre-treatment cross stenosis phase shift of the pulse wave. However, with post-treatment data showing unrealistic phase shifts and other more obvious inconsistencies within the dataset, the methods and results we present suggest that conditioning and uncertainty management of routine clinical data sets needs significantly more attention to obtain reasonable results in patient-specific cardiovascular modeling. Copyright © 2017 Elsevier Ltd. All rights reserved.

A Function-Behavior-State Approach to Designing Human Machine Interface for Nuclear Power Plant Operators

NASA Astrophysics Data System (ADS)

Lin, Y.; Zhang, W. J.

2005-02-01

This paper presents an approach to human-machine interface design for control room operators of nuclear power plants. The first step in designing an interface for a particular application is to determine information content that needs to be displayed. The design methodology for this step is called the interface design framework (called framework ). Several frameworks have been proposed for applications at varying levels, including process plants. However, none is based on the design and manufacture of a plant system for which the interface is designed. This paper presents an interface design framework which originates from design theory and methodology for general technical systems. Specifically, the framework is based on a set of core concepts of a function-behavior-state model originally proposed by the artificial intelligence research community and widely applied in the design research community. Benefits of this new framework include the provision of a model-based fault diagnosis facility, and the seamless integration of the design (manufacture, maintenance) of plants and the design of human-machine interfaces. The missing linkage between design and operation of a plant was one of the causes of the Three Mile Island nuclear reactor incident. A simulated plant system is presented to explain how to apply this framework in designing an interface. The resulting human-machine interface is discussed; specifically, several fault diagnosis examples are elaborated to demonstrate how this interface could support operators' fault diagnosis in an unanticipated situation.

Jupiter Europa Orbiter Architecture Definition Process

NASA Technical Reports Server (NTRS)

Rasmussen, Robert; Shishko, Robert

2011-01-01

The proposed Jupiter Europa Orbiter mission, planned for launch in 2020, is using a new architectural process and framework tool to drive its model-based systems engineering effort. The process focuses on getting the architecture right before writing requirements and developing a point design. A new architecture framework tool provides for the structured entry and retrieval of architecture artifacts based on an emerging architecture meta-model. This paper describes the relationships among these artifacts and how they are used in the systems engineering effort. Some early lessons learned are discussed.

6-D, A Process Framework for the Design and Development of Web-based Systems.

ERIC Educational Resources Information Center

Christian, Phillip

2001-01-01

Explores how the 6-D framework can form the core of a comprehensive systemic strategy and help provide a supporting structure for more robust design and development while allowing organizations to support whatever methods and models best suit their purpose. 6-D stands for the phases of Web design and development: Discovery, Definition, Design,…

Open-source framework for power system transmission and distribution dynamics co-simulation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Huang, Renke; Fan, Rui; Daily, Jeff

The promise of the smart grid entails more interactions between the transmission and distribution networks, and there is an immediate need for tools to provide the comprehensive modelling and simulation required to integrate operations at both transmission and distribution levels. Existing electromagnetic transient simulators can perform simulations with integration of transmission and distribution systems, but the computational burden is high for large-scale system analysis. For transient stability analysis, currently there are only separate tools for simulating transient dynamics of the transmission and distribution systems. In this paper, we introduce an open source co-simulation framework “Framework for Network Co-Simulation” (FNCS), togethermore » with the decoupled simulation approach that links existing transmission and distribution dynamic simulators through FNCS. FNCS is a middleware interface and framework that manages the interaction and synchronization of the transmission and distribution simulators. Preliminary testing results show the validity and capability of the proposed open-source co-simulation framework and the decoupled co-simulation methodology.« less

Reaping the benefits of an open systems approach: getting the commercial approach right

NASA Astrophysics Data System (ADS)

Pearson, Gavin; Dawe, Tony; Stubbs, Peter; Worthington, Olwen

2016-05-01

Critical to reaping the benefits of an Open System Approach within Defence, or any other sector, is the ability to design the appropriate commercial model (or framework). This paper reports on the development and testing of a commercial strategy decision support tool. The tool set comprises a number of elements, including a process model, and provides business intelligence insights into likely supplier behaviour. The tool has been developed by subject matter experts and has been tested with a number of UK Defence procurement teams. The paper will present the commercial model framework, the elements of the toolset and the results of testing.

A SVM framework for fault detection of the braking system in a high speed train

NASA Astrophysics Data System (ADS)

Liu, Jie; Li, Yan-Fu; Zio, Enrico

2017-03-01

In April 2015, the number of operating High Speed Trains (HSTs) in the world has reached 3603. An efficient, effective and very reliable braking system is evidently very critical for trains running at a speed around 300 km/h. Failure of a highly reliable braking system is a rare event and, consequently, informative recorded data on fault conditions are scarce. This renders the fault detection problem a classification problem with highly unbalanced data. In this paper, a Support Vector Machine (SVM) framework, including feature selection, feature vector selection, model construction and decision boundary optimization, is proposed for tackling this problem. Feature vector selection can largely reduce the data size and, thus, the computational burden. The constructed model is a modified version of the least square SVM, in which a higher cost is assigned to the error of classification of faulty conditions than the error of classification of normal conditions. The proposed framework is successfully validated on a number of public unbalanced datasets. Then, it is applied for the fault detection of braking systems in HST: in comparison with several SVM approaches for unbalanced datasets, the proposed framework gives better results.

Modeling socio-cultural processes in network-centric environments

NASA Astrophysics Data System (ADS)

Santos, Eunice E.; Santos, Eugene, Jr.; Korah, John; George, Riya; Gu, Qi; Kim, Keumjoo; Li, Deqing; Russell, Jacob; Subramanian, Suresh

2012-05-01

The major focus in the field of modeling & simulation for network centric environments has been on the physical layer while making simplifications for the human-in-the-loop. However, the human element has a big impact on the capabilities of network centric systems. Taking into account the socio-behavioral aspects of processes such as team building, group decision-making, etc. are critical to realistically modeling and analyzing system performance. Modeling socio-cultural processes is a challenge because of the complexity of the networks, dynamism in the physical and social layers, feedback loops and uncertainty in the modeling data. We propose an overarching framework to represent, model and analyze various socio-cultural processes within network centric environments. The key innovation in our methodology is to simultaneously model the dynamism in both the physical and social layers while providing functional mappings between them. We represent socio-cultural information such as friendships, professional relationships and temperament by leveraging the Culturally Infused Social Network (CISN) framework. The notion of intent is used to relate the underlying socio-cultural factors to observed behavior. We will model intent using Bayesian Knowledge Bases (BKBs), a probabilistic reasoning network, which can represent incomplete and uncertain socio-cultural information. We will leverage previous work on a network performance modeling framework called Network-Centric Operations Performance and Prediction (N-COPP) to incorporate dynamism in various aspects of the physical layer such as node mobility, transmission parameters, etc. We validate our framework by simulating a suitable scenario, incorporating relevant factors and providing analyses of the results.

Working Group 1: Software System Design and Implementation for Environmental Modeling

EPA Science Inventory

ISCMEM Working Group One Presentation, presentation with the purpose of fostering the exchange of information about environmental modeling tools, modeling frameworks, and environmental monitoring databases.

Advancing Ecological Models to Compare Scale in Multi-Level Educational Change

ERIC Educational Resources Information Center

Woo, David James

2016-01-01

Education systems as units of analysis have been metaphorically likened to ecologies to model change. However, ecological models to date have been ineffective in modelling educational change that is multi-scale and occurs across multiple levels of an education system. Thus, this paper advances two innovative, ecological frameworks that improve on…

RELEASE NOTES FOR MODELS-3 VERSION 4.1 PATCH: SMOKE TOOL AND FILE CONVERTER

EPA Science Inventory

This software patch to the Models-3 system corrects minor errors in the Models-3 framework, provides substantial improvements in the ASCII to I/O API format conversion of the File Converter utility, and new functionalities for the SMOKE Tool. Version 4.1 of the Models-3 system...

A system framework of inter-enterprise machining quality control based on fractal theory

NASA Astrophysics Data System (ADS)

Zhao, Liping; Qin, Yongtao; Yao, Yiyong; Yan, Peng

2014-03-01

In order to meet the quality control requirement of dynamic and complicated product machining processes among enterprises, a system framework of inter-enterprise machining quality control based on fractal was proposed. In this system framework, the fractal-specific characteristic of inter-enterprise machining quality control function was analysed, and the model of inter-enterprise machining quality control was constructed by the nature of fractal structures. Furthermore, the goal-driven strategy of inter-enterprise quality control and the dynamic organisation strategy of inter-enterprise quality improvement were constructed by the characteristic analysis on this model. In addition, the architecture of inter-enterprise machining quality control based on fractal was established by means of Web service. Finally, a case study for application was presented. The result showed that the proposed method was available, and could provide guidance for quality control and support for product reliability in inter-enterprise machining processes.

Improving benchmarking by using an explicit framework for the development of composite indicators: an example using pediatric quality of care

PubMed Central

2010-01-01

Background The measurement of healthcare provider performance is becoming more widespread. Physicians have been guarded about performance measurement, in part because the methodology for comparative measurement of care quality is underdeveloped. Comprehensive quality improvement will require comprehensive measurement, implying the aggregation of multiple quality metrics into composite indicators. Objective To present a conceptual framework to develop comprehensive, robust, and transparent composite indicators of pediatric care quality, and to highlight aspects specific to quality measurement in children. Methods We reviewed the scientific literature on composite indicator development, health systems, and quality measurement in the pediatric healthcare setting. Frameworks were selected for explicitness and applicability to a hospital-based measurement system. Results We synthesized various frameworks into a comprehensive model for the development of composite indicators of quality of care. Among its key premises, the model proposes identifying structural, process, and outcome metrics for each of the Institute of Medicine's six domains of quality (safety, effectiveness, efficiency, patient-centeredness, timeliness, and equity) and presents a step-by-step framework for embedding the quality of care measurement model into composite indicator development. Conclusions The framework presented offers researchers an explicit path to composite indicator development. Without a scientifically robust and comprehensive approach to measurement of the quality of healthcare, performance measurement will ultimately fail to achieve its quality improvement goals. PMID:20181129

The Goddard Snow Radiance Assimilation Project: An Integrated Snow Radiance and Snow Physics Modeling Framework for Snow/cold Land Surface Modeling

NASA Technical Reports Server (NTRS)

Kim, E.; Tedesco, M.; Reichle, R.; Choudhury, B.; Peters-Lidard C.; Foster, J.; Hall, D.; Riggs, G.

2006-01-01

Microwave-based retrievals of snow parameters from satellite observations have a long heritage and have so far been generated primarily by regression-based empirical "inversion" methods based on snapshots in time. Direct assimilation of microwave radiance into physical land surface models can be used to avoid errors associated with such retrieval/inversion methods, instead utilizing more straightforward forward models and temporal information. This approach has been used for years for atmospheric parameters by the operational weather forecasting community with great success. Recent developments in forward radiative transfer modeling, physical land surface modeling, and land data assimilation are converging to allow the assembly of an integrated framework for snow/cold lands modeling and radiance assimilation. The objective of the Goddard snow radiance assimilation project is to develop such a framework and explore its capabilities. 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. In fact, multiple models are available for each element enabling optimization to match the needs of a particular study. Together these form a modular and flexible framework for self-consistent, physically-based remote sensing and water/energy cycle studies. In this paper we will describe the elements and the integration plan. 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. Capabilities for assimilation of snow retrieval products are already under development for LIS. We will describe plans to add radiance-based assimilation capabilities. Plans for validation activities using field measurements will also be discussed.

The interactive systems framework applied to the strategic prevention framework: the Rhode Island experience.

PubMed

Florin, Paul; Friend, Karen B; Buka, Stephen; Egan, Crystelle; Barovier, Linda; Amodei, Brenda

2012-12-01

The Interactive Systems Framework for Dissemination and Implementation (ISF) was introduced as a heuristic systems level model to help bridge the gap between research and practice (Wandersman et al., in Am J Commun Psychol 41:171-181, 2008). This model describes three interacting systems with distinct functions that (1) distill knowledge to develop innovations; (2) provide supportive training and technical assistance for dissemination to; (3) a prevention delivery system responsible for implementation in the field. The Strategic Prevention Framework (SPF) is a major prevention innovation launched by the Center for Substance Abuse Prevention (CSAP) of the Substance Abuse and Mental Health Services Administration (SAMHSA). The SPF offers a structured, sequential, data-driven approach that explicitly targets environmental conditions in the community and aims for change in substance use and problems at the population level. This paper describes how the ISF was applied to the challenges of implementing the SPF in 14 Rhode Island communities, with a focus on the development of a new Training and Technical Assistance Resources Center to support SPF efforts. More specifically, we (1) describe each of the three ISF interacting systems as they evolved in Rhode Island; (2) articulate the lines of communication between the three systems; and (3) examine selected evaluation data to understand relationships between training and technical assistance and SPF implementation and outcomes.

Development, Validation, and Application of OSSEs at NASA/GMAO

NASA Technical Reports Server (NTRS)

Errico, Ronald; Prive, Nikki

2015-01-01

During the past several years, NASA Goddard's Global Modeling and Assimilation Office (GMAO) has been developing a framework for conducting Observing System Simulation Experiments (OSSEs). The motivation and design of that framework will be described and a sample of validation results presented. Fundamentals issues will be highlighted, particularly the critical importance of appropriately simulating system errors. Some problems that have just arisen in the newest experimental system will also be mentioned.

Dynamical Systems Approach to Endothelial Heterogeneity

PubMed Central

Regan, Erzsébet Ravasz; Aird, William C.

2012-01-01

Rationale Objective Here we reexamine our current understanding of the molecular basis of endothelial heterogeneity. We introduce multistability as a new explanatory framework in vascular biology. Methods We draw on the field of non-linear dynamics to propose a dynamical systems framework for modeling multistability and its derivative properties, including robustness, memory, and plasticity. Conclusions Our perspective allows for both a conceptual and quantitative description of system-level features of endothelial regulation. PMID:22723222

Conceptualising paediatric health disparities: a metanarrative systematic review and unified conceptual framework.

PubMed

Ridgeway, Jennifer L; Wang, Zhen; Finney Rutten, Lila J; van Ryn, Michelle; Griffin, Joan M; Murad, M Hassan; Asiedu, Gladys B; Egginton, Jason S; Beebe, Timothy J

2017-08-04

There exists a paucity of work in the development and testing of theoretical models specific to childhood health disparities even though they have been linked to the prevalence of adult health disparities including high rates of chronic disease. We conducted a systematic review and thematic analysis of existing models of health disparities specific to children to inform development of a unified conceptual framework. We systematically reviewed articles reporting theoretical or explanatory models of disparities on a range of outcomes related to child health. We searched Ovid Medline In-Process & Other Non-Indexed Citations, Ovid MEDLINE, Ovid Embase, Ovid Cochrane Central Register of Controlled Trials, Ovid Cochrane Database of Systematic Reviews, and Scopus (database inception to 9 July 2015). A metanarrative approach guided the analysis process. A total of 48 studies presenting 48 models were included. This systematic review found multiple models but no consensus on one approach. However, we did discover a fair amount of overlap, such that the 48 models reviewed converged into the unified conceptual framework. The majority of models included factors in three domains: individual characteristics and behaviours (88%), healthcare providers and systems (63%), and environment/community (56%), . Only 38% of models included factors in the health and public policies domain. A disease-agnostic unified conceptual framework may inform integration of existing knowledge of child health disparities and guide future research. This multilevel framework can focus attention among clinical, basic and social science research on the relationships between policy, social factors, health systems and the physical environment that impact children's health outcomes. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2017. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

A Model-Driven Co-Design Framework for Fusing Control and Scheduling Viewpoints.

PubMed

Sundharam, Sakthivel Manikandan; Navet, Nicolas; Altmeyer, Sebastian; Havet, Lionel

2018-02-20

Model-Driven Engineering (MDE) is widely applied in the industry to develop new software functions and integrate them into the existing run-time environment of a Cyber-Physical System (CPS). The design of a software component involves designers from various viewpoints such as control theory, software engineering, safety, etc. In practice, while a designer from one discipline focuses on the core aspects of his field (for instance, a control engineer concentrates on designing a stable controller), he neglects or considers less importantly the other engineering aspects (for instance, real-time software engineering or energy efficiency). This may cause some of the functional and non-functional requirements not to be met satisfactorily. In this work, we present a co-design framework based on timing tolerance contract to address such design gaps between control and real-time software engineering. The framework consists of three steps: controller design, verified by jitter margin analysis along with co-simulation, software design verified by a novel schedulability analysis, and the run-time verification by monitoring the execution of the models on target. This framework builds on CPAL (Cyber-Physical Action Language), an MDE design environment based on model-interpretation, which enforces a timing-realistic behavior in simulation through timing and scheduling annotations. The application of our framework is exemplified in the design of an automotive cruise control system.

A Model-Driven Co-Design Framework for Fusing Control and Scheduling Viewpoints

PubMed Central

Navet, Nicolas; Havet, Lionel

2018-01-01

Model-Driven Engineering (MDE) is widely applied in the industry to develop new software functions and integrate them into the existing run-time environment of a Cyber-Physical System (CPS). The design of a software component involves designers from various viewpoints such as control theory, software engineering, safety, etc. In practice, while a designer from one discipline focuses on the core aspects of his field (for instance, a control engineer concentrates on designing a stable controller), he neglects or considers less importantly the other engineering aspects (for instance, real-time software engineering or energy efficiency). This may cause some of the functional and non-functional requirements not to be met satisfactorily. In this work, we present a co-design framework based on timing tolerance contract to address such design gaps between control and real-time software engineering. The framework consists of three steps: controller design, verified by jitter margin analysis along with co-simulation, software design verified by a novel schedulability analysis, and the run-time verification by monitoring the execution of the models on target. This framework builds on CPAL (Cyber-Physical Action Language), an MDE design environment based on model-interpretation, which enforces a timing-realistic behavior in simulation through timing and scheduling annotations. The application of our framework is exemplified in the design of an automotive cruise control system. PMID:29461489

Modeling and control of operator functional state in a unified framework of fuzzy inference petri nets.

PubMed

Zhang, Jian-Hua; Xia, Jia-Jun; Garibaldi, Jonathan M; Groumpos, Petros P; Wang, Ru-Bin

2017-06-01

In human-machine (HM) hybrid control systems, human operator and machine cooperate to achieve the control objectives. To enhance the overall HM system performance, the discrete manual control task-load by the operator must be dynamically allocated in accordance with continuous-time fluctuation of psychophysiological functional status of the operator, so-called operator functional state (OFS). The behavior of the HM system is hybrid in nature due to the co-existence of discrete task-load (control) variable and continuous operator performance (system output) variable. Petri net is an effective tool for modeling discrete event systems, but for hybrid system involving discrete dynamics, generally Petri net model has to be extended. Instead of using different tools to represent continuous and discrete components of a hybrid system, this paper proposed a method of fuzzy inference Petri nets (FIPN) to represent the HM hybrid system comprising a Mamdani-type fuzzy model of OFS and a logical switching controller in a unified framework, in which the task-load level is dynamically reallocated between the operator and machine based on the model-predicted OFS. Furthermore, this paper used a multi-model approach to predict the operator performance based on three electroencephalographic (EEG) input variables (features) via the Wang-Mendel (WM) fuzzy modeling method. The membership function parameters of fuzzy OFS model for each experimental participant were optimized using artificial bee colony (ABC) evolutionary algorithm. Three performance indices, RMSE, MRE, and EPR, were computed to evaluate the overall modeling accuracy. Experiment data from six participants are analyzed. The results show that the proposed method (FIPN with adaptive task allocation) yields lower breakdown rate (from 14.8% to 3.27%) and higher human performance (from 90.30% to 91.99%). The simulation results of the FIPN-based adaptive HM (AHM) system on six experimental participants demonstrate that the FIPN framework provides an effective way to model and regulate/optimize the OFS in HM hybrid systems composed of continuous-time OFS model and discrete-event switching controller. Copyright © 2017 Elsevier B.V. All rights reserved.

Agent Based Modeling of Air Carrier Behavior for Evaluation of Technology Equipage and Adoption

NASA Technical Reports Server (NTRS)

Horio, Brant M.; DeCicco, Anthony H.; Stouffer, Virginia L.; Hasan, Shahab; Rosenbaum, Rebecca L.; Smith, Jeremy C.

2014-01-01

As part of ongoing research, the National Aeronautics and Space Administration (NASA) and LMI developed a research framework to assist policymakers in identifying impacts on the U.S. air transportation system (ATS) of potential policies and technology related to the implementation of the Next Generation Air Transportation System (NextGen). This framework, called the Air Transportation System Evolutionary Simulation (ATS-EVOS), integrates multiple models into a single process flow to best simulate responses by U.S. commercial airlines and other ATS stakeholders to NextGen-related policies, and in turn, how those responses impact the ATS. Development of this framework required NASA and LMI to create an agent-based model of airline and passenger behavior. This Airline Evolutionary Simulation (AIRLINE-EVOS) models airline decisions about tactical airfare and schedule adjustments, and strategic decisions related to fleet assignments, market prices, and equipage. AIRLINE-EVOS models its own heterogeneous population of passenger agents that interact with airlines; this interaction allows the model to simulate the cycle of action-reaction as airlines compete with each other and engage passengers. We validated a baseline configuration of AIRLINE-EVOS against Airline Origin and Destination Survey (DB1B) data and subject matter expert opinion, and we verified the ATS-EVOS framework and agent behavior logic through scenario-based experiments. These experiments demonstrated AIRLINE-EVOS's capabilities in responding to an input price shock in fuel prices, and to equipage challenges in a series of analyses based on potential incentive policies for best equipped best served, optimal-wind routing, and traffic management initiative exemption concepts..

Learning situation models in a smart home.

PubMed

Brdiczka, Oliver; Crowley, James L; Reignier, Patrick

2009-02-01

This paper addresses the problem of learning situation models for providing context-aware services. Context for modeling human behavior in a smart environment is represented by a situation model describing environment, users, and their activities. A framework for acquiring and evolving different layers of a situation model in a smart environment is proposed. Different learning methods are presented as part of this framework: role detection per entity, unsupervised extraction of situations from multimodal data, supervised learning of situation representations, and evolution of a predefined situation model with feedback. The situation model serves as frame and support for the different methods, permitting to stay in an intuitive declarative framework. The proposed methods have been integrated into a whole system for smart home environment. The implementation is detailed, and two evaluations are conducted in the smart home environment. The obtained results validate the proposed approach.

Mechanochemical models of processive molecular motors

NASA Astrophysics Data System (ADS)

Lan, Ganhui; Sun, Sean X.

2012-05-01

Motor proteins are the molecular engines powering the living cell. These nanometre-sized molecules convert chemical energy, both enthalpic and entropic, into useful mechanical work. High resolution single molecule experiments can now observe motor protein movement with increasing precision. The emerging data must be combined with structural and kinetic measurements to develop a quantitative mechanism. This article describes a modelling framework where quantitative understanding of motor behaviour can be developed based on the protein structure. The framework is applied to myosin motors, with emphasis on how synchrony between motor domains give rise to processive unidirectional movement. The modelling approach shows that the elasticity of protein domains are important in regulating motor function. Simple models of protein domain elasticity are presented. The framework can be generalized to other motor systems, or an ensemble of motors such as muscle contraction. Indeed, for hundreds of myosins, our framework can be reduced to the Huxely-Simmons description of muscle movement in the mean-field limit.

Modeling Complex Biological Flows in Multi-Scale Systems using the APDEC Framework

DOE Office of Scientific and Technical Information (OSTI.GOV)

Trebotich, D

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 viscousmore » 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.« less

Modeling complex biological flows in multi-scale systems using the APDEC framework

NASA Astrophysics Data System (ADS)

Trebotich, David

2006-09-01

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.

A Conceptual Framework for Educational Design at Modular Level to Promote Transfer of Learning

ERIC Educational Resources Information Center

Botma, Yvonne; Van Rensburg, G. H.; Coetzee, I. M.; Heyns, T.

2015-01-01

Students bridge the theory-practice gap when they apply in practice what they have learned in class. A conceptual framework was developed that can serve as foundation to design for learning transfer at modular level. The framework is based on an adopted and adapted systemic model of transfer of learning, existing learning theories, constructive…

SAINT: A combined simulation language for modeling man-machine systems

NASA Technical Reports Server (NTRS)

Seifert, D. J.

1979-01-01

SAINT (Systems Analysis of Integrated Networks of Tasks) is a network modeling and simulation technique for design and analysis of complex man machine systems. SAINT provides the conceptual framework for representing systems that consist of discrete task elements, continuous state variables, and interactions between them. It also provides a mechanism for combining human performance models and dynamic system behaviors in a single modeling structure. The SAINT technique is described and applications of the SAINT are discussed.

Development of solute transport models in YMPYRÄ framework to simulate solute migration in military shooting and training areas

NASA Astrophysics Data System (ADS)

Warsta, L.; Karvonen, T.

2017-12-01

There are currently 25 shooting and training areas in Finland managed by The Finnish Defence Forces (FDF), where military activities can cause contamination of open waters and groundwater reservoirs. In the YMPYRÄ project, a computer software framework is being developed that combines existing open environmental data and proprietary information collected by FDF with computational models to investigate current and prevent future environmental problems. A data centric philosophy is followed in the development of the system, i.e. the models are updated and extended to handle available data from different areas. The results generated by the models are summarized as easily understandable flow and risk maps that can be opened in GIS programs and used in environmental assessments by experts. Substances investigated with the system include explosives and metals such as lead, and both surface and groundwater dominated areas can be simulated. The YMPYRÄ framework is composed of a three dimensional soil and groundwater flow model, several solute transport models and an uncertainty assessment system. Solute transport models in the framework include particle based, stream tube and finite volume based approaches. The models can be used to simulate solute dissolution from source area, transport in the unsaturated layers to groundwater and finally migration in groundwater to water extraction wells and springs. The models can be used to simulate advection, dispersion, equilibrium adsorption on soil particles, solubility and dissolution from solute phase and dendritic solute decay chains. Correct numerical solutions were confirmed by comparing results to analytical 1D and 2D solutions and by comparing the numerical solutions to each other. The particle based and stream tube type solute transport models were useful as they could complement the traditional finite volume based approach which in certain circumstances produced numerical dispersion due to piecewise solution of the governing equations in computational grids and included computationally intensive and in some cases unstable iterative solutions. The YMPYRÄ framework is being developed by WaterHope, Gain Oy, and SITO Oy consulting companies and funded by FDF.

QuantumOptics.jl: A Julia framework for simulating open quantum systems

NASA Astrophysics Data System (ADS)

Krämer, Sebastian; Plankensteiner, David; Ostermann, Laurin; Ritsch, Helmut

2018-06-01

We present an open source computational framework geared towards the efficient numerical investigation of open quantum systems written in the Julia programming language. Built exclusively in Julia and based on standard quantum optics notation, the toolbox offers speed comparable to low-level statically typed languages, without compromising on the accessibility and code readability found in dynamic languages. After introducing the framework, we highlight its features and showcase implementations of generic quantum models. Finally, we compare its usability and performance to two well-established and widely used numerical quantum libraries.

Toward a unified approach to dose-response modeling in ecotoxicology.

PubMed

Ritz, Christian

2010-01-01

This study reviews dose-response models that are used in ecotoxicology. The focus lies on clarification of differences and similarities between models, and as a side effect, their different guises in ecotoxicology are unravelled. A look at frequently used dose-response models reveals major discrepancies, among other things in naming conventions. Therefore, there is a need for a unified view on dose-response modeling in order to improve the understanding of it and to facilitate communication and comparison of findings across studies, thus realizing its full potential. This study attempts to establish a general framework that encompasses most dose-response models that are of interest to ecotoxicologists in practice. The framework includes commonly used models such as the log-logistic and Weibull models, but also features entire suites of models as found in various guidance documents. An outline on how the proposed framework can be implemented in statistical software systems is also provided.

Coupled hydrological, ecological, decision and economic models for monetary valuation of riparian ecosystem services

NASA Astrophysics Data System (ADS)

Goodrich, D. C.; Brookshire, D.; Broadbent, C.; Dixon, M. D.; Brand, L. A.; Thacher, J.; Benedict, K. K.; Lansey, K. E.; Stromberg, J. C.; Stewart, S.; McIntosh, M.

2011-12-01

Water is a critical component for sustaining both natural and human systems. Yet the value of water for sustaining ecosystem services is not well quantified in monetary terms. Ideally decisions involving water resource management would include an apples-to-apples comparison of the costs and benefits in dollars of both market and non-market goods and services - human and ecosystem. To quantify the value of non-market ecosystem services, scientifically defensible relationships must be developed that link the effect of a decision (e.g. human growth) to the change in ecosystem attributes from current conditions. It is this linkage that requires the "poly-disciplinary" coupling of knowledge and models from the behavioral, physical, and ecological sciences. In our experience another key component of making this successful linkage is development of a strong poly-disciplinary scientific team that can readily communicate complex disciplinary knowledge to non-specialists outside their own discipline. The time to build such a team that communicates well and has a strong sense of trust should not be underestimated. The research described in the presentation incorporated hydrologic, vegetation, avian, economic, and decision models into an integrated framework to determine the value of changes in ecological systems that result from changes in human water use. We developed a hydro-bio-economic framework for the San Pedro River Region in Arizona that considers groundwater, stream flow, and riparian vegetation, as well as abundance, diversity, and distribution of birds. In addition, we developed a similar framework for the Middle Rio Grande of New Mexico. There are six research components for this project: (1) decision support and scenario specification, (2) regional groundwater model, (3) the riparian vegetation model, (4) the avian model, (5) methods for displaying the information gradients in the valuation survey instruments (Choice Modeling and Contingent Valuation), and (6) the economic framework. Our modeling framework began with the identification of factors that influence spatial and temporal changes in riparian vegetation on the two rivers. The linked modeling framework was then employed for making spatial predictions of the changes in presence of surface water, vegetation change, and avian populations in both river systems. An overview of the overall project will be provided, with lessons learned, and initial valuation survey results.

A predictive control framework for torque-based steering assistance to improve safety in highway driving

NASA Astrophysics Data System (ADS)

Ercan, Ziya; Carvalho, Ashwin; Tseng, H. Eric; Gökaşan, Metin; Borrelli, Francesco

2018-05-01

Haptic shared control framework opens up new perspectives on the design and implementation of the driver steering assistance systems which provide torque feedback to the driver in order to improve safety. While designing such a system, it is important to account for the human-machine interactions since the driver feels the feedback torque through the hand wheel. The controller should consider the driver's impact on the steering dynamics to achieve a better performance in terms of driver's acceptance and comfort. In this paper we present a predictive control framework which uses a model of driver-in-the-loop steering dynamics to optimise the torque intervention with respect to the driver's neuromuscular response. We first validate the system in simulations to compare the performance of the controller in nominal and model mismatch cases. Then we implement the controller in a test vehicle and perform experiments with a human driver. The results show the effectiveness of the proposed system in avoiding hazardous situations under different driver behaviours.

Development of a distributed air pollutant dry deposition modeling framework.

PubMed

Hirabayashi, Satoshi; Kroll, Charles N; Nowak, David J

2012-12-01

A distributed air pollutant dry deposition modeling system was 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 deposition of carbon monoxide (CO), nitrogen dioxide (NO(2)), sulfur dioxide (SO(2)), and particulate matter less than 10 microns (PM10) to trees can be spatially quantified. Employing nationally available road network, traffic volume, air pollutant emission/measurement and meteorological data, the developed system provides a framework for the U.S. city managers to identify spatial patterns of urban forest and locate potential areas for future urban forest planting and protection to improve air quality. To exhibit the usability of the framework, a case study was performed for July and August of 2005 in Baltimore, MD. Copyright © 2012 Elsevier Ltd. All rights reserved.

A multimodal 3D framework for fire characteristics estimation

NASA Astrophysics Data System (ADS)

Toulouse, T.; Rossi, L.; Akhloufi, M. A.; Pieri, A.; Maldague, X.

2018-02-01

In the last decade we have witnessed an increasing interest in using computer vision and image processing in forest fire research. Image processing techniques have been successfully used in different fire analysis areas such as early detection, monitoring, modeling and fire front characteristics estimation. While the majority of the work deals with the use of 2D visible spectrum images, recent work has introduced the use of 3D vision in this field. This work proposes a new multimodal vision framework permitting the extraction of the three-dimensional geometrical characteristics of fires captured by multiple 3D vision systems. The 3D system is a multispectral stereo system operating in both the visible and near-infrared (NIR) spectral bands. The framework supports the use of multiple stereo pairs positioned so as to capture complementary views of the fire front during its propagation. Multimodal registration is conducted using the captured views in order to build a complete 3D model of the fire front. The registration process is achieved using multisensory fusion based on visual data (2D and NIR images), GPS positions and IMU inertial data. Experiments were conducted outdoors in order to show the performance of the proposed framework. The obtained results are promising and show the potential of using the proposed framework in operational scenarios for wildland fire research and as a decision management system in fighting.

Macroscopic description of complex adaptive networks coevolving with dynamic node states

NASA Astrophysics Data System (ADS)

Wiedermann, Marc; Donges, Jonathan F.; Heitzig, Jobst; Lucht, Wolfgang; Kurths, Jürgen

2015-05-01

In many real-world complex systems, the time evolution of the network's structure and the dynamic state of its nodes are closely entangled. Here we study opinion formation and imitation on an adaptive complex network which is dependent on the individual dynamic state of each node and vice versa to model the coevolution of renewable resources with the dynamics of harvesting agents on a social network. The adaptive voter model is coupled to a set of identical logistic growth models and we mainly find that, in such systems, the rate of interactions between nodes as well as the adaptive rewiring probability are crucial parameters for controlling the sustainability of the system's equilibrium state. We derive a macroscopic description of the system in terms of ordinary differential equations which provides a general framework to model and quantify the influence of single node dynamics on the macroscopic state of the network. The thus obtained framework is applicable to many fields of study, such as epidemic spreading, opinion formation, or socioecological modeling.

The Regional Hydrologic Extremes Assessment System: A software framework for hydrologic modeling and data assimilation

PubMed Central

Das, Narendra; Stampoulis, Dimitrios; Ines, Amor; Fisher, Joshua B.; Granger, Stephanie; Kawata, Jessie; Han, Eunjin; Behrangi, Ali

2017-01-01

The Regional Hydrologic Extremes Assessment System (RHEAS) is a prototype software framework for hydrologic modeling and data assimilation that automates the deployment of water resources nowcasting and forecasting applications. A spatially-enabled database is a key component of the software that can ingest a suite of satellite and model datasets while facilitating the interfacing with Geographic Information System (GIS) applications. The datasets ingested are obtained from numerous space-borne sensors and represent multiple components of the water cycle. The object-oriented design of the software allows for modularity and extensibility, showcased here with the coupling of the core hydrologic model with a crop growth model. RHEAS can exploit multi-threading to scale with increasing number of processors, while the database allows delivery of data products and associated uncertainty through a variety of GIS platforms. A set of three example implementations of RHEAS in the United States and Kenya are described to demonstrate the different features of the system in real-world applications. PMID:28545077

The Regional Hydrologic Extremes Assessment System: A software framework for hydrologic modeling and data assimilation.

PubMed

Andreadis, Konstantinos M; Das, Narendra; Stampoulis, Dimitrios; Ines, Amor; Fisher, Joshua B; Granger, Stephanie; Kawata, Jessie; Han, Eunjin; Behrangi, Ali

2017-01-01

The Regional Hydrologic Extremes Assessment System (RHEAS) is a prototype software framework for hydrologic modeling and data assimilation that automates the deployment of water resources nowcasting and forecasting applications. A spatially-enabled database is a key component of the software that can ingest a suite of satellite and model datasets while facilitating the interfacing with Geographic Information System (GIS) applications. The datasets ingested are obtained from numerous space-borne sensors and represent multiple components of the water cycle. The object-oriented design of the software allows for modularity and extensibility, showcased here with the coupling of the core hydrologic model with a crop growth model. RHEAS can exploit multi-threading to scale with increasing number of processors, while the database allows delivery of data products and associated uncertainty through a variety of GIS platforms. A set of three example implementations of RHEAS in the United States and Kenya are described to demonstrate the different features of the system in real-world applications.

Macroscopic description of complex adaptive networks coevolving with dynamic node states.

PubMed

Wiedermann, Marc; Donges, Jonathan F; Heitzig, Jobst; Lucht, Wolfgang; Kurths, Jürgen

2015-05-01

In many real-world complex systems, the time evolution of the network's structure and the dynamic state of its nodes are closely entangled. Here we study opinion formation and imitation on an adaptive complex network which is dependent on the individual dynamic state of each node and vice versa to model the coevolution of renewable resources with the dynamics of harvesting agents on a social network. The adaptive voter model is coupled to a set of identical logistic growth models and we mainly find that, in such systems, the rate of interactions between nodes as well as the adaptive rewiring probability are crucial parameters for controlling the sustainability of the system's equilibrium state. We derive a macroscopic description of the system in terms of ordinary differential equations which provides a general framework to model and quantify the influence of single node dynamics on the macroscopic state of the network. The thus obtained framework is applicable to many fields of study, such as epidemic spreading, opinion formation, or socioecological modeling.

Integrating Cognitive Task Analysis into Instructional Systems Development.

ERIC Educational Resources Information Center

Ryder, Joan M.; Redding, Richard E.

1993-01-01

Discussion of instructional systems development (ISD) focuses on recent developments in cognitive task analysis and describes the Integrated Task Analysis Model, a framework for integrating cognitive and behavioral task analysis methods within the ISD model. Three components of expertise are analyzed: skills, knowledge, and mental models. (96…

Frequency response function-based explicit framework for dynamic identification in human-structure systems

NASA Astrophysics Data System (ADS)

Wei, Xiaojun; Živanović, Stana

2018-05-01

The aim of this paper is to propose a novel theoretical framework for dynamic identification in a structure occupied by a single human. The framework enables the prediction of the dynamics of the human-structure system from the known properties of the individual system components, the identification of human body dynamics from the known dynamics of the empty structure and the human-structure system and the identification of the properties of the structure from the known dynamics of the human and the human-structure system. The novelty of the proposed framework is the provision of closed-form solutions in terms of frequency response functions obtained by curve fitting measured data. The advantages of the framework over existing methods are that there is neither need for nonlinear optimisation nor need for spatial/modal models of the empty structure and the human-structure system. In addition, the second-order perturbation method is employed to quantify the effect of uncertainties in human body dynamics on the dynamic identification of the empty structure and the human-structure system. The explicit formulation makes the method computationally efficient and straightforward to use. A series of numerical examples and experiments are provided to illustrate the working of the method.

Vulnerable Populations in Hospital and Health Care Emergency Preparedness Planning: A Comprehensive Framework for Inclusion.

PubMed

Kreisberg, Debra; Thomas, Deborah S K; Valley, Morgan; Newell, Shannon; Janes, Enessa; Little, Charles

2016-04-01

As attention to emergency preparedness becomes a critical element of health care facility operations planning, efforts to recognize and integrate the needs of vulnerable populations in a comprehensive manner have lagged. This not only results in decreased levels of equitable service, but also affects the functioning of the health care system in disasters. While this report emphasizes the United States context, the concepts and approaches apply beyond this setting. This report: (1) describes a conceptual framework that provides a model for the inclusion of vulnerable populations into integrated health care and public health preparedness; and (2) applies this model to a pilot study. The framework is derived from literature, hospital regulatory policy, and health care standards, laying out the communication and relational interfaces that must occur at the systems, organizational, and community levels for a successful multi-level health care systems response that is inclusive of diverse populations explicitly. The pilot study illustrates the application of key elements of the framework, using a four-pronged approach that incorporates both quantitative and qualitative methods for deriving information that can inform hospital and health facility preparedness planning. The conceptual framework and model, applied to a pilot project, guide expanded work that ultimately can result in methodologically robust approaches to comprehensively incorporating vulnerable populations into the fabric of hospital disaster preparedness at levels from local to national, thus supporting best practices for a community resilience approach to disaster preparedness.

Patch models and their applications to multivehicle command and control.

PubMed

Rao, Venkatesh G; D'Andrea, Raffaello

2007-06-01

We introduce patch models, a computational modeling formalism for multivehicle combat domains, based on spatiotemporal abstraction methods developed in the computer science community. The framework yields models that are expressive enough to accommodate nontrivial controlled vehicle dynamics while being within the representational capabilities of common artificial intelligence techniques used in the construction of autonomous systems. The framework allows several key design requirements of next-generation network-centric command and control systems, such as maintenance of shared situation awareness, to be achieved. Major features include support for multiple situation models at each decision node and rapid mission plan adaptation. We describe the formal specification of patch models and our prototype implementation, i.e., Patchworks. The capabilities of patch models are validated through a combat mission simulation in Patchworks, which involves two defending teams protecting a camp from an enemy attacking team.

Temporal efficiency evaluation and small-worldness characterization in temporal networks

PubMed Central

Dai, Zhongxiang; Chen, Yu; Li, Junhua; Fam, Johnson; Bezerianos, Anastasios; Sun, Yu

2016-01-01

Numerous real-world systems can be modeled as networks. To date, most network studies have been conducted assuming stationary network characteristics. Many systems, however, undergo topological changes over time. Temporal networks, which incorporate time into conventional network models, are therefore more accurate representations of such dynamic systems. Here, we introduce a novel generalized analytical framework for temporal networks, which enables 1) robust evaluation of the efficiency of temporal information exchange using two new network metrics and 2) quantitative inspection of the temporal small-worldness. Specifically, we define new robust temporal network efficiency measures by incorporating the time dependency of temporal distance. We propose a temporal regular network model, and based on this plus the redefined temporal efficiency metrics and widely used temporal random network models, we introduce a quantitative approach for identifying temporal small-world architectures (featuring high temporal network efficiency both globally and locally). In addition, within this framework, we can uncover network-specific dynamic structures. Applications to brain networks, international trade networks, and social networks reveal prominent temporal small-world properties with distinct dynamic network structures. We believe that the framework can provide further insight into dynamic changes in the network topology of various real-world systems and significantly promote research on temporal networks. PMID:27682314

Temporal efficiency evaluation and small-worldness characterization in temporal networks

NASA Astrophysics Data System (ADS)

Dai, Zhongxiang; Chen, Yu; Li, Junhua; Fam, Johnson; Bezerianos, Anastasios; Sun, Yu

2016-09-01

Numerous real-world systems can be modeled as networks. To date, most network studies have been conducted assuming stationary network characteristics. Many systems, however, undergo topological changes over time. Temporal networks, which incorporate time into conventional network models, are therefore more accurate representations of such dynamic systems. Here, we introduce a novel generalized analytical framework for temporal networks, which enables 1) robust evaluation of the efficiency of temporal information exchange using two new network metrics and 2) quantitative inspection of the temporal small-worldness. Specifically, we define new robust temporal network efficiency measures by incorporating the time dependency of temporal distance. We propose a temporal regular network model, and based on this plus the redefined temporal efficiency metrics and widely used temporal random network models, we introduce a quantitative approach for identifying temporal small-world architectures (featuring high temporal network efficiency both globally and locally). In addition, within this framework, we can uncover network-specific dynamic structures. Applications to brain networks, international trade networks, and social networks reveal prominent temporal small-world properties with distinct dynamic network structures. We believe that the framework can provide further insight into dynamic changes in the network topology of various real-world systems and significantly promote research on temporal networks.

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...

SPARK: A Framework for Multi-Scale Agent-Based Biomedical Modeling.

PubMed

Solovyev, Alexey; Mikheev, Maxim; Zhou, Leming; Dutta-Moscato, Joyeeta; Ziraldo, Cordelia; An, Gary; Vodovotz, Yoram; Mi, Qi

2010-01-01

Multi-scale modeling of complex biological systems remains a central challenge in the systems biology community. A method of dynamic knowledge representation known as agent-based modeling enables the study of higher level behavior emerging from discrete events performed by individual components. With the advancement of computer technology, agent-based modeling has emerged as an innovative technique to model the complexities of systems biology. In this work, the authors describe SPARK (Simple Platform for Agent-based Representation of Knowledge), a framework for agent-based modeling specifically designed for systems-level biomedical model development. SPARK is a stand-alone application written in Java. It provides a user-friendly interface, and a simple programming language for developing Agent-Based Models (ABMs). SPARK has the following features specialized for modeling biomedical systems: 1) continuous space that can simulate real physical space; 2) flexible agent size and shape that can represent the relative proportions of various cell types; 3) multiple spaces that can concurrently simulate and visualize multiple scales in biomedical models; 4) a convenient graphical user interface. Existing ABMs of diabetic foot ulcers and acute inflammation were implemented in SPARK. Models of identical complexity were run in both NetLogo and SPARK; the SPARK-based models ran two to three times faster.

Modelling and analysis of the sugar cataract development process using stochastic hybrid systems.

PubMed

Riley, D; Koutsoukos, X; Riley, K

2009-05-01

Modelling and analysis of biochemical systems such as sugar cataract development (SCD) are critical because they can provide new insights into systems, which cannot be easily tested with experiments; however, they are challenging problems due to the highly coupled chemical reactions that are involved. The authors present a stochastic hybrid system (SHS) framework for modelling biochemical systems and demonstrate the approach for the SCD process. A novel feature of the framework is that it allows modelling the effect of drug treatment on the system dynamics. The authors validate the three sugar cataract models by comparing trajectories computed by two simulation algorithms. Further, the authors present a probabilistic verification method for computing the probability of sugar cataract formation for different chemical concentrations using safety and reachability analysis methods for SHSs. The verification method employs dynamic programming based on a discretisation of the state space and therefore suffers from the curse of dimensionality. To analyse the SCD process, a parallel dynamic programming implementation that can handle large, realistic systems was developed. Although scalability is a limiting factor, this work demonstrates that the proposed method is feasible for realistic biochemical systems.

What can we learn from international comparisons of health systems and health system reform?

PubMed Central

McPake, B.; Mills, A.

2000-01-01

Most commonly, lessons derived from comparisons of international health sector reform can only be generalized in a limited way to similar countries. However, there is little guidance as to what constitutes "similarity" in this respect. We propose that a framework for assessing similarity could be derived from the performance of individual policies in different contexts, and from the cause and effect processes related to the policies. We demonstrate this process by considering research evidence in the "public-private mix", and propose variables for an initial framework that we believe determine private involvement in the public health sector. The most influential model of public leadership places the private role in a contracting framework. Research in countries that have adopted this model suggests an additional list of variables to add to the framework. The variables can be grouped under the headings "demand factors", "supply factors", and "strength of the public sector". These illustrate the nature of a framework that could emerge, and which would help countries aiming to learn from international experience. PMID:10916918

Agent-based modeling of the spread of influenza-like illness in an emergency department: a simulation study.

PubMed

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

2011-11-01

The objective of this paper was to develop an agent-based modeling framework in order to simulate the spread of influenza virus infection on a layout based on a representative hospital emergency department in Winnipeg, Canada. In doing so, the study complements mathematical modeling techniques for disease spread, as well as modeling applications focused on the spread of antibiotic-resistant nosocomial infections in hospitals. Twenty different emergency department scenarios were simulated, with further simulation of four infection control strategies. The agent-based modeling approach represents systems modeling, in which the emergency department was modeled as a collection of agents (patients and healthcare workers) and their individual characteristics, behaviors, and interactions. The framework was coded in C++ using Qt4 libraries running under the Linux operating system. A simple ordinary least squares (OLS) regression was used to analyze the data, in which the percentage of patients that became infected in one day within the simulation was the dependent variable. The results suggest that within the given instance context, patient-oriented infection control policies (alternate treatment streams, masking symptomatic patients) tend to have a larger effect than policies that target healthcare workers. The agent-based modeling framework is a flexible tool that can be made to reflect any given environment; it is also a decision support tool for practitioners and policymakers to assess the relative impact of infection control strategies. The framework illuminates scenarios worthy of further investigation, as well as counterintuitive findings.

Learning in the model space for cognitive fault diagnosis.

PubMed

Chen, Huanhuan; Tino, Peter; Rodan, Ali; Yao, Xin

2014-01-01

The emergence of large sensor networks has facilitated the collection of large amounts of real-time data to monitor and control complex engineering systems. However, in many cases the collected data may be incomplete or inconsistent, while the underlying environment may be time-varying or unformulated. In this paper, we develop an innovative cognitive fault diagnosis framework that tackles the above challenges. This framework investigates fault diagnosis in the model space instead of the signal space. Learning in the model space is implemented by fitting a series of models using a series of signal segments selected with a sliding window. By investigating the learning techniques in the fitted model space, faulty models can be discriminated from healthy models using a one-class learning algorithm. The framework enables us to construct a fault library when unknown faults occur, which can be regarded as cognitive fault isolation. This paper also theoretically investigates how to measure the pairwise distance between two models in the model space and incorporates the model distance into the learning algorithm in the model space. The results on three benchmark applications and one simulated model for the Barcelona water distribution network confirm the effectiveness of the proposed framework.

A Cloud Based Framework For Monitoring And Predicting Subsurface System Behaviour

NASA Astrophysics Data System (ADS)

Versteeg, R. J.; Rodzianko, A.; Johnson, D. V.; Soltanian, M. R.; Dwivedi, D.; Dafflon, B.; Tran, A. P.; Versteeg, O. J.

2015-12-01

Subsurface system behavior is driven and controlled by the interplay of physical, chemical, and biological processes which occur at multiple temporal and spatial scales. Capabilities to monitor, understand and predict this behavior in an effective and timely manner are needed for both scientific purposes and for effective subsurface system management. Such capabilities require three elements: Models, Data and an enabling cyberinfrastructure, which allow users to use these models and data in an effective manner. Under a DOE Office of Science funded STTR award Subsurface Insights and LBNL have designed and implemented a cloud based predictive assimilation framework (PAF) which automatically ingests, controls quality and stores heterogeneous physical and chemical subsurface data and processes these data using different inversion and modeling codes to provide information on the current state and evolution of subsurface systems. PAF is implemented as a modular cloud based software application with five components: (1) data acquisition, (2) data management, (3) data assimilation and processing, (4) visualization and result delivery and (5) orchestration. Serverside PAF uses ZF2 (a PHP web application framework) and Python and both open source (ODM2) and in house developed data models. Clientside PAF uses CSS and JS to allow for interactive data visualization and analysis. Client side modularity (which allows for a responsive interface) of the system is achieved by implementing each core capability of PAF (such as data visualization, user configuration and control, electrical geophysical monitoring and email/SMS alerts on data streams) as a SPA (Single Page Application). One of the recent enhancements is the full integration of a number of flow and mass transport and parameter estimation codes (e.g., MODFLOW, MT3DMS, PHT3D, TOUGH, PFLOTRAN) in this framework. This integration allows for autonomous and user controlled modeling of hydrological and geochemical processes. In our presentation we will discuss our software architecture and present the results of using these codes and the overall developed performance of our framework using hydrological, geochemical and geophysical data from the LBNL SFA2 Rifle field site.

Multi-Disciplinary Analysis and Optimization Frameworks

NASA Technical Reports Server (NTRS)

Naiman, Cynthia Gutierrez

2009-01-01

Since July 2008, the Multidisciplinary Analysis & Optimization Working Group (MDAO WG) of the Systems Analysis Design & Optimization (SAD&O) discipline in the Fundamental Aeronautics Program s Subsonic Fixed Wing (SFW) project completed one major milestone, Define Architecture & Interfaces for Next Generation Open Source MDAO Framework Milestone (9/30/08), and is completing the Generation 1 Framework validation milestone, which is due December 2008. Included in the presentation are: details of progress on developing the Open MDAO framework, modeling and testing the Generation 1 Framework, progress toward establishing partnerships with external parties, and discussion of additional potential collaborations

Modeling Real-Time Coordination of Distributed Expertise and Event Response in NASA Mission Control Center Operations

NASA Astrophysics Data System (ADS)

Onken, Jeffrey

This dissertation introduces a multidisciplinary framework for the enabling of future research and analysis of alternatives for control centers for real-time operations of safety-critical systems. The multidisciplinary framework integrates functional and computational models that describe the dynamics in fundamental concepts of previously disparate engineering and psychology research disciplines, such as group performance and processes, supervisory control, situation awareness, events and delays, and expertise. The application in this dissertation is the real-time operations within the NASA Mission Control Center in Houston, TX. This dissertation operationalizes the framework into a model and simulation, which simulates the functional and computational models in the framework according to user-configured scenarios for a NASA human-spaceflight mission. The model and simulation generates data according to the effectiveness of the mission-control team in supporting the completion of mission objectives and detecting, isolating, and recovering from anomalies. Accompanying the multidisciplinary framework is a proof of concept, which demonstrates the feasibility of such a framework. The proof of concept demonstrates that variability occurs where expected based on the models. The proof of concept also demonstrates that the data generated from the model and simulation is useful for analyzing and comparing MCC configuration alternatives because an investigator can give a diverse set of scenarios to the simulation and the output compared in detail to inform decisions about the effect of MCC configurations on mission operations performance.

Gauge invariance of phenomenological models of the interaction of quantum dissipative systems with electromagnetic fields

NASA Astrophysics Data System (ADS)

Tokman, M. D.

2009-05-01

We discuss specific features of the electrodynamic characteristics of quantum systems within the framework of models that include a phenomenological description of the relaxation processes. As is shown by W. E. Lamb, Jr., R. R. Schlicher, and M. O. Scully [Phys. Rev. A 36, 2763 (1987)], the use of phenomenological relaxation operators, which adequately describe the attenuation of eigenvibrations of a quantum system, may lead to incorrect solutions in the presence of external electromagnetic fields determined by the vector potential for different resonance processes. This incorrectness can be eliminated by giving a gauge-invariant form to the relaxation operator. Lamb, Jr., proposed the corresponding gauge-invariant modification for the Weisskopf-Wigner relaxation operator, which is introduced directly into the Schrödinger equation within the framework of the two-level approximation. In the present paper, this problem is studied for the von Neumann equation supplemented by a relaxation operator. First, we show that the solution of the equation for the density matrix with the relaxation operator correctly obtained “from the first principles” has properties that ensure gauge invariance for the observables. Second, we propose a common recipe for transformation of the phenomenological relaxation operator into the correct (gauge-invariant) form in the density-matrix equations for a multilevel system. Also, we discuss the methods of elimination of other inaccuracies (not related to the gauge-invariance problem) which arise if the electrodynamic response of a dissipative quantum system is calculated within the framework of simplified relaxation models (first of all, the model corresponding to constant relaxation rates of coherences in quantum transitions). Examples illustrating the correctness of the results obtained within the framework of the proposed methods in contrast to inaccuracy of the results of the standard calculation techniques are given.

Can model-free reinforcement learning explain deontological moral judgments?

PubMed

Ayars, Alisabeth

2016-05-01

Dual-systems frameworks propose that moral judgments are derived from both an immediate emotional response, and controlled/rational cognition. Recently Cushman (2013) proposed a new dual-system theory based on model-free and model-based reinforcement learning. Model-free learning attaches values to actions based on their history of reward and punishment, and explains some deontological, non-utilitarian judgments. Model-based learning involves the construction of a causal model of the world and allows for far-sighted planning; this form of learning fits well with utilitarian considerations that seek to maximize certain kinds of outcomes. I present three concerns regarding the use of model-free reinforcement learning to explain deontological moral judgment. First, many actions that humans find aversive from model-free learning are not judged to be morally wrong. Moral judgment must require something in addition to model-free learning. Second, there is a dearth of evidence for central predictions of the reinforcement account-e.g., that people with different reinforcement histories will, all else equal, make different moral judgments. Finally, to account for the effect of intention within the framework requires certain assumptions which lack support. These challenges are reasonable foci for future empirical/theoretical work on the model-free/model-based framework. Copyright © 2016 Elsevier B.V. All rights reserved.

Kernel-Based Approximate Dynamic Programming Using Bellman Residual Elimination

DTIC Science & Technology

2010-02-01

framework is the ability to utilize stochastic system models, thereby allowing the system to make sound decisions even if there is randomness in the system ...approximate policy when a system model is unavailable. We present theoretical analysis of all BRE algorithms proving convergence to the optimal policy in...policies based on MDPs is that there may be parameters of the system model that are poorly known and/or vary with time as the system operates. System

Evaluating probabilistic dengue risk forecasts from a prototype early warning system for Brazil.

PubMed

Lowe, Rachel; Coelho, Caio As; Barcellos, Christovam; Carvalho, Marilia Sá; Catão, Rafael De Castro; Coelho, Giovanini E; Ramalho, Walter Massa; Bailey, Trevor C; Stephenson, David B; Rodó, Xavier

2016-02-24

Recently, a prototype dengue early warning system was developed to produce probabilistic forecasts of dengue risk three months ahead of the 2014 World Cup in Brazil. Here, we evaluate the categorical dengue forecasts across all microregions in Brazil, using dengue cases reported in June 2014 to validate the model. We also compare the forecast model framework to a null model, based on seasonal averages of previously observed dengue incidence. When considering the ability of the two models to predict high dengue risk across Brazil, the forecast model produced more hits and fewer missed events than the null model, with a hit rate of 57% for the forecast model compared to 33% for the null model. This early warning model framework may be useful to public health services, not only ahead of mass gatherings, but also before the peak dengue season each year, to control potentially explosive dengue epidemics.

Bayesian Parameter Inference and Model Selection by Population Annealing in Systems Biology

PubMed Central

Murakami, Yohei

2014-01-01

Parameter inference and model selection are very important for mathematical modeling in systems biology. Bayesian statistics can be used to conduct both parameter inference and model selection. Especially, the framework named approximate Bayesian computation is often used for parameter inference and model selection in systems biology. However, Monte Carlo methods needs to be used to compute Bayesian posterior distributions. In addition, the posterior distributions of parameters are sometimes almost uniform or very similar to their prior distributions. In such cases, it is difficult to choose one specific value of parameter with high credibility as the representative value of the distribution. To overcome the problems, we introduced one of the population Monte Carlo algorithms, population annealing. Although population annealing is usually used in statistical mechanics, we showed that population annealing can be used to compute Bayesian posterior distributions in the approximate Bayesian computation framework. To deal with un-identifiability of the representative values of parameters, we proposed to run the simulations with the parameter ensemble sampled from the posterior distribution, named “posterior parameter ensemble”. We showed that population annealing is an efficient and convenient algorithm to generate posterior parameter ensemble. We also showed that the simulations with the posterior parameter ensemble can, not only reproduce the data used for parameter inference, but also capture and predict the data which was not used for parameter inference. Lastly, we introduced the marginal likelihood in the approximate Bayesian computation framework for Bayesian model selection. We showed that population annealing enables us to compute the marginal likelihood in the approximate Bayesian computation framework and conduct model selection depending on the Bayes factor. PMID:25089832

Multilevel analysis of sports video sequences

NASA Astrophysics Data System (ADS)

Han, Jungong; Farin, Dirk; de With, Peter H. N.

2006-01-01

We propose a fully automatic and flexible framework for analysis and summarization of tennis broadcast video sequences, using visual features and specific game-context knowledge. Our framework can analyze a tennis video sequence at three levels, which provides a broad range of different analysis results. The proposed framework includes novel pixel-level and object-level tennis video processing algorithms, such as a moving-player detection taking both the color and the court (playing-field) information into account, and a player-position tracking algorithm based on a 3-D camera model. Additionally, we employ scene-level models for detecting events, like service, base-line rally and net-approach, based on a number real-world visual features. The system can summarize three forms of information: (1) all court-view playing frames in a game, (2) the moving trajectory and real-speed of each player, as well as relative position between the player and the court, (3) the semantic event segments in a game. The proposed framework is flexible in choosing the level of analysis that is desired. It is effective because the framework makes use of several visual cues obtained from the real-world domain to model important events like service, thereby increasing the accuracy of the scene-level analysis. The paper presents attractive experimental results highlighting the system efficiency and analysis capabilities.

BEATBOX v1.0: Background Error Analysis Testbed with Box Models

NASA Astrophysics Data System (ADS)

Knote, Christoph; Barré, Jérôme; Eckl, Max

2018-02-01

The Background Error Analysis Testbed (BEATBOX) is a new data assimilation framework for box models. Based on the BOX Model eXtension (BOXMOX) to the Kinetic Pre-Processor (KPP), this framework allows users to conduct performance evaluations of data assimilation experiments, sensitivity analyses, and detailed chemical scheme diagnostics from an observation simulation system experiment (OSSE) point of view. The BEATBOX framework incorporates an observation simulator and a data assimilation system with the possibility of choosing ensemble, adjoint, or combined sensitivities. A user-friendly, Python-based interface allows for the tuning of many parameters for atmospheric chemistry and data assimilation research as well as for educational purposes, for example observation error, model covariances, ensemble size, perturbation distribution in the initial conditions, and so on. In this work, the testbed is described and two case studies are presented to illustrate the design of a typical OSSE experiment, data assimilation experiments, a sensitivity analysis, and a method for diagnosing model errors. BEATBOX is released as an open source tool for the atmospheric chemistry and data assimilation communities.

Computational modeling of Metal-Organic Frameworks

NASA Astrophysics Data System (ADS)

Sung, Jeffrey Chuen-Fai

In this work, the metal-organic frameworks MIL-53(Cr), DMOF-2,3-NH 2Cl, DMOF-2,5-NH2Cl, and HKUST-1 were modeled using molecular mechanics and electronic structure. The effect of electronic polarization on the adsorption of water in MIL-53(Cr) was studied using molecular dynamics simulations of water-loaded MIL-53 systems with both polarizable and non-polarizable force fields. Molecular dynamics simulations of the full systems and DFT calculations on representative framework clusters were utilized to study the difference in nitrogen adsorption between DMOF-2,3-NH2Cl and DMOF-2,5-NH 2Cl. Finally, the control of proton conduction in HKUST-1 by complexation of molecules to the Cu open metal site was investigated using the MS-EVB methodology.

A framework for unravelling the complexities of unsustainable water resource use

NASA Astrophysics Data System (ADS)

Dermody, Brian; Bierkens, Marc; Wassen, Martin; Dekker, Stefan

2016-04-01

The majority of unsustainable water resource use is associated with food production, with the agricultural sector accounting for up to 70% of total freshwater use by humans. Water resource use in food production emerges as a result of dynamic interactions between humans and their environment in importing and exporting regions as well as the physical and socioeconomic trade infrastructure linking the two. Thus in order to understand unsustainable water resource use, it is essential to understand the complex socioecological food production and trade system. We present a modelling framework of the food production and trade system that facilitates an understanding of complex socioenvironmental processes that lead to unsustainable water resource use. Our framework is based on a coupling of the global hydrological model PC Raster Global Water Balance (PCR-GLOBWB) with a multi-agent socioeconomic food production and trade network. In our framework, agents perceive environmental conditions. They make food supply decisions based upon those perceptions and the heterogeneous socioeconomic conditions in which they exist. Agent decisions modify land and water resources. Those environmental changes feedback to influence decision making further. The framework presented has the potential to go beyond a diagnosis of the causes of unsustainable water resource and provide pathways towards a sustainable food system in terms of water resources.

An integrated chronic disease management model: a diagonal approach to health system strengthening in South Africa.

PubMed

Mahomed, Ozayr Haroon; Asmall, Shaidah; Freeman, Melvyn

2014-11-01

The integrated chronic disease management model provides a systematic framework for creating a fundamental change in the orientation of the health system. This model adopts a diagonal approach to health system strengthening by establishing a service-linked base to training, supervision, and the opportunity to try out, assess, and implement integrated interventions.

Scaling the Pyramid Model across Complex Systems Providing Early Care for Preschoolers: Exploring How Models for Decision Making May Enhance Implementation Science

ERIC Educational Resources Information Center

Johnson, LeAnne D.

2017-01-01

Bringing effective practices to scale across large systems requires attending to how information and belief systems come together in decisions to adopt, implement, and sustain those practices. Statewide scaling of the Pyramid Model, a framework for positive behavior intervention and support, across different types of early childhood programs…

Development and implementation of an integrated chronic disease model in South Africa: lessons in the management of change through improving the quality of clinical practice

PubMed Central

Asmall, Shaidah

2015-01-01

Background South Africa is facing a complex burden of disease arising from a combination of chronic infectious illness and non-communicable diseases. As the burden of chronic diseases (communicable and non-communicable) increases, providing affordable and effective care to the increasing numbers of chronic patients will be an immense challenge. Methods The framework recommended by the Medical Research Council of the United Kingdom for the development and evaluation of complex health interventions was used to conceptualise the intervention. The breakthrough series was utilised for the implementation process. These two frameworks were embedded within the clinical practice improvement model that served as the overarching framework for the development and implementation of the model. Results The Chronic Care Model was ideally suited to improve the facility component and patient experience; however, the deficiencies in other aspects of the health system building blocks necessitated a hybrid model. An integrated chronic disease management model using a health systems approach was initiated across 42 primary health care facilities. The interventions were implemented in a phased approach using learning sessions and action periods to introduce the planned and targeted changes. Conclusion The implementation of the integrated chronic disease management model is feasible at primary care in South Africa provided that systemic challenges and change management are addressed during the implementation process. PMID:26528101

Development and implementation of an integrated chronic disease model in South Africa: lessons in the management of change through improving the quality of clinical practice.

PubMed

Mahomed, Ozayr Haroon; Asmall, Shaidah

2015-01-01

South Africa is facing a complex burden of disease arising from a combination of chronic infectious illness and non-communicable diseases. As the burden of chronic diseases (communicable and non-communicable) increases, providing affordable and effective care to the increasing numbers of chronic patients will be an immense challenge. The framework recommended by the Medical Research Council of the United Kingdom for the development and evaluation of complex health interventions was used to conceptualise the intervention. The breakthrough series was utilised for the implementation process. These two frameworks were embedded within the clinical practice improvement model that served as the overarching framework for the development and implementation of the model. The Chronic Care Model was ideally suited to improve the facility component and patient experience; however, the deficiencies in other aspects of the health system building blocks necessitated a hybrid model. An integrated chronic disease management model using a health systems approach was initiated across 42 primary health care facilities. The interventions were implemented in a phased approach using learning sessions and action periods to introduce the planned and targeted changes. The implementation of the integrated chronic disease management model is feasible at primary care in South Africa provided that systemic challenges and change management are addressed during the implementation process.

A system dynamics optimization framework to achieve population desired of average weight target

NASA Astrophysics Data System (ADS)

Abidin, Norhaslinda Zainal; Zulkepli, Jafri Haji; Zaibidi, Nerda Zura

2017-11-01

Obesity is becoming a serious problem in Malaysia as it has been rated as the highest among Asian countries. The aim of the paper is to propose a system dynamics (SD) optimization framework to achieve population desired weight target based on the changes in physical activity behavior and its association to weight and obesity. The system dynamics approach of stocks and flows diagram was used to quantitatively model the impact of both behavior on the population's weight and obesity trends. This work seems to bring this idea together and highlighting the interdependence of the various aspects of eating and physical activity behavior on the complex of human weight regulation system. The model was used as an experimentation vehicle to investigate the impacts of changes in physical activity on weight and prevalence of obesity implications. This framework paper provides evidence on the usefulness of SD optimization as a strategic decision making approach to assist in decision making related to obesity prevention. SD applied in this research is relatively new in Malaysia and has a high potential to apply to any feedback models that address the behavior cause to obesity.

Framework Programmable Platform for the Advanced Software Development Workstation (FPP/ASDW). Demonstration framework document. Volume 2: Framework process description

NASA Technical Reports Server (NTRS)

Mayer, Richard J.; Blinn, Thomas M.; Dewitte, Paula S.; Crump, John W.; Ackley, Keith A.

1992-01-01

In the second volume of the Demonstration Framework Document, the graphical representation of the demonstration framework is given. This second document was created to facilitate the reading and comprehension of the demonstration framework. It is designed to be viewed in parallel with Section 4.2 of the first volume to help give a picture of the relationships between the UOB's (Unit of Behavior) of the model. The model is quite large and the design team felt that this form of presentation would make it easier for the reader to get a feel for the processes described in this document. The IDEF3 (Process Description Capture Method) diagrams of the processes of an Information System Development are presented. Volume 1 describes the processes and the agents involved with each process, while this volume graphically shows the precedence relationships among the processes.

Measurement in Service Businesses: Challenges and Future Directions

NASA Astrophysics Data System (ADS)

Tyagi, Rajesh Kumar

This chapter presents challenges faced by service businesses while implementing a measurement system. A review of existing frameworks is presented and a new framework, the Service Scorecard, is introduced. The Service Scorecard is an adaptation of the Six Sigma Business Scorecard for the service sector. The framework has also been influenced by existing frameworks such as the Malcom Baldrige award criteria, the Balanced Scorecard, the European Quality award and the Service Profit Chain model. The seven elements of the Service Scorecard are Growth, Leadership, Acceleration, Collaboration, Innovation, Execution, and Retention. The examples of measurement systems are presented with concrete real-world case examples. Final thoughts and the challenges faced are also presented.

Robustness Analysis of Integrated LPV-FDI Filters and LTI-FTC System for a Transport Aircraft

NASA Technical Reports Server (NTRS)

Khong, Thuan H.; Shin, Jong-Yeob

2007-01-01

This paper proposes an analysis framework for robustness analysis of a nonlinear dynamics system that can be represented by a polynomial linear parameter varying (PLPV) system with constant bounded uncertainty. The proposed analysis framework contains three key tools: 1) a function substitution method which can convert a nonlinear system in polynomial form into a PLPV system, 2) a matrix-based linear fractional transformation (LFT) modeling approach, which can convert a PLPV system into an LFT system with the delta block that includes key uncertainty and scheduling parameters, 3) micro-analysis, which is a well known robust analysis tool for linear systems. The proposed analysis framework is applied to evaluating the performance of the LPV-fault detection and isolation (FDI) filters of the closed-loop system of a transport aircraft in the presence of unmodeled actuator dynamics and sensor gain uncertainty. The robustness analysis results are compared with nonlinear time simulations.

Evaluating Health Information Systems Using Ontologies.

PubMed

Eivazzadeh, Shahryar; Anderberg, Peter; Larsson, Tobias C; Fricker, Samuel A; Berglund, Johan

2016-06-16

There are several frameworks that attempt to address the challenges of evaluation of health information systems by offering models, methods, and guidelines about what to evaluate, how to evaluate, and how to report the evaluation results. Model-based evaluation frameworks usually suggest universally applicable evaluation aspects but do not consider case-specific aspects. On the other hand, evaluation frameworks that are case specific, by eliciting user requirements, limit their output to the evaluation aspects suggested by the users in the early phases of system development. In addition, these case-specific approaches extract different sets of evaluation aspects from each case, making it challenging to collectively compare, unify, or aggregate the evaluation of a set of heterogeneous health information systems. The aim of this paper is to find a method capable of suggesting evaluation aspects for a set of one or more health information systems-whether similar or heterogeneous-by organizing, unifying, and aggregating the quality attributes extracted from those systems and from an external evaluation framework. On the basis of the available literature in semantic networks and ontologies, a method (called Unified eValuation using Ontology; UVON) was developed that can organize, unify, and aggregate the quality attributes of several health information systems into a tree-style ontology structure. The method was extended to integrate its generated ontology with the evaluation aspects suggested by model-based evaluation frameworks. An approach was developed to extract evaluation aspects from the ontology that also considers evaluation case practicalities such as the maximum number of evaluation aspects to be measured or their required degree of specificity. The method was applied and tested in Future Internet Social and Technological Alignment Research (FI-STAR), a project of 7 cloud-based eHealth applications that were developed and deployed across European Union countries. The relevance of the evaluation aspects created by the UVON method for the FI-STAR project was validated by the corresponding stakeholders of each case. These evaluation aspects were extracted from a UVON-generated ontology structure that reflects both the internally declared required quality attributes in the 7 eHealth applications of the FI-STAR project and the evaluation aspects recommended by the Model for ASsessment of Telemedicine applications (MAST) evaluation framework. The extracted evaluation aspects were used to create questionnaires (for the corresponding patients and health professionals) to evaluate each individual case and the whole of the FI-STAR project. The UVON method can provide a relevant set of evaluation aspects for a heterogeneous set of health information systems by organizing, unifying, and aggregating the quality attributes through ontological structures. Those quality attributes can be either suggested by evaluation models or elicited from the stakeholders of those systems in the form of system requirements. The method continues to be systematic, context sensitive, and relevant across a heterogeneous set of health information systems.

The Spatially-Distributed Agroecosystem-Watershed (Ages-W) Hydrologic/Water Quality (H/WQ) model for assessment of conservation effects

USDA-ARS?s Scientific Manuscript database

AgroEcoSystem-Watershed (AgES-W) is a modular, Java-based spatially distributed model which implements hydrologic/water quality (H/WQ) simulation components under the Object Modeling System (OMS3) environmental modeling framework. AgES-W has recently been enhanced with the addition of nitrogen (N) a...

A generic biogeochemical module for Earth system models: Next Generation BioGeoChemical Module (NGBGC), version 1.0

NASA Astrophysics Data System (ADS)

Fang, Y.; Huang, M.; Liu, C.; Li, H.; Leung, L. R.

2013-11-01

Physical and biogeochemical processes regulate soil carbon dynamics and CO2 flux to and from the atmosphere, influencing global climate changes. Integration of these processes into Earth system models (e.g., community land models (CLMs)), however, currently faces three major challenges: (1) extensive efforts are required to modify modeling structures and to rewrite computer programs to incorporate new or updated processes as new knowledge is being generated, (2) computational cost is prohibitively expensive to simulate biogeochemical processes in land models due to large variations in the rates of biogeochemical processes, and (3) various mathematical representations of biogeochemical processes exist to incorporate different aspects of fundamental mechanisms, but systematic evaluation of the different mathematical representations is difficult, if not impossible. To address these challenges, we propose a new computational framework to easily incorporate physical and biogeochemical processes into land models. The new framework consists of a new biogeochemical module, Next Generation BioGeoChemical Module (NGBGC), version 1.0, with a generic algorithm and reaction database so that new and updated processes can be incorporated into land models without the need to manually set up the ordinary differential equations to be solved numerically. The reaction database consists of processes of nutrient flow through the terrestrial ecosystems in plants, litter, and soil. This framework facilitates effective comparison studies of biogeochemical cycles in an ecosystem using different conceptual models under the same land modeling framework. The approach was first implemented in CLM and benchmarked against simulations from the original CLM-CN code. A case study was then provided to demonstrate the advantages of using the new approach to incorporate a phosphorus cycle into CLM. To our knowledge, the phosphorus-incorporated CLM is a new model that can be used to simulate phosphorus limitation on the productivity of terrestrial ecosystems. The method presented here could in theory be applied to simulate biogeochemical cycles in other Earth system models.

Organic Rankine Cycle for Residual Heat to Power Conversion in Natural Gas Compressor Station. Part I: Modelling and Optimisation Framework

NASA Astrophysics Data System (ADS)

Chaczykowski, Maciej

2016-06-01

Basic organic Rankine cycle (ORC), and two variants of regenerative ORC have been considered for the recovery of exhaust heat from natural gas compressor station. The modelling framework for ORC systems has been presented and the optimisation of the systems was carried out with turbine power output as the variable to be maximized. The determination of ORC system design parameters was accomplished by means of the genetic algorithm. The study was aimed at estimating the thermodynamic potential of different ORC configurations with several working fluids employed. The first part of this paper describes the ORC equipment models which are employed to build a NLP formulation to tackle design problems representative for waste energy recovery on gas turbines driving natural gas pipeline compressors.

Advanced process control framework initiative

NASA Astrophysics Data System (ADS)

Hill, Tom; Nettles, Steve

1997-01-01

The semiconductor industry, one the world's most fiercely competitive industries, is driven by increasingly complex process technologies and global competition to improve cycle time, quality, and process flexibility. Due to the complexity of these problems, current process control techniques are generally nonautomated, time-consuming, reactive, nonadaptive, and focused on individual fabrication tools and processes. As the semiconductor industry moves into higher density processes, radical new approaches are required. To address the need for advanced factory-level process control in this environment, Honeywell, Advanced Micro Devices (AMD), and SEMATECH formed the Advanced Process Control Framework Initiative (APCFI) joint research project. The project defines and demonstrates an Advanced Process Control (APC) approach based on SEMATECH's Computer Integrated Manufacturing (CIM) Framework. Its scope includes the coordination of Manufacturing Execution Systems, process control tools, and wafer fabrication equipment to provide necessary process control capabilities. Moreover, it takes advantage of the CIM Framework to integrate and coordinate applications from other suppliers that provide services necessary for the overall system to function. This presentation discusses the key concept of model-based process control that differentiates the APC Framework. This major improvement over current methods enables new systematic process control by linking the knowledge of key process settings to desired product characteristics that reside in models created with commercial model development tools The unique framework-based approach facilitates integration of commercial tools and reuse of their data by tying them together in an object-based structure. The presentation also explores the perspective of each organization's involvement in the APCFI project. Each has complementary goals and expertise to contribute; Honeywell represents the supplier viewpoint, AMD represents the user with 'real customer requirements', and SEMATECH provides a consensus-building organization that widely disseminates technology to suppliers and users in the semiconductor industry that face similar equipment and factory control systems challenges.

How to practice person-centred care: A conceptual framework.

PubMed

Santana, Maria J; Manalili, Kimberly; Jolley, Rachel J; Zelinsky, Sandra; Quan, Hude; Lu, Mingshan

2018-04-01

Globally, health-care systems and organizations are looking to improve health system performance through the implementation of a person-centred care (PCC) model. While numerous conceptual frameworks for PCC exist, a gap remains in practical guidance on PCC implementation. Based on a narrative review of the PCC literature, a generic conceptual framework was developed in collaboration with a patient partner, which synthesizes evidence, recommendations and best practice from existing frameworks and implementation case studies. The Donabedian model for health-care improvement was used to classify PCC domains into the categories of "Structure," "Process" and "Outcome" for health-care quality improvement. The framework emphasizes the structural domain, which relates to the health-care system or context in which care is delivered, providing the foundation for PCC, and influencing the processes and outcomes of care. Structural domains identified include: the creation of a PCC culture across the continuum of care; co-designing educational programs, as well as health promotion and prevention programs with patients; providing a supportive and accommodating environment; and developing and integrating structures to support health information technology and to measure and monitor PCC performance. Process domains describe the importance of cultivating communication and respectful and compassionate care; engaging patients in managing their care; and integration of care. Outcome domains identified include: access to care and Patient-Reported Outcomes. This conceptual framework provides a step-wise roadmap to guide health-care systems and organizations in the provision PCC across various health-care sectors. © 2017 The Authors Health Expectations published by John Wiley & Sons Ltd.

Generation capacity expansion planning in deregulated electricity markets

NASA Astrophysics Data System (ADS)

Sharma, Deepak

With increasing demand of electric power in the context of deregulated electricity markets, a good strategic planning for the growth of the power system is critical for our tomorrow. There is a need to build new resources in the form of generation plants and transmission lines while considering the effects of these new resources on power system operations, market economics and the long-term dynamics of the economy. In deregulation, the exercise of generation planning has undergone a paradigm shift. The first stage of generation planning is now undertaken by the individual investors. These investors see investments in generation capacity as an increasing business opportunity because of the increasing market prices. Therefore, the main objective of such a planning exercise, carried out by individual investors, is typically that of long-term profit maximization. This thesis presents some modeling frameworks for generation capacity expansion planning applicable to independent investor firms in the context of power industry deregulation. These modeling frameworks include various technical and financing issues within the process of power system planning. The proposed modeling frameworks consider the long-term decision making process of investor firms, the discrete nature of generation capacity addition and incorporates transmission network modeling. Studies have been carried out to examine the impact of the optimal investment plans on transmission network loadings in the long-run by integrating the generation capacity expansion planning framework within a modified IEEE 30-bus transmission system network. The work assesses the importance of arriving at an optimal IRR at which the firm's profit maximization objective attains an extremum value. The mathematical model is further improved to incorporate binary variables while considering discrete unit sizes, and subsequently to include the detailed transmission network representation. The proposed models are novel in the sense that the planning horizon is split into plan sub-periods so as to minimize the overall risks associated with long-term plan models, particularly in the context of deregulation.

An Integrated Framework for Model-Based Distributed Diagnosis and Prognosis

NASA Technical Reports Server (NTRS)

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

2012-01-01

Diagnosis and prognosis are necessary tasks for system reconfiguration and fault-adaptive control in complex systems. Diagnosis consists of detection, isolation and identification of faults, while prognosis consists of prediction of the remaining useful life of systems. This paper presents a novel integrated framework for model-based distributed diagnosis and prognosis, where system decomposition is used to enable the diagnosis and prognosis tasks to be performed in a distributed way. We show how different submodels can be automatically constructed to solve the local diagnosis and prognosis problems. We illustrate our approach using a simulated four-wheeled rover for different fault scenarios. Our experiments show that our approach correctly performs distributed fault diagnosis and prognosis in an efficient and robust manner.

SCaLeM: A Framework for Characterizing and Analyzing Execution Models

DOE Office of Scientific and Technical Information (OSTI.GOV)

Chavarría-Miranda, Daniel; Manzano Franco, Joseph B.; Krishnamoorthy, Sriram

2014-10-13

As scalable parallel systems evolve towards more complex nodes with many-core architectures and larger trans-petascale & upcoming exascale deployments, there is a need to understand, characterize and quantify the underlying execution models being used on such systems. Execution models are a conceptual layer between applications & algorithms and the underlying parallel hardware and systems software on which those applications run. This paper presents the SCaLeM (Synchronization, Concurrency, Locality, Memory) framework for characterizing and execution models. SCaLeM consists of three basic elements: attributes, compositions and mapping of these compositions to abstract parallel systems. The fundamental Synchronization, Concurrency, Locality and Memory attributesmore » are used to characterize each execution model, while the combinations of those attributes in the form of compositions are used to describe the primitive operations of the execution model. The mapping of the execution model’s primitive operations described by compositions, to an underlying abstract parallel system can be evaluated quantitatively to determine its effectiveness. Finally, SCaLeM also enables the representation and analysis of applications in terms of execution models, for the purpose of evaluating the effectiveness of such mapping.« less

Applications of General Systems Theory to the Development of an Adjustable Tutorial Software Machine.

ERIC Educational Resources Information Center

Vos, Hans J.

1994-01-01

Describes the construction of a model of computer-assisted instruction using a qualitative block diagram based on general systems theory (GST) as a framework. Subject matter representation is discussed, and appendices include system variables and system equations of the GST model, as well as an example of developing flexible courseware. (Contains…

A systems science perspective and transdisciplinary models for food and nutrition security

PubMed Central

Hammond, Ross A.; Dubé, Laurette

2012-01-01

We argue that food and nutrition security is driven by complex underlying systems and that both research and policy in this area would benefit from a systems approach. We present a framework for such an approach, examine key underlying systems, and identify transdisciplinary modeling tools that may prove especially useful. PMID:22826247

An integrated assessment modeling framework for uncertainty studies in global and regional climate change: the MIT IGSM-CAM (version 1.0)

NASA Astrophysics Data System (ADS)

Monier, E.; Scott, J. R.; Sokolov, A. P.; Forest, C. E.; Schlosser, C. A.

2013-12-01

This paper describes a computationally efficient framework for uncertainty studies in global and regional climate change. In this framework, the Massachusetts Institute of Technology (MIT) Integrated Global System Model (IGSM), an integrated assessment model that couples an Earth system model of intermediate complexity to a human activity model, is linked to the National Center for Atmospheric Research (NCAR) Community Atmosphere Model (CAM). Since the MIT IGSM-CAM framework (version 1.0) incorporates a human activity model, it is possible to analyze uncertainties in emissions resulting from both uncertainties in the underlying socio-economic characteristics of the economic model and in the choice of climate-related policies. Another major feature is the flexibility to vary key climate parameters controlling the climate system response to changes in greenhouse gases and aerosols concentrations, e.g., climate sensitivity, ocean heat uptake rate, and strength of the aerosol forcing. The IGSM-CAM is not only able to realistically simulate the present-day mean climate and the observed trends at the global and continental scale, but it also simulates ENSO variability with realistic time scales, seasonality and patterns of SST anomalies, albeit with stronger magnitudes than observed. The IGSM-CAM shares the same general strengths and limitations as the Coupled Model Intercomparison Project Phase 3 (CMIP3) models in simulating present-day annual mean surface temperature and precipitation. Over land, the IGSM-CAM shows similar biases to the NCAR Community Climate System Model (CCSM) version 3, which shares the same atmospheric model. This study also presents 21st century simulations based on two emissions scenarios (unconstrained scenario and stabilization scenario at 660 ppm CO2-equivalent) similar to, respectively, the Representative Concentration Pathways RCP8.5 and RCP4.5 scenarios, and three sets of climate parameters. Results of the simulations with the chosen climate parameters provide a good approximation for the median, and the 5th and 95th percentiles of the probability distribution of 21st century changes in global mean surface air temperature from previous work with the IGSM. Because the IGSM-CAM framework only considers one particular climate model, it cannot be used to assess the structural modeling uncertainty arising from differences in the parameterization suites of climate models. However, comparison of the IGSM-CAM projections with simulations of 31 CMIP5 models under the RCP4.5 and RCP8.5 scenarios show that the range of warming at the continental scale shows very good agreement between the two ensemble simulations, except over Antarctica, where the IGSM-CAM overestimates the warming. This demonstrates that by sampling the climate system response, the IGSM-CAM, even though it relies on one single climate model, can essentially reproduce the range of future continental warming simulated by more than 30 different models. Precipitation changes projected in the IGSM-CAM simulations and the CMIP5 multi-model ensemble both display a large uncertainty at the continental scale. The two ensemble simulations show good agreement over Asia and Europe. However, the ranges of precipitation changes do not overlap - but display similar size - over Africa and South America, two continents where models generally show little agreement in the sign of precipitation changes and where CCSM3 tends to be an outlier. Overall, the IGSM-CAM provides an efficient and consistent framework to explore the large uncertainty in future projections of global and regional climate change associated with uncertainty in the climate response and projected emissions.

An integrated decision-making framework for transportation architectures: Application to aviation systems design

NASA Astrophysics Data System (ADS)

Lewe, Jung-Ho

The National Transportation System (NTS) is undoubtedly a complex system-of-systems---a collection of diverse 'things' that evolve over time, organized at multiple levels, to achieve a range of possibly conflicting objectives, and never quite behaving as planned. The purpose of this research is to develop a virtual transportation architecture for the ultimate goal of formulating an integrated decision-making framework. The foundational endeavor begins with creating an abstraction of the NTS with the belief that a holistic frame of reference is required to properly study such a multi-disciplinary, trans-domain system. The culmination of the effort produces the Transportation Architecture Field (TAF) as a mental model of the NTS, in which the relationships between four basic entity groups are identified and articulated. This entity-centric abstraction framework underpins the construction of a virtual NTS couched in the form of an agent-based model. The transportation consumers and the service providers are identified as adaptive agents that apply a set of preprogrammed behavioral rules to achieve their respective goals. The transportation infrastructure and multitude of exogenous entities (disruptors and drivers) in the whole system can also be represented without resorting to an extremely complicated structure. The outcome is a flexible, scalable, computational model that allows for examination of numerous scenarios which involve the cascade of interrelated effects of aviation technology, infrastructure, and socioeconomic changes throughout the entire system.

Integrated, systems metabolic picture of acetone-butanol-ethanol fermentation by Clostridium acetobutylicum.

PubMed

Liao, Chen; Seo, Seung-Oh; Celik, Venhar; Liu, Huaiwei; Kong, Wentao; Wang, Yi; Blaschek, Hans; Jin, Yong-Su; Lu, Ting

2015-07-07

Microbial metabolism involves complex, system-level processes implemented via the orchestration of metabolic reactions, gene regulation, and environmental cues. One canonical example of such processes is acetone-butanol-ethanol (ABE) fermentation by Clostridium acetobutylicum, during which cells convert carbon sources to organic acids that are later reassimilated to produce solvents as a strategy for cellular survival. The complexity and systems nature of the process have been largely underappreciated, rendering challenges in understanding and optimizing solvent production. Here, we present a system-level computational framework for ABE fermentation that combines metabolic reactions, gene regulation, and environmental cues. We developed the framework by decomposing the entire system into three modules, building each module separately, and then assembling them back into an integrated system. During the model construction, a bottom-up approach was used to link molecular events at the single-cell level into the events at the population level. The integrated model was able to successfully reproduce ABE fermentations of the WT C. acetobutylicum (ATCC 824), as well as its mutants, using data obtained from our own experiments and from literature. Furthermore, the model confers successful predictions of the fermentations with various network perturbations across metabolic, genetic, and environmental aspects. From foundation to applications, the framework advances our understanding of complex clostridial metabolism and physiology and also facilitates the development of systems engineering strategies for the production of advanced biofuels.

Integrated, systems metabolic picture of acetone-butanol-ethanol fermentation by Clostridium acetobutylicum

PubMed Central

Liao, Chen; Seo, Seung-Oh; Celik, Venhar; Liu, Huaiwei; Kong, Wentao; Wang, Yi; Blaschek, Hans; Jin, Yong-Su; Lu, Ting

2015-01-01

Microbial metabolism involves complex, system-level processes implemented via the orchestration of metabolic reactions, gene regulation, and environmental cues. One canonical example of such processes is acetone-butanol-ethanol (ABE) fermentation by Clostridium acetobutylicum, during which cells convert carbon sources to organic acids that are later reassimilated to produce solvents as a strategy for cellular survival. The complexity and systems nature of the process have been largely underappreciated, rendering challenges in understanding and optimizing solvent production. Here, we present a system-level computational framework for ABE fermentation that combines metabolic reactions, gene regulation, and environmental cues. We developed the framework by decomposing the entire system into three modules, building each module separately, and then assembling them back into an integrated system. During the model construction, a bottom-up approach was used to link molecular events at the single-cell level into the events at the population level. The integrated model was able to successfully reproduce ABE fermentations of the WT C. acetobutylicum (ATCC 824), as well as its mutants, using data obtained from our own experiments and from literature. Furthermore, the model confers successful predictions of the fermentations with various network perturbations across metabolic, genetic, and environmental aspects. From foundation to applications, the framework advances our understanding of complex clostridial metabolism and physiology and also facilitates the development of systems engineering strategies for the production of advanced biofuels. PMID:26100881

Model reduction in mathematical pharmacology : Integration, reduction and linking of PBPK and systems biology models.

PubMed

Snowden, Thomas J; van der Graaf, Piet H; Tindall, Marcus J

2018-03-26

In this paper we present a framework for the reduction and linking of physiologically based pharmacokinetic (PBPK) models with models of systems biology to describe the effects of drug administration across multiple scales. To address the issue of model complexity, we propose the reduction of each type of model separately prior to being linked. We highlight the use of balanced truncation in reducing the linear components of PBPK models, whilst proper lumping is shown to be efficient in reducing typically nonlinear systems biology type models. The overall methodology is demonstrated via two example systems; a model of bacterial chemotactic signalling in Escherichia coli and a model of extracellular regulatory kinase activation mediated via the extracellular growth factor and nerve growth factor receptor pathways. Each system is tested under the simulated administration of three hypothetical compounds; a strong base, a weak base, and an acid, mirroring the parameterisation of pindolol, midazolam, and thiopental, respectively. Our method can produce up to an 80% decrease in simulation time, allowing substantial speed-up for computationally intensive applications including parameter fitting or agent based modelling. The approach provides a straightforward means to construct simplified Quantitative Systems Pharmacology models that still provide significant insight into the mechanisms of drug action. Such a framework can potentially bridge pre-clinical and clinical modelling - providing an intermediate level of model granularity between classical, empirical approaches and mechanistic systems describing the molecular scale.

A framework for optimizing micro-CT in dual-modality micro-CT/XFCT small-animal imaging system

NASA Astrophysics Data System (ADS)

Vedantham, Srinivasan; Shrestha, Suman; Karellas, Andrew; Cho, Sang Hyun

2017-09-01

Dual-modality Computed Tomography (CT)/X-ray Fluorescence Computed Tomography (XFCT) can be a valuable tool for imaging and quantifying the organ and tissue distribution of small concentrations of high atomic number materials in small-animal system. In this work, the framework for optimizing the micro-CT imaging system component of the dual-modality system is described, either when the micro-CT images are concurrently acquired with XFCT and using the x-ray spectral conditions for XFCT, or when the micro-CT images are acquired sequentially and independently of XFCT. This framework utilizes the cascaded systems analysis for task-specific determination of the detectability index using numerical observer models at a given radiation dose, where the radiation dose is determined using Monte Carlo simulations.

An Integrated Framework for Process-Driven Model Construction in Disease Ecology and Animal Health

PubMed Central

Mancy, Rebecca; Brock, Patrick M.; Kao, Rowland R.

2017-01-01

Process models that focus on explicitly representing biological mechanisms are increasingly important in disease ecology and animal health research. However, the large number of process modelling approaches makes it difficult to decide which is most appropriate for a given disease system and research question. Here, we discuss different motivations for using process models and present an integrated conceptual analysis that can be used to guide the construction of infectious disease process models and comparisons between them. Our presentation complements existing work by clarifying the major differences between modelling approaches and their relationship with the biological characteristics of the epidemiological system. We first discuss distinct motivations for using process models in epidemiological research, identifying the key steps in model design and use associated with each. We then present a conceptual framework for guiding model construction and comparison, organised according to key aspects of epidemiological systems. Specifically, we discuss the number and type of disease states, whether to focus on individual hosts (e.g., cows) or groups of hosts (e.g., herds or farms), how space or host connectivity affect disease transmission, whether demographic and epidemiological processes are periodic or can occur at any time, and the extent to which stochasticity is important. We use foot-and-mouth disease and bovine tuberculosis in cattle to illustrate our discussion and support explanations of cases in which different models are used to address similar problems. The framework should help those constructing models to structure their approach to modelling decisions and facilitate comparisons between models in the literature. PMID:29021983

An Integrated Framework for Process-Driven Model Construction in Disease Ecology and Animal Health.

PubMed

Mancy, Rebecca; Brock, Patrick M; Kao, Rowland R

2017-01-01

Process models that focus on explicitly representing biological mechanisms are increasingly important in disease ecology and animal health research. However, the large number of process modelling approaches makes it difficult to decide which is most appropriate for a given disease system and research question. Here, we discuss different motivations for using process models and present an integrated conceptual analysis that can be used to guide the construction of infectious disease process models and comparisons between them. Our presentation complements existing work by clarifying the major differences between modelling approaches and their relationship with the biological characteristics of the epidemiological system. We first discuss distinct motivations for using process models in epidemiological research, identifying the key steps in model design and use associated with each. We then present a conceptual framework for guiding model construction and comparison, organised according to key aspects of epidemiological systems. Specifically, we discuss the number and type of disease states, whether to focus on individual hosts (e.g., cows) or groups of hosts (e.g., herds or farms), how space or host connectivity affect disease transmission, whether demographic and epidemiological processes are periodic or can occur at any time, and the extent to which stochasticity is important. We use foot-and-mouth disease and bovine tuberculosis in cattle to illustrate our discussion and support explanations of cases in which different models are used to address similar problems. The framework should help those constructing models to structure their approach to modelling decisions and facilitate comparisons between models in the literature.

An integrated modeling framework for exploring flow regime and water quality changes with increasing biofuel crop production in the U.S. Corn Belt

NASA Astrophysics Data System (ADS)

Yaeger, Mary A.; Housh, Mashor; Cai, Ximing; Sivapalan, Murugesu

2014-12-01

To better address the dynamic interactions between human and hydrologic systems, we develop an integrated modeling framework that employs a System of Systems optimization model to emulate human development decisions which are then incorporated into a watershed model to estimate the resulting hydrologic impacts. The two models are run interactively to simulate the coevolution of coupled human-nature systems, such that reciprocal feedbacks between hydrologic processes and human decisions (i.e., human impacts on critical low flows and hydrologic impacts on human decisions on land and water use) can be assessed. The framework is applied to a Midwestern U.S. agricultural watershed, in the context of proposed biofuels development. This operation is illustrated by projecting three possible future coevolution trajectories, two of which use dedicated biofuel crops to reduce annual watershed nitrate export while meeting ethanol production targets. Imposition of a primary external driver (biofuel mandate) combined with different secondary drivers (water quality targets) results in highly nonlinear and multiscale responses of both the human and hydrologic systems, including multiple tradeoffs, impacting the future coevolution of the system in complex, heterogeneous ways. The strength of the hydrologic response is sensitive to the magnitude of the secondary driver; 45% nitrate reduction target leads to noticeable impacts at the outlet, while a 30% reduction leads to noticeable impacts that are mainly local. The local responses are conditioned by previous human-hydrologic modifications and their spatial relationship to the new biofuel development, highlighting the importance of past coevolutionary history in predicting future trajectories of change.

Integrating systems biology models and biomedical ontologies

PubMed Central

2011-01-01

Background Systems biology is an approach to biology that emphasizes the structure and dynamic behavior of biological systems and the interactions that occur within them. To succeed, systems biology crucially depends on the accessibility and integration of data across domains and levels of granularity. Biomedical ontologies were developed to facilitate such an integration of data and are often used to annotate biosimulation models in systems biology. Results We provide a framework to integrate representations of in silico systems biology with those of in vivo biology as described by biomedical ontologies and demonstrate this framework using the Systems Biology Markup Language. We developed the SBML Harvester software that automatically converts annotated SBML models into OWL and we apply our software to those biosimulation models that are contained in the BioModels Database. We utilize the resulting knowledge base for complex biological queries that can bridge levels of granularity, verify models based on the biological phenomenon they represent and provide a means to establish a basic qualitative layer on which to express the semantics of biosimulation models. Conclusions We establish an information flow between biomedical ontologies and biosimulation models and we demonstrate that the integration of annotated biosimulation models and biomedical ontologies enables the verification of models as well as expressive queries. Establishing a bi-directional information flow between systems biology and biomedical ontologies has the potential to enable large-scale analyses of biological systems that span levels of granularity from molecules to organisms. PMID:21835028

Modeling Multiple Human-Automation Distributed Systems using Network-form Games

NASA Technical Reports Server (NTRS)

Brat, Guillaume

2012-01-01

The paper describes at a high-level the network-form game framework (based on Bayes net and game theory), which can be used to model and analyze safety issues in large, distributed, mixed human-automation systems such as NextGen.

A nursing-specific model of EPR documentation: organizational and professional requirements.

PubMed

von Krogh, Gunn; Nåden, Dagfinn

2008-01-01

To present the Norwegian documentation KPO model (quality assurance, problem solving, and caring). To present the requirements and multiple electronic patient record (EPR) functions the model is designed to address. The model's professional substance, a conceptual framework for nursing practice is developed by examining, reorganizing, and completing existing frameworks. The model's methodology, an information management system, is developed using an expert group. Both model elements were clinically tested over a period of 1 year. The model is designed for nursing documentation in step with statutory, organizational, and professional requirements. Complete documentation is arranged for by incorporating the Nursing Minimum Data Set. A systematic and comprehensive documentation is arranged for by establishing categories as provided in the model's framework domains. Consistent documentation is arranged for by incorporating NANDA-I Nursing Diagnoses, Nursing Intervention Classification, and Nursing Outcome Classification. The model can be used as a tool in cooperation with vendors to ensure the interests of the nursing profession is met when developing EPR solutions in healthcare. The model can provide clinicians with a framework for documentation in step with legal and organizational requirements and at the same time retain the ability to record all aspects of clinical nursing.

From microscopic taxation and redistribution models to macroscopic income distributions

NASA Astrophysics Data System (ADS)

Bertotti, Maria Letizia; Modanese, Giovanni

2011-10-01

We present here a general framework, expressed by a system of nonlinear differential equations, suitable for the modeling of taxation and redistribution in a closed society. This framework allows one to describe the evolution of income distribution over the population and to explain the emergence of collective features based on knowledge of the individual interactions. By making different choices of the framework parameters, we construct different models, whose long-time behavior is then investigated. Asymptotic stationary distributions are found, which enjoy similar properties as those observed in empirical distributions. In particular, they exhibit power law tails of Pareto type and their Lorenz curves and Gini indices are consistent with some real world ones.

Detecting Anomalous Insiders in Collaborative Information Systems

PubMed Central

Chen, You; Nyemba, Steve; Malin, Bradley

2012-01-01

Collaborative information systems (CISs) are deployed within a diverse array of environments that manage sensitive information. Current security mechanisms detect insider threats, but they are ill-suited to monitor systems in which users function in dynamic teams. In this paper, we introduce the community anomaly detection system (CADS), an unsupervised learning framework to detect insider threats based on the access logs of collaborative environments. The framework is based on the observation that typical CIS users tend to form community structures based on the subjects accessed (e.g., patients’ records viewed by healthcare providers). CADS consists of two components: 1) relational pattern extraction, which derives community structures and 2) anomaly prediction, which leverages a statistical model to determine when users have sufficiently deviated from communities. We further extend CADS into MetaCADS to account for the semantics of subjects (e.g., patients’ diagnoses). To empirically evaluate the framework, we perform an assessment with three months of access logs from a real electronic health record (EHR) system in a large medical center. The results illustrate our models exhibit significant performance gains over state-of-the-art competitors. When the number of illicit users is low, MetaCADS is the best model, but as the number grows, commonly accessed semantics lead to hiding in a crowd, such that CADS is more prudent. PMID:24489520

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

DOE Office of Scientific and Technical Information (OSTI.GOV)

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.

Generic Software Architecture for Prognostics (GSAP) User Guide

NASA Technical Reports Server (NTRS)

Teubert, Christopher Allen; Daigle, Matthew John; Watkins, Jason; Sankararaman, Shankar; Goebel, Kai

2016-01-01

The Generic Software Architecture for Prognostics (GSAP) is a framework for applying prognostics. It makes applying prognostics easier by implementing many of the common elements across prognostic applications. The standard interface enables reuse of prognostic algorithms and models across systems using the GSAP framework.

A systems framework for identifying candidate microbial assemblages for disease management

USDA-ARS?s Scientific Manuscript database

Network models of soil and plant microbiomes present new opportunities for enhancing disease management, but also challenges for interpretation. We present a framework for interpreting microbiome networks, illustrating how the observed structure of networks can be used to generate testable hypothese...

Applying air pollution modelling within a multi-criteria decision analysis framework to evaluate UK air quality policies

NASA Astrophysics Data System (ADS)

Chalabi, Zaid; Milojevic, Ai; Doherty, Ruth M.; Stevenson, David S.; MacKenzie, Ian A.; Milner, James; Vieno, Massimo; Williams, Martin; Wilkinson, Paul

2017-10-01

A decision support system for evaluating UK air quality policies is presented. It combines the output from a chemistry transport model, a health impact model and other impact models within a multi-criteria decision analysis (MCDA) framework. As a proof-of-concept, the MCDA framework is used to evaluate and compare idealized emission reduction policies in four sectors (combustion in energy and transformation industries, non-industrial combustion plants, road transport and agriculture) and across six outcomes or criteria (mortality, health inequality, greenhouse gas emissions, biodiversity, crop yield and air quality legal compliance). To illustrate a realistic use of the MCDA framework, the relative importance of the criteria were elicited from a number of stakeholders acting as proxy policy makers. In the prototype decision problem, we show that reducing emissions from industrial combustion (followed very closely by road transport and agriculture) is more advantageous than equivalent reductions from the other sectors when all the criteria are taken into account. Extensions of the MCDA framework to support policy makers in practice are discussed.

The P-chain: relating sentence production and its disorders to comprehension and acquisition

PubMed Central

Dell, Gary S.; Chang, Franklin

2014-01-01

This article introduces the P-chain, an emerging framework for theory in psycholinguistics that unifies research on comprehension, production and acquisition. The framework proposes that language processing involves incremental prediction, which is carried out by the production system. Prediction necessarily leads to prediction error, which drives learning, including both adaptive adjustment to the mature language processing system as well as language acquisition. To illustrate the P-chain, we review the Dual-path model of sentence production, a connectionist model that explains structural priming in production and a number of facts about language acquisition. The potential of this and related models for explaining acquired and developmental disorders of sentence production is discussed. PMID:24324238

The P-chain: relating sentence production and its disorders to comprehension and acquisition.

PubMed

Dell, Gary S; Chang, Franklin

2014-01-01

This article introduces the P-chain, an emerging framework for theory in psycholinguistics that unifies research on comprehension, production and acquisition. The framework proposes that language processing involves incremental prediction, which is carried out by the production system. Prediction necessarily leads to prediction error, which drives learning, including both adaptive adjustment to the mature language processing system as well as language acquisition. To illustrate the P-chain, we review the Dual-path model of sentence production, a connectionist model that explains structural priming in production and a number of facts about language acquisition. The potential of this and related models for explaining acquired and developmental disorders of sentence production is discussed.

A Systemic Cause Analysis Model for Human Performance Technicians

ERIC Educational Resources Information Center

Sostrin, Jesse

2011-01-01

This article presents a systemic, research-based cause analysis model for use in the field of human performance technology (HPT). The model organizes the most prominent barriers to workplace learning and performance into a conceptual framework that explains and illuminates the architecture of these barriers that exist within the fabric of everyday…