How Accumulated Real Life Stress Experience and Cognitive Speed Interact on Decision-Making Processes

PubMed Central

Friedel, Eva; Sebold, Miriam; Kuitunen-Paul, Sören; Nebe, Stephan; Veer, Ilya M.; Zimmermann, Ulrich S.; Schlagenhauf, Florian; Smolka, Michael N.; Rapp, Michael; Walter, Henrik; Heinz, Andreas

2017-01-01

Rationale: Advances in neurocomputational modeling suggest that valuation systems for goal-directed (deliberative) on one side, and habitual (automatic) decision-making on the other side may rely on distinct computational strategies for reinforcement learning, namely model-free vs. model-based learning. As a key theoretical difference, the model-based system strongly demands cognitive functions to plan actions prospectively based on an internal cognitive model of the environment, whereas valuation in the model-free system relies on rather simple learning rules from operant conditioning to retrospectively associate actions with their outcomes and is thus cognitively less demanding. Acute stress reactivity is known to impair model-based but not model-free choice behavior, with higher working memory capacity protecting the model-based system from acute stress. However, it is not clear which impact accumulated real life stress has on model-free and model-based decision systems and how this influence interacts with cognitive abilities. Methods: We used a sequential decision-making task distinguishing relative contributions of both learning strategies to choice behavior, the Social Readjustment Rating Scale questionnaire to assess accumulated real life stress, and the Digit Symbol Substitution Test to test cognitive speed in 95 healthy subjects. Results: Individuals reporting high stress exposure who had low cognitive speed showed reduced model-based but increased model-free behavioral control. In contrast, subjects exposed to accumulated real life stress with high cognitive speed displayed increased model-based performance but reduced model-free control. Conclusion: These findings suggest that accumulated real life stress exposure can enhance reliance on cognitive speed for model-based computations, which may ultimately protect the model-based system from the detrimental influences of accumulated real life stress. The combination of accumulated real life stress exposure and slower information processing capacities, however, might favor model-free strategies. Thus, the valence and preference of either system strongly depends on stressful experiences and individual cognitive capacities. PMID:28642696

How Accumulated Real Life Stress Experience and Cognitive Speed Interact on Decision-Making Processes.

PubMed

Friedel, Eva; Sebold, Miriam; Kuitunen-Paul, Sören; Nebe, Stephan; Veer, Ilya M; Zimmermann, Ulrich S; Schlagenhauf, Florian; Smolka, Michael N; Rapp, Michael; Walter, Henrik; Heinz, Andreas

2017-01-01

Rationale: Advances in neurocomputational modeling suggest that valuation systems for goal-directed (deliberative) on one side, and habitual (automatic) decision-making on the other side may rely on distinct computational strategies for reinforcement learning, namely model-free vs. model-based learning. As a key theoretical difference, the model-based system strongly demands cognitive functions to plan actions prospectively based on an internal cognitive model of the environment, whereas valuation in the model-free system relies on rather simple learning rules from operant conditioning to retrospectively associate actions with their outcomes and is thus cognitively less demanding. Acute stress reactivity is known to impair model-based but not model-free choice behavior, with higher working memory capacity protecting the model-based system from acute stress. However, it is not clear which impact accumulated real life stress has on model-free and model-based decision systems and how this influence interacts with cognitive abilities. Methods: We used a sequential decision-making task distinguishing relative contributions of both learning strategies to choice behavior, the Social Readjustment Rating Scale questionnaire to assess accumulated real life stress, and the Digit Symbol Substitution Test to test cognitive speed in 95 healthy subjects. Results: Individuals reporting high stress exposure who had low cognitive speed showed reduced model-based but increased model-free behavioral control. In contrast, subjects exposed to accumulated real life stress with high cognitive speed displayed increased model-based performance but reduced model-free control. Conclusion: These findings suggest that accumulated real life stress exposure can enhance reliance on cognitive speed for model-based computations, which may ultimately protect the model-based system from the detrimental influences of accumulated real life stress. The combination of accumulated real life stress exposure and slower information processing capacities, however, might favor model-free strategies. Thus, the valence and preference of either system strongly depends on stressful experiences and individual cognitive capacities.

NED-IIS: An Intelligent Information System for Forest Ecosystem Management

Treesearch

W.D. Potter; S. Somasekar; R. Kommineni; H.M. Rauscher

1999-01-01

We view Intelligent Information System (IIS) as composed of a unified knowledge base, database, and model base. The model base includes decision support models, forecasting models, and cvsualization models for example. In addition, we feel that the model base should include domain specific porblems solving modules as well as decision support models. This, then,...

Agent autonomy approach to probabilistic physics-of-failure modeling of complex dynamic systems with interacting failure mechanisms

NASA Astrophysics Data System (ADS)

Gromek, Katherine Emily

A novel computational and inference framework of the physics-of-failure (PoF) reliability modeling for complex dynamic systems has been established in this research. The PoF-based reliability models are used to perform a real time simulation of system failure processes, so that the system level reliability modeling would constitute inferences from checking the status of component level reliability at any given time. The "agent autonomy" concept is applied as a solution method for the system-level probabilistic PoF-based (i.e. PPoF-based) modeling. This concept originated from artificial intelligence (AI) as a leading intelligent computational inference in modeling of multi agents systems (MAS). The concept of agent autonomy in the context of reliability modeling was first proposed by M. Azarkhail [1], where a fundamentally new idea of system representation by autonomous intelligent agents for the purpose of reliability modeling was introduced. Contribution of the current work lies in the further development of the agent anatomy concept, particularly the refined agent classification within the scope of the PoF-based system reliability modeling, new approaches to the learning and the autonomy properties of the intelligent agents, and modeling interacting failure mechanisms within the dynamic engineering system. The autonomous property of intelligent agents is defined as agent's ability to self-activate, deactivate or completely redefine their role in the analysis. This property of agents and the ability to model interacting failure mechanisms of the system elements makes the agent autonomy fundamentally different from all existing methods of probabilistic PoF-based reliability modeling. 1. Azarkhail, M., "Agent Autonomy Approach to Physics-Based Reliability Modeling of Structures and Mechanical Systems", PhD thesis, University of Maryland, College Park, 2007.

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.

Model-based verification and validation of the SMAP uplink processes

NASA Astrophysics Data System (ADS)

Khan, M. O.; Dubos, G. F.; Tirona, J.; Standley, S.

Model-Based Systems Engineering (MBSE) is being used increasingly within the spacecraft design community because of its benefits when compared to document-based approaches. As the complexity of projects expands dramatically with continually increasing computational power and technology infusion, the time and effort needed for verification and validation (V& V) increases geometrically. Using simulation to perform design validation with system-level models earlier in the life cycle stands to bridge the gap between design of the system (based on system-level requirements) and verifying those requirements/validating the system as a whole. This case study stands as an example of how a project can validate a system-level design earlier in the project life cycle than traditional V& V processes by using simulation on a system model. Specifically, this paper describes how simulation was added to a system model of the Soil Moisture Active-Passive (SMAP) mission's uplink process. Also discussed are the advantages and disadvantages of the methods employed and the lessons learned; which are intended to benefit future model-based and simulation-based development efforts.

Organization-based Model-driven Development of High-assurance Multiagent Systems

DTIC Science & Technology

2009-02-27

based Model -driven Development of High-assurance Multiagent Systems " performed by Dr. Scott A . DeLoach and Dr Robby at Kansas State University... A Capabilities Based Model for Artificial Organizations. Journal of Autonomous Agents and Multiagent Systems . Volume 16, no. 1, February 2008, pp...Matson, E . T. (2007). A capabilities based theory of artificial organizations. Journal of Autonomous Agents and Multiagent Systems

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.

Comparison of an Agent-based Model of Disease Propagation with the Generalised SIR Epidemic Model

DTIC Science & Technology

2009-08-01

has become a practical method for conducting Epidemiological Modelling. In the agent- based approach the whole township can be modelled as a system of...SIR system was initially developed based on a very simplified model of social interaction. For instance an assumption of uniform population mixing was...simulating the progress of a disease within a host and of transmission between hosts is based upon Transportation Analysis and Simulation System

A hybrid agent-based approach for modeling microbiological systems.

PubMed

Guo, Zaiyi; Sloot, Peter M A; Tay, Joc Cing

2008-11-21

Models for systems biology commonly adopt Differential Equations or Agent-Based modeling approaches for simulating the processes as a whole. Models based on differential equations presuppose phenomenological intracellular behavioral mechanisms, while models based on Multi-Agent approach often use directly translated, and quantitatively less precise if-then logical rule constructs. We propose an extendible systems model based on a hybrid agent-based approach where biological cells are modeled as individuals (agents) while molecules are represented by quantities. This hybridization in entity representation entails a combined modeling strategy with agent-based behavioral rules and differential equations, thereby balancing the requirements of extendible model granularity with computational tractability. We demonstrate the efficacy of this approach with models of chemotaxis involving an assay of 10(3) cells and 1.2x10(6) molecules. The model produces cell migration patterns that are comparable to laboratory observations.

DFM flow by using combination between design based metrology system and model based verification at sub-50nm memory device

NASA Astrophysics Data System (ADS)

Kim, Cheol-kyun; Kim, Jungchan; Choi, Jaeseung; Yang, Hyunjo; Yim, Donggyu; Kim, Jinwoong

2007-03-01

As the minimum transistor length is getting smaller, the variation and uniformity of transistor length seriously effect device performance. So, the importance of optical proximity effects correction (OPC) and resolution enhancement technology (RET) cannot be overemphasized. However, OPC process is regarded by some as a necessary evil in device performance. In fact, every group which includes process and design, are interested in whole chip CD variation trend and CD uniformity, which represent real wafer. Recently, design based metrology systems are capable of detecting difference between data base to wafer SEM image. Design based metrology systems are able to extract information of whole chip CD variation. According to the results, OPC abnormality was identified and design feedback items are also disclosed. The other approaches are accomplished on EDA companies, like model based OPC verifications. Model based verification will be done for full chip area by using well-calibrated model. The object of model based verification is the prediction of potential weak point on wafer and fast feed back to OPC and design before reticle fabrication. In order to achieve robust design and sufficient device margin, appropriate combination between design based metrology system and model based verification tools is very important. Therefore, we evaluated design based metrology system and matched model based verification system for optimum combination between two systems. In our study, huge amount of data from wafer results are classified and analyzed by statistical method and classified by OPC feedback and design feedback items. Additionally, novel DFM flow would be proposed by using combination of design based metrology and model based verification tools.

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.

Using a data base management system for modelling SSME test history data

NASA Technical Reports Server (NTRS)

Abernethy, K.

1985-01-01

The usefulness of a data base management system (DBMS) for modelling historical test data for the complete series of static test firings for the Space Shuttle Main Engine (SSME) was assessed. From an analysis of user data base query requirements, it became clear that a relational DMBS which included a relationally complete query language would permit a model satisfying the query requirements. Representative models and sample queries are discussed. A list of environment-particular evaluation criteria for the desired DBMS was constructed; these criteria include requirements in the areas of user-interface complexity, program independence, flexibility, modifiability, and output capability. The evaluation process included the construction of several prototype data bases for user assessement. The systems studied, representing the three major DBMS conceptual models, were: MIRADS, a hierarchical system; DMS-1100, a CODASYL-based network system; ORACLE, a relational system; and DATATRIEVE, a relational-type system.

A Model-Based Approach to Developing Your Mission Operations System

NASA Technical Reports Server (NTRS)

Smith, Robert R.; Schimmels, Kathryn A.; Lock, Patricia D; Valerio, Charlene P.

2014-01-01

Model-Based System Engineering (MBSE) is an increasingly popular methodology for designing complex engineering systems. As the use of MBSE has grown, it has begun to be applied to systems that are less hardware-based and more people- and process-based. We describe our approach to incorporating MBSE as a way to streamline development, and how to build a model consisting of core resources, such as requirements and interfaces, that can be adapted and used by new and upcoming projects. By comparing traditional Mission Operations System (MOS) system engineering with an MOS designed via a model, we will demonstrate the benefits to be obtained by incorporating MBSE in system engineering design processes.

Understanding Elementary Astronomy by Making Drawing-Based Models

NASA Astrophysics Data System (ADS)

van Joolingen, W. R.; Aukes, Annika V. A.; Gijlers, H.; Bollen, L.

2015-04-01

Modeling is an important approach in the teaching and learning of science. In this study, we attempt to bring modeling within the reach of young children by creating the SimSketch modeling system, which is based on freehand drawings that can be turned into simulations. This system was used by 247 children (ages ranging from 7 to 15) to create a drawing-based model of the solar system. The results show that children in the target age group are capable of creating a drawing-based model of the solar system and can use it to show the situations in which eclipses occur. Structural equation modeling predicting post-test knowledge scores based on learners' pre-test knowledge scores, the quality of their drawings and motivational aspects yielded some evidence that such drawing contributes to learning. Consequences for using modeling with young children are considered.

A Model-based Approach to Reactive Self-Configuring Systems

NASA Technical Reports Server (NTRS)

Williams, Brian C.; Nayak, P. Pandurang

1996-01-01

This paper describes Livingstone, an implemented kernel for a self-reconfiguring autonomous system, that is reactive and uses component-based declarative models. The paper presents a formal characterization of the representation formalism used in Livingstone, and reports on our experience with the implementation in a variety of domains. Livingstone's representation formalism achieves broad coverage of hybrid software/hardware systems by coupling the concurrent transition system models underlying concurrent reactive languages with the discrete qualitative representations developed in model-based reasoning. We achieve a reactive system that performs significant deductions in the sense/response loop by drawing on our past experience at building fast prepositional conflict-based algorithms for model-based diagnosis, and by framing a model-based configuration manager as a prepositional, conflict-based feedback controller that generates focused, optimal responses. Livingstone automates all these tasks using a single model and a single core deductive engine, thus making significant progress towards achieving a central goal of model-based reasoning. Livingstone, together with the HSTS planning and scheduling engine and the RAPS executive, has been selected as the core autonomy architecture for Deep Space One, the first spacecraft for NASA's New Millennium program.

An Object-Based Requirements Modeling Method.

ERIC Educational Resources Information Center

Cordes, David W.; Carver, Doris L.

1992-01-01

Discusses system modeling and specification as it relates to object-based information systems development and software development. An automated system model based on the objects in the initial requirements document is described, the requirements document translator is explained, and a sample application of the technique is provided. (12…

Measurement-based reliability/performability models

NASA Technical Reports Server (NTRS)

Hsueh, Mei-Chen

1987-01-01

Measurement-based models based on real error-data collected on a multiprocessor system are described. Model development from the raw error-data to the estimation of cumulative reward is also described. A workload/reliability model is developed based on low-level error and resource usage data collected on an IBM 3081 system during its normal operation in order to evaluate the resource usage/error/recovery process in a large mainframe system. Thus, both normal and erroneous behavior of the system are modeled. The results provide an understanding of the different types of errors and recovery processes. The measured data show that the holding times in key operational and error states are not simple exponentials and that a semi-Markov process is necessary to model the system behavior. A sensitivity analysis is performed to investigate the significance of using a semi-Markov process, as opposed to a Markov process, to model the measured system.

Stability of model-based event-triggered control systems: a separation property

NASA Astrophysics Data System (ADS)

Hao, Fei; Yu, Hao

2017-04-01

To save resource of communication, this paper investigates the model-based event-triggered control systems. Two main problems are considered in this paper. One is, for given plant and model, to design event conditions to guarantee the stability of the systems. The other is to consider the effect of the model matrices on the stability. The results show that the closed-loop systems can be asymptotically stabilised with any model matrices in compact sets if the parameters in the event conditions are within the designed ranges. Then, a separation property of model-based event-triggered control is proposed. Namely, the design of the controller gain and the event condition can be separated from the selection of the model matrices. Based on this property, an adaption mechanism is introduced to the model-based event-triggered control systems, which can further improve the sampling performance. Finally, a numerical example is given to show the efficiency and feasibility of the developed results.

Applications of SPICE for modeling miniaturized biomedical sensor systems

NASA Technical Reports Server (NTRS)

Mundt, C. W.; Nagle, H. T.

2000-01-01

This paper proposes a model for a miniaturized signal conditioning system for biopotential and ion-selective electrode arrays. The system consists of three main components: sensors, interconnections, and signal conditioning chip. The model for this system is based on SPICE. Transmission-line based equivalent circuits are used to represent the sensors, lumped resistance-capacitance circuits describe the interconnections, and a model for the signal conditioning chip is extracted from its layout. A system for measurements of biopotentials and ionic activities can be miniaturized and optimized for cardiovascular applications based on the development of an integrated SPICE system model of its electrochemical, interconnection, and electronic components.

Dragon pulse information management system (DPIMS): A unique model-based approach to implementing domain agnostic system of systems and behaviors

NASA Astrophysics Data System (ADS)

Anderson, Thomas S.

2016-05-01

The Global Information Network Architecture is an information technology based on Vector Relational Data Modeling, a unique computational paradigm, DoD network certified by USARMY as the Dragon Pulse Informa- tion Management System. This network available modeling environment for modeling models, where models are configured using domain relevant semantics and use network available systems, sensors, databases and services as loosely coupled component objects and are executable applications. Solutions are based on mission tactics, techniques, and procedures and subject matter input. Three recent ARMY use cases are discussed a) ISR SoS. b) Modeling and simulation behavior validation. c) Networked digital library with behaviors.

A CLIPS-based expert system for the evaluation and selection of robots

NASA Technical Reports Server (NTRS)

Nour, Mohamed A.; Offodile, Felix O.; Madey, Gregory R.

1994-01-01

This paper describes the development of a prototype expert system for intelligent selection of robots for manufacturing operations. The paper first develops a comprehensive, three-stage process to model the robot selection problem. The decisions involved in this model easily lend themselves to an expert system application. A rule-based system, based on the selection model, is developed using the CLIPS expert system shell. Data about actual robots is used to test the performance of the prototype system. Further extensions to the rule-based system for data handling and interfacing capabilities are suggested.

New approaches in agent-based modeling of complex financial systems

NASA Astrophysics Data System (ADS)

Chen, Ting-Ting; Zheng, Bo; Li, Yan; Jiang, Xiong-Fei

2017-12-01

Agent-based modeling is a powerful simulation technique to understand the collective behavior and microscopic interaction in complex financial systems. Recently, the concept for determining the key parameters of agent-based models from empirical data instead of setting them artificially was suggested. We first review several agent-based models and the new approaches to determine the key model parameters from historical market data. Based on the agents' behaviors with heterogeneous personal preferences and interactions, these models are successful in explaining the microscopic origination of the temporal and spatial correlations of financial markets. We then present a novel paradigm combining big-data analysis with agent-based modeling. Specifically, from internet query and stock market data, we extract the information driving forces and develop an agent-based model to simulate the dynamic behaviors of complex financial systems.

An architecture for the development of real-time fault diagnosis systems using model-based reasoning

NASA Technical Reports Server (NTRS)

Hall, Gardiner A.; Schuetzle, James; Lavallee, David; Gupta, Uday

1992-01-01

Presented here is an architecture for implementing real-time telemetry based diagnostic systems using model-based reasoning. First, we describe Paragon, a knowledge acquisition tool for offline entry and validation of physical system models. Paragon provides domain experts with a structured editing capability to capture the physical component's structure, behavior, and causal relationships. We next describe the architecture of the run time diagnostic system. The diagnostic system, written entirely in Ada, uses the behavioral model developed offline by Paragon to simulate expected component states as reflected in the telemetry stream. The diagnostic algorithm traces causal relationships contained within the model to isolate system faults. Since the diagnostic process relies exclusively on the behavioral model and is implemented without the use of heuristic rules, it can be used to isolate unpredicted faults in a wide variety of systems. Finally, we discuss the implementation of a prototype system constructed using this technique for diagnosing faults in a science instrument. The prototype demonstrates the use of model-based reasoning to develop maintainable systems with greater diagnostic capabilities at a lower cost.

High pressure common rail injection system modeling and control.

PubMed

Wang, H P; Zheng, D; Tian, Y

2016-07-01

In this paper modeling and common-rail pressure control of high pressure common rail injection system (HPCRIS) is presented. The proposed mathematical model of high pressure common rail injection system which contains three sub-systems: high pressure pump sub-model, common rail sub-model and injector sub-model is a relative complicated nonlinear system. The mathematical model is validated by the software Matlab and a virtual detailed simulation environment. For the considered HPCRIS, an effective model free controller which is called Extended State Observer - based intelligent Proportional Integral (ESO-based iPI) controller is designed. And this proposed method is composed mainly of the referred ESO observer, and a time delay estimation based iPI controller. Finally, to demonstrate the performances of the proposed controller, the proposed ESO-based iPI controller is compared with a conventional PID controller and ADRC. Copyright © 2016 ISA. Published by Elsevier Ltd. All rights reserved.

Emulating a System Dynamics Model with Agent-Based Models: A Methodological Case Study in Simulation of Diabetes Progression

DOE PAGES

Schryver, Jack; Nutaro, James; Shankar, Mallikarjun

2015-10-30

An agent-based simulation model hierarchy emulating disease states and behaviors critical to progression of diabetes type 2 was designed and implemented in the DEVS framework. The models are translations of basic elements of an established system dynamics model of diabetes. In this model hierarchy, which mimics diabetes progression over an aggregated U.S. population, was dis-aggregated and reconstructed bottom-up at the individual (agent) level. Four levels of model complexity were defined in order to systematically evaluate which parameters are needed to mimic outputs of the system dynamics model. Moreover, the four estimated models attempted to replicate stock counts representing disease statesmore » in the system dynamics model, while estimating impacts of an elderliness factor, obesity factor and health-related behavioral parameters. Health-related behavior was modeled as a simple realization of the Theory of Planned Behavior, a joint function of individual attitude and diffusion of social norms that spread over each agent s social network. Although the most complex agent-based simulation model contained 31 adjustable parameters, all models were considerably less complex than the system dynamics model which required numerous time series inputs to make its predictions. In all three elaborations of the baseline model provided significantly improved fits to the output of the system dynamics model. The performances of the baseline agent-based model and its extensions illustrate a promising approach to translate complex system dynamics models into agent-based model alternatives that are both conceptually simpler and capable of capturing main effects of complex local agent-agent interactions.« less

Emulating a System Dynamics Model with Agent-Based Models: A Methodological Case Study in Simulation of Diabetes Progression

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

Schryver, Jack; Nutaro, James; Shankar, Mallikarjun

An agent-based simulation model hierarchy emulating disease states and behaviors critical to progression of diabetes type 2 was designed and implemented in the DEVS framework. The models are translations of basic elements of an established system dynamics model of diabetes. In this model hierarchy, which mimics diabetes progression over an aggregated U.S. population, was dis-aggregated and reconstructed bottom-up at the individual (agent) level. Four levels of model complexity were defined in order to systematically evaluate which parameters are needed to mimic outputs of the system dynamics model. Moreover, the four estimated models attempted to replicate stock counts representing disease statesmore » in the system dynamics model, while estimating impacts of an elderliness factor, obesity factor and health-related behavioral parameters. Health-related behavior was modeled as a simple realization of the Theory of Planned Behavior, a joint function of individual attitude and diffusion of social norms that spread over each agent s social network. Although the most complex agent-based simulation model contained 31 adjustable parameters, all models were considerably less complex than the system dynamics model which required numerous time series inputs to make its predictions. In all three elaborations of the baseline model provided significantly improved fits to the output of the system dynamics model. The performances of the baseline agent-based model and its extensions illustrate a promising approach to translate complex system dynamics models into agent-based model alternatives that are both conceptually simpler and capable of capturing main effects of complex local agent-agent interactions.« less

Patterns of Use of an Agent-Based Model and a System Dynamics Model: The Application of Patterns of Use and the Impacts on Learning Outcomes

ERIC Educational Resources Information Center

Thompson, Kate; Reimann, Peter

2010-01-01

A classification system that was developed for the use of agent-based models was applied to strategies used by school-aged students to interrogate an agent-based model and a system dynamics model. These were compared, and relationships between learning outcomes and the strategies used were also analysed. It was found that the classification system…

A Model for Communications Satellite System Architecture Assessment

DTIC Science & Technology

2011-09-01

This is shown in Equation 4. The total system cost includes all development, acquisition, fielding, operations, maintenance and upgrades, and system...protection. A mathematical model was implemented to enable the analysis of communications satellite system architectures based on multiple system... implemented to enable the analysis of communications satellite system architectures based on multiple system attributes. Utilization of the model in

Models of morality

PubMed Central

Crockett, Molly J.

2013-01-01

Moral dilemmas engender conflicts between two traditions: consequentialism, which evaluates actions based on their outcomes, and deontology, which evaluates actions themselves. These strikingly resemble two distinct decision-making architectures: a model-based system that selects actions based on inferences about their consequences; and a model-free system that selects actions based on their reinforcement history. Here, I consider how these systems, along with a Pavlovian system that responds reflexively to rewards and punishments, can illuminate puzzles in moral psychology. PMID:23845564

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…

[The role of research-based evidence in health system policy decision-making].

PubMed

Patiño, Daniel; Lavis, John N; Moat, Kaelan

2013-01-01

Different models may be used for explaining how research-based evidence is used in healthcare system policy-making. It is argued that models arising from a clinical setting (i.e. evidence-based policy-making model) could be useful regarding some types of healthcare system decision-making. However, such models are "silent" concerning the influence of political contextual factors on healthcare policy-making and are thus inconsistent with decision-making regarding the modification of healthcare system arrangements. Other political science-based models would seem to be more useful for understanding that research is just one factor affecting decision-making and that different types of research-based evidence can be used instrumentally, conceptual or strategically during different policy-making stages.

DEVS representation of dynamical systems - Event-based intelligent control. [Discrete Event System Specification

NASA Technical Reports Server (NTRS)

Zeigler, Bernard P.

1989-01-01

It is shown how systems can be advantageously represented as discrete-event models by using DEVS (discrete-event system specification), a set-theoretic formalism. Such DEVS models provide a basis for the design of event-based logic control. In this control paradigm, the controller expects to receive confirming sensor responses to its control commands within definite time windows determined by its DEVS model of the system under control. The event-based contral paradigm is applied in advanced robotic and intelligent automation, showing how classical process control can be readily interfaced with rule-based symbolic reasoning systems.

Object-Oriented Modeling of an Energy Harvesting System Based on Thermoelectric Generators

NASA Astrophysics Data System (ADS)

Nesarajah, Marco; Frey, Georg

This paper deals with the modeling of an energy harvesting system based on thermoelectric generators (TEG), and the validation of the model by means of a test bench. TEGs are capable to improve the overall energy efficiency of energy systems, e.g. combustion engines or heating systems, by using the remaining waste heat to generate electrical power. Previously, a component-oriented model of the TEG itself was developed in Modelica® language. With this model any TEG can be described and simulated given the material properties and the physical dimension. Now, this model was extended by the surrounding components to a complete model of a thermoelectric energy harvesting system. In addition to the TEG, the model contains the cooling system, the heat source, and the power electronics. To validate the simulation model, a test bench was built and installed on an oil-fired household heating system. The paper reports results of the measurements and discusses the validity of the developed simulation models. Furthermore, the efficiency of the proposed energy harvesting system is derived and possible improvements based on design variations tested in the simulation model are proposed.

High-precision measurements of cementless acetabular components using model-based RSA: an experimental study.

PubMed

Baad-Hansen, Thomas; Kold, Søren; Kaptein, Bart L; Søballe, Kjeld

2007-08-01

In RSA, tantalum markers attached to metal-backed acetabular cups are often difficult to detect on stereo radiographs due to the high density of the metal shell. This results in occlusion of the prosthesis markers and may lead to inconclusive migration results. Within the last few years, new software systems have been developed to solve this problem. We compared the precision of 3 RSA systems in migration analysis of the acetabular component. A hemispherical and a non-hemispherical acetabular component were mounted in a phantom. Both acetabular components underwent migration analyses with 3 different RSA systems: conventional RSA using tantalum markers, an RSA system using a hemispherical cup algorithm, and a novel model-based RSA system. We found narrow confidence intervals, indicating high precision of the conventional marker system and model-based RSA with regard to migration and rotation. The confidence intervals of conventional RSA and model-based RSA were narrower than those of the hemispherical cup algorithm-based system regarding cup migration and rotation. The model-based RSA software combines the precision of the conventional RSA software with the convenience of the hemispherical cup algorithm-based system. Based on our findings, we believe that these new tools offer an improvement in the measurement of acetabular component migration.

Systems Engineering Model and Training Application for Desktop Environment

NASA Technical Reports Server (NTRS)

May, Jeffrey T.

2010-01-01

Provide a graphical user interface based simulator for desktop training, operations and procedure development and system reference. This simulator allows for engineers to train and further understand the dynamics of their system from their local desktops. It allows the users to train and evaluate their system at a pace and skill level based on the user's competency and from a perspective based on the user's need. The simulator will not require any special resources to execute and should generally be available for use. The interface is based on a concept of presenting the model of the system in ways that best suits the user's application or training needs. The three levels of views are Component View, the System View (overall system), and the Console View (monitor). These views are portals into a single model, so changing the model from one view or from a model manager Graphical User Interface will be reflected on all other views.

Modeling ground-based timber harvesting systems using computer simulation

Treesearch

Jingxin Wang; Chris B. LeDoux

2001-01-01

Modeling ground-based timber harvesting systems with an object-oriented methodology was investigated. Object-oriented modeling and design promote a better understanding of requirements, cleaner designs, and better maintainability of the harvesting simulation system. The model developed simulates chainsaw felling, drive-to-tree feller-buncher, swing-to-tree single-grip...

Modeling of Electrocardiograph Telediagnosing System Based on Petri Net

NASA Astrophysics Data System (ADS)

Hu, Wensong; Li, Ming; Li, Lan

This paper analyzed the characteristics of the electrocardiograph telediagnosing system. Firstly, we introduce the system and Petri nets. Secondly, we built a topological diagram of this system. Then we use Petri nets to show the physical process of this system. Finally, we verified the model of the electrocardiograph telediagnosing system. With the help of model based on Petri nets, we analyzed the system performance and feasibility.

Diagnosing Students' Mental Models via the Web-Based Mental Models Diagnosis System

ERIC Educational Resources Information Center

Wang, Tzu-Hua; Chiu, Mei-Hung; Lin, Jing-Wen; Chou, Chin-Cheng

2013-01-01

Mental models play an important role in science education research. To extend the effectiveness of conceptual change research and to improve mental model identi?cation and diagnosis, the authors developed and tested the Web-Based Mental Models Diagnosis (WMMD) system. In this article, they describe their WMMD system, which goes beyond the…

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…

Designing an Adaptive Web-Based Learning System Based on Students' Cognitive Styles Identified Online

ERIC Educational Resources Information Center

Lo, Jia-Jiunn; Chan, Ya-Chen; Yeh, Shiou-Wen

2012-01-01

This study developed an adaptive web-based learning system focusing on students' cognitive styles. The system is composed of a student model and an adaptation model. It collected students' browsing behaviors to update the student model for unobtrusively identifying student cognitive styles through a multi-layer feed-forward neural network (MLFF).…

Intelligent model-based diagnostics for vehicle health management

NASA Astrophysics Data System (ADS)

Luo, Jianhui; Tu, Fang; Azam, Mohammad S.; Pattipati, Krishna R.; Willett, Peter K.; Qiao, Liu; Kawamoto, Masayuki

2003-08-01

The recent advances in sensor technology, remote communication and computational capabilities, and standardized hardware/software interfaces are creating a dramatic shift in the way the health of vehicles is monitored and managed. These advances facilitate remote monitoring, diagnosis and condition-based maintenance of automotive systems. With the increased sophistication of electronic control systems in vehicles, there is a concomitant increased difficulty in the identification of the malfunction phenomena. Consequently, the current rule-based diagnostic systems are difficult to develop, validate and maintain. New intelligent model-based diagnostic methodologies that exploit the advances in sensor, telecommunications, computing and software technologies are needed. In this paper, we will investigate hybrid model-based techniques that seamlessly employ quantitative (analytical) models and graph-based dependency models for intelligent diagnosis. Automotive engineers have found quantitative simulation (e.g. MATLAB/SIMULINK) to be a vital tool in the development of advanced control systems. The hybrid method exploits this capability to improve the diagnostic system's accuracy and consistency, utilizes existing validated knowledge on rule-based methods, enables remote diagnosis, and responds to the challenges of increased system complexity. The solution is generic and has the potential for application in a wide range of systems.

A database perspective of the transition from single-use (ancillary-based) systems to integrated models supporting clinical care and research in a MUMPS-based system.

PubMed

Siegel, J; Kirkland, D

1991-01-01

The Composite Health Care System (CHCS), a MUMPS-based hospital information system (HIS), has evolved from the Decentralized Hospital Computer Program (DHCP) installed within VA Hospitals. The authors explore the evolution of an ancillary-based system toward an integrated model with a look at its current state and possible future. The history and relationships between orders of different types tie specific patient-related data into a logical and temporal model. Diagrams demonstrate how the database structure has evolved to support clinical needs for integration. It is suggested that a fully integrated model is capable of meeting traditional HIS needs.

A measurement-based performability model for a multiprocessor system

NASA Technical Reports Server (NTRS)

Ilsueh, M. C.; Iyer, Ravi K.; Trivedi, K. S.

1987-01-01

A measurement-based performability model based on real error-data collected on a multiprocessor system is described. Model development from the raw errror-data to the estimation of cumulative reward is described. Both normal and failure behavior of the system are characterized. The measured data show that the holding times in key operational and failure states are not simple exponential and that semi-Markov process is necessary to model the system behavior. A reward function, based on the service rate and the error rate in each state, is then defined in order to estimate the performability of the system and to depict the cost of different failure types and recovery procedures.

Control Theory Perspective of Effects-Based Thinking and Operations: Modelling Operations as a Feedback Control System

DTIC Science & Technology

2007-11-01

Control Theory Perspective of Effects-Based Thinking and Operations Modelling “Operations” as a Feedback Control System Philip S. E... Theory Perspective of Effects-Based Thinking and Operations Modelling “Operations” as a Feedback Control System Philip S. E. Farrell...Abstract This paper explores operations that involve effects-based thinking (EBT) using Control Theory techniques in order to highlight the concept’s

Base stock system for patient vs impatient customers with varying demand distribution

NASA Astrophysics Data System (ADS)

Fathima, Dowlath; Uduman, P. Sheik

2013-09-01

An optimal Base-Stock inventory policy for Patient and Impatient Customers using finite-horizon models is examined. The Base stock system for Patient and Impatient customers is a different type of inventory policy. In case of the model I, Base stock for Patient customer case is evaluated using the Truncated Exponential Distribution. The model II involves the study of Base-stock inventory policies for Impatient customer. A study on these systems reveals that the Customers wait until the arrival of the next order or the customers leaves the system which leads to lost sale. In both the models demand during the period [0, t] is taken to be a random variable. In this paper, Truncated Exponential Distribution satisfies the Base stock policy for the patient customer as a continuous model. So far the Base stock for Impatient Customers leaded to a discrete case but, in this paper we have modeled this condition into a continuous case. We justify this approach mathematically and also numerically.

Virtual Observation System for Earth System Model: An Application to ACME Land Model Simulations

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

Wang, Dali; Yuan, Fengming; Hernandez, Benjamin

Investigating and evaluating physical-chemical-biological processes within an Earth system model (EMS) can be very challenging due to the complexity of both model design and software implementation. A virtual observation system (VOS) is presented to enable interactive observation of these processes during system simulation. Based on advance computing technologies, such as compiler-based software analysis, automatic code instrumentation, and high-performance data transport, the VOS provides run-time observation capability, in-situ data analytics for Earth system model simulation, model behavior adjustment opportunities through simulation steering. A VOS for a terrestrial land model simulation within the Accelerated Climate Modeling for Energy model is also presentedmore » to demonstrate the implementation details and system innovations.« less

Virtual Observation System for Earth System Model: An Application to ACME Land Model Simulations

DOE PAGES

Wang, Dali; Yuan, Fengming; Hernandez, Benjamin; ...

2017-01-01

Investigating and evaluating physical-chemical-biological processes within an Earth system model (EMS) can be very challenging due to the complexity of both model design and software implementation. A virtual observation system (VOS) is presented to enable interactive observation of these processes during system simulation. Based on advance computing technologies, such as compiler-based software analysis, automatic code instrumentation, and high-performance data transport, the VOS provides run-time observation capability, in-situ data analytics for Earth system model simulation, model behavior adjustment opportunities through simulation steering. A VOS for a terrestrial land model simulation within the Accelerated Climate Modeling for Energy model is also presentedmore » to demonstrate the implementation details and system innovations.« less

Implementation of a Sage-Based Stirling Model Into a System-Level Numerical Model of the Fission Power System Technology Demonstration Unit

NASA Technical Reports Server (NTRS)

Briggs, Maxwell H.

2011-01-01

The Fission Power System (FPS) project is developing a Technology Demonstration Unit (TDU) to verify the performance and functionality of a subscale version of the FPS reference concept in a relevant environment, and to verify component and system models. As hardware is developed for the TDU, component and system models must be refined to include the details of specific component designs. This paper describes the development of a Sage-based pseudo-steady-state Stirling convertor model and its implementation into a system-level model of the TDU.

DEVELOPMENT OF A WATERSHED-BASED MERCURY POLLUTION CHARACTERIZATION SYSTEM

EPA Science Inventory

To investigate total mercury loadings to streams in a watershed, we have developed a watershed-based source quantification model ? Watershed Mercury Characterization System. The system uses the grid-based GIS modeling technology to calculate total soil mercury concentrations and ...

A model-based executive for commanding robot teams

NASA Technical Reports Server (NTRS)

Barrett, Anthony

2005-01-01

The paper presents a way to robustly command a system of systems as a single entity. Instead of modeling each component system in isolation and then manually crafting interaction protocols, this approach starts with a model of the collective population as a single system. By compiling the model into separate elements for each component system and utilizing a teamwork model for coordination, it circumvents the complexities of manually crafting robust interaction protocols. The resulting systems are both globally responsive by virtue of a team oriented interaction model and locally responsive by virtue of a distributed approach to model-based fault detection, isolation, and recovery.

A Modelica-based Model Library for Building Energy and Control Systems

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

Wetter, Michael

2009-04-07

This paper describes an open-source library with component models for building energy and control systems that is based on Modelica, an equation-based objectoriented language that is well positioned to become the standard for modeling of dynamic systems in various industrial sectors. The library is currently developed to support computational science and engineering for innovative building energy and control systems. Early applications will include controls design and analysis, rapid prototyping to support innovation of new building systems and the use of models during operation for controls, fault detection and diagnostics. This paper discusses the motivation for selecting an equation-based object-oriented language.more » It presents the architecture of the library and explains how base models can be used to rapidly implement new models. To demonstrate the capability of analyzing novel energy and control systems, the paper closes with an example where we compare the dynamic performance of a conventional hydronic heating system with thermostatic radiator valves to an innovative heating system. In the new system, instead of a centralized circulation pump, each of the 18 radiators has a pump whose speed is controlled using a room temperature feedback loop, and the temperature of the boiler is controlled based on the speed of the radiator pump. All flows are computed by solving for the pressure distribution in the piping network, and the controls include continuous and discrete time controls.« less

Fuzzy model-based servo and model following control for nonlinear systems.

PubMed

Ohtake, Hiroshi; Tanaka, Kazuo; Wang, Hua O

2009-12-01

This correspondence presents servo and nonlinear model following controls for a class of nonlinear systems using the Takagi-Sugeno fuzzy model-based control approach. First, the construction method of the augmented fuzzy system for continuous-time nonlinear systems is proposed by differentiating the original nonlinear system. Second, the dynamic fuzzy servo controller and the dynamic fuzzy model following controller, which can make outputs of the nonlinear system converge to target points and to outputs of the reference system, respectively, are introduced. Finally, the servo and model following controller design conditions are given in terms of linear matrix inequalities. Design examples illustrate the utility of this approach.

Validating the ACE Model for Evaluating Student Performance Using a Teaching-Learning Process Based on Computational Modeling Systems

ERIC Educational Resources Information Center

Louzada, Alexandre Neves; Elia, Marcos da Fonseca; Sampaio, Fábio Ferrentini; Vidal, Andre Luiz Pestana

2014-01-01

The aim of this work is to adapt and test, in a Brazilian public school, the ACE model proposed by Borkulo for evaluating student performance as a teaching-learning process based on computational modeling systems. The ACE model is based on different types of reasoning involving three dimensions. In addition to adapting the model and introducing…

Formal Specification of Information Systems Requirements.

ERIC Educational Resources Information Center

Kampfner, Roberto R.

1985-01-01

Presents a formal model for specification of logical requirements of computer-based information systems that incorporates structural and dynamic aspects based on two separate models: the Logical Information Processing Structure and the Logical Information Processing Network. The model's role in systems development is discussed. (MBR)

Performability modeling based on real data: A case study

NASA Technical Reports Server (NTRS)

Hsueh, M. C.; Iyer, R. K.; Trivedi, K. S.

1988-01-01

Described is a measurement-based performability model based on error and resource usage data collected on a multiprocessor system. A method for identifying the model structure is introduced and the resulting model is validated against real data. Model development from the collection of raw data to the estimation of the expected reward is described. Both normal and error behavior of the system are characterized. The measured data show that the holding times in key operational and error states are not simple exponentials and that a semi-Markov process is necessary to model system behavior. A reward function, based on the service rate and the error rate in each state, is then defined in order to estimate the performability of the system and to depict the cost of apparent types of errors.

Performability modeling based on real data: A casestudy

NASA Technical Reports Server (NTRS)

Hsueh, M. C.; Iyer, R. K.; Trivedi, K. S.

1987-01-01

Described is a measurement-based performability model based on error and resource usage data collected on a multiprocessor system. A method for identifying the model structure is introduced and the resulting model is validated against real data. Model development from the collection of raw data to the estimation of the expected reward is described. Both normal and error behavior of the system are characterized. The measured data show that the holding times in key operational and error states are not simple exponentials and that a semi-Markov process is necessary to model the system behavior. A reward function, based on the service rate and the error rate in each state, is then defined in order to estimate the performability of the system and to depict the cost of different types of errors.

Robust model predictive control for constrained continuous-time nonlinear systems

NASA Astrophysics Data System (ADS)

Sun, Tairen; Pan, Yongping; Zhang, Jun; Yu, Haoyong

2018-02-01

In this paper, a robust model predictive control (MPC) is designed for a class of constrained continuous-time nonlinear systems with bounded additive disturbances. The robust MPC consists of a nonlinear feedback control and a continuous-time model-based dual-mode MPC. The nonlinear feedback control guarantees the actual trajectory being contained in a tube centred at the nominal trajectory. The dual-mode MPC is designed to ensure asymptotic convergence of the nominal trajectory to zero. This paper extends current results on discrete-time model-based tube MPC and linear system model-based tube MPC to continuous-time nonlinear model-based tube MPC. The feasibility and robustness of the proposed robust MPC have been demonstrated by theoretical analysis and applications to a cart-damper springer system and a one-link robot manipulator.

A Model-Driven Architecture Approach for Modeling, Specifying and Deploying Policies in Autonomous and Autonomic Systems

NASA Technical Reports Server (NTRS)

Pena, Joaquin; Hinchey, Michael G.; Sterritt, Roy; Ruiz-Cortes, Antonio; Resinas, Manuel

2006-01-01

Autonomic Computing (AC), self-management based on high level guidance from humans, is increasingly gaining momentum as the way forward in designing reliable systems that hide complexity and conquer IT management costs. Effectively, AC may be viewed as Policy-Based Self-Management. The Model Driven Architecture (MDA) approach focuses on building models that can be transformed into code in an automatic manner. In this paper, we look at ways to implement Policy-Based Self-Management by means of models that can be converted to code using transformations that follow the MDA philosophy. We propose a set of UML-based models to specify autonomic and autonomous features along with the necessary procedures, based on modification and composition of models, to deploy a policy as an executing system.

A Turbine Based Combined Cycle Engine Inlet Model and Mode Transition Simulation Based on HiTECC Tool

NASA Technical Reports Server (NTRS)

Csank, Jeffrey; Stueber, Thomas

2012-01-01

An inlet system is being tested to evaluate methodologies for a turbine based combined cycle propulsion system to perform a controlled inlet mode transition. Prior to wind tunnel based hardware testing of controlled mode transitions, simulation models are used to test, debug, and validate potential control algorithms. One candidate simulation package for this purpose is the High Mach Transient Engine Cycle Code (HiTECC). The HiTECC simulation package models the inlet system, propulsion systems, thermal energy, geometry, nozzle, and fuel systems. This paper discusses the modification and redesign of the simulation package and control system to represent the NASA large-scale inlet model for Combined Cycle Engine mode transition studies, mounted in NASA Glenn s 10-foot by 10-foot Supersonic Wind Tunnel. This model will be used for designing and testing candidate control algorithms before implementation.

A Turbine Based Combined Cycle Engine Inlet Model and Mode Transition Simulation Based on HiTECC Tool

NASA Technical Reports Server (NTRS)

Csank, Jeffrey T.; Stueber, Thomas J.

2012-01-01

An inlet system is being tested to evaluate methodologies for a turbine based combined cycle propulsion system to perform a controlled inlet mode transition. Prior to wind tunnel based hardware testing of controlled mode transitions, simulation models are used to test, debug, and validate potential control algorithms. One candidate simulation package for this purpose is the High Mach Transient Engine Cycle Code (HiTECC). The HiTECC simulation package models the inlet system, propulsion systems, thermal energy, geometry, nozzle, and fuel systems. This paper discusses the modification and redesign of the simulation package and control system to represent the NASA large-scale inlet model for Combined Cycle Engine mode transition studies, mounted in NASA Glenn s 10- by 10-Foot Supersonic Wind Tunnel. This model will be used for designing and testing candidate control algorithms before implementation.

An error bound for a discrete reduced order model of a linear multivariable system

NASA Technical Reports Server (NTRS)

Al-Saggaf, Ubaid M.; Franklin, Gene F.

1987-01-01

The design of feasible controllers for high dimension multivariable systems can be greatly aided by a method of model reduction. In order for the design based on the order reduction to include a guarantee of stability, it is sufficient to have a bound on the model error. Previous work has provided such a bound for continuous-time systems for algorithms based on balancing. In this note an L-infinity bound is derived for model error for a method of order reduction of discrete linear multivariable systems based on balancing.

[Model-based biofuels system analysis: a review].

PubMed

Chang, Shiyan; Zhang, Xiliang; Zhao, Lili; Ou, Xunmin

2011-03-01

Model-based system analysis is an important tool for evaluating the potential and impacts of biofuels, and for drafting biofuels technology roadmaps and targets. The broad reach of the biofuels supply chain requires that biofuels system analyses span a range of disciplines, including agriculture/forestry, energy, economics, and the environment. Here we reviewed various models developed for or applied to modeling biofuels, and presented a critical analysis of Agriculture/Forestry System Models, Energy System Models, Integrated Assessment Models, Micro-level Cost, Energy and Emission Calculation Models, and Specific Macro-level Biofuel Models. We focused on the models' strengths, weaknesses, and applicability, facilitating the selection of a suitable type of model for specific issues. Such an analysis was a prerequisite for future biofuels system modeling, and represented a valuable resource for researchers and policy makers.

Model-Based Compositional Reasoning for Complex Systems of Systems (SoS)

DTIC Science & Technology

2016-11-01

more structured approach for finding flaws /weaknesses in the systems . As the system is updated, either in response to a found flaw or new...AFRL-RQ-WP-TR-2016-0172 MODEL-BASED COMPOSITIONAL REASONING FOR COMPLEX SYSTEMS OF SYSTEMS (SoS) M. Anthony Aiello, Benjamin D. Rodes...LABORATORY AEROSPACE SYSTEMS DIRECTORATE WRIGHT-PATTERSON AIR FORCE BASE, OH 45433-7541 AIR FORCE MATERIEL COMMAND UNITED STATES AIR FORCE NOTICE

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

Modelling and Experiment Based on a Navigation System for a Cranio-Maxillofacial Surgical Robot.

PubMed

Duan, Xingguang; Gao, Liang; Wang, Yonggui; Li, Jianxi; Li, Haoyuan; Guo, Yanjun

2018-01-01

In view of the characteristics of high risk and high accuracy in cranio-maxillofacial surgery, we present a novel surgical robot system that can be used in a variety of surgeries. The surgical robot system can assist surgeons in completing biopsy of skull base lesions, radiofrequency thermocoagulation of the trigeminal ganglion, and radioactive particle implantation of skull base malignant tumors. This paper focuses on modelling and experimental analyses of the robot system based on navigation technology. Firstly, the transformation relationship between the subsystems is realized based on the quaternion and the iterative closest point registration algorithm. The hand-eye coordination model based on optical navigation is established to control the end effector of the robot moving to the target position along the planning path. The closed-loop control method, "kinematics + optics" hybrid motion control method, is presented to improve the positioning accuracy of the system. Secondly, the accuracy of the system model was tested by model experiments. And the feasibility of the closed-loop control method was verified by comparing the positioning accuracy before and after the application of the method. Finally, the skull model experiments were performed to evaluate the function of the surgical robot system. The results validate its feasibility and are consistent with the preoperative surgical planning.

Modelling and Experiment Based on a Navigation System for a Cranio-Maxillofacial Surgical Robot

PubMed Central

Duan, Xingguang; Gao, Liang; Li, Jianxi; Li, Haoyuan; Guo, Yanjun

2018-01-01

In view of the characteristics of high risk and high accuracy in cranio-maxillofacial surgery, we present a novel surgical robot system that can be used in a variety of surgeries. The surgical robot system can assist surgeons in completing biopsy of skull base lesions, radiofrequency thermocoagulation of the trigeminal ganglion, and radioactive particle implantation of skull base malignant tumors. This paper focuses on modelling and experimental analyses of the robot system based on navigation technology. Firstly, the transformation relationship between the subsystems is realized based on the quaternion and the iterative closest point registration algorithm. The hand-eye coordination model based on optical navigation is established to control the end effector of the robot moving to the target position along the planning path. The closed-loop control method, “kinematics + optics” hybrid motion control method, is presented to improve the positioning accuracy of the system. Secondly, the accuracy of the system model was tested by model experiments. And the feasibility of the closed-loop control method was verified by comparing the positioning accuracy before and after the application of the method. Finally, the skull model experiments were performed to evaluate the function of the surgical robot system. The results validate its feasibility and are consistent with the preoperative surgical planning. PMID:29599948

Model-based Systems Engineering: Creation and Implementation of Model Validation Rules for MOS 2.0

NASA Technical Reports Server (NTRS)

Schmidt, Conrad K.

2013-01-01

Model-based Systems Engineering (MBSE) is an emerging modeling application that is used to enhance the system development process. MBSE allows for the centralization of project and system information that would otherwise be stored in extraneous locations, yielding better communication, expedited document generation and increased knowledge capture. Based on MBSE concepts and the employment of the Systems Modeling Language (SysML), extremely large and complex systems can be modeled from conceptual design through all system lifecycles. The Operations Revitalization Initiative (OpsRev) seeks to leverage MBSE to modernize the aging Advanced Multi-Mission Operations Systems (AMMOS) into the Mission Operations System 2.0 (MOS 2.0). The MOS 2.0 will be delivered in a series of conceptual and design models and documents built using the modeling tool MagicDraw. To ensure model completeness and cohesiveness, it is imperative that the MOS 2.0 models adhere to the specifications, patterns and profiles of the Mission Service Architecture Framework, thus leading to the use of validation rules. This paper outlines the process by which validation rules are identified, designed, implemented and tested. Ultimately, these rules provide the ability to maintain model correctness and synchronization in a simple, quick and effective manner, thus allowing the continuation of project and system progress.

Integrated Turbine-Based Combined Cycle Dynamic Simulation Model

NASA Technical Reports Server (NTRS)

Haid, Daniel A.; Gamble, Eric J.

2011-01-01

A Turbine-Based Combined Cycle (TBCC) dynamic simulation model has been developed to demonstrate all modes of operation, including mode transition, for a turbine-based combined cycle propulsion system. The High Mach Transient Engine Cycle Code (HiTECC) is a highly integrated tool comprised of modules for modeling each of the TBCC systems whose interactions and controllability affect the TBCC propulsion system thrust and operability during its modes of operation. By structuring the simulation modeling tools around the major TBCC functional modes of operation (Dry Turbojet, Afterburning Turbojet, Transition, and Dual Mode Scramjet) the TBCC mode transition and all necessary intermediate events over its entire mission may be developed, modeled, and validated. The reported work details the use of the completed model to simulate a TBCC propulsion system as it accelerates from Mach 2.5, through mode transition, to Mach 7. The completion of this model and its subsequent use to simulate TBCC mode transition significantly extends the state-of-the-art for all TBCC modes of operation by providing a numerical simulation of the systems, interactions, and transient responses affecting the ability of the propulsion system to transition from turbine-based to ramjet/scramjet-based propulsion while maintaining constant thrust.

Getting expert systems off the ground: Lessons learned from integrating model-based diagnostics with prototype flight hardware

NASA Technical Reports Server (NTRS)

Stephan, Amy; Erikson, Carol A.

1991-01-01

As an initial attempt to introduce expert system technology into an onboard environment, a model based diagnostic system using the TRW MARPLE software tool was integrated with prototype flight hardware and its corresponding control software. Because this experiment was designed primarily to test the effectiveness of the model based reasoning technique used, the expert system ran on a separate hardware platform, and interactions between the control software and the model based diagnostics were limited. While this project met its objective of showing that model based reasoning can effectively isolate failures in flight hardware, it also identified the need for an integrated development path for expert system and control software for onboard applications. In developing expert systems that are ready for flight, artificial intelligence techniques must be evaluated to determine whether they offer a real advantage onboard, identify which diagnostic functions should be performed by the expert systems and which are better left to the procedural software, and work closely with both the hardware and the software developers from the beginning of a project to produce a well designed and thoroughly integrated application.

Data-base development for water-quality modeling of the Patuxent River basin, Maryland

USGS Publications Warehouse

Fisher, G.T.; Summers, R.M.

1987-01-01

Procedures and rationale used to develop a data base and data management system for the Patuxent Watershed Nonpoint Source Water Quality Monitoring and Modeling Program of the Maryland Department of the Environment and the U.S. Geological Survey are described. A detailed data base and data management system has been developed to facilitate modeling of the watershed for water quality planning purposes; statistical analysis; plotting of meteorologic, hydrologic and water quality data; and geographic data analysis. The system is Maryland 's prototype for development of a basinwide water quality management program. A key step in the program is to build a calibrated and verified water quality model of the basin using the Hydrological Simulation Program--FORTRAN (HSPF) hydrologic model, which has been used extensively in large-scale basin modeling. The compilation of the substantial existing data base for preliminary calibration of the basin model, including meteorologic, hydrologic, and water quality data from federal and state data bases and a geographic information system containing digital land use and soils data is described. The data base development is significant in its application of an integrated, uniform approach to data base management and modeling. (Lantz-PTT)

Space-time modeling using environmental constraints in a mobile robot system

NASA Technical Reports Server (NTRS)

Slack, Marc G.

1990-01-01

Grid-based models of a robot's local environment have been used by many researchers building mobile robot control systems. The attraction of grid-based models is their clear parallel between the internal model and the external world. However, the discrete nature of such representations does not match well with the continuous nature of actions and usually serves to limit the abilities of the robot. This work describes a spatial modeling system that extracts information from a grid-based representation to form a symbolic representation of the robot's local environment. The approach makes a separation between the representation provided by the sensing system and the representation used by the action system. Separation allows asynchronous operation between sensing and action in a mobile robot, as well as the generation of a more continuous representation upon which to base actions.

A Model-Based Prognostics Approach Applied to Pneumatic Valves

NASA Technical Reports Server (NTRS)

Daigle, Matthew J.; Goebel, Kai

2011-01-01

Within the area of systems health management, the task of prognostics centers on predicting when components will fail. Model-based prognostics exploits domain knowledge of the system, its components, and how they fail by casting the underlying physical phenomena in a physics-based model that is derived from first principles. Uncertainty cannot be avoided in prediction, therefore, algorithms are employed that help in managing these uncertainties. The particle filtering algorithm has become a popular choice for model-based prognostics due to its wide applicability, ease of implementation, and support for uncertainty management. We develop a general model-based prognostics methodology within a robust probabilistic framework using particle filters. As a case study, we consider a pneumatic valve from the Space Shuttle cryogenic refueling system. We develop a detailed physics-based model of the pneumatic valve, and perform comprehensive simulation experiments to illustrate our prognostics approach and evaluate its effectiveness and robustness. The approach is demonstrated using historical pneumatic valve data from the refueling system.

Exploratory Model Analysis of the Space Based Infrared System (SBIRS) Low Global Scheduler Problem

DTIC Science & Technology

1999-12-01

solution. The non- linear least squares model is defined as Y = f{e,t) where: 0 =M-element parameter vector Y =N-element vector of all data t...NAVAL POSTGRADUATE SCHOOL Monterey, California THESIS EXPLORATORY MODEL ANALYSIS OF THE SPACE BASED INFRARED SYSTEM (SBIRS) LOW GLOBAL SCHEDULER...December 1999 3. REPORT TYPE AND DATES COVERED Master’s Thesis 4. TITLE AND SUBTITLE EXPLORATORY MODEL ANALYSIS OF THE SPACE BASED INFRARED SYSTEM

ADAM: analysis of discrete models of biological systems using computer algebra.

PubMed

Hinkelmann, Franziska; Brandon, Madison; Guang, Bonny; McNeill, Rustin; Blekherman, Grigoriy; Veliz-Cuba, Alan; Laubenbacher, Reinhard

2011-07-20

Many biological systems are modeled qualitatively with discrete models, such as probabilistic Boolean networks, logical models, Petri nets, and agent-based models, to gain a better understanding of them. The computational complexity to analyze the complete dynamics of these models grows exponentially in the number of variables, which impedes working with complex models. There exist software tools to analyze discrete models, but they either lack the algorithmic functionality to analyze complex models deterministically or they are inaccessible to many users as they require understanding the underlying algorithm and implementation, do not have a graphical user interface, or are hard to install. Efficient analysis methods that are accessible to modelers and easy to use are needed. We propose a method for efficiently identifying attractors and introduce the web-based tool Analysis of Dynamic Algebraic Models (ADAM), which provides this and other analysis methods for discrete models. ADAM converts several discrete model types automatically into polynomial dynamical systems and analyzes their dynamics using tools from computer algebra. Specifically, we propose a method to identify attractors of a discrete model that is equivalent to solving a system of polynomial equations, a long-studied problem in computer algebra. Based on extensive experimentation with both discrete models arising in systems biology and randomly generated networks, we found that the algebraic algorithms presented in this manuscript are fast for systems with the structure maintained by most biological systems, namely sparseness and robustness. For a large set of published complex discrete models, ADAM identified the attractors in less than one second. Discrete modeling techniques are a useful tool for analyzing complex biological systems and there is a need in the biological community for accessible efficient analysis tools. ADAM provides analysis methods based on mathematical algorithms as a web-based tool for several different input formats, and it makes analysis of complex models accessible to a larger community, as it is platform independent as a web-service and does not require understanding of the underlying mathematics.

Distributed Prognostics based on Structural Model Decomposition

NASA Technical Reports Server (NTRS)

Daigle, Matthew J.; Bregon, Anibal; Roychoudhury, I.

2014-01-01

Within systems health management, prognostics focuses on predicting the remaining useful life of a system. In the model-based prognostics paradigm, physics-based models are constructed that describe the operation of a system and how it fails. Such approaches consist of an estimation phase, in which the health state of the system is first identified, and a prediction phase, in which the health state is projected forward in time to determine the end of life. Centralized solutions to these problems are often computationally expensive, do not scale well as the size of the system grows, and introduce a single point of failure. In this paper, we propose a novel distributed model-based prognostics scheme that formally describes how to decompose both the estimation and prediction problems into independent local subproblems whose solutions may be easily composed into a global solution. The decomposition of the prognostics problem is achieved through structural decomposition of the underlying models. The decomposition algorithm creates from the global system model a set of local submodels suitable for prognostics. Independent local estimation and prediction problems are formed based on these local submodels, resulting in a scalable distributed prognostics approach that allows the local subproblems to be solved in parallel, thus offering increases in computational efficiency. Using a centrifugal pump as a case study, we perform a number of simulation-based experiments to demonstrate the distributed approach, compare the performance with a centralized approach, and establish its scalability. Index Terms-model-based prognostics, distributed prognostics, structural model decomposition ABBREVIATIONS

Applying Model Based Systems Engineering to NASA's Space Communications Networks

NASA Technical Reports Server (NTRS)

Bhasin, Kul; Barnes, Patrick; Reinert, Jessica; Golden, Bert

2013-01-01

System engineering practices for complex systems and networks now require that requirement, architecture, and concept of operations product development teams, simultaneously harmonize their activities to provide timely, useful and cost-effective products. When dealing with complex systems of systems, traditional systems engineering methodology quickly falls short of achieving project objectives. This approach is encumbered by the use of a number of disparate hardware and software tools, spreadsheets and documents to grasp the concept of the network design and operation. In case of NASA's space communication networks, since the networks are geographically distributed, and so are its subject matter experts, the team is challenged to create a common language and tools to produce its products. Using Model Based Systems Engineering methods and tools allows for a unified representation of the system in a model that enables a highly related level of detail. To date, Program System Engineering (PSE) team has been able to model each network from their top-level operational activities and system functions down to the atomic level through relational modeling decomposition. These models allow for a better understanding of the relationships between NASA's stakeholders, internal organizations, and impacts to all related entities due to integration and sustainment of existing systems. Understanding the existing systems is essential to accurate and detailed study of integration options being considered. In this paper, we identify the challenges the PSE team faced in its quest to unify complex legacy space communications networks and their operational processes. We describe the initial approaches undertaken and the evolution toward model based system engineering applied to produce Space Communication and Navigation (SCaN) PSE products. We will demonstrate the practice of Model Based System Engineering applied to integrating space communication networks and the summary of its results and impact. We will highlight the insights gained by applying the Model Based System Engineering and provide recommendations for its applications and improvements.

Modeling Web-Based Educational Systems: Process Design Teaching Model

ERIC Educational Resources Information Center

Rokou, Franca Pantano; Rokou, Elena; Rokos, Yannis

2004-01-01

Using modeling languages is essential to the construction of educational systems based on software engineering principles and methods. Furthermore, the instructional design is undoubtedly the cornerstone of the design and development of educational systems. Although several methodologies and languages have been proposed for the specification of…

A family systems-based model of organizational intervention.

PubMed

Shumway, Sterling T; Kimball, Thomas G; Korinek, Alan W; Arredondo, Rudy

2007-04-01

Employee assistance professionals are expected to be proficient at intervening in organizations and creating meaningful behavioral change in interpersonal functioning. Because of their training in family systems theories and concepts, marriage and family therapists (MFTs) are well suited to serve organizations as "systems consultants." Unfortunately, the authors were unable to identify any family systems-based models for organizational intervention that have been empirically tested and supported. In this article, the authors present a family systems-based model of intervention that they developed while working in an employee assistance program (EAP). They also present research that was used to refine the model and to provide initial support for its effectiveness.

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.

Model Error Budgets

NASA Technical Reports Server (NTRS)

Briggs, Hugh C.

2008-01-01

An error budget is a commonly used tool in design of complex aerospace systems. It represents system performance requirements in terms of allowable errors and flows these down through a hierarchical structure to lower assemblies and components. The requirements may simply be 'allocated' based upon heuristics or experience, or they may be designed through use of physics-based models. This paper presents a basis for developing an error budget for models of the system, as opposed to the system itself. The need for model error budgets arises when system models are a principle design agent as is increasingly more common for poorly testable high performance space systems.

Managing Analysis Models in the Design Process

NASA Technical Reports Server (NTRS)

Briggs, Clark

2006-01-01

Design of large, complex space systems depends on significant model-based support for exploration of the design space. Integrated models predict system performance in mission-relevant terms given design descriptions and multiple physics-based numerical models. Both the design activities and the modeling activities warrant explicit process definitions and active process management to protect the project from excessive risk. Software and systems engineering processes have been formalized and similar formal process activities are under development for design engineering and integrated modeling. JPL is establishing a modeling process to define development and application of such system-level models.

Ionospheric Slant Total Electron Content Analysis Using Global Positioning System Based Estimation

NASA Technical Reports Server (NTRS)

Komjathy, Attila (Inventor); Mannucci, Anthony J. (Inventor); Sparks, Lawrence C. (Inventor)

2017-01-01

A method, system, apparatus, and computer program product provide the ability to analyze ionospheric slant total electron content (TEC) using global navigation satellite systems (GNSS)-based estimation. Slant TEC is estimated for a given set of raypath geometries by fitting historical GNSS data to a specified delay model. The accuracy of the specified delay model is estimated by computing delay estimate residuals and plotting a behavior of the delay estimate residuals. An ionospheric threat model is computed based on the specified delay model. Ionospheric grid delays (IGDs) and grid ionospheric vertical errors (GIVEs) are computed based on the ionospheric threat model.

A prototype computer-aided modelling tool for life-support system models

NASA Technical Reports Server (NTRS)

Preisig, H. A.; Lee, Tae-Yeong; Little, Frank

1990-01-01

Based on the canonical decomposition of physical-chemical-biological systems, a prototype kernel has been developed to efficiently model alternative life-support systems. It supports (1) the work in an interdisciplinary group through an easy-to-use mostly graphical interface, (2) modularized object-oriented model representation, (3) reuse of models, (4) inheritance of structures from model object to model object, and (5) model data base. The kernel is implemented in Modula-II and presently operates on an IBM PC.

Analyzing Cyber Security Threats on Cyber-Physical Systems Using Model-Based Systems Engineering

NASA Technical Reports Server (NTRS)

Kerzhner, Aleksandr; Pomerantz, Marc; Tan, Kymie; Campuzano, Brian; Dinkel, Kevin; Pecharich, Jeremy; Nguyen, Viet; Steele, Robert; Johnson, Bryan

2015-01-01

The spectre of cyber attacks on aerospace systems can no longer be ignored given that many of the components and vulnerabilities that have been successfully exploited by the adversary on other infrastructures are the same as those deployed and used within the aerospace environment. An important consideration with respect to the mission/safety critical infrastructure supporting space operations is that an appropriate defensive response to an attack invariably involves the need for high precision and accuracy, because an incorrect response can trigger unacceptable losses involving lives and/or significant financial damage. A highly precise defensive response, considering the typical complexity of aerospace environments, requires a detailed and well-founded understanding of the underlying system where the goal of the defensive response is to preserve critical mission objectives in the presence of adversarial activity. In this paper, a structured approach for modeling aerospace systems is described. The approach includes physical elements, network topology, software applications, system functions, and usage scenarios. We leverage Model-Based Systems Engineering methodology by utilizing the Object Management Group's Systems Modeling Language to represent the system being analyzed and also utilize model transformations to change relevant aspects of the model into specialized analyses. A novel visualization approach is utilized to visualize the entire model as a three-dimensional graph, allowing easier interaction with subject matter experts. The model provides a unifying structure for analyzing the impact of a particular attack or a particular type of attack. Two different example analysis types are demonstrated in this paper: a graph-based propagation analysis based on edge labels, and a graph-based propagation analysis based on node labels.

Discovering the Power of Individual-Based Modelling in Teaching and Learning: The Study of a Predator-Prey System

NASA Astrophysics Data System (ADS)

Ginovart, Marta

2014-08-01

The general aim is to promote the use of individual-based models (biological agent-based models) in teaching and learning contexts in life sciences and to make their progressive incorporation into academic curricula easier, complementing other existing modelling strategies more frequently used in the classroom. Modelling activities for the study of a predator-prey system for a mathematics classroom in the first year of an undergraduate program in biosystems engineering have been designed and implemented. These activities were designed to put two modelling approaches side by side, an individual-based model and a set of ordinary differential equations. In order to organize and display this, a system with wolves and sheep in a confined domain was considered and studied. With the teaching material elaborated and a computer to perform the numerical resolutions involved and the corresponding individual-based simulations, the students answered questions and completed exercises to achieve the learning goals set. Students' responses regarding the modelling of biological systems and these two distinct methodologies applied to the study of a predator-prey system were collected via questionnaires, open-ended queries and face-to-face dialogues. Taking into account the positive responses of the students when they were doing these activities, it was clear that using a discrete individual-based model to deal with a predator-prey system jointly with a set of ordinary differential equations enriches the understanding of the modelling process, adds new insights and opens novel perspectives of what can be done with computational models versus other models. The complementary views given by the two modelling approaches were very well assessed by students.

When Does Model-Based Control Pay Off?

PubMed

Kool, Wouter; Cushman, Fiery A; Gershman, Samuel J

2016-08-01

Many accounts of decision making and reinforcement learning posit the existence of two distinct systems that control choice: a fast, automatic system and a slow, deliberative system. Recent research formalizes this distinction by mapping these systems to "model-free" and "model-based" strategies in reinforcement learning. Model-free strategies are computationally cheap, but sometimes inaccurate, because action values can be accessed by inspecting a look-up table constructed through trial-and-error. In contrast, model-based strategies compute action values through planning in a causal model of the environment, which is more accurate but also more cognitively demanding. It is assumed that this trade-off between accuracy and computational demand plays an important role in the arbitration between the two strategies, but we show that the hallmark task for dissociating model-free and model-based strategies, as well as several related variants, do not embody such a trade-off. We describe five factors that reduce the effectiveness of the model-based strategy on these tasks by reducing its accuracy in estimating reward outcomes and decreasing the importance of its choices. Based on these observations, we describe a version of the task that formally and empirically obtains an accuracy-demand trade-off between model-free and model-based strategies. Moreover, we show that human participants spontaneously increase their reliance on model-based control on this task, compared to the original paradigm. Our novel task and our computational analyses may prove important in subsequent empirical investigations of how humans balance accuracy and demand.

Integrating physically based simulators with Event Detection Systems: Multi-site detection approach.

PubMed

Housh, Mashor; Ohar, Ziv

2017-03-01

The Fault Detection (FD) Problem in control theory concerns of monitoring a system to identify when a fault has occurred. Two approaches can be distinguished for the FD: Signal processing based FD and Model-based FD. The former concerns of developing algorithms to directly infer faults from sensors' readings, while the latter uses a simulation model of the real-system to analyze the discrepancy between sensors' readings and expected values from the simulation model. Most contamination Event Detection Systems (EDSs) for water distribution systems have followed the signal processing based FD, which relies on analyzing the signals from monitoring stations independently of each other, rather than evaluating all stations simultaneously within an integrated network. In this study, we show that a model-based EDS which utilizes a physically based water quality and hydraulics simulation models, can outperform the signal processing based EDS. We also show that the model-based EDS can facilitate the development of a Multi-Site EDS (MSEDS), which analyzes the data from all the monitoring stations simultaneously within an integrated network. The advantage of the joint analysis in the MSEDS is expressed by increased detection accuracy (higher true positive alarms and fewer false alarms) and shorter detection time. Copyright © 2016 Elsevier Ltd. 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

Artificial intelligence in process control: Knowledge base for the shuttle ECS model

NASA Technical Reports Server (NTRS)

Stiffler, A. Kent

1989-01-01

The general operation of KATE, an artificial intelligence controller, is outlined. A shuttle environmental control system (ECS) demonstration system for KATE is explained. The knowledge base model for this system is derived. An experimental test procedure is given to verify parameters in the model.

The System Dynamics Model User Sustainability Explorer (SD-MUSE) user interface: a user-friendly tool for interpreting system dynamic models

EPA Science Inventory

Sustainability-based decision making is a challenging process that requires balancing trade-offs among social, economic, and environmental components. System Dynamic (SD) models can be useful tools to inform sustainability-based decision making because they provide a holistic co...

Identifying Model-Based Reconfiguration Goals through Functional Deficiencies

NASA Technical Reports Server (NTRS)

Benazera, Emmanuel; Trave-Massuyes, Louise

2004-01-01

Model-based diagnosis is now advanced to the point autonomous systems face some uncertain and faulty situations with success. The next step toward more autonomy is to have the system recovering itself after faults occur, a process known as model-based reconfiguration. After faults occur, given a prediction of the nominal behavior of the system and the result of the diagnosis operation, this paper details how to automatically determine the functional deficiencies of the system. These deficiencies are characterized in the case of uncertain state estimates. A methodology is then presented to determine the reconfiguration goals based on the deficiencies. Finally, a recovery process interleaves planning and model predictive control to restore the functionalities in prioritized order.

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...

Expert systems and simulation models; Proceedings of the Seminar, Tucson, AZ, November 18, 19, 1985

NASA Technical Reports Server (NTRS)

1986-01-01

The seminar presents papers on modeling and simulation methodology, artificial intelligence and expert systems, environments for simulation/expert system development, and methodology for simulation/expert system development. Particular attention is given to simulation modeling concepts and their representation, modular hierarchical model specification, knowledge representation, and rule-based diagnostic expert system development. Other topics include the combination of symbolic and discrete event simulation, real time inferencing, and the management of large knowledge-based simulation projects.

Feedback loops and temporal misalignment in component-based hydrologic modeling

NASA Astrophysics Data System (ADS)

Elag, Mostafa M.; Goodall, Jonathan L.; Castronova, Anthony M.

2011-12-01

In component-based modeling, a complex system is represented as a series of loosely integrated components with defined interfaces and data exchanges that allow the components to be coupled together through shared boundary conditions. Although the component-based paradigm is commonly used in software engineering, it has only recently been applied for modeling hydrologic and earth systems. As a result, research is needed to test and verify the applicability of the approach for modeling hydrologic systems. The objective of this work was therefore to investigate two aspects of using component-based software architecture for hydrologic modeling: (1) simulation of feedback loops between components that share a boundary condition and (2) data transfers between temporally misaligned model components. We investigated these topics using a simple case study where diffusion of mass is modeled across a water-sediment interface. We simulated the multimedia system using two model components, one for the water and one for the sediment, coupled using the Open Modeling Interface (OpenMI) standard. The results were compared with a more conventional numerical approach for solving the system where the domain is represented by a single multidimensional array. Results showed that the component-based approach was able to produce the same results obtained with the more conventional numerical approach. When the two components were temporally misaligned, we explored the use of different interpolation schemes to minimize mass balance error within the coupled system. The outcome of this work provides evidence that component-based modeling can be used to simulate complicated feedback loops between systems and guidance as to how different interpolation schemes minimize mass balance error introduced when components are temporally misaligned.

IPA (v1): a framework for agent-based modelling of soil water movement

NASA Astrophysics Data System (ADS)

Mewes, Benjamin; Schumann, Andreas H.

2018-06-01

In the last decade, agent-based modelling (ABM) became a popular modelling technique in social sciences, medicine, biology, and ecology. ABM was designed to simulate systems that are highly dynamic and sensitive to small variations in their composition and their state. As hydrological systems, and natural systems in general, often show dynamic and non-linear behaviour, ABM can be an appropriate way to model these systems. Nevertheless, only a few studies have utilized the ABM method for process-based modelling in hydrology. The percolation of water through the unsaturated soil is highly responsive to the current state of the soil system; small variations in composition lead to major changes in the transport system. Hence, we present a new approach for modelling the movement of water through a soil column: autonomous water agents that transport water through the soil while interacting with their environment as well as with other agents under physical laws.

Trajectory-Based Loads for the Ares I-X Test Flight Vehicle

NASA Technical Reports Server (NTRS)

Vause, Roland F.; Starr, Brett R.

2011-01-01

In trajectory-based loads, the structural engineer treats each point on the trajectory as a load case. Distributed aero, inertial, and propulsion forces are developed for the structural model which are equivalent to the integrated values of the trajectory model. Free-body diagrams are then used to solve for the internal forces, or loads, that keep the applied aero, inertial, and propulsion forces in dynamic equilibrium. There are several advantages to using trajectory-based loads. First, consistency is maintained between the integrated equilibrium equations of the trajectory analysis and the distributed equilibrium equations of the structural analysis. Second, the structural loads equations are tied to the uncertainty model for the trajectory systems analysis model. Atmosphere, aero, propulsion, mass property, and controls uncertainty models all feed into the dispersions that are generated for the trajectory systems analysis model. Changes in any of these input models will affect structural loads response. The trajectory systems model manages these inputs as well as the output from the structural model over thousands of dispersed cases. Large structural models with hundreds of thousands of degrees of freedom would execute too slowly to be an efficient part of several thousand system analyses. Trajectory-based loads provide a means for the structures discipline to be included in the integrated systems analysis. Successful applications of trajectory-based loads methods for the Ares I-X vehicle are covered in this paper. Preliminary design loads were based on 2000 trajectories using Monte Carlo dispersions. Range safety loads were tied to 8423 malfunction turn trajectories. In addition, active control system loads were based on 2000 preflight trajectories using Monte Carlo dispersions.

State Analysis Database Tool

NASA Technical Reports Server (NTRS)

Rasmussen, Robert; Bennett, Matthew

2006-01-01

The State Analysis Database Tool software establishes a productive environment for collaboration among software and system engineers engaged in the development of complex interacting systems. The tool embodies State Analysis, a model-based system engineering methodology founded on a state-based control architecture (see figure). A state represents a momentary condition of an evolving system, and a model may describe how a state evolves and is affected by other states. The State Analysis methodology is a process for capturing system and software requirements in the form of explicit models and states, and defining goal-based operational plans consistent with the models. Requirements, models, and operational concerns have traditionally been documented in a variety of system engineering artifacts that address different aspects of a mission s lifecycle. In State Analysis, requirements, models, and operations information are State Analysis artifacts that are consistent and stored in a State Analysis Database. The tool includes a back-end database, a multi-platform front-end client, and Web-based administrative functions. The tool is structured to prompt an engineer to follow the State Analysis methodology, to encourage state discovery and model description, and to make software requirements and operations plans consistent with model descriptions.

Disaggregation and Refinement of System Dynamics Models via Agent-based Modeling

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

Nutaro, James J; Ozmen, Ozgur; Schryver, Jack C

System dynamics models are usually used to investigate aggregate level behavior, but these models can be decomposed into agents that have more realistic individual behaviors. Here we develop a simple model of the STEM workforce to illuminate the impacts that arise from the disaggregation and refinement of system dynamics models via agent-based modeling. Particularly, alteration of Poisson assumptions, adding heterogeneity to decision-making processes of agents, and discrete-time formulation are investigated and their impacts are illustrated. The goal is to demonstrate both the promise and danger of agent-based modeling in the context of a relatively simple model and to delineate themore » importance of modeling decisions that are often overlooked.« less

Conceptual Model of Quantities, Units, Dimensions, and Values

NASA Technical Reports Server (NTRS)

Rouquette, Nicolas F.; DeKoenig, Hans-Peter; Burkhart, Roger; Espinoza, Huascar

2011-01-01

JPL collaborated with experts from industry and other organizations to develop a conceptual model of quantities, units, dimensions, and values based on the current work of the ISO 80000 committee revising the International System of Units & Quantities based on the International Vocabulary of Metrology (VIM). By providing support for ISO 80000 in SysML via the International Vocabulary of Metrology (VIM), this conceptual model provides, for the first time, a standard-based approach for addressing issues of unit coherence and dimensional analysis into the practice of systems engineering with SysML-based tools. This conceptual model provides support for two kinds of analyses specified in the International Vocabulary of Metrology (VIM): coherence of units as well as of systems of units, and dimension analysis of systems of quantities. To provide a solid and stable foundation, the model for defining quantities, units, dimensions, and values in SysML is explicitly based on the concepts defined in VIM. At the same time, the model library is designed in such a way that extensions to the ISQ (International System of Quantities) and SI Units (Systeme International d Unites) can be represented, as well as any alternative systems of quantities and units. The model library can be used to support SysML user models in various ways. A simple approach is to define and document libraries of reusable systems of units and quantities for reuse across multiple projects, and to link units and quantity kinds from these libraries to Unit and QuantityKind stereotypes defined in SysML user models.

Application of Complex Adaptive Systems in Portfolio Management

ERIC Educational Resources Information Center

Su, Zheyuan

2017-01-01

Simulation-based methods are becoming a promising research tool in financial markets. A general Complex Adaptive System can be tailored to different application scenarios. Based on the current research, we built two models that would benefit portfolio management by utilizing Complex Adaptive Systems (CAS) in Agent-based Modeling (ABM) approach.…

Nonlinear dynamic modeling of a simple flexible rotor system subjected to time-variable base motions

NASA Astrophysics Data System (ADS)

Chen, Liqiang; Wang, Jianjun; Han, Qinkai; Chu, Fulei

2017-09-01

Rotor systems carried in transportation system or under seismic excitations are considered to have a moving base. To study the dynamic behavior of flexible rotor systems subjected to time-variable base motions, a general model is developed based on finite element method and Lagrange's equation. Two groups of Euler angles are defined to describe the rotation of the rotor with respect to the base and that of the base with respect to the ground. It is found that the base rotations would cause nonlinearities in the model. To verify the proposed model, a novel test rig which could simulate the base angular-movement is designed. Dynamic experiments on a flexible rotor-bearing system with base angular motions are carried out. Based upon these, numerical simulations are conducted to further study the dynamic response of the flexible rotor under harmonic angular base motions. The effects of base angular amplitude, rotating speed and base frequency on response behaviors are discussed by means of FFT, waterfall, frequency response curve and orbits of the rotor. The FFT and waterfall plots of the disk horizontal and vertical vibrations are marked with multiplications of the base frequency and sum and difference tones of the rotating frequency and the base frequency. Their amplitudes will increase remarkably when they meet the whirling frequencies of the rotor system.

A Classification Model and an Open E-Learning System Based on Intuitionistic Fuzzy Sets for Instructional Design Concepts

ERIC Educational Resources Information Center

Güyer, Tolga; Aydogdu, Seyhmus

2016-01-01

This study suggests a classification model and an e-learning system based on this model for all instructional theories, approaches, models, strategies, methods, and technics being used in the process of instructional design that constitutes a direct or indirect resource for educational technology based on the theory of intuitionistic fuzzy sets…

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.

Faults Discovery By Using Mined Data

NASA Technical Reports Server (NTRS)

Lee, Charles

2005-01-01

Fault discovery in the complex systems consist of model based reasoning, fault tree analysis, rule based inference methods, and other approaches. Model based reasoning builds models for the systems either by mathematic formulations or by experiment model. Fault Tree Analysis shows the possible causes of a system malfunction by enumerating the suspect components and their respective failure modes that may have induced the problem. The rule based inference build the model based on the expert knowledge. Those models and methods have one thing in common; they have presumed some prior-conditions. Complex systems often use fault trees to analyze the faults. Fault diagnosis, when error occurs, is performed by engineers and analysts performing extensive examination of all data gathered during the mission. International Space Station (ISS) control center operates on the data feedback from the system and decisions are made based on threshold values by using fault trees. Since those decision-making tasks are safety critical and must be done promptly, the engineers who manually analyze the data are facing time challenge. To automate this process, this paper present an approach that uses decision trees to discover fault from data in real-time and capture the contents of fault trees as the initial state of the trees.

Model-based diagnostics for Space Station Freedom

NASA Technical Reports Server (NTRS)

Fesq, Lorraine M.; Stephan, Amy; Martin, Eric R.; Lerutte, Marcel G.

1991-01-01

An innovative approach to fault management was recently demonstrated for the NASA LeRC Space Station Freedom (SSF) power system testbed. This project capitalized on research in model-based reasoning, which uses knowledge of a system's behavior to monitor its health. The fault management system (FMS) can isolate failures online, or in a post analysis mode, and requires no knowledge of failure symptoms to perform its diagnostics. An in-house tool called MARPLE was used to develop and run the FMS. MARPLE's capabilities are similar to those available from commercial expert system shells, although MARPLE is designed to build model-based as opposed to rule-based systems. These capabilities include functions for capturing behavioral knowledge, a reasoning engine that implements a model-based technique known as constraint suspension, and a tool for quickly generating new user interfaces. The prototype produced by applying MARPLE to SSF not only demonstrated that model-based reasoning is a valuable diagnostic approach, but it also suggested several new applications of MARPLE, including an integration and testing aid, and a complement to state estimation.

Can We Practically Bring Physics-based Modeling Into Operational Analytics Tools?

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

Granderson, Jessica; Bonvini, Marco; Piette, Mary Ann

We present that analytics software is increasingly used to improve and maintain operational efficiency in commercial buildings. Energy managers, owners, and operators are using a diversity of commercial offerings often referred to as Energy Information Systems, Fault Detection and Diagnostic (FDD) systems, or more broadly Energy Management and Information Systems, to cost-effectively enable savings on the order of ten to twenty percent. Most of these systems use data from meters and sensors, with rule-based and/or data-driven models to characterize system and building behavior. In contrast, physics-based modeling uses first-principles and engineering models (e.g., efficiency curves) to characterize system and buildingmore » behavior. Historically, these physics-based approaches have been used in the design phase of the building life cycle or in retrofit analyses. Researchers have begun exploring the benefits of integrating physics-based models with operational data analytics tools, bridging the gap between design and operations. In this paper, we detail the development and operator use of a software tool that uses hybrid data-driven and physics-based approaches to cooling plant FDD and optimization. Specifically, we describe the system architecture, models, and FDD and optimization algorithms; advantages and disadvantages with respect to purely data-driven approaches; and practical implications for scaling and replicating these techniques. Finally, we conclude with an evaluation of the future potential for such tools and future research opportunities.« less

Electromagnetic interference modeling and suppression techniques in variable-frequency drive systems

NASA Astrophysics Data System (ADS)

Yang, Le; Wang, Shuo; Feng, Jianghua

2017-11-01

Electromagnetic interference (EMI) causes electromechanical damage to the motors and degrades the reliability of variable-frequency drive (VFD) systems. Unlike fundamental frequency components in motor drive systems, high-frequency EMI noise, coupled with the parasitic parameters of the trough system, are difficult to analyze and reduce. In this article, EMI modeling techniques for different function units in a VFD system, including induction motors, motor bearings, and rectifierinverters, are reviewed and evaluated in terms of applied frequency range, model parameterization, and model accuracy. The EMI models for the motors are categorized based on modeling techniques and model topologies. Motor bearing and shaft models are also reviewed, and techniques that are used to eliminate bearing current are evaluated. Modeling techniques for conventional rectifierinverter systems are also summarized. EMI noise suppression techniques, including passive filter, Wheatstone bridge balance, active filter, and optimized modulation, are reviewed and compared based on the VFD system models.

LINKING THE CMAQ AND HYSPLIT MODELING SYSTEM INTERFACE PROGRAM AND EXAMPLE APPLICATION

EPA Science Inventory

A new software tool has been developed to link the Eulerian-based Community Multiscale Air Quality (CMAQ) modeling system with the Lagrangian-based HYSPLIT (HYbrid Single-Particle Lagrangian Integrated Trajectory) model. Both models require many of the same hourly meteorological...

A novel AIDS/HIV intelligent medical consulting system based on expert systems.

PubMed

Ebrahimi, Alireza Pour; Toloui Ashlaghi, Abbas; Mahdavy Rad, Maryam

2013-01-01

The purpose of this paper is to propose a novel intelligent model for AIDS/HIV data based on expert system and using it for developing an intelligent medical consulting system for AIDS/HIV. In this descriptive research, 752 frequently asked questions (FAQs) about AIDS/HIV are gathered from numerous websites about this disease. To perform the data mining and extracting the intelligent model, the 6 stages of Crisp method has been completed for FAQs. The 6 stages include: Business understanding, data understanding, data preparation, modelling, evaluation and deployment. C5.0 Tree classification algorithm is used for modelling. Also, rational unified process (RUP) is used to develop the web-based medical consulting software. Stages of RUP are as follows: Inception, elaboration, construction and transition. The intelligent developed model has been used in the infrastructure of the software and based on client's inquiry and keywords related FAQs are displayed to the client, according to the rank. FAQs' ranks are gradually determined considering clients reading it. Based on displayed FAQs, test and entertainment links are also displayed. The accuracy of the AIDS/HIV intelligent web-based medical consulting system is estimated to be 78.76%. AIDS/HIV medical consulting systems have been developed using intelligent infrastructure. Being equipped with an intelligent model, providing consulting services on systematic textual data and providing side services based on client's activities causes the implemented system to be unique. The research has been approved by Iranian Ministry of Health and Medical Education for being practical.

Model-Based Diagnostics for Propellant Loading Systems

NASA Technical Reports Server (NTRS)

Daigle, Matthew John; Foygel, Michael; Smelyanskiy, Vadim N.

2011-01-01

The loading of spacecraft propellants is a complex, risky operation. Therefore, diagnostic solutions are necessary to quickly identify when a fault occurs, so that recovery actions can be taken or an abort procedure can be initiated. Model-based diagnosis solutions, established using an in-depth analysis and understanding of the underlying physical processes, offer the advanced capability to quickly detect and isolate faults, identify their severity, and predict their effects on system performance. We develop a physics-based model of a cryogenic propellant loading system, which describes the complex dynamics of liquid hydrogen filling from a storage tank to an external vehicle tank, as well as the influence of different faults on this process. The model takes into account the main physical processes such as highly nonequilibrium condensation and evaporation of the hydrogen vapor, pressurization, and also the dynamics of liquid hydrogen and vapor flows inside the system in the presence of helium gas. Since the model incorporates multiple faults in the system, it provides a suitable framework for model-based diagnostics and prognostics algorithms. Using this model, we analyze the effects of faults on the system, derive symbolic fault signatures for the purposes of fault isolation, and perform fault identification using a particle filter approach. We demonstrate the detection, isolation, and identification of a number of faults using simulation-based experiments.

Hybrid forecasting of chaotic processes: Using machine learning in conjunction with a knowledge-based model

NASA Astrophysics Data System (ADS)

Pathak, Jaideep; Wikner, Alexander; Fussell, Rebeckah; Chandra, Sarthak; Hunt, Brian R.; Girvan, Michelle; Ott, Edward

2018-04-01

A model-based approach to forecasting chaotic dynamical systems utilizes knowledge of the mechanistic processes governing the dynamics to build an approximate mathematical model of the system. In contrast, machine learning techniques have demonstrated promising results for forecasting chaotic systems purely from past time series measurements of system state variables (training data), without prior knowledge of the system dynamics. The motivation for this paper is the potential of machine learning for filling in the gaps in our underlying mechanistic knowledge that cause widely-used knowledge-based models to be inaccurate. Thus, we here propose a general method that leverages the advantages of these two approaches by combining a knowledge-based model and a machine learning technique to build a hybrid forecasting scheme. Potential applications for such an approach are numerous (e.g., improving weather forecasting). We demonstrate and test the utility of this approach using a particular illustrative version of a machine learning known as reservoir computing, and we apply the resulting hybrid forecaster to a low-dimensional chaotic system, as well as to a high-dimensional spatiotemporal chaotic system. These tests yield extremely promising results in that our hybrid technique is able to accurately predict for a much longer period of time than either its machine-learning component or its model-based component alone.

Web-based applications for building, managing and analysing kinetic models of biological systems.

PubMed

Lee, Dong-Yup; Saha, Rajib; Yusufi, Faraaz Noor Khan; Park, Wonjun; Karimi, Iftekhar A

2009-01-01

Mathematical modelling and computational analysis play an essential role in improving our capability to elucidate the functions and characteristics of complex biological systems such as metabolic, regulatory and cell signalling pathways. The modelling and concomitant simulation render it possible to predict the cellular behaviour of systems under various genetically and/or environmentally perturbed conditions. This motivates systems biologists/bioengineers/bioinformaticians to develop new tools and applications, allowing non-experts to easily conduct such modelling and analysis. However, among a multitude of systems biology tools developed to date, only a handful of projects have adopted a web-based approach to kinetic modelling. In this report, we evaluate the capabilities and characteristics of current web-based tools in systems biology and identify desirable features, limitations and bottlenecks for further improvements in terms of usability and functionality. A short discussion on software architecture issues involved in web-based applications and the approaches taken by existing tools is included for those interested in developing their own simulation applications.

Automated knowledge-base refinement

NASA Technical Reports Server (NTRS)

Mooney, Raymond J.

1994-01-01

Over the last several years, we have developed several systems for automatically refining incomplete and incorrect knowledge bases. These systems are given an imperfect rule base and a set of training examples and minimally modify the knowledge base to make it consistent with the examples. One of our most recent systems, FORTE, revises first-order Horn-clause knowledge bases. This system can be viewed as automatically debugging Prolog programs based on examples of correct and incorrect I/O pairs. In fact, we have already used the system to debug simple Prolog programs written by students in a programming language course. FORTE has also been used to automatically induce and revise qualitative models of several continuous dynamic devices from qualitative behavior traces. For example, it has been used to induce and revise a qualitative model of a portion of the Reaction Control System (RCS) of the NASA Space Shuttle. By fitting a correct model of this portion of the RCS to simulated qualitative data from a faulty system, FORTE was also able to correctly diagnose simple faults in this system.

Efficient Embedded Decoding of Neural Network Language Models in a Machine Translation System.

PubMed

Zamora-Martinez, Francisco; Castro-Bleda, Maria Jose

2018-02-22

Neural Network Language Models (NNLMs) are a successful approach to Natural Language Processing tasks, such as Machine Translation. We introduce in this work a Statistical Machine Translation (SMT) system which fully integrates NNLMs in the decoding stage, breaking the traditional approach based on [Formula: see text]-best list rescoring. The neural net models (both language models (LMs) and translation models) are fully coupled in the decoding stage, allowing to more strongly influence the translation quality. Computational issues were solved by using a novel idea based on memorization and smoothing of the softmax constants to avoid their computation, which introduces a trade-off between LM quality and computational cost. These ideas were studied in a machine translation task with different combinations of neural networks used both as translation models and as target LMs, comparing phrase-based and [Formula: see text]-gram-based systems, showing that the integrated approach seems more promising for [Formula: see text]-gram-based systems, even with nonfull-quality NNLMs.

Mathematical modeling and characteristic analysis for over-under turbine based combined cycle engine

NASA Astrophysics Data System (ADS)

Ma, Jingxue; Chang, Juntao; Ma, Jicheng; Bao, Wen; Yu, Daren

2018-07-01

The turbine based combined cycle engine has become the most promising hypersonic airbreathing propulsion system for its superiority of ground self-starting, wide flight envelop and reusability. The simulation model of the turbine based combined cycle engine plays an important role in the research of performance analysis and control system design. In this paper, a turbine based combined cycle engine mathematical model is built on the Simulink platform, including a dual-channel air intake system, a turbojet engine and a ramjet. It should be noted that the model of the air intake system is built based on computational fluid dynamics calculation, which provides valuable raw data for modeling of the turbine based combined cycle engine. The aerodynamic characteristics of turbine based combined cycle engine in turbojet mode, ramjet mode and mode transition process are studied by the mathematical model, and the influence of dominant variables on performance and safety of the turbine based combined cycle engine is analyzed. According to the stability requirement of thrust output and the safety in the working process of turbine based combined cycle engine, a control law is proposed that could guarantee the steady output of thrust by controlling the control variables of the turbine based combined cycle engine in the whole working process.

When Does Model-Based Control Pay Off?

PubMed Central

2016-01-01

Many accounts of decision making and reinforcement learning posit the existence of two distinct systems that control choice: a fast, automatic system and a slow, deliberative system. Recent research formalizes this distinction by mapping these systems to “model-free” and “model-based” strategies in reinforcement learning. Model-free strategies are computationally cheap, but sometimes inaccurate, because action values can be accessed by inspecting a look-up table constructed through trial-and-error. In contrast, model-based strategies compute action values through planning in a causal model of the environment, which is more accurate but also more cognitively demanding. It is assumed that this trade-off between accuracy and computational demand plays an important role in the arbitration between the two strategies, but we show that the hallmark task for dissociating model-free and model-based strategies, as well as several related variants, do not embody such a trade-off. We describe five factors that reduce the effectiveness of the model-based strategy on these tasks by reducing its accuracy in estimating reward outcomes and decreasing the importance of its choices. Based on these observations, we describe a version of the task that formally and empirically obtains an accuracy-demand trade-off between model-free and model-based strategies. Moreover, we show that human participants spontaneously increase their reliance on model-based control on this task, compared to the original paradigm. Our novel task and our computational analyses may prove important in subsequent empirical investigations of how humans balance accuracy and demand. PMID:27564094

An approach to the mathematical modelling of a controlled ecological life support system

NASA Technical Reports Server (NTRS)

Averner, M. M.

1981-01-01

An approach to the design of a computer based model of a closed ecological life-support system suitable for use in extraterrestrial habitats is presented. The model is based on elemental mass balance and contains representations of the metabolic activities of biological components. The model can be used as a tool in evaluating preliminary designs for closed regenerative life support systems and as a method for predicting the behavior of such systems.

Neuman systems model-based research: an integrative review project.

PubMed

Fawcett, J; Giangrande, S K

2001-07-01

The project integrated Neuman systems model-based research literature. Two hundred published studies were located. This article is limited to the 59 full journal articles and 3 book chapters identified. A total of 37% focused on prevention interventions; 21% on perception of stressors; and 10% on stressor reactions. Only 50% of the reports explicitly linked the model with the study variables, and 61% did not include conclusions regarding model utility or credibility. No programs of research were identified. Academic courses and continuing education workshops are needed to help researchers design programs of Neuman systems model-based research and better explicate linkages between the model and the research.

Design of a Model-Based Online Management Information System for Interlibrary Loan Networks.

ERIC Educational Resources Information Center

Rouse, Sandra H.; Rouse, William B.

1979-01-01

Discusses the design of a model-based management information system in terms of mathematical/statistical, information processing, and human factors issues and presents a prototype system for interlibrary loan networks. (Author/CWM)

Test Platforms for Model-Based Flight Research

NASA Astrophysics Data System (ADS)

Dorobantu, Andrei

Demonstrating the reliability of flight control algorithms is critical to integrating unmanned aircraft systems into the civilian airspace. For many potential applications, design and certification of these algorithms will rely heavily on mathematical models of the aircraft dynamics. Therefore, the aerospace community must develop flight test platforms to support the advancement of model-based techniques. The University of Minnesota has developed a test platform dedicated to model-based flight research for unmanned aircraft systems. This thesis provides an overview of the test platform and its research activities in the areas of system identification, model validation, and closed-loop control for small unmanned aircraft.

Self-reconfigurable ship fluid-network modeling for simulation-based design

NASA Astrophysics Data System (ADS)

Moon, Kyungjin

Our world is filled with large-scale engineering systems, which provide various services and conveniences in our daily life. A distinctive trend in the development of today's large-scale engineering systems is the extensive and aggressive adoption of automation and autonomy that enable the significant improvement of systems' robustness, efficiency, and performance, with considerably reduced manning and maintenance costs, and the U.S. Navy's DD(X), the next-generation destroyer program, is considered as an extreme example of such a trend. This thesis pursues a modeling solution for performing simulation-based analysis in the conceptual or preliminary design stage of an intelligent, self-reconfigurable ship fluid system, which is one of the concepts of DD(X) engineering plant development. Through the investigations on the Navy's approach for designing a more survivable ship system, it is found that the current naval simulation-based analysis environment is limited by the capability gaps in damage modeling, dynamic model reconfiguration, and simulation speed of the domain specific models, especially fluid network models. As enablers of filling these gaps, two essential elements were identified in the formulation of the modeling method. The first one is the graph-based topological modeling method, which will be employed for rapid model reconstruction and damage modeling, and the second one is the recurrent neural network-based, component-level surrogate modeling method, which will be used to improve the affordability and efficiency of the modeling and simulation (M&S) computations. The integration of the two methods can deliver computationally efficient, flexible, and automation-friendly M&S which will create an environment for more rigorous damage analysis and exploration of design alternatives. As a demonstration for evaluating the developed method, a simulation model of a notional ship fluid system was created, and a damage analysis was performed. Next, the models representing different design configurations of the fluid system were created, and damage analyses were performed with them in order to find an optimal design configuration for system survivability. Finally, the benefits and drawbacks of the developed method were discussed based on the result of the demonstration.

Separate encoding of model-based and model-free valuations in the human brain.

PubMed

Beierholm, Ulrik R; Anen, Cedric; Quartz, Steven; Bossaerts, Peter

2011-10-01

Behavioral studies have long shown that humans solve problems in two ways, one intuitive and fast (System 1, model-free), and the other reflective and slow (System 2, model-based). The neurobiological basis of dual process problem solving remains unknown due to challenges of separating activation in concurrent systems. We present a novel neuroeconomic task that predicts distinct subjective valuation and updating signals corresponding to these two systems. We found two concurrent value signals in human prefrontal cortex: a System 1 model-free reinforcement signal and a System 2 model-based Bayesian signal. We also found a System 1 updating signal in striatal areas and a System 2 updating signal in lateral prefrontal cortex. Further, signals in prefrontal cortex preceded choices that are optimal according to either updating principle, while signals in anterior cingulate cortex and globus pallidus preceded deviations from optimal choice for reinforcement learning. These deviations tended to occur when uncertainty regarding optimal values was highest, suggesting that disagreement between dual systems is mediated by uncertainty rather than conflict, confirming recent theoretical proposals. Copyright © 2011 Elsevier Inc. All rights reserved.

Towards Symbolic Model Checking for Multi-Agent Systems via OBDDs

NASA Technical Reports Server (NTRS)

Raimondi, Franco; Lomunscio, Alessio

2004-01-01

We present an algorithm for model checking temporal-epistemic properties of multi-agent systems, expressed in the formalism of interpreted systems. We first introduce a technique for the translation of interpreted systems into boolean formulae, and then present a model-checking algorithm based on this translation. The algorithm is based on OBDD's, as they offer a compact and efficient representation for boolean formulae.

Agent-based model for rural-urban migration: A dynamic consideration

NASA Astrophysics Data System (ADS)

Cai, Ning; Ma, Hai-Ying; Khan, M. Junaid

2015-10-01

This paper develops a dynamic agent-based model for rural-urban migration, based on the previous relevant works. The model conforms to the typical dynamic linear multi-agent systems model concerned extensively in systems science, in which the communication network is formulated as a digraph. Simulations reveal that consensus of certain variable could be harmful to the overall stability and should be avoided.

Design of Soil Salinity Policies with Tinamit, a Flexible and Rapid Tool to Couple Stakeholder-Built System Dynamics Models with Physically-Based Models

NASA Astrophysics Data System (ADS)

Malard, J. J.; Baig, A. I.; Hassanzadeh, E.; Adamowski, J. F.; Tuy, H.; Melgar-Quiñonez, H.

2016-12-01

Model coupling is a crucial step to constructing many environmental models, as it allows for the integration of independently-built models representing different system sub-components to simulate the entire system. Model coupling has been of particular interest in combining socioeconomic System Dynamics (SD) models, whose visual interface facilitates their direct use by stakeholders, with more complex physically-based models of the environmental system. However, model coupling processes are often cumbersome and inflexible and require extensive programming knowledge, limiting their potential for continued use by stakeholders in policy design and analysis after the end of the project. Here, we present Tinamit, a flexible Python-based model-coupling software tool whose easy-to-use API and graphical user interface make the coupling of stakeholder-built SD models with physically-based models rapid, flexible and simple for users with limited to no coding knowledge. The flexibility of the system allows end users to modify the SD model as well as the linking variables between the two models themselves with no need for recoding. We use Tinamit to couple a stakeholder-built socioeconomic model of soil salinization in Pakistan with the physically-based soil salinity model SAHYSMOD. As climate extremes increase in the region, policies to slow or reverse soil salinity buildup are increasing in urgency and must take both socioeconomic and biophysical spheres into account. We use the Tinamit-coupled model to test the impact of integrated policy options (economic and regulatory incentives to farmers) on soil salinity in the region in the face of future climate change scenarios. Use of the Tinamit model allowed for rapid and flexible coupling of the two models, allowing the end user to continue making model structure and policy changes. In addition, the clear interface (in contrast to most model coupling code) makes the final coupled model easily accessible to stakeholders with limited technical background.

A methodological approach for using high-level Petri Nets to model the immune system response.

PubMed

Pennisi, Marzio; Cavalieri, Salvatore; Motta, Santo; Pappalardo, Francesco

2016-12-22

Mathematical and computational models showed to be a very important support tool for the comprehension of the immune system response against pathogens. Models and simulations allowed to study the immune system behavior, to test biological hypotheses about diseases and infection dynamics, and to improve and optimize novel and existing drugs and vaccines. Continuous models, mainly based on differential equations, usually allow to qualitatively study the system but lack in description; conversely discrete models, such as agent based models and cellular automata, permit to describe in detail entities properties at the cost of losing most qualitative analyses. Petri Nets (PN) are a graphical modeling tool developed to model concurrency and synchronization in distributed systems. Their use has become increasingly marked also thanks to the introduction in the years of many features and extensions which lead to the born of "high level" PN. We propose a novel methodological approach that is based on high level PN, and in particular on Colored Petri Nets (CPN), that can be used to model the immune system response at the cellular scale. To demonstrate the potentiality of the approach we provide a simple model of the humoral immune system response that is able of reproducing some of the most complex well-known features of the adaptive response like memory and specificity features. The methodology we present has advantages of both the two classical approaches based on continuous and discrete models, since it allows to gain good level of granularity in the description of cells behavior without losing the possibility of having a qualitative analysis. Furthermore, the presented methodology based on CPN allows the adoption of the same graphical modeling technique well known to life scientists that use PN for the modeling of signaling pathways. Finally, such an approach may open the floodgates to the realization of multi scale models that integrate both signaling pathways (intra cellular) models and cellular (population) models built upon the same technique and software.

Abstracting event-based control models for high autonomy systems

NASA Technical Reports Server (NTRS)

Luh, Cheng-Jye; Zeigler, Bernard P.

1993-01-01

A high autonomy system needs many models on which to base control, management, design, and other interventions. These models differ in level of abstraction and in formalism. Concepts and tools are needed to organize the models into a coherent whole. The paper deals with the abstraction processes for systematic derivation of related models for use in event-based control. The multifaceted modeling methodology is briefly reviewed. The morphism concepts needed for application to model abstraction are described. A theory for supporting the construction of DEVS models needed for event-based control is then presented. An implemented morphism on the basis of this theory is also described.

Highway Air Pollution Dispersion Modeling : Preliminary Evaluation of Thirteen Models

DOT National Transportation Integrated Search

1978-06-01

Thirteen highway air pollution dispersion models have been tested, using a portion of the Airedale air quality data base. The Transportation Air Pollution Studies (TAPS) System, a data base management system specifically designed for evaluating dispe...

Highway Air Pollution Dispersion Modeling : Preliminary Evaluation of Thirteen Models

DOT National Transportation Integrated Search

1977-01-01

Thirteen highway air pollution dispersion models have been tested, using a portion of the Airedale air quality data base. The Transportation Air Pollution Studies (TAPS) System, a data base management system specifically designed for evaluating dispe...

Model-Based Verification and Validation of the SMAP Uplink Processes

NASA Technical Reports Server (NTRS)

Khan, M. Omair; Dubos, Gregory F.; Tirona, Joseph; Standley, Shaun

2013-01-01

This case study stands as an example of how a project can validate a system-level design earlier in the project life cycle than traditional V&V processes by using simulation on a system model. Specifically, this paper describes how simulation was added to a system model of the Soil Moisture Active-Passive (SMAP) mission's uplink process.Also discussed are the advantages and disadvantages of the methods employed and the lessons learned; which are intended to benefit future model-based and simulation-based V&V development efforts.

Study of a risk-based piping inspection guideline system.

PubMed

Tien, Shiaw-Wen; Hwang, Wen-Tsung; Tsai, Chih-Hung

2007-02-01

A risk-based inspection system and a piping inspection guideline model were developed in this study. The research procedure consists of two parts--the building of a risk-based inspection model for piping and the construction of a risk-based piping inspection guideline model. Field visits at the plant were conducted to develop the risk-based inspection and strategic analysis system. A knowledge-based model had been built in accordance with international standards and local government regulations, and the rational unified process was applied for reducing the discrepancy in the development of the models. The models had been designed to analyze damage factors, damage models, and potential damage positions of piping in the petrochemical plants. The purpose of this study was to provide inspection-related personnel with the optimal planning tools for piping inspections, hence, to enable effective predictions of potential piping risks and to enhance the better degree of safety in plant operations that the petrochemical industries can be expected to achieve. A risk analysis was conducted on the piping system of a petrochemical plant. The outcome indicated that most of the risks resulted from a small number of pipelines.

ADAM: Analysis of Discrete Models of Biological Systems Using Computer Algebra

PubMed Central

2011-01-01

Background Many biological systems are modeled qualitatively with discrete models, such as probabilistic Boolean networks, logical models, Petri nets, and agent-based models, to gain a better understanding of them. The computational complexity to analyze the complete dynamics of these models grows exponentially in the number of variables, which impedes working with complex models. There exist software tools to analyze discrete models, but they either lack the algorithmic functionality to analyze complex models deterministically or they are inaccessible to many users as they require understanding the underlying algorithm and implementation, do not have a graphical user interface, or are hard to install. Efficient analysis methods that are accessible to modelers and easy to use are needed. Results We propose a method for efficiently identifying attractors and introduce the web-based tool Analysis of Dynamic Algebraic Models (ADAM), which provides this and other analysis methods for discrete models. ADAM converts several discrete model types automatically into polynomial dynamical systems and analyzes their dynamics using tools from computer algebra. Specifically, we propose a method to identify attractors of a discrete model that is equivalent to solving a system of polynomial equations, a long-studied problem in computer algebra. Based on extensive experimentation with both discrete models arising in systems biology and randomly generated networks, we found that the algebraic algorithms presented in this manuscript are fast for systems with the structure maintained by most biological systems, namely sparseness and robustness. For a large set of published complex discrete models, ADAM identified the attractors in less than one second. Conclusions Discrete modeling techniques are a useful tool for analyzing complex biological systems and there is a need in the biological community for accessible efficient analysis tools. ADAM provides analysis methods based on mathematical algorithms as a web-based tool for several different input formats, and it makes analysis of complex models accessible to a larger community, as it is platform independent as a web-service and does not require understanding of the underlying mathematics. PMID:21774817

An OpenACC-Based Unified Programming Model for Multi-accelerator Systems

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

Kim, Jungwon; Lee, Seyong; Vetter, Jeffrey S

2015-01-01

This paper proposes a novel SPMD programming model of OpenACC. Our model integrates the different granularities of parallelism from vector-level parallelism to node-level parallelism into a single, unified model based on OpenACC. It allows programmers to write programs for multiple accelerators using a uniform programming model whether they are in shared or distributed memory systems. We implement a prototype of our model and evaluate its performance with a GPU-based supercomputer using three benchmark applications.

Hierarchical modeling and inference in ecology: The analysis of data from populations, metapopulations and communities

USGS Publications Warehouse

Royle, J. Andrew; Dorazio, Robert M.

2008-01-01

A guide to data collection, modeling and inference strategies for biological survey data using Bayesian and classical statistical methods. This book describes a general and flexible framework for modeling and inference in ecological systems based on hierarchical models, with a strict focus on the use of probability models and parametric inference. Hierarchical models represent a paradigm shift in the application of statistics to ecological inference problems because they combine explicit models of ecological system structure or dynamics with models of how ecological systems are observed. The principles of hierarchical modeling are developed and applied to problems in population, metapopulation, community, and metacommunity systems. The book provides the first synthetic treatment of many recent methodological advances in ecological modeling and unifies disparate methods and procedures. The authors apply principles of hierarchical modeling to ecological problems, including * occurrence or occupancy models for estimating species distribution * abundance models based on many sampling protocols, including distance sampling * capture-recapture models with individual effects * spatial capture-recapture models based on camera trapping and related methods * population and metapopulation dynamic models * models of biodiversity, community structure and dynamics.

Architectural approaches for HL7-based health information systems implementation.

PubMed

López, D M; Blobel, B

2010-01-01

Information systems integration is hard, especially when semantic and business process interoperability requirements need to be met. To succeed, a unified methodology, approaching different aspects of systems architecture such as business, information, computational, engineering and technology viewpoints, has to be considered. The paper contributes with an analysis and demonstration on how the HL7 standard set can support health information systems integration. Based on the Health Information Systems Development Framework (HIS-DF), common architectural models for HIS integration are analyzed. The framework is a standard-based, consistent, comprehensive, customizable, scalable methodology that supports the design of semantically interoperable health information systems and components. Three main architectural models for system integration are analyzed: the point to point interface, the messages server and the mediator models. Point to point interface and messages server models are completely supported by traditional HL7 version 2 and version 3 messaging. The HL7 v3 standard specification, combined with service-oriented, model-driven approaches provided by HIS-DF, makes the mediator model possible. The different integration scenarios are illustrated by describing a proof-of-concept implementation of an integrated public health surveillance system based on Enterprise Java Beans technology. Selecting the appropriate integration architecture is a fundamental issue of any software development project. HIS-DF provides a unique methodological approach guiding the development of healthcare integration projects. The mediator model - offered by the HIS-DF and supported in HL7 v3 artifacts - is the more promising one promoting the development of open, reusable, flexible, semantically interoperable, platform-independent, service-oriented and standard-based health information systems.

Reliability analysis in interdependent smart grid systems

NASA Astrophysics Data System (ADS)

Peng, Hao; Kan, Zhe; Zhao, Dandan; Han, Jianmin; Lu, Jianfeng; Hu, Zhaolong

2018-06-01

Complex network theory is a useful way to study many real complex systems. In this paper, a reliability analysis model based on complex network theory is introduced in interdependent smart grid systems. In this paper, we focus on understanding the structure of smart grid systems and studying the underlying network model, their interactions, and relationships and how cascading failures occur in the interdependent smart grid systems. We propose a practical model for interdependent smart grid systems using complex theory. Besides, based on percolation theory, we also study the effect of cascading failures effect and reveal detailed mathematical analysis of failure propagation in such systems. We analyze the reliability of our proposed model caused by random attacks or failures by calculating the size of giant functioning components in interdependent smart grid systems. Our simulation results also show that there exists a threshold for the proportion of faulty nodes, beyond which the smart grid systems collapse. Also we determine the critical values for different system parameters. In this way, the reliability analysis model based on complex network theory can be effectively utilized for anti-attack and protection purposes in interdependent smart grid systems.

Cost-Benefit Arbitration Between Multiple Reinforcement-Learning Systems.

PubMed

Kool, Wouter; Gershman, Samuel J; Cushman, Fiery A

2017-09-01

Human behavior is sometimes determined by habit and other times by goal-directed planning. Modern reinforcement-learning theories formalize this distinction as a competition between a computationally cheap but inaccurate model-free system that gives rise to habits and a computationally expensive but accurate model-based system that implements planning. It is unclear, however, how people choose to allocate control between these systems. Here, we propose that arbitration occurs by comparing each system's task-specific costs and benefits. To investigate this proposal, we conducted two experiments showing that people increase model-based control when it achieves greater accuracy than model-free control, and especially when the rewards of accurate performance are amplified. In contrast, they are insensitive to reward amplification when model-based and model-free control yield equivalent accuracy. This suggests that humans adaptively balance habitual and planned action through on-line cost-benefit analysis.

Two degree of freedom internal model control-PID design for LFC of power systems via logarithmic approximations.

PubMed

Singh, Jay; Chattterjee, Kalyan; Vishwakarma, C B

2018-01-01

Load frequency controller has been designed for reduced order model of single area and two-area reheat hydro-thermal power system through internal model control - proportional integral derivative (IMC-PID) control techniques. The controller design method is based on two degree of freedom (2DOF) internal model control which combines with model order reduction technique. Here, in spite of taking full order system model a reduced order model has been considered for 2DOF-IMC-PID design and the designed controller is directly applied to full order system model. The Logarithmic based model order reduction technique is proposed to reduce the single and two-area high order power systems for the application of controller design.The proposed IMC-PID design of reduced order model achieves good dynamic response and robustness against load disturbance with the original high order system. Copyright © 2018 ISA. Published by Elsevier Ltd. All rights reserved.

Photovoltaic Grid-Connected Modeling and Characterization Based on Experimental Results.

PubMed

Humada, Ali M; Hojabri, Mojgan; Sulaiman, Mohd Herwan Bin; Hamada, Hussein M; Ahmed, Mushtaq N

2016-01-01

A grid-connected photovoltaic (PV) system operates under fluctuated weather condition has been modeled and characterized based on specific test bed. A mathematical model of a small-scale PV system has been developed mainly for residential usage, and the potential results have been simulated. The proposed PV model based on three PV parameters, which are the photocurrent, IL, the reverse diode saturation current, Io, the ideality factor of diode, n. Accuracy of the proposed model and its parameters evaluated based on different benchmarks. The results showed that the proposed model fitting the experimental results with high accuracy compare to the other models, as well as the I-V characteristic curve. The results of this study can be considered valuable in terms of the installation of a grid-connected PV system in fluctuated climatic conditions.

Photovoltaic Grid-Connected Modeling and Characterization Based on Experimental Results

PubMed Central

Humada, Ali M.; Hojabri, Mojgan; Sulaiman, Mohd Herwan Bin; Hamada, Hussein M.; Ahmed, Mushtaq N.

2016-01-01

A grid-connected photovoltaic (PV) system operates under fluctuated weather condition has been modeled and characterized based on specific test bed. A mathematical model of a small-scale PV system has been developed mainly for residential usage, and the potential results have been simulated. The proposed PV model based on three PV parameters, which are the photocurrent, IL, the reverse diode saturation current, Io, the ideality factor of diode, n. Accuracy of the proposed model and its parameters evaluated based on different benchmarks. The results showed that the proposed model fitting the experimental results with high accuracy compare to the other models, as well as the I-V characteristic curve. The results of this study can be considered valuable in terms of the installation of a grid-connected PV system in fluctuated climatic conditions. PMID:27035575

Design and Implementation of C-iLearning: A Cloud-Based Intelligent Learning System

ERIC Educational Resources Information Center

Xiao, Jun; Wang, Minjuan; Wang, Lamei; Zhu, Xiaoxiao

2013-01-01

The gradual development of intelligent learning (iLearning) systems has prompted the changes of teaching and learning. This paper presents the architecture of an intelligent learning (iLearning) system built upon the recursive iLearning model and the key technologies associated with this model. Based on this model and the technical structure of a…

Uncertainty Analysis of Coupled Socioeconomic-Cropping Models: Building Confidence in Climate Change Decision-Support Tools for Local Stakeholders

NASA Astrophysics Data System (ADS)

Malard, J. J.; Rojas, M.; Adamowski, J. F.; Gálvez, J.; Tuy, H. A.; Melgar-Quiñonez, H.

2015-12-01

While cropping models represent the biophysical aspects of agricultural systems, system dynamics modelling offers the possibility of representing the socioeconomic (including social and cultural) aspects of these systems. The two types of models can then be coupled in order to include the socioeconomic dimensions of climate change adaptation in the predictions of cropping models.We develop a dynamically coupled socioeconomic-biophysical model of agricultural production and its repercussions on food security in two case studies from Guatemala (a market-based, intensive agricultural system and a low-input, subsistence crop-based system). Through the specification of the climate inputs to the cropping model, the impacts of climate change on the entire system can be analysed, and the participatory nature of the system dynamics model-building process, in which stakeholders from NGOs to local governmental extension workers were included, helps ensure local trust in and use of the model.However, the analysis of climate variability's impacts on agroecosystems includes uncertainty, especially in the case of joint physical-socioeconomic modelling, and the explicit representation of this uncertainty in the participatory development of the models is important to ensure appropriate use of the models by the end users. In addition, standard model calibration, validation, and uncertainty interval estimation techniques used for physically-based models are impractical in the case of socioeconomic modelling. We present a methodology for the calibration and uncertainty analysis of coupled biophysical (cropping) and system dynamics (socioeconomic) agricultural models, using survey data and expert input to calibrate and evaluate the uncertainty of the system dynamics as well as of the overall coupled model. This approach offers an important tool for local decision makers to evaluate the potential impacts of climate change and their feedbacks through the associated socioeconomic system.

Evaluating Emulation-based Models of Distributed Computing Systems

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

Jones, Stephen T.; Gabert, Kasimir G.; Tarman, Thomas D.

Emulation-based models of distributed computing systems are collections of virtual ma- chines, virtual networks, and other emulation components configured to stand in for oper- ational systems when performing experimental science, training, analysis of design alterna- tives, test and evaluation, or idea generation. As with any tool, we should carefully evaluate whether our uses of emulation-based models are appropriate and justified. Otherwise, we run the risk of using a model incorrectly and creating meaningless results. The variety of uses of emulation-based models each have their own goals and deserve thoughtful evaluation. In this paper, we enumerate some of these uses andmore » describe approaches that one can take to build an evidence-based case that a use of an emulation-based model is credible. Predictive uses of emulation-based models, where we expect a model to tell us something true about the real world, set the bar especially high and the principal evaluation method, called validation , is comensurately rigorous. We spend the majority of our time describing and demonstrating the validation of a simple predictive model using a well-established methodology inherited from decades of development in the compuational science and engineering community.« less

Computational Modeling of Human Metabolism and Its Application to Systems Biomedicine.

PubMed

Aurich, Maike K; Thiele, Ines

2016-01-01

Modern high-throughput techniques offer immense opportunities to investigate whole-systems behavior, such as those underlying human diseases. However, the complexity of the data presents challenges in interpretation, and new avenues are needed to address the complexity of both diseases and data. Constraint-based modeling is one formalism applied in systems biology. It relies on a genome-scale reconstruction that captures extensive biochemical knowledge regarding an organism. The human genome-scale metabolic reconstruction is increasingly used to understand normal cellular and disease states because metabolism is an important factor in many human diseases. The application of human genome-scale reconstruction ranges from mere querying of the model as a knowledge base to studies that take advantage of the model's topology and, most notably, to functional predictions based on cell- and condition-specific metabolic models built based on omics data.An increasing number and diversity of biomedical questions are being addressed using constraint-based modeling and metabolic models. One of the most successful biomedical applications to date is cancer metabolism, but constraint-based modeling also holds great potential for inborn errors of metabolism or obesity. In addition, it offers great prospects for individualized approaches to diagnostics and the design of disease prevention and intervention strategies. Metabolic models support this endeavor by providing easy access to complex high-throughput datasets. Personalized metabolic models have been introduced. Finally, constraint-based modeling can be used to model whole-body metabolism, which will enable the elucidation of metabolic interactions between organs and disturbances of these interactions as either causes or consequence of metabolic diseases. This chapter introduces constraint-based modeling and describes some of its contributions to systems biomedicine.

Model compilation: An approach to automated model derivation

NASA Technical Reports Server (NTRS)

Keller, Richard M.; Baudin, Catherine; Iwasaki, Yumi; Nayak, Pandurang; Tanaka, Kazuo

1990-01-01

An approach is introduced to automated model derivation for knowledge based systems. The approach, model compilation, involves procedurally generating the set of domain models used by a knowledge based system. With an implemented example, how this approach can be used to derive models of different precision and abstraction is illustrated, and models are tailored to different tasks, from a given set of base domain models. In particular, two implemented model compilers are described, each of which takes as input a base model that describes the structure and behavior of a simple electromechanical device, the Reaction Wheel Assembly of NASA's Hubble Space Telescope. The compilers transform this relatively general base model into simple task specific models for troubleshooting and redesign, respectively, by applying a sequence of model transformations. Each transformation in this sequence produces an increasingly more specialized model. The compilation approach lessens the burden of updating and maintaining consistency among models by enabling their automatic regeneration.

An Agent-Based Model for Analyzing Control Policies and the Dynamic Service-Time Performance of a Capacity-Constrained Air Traffic Management Facility

NASA Technical Reports Server (NTRS)

Conway, Sheila R.

2006-01-01

Simple agent-based models may be useful for investigating air traffic control strategies as a precursory screening for more costly, higher fidelity simulation. Of concern is the ability of the models to capture the essence of the system and provide insight into system behavior in a timely manner and without breaking the bank. The method is put to the test with the development of a model to address situations where capacity is overburdened and potential for propagation of the resultant delay though later flights is possible via flight dependencies. The resultant model includes primitive representations of principal air traffic system attributes, namely system capacity, demand, airline schedules and strategy, and aircraft capability. It affords a venue to explore their interdependence in a time-dependent, dynamic system simulation. The scope of the research question and the carefully-chosen modeling fidelity did allow for the development of an agent-based model in short order. The model predicted non-linear behavior given certain initial conditions and system control strategies. Additionally, a combination of the model and dimensionless techniques borrowed from fluid systems was demonstrated that can predict the system s dynamic behavior across a wide range of parametric settings.

Modeling and Fault Simulation of Propellant Filling System

NASA Astrophysics Data System (ADS)

Jiang, Yunchun; Liu, Weidong; Hou, Xiaobo

2012-05-01

Propellant filling system is one of the key ground plants in launching site of rocket that use liquid propellant. There is an urgent demand for ensuring and improving its reliability and safety, and there is no doubt that Failure Mode Effect Analysis (FMEA) is a good approach to meet it. Driven by the request to get more fault information for FMEA, and because of the high expense of propellant filling, in this paper, the working process of the propellant filling system in fault condition was studied by simulating based on AMESim. Firstly, based on analyzing its structure and function, the filling system was modular decomposed, and the mathematic models of every module were given, based on which the whole filling system was modeled in AMESim. Secondly, a general method of fault injecting into dynamic system was proposed, and as an example, two typical faults - leakage and blockage - were injected into the model of filling system, based on which one can get two fault models in AMESim. After that, fault simulation was processed and the dynamic characteristics of several key parameters were analyzed under fault conditions. The results show that the model can simulate effectively the two faults, and can be used to provide guidance for the filling system maintain and amelioration.

Modelling hourly dissolved oxygen concentration (DO) using dynamic evolving neural-fuzzy inference system (DENFIS)-based approach: case study of Klamath River at Miller Island Boat Ramp, OR, USA.

PubMed

Heddam, Salim

2014-01-01

In this study, we present application of an artificial intelligence (AI) technique model called dynamic evolving neural-fuzzy inference system (DENFIS) based on an evolving clustering method (ECM), for modelling dissolved oxygen concentration in a river. To demonstrate the forecasting capability of DENFIS, a one year period from 1 January 2009 to 30 December 2009, of hourly experimental water quality data collected by the United States Geological Survey (USGS Station No: 420853121505500) station at Klamath River at Miller Island Boat Ramp, OR, USA, were used for model development. Two DENFIS-based models are presented and compared. The two DENFIS systems are: (1) offline-based system named DENFIS-OF, and (2) online-based system, named DENFIS-ON. The input variables used for the two models are water pH, temperature, specific conductance, and sensor depth. The performances of the models are evaluated using root mean square errors (RMSE), mean absolute error (MAE), Willmott index of agreement (d) and correlation coefficient (CC) statistics. The lowest root mean square error and highest correlation coefficient values were obtained with the DENFIS-ON method. The results obtained with DENFIS models are compared with linear (multiple linear regression, MLR) and nonlinear (multi-layer perceptron neural networks, MLPNN) methods. This study demonstrates that DENFIS-ON investigated herein outperforms all the proposed techniques for DO modelling.

An Interactive, Web-based High Performance Modeling Environment for Computational Epidemiology.

PubMed

Deodhar, Suruchi; Bisset, Keith R; Chen, Jiangzhuo; Ma, Yifei; Marathe, Madhav V

2014-07-01

We present an integrated interactive modeling environment to support public health epidemiology. The environment combines a high resolution individual-based model with a user-friendly web-based interface that allows analysts to access the models and the analytics back-end remotely from a desktop or a mobile device. The environment is based on a loosely-coupled service-oriented-architecture that allows analysts to explore various counter factual scenarios. As the modeling tools for public health epidemiology are getting more sophisticated, it is becoming increasingly hard for non-computational scientists to effectively use the systems that incorporate such models. Thus an important design consideration for an integrated modeling environment is to improve ease of use such that experimental simulations can be driven by the users. This is achieved by designing intuitive and user-friendly interfaces that allow users to design and analyze a computational experiment and steer the experiment based on the state of the system. A key feature of a system that supports this design goal is the ability to start, stop, pause and roll-back the disease propagation and intervention application process interactively. An analyst can access the state of the system at any point in time and formulate dynamic interventions based on additional information obtained through state assessment. In addition, the environment provides automated services for experiment set-up and management, thus reducing the overall time for conducting end-to-end experimental studies. We illustrate the applicability of the system by describing computational experiments based on realistic pandemic planning scenarios. The experiments are designed to demonstrate the system's capability and enhanced user productivity.

An Interactive, Web-based High Performance Modeling Environment for Computational Epidemiology

PubMed Central

Deodhar, Suruchi; Bisset, Keith R.; Chen, Jiangzhuo; Ma, Yifei; Marathe, Madhav V.

2014-01-01

We present an integrated interactive modeling environment to support public health epidemiology. The environment combines a high resolution individual-based model with a user-friendly web-based interface that allows analysts to access the models and the analytics back-end remotely from a desktop or a mobile device. The environment is based on a loosely-coupled service-oriented-architecture that allows analysts to explore various counter factual scenarios. As the modeling tools for public health epidemiology are getting more sophisticated, it is becoming increasingly hard for non-computational scientists to effectively use the systems that incorporate such models. Thus an important design consideration for an integrated modeling environment is to improve ease of use such that experimental simulations can be driven by the users. This is achieved by designing intuitive and user-friendly interfaces that allow users to design and analyze a computational experiment and steer the experiment based on the state of the system. A key feature of a system that supports this design goal is the ability to start, stop, pause and roll-back the disease propagation and intervention application process interactively. An analyst can access the state of the system at any point in time and formulate dynamic interventions based on additional information obtained through state assessment. In addition, the environment provides automated services for experiment set-up and management, thus reducing the overall time for conducting end-to-end experimental studies. We illustrate the applicability of the system by describing computational experiments based on realistic pandemic planning scenarios. The experiments are designed to demonstrate the system's capability and enhanced user productivity. PMID:25530914

Modular Architecture for Integrated Model-Based Decision Support.

PubMed

Gaebel, Jan; Schreiber, Erik; Oeser, Alexander; Oeltze-Jafra, Steffen

2018-01-01

Model-based decision support systems promise to be a valuable addition to oncological treatments and the implementation of personalized therapies. For the integration and sharing of decision models, the involved systems must be able to communicate with each other. In this paper, we propose a modularized architecture of dedicated systems for the integration of probabilistic decision models into existing hospital environments. These systems interconnect via web services and provide model sharing and processing capabilities for clinical information systems. Along the lines of IHE integration profiles from other disciplines and the meaningful reuse of routinely recorded patient data, our approach aims for the seamless integration of decision models into hospital infrastructure and the physicians' daily work.

A novel AIDS/HIV intelligent medical consulting system based on expert systems

PubMed Central

Ebrahimi, Alireza Pour; Toloui Ashlaghi, Abbas; Mahdavy Rad, Maryam

2013-01-01

Background: The purpose of this paper is to propose a novel intelligent model for AIDS/HIV data based on expert system and using it for developing an intelligent medical consulting system for AIDS/HIV. Materials and Methods: In this descriptive research, 752 frequently asked questions (FAQs) about AIDS/HIV are gathered from numerous websites about this disease. To perform the data mining and extracting the intelligent model, the 6 stages of Crisp method has been completed for FAQs. The 6 stages include: Business understanding, data understanding, data preparation, modelling, evaluation and deployment. C5.0 Tree classification algorithm is used for modelling. Also, rational unified process (RUP) is used to develop the web-based medical consulting software. Stages of RUP are as follows: Inception, elaboration, construction and transition. The intelligent developed model has been used in the infrastructure of the software and based on client's inquiry and keywords related FAQs are displayed to the client, according to the rank. FAQs’ ranks are gradually determined considering clients reading it. Based on displayed FAQs, test and entertainment links are also displayed. Result: The accuracy of the AIDS/HIV intelligent web-based medical consulting system is estimated to be 78.76%. Conclusion: AIDS/HIV medical consulting systems have been developed using intelligent infrastructure. Being equipped with an intelligent model, providing consulting services on systematic textual data and providing side services based on client's activities causes the implemented system to be unique. The research has been approved by Iranian Ministry of Health and Medical Education for being practical. PMID:24251290

EMPIRE and pyenda: Two ensemble-based data assimilation systems written in Fortran and Python

NASA Astrophysics Data System (ADS)

Geppert, Gernot; Browne, Phil; van Leeuwen, Peter Jan; Merker, Claire

2017-04-01

We present and compare the features of two ensemble-based data assimilation frameworks, EMPIRE and pyenda. Both frameworks allow to couple models to the assimilation codes using the Message Passing Interface (MPI), leading to extremely efficient and fast coupling between models and the data-assimilation codes. The Fortran-based system EMPIRE (Employing Message Passing Interface for Researching Ensembles) is optimized for parallel, high-performance computing. It currently includes a suite of data assimilation algorithms including variants of the ensemble Kalman and several the particle filters. EMPIRE is targeted at models of all kinds of complexity and has been coupled to several geoscience models, eg. the Lorenz-63 model, a barotropic vorticity model, the general circulation model HadCM3, the ocean model NEMO, and the land-surface model JULES. The Python-based system pyenda (Python Ensemble Data Assimilation) allows Fortran- and Python-based models to be used for data assimilation. Models can be coupled either using MPI or by using a Python interface. Using Python allows quick prototyping and pyenda is aimed at small to medium scale models. pyenda currently includes variants of the ensemble Kalman filter and has been coupled to the Lorenz-63 model, an advection-based precipitation nowcasting scheme, and the dynamic global vegetation model JSBACH.

Reliability modeling of fault-tolerant computer based systems

NASA Technical Reports Server (NTRS)

Bavuso, Salvatore J.

1987-01-01

Digital fault-tolerant computer-based systems have become commonplace in military and commercial avionics. These systems hold the promise of increased availability, reliability, and maintainability over conventional analog-based systems through the application of replicated digital computers arranged in fault-tolerant configurations. Three tightly coupled factors of paramount importance, ultimately determining the viability of these systems, are reliability, safety, and profitability. Reliability, the major driver affects virtually every aspect of design, packaging, and field operations, and eventually produces profit for commercial applications or increased national security. However, the utilization of digital computer systems makes the task of producing credible reliability assessment a formidable one for the reliability engineer. The root of the problem lies in the digital computer's unique adaptability to changing requirements, computational power, and ability to test itself efficiently. Addressed here are the nuances of modeling the reliability of systems with large state sizes, in the Markov sense, which result from systems based on replicated redundant hardware and to discuss the modeling of factors which can reduce reliability without concomitant depletion of hardware. Advanced fault-handling models are described and methods of acquiring and measuring parameters for these models are delineated.

An accurate nonlinear stochastic model for MEMS-based inertial sensor error with wavelet networks

NASA Astrophysics Data System (ADS)

El-Diasty, Mohammed; El-Rabbany, Ahmed; Pagiatakis, Spiros

2007-12-01

The integration of Global Positioning System (GPS) with Inertial Navigation System (INS) has been widely used in many applications for positioning and orientation purposes. Traditionally, random walk (RW), Gauss-Markov (GM), and autoregressive (AR) processes have been used to develop the stochastic model in classical Kalman filters. The main disadvantage of classical Kalman filter is the potentially unstable linearization of the nonlinear dynamic system. Consequently, a nonlinear stochastic model is not optimal in derivative-based filters due to the expected linearization error. With a derivativeless-based filter such as the unscented Kalman filter or the divided difference filter, the filtering process of a complicated highly nonlinear dynamic system is possible without linearization error. This paper develops a novel nonlinear stochastic model for inertial sensor error using a wavelet network (WN). A wavelet network is a highly nonlinear model, which has recently been introduced as a powerful tool for modelling and prediction. Static and kinematic data sets are collected using a MEMS-based IMU (DQI-100) to develop the stochastic model in the static mode and then implement it in the kinematic mode. The derivativeless-based filtering method using GM, AR, and the proposed WN-based processes are used to validate the new model. It is shown that the first-order WN-based nonlinear stochastic model gives superior positioning results to the first-order GM and AR models with an overall improvement of 30% when 30 and 60 seconds GPS outages are introduced.

Development of fish-based model systems with various microstructures.

PubMed

Verheyen, Davy; Baka, Maria; Glorieux, Seline; Duquenne, Barbara; Fraeye, Ilse; Skåra, Torstein; Van Impe, Jan F

2018-04-01

The effectiveness of predictive microbiology is limited by the lack of knowledge concerning the influence of food microstructure on microbial dynamics. Therefore, future modelling attempts should be based on experiments in structured food model systems as well as liquid systems. In this study, fish-based model systems with various microstructures were developed, i.e., two liquid systems (with and without xanthan gum), an emulsion, an aqueous gel, and a gelled emulsion. The microstructural effect was isolated by minimising compositional and physico-chemical changes among the different model systems. The systems were suitable for common growth and mild thermal inactivation experiments involving both homogeneous and surface inoculation. Average pH of the model systems was 6.36±0.03 and average a w was 0.988±0.002. The liquid system without xanthan gum behaved like a Newtonian fluid, while the emulsion and the liquid containing xanthan gum exhibited (non-Newtonian) pseudo-plastic behaviour. Both the aqueous gel and gelled emulsion were classified as strong gels, with a hardness of 1.35±0.07N and 1.25±0.05N, respectively. Fat droplet size of the emulsion and gelled emulsion model systems was evenly distributed around 1μm. In general, the set of model systems was proven to be suitable to study the influence of important aspects of food microstructure on microbial dynamics. Copyright © 2017. Published by Elsevier Ltd.

Integrated Main Propulsion System Performance Reconstruction Process/Models

NASA Technical Reports Server (NTRS)

Lopez, Eduardo; Elliott, Katie; Snell, Steven; Evans, Michael

2013-01-01

The Integrated Main Propulsion System (MPS) Performance Reconstruction process provides the MPS post-flight data files needed for postflight reporting to the project integration management and key customers to verify flight performance. This process/model was used as the baseline for the currently ongoing Space Launch System (SLS) work. The process utilizes several methodologies, including multiple software programs, to model integrated propulsion system performance through space shuttle ascent. It is used to evaluate integrated propulsion systems, including propellant tanks, feed systems, rocket engine, and pressurization systems performance throughout ascent based on flight pressure and temperature data. The latest revision incorporates new methods based on main engine power balance model updates to model higher mixture ratio operation at lower engine power levels.

Access Control for Cooperation Systems Based on Group Situation

NASA Astrophysics Data System (ADS)

Kim, Minsoo; Joshi, James B. D.; Kim, Minkoo

Cooperation systems characterize many emerging environments such as ubiquitous and pervasive systems. Agent based cooperation systems have been proposed in the literature to address challenges of such emerging application environments. A key aspect of such agent based cooperation system is the group situation that changes dynamically and governs the requirements of the cooperation. While individual agent context is important, the overall cooperation behavior is more driven by the group context because of relationships and interactions between agents. Dynamic access control based on group situation is a crucial challenge in such cooperation systems. In this paper we propose a dynamic role based access control model for cooperation systems based on group situation. The model emphasizes capability based agent to role mapping and group situation based permission assignment to allow capturing dynamic access policies that evolve continuously.

MTK: An AI tool for model-based reasoning

NASA Technical Reports Server (NTRS)

Erickson, William K.; Rudokas, Mary R.

1988-01-01

A 1988 goal for the Systems Autonomy Demonstration Project Office of the NASA Ames Research Office is to apply model-based representation and reasoning techniques in a knowledge-based system that will provide monitoring, fault diagnosis, control, and trend analysis of the Space Station Thermal Control System (TCS). A number of issues raised during the development of the first prototype system inspired the design and construction of a model-based reasoning tool called MTK, which was used in the building of the second prototype. These issues are outlined here with examples from the thermal system to highlight the motivating factors behind them, followed by an overview of the capabilities of MTK, which was developed to address these issues in a generic fashion.

Comparing administered and market-based water allocation systems using an agent-based modeling approach

NASA Astrophysics Data System (ADS)

Zhao, J.; Cai, X.; Wang, Z.

2009-12-01

It also has been well recognized that market-based systems can have significant advantages over administered systems for water allocation. However there are not many successful water markets around the world yet and administered systems exist commonly in water allocation management practice. This paradox has been under discussion for decades and still calls for attention for both research and practice. This paper explores some insights for the paradox and tries to address why market systems have not been widely implemented for water allocation. Adopting the theory of agent-based system we develop a consistent analytical model to interpret both systems. First we derive some theorems based on the analytical model, with respect to the necessary conditions for economic efficiency of water allocation. Following that the agent-based model is used to illustrate the coherence and difference between administered and market-based systems. The two systems are compared from three aspects: 1) the driving forces acting on the system state, 2) system efficiency, and 3) equity. Regarding economic efficiency, penalty on the violation of water use permits (or rights) under an administered system can lead to system-wide economic efficiency, as well as being acceptable by some agents, which follows the theory of the so-call rational violation. Ideal equity will be realized if penalty equals incentive with an administered system and if transaction costs are zero with a market system. The performances of both agents and the over system are explained with an administered system and market system, respectively. The performances of agents are subject to different mechanisms of interactions between agents under the two systems. The system emergency (i.e., system benefit, equilibrium market price, etc), resulting from the performance at the agent level, reflects the different mechanism of the two systems, the “invisible hand” with the market system and administrative measures (penalty and subsidy) with the administered system. Furthermore, the impact of hydrological uncertainty on the performance of water users under the two systems is analyzed by extending the deterministic model to a stochastic one subject to the uncertainty of water availability. It is found that the system response to hydrologic uncertainty depends on risk management mechanics - sharing risk equally among the agents or by prescribed priorities on some agents. Figure1. Agent formulation and its implications in administered system and market-based system

Using Agent Base Models to Optimize Large Scale Network for Large System Inventories

NASA Technical Reports Server (NTRS)

Shameldin, Ramez Ahmed; Bowling, Shannon R.

2010-01-01

The aim of this paper is to use Agent Base Models (ABM) to optimize large scale network handling capabilities for large system inventories and to implement strategies for the purpose of reducing capital expenses. The models used in this paper either use computational algorithms or procedure implementations developed by Matlab to simulate agent based models in a principal programming language and mathematical theory using clusters, these clusters work as a high performance computational performance to run the program in parallel computational. In both cases, a model is defined as compilation of a set of structures and processes assumed to underlie the behavior of a network system.

Propagation Effects in Space-Based Surveillance Systems

DTIC Science & Technology

1982-02-01

This report describes the first year’s effort to investigate propagation effects in space - based radars. A model was developed for analyzing the...deleterious systems effects by first developing a generalized aperture distribution that ultimately can be applied to any space - based radar configuration...The propagation effects are characterized in terms of the SATCOM model striation parameters. The form of a generalized channel model for space - based radars

Modeling the long-term evolution of space debris

DOEpatents

Nikolaev, Sergei; De Vries, Willem H.; Henderson, John R.; Horsley, Matthew A.; Jiang, Ming; Levatin, Joanne L.; Olivier, Scot S.; Pertica, Alexander J.; Phillion, Donald W.; Springer, Harry K.

2017-03-07

A space object modeling system that models the evolution of space debris is provided. The modeling system simulates interaction of space objects at simulation times throughout a simulation period. The modeling system includes a propagator that calculates the position of each object at each simulation time based on orbital parameters. The modeling system also includes a collision detector that, for each pair of objects at each simulation time, performs a collision analysis. When the distance between objects satisfies a conjunction criterion, the modeling system calculates a local minimum distance between the pair of objects based on a curve fitting to identify a time of closest approach at the simulation times and calculating the position of the objects at the identified time. When the local minimum distance satisfies a collision criterion, the modeling system models the debris created by the collision of the pair of objects.

Automated Decomposition of Model-based Learning Problems

NASA Technical Reports Server (NTRS)

Williams, Brian C.; Millar, Bill

1996-01-01

A new generation of sensor rich, massively distributed autonomous systems is being developed that has the potential for unprecedented performance, such as smart buildings, reconfigurable factories, adaptive traffic systems and remote earth ecosystem monitoring. To achieve high performance these massive systems will need to accurately model themselves and their environment from sensor information. Accomplishing this on a grand scale requires automating the art of large-scale modeling. This paper presents a formalization of [\\em decompositional model-based learning (DML)], a method developed by observing a modeler's expertise at decomposing large scale model estimation tasks. The method exploits a striking analogy between learning and consistency-based diagnosis. Moriarty, an implementation of DML, has been applied to thermal modeling of a smart building, demonstrating a significant improvement in learning rate.

Distributed, cooperating knowledge-based systems

NASA Technical Reports Server (NTRS)

Truszkowski, Walt

1991-01-01

Some current research in the development and application of distributed, cooperating knowledge-based systems technology is addressed. The focus of the current research is the spacecraft ground operations environment. The underlying hypothesis is that, because of the increasing size, complexity, and cost of planned systems, conventional procedural approaches to the architecture of automated systems will give way to a more comprehensive knowledge-based approach. A hallmark of these future systems will be the integration of multiple knowledge-based agents which understand the operational goals of the system and cooperate with each other and the humans in the loop to attain the goals. The current work includes the development of a reference model for knowledge-base management, the development of a formal model of cooperating knowledge-based agents, the use of testbed for prototyping and evaluating various knowledge-based concepts, and beginning work on the establishment of an object-oriented model of an intelligent end-to-end (spacecraft to user) system. An introductory discussion of these activities is presented, the major concepts and principles being investigated are highlighted, and their potential use in other application domains is indicated.

Practical Application of Model-based Programming and State-based Architecture to Space Missions

NASA Technical Reports Server (NTRS)

Horvath, Gregory A.; Ingham, Michel D.; Chung, Seung; Martin, Oliver; Williams, Brian

2006-01-01

Innovative systems and software engineering solutions are required to meet the increasingly challenging demands of deep-space robotic missions. While recent advances in the development of an integrated systems and software engineering approach have begun to address some of these issues, they are still at the core highly manual and, therefore, error-prone. This paper describes a task aimed at infusing MIT's model-based executive, Titan, into JPL's Mission Data System (MDS), a unified state-based architecture, systems engineering process, and supporting software framework. Results of the task are presented, including a discussion of the benefits and challenges associated with integrating mature model-based programming techniques and technologies into a rigorously-defined domain specific architecture.

Task Delegation Based Access Control Models for Workflow Systems

NASA Astrophysics Data System (ADS)

Gaaloul, Khaled; Charoy, François

e-Government organisations are facilitated and conducted using workflow management systems. Role-based access control (RBAC) is recognised as an efficient access control model for large organisations. The application of RBAC in workflow systems cannot, however, grant permissions to users dynamically while business processes are being executed. We currently observe a move away from predefined strict workflow modelling towards approaches supporting flexibility on the organisational level. One specific approach is that of task delegation. Task delegation is a mechanism that supports organisational flexibility, and ensures delegation of authority in access control systems. In this paper, we propose a Task-oriented Access Control (TAC) model based on RBAC to address these requirements. We aim to reason about task from organisational perspectives and resources perspectives to analyse and specify authorisation constraints. Moreover, we present a fine grained access control protocol to support delegation based on the TAC model.

New model performance index for engineering design of control systems

NASA Technical Reports Server (NTRS)

1970-01-01

Performance index includes a model representing linear control-system design specifications. Based on a geometric criterion for approximation of the model by the actual system, the index can be interpreted directly in terms of the desired system response model without actually having the model's time response.

Retrospective revaluation in sequential decision making: a tale of two systems.

PubMed

Gershman, Samuel J; Markman, Arthur B; Otto, A Ross

2014-02-01

Recent computational theories of decision making in humans and animals have portrayed 2 systems locked in a battle for control of behavior. One system--variously termed model-free or habitual--favors actions that have previously led to reward, whereas a second--called the model-based or goal-directed system--favors actions that causally lead to reward according to the agent's internal model of the environment. Some evidence suggests that control can be shifted between these systems using neural or behavioral manipulations, but other evidence suggests that the systems are more intertwined than a competitive account would imply. In 4 behavioral experiments, using a retrospective revaluation design and a cognitive load manipulation, we show that human decisions are more consistent with a cooperative architecture in which the model-free system controls behavior, whereas the model-based system trains the model-free system by replaying and simulating experience.

The System of Systems Architecture Feasibility Assessment Model

DTIC Science & Technology

2016-06-01

OF SYSTEMS ARCHITECTURE FEASIBILITY ASSESSMENT MODEL by Stephen E. Gillespie June 2016 Dissertation Supervisor Eugene Paulo THIS PAGE...Dissertation 4. TITLE AND SUBTITLE THE SYSTEM OF SYSTEMS ARCHITECTURE FEASIBILITY ASSESSMENT MODEL 5. FUNDING NUMBERS 6. AUTHOR(S) Stephen E...SoS architecture feasibility assessment model (SoS-AFAM). Together, these extend current model- based systems engineering (MBSE) and SoS engineering

Comparative analysis of zonal systems for macro-level crash modeling.

PubMed

Cai, Qing; Abdel-Aty, Mohamed; Lee, Jaeyoung; Eluru, Naveen

2017-06-01

Macro-level traffic safety analysis has been undertaken at different spatial configurations. However, clear guidelines for the appropriate zonal system selection for safety analysis are unavailable. In this study, a comparative analysis was conducted to determine the optimal zonal system for macroscopic crash modeling considering census tracts (CTs), state-wide traffic analysis zones (STAZs), and a newly developed traffic-related zone system labeled traffic analysis districts (TADs). Poisson lognormal models for three crash types (i.e., total, severe, and non-motorized mode crashes) are developed based on the three zonal systems without and with consideration of spatial autocorrelation. The study proposes a method to compare the modeling performance of the three types of geographic units at different spatial configurations through a grid based framework. Specifically, the study region is partitioned to grids of various sizes and the model prediction accuracy of the various macro models is considered within these grids of various sizes. These model comparison results for all crash types indicated that the models based on TADs consistently offer a better performance compared to the others. Besides, the models considering spatial autocorrelation outperform the ones that do not consider it. Based on the modeling results and motivation for developing the different zonal systems, it is recommended using CTs for socio-demographic data collection, employing TAZs for transportation demand forecasting, and adopting TADs for transportation safety planning. The findings from this study can help practitioners select appropriate zonal systems for traffic crash modeling, which leads to develop more efficient policies to enhance transportation safety. Copyright © 2017 Elsevier Ltd and National Safety Council. All rights reserved.

Multiple memory systems as substrates for multiple decision systems

PubMed Central

Doll, Bradley B.; Shohamy, Daphna; Daw, Nathaniel D.

2014-01-01

It has recently become widely appreciated that value-based decision making is supported by multiple computational strategies. In particular, animal and human behavior in learning tasks appears to include habitual responses described by prominent model-free reinforcement learning (RL) theories, but also more deliberative or goal-directed actions that can be characterized by a different class of theories, model-based RL. The latter theories evaluate actions by using a representation of the contingencies of the task (as with a learned map of a spatial maze), called an “internal model.” Given the evidence of behavioral and neural dissociations between these approaches, they are often characterized as dissociable learning systems, though they likely interact and share common mechanisms. In many respects, this division parallels a longstanding dissociation in cognitive neuroscience between multiple memory systems, describing, at the broadest level, separate systems for declarative and procedural learning. Procedural learning has notable parallels with model-free RL: both involve learning of habits and both are known to depend on parts of the striatum. Declarative memory, by contrast, supports memory for single events or episodes and depends on the hippocampus. The hippocampus is thought to support declarative memory by encoding temporal and spatial relations among stimuli and thus is often referred to as a relational memory system. Such relational encoding is likely to play an important role in learning an internal model, the representation that is central to model-based RL. Thus, insofar as the memory systems represent more general-purpose cognitive mechanisms that might subserve performance on many sorts of tasks including decision making, these parallels raise the question whether the multiple decision systems are served by multiple memory systems, such that one dissociation is grounded in the other. Here we investigated the relationship between model-based RL and relational memory by comparing individual differences across behavioral tasks designed to measure either capacity. Human subjects performed two tasks, a learning and generalization task (acquired equivalence) which involves relational encoding and depends on the hippocampus; and a sequential RL task that could be solved by either a model-based or model-free strategy. We assessed the correlation between subjects’ use of flexible, relational memory, as measured by generalization in the acquired equivalence task, and their differential reliance on either RL strategy in the decision task. We observed a significant positive relationship between generalization and model-based, but not model-free, choice strategies. These results are consistent with the hypothesis that model-based RL, like acquired equivalence, relies on a more general-purpose relational memory system. PMID:24846190

Model Predictive Control Based on System Re-Identification (MPC-SRI) to Control Bio-H2 Production from Biomass

NASA Astrophysics Data System (ADS)

Wahid, A.; Taqwallah, H. M. H.

2018-03-01

Compressors and a steam reformer are the important units in biohydrogen from biomass plant. The compressors are useful for achieving high-pressure operating conditions while the steam reformer is the main process to produce H2 gas. To control them, in this research used a model predictive control (MPC) expected to have better controller performance than conventional controllers. Because of the explicit model empowerment in MPC, obtaining a better model is the main objective before employing MPC. The common way to get the empirical model is through the identification system, so that obtained a first-order plus dead-time (FOPDT) model. This study has already improved that way since used the system re-identification (SRI) based on closed loop mode. Based on this method the results of the compressor pressure control and temperature control of steam reformer were that MPC based on system re-identification (MPC-SRI) has better performance than MPC without system re-identification (MPCWSRI) and the proportional-integral (PI) controller, by % improvement of 73% against MPCWSRI and 75% against the PI controller.

Modeling Complex Cross-Systems Software Interfaces Using SysML

NASA Technical Reports Server (NTRS)

Mandutianu, Sanda; Morillo, Ron; Simpson, Kim; Liepack, Otfrid; Bonanne, Kevin

2013-01-01

The complex flight and ground systems for NASA human space exploration are designed, built, operated and managed as separate programs and projects. However, each system relies on one or more of the other systems in order to accomplish specific mission objectives, creating a complex, tightly coupled architecture. Thus, there is a fundamental need to understand how each system interacts with the other. To determine if a model-based system engineering approach could be utilized to assist with understanding the complex system interactions, the NASA Engineering and Safety Center (NESC) sponsored a task to develop an approach for performing cross-system behavior modeling. This paper presents the results of applying Model Based Systems Engineering (MBSE) principles using the System Modeling Language (SysML) to define cross-system behaviors and how they map to crosssystem software interfaces documented in system-level Interface Control Documents (ICDs).

The Geolocation model for lunar-based Earth observation

NASA Astrophysics Data System (ADS)

Ding, Yixing; Liu, Guang; Ren, Yuanzhen; Ye, Hanlin; Guo, Huadong; Lv, Mingyang

2016-07-01

In recent years, people are more and more aware of that the earth need to treated as an entirety, and consequently to be observed in a holistic, systematic and multi-scale view. However, the interaction mechanism between the Earth's inner layers and outer layers is still unclear. Therefore, we propose to observe the Earth's inner layers and outer layers instantaneously on the Moon which may be helpful to the studies in climatology, meteorology, seismology, etc. At present, the Moon has been proved to be an irreplaceable platform for Earth's outer layers observation. Meanwhile, some discussions have been made in lunar-based observation of the Earth's inner layers, but the geolocation model of lunar-based observation has not been specified yet. In this paper, we present a geolocation model based on transformation matrix. The model includes six coordinate systems: The telescope coordinate system, the lunar local coordinate system, the lunar-reference coordinate system, the selenocentric inertial coordinate system, the geocentric inertial coordinate system and the geo-reference coordinate system. The parameters, lncluding the position of the Sun, the Earth, the Moon, the libration and the attitude of the Earth, can be acquired from the Ephemeris. By giving an elevation angle and an azimuth angle of the lunar-based telescope, this model links the image pixel to the ground point uniquely.

A systems-based partnership learning model for strengthening primary healthcare

PubMed Central

2013-01-01

Background Strengthening primary healthcare systems is vital to improving health outcomes and reducing inequity. However, there are few tools and models available in published literature showing how primary care system strengthening can be achieved on a large scale. Challenges to strengthening primary healthcare (PHC) systems include the dispersion, diversity and relative independence of primary care providers; the scope and complexity of PHC; limited infrastructure available to support population health approaches; and the generally poor and fragmented state of PHC information systems. Drawing on concepts of comprehensive PHC, integrated quality improvement (IQI) methods, system-based research networks, and system-based participatory action research, we describe a learning model for strengthening PHC that addresses these challenges. We describe the evolution of this model within the Australian Aboriginal and Torres Strait Islander primary healthcare context, successes and challenges in its application, and key issues for further research. Discussion IQI approaches combined with system-based participatory action research and system-based research networks offer potential to support program implementation and ongoing learning across a wide scope of primary healthcare practice and on a large scale. The Partnership Learning Model (PLM) can be seen as an integrated model for large-scale knowledge translation across the scope of priority aspects of PHC. With appropriate engagement of relevant stakeholders, the model may be applicable to a wide range of settings. In IQI, and in the PLM specifically, there is a clear role for research in contributing to refining and evaluating existing tools and processes, and in developing and trialling innovations. Achieving an appropriate balance between funding IQI activity as part of routine service delivery and funding IQI related research will be vital to developing and sustaining this type of PLM. Summary This paper draws together several different previously described concepts and extends the understanding of how PHC systems can be strengthened through systematic and partnership-based approaches. We describe a model developed from these concepts and its application in the Australian Indigenous primary healthcare context, and raise questions about sustainability and wider relevance of the model. PMID:24344640

A task-based support architecture for developing point-of-care clinical decision support systems for the emergency department.

PubMed

Wilk, S; Michalowski, W; O'Sullivan, D; Farion, K; Sayyad-Shirabad, J; Kuziemsky, C; Kukawka, B

2013-01-01

The purpose of this study was to create a task-based support architecture for developing clinical decision support systems (CDSSs) that assist physicians in making decisions at the point-of-care in the emergency department (ED). The backbone of the proposed architecture was established by a task-based emergency workflow model for a patient-physician encounter. The architecture was designed according to an agent-oriented paradigm. Specifically, we used the O-MaSE (Organization-based Multi-agent System Engineering) method that allows for iterative translation of functional requirements into architectural components (e.g., agents). The agent-oriented paradigm was extended with ontology-driven design to implement ontological models representing knowledge required by specific agents to operate. The task-based architecture allows for the creation of a CDSS that is aligned with the task-based emergency workflow model. It facilitates decoupling of executable components (agents) from embedded domain knowledge (ontological models), thus supporting their interoperability, sharing, and reuse. The generic architecture was implemented as a pilot system, MET3-AE--a CDSS to help with the management of pediatric asthma exacerbation in the ED. The system was evaluated in a hospital ED. The architecture allows for the creation of a CDSS that integrates support for all tasks from the task-based emergency workflow model, and interacts with hospital information systems. Proposed architecture also allows for reusing and sharing system components and knowledge across disease-specific CDSSs.

Implementation of a next-generation electronic nursing records system based on detailed clinical models and integration of clinical practice guidelines.

PubMed

Min, Yul Ha; Park, Hyeoun-Ae; Chung, Eunja; Lee, Hyunsook

2013-12-01

The purpose of this paper is to describe the components of a next-generation electronic nursing records system ensuring full semantic interoperability and integrating evidence into the nursing records system. A next-generation electronic nursing records system based on detailed clinical models and clinical practice guidelines was developed at Seoul National University Bundang Hospital in 2013. This system has two components, a terminology server and a nursing documentation system. The terminology server manages nursing narratives generated from entity-attribute-value triplets of detailed clinical models using a natural language generation system. The nursing documentation system provides nurses with a set of nursing narratives arranged around the recommendations extracted from clinical practice guidelines. An electronic nursing records system based on detailed clinical models and clinical practice guidelines was successfully implemented in a hospital in Korea. The next-generation electronic nursing records system can support nursing practice and nursing documentation, which in turn will improve data quality.

Evaluation of Student Models on Current Socio-Scientific Topics Based on System Dynamics

ERIC Educational Resources Information Center

Nuhoglu, Hasret

2014-01-01

This study aims to 1) enable primary school students to develop models that will help them understand and analyze a system, through a learning process based on system dynamics approach, 2) examine and evaluate students' models related to socio-scientific issues using certain criteria. The research method used is a case study. The study sample…

Agent-Based Modeling in Systems Pharmacology.

PubMed

Cosgrove, J; Butler, J; Alden, K; Read, M; Kumar, V; Cucurull-Sanchez, L; Timmis, J; Coles, M

2015-11-01

Modeling and simulation (M&S) techniques provide a platform for knowledge integration and hypothesis testing to gain insights into biological systems that would not be possible a priori. Agent-based modeling (ABM) is an M&S technique that focuses on describing individual components rather than homogenous populations. This tutorial introduces ABM to systems pharmacologists, using relevant case studies to highlight how ABM-specific strengths have yielded success in the area of preclinical mechanistic modeling.

Use of metaknowledge in the verification of knowledge-based systems

NASA Technical Reports Server (NTRS)

Morell, Larry J.

1989-01-01

Knowledge-based systems are modeled as deductive systems. The model indicates that the two primary areas of concern in verification are demonstrating consistency and completeness. A system is inconsistent if it asserts something that is not true of the modeled domain. A system is incomplete if it lacks deductive capability. Two forms of consistency are discussed along with appropriate verification methods. Three forms of incompleteness are discussed. The use of metaknowledge, knowledge about knowledge, is explored in connection to each form of incompleteness.

Unifying Model-Based and Reactive Programming within a Model-Based Executive

NASA Technical Reports Server (NTRS)

Williams, Brian C.; Gupta, Vineet; Norvig, Peter (Technical Monitor)

1999-01-01

Real-time, model-based, deduction has recently emerged as a vital component in AI's tool box for developing highly autonomous reactive systems. Yet one of the current hurdles towards developing model-based reactive systems is the number of methods simultaneously employed, and their corresponding melange of programming and modeling languages. This paper offers an important step towards unification. We introduce RMPL, a rich modeling language that combines probabilistic, constraint-based modeling with reactive programming constructs, while offering a simple semantics in terms of hidden state Markov processes. We introduce probabilistic, hierarchical constraint automata (PHCA), which allow Markov processes to be expressed in a compact representation that preserves the modularity of RMPL programs. Finally, a model-based executive, called Reactive Burton is described that exploits this compact encoding to perform efficIent simulation, belief state update and control sequence generation.

Hypoglycemia early alarm systems based on recursive autoregressive partial least squares models.

PubMed

Bayrak, Elif Seyma; Turksoy, Kamuran; Cinar, Ali; Quinn, Lauretta; Littlejohn, Elizabeth; Rollins, Derrick

2013-01-01

Hypoglycemia caused by intensive insulin therapy is a major challenge for artificial pancreas systems. Early detection and prevention of potential hypoglycemia are essential for the acceptance of fully automated artificial pancreas systems. Many of the proposed alarm systems are based on interpretation of recent values or trends in glucose values. In the present study, subject-specific linear models are introduced to capture glucose variations and predict future blood glucose concentrations. These models can be used in early alarm systems of potential hypoglycemia. A recursive autoregressive partial least squares (RARPLS) algorithm is used to model the continuous glucose monitoring sensor data and predict future glucose concentrations for use in hypoglycemia alarm systems. The partial least squares models constructed are updated recursively at each sampling step with a moving window. An early hypoglycemia alarm algorithm using these models is proposed and evaluated. Glucose prediction models based on real-time filtered data has a root mean squared error of 7.79 and a sum of squares of glucose prediction error of 7.35% for six-step-ahead (30 min) glucose predictions. The early alarm systems based on RARPLS shows good performance. A sensitivity of 86% and a false alarm rate of 0.42 false positive/day are obtained for the early alarm system based on six-step-ahead predicted glucose values with an average early detection time of 25.25 min. The RARPLS models developed provide satisfactory glucose prediction with relatively smaller error than other proposed algorithms and are good candidates to forecast and warn about potential hypoglycemia unless preventive action is taken far in advance. © 2012 Diabetes Technology Society.

Hypoglycemia Early Alarm Systems Based on Recursive Autoregressive Partial Least Squares Models

PubMed Central

Bayrak, Elif Seyma; Turksoy, Kamuran; Cinar, Ali; Quinn, Lauretta; Littlejohn, Elizabeth; Rollins, Derrick

2013-01-01

Background Hypoglycemia caused by intensive insulin therapy is a major challenge for artificial pancreas systems. Early detection and prevention of potential hypoglycemia are essential for the acceptance of fully automated artificial pancreas systems. Many of the proposed alarm systems are based on interpretation of recent values or trends in glucose values. In the present study, subject-specific linear models are introduced to capture glucose variations and predict future blood glucose concentrations. These models can be used in early alarm systems of potential hypoglycemia. Methods A recursive autoregressive partial least squares (RARPLS) algorithm is used to model the continuous glucose monitoring sensor data and predict future glucose concentrations for use in hypoglycemia alarm systems. The partial least squares models constructed are updated recursively at each sampling step with a moving window. An early hypoglycemia alarm algorithm using these models is proposed and evaluated. Results Glucose prediction models based on real-time filtered data has a root mean squared error of 7.79 and a sum of squares of glucose prediction error of 7.35% for six-step-ahead (30 min) glucose predictions. The early alarm systems based on RARPLS shows good performance. A sensitivity of 86% and a false alarm rate of 0.42 false positive/day are obtained for the early alarm system based on six-step-ahead predicted glucose values with an average early detection time of 25.25 min. Conclusions The RARPLS models developed provide satisfactory glucose prediction with relatively smaller error than other proposed algorithms and are good candidates to forecast and warn about potential hypoglycemia unless preventive action is taken far in advance. PMID:23439179

Evaluating model accuracy for model-based reasoning

NASA Technical Reports Server (NTRS)

Chien, Steve; Roden, Joseph

1992-01-01

Described here is an approach to automatically assessing the accuracy of various components of a model. In this approach, actual data from the operation of a target system is used to drive statistical measures to evaluate the prediction accuracy of various portions of the model. We describe how these statistical measures of model accuracy can be used in model-based reasoning for monitoring and design. We then describe the application of these techniques to the monitoring and design of the water recovery system of the Environmental Control and Life Support System (ECLSS) of Space Station Freedom.

A Model-Based Approach to Support Validation of Medical Cyber-Physical Systems.

PubMed

Silva, Lenardo C; Almeida, Hyggo O; Perkusich, Angelo; Perkusich, Mirko

2015-10-30

Medical Cyber-Physical Systems (MCPS) are context-aware, life-critical systems with patient safety as the main concern, demanding rigorous processes for validation to guarantee user requirement compliance and specification-oriented correctness. In this article, we propose a model-based approach for early validation of MCPS, focusing on promoting reusability and productivity. It enables system developers to build MCPS formal models based on a library of patient and medical device models, and simulate the MCPS to identify undesirable behaviors at design time. Our approach has been applied to three different clinical scenarios to evaluate its reusability potential for different contexts. We have also validated our approach through an empirical evaluation with developers to assess productivity and reusability. Finally, our models have been formally verified considering functional and safety requirements and model coverage.

A Model-Based Approach to Support Validation of Medical Cyber-Physical Systems

PubMed Central

Silva, Lenardo C.; Almeida, Hyggo O.; Perkusich, Angelo; Perkusich, Mirko

2015-01-01

Medical Cyber-Physical Systems (MCPS) are context-aware, life-critical systems with patient safety as the main concern, demanding rigorous processes for validation to guarantee user requirement compliance and specification-oriented correctness. In this article, we propose a model-based approach for early validation of MCPS, focusing on promoting reusability and productivity. It enables system developers to build MCPS formal models based on a library of patient and medical device models, and simulate the MCPS to identify undesirable behaviors at design time. Our approach has been applied to three different clinical scenarios to evaluate its reusability potential for different contexts. We have also validated our approach through an empirical evaluation with developers to assess productivity and reusability. Finally, our models have been formally verified considering functional and safety requirements and model coverage. PMID:26528982

Method and system for detecting a failure or performance degradation in a dynamic system such as a flight vehicle

NASA Technical Reports Server (NTRS)

Miller, Robert H. (Inventor); Ribbens, William B. (Inventor)

2003-01-01

A method and system for detecting a failure or performance degradation in a dynamic system having sensors for measuring state variables and providing corresponding output signals in response to one or more system input signals are provided. The method includes calculating estimated gains of a filter and selecting an appropriate linear model for processing the output signals based on the input signals. The step of calculating utilizes one or more models of the dynamic system to obtain estimated signals. The method further includes calculating output error residuals based on the output signals and the estimated signals. The method also includes detecting one or more hypothesized failures or performance degradations of a component or subsystem of the dynamic system based on the error residuals. The step of calculating the estimated values is performed optimally with respect to one or more of: noise, uncertainty of parameters of the models and un-modeled dynamics of the dynamic system which may be a flight vehicle or financial market or modeled financial system.

A physical data model for fields and agents

NASA Astrophysics Data System (ADS)

de Jong, Kor; de Bakker, Merijn; Karssenberg, Derek

2016-04-01

Two approaches exist in simulation modeling: agent-based and field-based modeling. In agent-based (or individual-based) simulation modeling, the entities representing the system's state are represented by objects, which are bounded in space and time. Individual objects, like an animal, a house, or a more abstract entity like a country's economy, have properties representing their state. In an agent-based model this state is manipulated. In field-based modeling, the entities representing the system's state are represented by fields. Fields capture the state of a continuous property within a spatial extent, examples of which are elevation, atmospheric pressure, and water flow velocity. With respect to the technology used to create these models, the domains of agent-based and field-based modeling have often been separate worlds. In environmental modeling, widely used logical data models include feature data models for point, line and polygon objects, and the raster data model for fields. Simulation models are often either agent-based or field-based, even though the modeled system might contain both entities that are better represented by individuals and entities that are better represented by fields. We think that the reason for this dichotomy in kinds of models might be that the traditional object and field data models underlying those models are relatively low level. We have developed a higher level conceptual data model for representing both non-spatial and spatial objects, and spatial fields (De Bakker et al. 2016). Based on this conceptual data model we designed a logical and physical data model for representing many kinds of data, including the kinds used in earth system modeling (e.g. hydrological and ecological models). The goal of this work is to be able to create high level code and tools for the creation of models in which entities are representable by both objects and fields. Our conceptual data model is capable of representing the traditional feature data models and the raster data model, among many other data models. Our physical data model is capable of storing a first set of kinds of data, like omnipresent scalars, mobile spatio-temporal points and property values, and spatio-temporal rasters. With our poster we will provide an overview of the physical data model expressed in HDF5 and show examples of how it can be used to capture both object- and field-based information. References De Bakker, M, K. de Jong, D. Karssenberg. 2016. A conceptual data model and language for fields and agents. European Geosciences Union, EGU General Assembly, 2016, Vienna.

A Performance Prediction Model for a Fault-Tolerant Computer During Recovery and Restoration

NASA Technical Reports Server (NTRS)

Obando, Rodrigo A.; Stoughton, John W.

1995-01-01

The modeling and design of a fault-tolerant multiprocessor system is addressed. Of interest is the behavior of the system during recovery and restoration after a fault has occurred. The multiprocessor systems are based on the Algorithm to Architecture Mapping Model (ATAMM) and the fault considered is the death of a processor. The developed model is useful in the determination of performance bounds of the system during recovery and restoration. The performance bounds include time to recover from the fault, time to restore the system, and determination of any permanent delay in the input to output latency after the system has regained steady state. Implementation of an ATAMM based computer was developed for a four-processor generic VHSIC spaceborne computer (GVSC) as the target system. A simulation of the GVSC was also written on the code used in the ATAMM Multicomputer Operating System (AMOS). The simulation is used to verify the new model for tracking the propagation of the delay through the system and predicting the behavior of the transient state of recovery and restoration. The model is shown to accurately predict the transient behavior of an ATAMM based multicomputer during recovery and restoration.

An event-version-based spatio-temporal modeling approach and its application in the cadastral management

NASA Astrophysics Data System (ADS)

Li, Yangdong; Han, Zhen; Liao, Zhongping

2009-10-01

Spatiality, temporality, legality, accuracy and continuality are characteristic of cadastral information, and the cadastral management demands that the cadastral data should be accurate, integrated and updated timely. It's a good idea to build an effective GIS management system to manage the cadastral data which are characterized by spatiality and temporality. Because no sound spatio-temporal data models have been adopted, however, the spatio-temporal characteristics of cadastral data are not well expressed in the existing cadastral management systems. An event-version-based spatio-temporal modeling approach is first proposed from the angle of event and version. Then with the help of it, an event-version-based spatio-temporal cadastral data model is built to represent spatio-temporal cadastral data. At last, the previous model is used in the design and implementation of a spatio-temporal cadastral management system. The result of the application of the system shows that the event-version-based spatio-temporal data model is very suitable for the representation and organization of cadastral data.

Assessing Online Textual Feedback to Support Student Intrinsic Motivation Using a Collaborative Text-Based Dialogue System: A Qualitative Study

ERIC Educational Resources Information Center

Shroff, Ronnie H.; Deneen, Christopher

2011-01-01

This paper assesses textual feedback to support student intrinsic motivation using a collaborative text-based dialogue system. A research model is presented based on research into intrinsic motivation, and the specific construct of feedback provides a framework for the model. A qualitative research methodology is used to validate the model.…

An extensible simulation environment and movement metrics for testing walking behavior in agent-based models

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

Paul M. Torrens; Atsushi Nara; Xun Li

2012-01-01

Human movement is a significant ingredient of many social, environmental, and technical systems, yet the importance of movement is often discounted in considering systems complexity. Movement is commonly abstracted in agent-based modeling (which is perhaps the methodological vehicle for modeling complex systems), despite the influence of movement upon information exchange and adaptation in a system. In particular, agent-based models of urban pedestrians often treat movement in proxy form at the expense of faithfully treating movement behavior with realistic agency. There exists little consensus about which method is appropriate for representing movement in agent-based schemes. In this paper, we examine popularly-usedmore » methods to drive movement in agent-based models, first by introducing a methodology that can flexibly handle many representations of movement at many different scales and second, introducing a suite of tools to benchmark agent movement between models and against real-world trajectory data. We find that most popular movement schemes do a relatively poor job of representing movement, but that some schemes may well be 'good enough' for some applications. We also discuss potential avenues for improving the representation of movement in agent-based frameworks.« less

Model-Based Systems

NASA Technical Reports Server (NTRS)

Frisch, Harold P.

2007-01-01

Engineers, who design systems using text specification documents, focus their work upon the completed system to meet Performance, time and budget goals. Consistency and integrity is difficult to maintain within text documents for a single complex system and more difficult to maintain as several systems are combined into higher-level systems, are maintained over decades, and evolve technically and in performance through updates. This system design approach frequently results in major changes during the system integration and test phase, and in time and budget overruns. Engineers who build system specification documents within a model-based systems environment go a step further and aggregate all of the data. They interrelate all of the data to insure consistency and integrity. After the model is constructed, the various system specification documents are prepared, all from the same database. The consistency and integrity of the model is assured, therefore the consistency and integrity of the various specification documents is insured. This article attempts to define model-based systems relative to such an environment. The intent is to expose the complexity of the enabling problem by outlining what is needed, why it is needed and how needs are being addressed by international standards writing teams.

Modeling Long-term Creep Performance for Welded Nickel-base Superalloy Structures for Power Generation Systems

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

Shen, Chen; Gupta, Vipul; Huang, Shenyan

The goal of this project is to model long-term creep performance for nickel-base superalloy weldments in high temperature power generation systems. The project uses physics-based modeling methodologies and algorithms for predicting alloy properties in heterogeneous material structures. The modeling methodology will be demonstrated on a gas turbine combustor liner weldment of Haynes 282 precipitate-strengthened nickel-base superalloy. The major developments are: (1) microstructure-property relationships under creep conditions and microstructure characterization (2) modeling inhomogeneous microstructure in superalloy weld (3) modeling mesoscale plastic deformation in superalloy weld and (4) a constitutive creep model that accounts for weld and base metal microstructure and theirmore » long term evolution. The developed modeling technology is aimed to provide a more efficient and accurate assessment of a material’s long-term performance compared with current testing and extrapolation methods. This modeling technology will also accelerate development and qualification of new materials in advanced power generation systems. This document is a final technical report for the project, covering efforts conducted from October 2014 to December 2016.« less

Development and Validation of a Slurry Model for Chemical Hydrogen Storage in Fuel Cell Applications

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

Brooks, Kriston P.; Pires, Richard P.; Simmons, Kevin L.

2014-07-25

The US Department of Energy's (DOE) Hydrogen Storage Engineering Center of Excellence (HSECoE) is developing models for hydrogen storage systems for fuel cell-based light duty vehicle applications for a variety of promising materials. These transient models simulate the performance of the storage system for comparison to the DOE’s Technical Targets and a set of four drive cycles. The purpose of this research is to describe the models developed for slurry-based chemical hydrogen storage materials. The storage systems of both a representative exothermic system based on ammonia borane and endothermic system based on alane were developed and modeled in Simulink®. Oncemore » complete the reactor and radiator components of the model were validated with experimental data. The model was then run using a highway cycle, an aggressive cycle, cold-start cycle and hot drive cycle. The system design was adjusted to meet these drive cycles. A sensitivity analysis was then performed to identify the range of material properties where these DOE targets and drive cycles could be met. Materials with a heat of reaction greater than 11 kJ/mol H2 generated and a slurry hydrogen capacity of greater than 11.4% will meet the on-board efficiency and gravimetric capacity targets, respectively.« less

Model-based frequency response characterization of a digital-image analysis system for epifluorescence microscopy

NASA Technical Reports Server (NTRS)

Hazra, Rajeeb; Viles, Charles L.; Park, Stephen K.; Reichenbach, Stephen E.; Sieracki, Michael E.

1992-01-01

Consideration is given to a model-based method for estimating the spatial frequency response of a digital-imaging system (e.g., a CCD camera) that is modeled as a linear, shift-invariant image acquisition subsystem that is cascaded with a linear, shift-variant sampling subsystem. The method characterizes the 2D frequency response of the image acquisition subsystem to beyond the Nyquist frequency by accounting explicitly for insufficient sampling and the sample-scene phase. Results for simulated systems and a real CCD-based epifluorescence microscopy system are presented to demonstrate the accuracy of the method.

Real-time simulation of a Doubly-Fed Induction Generator based wind power system on eMEGASimRTM Real-Time Digital Simulator

NASA Astrophysics Data System (ADS)

Boakye-Boateng, Nasir Abdulai

The growing demand for wind power integration into the generation mix prompts the need to subject these systems to stringent performance requirements. This study sought to identify the required tools and procedures needed to perform real-time simulation studies of Doubly-Fed Induction Generator (DFIG) based wind generation systems as basis for performing more practical tests of reliability and performance for both grid-connected and islanded wind generation systems. The author focused on developing a platform for wind generation studies and in addition, the author tested the performance of two DFIG models on the platform real-time simulation model; an average SimpowerSystemsRTM DFIG wind turbine, and a detailed DFIG based wind turbine using ARTEMiSRTM components. The platform model implemented here consists of a high voltage transmission system with four integrated wind farm models consisting in total of 65 DFIG based wind turbines and it was developed and tested on OPAL-RT's eMEGASimRTM Real-Time Digital Simulator.

Nonlinear Friction Compensation of Ball Screw Driven Stage Based on Variable Natural Length Spring Model and Disturbance Observer

NASA Astrophysics Data System (ADS)

Asaumi, Hiroyoshi; Fujimoto, Hiroshi

Ball screw driven stages are used for industrial equipments such as machine tools and semiconductor equipments. Fast and precise positioning is necessary to enhance productivity and microfabrication technology of the system. The rolling friction of the ball screw driven stage deteriorate the positioning performance. Therefore, the control system based on the friction model is necessary. In this paper, we propose variable natural length spring model (VNLS model) as the friction model. VNLS model is simple and easy to implement as friction controller. Next, we propose multi variable natural length spring model (MVNLS model) as the friction model. MVNLS model can represent friction characteristic of the stage precisely. Moreover, the control system based on MVNLS model and disturbance observer is proposed. Finally, the simulation results and experimental results show the advantages of the proposed method.

Passivity-based Robust Control of Aerospace Systems

NASA Technical Reports Server (NTRS)

Kelkar, Atul G.; Joshi, Suresh M. (Technical Monitor)

2000-01-01

This report provides a brief summary of the research work performed over the duration of the cooperative research agreement between NASA Langley Research Center and Kansas State University. The cooperative agreement which was originally for the duration the three years was extended by another year through no-cost extension in order to accomplish the goals of the project. The main objective of the research was to develop passivity-based robust control methodology for passive and non-passive aerospace systems. The focus of the first-year's research was limited to the investigation of passivity-based methods for the robust control of Linear Time-Invariant (LTI) single-input single-output (SISO), open-loop stable, minimum-phase non-passive systems. The second year's focus was mainly on extending the passivity-based methodology to a larger class of non-passive LTI systems which includes unstable and nonminimum phase SISO systems. For LTI non-passive systems, five different passification. methods were developed. The primary effort during the years three and four was on the development of passification methodology for MIMO systems, development of methods for checking robustness of passification, and developing synthesis techniques for passifying compensators. For passive LTI systems optimal synthesis procedure was also developed for the design of constant-gain positive real controllers. For nonlinear passive systems, numerical optimization-based technique was developed for the synthesis of constant as well as time-varying gain positive-real controllers. The passivity-based control design methodology developed during the duration of this project was demonstrated by its application to various benchmark examples. These example systems included longitudinal model of an F-18 High Alpha Research Vehicle (HARV) for pitch axis control, NASA's supersonic transport wind tunnel model, ACC benchmark model, 1-D acoustic duct model, piezo-actuated flexible link model, and NASA's Benchmark Active Controls Technology (BACT) Wing model. Some of the stability results for linear passive systems were also extended to nonlinear passive systems. Several publications and conference presentations resulted from this research.

A Method for Generating Reduced Order Linear Models of Supersonic Inlets

NASA Technical Reports Server (NTRS)

Chicatelli, Amy; Hartley, Tom T.

1997-01-01

For the modeling of high speed propulsion systems, there are at least two major categories of models. One is based on computational fluid dynamics (CFD), and the other is based on design and analysis of control systems. CFD is accurate and gives a complete view of the internal flow field, but it typically has many states and runs much slower dm real-time. Models based on control design typically run near real-time but do not always capture the fundamental dynamics. To provide improved control models, methods are needed that are based on CFD techniques but yield models that are small enough for control analysis and design.

Lessons Learned from using a Livingstone Model to Diagnose a Main Propulsion System

NASA Technical Reports Server (NTRS)

Sweet, Adam; Bajwa, Anupa

2003-01-01

NASA researchers have demonstrated that qualitative, model-based reasoning can be used for fault detection in a Main Propulsion System (MPS), a complex, continuous system. At the heart of this diagnostic system is Livingstone, a discrete, propositional logic-based inference engine. Livingstone comprises a language for specifying a discrete model of the system and a set of algorithms that use the model to track the system's state. Livingstone uses the model to test assumptions about the state of a component - observations from the system are compared with values predicted by the model. The intent of this paper is to summarize some advantages of Livingstone seen through our modeling experience: for instance, flexibility in modeling, speed and maturity. We also describe some shortcomings we perceived in the implementation of Livingstone, such as modeling continuous dynamics and handling of transients. We list some upcoming enhancements to the next version of Livingstone that may resolve some of the current limitations.

A security and privacy preserving e-prescription system based on smart cards.

PubMed

Hsu, Chien-Lung; Lu, Chung-Fu

2012-12-01

In 2002, Ateniese and Medeiros proposed an e-prescription system, in which the patient can store e-prescription and related information using smart card. Latter, Yang et al. proposed a novel smart-card based e-prescription system based on Ateniese and Medeiros's system in 2004. Yang et al. considered the privacy issues of prescription data and adopted the concept of a group signature to provide patient's privacy protection. To make the e-prescription system more realistic, they further applied a proxy signature to allow a patient to delegate his signing capability to other people. This paper proposed a novel security and privacy preserving e-prescription system model based on smart cards. A new role, chemist, is included in the system model for settling the medicine dispute. We further presented a concrete identity-based (ID-based) group signature scheme and an ID-based proxy signature scheme to realize the proposed model. Main property of an ID-based system is that public key is simple user's identity and can be verified without extra public key certificates. Our ID-based group signature scheme can allow doctors to sign e-prescription anonymously. In a case of a medical dispute, identities of the doctors can be identified. The proposed ID-based proxy signature scheme can improve signing delegation and allows a delegation chain. The proposed e-prescription system based on our proposed two cryptographic schemes is more practical and efficient than Yang et al.'s system in terms of security, communication overheads, computational costs, practical considerations.

A geographic information system-based 3D city estate modeling and simulation system

NASA Astrophysics Data System (ADS)

Chong, Xiaoli; Li, Sha

2015-12-01

This paper introduces a 3D city simulation system which is based on geographic information system (GIS), covering all commercial housings of the city. A regional- scale, GIS-based approach is used to capture, describe, and track the geographical attributes of each house in the city. A sorting algorithm of "Benchmark + Parity Rate" is developed to cluster houses with similar spatial and construction attributes. This system is applicable for digital city modeling, city planning, housing evaluation, housing monitoring, and visualizing housing transaction. Finally, taking Jingtian area of Shenzhen as an example, the each unit of 35,997 houses in the area could be displayed, tagged, and easily tracked by the GIS-based city modeling and simulation system. The match market real conditions well and can be provided to house buyers as reference.

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...

Postural effects on intracranial pressure: modeling and clinical evaluation.

PubMed

Qvarlander, Sara; Sundström, Nina; Malm, Jan; Eklund, Anders

2013-11-01

The physiological effect of posture on intracranial pressure (ICP) is not well described. This study defined and evaluated three mathematical models describing the postural effects on ICP, designed to predict ICP at different head-up tilt angles from the supine ICP value. Model I was based on a hydrostatic indifference point for the cerebrospinal fluid (CSF) system, i.e., the existence of a point in the system where pressure is independent of body position. Models II and III were based on Davson's equation for CSF absorption, which relates ICP to venous pressure, and postulated that gravitational effects within the venous system are transferred to the CSF system. Model II assumed a fully communicating venous system, and model III assumed that collapse of the jugular veins at higher tilt angles creates two separate hydrostatic compartments. Evaluation of the models was based on ICP measurements at seven tilt angles (0-71°) in 27 normal pressure hydrocephalus patients. ICP decreased with tilt angle (ANOVA: P < 0.01). The reduction was well predicted by model III (ANOVA lack-of-fit: P = 0.65), which showed excellent fit against measured ICP. Neither model I nor II adequately described the reduction in ICP (ANOVA lack-of-fit: P < 0.01). Postural changes in ICP could not be predicted based on the currently accepted theory of a hydrostatic indifference point for the CSF system, but a new model combining Davson's equation for CSF absorption and hydrostatic gradients in a collapsible venous system performed well and can be useful in future research on gravity and CSF physiology.

Modeling the data management system of Space Station Freedom with DEPEND

NASA Technical Reports Server (NTRS)

Olson, Daniel P.; Iyer, Ravishankar K.; Boyd, Mark A.

1993-01-01

Some of the features and capabilities of the DEPEND simulation-based modeling tool are described. A study of a 1553B local bus subsystem of the Space Station Freedom Data Management System (SSF DMS) is used to illustrate some types of system behavior that can be important to reliability and performance evaluations of this type of spacecraft. A DEPEND model of the subsystem is used to illustrate how these types of system behavior can be modeled, and shows what kinds of engineering and design questions can be answered through the use of these modeling techniques. DEPEND's process-based simulation environment is shown to provide a flexible method for modeling complex interactions between hardware and software elements of a fault-tolerant computing system.

Continuous system modeling

NASA Technical Reports Server (NTRS)

Cellier, Francois E.

1991-01-01

A comprehensive and systematic introduction is presented for the concepts associated with 'modeling', involving the transition from a physical system down to an abstract description of that system in the form of a set of differential and/or difference equations, and basing its treatment of modeling on the mathematics of dynamical systems. Attention is given to the principles of passive electrical circuit modeling, planar mechanical systems modeling, hierarchical modular modeling of continuous systems, and bond-graph modeling. Also discussed are modeling in equilibrium thermodynamics, population dynamics, and system dynamics, inductive reasoning, artificial neural networks, and automated model synthesis.

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.

Internet-based system for simulation-based medical planning for cardiovascular disease.

PubMed

Steele, Brooke N; Draney, Mary T; Ku, Joy P; Taylor, Charles A

2003-06-01

Current practice in vascular surgery utilizes only diagnostic and empirical data to plan treatments, which does not enable quantitative a priori prediction of the outcomes of interventions. We have previously described simulation-based medical planning methods to model blood flow in arteries and plan medical treatments based on physiologic models. An important consideration for the design of these patient-specific modeling systems is the accessibility to physicians with modest computational resources. We describe a simulation-based medical planning environment developed for the World Wide Web (WWW) using the Virtual Reality Modeling Language (VRML) and the Java programming language.

Quality evaluation on an e-learning system in continuing professional education of nurses.

PubMed

Lin, I-Chun; Chien, Yu-Mei; Chang, I-Chiu

2006-01-01

Maintaining high quality in Web-based learning is a powerful means of increasing the overall efficiency and effectiveness of distance learning. Many studies have evaluated Web-based learning but seldom evaluate from the information systems (IS) perspective. This study applied the famous IS Success model in measuring the quality of a Web-based learning system using a Web-based questionnaire for data collection. One hundred and fifty four nurses participated in the survey. Based on confirmatory factor analysis, the variables of the research model fit for measuring the quality of a Web-based learning system. As Web-based education continues to grow worldwide, the results of this study may assist the system adopter (hospital executives), the learner (nurses), and the system designers in making reasonable and informed judgments with regard to the quality of Web-based learning system in continuing professional education.

Evaluating Water Demand Using Agent-Based Modeling

NASA Astrophysics Data System (ADS)

Lowry, T. S.

2004-12-01

The supply and demand of water resources are functions of complex, inter-related systems including hydrology, climate, demographics, economics, and policy. To assess the safety and sustainability of water resources, planners often rely on complex numerical models that relate some or all of these systems using mathematical abstractions. The accuracy of these models relies on how well the abstractions capture the true nature of the systems interactions. Typically, these abstractions are based on analyses of observations and/or experiments that account only for the statistical mean behavior of each system. This limits the approach in two important ways: 1) It cannot capture cross-system disruptive events, such as major drought, significant policy change, or terrorist attack, and 2) it cannot resolve sub-system level responses. To overcome these limitations, we are developing an agent-based water resources model that includes the systems of hydrology, climate, demographics, economics, and policy, to examine water demand during normal and extraordinary conditions. Agent-based modeling (ABM) develops functional relationships between systems by modeling the interaction between individuals (agents), who behave according to a probabilistic set of rules. ABM is a "bottom-up" modeling approach in that it defines macro-system behavior by modeling the micro-behavior of individual agents. While each agent's behavior is often simple and predictable, the aggregate behavior of all agents in each system can be complex, unpredictable, and different than behaviors observed in mean-behavior models. Furthermore, the ABM approach creates a virtual laboratory where the effects of policy changes and/or extraordinary events can be simulated. Our model, which is based on the demographics and hydrology of the Middle Rio Grande Basin in the state of New Mexico, includes agent groups of residential, agricultural, and industrial users. Each agent within each group determines its water usage based on its own condition and the condition of the world around it. For example, residential agents can make decisions to convert to or from xeriscaping and/or low-flow appliances based on policy implementation, economic status, weather, and climatic conditions. Agricultural agents may vary their usage by making decisions on crop distribution and irrigation design. Preliminary results show that water usage can be highly irrational under certain conditions. Results also identify sub-sectors within each group that have the highest influence on ensemble group behavior, providing a means for policy makers to target their efforts. Finally, the model is able to predict the impact of low-probability, high-impact events such as catastrophic denial of service due to natural and/or man-made events.

DEVS Unified Process for Web-Centric Development and Testing of System of Systems

DTIC Science & Technology

2008-05-20

gathering from the user. Further, methodologies have been developed to generate DEVS models from BPMN /BPEL-based and message-based requirement specifications...27] 3. BPMN /BPEL based system specifications: Business Process Modeling Notation ( BPMN ) [bpm] or Business Process Execution Language (BPEL) provide a...information is stored in .wsdl and .bpel files for BPEL but in proprietary format for BPMN . 4. DoDAF-based requirement specifications: Department of

Identification of Putative Cardiovascular System Developmental Toxicants using a Classification Model based on Signaling Pathway-Adverse Outcome Pathways

EPA Science Inventory

An important challenge for an integrative approach to developmental systems toxicology is associating putative molecular initiating events (MIEs), cell signaling pathways, cell function and modeled fetal exposure kinetics. We have developed a chemical classification model based o...

Viewing Knowledge Bases as Qualitative Models.

ERIC Educational Resources Information Center

Clancey, William J.

The concept of a qualitative model provides a unifying perspective for understanding how expert systems differ from conventional programs. Knowledge bases contain qualitative models of systems in the world, that is, primarily non-numeric descriptions that provide a basis for explaining and predicting behavior and formulating action plans. The…

Effect of Bayesian Student Modeling on Academic Achievement in Foreign Language Teaching (University Level English Preparatory School Example)

ERIC Educational Resources Information Center

Aslan, Burak Galip; Öztürk, Özlem; Inceoglu, Mustafa Murat

2014-01-01

Considering the increasing importance of adaptive approaches in CALL systems, this study implemented a machine learning based student modeling middleware with Bayesian networks. The profiling approach of the student modeling system is based on Felder and Silverman's Learning Styles Model and Felder and Soloman's Index of Learning Styles…

A component-based, integrated spatially distributed hydrologic/water quality model: AgroEcoSystem-Watershed (AgES-W) overview and application

USDA-ARS?s Scientific Manuscript database

AgroEcoSystem-Watershed (AgES-W) is a modular, Java-based spatially distributed model which implements hydrologic/water quality simulation components. The AgES-W model was previously evaluated for streamflow and recently has been enhanced with the addition of nitrogen (N) and sediment modeling compo...

Introduction to Information Visualization (InfoVis) Techniques for Model-Based Systems Engineering

NASA Technical Reports Server (NTRS)

Sindiy, Oleg; Litomisky, Krystof; Davidoff, Scott; Dekens, Frank

2013-01-01

This paper presents insights that conform to numerous system modeling languages/representation standards. The insights are drawn from best practices of Information Visualization as applied to aerospace-based applications.

Systematic reconstruction of TRANSPATH data into Cell System Markup Language

PubMed Central

Nagasaki, Masao; Saito, Ayumu; Li, Chen; Jeong, Euna; Miyano, Satoru

2008-01-01

Background Many biological repositories store information based on experimental study of the biological processes within a cell, such as protein-protein interactions, metabolic pathways, signal transduction pathways, or regulations of transcription factors and miRNA. Unfortunately, it is difficult to directly use such information when generating simulation-based models. Thus, modeling rules for encoding biological knowledge into system-dynamics-oriented standardized formats would be very useful for fully understanding cellular dynamics at the system level. Results We selected the TRANSPATH database, a manually curated high-quality pathway database, which provides a plentiful source of cellular events in humans, mice, and rats, collected from over 31,500 publications. In this work, we have developed 16 modeling rules based on hybrid functional Petri net with extension (HFPNe), which is suitable for graphical representing and simulating biological processes. In the modeling rules, each Petri net element is incorporated with Cell System Ontology to enable semantic interoperability of models. As a formal ontology for biological pathway modeling with dynamics, CSO also defines biological terminology and corresponding icons. By combining HFPNe with the CSO features, it is possible to make TRANSPATH data to simulation-based and semantically valid models. The results are encoded into a biological pathway format, Cell System Markup Language (CSML), which eases the exchange and integration of biological data and models. Conclusion By using the 16 modeling rules, 97% of the reactions in TRANSPATH are converted into simulation-based models represented in CSML. This reconstruction demonstrates that it is possible to use our rules to generate quantitative models from static pathway descriptions. PMID:18570683

Systematic reconstruction of TRANSPATH data into cell system markup language.

PubMed

Nagasaki, Masao; Saito, Ayumu; Li, Chen; Jeong, Euna; Miyano, Satoru

2008-06-23

Many biological repositories store information based on experimental study of the biological processes within a cell, such as protein-protein interactions, metabolic pathways, signal transduction pathways, or regulations of transcription factors and miRNA. Unfortunately, it is difficult to directly use such information when generating simulation-based models. Thus, modeling rules for encoding biological knowledge into system-dynamics-oriented standardized formats would be very useful for fully understanding cellular dynamics at the system level. We selected the TRANSPATH database, a manually curated high-quality pathway database, which provides a plentiful source of cellular events in humans, mice, and rats, collected from over 31,500 publications. In this work, we have developed 16 modeling rules based on hybrid functional Petri net with extension (HFPNe), which is suitable for graphical representing and simulating biological processes. In the modeling rules, each Petri net element is incorporated with Cell System Ontology to enable semantic interoperability of models. As a formal ontology for biological pathway modeling with dynamics, CSO also defines biological terminology and corresponding icons. By combining HFPNe with the CSO features, it is possible to make TRANSPATH data to simulation-based and semantically valid models. The results are encoded into a biological pathway format, Cell System Markup Language (CSML), which eases the exchange and integration of biological data and models. By using the 16 modeling rules, 97% of the reactions in TRANSPATH are converted into simulation-based models represented in CSML. This reconstruction demonstrates that it is possible to use our rules to generate quantitative models from static pathway descriptions.

A text-based data mining and toxicity prediction modeling system for a clinical decision support in radiation oncology: A preliminary study

NASA Astrophysics Data System (ADS)

Kim, Kwang Hyeon; Lee, Suk; Shim, Jang Bo; Chang, Kyung Hwan; Yang, Dae Sik; Yoon, Won Sup; Park, Young Je; Kim, Chul Yong; Cao, Yuan Jie

2017-08-01

The aim of this study is an integrated research for text-based data mining and toxicity prediction modeling system for clinical decision support system based on big data in radiation oncology as a preliminary research. The structured and unstructured data were prepared by treatment plans and the unstructured data were extracted by dose-volume data image pattern recognition of prostate cancer for research articles crawling through the internet. We modeled an artificial neural network to build a predictor model system for toxicity prediction of organs at risk. We used a text-based data mining approach to build the artificial neural network model for bladder and rectum complication predictions. The pattern recognition method was used to mine the unstructured toxicity data for dose-volume at the detection accuracy of 97.9%. The confusion matrix and training model of the neural network were achieved with 50 modeled plans (n = 50) for validation. The toxicity level was analyzed and the risk factors for 25% bladder, 50% bladder, 20% rectum, and 50% rectum were calculated by the artificial neural network algorithm. As a result, 32 plans could cause complication but 18 plans were designed as non-complication among 50 modeled plans. We integrated data mining and a toxicity modeling method for toxicity prediction using prostate cancer cases. It is shown that a preprocessing analysis using text-based data mining and prediction modeling can be expanded to personalized patient treatment decision support based on big data.

A simple computational algorithm of model-based choice preference.

PubMed

Toyama, Asako; Katahira, Kentaro; Ohira, Hideki

2017-08-01

A broadly used computational framework posits that two learning systems operate in parallel during the learning of choice preferences-namely, the model-free and model-based reinforcement-learning systems. In this study, we examined another possibility, through which model-free learning is the basic system and model-based information is its modulator. Accordingly, we proposed several modified versions of a temporal-difference learning model to explain the choice-learning process. Using the two-stage decision task developed by Daw, Gershman, Seymour, Dayan, and Dolan (2011), we compared their original computational model, which assumes a parallel learning process, and our proposed models, which assume a sequential learning process. Choice data from 23 participants showed a better fit with the proposed models. More specifically, the proposed eligibility adjustment model, which assumes that the environmental model can weight the degree of the eligibility trace, can explain choices better under both model-free and model-based controls and has a simpler computational algorithm than the original model. In addition, the forgetting learning model and its variation, which assume changes in the values of unchosen actions, substantially improved the fits to the data. Overall, we show that a hybrid computational model best fits the data. The parameters used in this model succeed in capturing individual tendencies with respect to both model use in learning and exploration behavior. This computational model provides novel insights into learning with interacting model-free and model-based components.

Improved Traceability of a Small Satellite Mission Concept to Requirements Using Model Based System Engineering

NASA Technical Reports Server (NTRS)

Reil, Robin L.

2014-01-01

Model Based Systems Engineering (MBSE) has recently been gaining significant support as a means to improve the "traditional" document-based systems engineering (DBSE) approach to engineering complex systems. In the spacecraft design domain, there are many perceived and propose benefits of an MBSE approach, but little analysis has been presented to determine the tangible benefits of such an approach (e.g. time and cost saved, increased product quality). This paper presents direct examples of how developing a small satellite system model can improve traceability of the mission concept to its requirements. A comparison of the processes and approaches for MBSE and DBSE is made using the NASA Ames Research Center SporeSat CubeSat mission as a case study. A model of the SporeSat mission is built using the Systems Modeling Language standard and No Magic's MagicDraw modeling tool. The model incorporates mission concept and requirement information from the mission's original DBSE design efforts. Active dependency relationships are modeled to demonstrate the completeness and consistency of the requirements to the mission concept. Anecdotal information and process-duration metrics are presented for both the MBSE and original DBSE design efforts of SporeSat.

Improved Traceability of Mission Concept to Requirements Using Model Based Systems Engineering

NASA Technical Reports Server (NTRS)

Reil, Robin

2014-01-01

Model Based Systems Engineering (MBSE) has recently been gaining significant support as a means to improve the traditional document-based systems engineering (DBSE) approach to engineering complex systems. In the spacecraft design domain, there are many perceived and propose benefits of an MBSE approach, but little analysis has been presented to determine the tangible benefits of such an approach (e.g. time and cost saved, increased product quality). This thesis presents direct examples of how developing a small satellite system model can improve traceability of the mission concept to its requirements. A comparison of the processes and approaches for MBSE and DBSE is made using the NASA Ames Research Center SporeSat CubeSat mission as a case study. A model of the SporeSat mission is built using the Systems Modeling Language standard and No Magics MagicDraw modeling tool. The model incorporates mission concept and requirement information from the missions original DBSE design efforts. Active dependency relationships are modeled to analyze the completeness and consistency of the requirements to the mission concept. Overall experience and methodology are presented for both the MBSE and original DBSE design efforts of SporeSat.

A Model-Driven Visualization Tool for Use with Model-Based Systems Engineering Projects

NASA Technical Reports Server (NTRS)

Trase, Kathryn; Fink, Eric

2014-01-01

Model-Based Systems Engineering (MBSE) promotes increased consistency between a system's design and its design documentation through the use of an object-oriented system model. The creation of this system model facilitates data presentation by providing a mechanism from which information can be extracted by automated manipulation of model content. Existing MBSE tools enable model creation, but are often too complex for the unfamiliar model viewer to easily use. These tools do not yet provide many opportunities for easing into the development and use of a system model when system design documentation already exists. This study creates a Systems Modeling Language (SysML) Document Traceability Framework (SDTF) for integrating design documentation with a system model, and develops an Interactive Visualization Engine for SysML Tools (InVEST), that exports consistent, clear, and concise views of SysML model data. These exported views are each meaningful to a variety of project stakeholders with differing subjects of concern and depth of technical involvement. InVEST allows a model user to generate multiple views and reports from a MBSE model, including wiki pages and interactive visualizations of data. System data can also be filtered to present only the information relevant to the particular stakeholder, resulting in a view that is both consistent with the larger system model and other model views. Viewing the relationships between system artifacts and documentation, and filtering through data to see specialized views improves the value of the system as a whole, as data becomes information

Machine Learning

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

Chikkagoudar, Satish; Chatterjee, Samrat; Thomas, Dennis G.

The absence of a robust and unified theory of cyber dynamics presents challenges and opportunities for using machine learning based data-driven approaches to further the understanding of the behavior of such complex systems. Analysts can also use machine learning approaches to gain operational insights. In order to be operationally beneficial, cybersecurity machine learning based models need to have the ability to: (1) represent a real-world system, (2) infer system properties, and (3) learn and adapt based on expert knowledge and observations. Probabilistic models and Probabilistic graphical models provide these necessary properties and are further explored in this chapter. Bayesian Networksmore » and Hidden Markov Models are introduced as an example of a widely used data driven classification/modeling strategy.« less

Quasi-dynamic earthquake fault systems with rheological heterogeneity

NASA Astrophysics Data System (ADS)

Brietzke, G. B.; Hainzl, S.; Zoeller, G.; Holschneider, M.

2009-12-01

Seismic risk and hazard estimates mostly use pure empirical, stochastic models of earthquake fault systems tuned specifically to the vulnerable areas of interest. Although such models allow for reasonable risk estimates, such models cannot allow for physical statements of the described seismicity. In contrary such empirical stochastic models, physics based earthquake fault systems models allow for a physical reasoning and interpretation of the produced seismicity and system dynamics. Recently different fault system earthquake simulators based on frictional stick-slip behavior have been used to study effects of stress heterogeneity, rheological heterogeneity, or geometrical complexity on earthquake occurrence, spatial and temporal clustering of earthquakes, and system dynamics. Here we present a comparison of characteristics of synthetic earthquake catalogs produced by two different formulations of quasi-dynamic fault system earthquake simulators. Both models are based on discretized frictional faults embedded in an elastic half-space. While one (1) is governed by rate- and state-dependent friction with allowing three evolutionary stages of independent fault patches, the other (2) is governed by instantaneous frictional weakening with scheduled (and therefore causal) stress transfer. We analyze spatial and temporal clustering of events and characteristics of system dynamics by means of physical parameters of the two approaches.

Archetype-based conversion of EHR content models: pilot experience with a regional EHR system.

PubMed

Chen, Rong; Klein, Gunnar O; Sundvall, Erik; Karlsson, Daniel; Ahlfeldt, Hans

2009-07-01

Exchange of Electronic Health Record (EHR) data between systems from different suppliers is a major challenge. EHR communication based on archetype methodology has been developed by openEHR and CEN/ISO. The experience of using archetypes in deployed EHR systems is quite limited today. Currently deployed EHR systems with large user bases have their own proprietary way of representing clinical content using various models. This study was designed to investigate the feasibility of representing EHR content models from a regional EHR system as openEHR archetypes and inversely to convert archetypes to the proprietary format. The openEHR EHR Reference Model (RM) and Archetype Model (AM) specifications were used. The template model of the Cambio COSMIC, a regional EHR product from Sweden, was analyzed and compared to the openEHR RM and AM. This study was focused on the convertibility of the EHR semantic models. A semantic mapping between the openEHR RM/AM and the COSMIC template model was produced and used as the basis for developing prototype software that performs automated bi-directional conversion between openEHR archetypes and COSMIC templates. Automated bi-directional conversion between openEHR archetype format and COSMIC template format has been achieved. Several archetypes from the openEHR Clinical Knowledge Repository have been imported into COSMIC, preserving most of the structural and terminology related constraints. COSMIC templates from a large regional installation were successfully converted into the openEHR archetype format. The conversion from the COSMIC templates into archetype format preserves nearly all structural and semantic definitions of the original content models. A strategy of gradually adding archetype support to legacy EHR systems was formulated in order to allow sharing of clinical content models defined using different formats. The openEHR RM and AM are expressive enough to represent the existing clinical content models from the template based EHR system tested and legacy content models can automatically be converted to archetype format for sharing of knowledge. With some limitations, internationally available archetypes could be converted to the legacy EHR models. Archetype support can be added to legacy EHR systems in an incremental way allowing a migration path to interoperability based on standards.

Dynamic Gate Product and Artifact Generation from System Models

NASA Technical Reports Server (NTRS)

Jackson, Maddalena; Delp, Christopher; Bindschadler, Duane; Sarrel, Marc; Wollaeger, Ryan; Lam, Doris

2011-01-01

Model Based Systems Engineering (MBSE) is gaining acceptance as a way to formalize systems engineering practice through the use of models. The traditional method of producing and managing a plethora of disjointed documents and presentations ("Power-Point Engineering") has proven both costly and limiting as a means to manage the complex and sophisticated specifications of modern space systems. We have developed a tool and method to produce sophisticated artifacts as views and by-products of integrated models, allowing us to minimize the practice of "Power-Point Engineering" from model-based projects and demonstrate the ability of MBSE to work within and supersede traditional engineering practices. This paper describes how we have created and successfully used model-based document generation techniques to extract paper artifacts from complex SysML and UML models in support of successful project reviews. Use of formal SysML and UML models for architecture and system design enables production of review documents, textual artifacts, and analyses that are consistent with one-another and require virtually no labor-intensive maintenance across small-scale design changes and multiple authors. This effort thus enables approaches that focus more on rigorous engineering work and less on "PowerPoint engineering" and production of paper-based documents or their "office-productivity" file equivalents.

Analysis of Effects of Organizational Behavior on Evolving System of Systems Acquisition Programs Through Agent Based Modeling

DTIC Science & Technology

2013-03-01

function is based on how individualistic or collectivistic a system is. Low individualism values mean the system is more collective and is less likely...Hofstede’s cultural dimensions, integrated with a modified version of the Bak- Sneppen biological evolutionary model, this research highlights which set...14 Hofstede’s Cultural Dimensions

Model-Based Engineering for Supply Chain Risk Management

DTIC Science & Technology

2015-09-30

Privacy, 2009 [19] Julien Delange Wheel Brake System Example using AADL; Feiler, Peter; Hansson, Jörgen; de Niz, Dionisio; & Wrage, Lutz. System ...University Software Engineering Institute Abstract—Expanded use of commercial components has increased the complexity of system assurance...verification. Model- based engineering (MBE) offers a means to design, develop, analyze, and maintain a complex system architecture. Architecture Analysis

Trace Assessment for BWR ATWS Analysis

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

Cheng, L.Y.; Diamond, D.; Arantxa Cuadra, Gilad Raitses, Arnold Aronson

2010-04-22

A TRACE/PARCS input model has been developed in order to be able to analyze anticipated transients without scram (ATWS) in a boiling water reactor. The model is based on one developed previously for the Browns Ferry reactor for doing loss-of-coolant accident analysis. This model was updated by adding the control systems needed for ATWS and a core model using PARCS. The control systems were based on models previously developed for the TRAC-B code. The PARCS model is based on information (e.g., exposure and moderator density (void) history distributions) obtained from General Electric Hitachi and cross sections for GE14 fuel obtainedmore » from an independent source. The model is able to calculate an ATWS, initiated by the closure of main steam isolation valves, with recirculation pump trip, water level control, injection of borated water from the standby liquid control system and actuation of the automatic depres-surization system. The model is not considered complete and recommendations are made on how it should be improved.« less

A model-driven approach to information security compliance

NASA Astrophysics Data System (ADS)

Correia, Anacleto; Gonçalves, António; Teodoro, M. Filomena

2017-06-01

The availability, integrity and confidentiality of information are fundamental to the long-term survival of any organization. Information security is a complex issue that must be holistically approached, combining assets that support corporate systems, in an extended network of business partners, vendors, customers and other stakeholders. This paper addresses the conception and implementation of information security systems, conform the ISO/IEC 27000 set of standards, using the model-driven approach. The process begins with the conception of a domain level model (computation independent model) based on information security vocabulary present in the ISO/IEC 27001 standard. Based on this model, after embedding in the model mandatory rules for attaining ISO/IEC 27001 conformance, a platform independent model is derived. Finally, a platform specific model serves the base for testing the compliance of information security systems with the ISO/IEC 27000 set of standards.

Knowledge representation to support reasoning based on multiple models

NASA Technical Reports Server (NTRS)

Gillam, April; Seidel, Jorge P.; Parker, Alice C.

1990-01-01

Model Based Reasoning is a powerful tool used to design and analyze systems, which are often composed of numerous interactive, interrelated subsystems. Models of the subsystems are written independently and may be used together while they are still under development. Thus the models are not static. They evolve as information becomes obsolete, as improved artifact descriptions are developed, and as system capabilities change. Researchers are using three methods to support knowledge/data base growth, to track the model evolution, and to handle knowledge from diverse domains. First, the representation methodology is based on having pools, or types, of knowledge from which each model is constructed. In addition information is explicit. This includes the interactions between components, the description of the artifact structure, and the constraints and limitations of the models. The third principle we have followed is the separation of the data and knowledge from the inferencing and equation solving mechanisms. This methodology is used in two distinct knowledge-based systems: one for the design of space systems and another for the synthesis of VLSI circuits. It has facilitated the growth and evolution of our models, made accountability of results explicit, and provided credibility for the user community. These capabilities have been implemented and are being used in actual design projects.

The development of a tele-monitoring system for physiological parameters based on the B/S model.

PubMed

Shuicai, Wu; Peijie, Jiang; Chunlan, Yang; Haomin, Li; Yanping, Bai

2010-01-01

The development of a new physiological multi-parameter remote monitoring system is based on the B/S model. The system consists of a server monitoring center, Internet network and PC-based multi-parameter monitors. Using the B/S model, the clients can browse web pages via the server monitoring center and download and install ActiveX controls. The physiological multi-parameters are collected, displayed and remotely transmitted. The experimental results show that the system is stable, reliable and operates in real time. The system is suitable for use in physiological multi-parameter remote monitoring for family and community healthcare. Copyright © 2010 Elsevier Ltd. All rights reserved.

Milestone-specific, Observed data points for evaluating levels of performance (MODEL) assessment strategy for anesthesiology residency programs.

PubMed

Nagy, Christopher J; Fitzgerald, Brian M; Kraus, Gregory P

2014-01-01

Anesthesiology residency programs will be expected to have Milestones-based evaluation systems in place by July 2014 as part of the Next Accreditation System. The San Antonio Uniformed Services Health Education Consortium (SAUSHEC) anesthesiology residency program developed and implemented a Milestones-based feedback and evaluation system a year ahead of schedule. It has been named the Milestone-specific, Observed Data points for Evaluating Levels of performance (MODEL) assessment strategy. The "MODEL Menu" and the "MODEL Blueprint" are tools that other anesthesiology residency programs can use in developing their own Milestones-based feedback and evaluation systems prior to ACGME-required implementation. Data from our early experience with the streamlined MODEL blueprint assessment strategy showed substantially improved faculty compliance with reporting requirements. The MODEL assessment strategy provides programs with a workable assessment method for residents, and important Milestones data points to programs for ACGME reporting.

Flatness-based control and Kalman filtering for a continuous-time macroeconomic model

NASA Astrophysics Data System (ADS)

Rigatos, G.; Siano, P.; Ghosh, T.; Busawon, K.; Binns, R.

2017-11-01

The article proposes flatness-based control for a nonlinear macro-economic model of the UK economy. The differential flatness properties of the model are proven. This enables to introduce a transformation (diffeomorphism) of the system's state variables and to express the state-space description of the model in the linear canonical (Brunowsky) form in which both the feedback control and the state estimation problem can be solved. For the linearized equivalent model of the macroeconomic system, stabilizing feedback control can be achieved using pole placement methods. Moreover, to implement stabilizing feedback control of the system by measuring only a subset of its state vector elements the Derivative-free nonlinear Kalman Filter is used. This consists of the Kalman Filter recursion applied on the linearized equivalent model of the financial system and of an inverse transformation that is based again on differential flatness theory. The asymptotic stability properties of the control scheme are confirmed.

Formal implementation of a performance evaluation model for the face recognition system.

PubMed

Shin, Yong-Nyuo; Kim, Jason; Lee, Yong-Jun; Shin, Woochang; Choi, Jin-Young

2008-01-01

Due to usability features, practical applications, and its lack of intrusiveness, face recognition technology, based on information, derived from individuals' facial features, has been attracting considerable attention recently. Reported recognition rates of commercialized face recognition systems cannot be admitted as official recognition rates, as they are based on assumptions that are beneficial to the specific system and face database. Therefore, performance evaluation methods and tools are necessary to objectively measure the accuracy and performance of any face recognition system. In this paper, we propose and formalize a performance evaluation model for the biometric recognition system, implementing an evaluation tool for face recognition systems based on the proposed model. Furthermore, we performed evaluations objectively by providing guidelines for the design and implementation of a performance evaluation system, formalizing the performance test process.

77 FR 25904 - Acequinocyl; Pesticide Tolerances

Federal Register 2010, 2011, 2012, 2013, 2014

2012-05-02

.../oppefed1/models/water/index.htm . Based on the Pesticide Root Zone Model/Exposure Analysis Modeling System... Classification System (NAICS) codes have been provided to assist you and others in determining whether this... comments received in response to the notice of filing. Based upon review of the data supporting the...

Development and evaluation of a physics-based windblown dust emission scheme implemented in the CMAQ modeling system

EPA Science Inventory

A new windblown dust emission treatment was incorporated in the Community Multiscale Air Quality (CMAQ) modeling system. This new model treatment has been built upon previously developed physics-based parameterization schemes from the literature. A distinct and novel feature of t...

Update on Small Modular Reactors Dynamic System Modeling Tool: Web Application

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

Hale, Richard Edward; Cetiner, Sacit M.; Fugate, David L.

Previous reports focused on the development of component and system models as well as end-to-end system models using Modelica and Dymola for two advanced reactor architectures: (1) Advanced Liquid Metal Reactor and (2) fluoride high-temperature reactor (FHR). The focus of this report is the release of the first beta version of the web-based application for model use and collaboration, as well as an update on the FHR model. The web-based application allows novice users to configure end-to-end system models from preconfigured choices to investigate the instrumentation and controls implications of these designs and allows for the collaborative development of individualmore » component models that can be benchmarked against test systems for potential inclusion in the model library. A description of this application is provided along with examples of its use and a listing and discussion of all the models that currently exist in the library.« less

Active imaging system performance model for target acquisition

NASA Astrophysics Data System (ADS)

Espinola, Richard L.; Teaney, Brian; Nguyen, Quang; Jacobs, Eddie L.; Halford, Carl E.; Tofsted, David H.

2007-04-01

The U.S. Army RDECOM CERDEC Night Vision & Electronic Sensors Directorate has developed a laser-range-gated imaging system performance model for the detection, recognition, and identification of vehicle targets. The model is based on the established US Army RDECOM CERDEC NVESD sensor performance models of the human system response through an imaging system. The Java-based model, called NVLRG, accounts for the effect of active illumination, atmospheric attenuation, and turbulence effects relevant to LRG imagers, such as speckle and scintillation, and for the critical sensor and display components. This model can be used to assess the performance of recently proposed active SWIR systems through various trade studies. This paper will describe the NVLRG model in detail, discuss the validation of recent model components, present initial trade study results, and outline plans to validate and calibrate the end-to-end model with field data through human perception testing.

Use case driven approach to develop simulation model for PCS of APR1400 simulator

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

Dong Wook, Kim; Hong Soo, Kim; Hyeon Tae, Kang

2006-07-01

The full-scope simulator is being developed to evaluate specific design feature and to support the iterative design and validation in the Man-Machine Interface System (MMIS) design of Advanced Power Reactor (APR) 1400. The simulator consists of process model, control logic model, and MMI for the APR1400 as well as the Power Control System (PCS). In this paper, a use case driven approach is proposed to develop a simulation model for PCS. In this approach, a system is considered from the point of view of its users. User's view of the system is based on interactions with the system and themore » resultant responses. In use case driven approach, we initially consider the system as a black box and look at its interactions with the users. From these interactions, use cases of the system are identified. Then the system is modeled using these use cases as functions. Lower levels expand the functionalities of each of these use cases. Hence, starting from the topmost level view of the system, we proceeded down to the lowest level (the internal view of the system). The model of the system thus developed is use case driven. This paper will introduce the functionality of the PCS simulation model, including a requirement analysis based on use case and the validation result of development of PCS model. The PCS simulation model using use case will be first used during the full-scope simulator development for nuclear power plant and will be supplied to Shin-Kori 3 and 4 plant. The use case based simulation model development can be useful for the design and implementation of simulation models. (authors)« less

Combining Interactive Infrastructure Modeling and Evolutionary Algorithm Optimization for Sustainable Water Resources Design

NASA Astrophysics Data System (ADS)

Smith, R.; Kasprzyk, J. R.; Zagona, E. A.

2013-12-01

Population growth and climate change, combined with difficulties in building new infrastructure, motivate portfolio-based solutions to ensuring sufficient water supply. Powerful simulation models with graphical user interfaces (GUI) are often used to evaluate infrastructure portfolios; these GUI based models require manual modification of the system parameters, such as reservoir operation rules, water transfer schemes, or system capacities. Multiobjective evolutionary algorithm (MOEA) based optimization can be employed to balance multiple objectives and automatically suggest designs for infrastructure systems, but MOEA based decision support typically uses a fixed problem formulation (i.e., a single set of objectives, decisions, and constraints). This presentation suggests a dynamic framework for linking GUI-based infrastructure models with MOEA search. The framework begins with an initial formulation which is solved using a MOEA. Then, stakeholders can interact with candidate solutions, viewing their properties in the GUI model. This is followed by changes in the formulation which represent users' evolving understanding of exigent system properties. Our case study is built using RiverWare, an object-oriented, data-centered model that facilitates the representation of a diverse array of water resources systems. Results suggest that assumptions within the initial MOEA search are violated after investigating tradeoffs and reveal how formulations should be modified to better capture stakeholders' preferences.

Ionospheric Simulation System for Satellite Observations and Global Assimilative Modeling Experiments (ISOGAME)

NASA Technical Reports Server (NTRS)

Pi, Xiaoqing; Mannucci, Anthony J.; Verkhoglyadova, Olga P.; Stephens, Philip; Wilson, Brian D.; Akopian, Vardan; Komjathy, Attila; Lijima, Byron A.

2013-01-01

ISOGAME is designed and developed to assess quantitatively the impact of new observation systems on the capability of imaging and modeling the ionosphere. With ISOGAME, one can perform observation system simulation experiments (OSSEs). A typical OSSE using ISOGAME would involve: (1) simulating various ionospheric conditions on global scales; (2) simulating ionospheric measurements made from a constellation of low-Earth-orbiters (LEOs), particularly Global Navigation Satellite System (GNSS) radio occultation data, and from ground-based global GNSS networks; (3) conducting ionospheric data assimilation experiments with the Global Assimilative Ionospheric Model (GAIM); and (4) analyzing modeling results with visualization tools. ISOGAME can provide quantitative assessment of the accuracy of assimilative modeling with the interested observation system. Other observation systems besides those based on GNSS are also possible to analyze. The system is composed of a suite of software that combines the GAIM, including a 4D first-principles ionospheric model and data assimilation modules, an Internal Reference Ionosphere (IRI) model that has been developed by international ionospheric research communities, observation simulator, visualization software, and orbit design, simulation, and optimization software. The core GAIM model used in ISOGAME is based on the GAIM++ code (written in C++) that includes a new high-fidelity geomagnetic field representation (multi-dipole). New visualization tools and analysis algorithms for the OSSEs are now part of ISOGAME.

High-level PC-based laser system modeling

NASA Astrophysics Data System (ADS)

Taylor, Michael S.

1991-05-01

Since the inception of the Strategic Defense Initiative (SDI) there have been a multitude of comparison studies done in an attempt to evaluate the effectiveness and relative sizes of complementary, and sometimes competitive, laser weapon systems. It became more and more apparent that what the systems analyst needed was not only a fast, but a cost effective way to perform high-level trade studies. In the present investigation, a general procedure is presented for the development of PC-based algorithmic systems models for laser systems. This procedure points out all of the major issues that should be addressed in the design and development of such a model. Issues addressed include defining the problem to be modeled, defining a strategy for development, and finally, effective use of the model once developed. Being a general procedure, it will allow a systems analyst to develop a model to meet specific needs. To illustrate this method of model development, a description of the Strategic Defense Simulation - Design To (SDS-DT) model developed and used by Science Applications International Corporation (SAIC) is presented. SDS-DT is a menu-driven, fast executing, PC-based program that can be used to either calculate performance, weight, volume, and cost values for a particular design or, alternatively, to run parametrics on particular system parameters to perhaps optimize a design.

Exact Hybrid Particle/Population Simulation of Rule-Based Models of Biochemical Systems

PubMed Central

Stover, Lori J.; Nair, Niketh S.; Faeder, James R.

2014-01-01

Detailed modeling and simulation of biochemical systems is complicated by the problem of combinatorial complexity, an explosion in the number of species and reactions due to myriad protein-protein interactions and post-translational modifications. Rule-based modeling overcomes this problem by representing molecules as structured objects and encoding their interactions as pattern-based rules. This greatly simplifies the process of model specification, avoiding the tedious and error prone task of manually enumerating all species and reactions that can potentially exist in a system. From a simulation perspective, rule-based models can be expanded algorithmically into fully-enumerated reaction networks and simulated using a variety of network-based simulation methods, such as ordinary differential equations or Gillespie's algorithm, provided that the network is not exceedingly large. Alternatively, rule-based models can be simulated directly using particle-based kinetic Monte Carlo methods. This “network-free” approach produces exact stochastic trajectories with a computational cost that is independent of network size. However, memory and run time costs increase with the number of particles, limiting the size of system that can be feasibly simulated. Here, we present a hybrid particle/population simulation method that combines the best attributes of both the network-based and network-free approaches. The method takes as input a rule-based model and a user-specified subset of species to treat as population variables rather than as particles. The model is then transformed by a process of “partial network expansion” into a dynamically equivalent form that can be simulated using a population-adapted network-free simulator. The transformation method has been implemented within the open-source rule-based modeling platform BioNetGen, and resulting hybrid models can be simulated using the particle-based simulator NFsim. Performance tests show that significant memory savings can be achieved using the new approach and a monetary cost analysis provides a practical measure of its utility. PMID:24699269

Exact hybrid particle/population simulation of rule-based models of biochemical systems.

PubMed

Hogg, Justin S; Harris, Leonard A; Stover, Lori J; Nair, Niketh S; Faeder, James R

2014-04-01

Detailed modeling and simulation of biochemical systems is complicated by the problem of combinatorial complexity, an explosion in the number of species and reactions due to myriad protein-protein interactions and post-translational modifications. Rule-based modeling overcomes this problem by representing molecules as structured objects and encoding their interactions as pattern-based rules. This greatly simplifies the process of model specification, avoiding the tedious and error prone task of manually enumerating all species and reactions that can potentially exist in a system. From a simulation perspective, rule-based models can be expanded algorithmically into fully-enumerated reaction networks and simulated using a variety of network-based simulation methods, such as ordinary differential equations or Gillespie's algorithm, provided that the network is not exceedingly large. Alternatively, rule-based models can be simulated directly using particle-based kinetic Monte Carlo methods. This "network-free" approach produces exact stochastic trajectories with a computational cost that is independent of network size. However, memory and run time costs increase with the number of particles, limiting the size of system that can be feasibly simulated. Here, we present a hybrid particle/population simulation method that combines the best attributes of both the network-based and network-free approaches. The method takes as input a rule-based model and a user-specified subset of species to treat as population variables rather than as particles. The model is then transformed by a process of "partial network expansion" into a dynamically equivalent form that can be simulated using a population-adapted network-free simulator. The transformation method has been implemented within the open-source rule-based modeling platform BioNetGen, and resulting hybrid models can be simulated using the particle-based simulator NFsim. Performance tests show that significant memory savings can be achieved using the new approach and a monetary cost analysis provides a practical measure of its utility.

Using Model-Based Systems Engineering To Provide Artifacts for NASA Project Life-Cycle and Technical Reviews

NASA Technical Reports Server (NTRS)

Parrott, Edith L.; Weiland, Karen J.

2017-01-01

The ability of systems engineers to use model-based systems engineering (MBSE) to generate self-consistent, up-to-date systems engineering products for project life-cycle and technical reviews is an important aspect for the continued and accelerated acceptance of MBSE. Currently, many review products are generated using labor-intensive, error-prone approaches based on documents, spreadsheets, and chart sets; a promised benefit of MBSE is that users will experience reductions in inconsistencies and errors. This work examines features of SysML that can be used to generate systems engineering products. Model elements, relationships, tables, and diagrams are identified for a large number of the typical systems engineering artifacts. A SysML system model can contain and generate most systems engineering products to a significant extent and this paper provides a guide on how to use MBSE to generate products for project life-cycle and technical reviews. The use of MBSE can reduce the schedule impact usually experienced for review preparation, as in many cases the review products can be auto-generated directly from the system model. These approaches are useful to systems engineers, project managers, review board members, and other key project stakeholders.

Performance-based maintenance of gas turbines for reliable control of degraded power systems

NASA Astrophysics Data System (ADS)

Mo, Huadong; Sansavini, Giovanni; Xie, Min

2018-03-01

Maintenance actions are necessary for ensuring proper operations of control systems under component degradation. However, current condition-based maintenance (CBM) models based on component health indices are not suitable for degraded control systems. Indeed, failures of control systems are only determined by the controller outputs, and the feedback mechanism compensates the control performance loss caused by the component deterioration. Thus, control systems may still operate normally even if the component health indices exceed failure thresholds. This work investigates the CBM model of control systems and employs the reduced control performance as a direct degradation measure for deciding maintenance activities. The reduced control performance depends on the underlying component degradation modelled as a Wiener process and the feedback mechanism. To this aim, the controller features are quantified by developing a dynamic and stochastic control block diagram-based simulation model, consisting of the degraded components and the control mechanism. At each inspection, the system receives a maintenance action if the control performance deterioration exceeds its preventive-maintenance or failure thresholds. Inspired by realistic cases, the component degradation model considers random start time and unit-to-unit variability. The cost analysis of maintenance model is conducted via Monte Carlo simulation. Optimal maintenance strategies are investigated to minimize the expected maintenance costs, which is a direct consequence of the control performance. The proposed framework is able to design preventive maintenance actions on a gas power plant, to ensuring required load frequency control performance against a sudden load increase. The optimization results identify the trade-off between system downtime and maintenance costs as a function of preventive maintenance thresholds and inspection frequency. Finally, the control performance-based maintenance model can reduce maintenance costs as compared to CBM and pre-scheduled maintenance.

A modeling approach to describe ZVI-based anaerobic system.

PubMed

Xiao, Xiao; Sheng, Guo-Ping; Mu, Yang; Yu, Han-Qing

2013-10-15

Zero-valent iron (ZVI) is increasingly being added into anaerobic reactors to enhance the biological conversion of various less biodegradable pollutants (LBPs). Our study aimed to establish a new structure model based on the Anaerobic Digestion Model No. 1 (ADM1) to simulate such a ZVI-based anaerobic reactor. Three new processes, i.e., electron release from ZVI corrosion, H2 formation from ZVI corrosion, and transformation of LBPs, were integrated into ADM1. The established model was calibrated and tested using the experimental data from one published study, and validated using the data from another work. A good relationship between the predicted and measured results indicates that the proposed model was appropriate to describe the performance of the ZVI-based anaerobic system. Our model could provide more precise strategies for the design, development, and application of anaerobic systems especially for treating various LBPs-containing wastewaters. Copyright © 2013 Elsevier Ltd. All rights reserved.

Therapy for Family Systems.

ERIC Educational Resources Information Center

Rosmann, Michael R.

A family therapy model, based on a conceptualization of the family as a behavioral system whose members interact adaptively so that an optimal level of functioning is maintained within the system, is described. The divergent roots of this conceptualization are discussed briefly, as are the treatment approaches based on it. The author's model,…

An Instructional Systems Technology Model for Institutional Change.

ERIC Educational Resources Information Center

Dudgeon, Paul J.

A program based on instructional systems technology was developed at Canadore College as a means of devising the optimal learning experience for each individual student. The systems approach is used to solve educational problems through a process of analysis, synthesis, modeling, and simulation, based on the LOGOS (Language for Optimizing…

User's guide to the Reliability Estimation System Testbed (REST)

NASA Technical Reports Server (NTRS)

Nicol, David M.; Palumbo, Daniel L.; Rifkin, Adam

1992-01-01

The Reliability Estimation System Testbed is an X-window based reliability modeling tool that was created to explore the use of the Reliability Modeling Language (RML). RML was defined to support several reliability analysis techniques including modularization, graphical representation, Failure Mode Effects Simulation (FMES), and parallel processing. These techniques are most useful in modeling large systems. Using modularization, an analyst can create reliability models for individual system components. The modules can be tested separately and then combined to compute the total system reliability. Because a one-to-one relationship can be established between system components and the reliability modules, a graphical user interface may be used to describe the system model. RML was designed to permit message passing between modules. This feature enables reliability modeling based on a run time simulation of the system wide effects of a component's failure modes. The use of failure modes effects simulation enhances the analyst's ability to correctly express system behavior when using the modularization approach to reliability modeling. To alleviate the computation bottleneck often found in large reliability models, REST was designed to take advantage of parallel processing on hypercube processors.

A dynamical system of deposit and loan volumes based on the Lotka-Volterra model

NASA Astrophysics Data System (ADS)

Sumarti, N.; Nurfitriyana, R.; Nurwenda, W.

2014-02-01

In this research, we proposed a dynamical system of deposit and loan volumes of a bank using a predator-prey paradigm, where the predator is loan volumes, and the prey is deposit volumes. The existence of loan depends on the existence of deposit because the bank will allocate the loan volume from a portion of the deposit volume. The dynamical systems have been constructed are a simple model, a model with Michaelis-Menten Response and a model with the Reserve Requirement. Equilibria of the systems are analysed whether they are stable or unstable based on their linearised system.

Information Interaction Study for DER and DMS Interoperability

NASA Astrophysics Data System (ADS)

Liu, Haitao; Lu, Yiming; Lv, Guangxian; Liu, Peng; Chen, Yu; Zhang, Xinhui

The Common Information Model (CIM) is an abstract data model that can be used to represent the major objects in Distribution Management System (DMS) applications. Because the Common Information Model (CIM) doesn't modeling the Distributed Energy Resources (DERs), it can't meet the requirements of DER operation and management for Distribution Management System (DMS) advanced applications. Modeling of DER were studied based on a system point of view, the article initially proposed a CIM extended information model. By analysis the basic structure of the message interaction between DMS and DER, a bidirectional messaging mapping method based on data exchange was proposed.

Modeling of BN Lifetime Prediction of a System Based on Integrated Multi-Level Information

PubMed Central

Wang, Xiaohong; Wang, Lizhi

2017-01-01

Predicting system lifetime is important to ensure safe and reliable operation of products, which requires integrated modeling based on multi-level, multi-sensor information. However, lifetime characteristics of equipment in a system are different and failure mechanisms are inter-coupled, which leads to complex logical correlations and the lack of a uniform lifetime measure. Based on a Bayesian network (BN), a lifetime prediction method for systems that combine multi-level sensor information is proposed. The method considers the correlation between accidental failures and degradation failure mechanisms, and achieves system modeling and lifetime prediction under complex logic correlations. This method is applied in the lifetime prediction of a multi-level solar-powered unmanned system, and the predicted results can provide guidance for the improvement of system reliability and for the maintenance and protection of the system. PMID:28926930

Modeling of BN Lifetime Prediction of a System Based on Integrated Multi-Level Information.

PubMed

Wang, Jingbin; Wang, Xiaohong; Wang, Lizhi

2017-09-15

Predicting system lifetime is important to ensure safe and reliable operation of products, which requires integrated modeling based on multi-level, multi-sensor information. However, lifetime characteristics of equipment in a system are different and failure mechanisms are inter-coupled, which leads to complex logical correlations and the lack of a uniform lifetime measure. Based on a Bayesian network (BN), a lifetime prediction method for systems that combine multi-level sensor information is proposed. The method considers the correlation between accidental failures and degradation failure mechanisms, and achieves system modeling and lifetime prediction under complex logic correlations. This method is applied in the lifetime prediction of a multi-level solar-powered unmanned system, and the predicted results can provide guidance for the improvement of system reliability and for the maintenance and protection of the system.

Combining Model-driven and Schema-based Program Synthesis

NASA Technical Reports Server (NTRS)

Denney, Ewen; Whittle, John

2004-01-01

We describe ongoing work which aims to extend the schema-based program synthesis paradigm with explicit models. In this context, schemas can be considered as model-to-model transformations. The combination of schemas with explicit models offers a number of advantages, namely, that building synthesis systems becomes much easier since the models can be used in verification and in adaptation of the synthesis systems. We illustrate our approach using an example from signal processing.

Stabilization of nonlinear systems using sampled-data output-feedback fuzzy controller based on polynomial-fuzzy-model-based control approach.

PubMed

Lam, H K

2012-02-01

This paper investigates the stability of sampled-data output-feedback (SDOF) polynomial-fuzzy-model-based control systems. Representing the nonlinear plant using a polynomial fuzzy model, an SDOF fuzzy controller is proposed to perform the control process using the system output information. As only the system output is available for feedback compensation, it is more challenging for the controller design and system analysis compared to the full-state-feedback case. Furthermore, because of the sampling activity, the control signal is kept constant by the zero-order hold during the sampling period, which complicates the system dynamics and makes the stability analysis more difficult. In this paper, two cases of SDOF fuzzy controllers, which either share the same number of fuzzy rules or not, are considered. The system stability is investigated based on the Lyapunov stability theory using the sum-of-squares (SOS) approach. SOS-based stability conditions are obtained to guarantee the system stability and synthesize the SDOF fuzzy controller. Simulation examples are given to demonstrate the merits of the proposed SDOF fuzzy control approach.

Stochastic simulation of multiscale complex systems with PISKaS: A rule-based approach.

PubMed

Perez-Acle, Tomas; Fuenzalida, Ignacio; Martin, Alberto J M; Santibañez, Rodrigo; Avaria, Rodrigo; Bernardin, Alejandro; Bustos, Alvaro M; Garrido, Daniel; Dushoff, Jonathan; Liu, James H

2018-03-29

Computational simulation is a widely employed methodology to study the dynamic behavior of complex systems. Although common approaches are based either on ordinary differential equations or stochastic differential equations, these techniques make several assumptions which, when it comes to biological processes, could often lead to unrealistic models. Among others, model approaches based on differential equations entangle kinetics and causality, failing when complexity increases, separating knowledge from models, and assuming that the average behavior of the population encompasses any individual deviation. To overcome these limitations, simulations based on the Stochastic Simulation Algorithm (SSA) appear as a suitable approach to model complex biological systems. In this work, we review three different models executed in PISKaS: a rule-based framework to produce multiscale stochastic simulations of complex systems. These models span multiple time and spatial scales ranging from gene regulation up to Game Theory. In the first example, we describe a model of the core regulatory network of gene expression in Escherichia coli highlighting the continuous model improvement capacities of PISKaS. The second example describes a hypothetical outbreak of the Ebola virus occurring in a compartmentalized environment resembling cities and highways. Finally, in the last example, we illustrate a stochastic model for the prisoner's dilemma; a common approach from social sciences describing complex interactions involving trust within human populations. As whole, these models demonstrate the capabilities of PISKaS providing fertile scenarios where to explore the dynamics of complex systems. Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.

Imbalance detection in a manufacturing system: An agent-based model usage

NASA Astrophysics Data System (ADS)

Shevchuk, G. K.; Zvereva, O. M.; Medvedev, M. A.

2017-11-01

This paper delivers the results of the research work targeted at communications in a manufacturing system. A computer agent-based model which simulates manufacturing system functioning has been engineered. The system lifecycle consists of two recursively repeated stages: a communication stage and a production stage. Model data sets were estimated with the static Leontief's equilibrium equation usage. In experiments relationships between the manufacturing system lifecycle time and conditions of equilibrium violations have been identified. The research results are to be used to propose violation negative influence compensation methods.

Utilization-Based Modeling and Optimization for Cognitive Radio Networks

NASA Astrophysics Data System (ADS)

Liu, Yanbing; Huang, Jun; Liu, Zhangxiong

The cognitive radio technique promises to manage and allocate the scarce radio spectrum in the highly varying and disparate modern environments. This paper considers a cognitive radio scenario composed of two queues for the primary (licensed) users and cognitive (unlicensed) users. According to the Markov process, the system state equations are derived and an optimization model for the system is proposed. Next, the system performance is evaluated by calculations which show the rationality of our system model. Furthermore, discussions among different parameters for the system are presented based on the experimental results.

Application of a Genetic Algorithm and Multi Agent System to Explore Emergent Patterns of Social Rationality and a Distress-Based Model for Deceit in the Workplace

DTIC Science & Technology

2008-06-01

postponed the fulfillment of her own Masters Degree by at least 18 months so that I would have the opportunity to earn mine. She is smart , lovely...GENETIC ALGORITHM AND MULTI AGENT SYSTEM TO EXPLORE EMERGENT PATTERNS OF SOCIAL RATIONALITY AND A DISTRESS-BASED MODEL FOR DECEIT IN THE WORKPLACE...of a Genetic Algorithm and Mutli Agent System to Explore Emergent Patterns of Social Rationality and a Distress-Based Model for Deceit in the

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.

Behavioral modeling of VCSELs for high-speed optical interconnects

NASA Astrophysics Data System (ADS)

Szczerba, Krzysztof; Kocot, Chris

2018-02-01

Transition from on-off keying to 4-level pulse amplitude modulation (PAM) in VCSEL based optical interconnects allows for an increase of data rates, at the cost of 4.8 dB sensitivity penalty. The resulting strained link budget creates a need for accurate VCSEL models for driver integrated circuit (IC) design and system level simulations. Rate equation based equivalent circuit models are convenient for the IC design, but system level analysis requires computationally efficient closed form behavioral models based Volterra series and neural networks. In this paper we present and compare these models.

Model-Based Diagnosis in a Power Distribution Test-Bed

NASA Technical Reports Server (NTRS)

Scarl, E.; McCall, K.

1998-01-01

The Rodon model-based diagnosis shell was applied to a breadboard test-bed, modeling an automated power distribution system. The constraint-based modeling paradigm and diagnostic algorithm were found to adequately represent the selected set of test scenarios.

Enhancements to the KATE model-based reasoning system

NASA Technical Reports Server (NTRS)

Thomas, Stan J.

1994-01-01

KATE (Knowledge-based Autonomous Test Engineer) is a model-based software system developed in the Artificial Intelligence Laboratory at the Kennedy Space Center for monitoring, fault detection, and control of launch vehicles and ground support systems. This report describes two software efforts which enhance the functionality and usability of KATE. The first addition, a flow solver, adds to KATE a tool for modeling the flow of liquid in a pipe system. The second addition adds support for editing KATE knowledge base files to the Emacs editor. The body of this report discusses design and implementation issues having to do with these two tools. It will be useful to anyone maintaining or extending either the flow solver or the editor enhancements.

Flexible system model reduction and control system design based upon actuator and sensor influence functions

NASA Technical Reports Server (NTRS)

Yam, Yeung; Johnson, Timothy L.; Lang, Jeffrey H.

1987-01-01

A model reduction technique based on aggregation with respect to sensor and actuator influence functions rather than modes is presented for large systems of coupled second-order differential equations. Perturbation expressions which can predict the effects of spillover on both the reduced-order plant model and the neglected plant model are derived. For the special case of collocated actuators and sensors, these expressions lead to the derivation of constraints on the controller gains that are, given the validity of the perturbation technique, sufficient to guarantee the stability of the closed-loop system. A case study demonstrates the derivation of stabilizing controllers based on the present technique. The use of control and observation synthesis in modifying the dimension of the reduced-order plant model is also discussed. A numerical example is provided for illustration.

Understanding Elementary Astronomy by Making Drawing-Based Models

ERIC Educational Resources Information Center

van Joolingen, W. R.; Aukes, Annika V.; Gijlers, H.; Bollen, L.

2015-01-01

Modeling is an important approach in the teaching and learning of science. In this study, we attempt to bring modeling within the reach of young children by creating the SimSketch modeling system, which is based on freehand drawings that can be turned into simulations. This system was used by 247 children (ages ranging from 7 to 15) to create a…

A Model of Process-Based Automation: Cost and Quality Implications in the Medication Management Process

ERIC Educational Resources Information Center

Spaulding, Trent Joseph

2011-01-01

The objective of this research is to understand how a set of systems, as defined by the business process, creates value. The three studies contained in this work develop the model of process-based automation. The model states that complementarities among systems are specified by handoffs in the business process. The model also provides theory to…

Research and Design of the Three-tier Distributed Network Management System Based on COM / COM + and DNA

NASA Astrophysics Data System (ADS)

Liang, Likai; Bi, Yushen

Considered on the distributed network management system's demand of high distributives, extensibility and reusability, a framework model of Three-tier distributed network management system based on COM/COM+ and DNA is proposed, which adopts software component technology and N-tier application software framework design idea. We also give the concrete design plan of each layer of this model. Finally, we discuss the internal running process of each layer in the distributed network management system's framework model.

Software for occupational health and safety risk analysis based on a fuzzy model.

PubMed

Stefanovic, Miladin; Tadic, Danijela; Djapan, Marko; Macuzic, Ivan

2012-01-01

Risk and safety management are very important issues in healthcare systems. Those are complex systems with many entities, hazards and uncertainties. In such an environment, it is very hard to introduce a system for evaluating and simulating significant hazards. In this paper, we analyzed different types of hazards in healthcare systems and we introduced a new fuzzy model for evaluating and ranking hazards. Finally, we presented a developed software solution, based on the suggested fuzzy model for evaluating and monitoring risk.

Space station ECLSS integration analysis: Simplified General Cluster Systems Model, ECLS System Assessment Program enhancements

NASA Technical Reports Server (NTRS)

Ferguson, R. E.

1985-01-01

The data base verification of the ECLS Systems Assessment Program (ESAP) was documented and changes made to enhance the flexibility of the water recovery subsystem simulations are given. All changes which were made to the data base values are described and the software enhancements performed. The refined model documented herein constitutes the submittal of the General Cluster Systems Model. A source listing of the current version of ESAP is provided in Appendix A.

Model based manipulator control

NASA Technical Reports Server (NTRS)

Petrosky, Lyman J.; Oppenheim, Irving J.

1989-01-01

The feasibility of using model based control (MBC) for robotic manipulators was investigated. A double inverted pendulum system was constructed as the experimental system for a general study of dynamically stable manipulation. The original interest in dynamically stable systems was driven by the objective of high vertical reach (balancing), and the planning of inertially favorable trajectories for force and payload demands. The model-based control approach is described and the results of experimental tests are summarized. Results directly demonstrate that MBC can provide stable control at all speeds of operation and support operations requiring dynamic stability such as balancing. The application of MBC to systems with flexible links is also discussed.

Multilingual Medical Data Models in ODM Format

PubMed Central

Breil, B.; Kenneweg, J.; Fritz, F.; Bruland, P.; Doods, D.; Trinczek, B.; Dugas, M.

2012-01-01

Background Semantic interoperability between routine healthcare and clinical research is an unsolved issue, as information systems in the healthcare domain still use proprietary and site-specific data models. However, information exchange and data harmonization are essential for physicians and scientists if they want to collect and analyze data from different hospitals in order to build up registries and perform multicenter clinical trials. Consequently, there is a need for a standardized metadata exchange based on common data models. Currently this is mainly done by informatics experts instead of medical experts. Objectives We propose to enable physicians to exchange, rate, comment and discuss their own medical data models in a collaborative web-based repository of medical forms in a standardized format. Methods Based on a comprehensive requirement analysis, a web-based portal for medical data models was specified. In this context, a data model is the technical specification (attributes, data types, value lists) of a medical form without any layout information. The CDISC Operational Data Model (ODM) was chosen as the appropriate format for the standardized representation of data models. The system was implemented with Ruby on Rails and applies web 2.0 technologies to provide a community based solution. Forms from different source systems – both routine care and clinical research – were converted into ODM format and uploaded into the portal. Results A portal for medical data models based on ODM-files was implemented (http://www.medical-data-models.org). Physicians are able to upload, comment, rate and download medical data models. More than 250 forms with approximately 8000 items are provided in different views (overview and detailed presentation) and in multiple languages. For instance, the portal contains forms from clinical and research information systems. Conclusion The portal provides a system-independent repository for multilingual data models in ODM format which can be used by physicians. It serves as a platform for discussion and enables the exchange of multilingual medical data models in a standardized way. PMID:23620720

Evaluation of an ARPS-based canopy flow modeling system for use in future operational smoke prediction efforts

Treesearch

M. T. Kiefer; S. Zhong; W. E. Heilman; J. J. Charney; X. Bian

2013-01-01

Efforts to develop a canopy flow modeling system based on the Advanced Regional Prediction System (ARPS) model are discussed. The standard version of ARPS is modified to account for the effect of drag forces on mean and turbulent flow through a vegetation canopy, via production and sink terms in the momentum and subgrid-scale turbulent kinetic energy (TKE) equations....

Completing and Adapting Models of Biological Processes

NASA Technical Reports Server (NTRS)

Margaria, Tiziana; Hinchey, Michael G.; Raffelt, Harald; Rash, James L.; Rouff, Christopher A.; Steffen, Bernhard

2006-01-01

We present a learning-based method for model completion and adaptation, which is based on the combination of two approaches: 1) R2D2C, a technique for mechanically transforming system requirements via provably equivalent models to running code, and 2) automata learning-based model extrapolation. The intended impact of this new combination is to make model completion and adaptation accessible to experts of the field, like biologists or engineers. The principle is briefly illustrated by generating models of biological procedures concerning gene activities in the production of proteins, although the main application is going to concern autonomic systems for space exploration.

Evolvable social agents for bacterial systems modeling.

PubMed

Paton, Ray; Gregory, Richard; Vlachos, Costas; Saunders, Jon; Wu, Henry

2004-09-01

We present two approaches to the individual-based modeling (IbM) of bacterial ecologies and evolution using computational tools. The IbM approach is introduced, and its important complementary role to biosystems modeling is discussed. A fine-grained model of bacterial evolution is then presented that is based on networks of interactivity between computational objects representing genes and proteins. This is followed by a coarser grained agent-based model, which is designed to explore the evolvability of adaptive behavioral strategies in artificial bacteria represented by learning classifier systems. The structure and implementation of the two proposed individual-based bacterial models are discussed, and some results from simulation experiments are presented, illustrating their adaptive properties.

Making the most of MBSE: pragmatic model-based engineering for the SKA Telescope Manager

NASA Astrophysics Data System (ADS)

Le Roux, Gerhard; Bridger, Alan; MacIntosh, Mike; Nicol, Mark; Schnetler, Hermine; Williams, Stewart

2016-08-01

Many large projects including major astronomy projects are adopting a Model Based Systems Engineering approach. How far is it possible to get value for the effort involved in developing a model that accurately represents a significant project such as SKA? Is it possible for such a large project to ensure that high-level requirements are traceable through the various system-engineering artifacts? Is it possible to utilize the tools available to produce meaningful measures for the impact of change? This paper shares one aspect of the experience gained on the SKA project. It explores some of the recommended and pragmatic approaches developed, to get the maximum value from the modeling activity while designing the Telescope Manager for the SKA. While it is too early to provide specific measures of success, certain areas are proving to be the most helpful and offering significant potential over the lifetime of the project. The experience described here has been on the 'Cameo Systems Modeler' tool-set, supporting a SysML based System Engineering approach; however the concepts and ideas covered would potentially be of value to any large project considering a Model based approach to their Systems Engineering.

Integrating 3D geological information with a national physically-based hydrological modelling system

NASA Astrophysics Data System (ADS)

Lewis, Elizabeth; Parkin, Geoff; Kessler, Holger; Whiteman, Mark

2016-04-01

Robust numerical models are an essential tool for informing flood and water management and policy around the world. Physically-based hydrological models have traditionally not been used for such applications due to prohibitively large data, time and computational resource requirements. Given recent advances in computing power and data availability, a robust, physically-based hydrological modelling system for Great Britain using the SHETRAN model and national datasets has been created. Such a model has several advantages over less complex systems. Firstly, compared with conceptual models, a national physically-based model is more readily applicable to ungauged catchments, in which hydrological predictions are also required. Secondly, the results of a physically-based system may be more robust under changing conditions such as climate and land cover, as physical processes and relationships are explicitly accounted for. Finally, a fully integrated surface and subsurface model such as SHETRAN offers a wider range of applications compared with simpler schemes, such as assessments of groundwater resources, sediment and nutrient transport and flooding from multiple sources. As such, SHETRAN provides a robust means of simulating numerous terrestrial system processes which will add physical realism when coupled to the JULES land surface model. 306 catchments spanning Great Britain have been modelled using this system. The standard configuration of this system performs satisfactorily (NSE > 0.5) for 72% of catchments and well (NSE > 0.7) for 48%. Many of the remaining 28% of catchments that performed relatively poorly (NSE < 0.5) are located in the chalk in the south east of England. As such, the British Geological Survey 3D geology model for Great Britain (GB3D) has been incorporated, for the first time in any hydrological model, to pave the way for improvements to be made to simulations of catchments with important groundwater regimes. This coupling has involved development of software to allow for easy incorporation of geological information into SHETRAN for any model setup. The addition of more realistic subsurface representation following this approach is shown to greatly improve model performance in areas dominated by groundwater processes. The resulting modelling system has great potential to be used as a resource at national, regional and local scales in an array of different applications, including climate change impact assessments, land cover change studies and integrated assessments of groundwater and surface water resources.

Model-free and model-based reward prediction errors in EEG.

PubMed

Sambrook, Thomas D; Hardwick, Ben; Wills, Andy J; Goslin, Jeremy

2018-05-24

Learning theorists posit two reinforcement learning systems: model-free and model-based. Model-based learning incorporates knowledge about structure and contingencies in the world to assign candidate actions with an expected value. Model-free learning is ignorant of the world's structure; instead, actions hold a value based on prior reinforcement, with this value updated by expectancy violation in the form of a reward prediction error. Because they use such different learning mechanisms, it has been previously assumed that model-based and model-free learning are computationally dissociated in the brain. However, recent fMRI evidence suggests that the brain may compute reward prediction errors to both model-free and model-based estimates of value, signalling the possibility that these systems interact. Because of its poor temporal resolution, fMRI risks confounding reward prediction errors with other feedback-related neural activity. In the present study, EEG was used to show the presence of both model-based and model-free reward prediction errors and their place in a temporal sequence of events including state prediction errors and action value updates. This demonstration of model-based prediction errors questions a long-held assumption that model-free and model-based learning are dissociated in the brain. Copyright © 2018 Elsevier Inc. All rights reserved.

Online model-based diagnosis to support autonomous operation of an advanced life support system.

PubMed

Biswas, Gautam; Manders, Eric-Jan; Ramirez, John; Mahadevan, Nagabhusan; Abdelwahed, Sherif

2004-01-01

This article describes methods for online model-based diagnosis of subsystems of the advanced life support system (ALS). The diagnosis methodology is tailored to detect, isolate, and identify faults in components of the system quickly so that fault-adaptive control techniques can be applied to maintain system operation without interruption. We describe the components of our hybrid modeling scheme and the diagnosis methodology, and then demonstrate the effectiveness of this methodology by building a detailed model of the reverse osmosis (RO) system of the water recovery system (WRS) of the ALS. This model is validated with real data collected from an experimental testbed at NASA JSC. A number of diagnosis experiments run on simulated faulty data are presented and the results are discussed.

Online model-based diagnosis to support autonomous operation of an advanced life support system

NASA Technical Reports Server (NTRS)

Biswas, Gautam; Manders, Eric-Jan; Ramirez, John; Mahadevan, Nagabhusan; Abdelwahed, Sherif

2004-01-01

This article describes methods for online model-based diagnosis of subsystems of the advanced life support system (ALS). The diagnosis methodology is tailored to detect, isolate, and identify faults in components of the system quickly so that fault-adaptive control techniques can be applied to maintain system operation without interruption. We describe the components of our hybrid modeling scheme and the diagnosis methodology, and then demonstrate the effectiveness of this methodology by building a detailed model of the reverse osmosis (RO) system of the water recovery system (WRS) of the ALS. This model is validated with real data collected from an experimental testbed at NASA JSC. A number of diagnosis experiments run on simulated faulty data are presented and the results are discussed.

Flexible data registration and automation in semiconductor production

NASA Astrophysics Data System (ADS)

Dudde, Ralf; Staudt-Fischbach, Peter; Kraemer, Benedict

1997-08-01

The need for cost reduction and flexibility in semiconductor production will result in a wider application of computer based automation systems. With the setup of a new and advanced CMOS semiconductor line in the Fraunhofer Institute for Silicon Technology [ISIT, Itzehoe (D)] a new line information system (LIS) was introduced based on an advanced model for the underlying data structure. This data model was implemented into an ORACLE-RDBMS. A cellworks based system (JOSIS) was used for the integration of the production equipment, communication and automated database bookings and information retrievals. During the ramp up of the production line this new system is used for the fab control. The data model and the cellworks based system integration is explained. This system enables an on-line overview of the work in progress in the fab, lot order history and equipment status and history. Based on this figures improved production and cost monitoring and optimization is possible. First examples of the information gained by this system are presented. The modular set-up of the LIS system will allow easy data exchange with additional software tools like scheduler, different fab control systems like PROMIS and accounting systems like SAP. Modifications necessary for the integration of PROMIS are described.

Performance Investigation of FSO-OFDM Communication Systems under the Heavy Rain Weather

NASA Astrophysics Data System (ADS)

Rashidi, Florence; He, Jing; Chen, Lin

2017-12-01

The challenge in the free-space optical (FSO) communication is the propagation of optical signal through different atmospheric conditions such as rain, snow and fog. In this paper, an orthogonal frequency-division multiplexing technique (OFDM) is proposed in the FSO communication system. Meanwhile, considering the rain attenuation models based on Marshal & Palmer and Carbonneau models, the performance of FSO communication system based on the OFDM is evaluated under the heavy-rain condition in Changsha, China. The simulation results show that, under a heavy-rainfall condition of 106.18 mm/h, with an attenuation factor of 7 dB/km based on the Marshal & Palmer model, the bit rate of 2.5 and 4.0 Gbps data can be transmitted over the FSO channels of 1.6 and 1.3 km, respectively, and the bit error rate of less than 1E - 4 can be achieved. In addition, the effect on rain attenuation over the FSO communication system based on the Marshal & Palmer model is less than that of the Carbonneau model.

Model and system learners, optimal process constructors and kinetic theory-based goal-oriented design: A new paradigm in materials and processes informatics

NASA Astrophysics Data System (ADS)

Abisset-Chavanne, Emmanuelle; Duval, Jean Louis; Cueto, Elias; Chinesta, Francisco

2018-05-01

Traditionally, Simulation-Based Engineering Sciences (SBES) has relied on the use of static data inputs (model parameters, initial or boundary conditions, … obtained from adequate experiments) to perform simulations. A new paradigm in the field of Applied Sciences and Engineering has emerged in the last decade. Dynamic Data-Driven Application Systems [9, 10, 11, 12, 22] allow the linkage of simulation tools with measurement devices for real-time control of simulations and applications, entailing the ability to dynamically incorporate additional data into an executing application, and in reverse, the ability of an application to dynamically steer the measurement process. It is in that context that traditional "digital-twins" are giving raise to a new generation of goal-oriented data-driven application systems, also known as "hybrid-twins", embracing models based on physics and models exclusively based on data adequately collected and assimilated for filling the gap between usual model predictions and measurements. Within this framework new methodologies based on model learners, machine learning and kinetic goal-oriented design are defining a new paradigm in materials, processes and systems engineering.

A study on spatial decision support systems for HIV/AIDS prevention based on COM GIS technology

NASA Astrophysics Data System (ADS)

Yang, Kun; Luo, Huasong; Peng, Shungyun; Xu, Quanli

2007-06-01

Based on the deeply analysis of the current status and the existing problems of GIS technology applications in Epidemiology, this paper has proposed the method and process for establishing the spatial decision support systems of AIDS epidemic prevention by integrating the COM GIS, Spatial Database, GPS, Remote Sensing, and Communication technologies, as well as ASP and ActiveX software development technologies. One of the most important issues for constructing the spatial decision support systems of AIDS epidemic prevention is how to integrate the AIDS spreading models with GIS. The capabilities of GIS applications in the AIDS epidemic prevention have been described here in this paper firstly. Then some mature epidemic spreading models have also been discussed for extracting the computation parameters. Furthermore, a technical schema has been proposed for integrating the AIDS spreading models with GIS and relevant geospatial technologies, in which the GIS and model running platforms share a common spatial database and the computing results can be spatially visualized on Desktop or Web GIS clients. Finally, a complete solution for establishing the decision support systems of AIDS epidemic prevention has been offered in this paper based on the model integrating methods and ESRI COM GIS software packages. The general decision support systems are composed of data acquisition sub-systems, network communication sub-systems, model integrating sub-systems, AIDS epidemic information spatial database sub-systems, AIDS epidemic information querying and statistical analysis sub-systems, AIDS epidemic dynamic surveillance sub-systems, AIDS epidemic information spatial analysis and decision support sub-systems, as well as AIDS epidemic information publishing sub-systems based on Web GIS.

Radiology Reporting System Data Exchange With the Electronic Health Record System: A Case Study in Iran.

PubMed

Ahmadi, Maryam; Ghazisaeidi, Marjan; Bashiri, Azadeh

2015-03-18

In order to better designing of electronic health record system in Iran, integration of health information systems based on a common language must be done to interpret and exchange this information with this system is required. This study provides a conceptual model of radiology reporting system using unified modeling language. The proposed model can solve the problem of integration this information system with the electronic health record system. By using this model and design its service based, easily connect to electronic health record in Iran and facilitate transfer radiology report data. This is a cross-sectional study that was conducted in 2013. The study population was 22 experts that working at the Imaging Center in Imam Khomeini Hospital in Tehran and the sample was accorded with the community. Research tool was a questionnaire that prepared by the researcher to determine the information requirements. Content validity and test-retest method was used to measure validity and reliability of questioner respectively. Data analyzed with average index, using SPSS. Also Visual Paradigm software was used to design a conceptual model. Based on the requirements assessment of experts and related texts, administrative, demographic and clinical data and radiological examination results and if the anesthesia procedure performed, anesthesia data suggested as minimum data set for radiology report and based it class diagram designed. Also by identifying radiology reporting system process, use case was drawn. According to the application of radiology reports in electronic health record system for diagnosing and managing of clinical problem of the patient, with providing the conceptual Model for radiology reporting system; in order to systematically design it, the problem of data sharing between these systems and electronic health records system would eliminate.

Reprint of “Performance analysis of a model-sized superconducting DC transmission system based VSC-HVDC transmission technologies using RTDS”

NASA Astrophysics Data System (ADS)

Dinh, Minh-Chau; Ju, Chang-Hyeon; Kim, Sung-Kyu; Kim, Jin-Geun; Park, Minwon; Yu, In-Keun

2013-01-01

The combination of a high temperature superconducting DC power cable and a voltage source converter based HVDC (VSC-HVDC) creates a new option for transmitting power with multiple collection and distribution points for long distance and bulk power transmissions. It offers some greater advantages compared with HVAC or conventional HVDC transmission systems, and it is well suited for the grid integration of renewable energy sources in existing distribution or transmission systems. For this reason, a superconducting DC transmission system based HVDC transmission technologies is planned to be set up in the Jeju power system, Korea. Before applying this system to a real power system on Jeju Island, system analysis should be performed through a real time test. In this paper, a model-sized superconducting VSC-HVDC system, which consists of a small model-sized VSC-HVDC connected to a 2 m YBCO HTS DC model cable, is implemented. The authors have performed the real-time simulation method that incorporates the model-sized superconducting VSC-HVDC system into the simulated Jeju power system using Real Time Digital Simulator (RTDS). The performance analysis of the superconducting VSC-HVDC systems has been verified by the proposed test platform and the results were discussed in detail.

Performance analysis of a model-sized superconducting DC transmission system based VSC-HVDC transmission technologies using RTDS

NASA Astrophysics Data System (ADS)

Dinh, Minh-Chau; Ju, Chang-Hyeon; Kim, Sung-Kyu; Kim, Jin-Geun; Park, Minwon; Yu, In-Keun

2012-08-01

The combination of a high temperature superconducting DC power cable and a voltage source converter based HVDC (VSC-HVDC) creates a new option for transmitting power with multiple collection and distribution points for long distance and bulk power transmissions. It offers some greater advantages compared with HVAC or conventional HVDC transmission systems, and it is well suited for the grid integration of renewable energy sources in existing distribution or transmission systems. For this reason, a superconducting DC transmission system based HVDC transmission technologies is planned to be set up in the Jeju power system, Korea. Before applying this system to a real power system on Jeju Island, system analysis should be performed through a real time test. In this paper, a model-sized superconducting VSC-HVDC system, which consists of a small model-sized VSC-HVDC connected to a 2 m YBCO HTS DC model cable, is implemented. The authors have performed the real-time simulation method that incorporates the model-sized superconducting VSC-HVDC system into the simulated Jeju power system using Real Time Digital Simulator (RTDS). The performance analysis of the superconducting VSC-HVDC systems has been verified by the proposed test platform and the results were discussed in detail.

Using Hi-FAME (High Feedback-Assessment-Multimedia-Environment) Instructional Model in WBI: A Case Study for Biology Teacher Education.

ERIC Educational Resources Information Center

Wang, Tzu-Hua; Wang, Wei-Lung; Wang, Kuo-Hua; Huang, Shih-Chieh

The study attempted to adapt two web tools, FFS system (Frontpage Feedback System) and WATA system (Web-based Assessment and Test Analysis System), to construct a Hi-FAME (High Feedback-Assessment-Multimedia-Environment) Model in WBI (Web-based Instruction) to facilitate pre-service teacher training. Participants were 30 junior pre-service…

Study of Personalized Network Tutoring System Based on Emotional-cognitive Interaction

NASA Astrophysics Data System (ADS)

Qi, Manfei; Ma, Ding; Wang, Wansen

Aiming at emotion deficiency in present Network tutoring system, a lot of negative effects is analyzed and corresponding countermeasures are proposed. The model of Personalized Network tutoring system based on Emotional-cognitive interaction is constructed in the paper. The key techniques of realizing the system such as constructing emotional model and adjusting teaching strategies are also introduced.

Tinamit: Making coupled system dynamics models accessible to stakeholders

NASA Astrophysics Data System (ADS)

Malard, Julien; Inam Baig, Azhar; Rojas Díaz, Marcela; Hassanzadeh, Elmira; Adamowski, Jan; Tuy, Héctor; Melgar-Quiñonez, Hugo

2017-04-01

Model coupling is increasingly used as a method of combining the best of two models when representing socio-environmental systems, though barriers to successful model adoption by stakeholders are particularly present with the use of coupled models, due to their high complexity and typically low implementation flexibility. Coupled system dynamics - physically-based modelling is a promising method to improve stakeholder participation in environmental modelling while retaining a high level of complexity for physical process representation, as the system dynamics components are readily understandable and can be built by stakeholders themselves. However, this method is not without limitations in practice, including 1) inflexible and complicated coupling methods, 2) difficult model maintenance after the end of the project, and 3) a wide variety of end-user cultures and languages. We have developed the open-source Python-language software tool Tinamit to overcome some of these limitations to the adoption of stakeholder-based coupled system dynamics - physically-based modelling. The software is unique in 1) its inclusion of both a graphical user interface (GUI) and a library of available commands (API) that allow users with little or no coding abilities to rapidly, effectively, and flexibly couple models, 2) its multilingual support for the GUI, allowing users to couple models in their preferred language (and to add new languages as necessary for their community work), and 3) its modular structure allowing for very easy model coupling and modification without the direct use of code, and to which programming-savvy users can easily add support for new types of physically-based models. We discuss how the use of Tinamit for model coupling can greatly increase the accessibility of coupled models to stakeholders, using an example of a stakeholder-built system dynamics model of soil salinity issues in Pakistan coupled with the physically-based soil salinity and water flow model SAHYSMOD. Different socioeconomic and environmental policies for soil salinity remediation are tested within the coupled model, allowing for the identification of the most efficient actions from an environmental and a farmer economy standpoint while taking into account the complex feedbacks between socioeconomics and the physical environment.

Estimation of single plane unbalance parameters of a rotor-bearing system using Kalman filtering based force estimation technique

NASA Astrophysics Data System (ADS)

Shrivastava, Akash; Mohanty, A. R.

2018-03-01

This paper proposes a model-based method to estimate single plane unbalance parameters (amplitude and phase angle) in a rotor using Kalman filter and recursive least square based input force estimation technique. Kalman filter based input force estimation technique requires state-space model and response measurements. A modified system equivalent reduction expansion process (SEREP) technique is employed to obtain a reduced-order model of the rotor system so that limited response measurements can be used. The method is demonstrated using numerical simulations on a rotor-disk-bearing system. Results are presented for different measurement sets including displacement, velocity, and rotational response. Effects of measurement noise level, filter parameters (process noise covariance and forgetting factor), and modeling error are also presented and it is observed that the unbalance parameter estimation is robust with respect to measurement noise.

Verification of Autonomous Systems for Space Applications

NASA Technical Reports Server (NTRS)

Brat, G.; Denney, E.; Giannakopoulou, D.; Frank, J.; Jonsson, A.

2006-01-01

Autonomous software, especially if it is based on model, can play an important role in future space applications. For example, it can help streamline ground operations, or, assist in autonomous rendezvous and docking operations, or even, help recover from problems (e.g., planners can be used to explore the space of recovery actions for a power subsystem and implement a solution without (or with minimal) human intervention). In general, the exploration capabilities of model-based systems give them great flexibility. Unfortunately, it also makes them unpredictable to our human eyes, both in terms of their execution and their verification. The traditional verification techniques are inadequate for these systems since they are mostly based on testing, which implies a very limited exploration of their behavioral space. In our work, we explore how advanced V&V techniques, such as static analysis, model checking, and compositional verification, can be used to gain trust in model-based systems. We also describe how synthesis can be used in the context of system reconfiguration and in the context of verification.

Off-policy reinforcement learning for H∞ control design.

PubMed

Luo, Biao; Wu, Huai-Ning; Huang, Tingwen

2015-01-01

The H∞ control design problem is considered for nonlinear systems with unknown internal system model. It is known that the nonlinear H∞ control problem can be transformed into solving the so-called Hamilton-Jacobi-Isaacs (HJI) equation, which is a nonlinear partial differential equation that is generally impossible to be solved analytically. Even worse, model-based approaches cannot be used for approximately solving HJI equation, when the accurate system model is unavailable or costly to obtain in practice. To overcome these difficulties, an off-policy reinforcement leaning (RL) method is introduced to learn the solution of HJI equation from real system data instead of mathematical system model, and its convergence is proved. In the off-policy RL method, the system data can be generated with arbitrary policies rather than the evaluating policy, which is extremely important and promising for practical systems. For implementation purpose, a neural network (NN)-based actor-critic structure is employed and a least-square NN weight update algorithm is derived based on the method of weighted residuals. Finally, the developed NN-based off-policy RL method is tested on a linear F16 aircraft plant, and further applied to a rotational/translational actuator system.

Equivalent model construction for a non-linear dynamic system based on an element-wise stiffness evaluation procedure and reduced analysis of the equivalent system

NASA Astrophysics Data System (ADS)

Kim, Euiyoung; Cho, Maenghyo

2017-11-01

In most non-linear analyses, the construction of a system matrix uses a large amount of computation time, comparable to the computation time required by the solving process. If the process for computing non-linear internal force matrices is substituted with an effective equivalent model that enables the bypass of numerical integrations and assembly processes used in matrix construction, efficiency can be greatly enhanced. A stiffness evaluation procedure (STEP) establishes non-linear internal force models using polynomial formulations of displacements. To efficiently identify an equivalent model, the method has evolved such that it is based on a reduced-order system. The reduction process, however, makes the equivalent model difficult to parameterize, which significantly affects the efficiency of the optimization process. In this paper, therefore, a new STEP, E-STEP, is proposed. Based on the element-wise nature of the finite element model, the stiffness evaluation is carried out element-by-element in the full domain. Since the unit of computation for the stiffness evaluation is restricted by element size, and since the computation is independent, the equivalent model can be constructed efficiently in parallel, even in the full domain. Due to the element-wise nature of the construction procedure, the equivalent E-STEP model is easily characterized by design parameters. Various reduced-order modeling techniques can be applied to the equivalent system in a manner similar to how they are applied in the original system. The reduced-order model based on E-STEP is successfully demonstrated for the dynamic analyses of non-linear structural finite element systems under varying design parameters.

Salmonella Typhimurium and Staphylococcus aureus dynamics in/on variable (micro)structures of fish-based model systems at suboptimal temperatures.

PubMed

Baka, Maria; Verheyen, Davy; Cornette, Nicolas; Vercruyssen, Stijn; Van Impe, Jan F

2017-01-02

The limited knowledge concerning the influence of food (micro)structure on microbial dynamics decreases the accuracy of the developed predictive models, as most studies have mainly been based on experimental data obtained in liquid microbiological media or in/on real foods. The use of model systems has a great potential when studying this complex factor. Apart from the variability in (micro)structural properties, model systems vary in compositional aspects, as a consequence of their (micro)structural variation. In this study, different experimental food model systems, with compositional and physicochemical properties similar to fish patés, are developed to study the influence of food (micro)structure on microbial dynamics. The microbiological safety of fish products is of major importance given the numerous cases of salmonellosis and infections attributed to staphylococcus toxins. The model systems understudy represent food (micro)structures of liquids, aqueous gels, emulsions and gelled emulsions. The growth/inactivation dynamics and a modelling approach of combined growth and inactivation of Salmonella Typhimurium and Staphylococcus aureus, related to fish products, are investigated in/on these model systems at temperatures relevant to fish products' common storage (4°C) and to abuse storage temperatures (8 and 12°C). ComBase (http://www.combase.cc/) predictions compared with the maximum specific growth rate (μ max ) values estimated by the Baranyi and Roberts model in the current study indicated that the (micro)structure influences the microbial dynamics. Overall, ComBase overestimated microbial growth at the same pH, a w and storage temperature. Finally, the storage temperature had also an influence on how much each model system affected the microbial dynamics. Copyright © 2016. Published by Elsevier B.V.

Advanced reliability modeling of fault-tolerant computer-based systems

NASA Technical Reports Server (NTRS)

Bavuso, S. J.

1982-01-01

Two methodologies for the reliability assessment of fault tolerant digital computer based systems are discussed. The computer-aided reliability estimation 3 (CARE 3) and gate logic software simulation (GLOSS) are assessment technologies that were developed to mitigate a serious weakness in the design and evaluation process of ultrareliable digital systems. The weak link is based on the unavailability of a sufficiently powerful modeling technique for comparing the stochastic attributes of one system against others. Some of the more interesting attributes are reliability, system survival, safety, and mission success.

Approaching mathematical model of the immune network based DNA Strand Displacement system.

PubMed

Mardian, Rizki; Sekiyama, Kosuke; Fukuda, Toshio

2013-12-01

One biggest obstacle in molecular programming is that there is still no direct method to compile any existed mathematical model into biochemical reaction in order to solve a computational problem. In this paper, the implementation of DNA Strand Displacement system based on nature-inspired computation is observed. By using the Immune Network Theory and Chemical Reaction Network, the compilation of DNA-based operation is defined and the formulation of its mathematical model is derived. Furthermore, the implementation on this system is compared with the conventional implementation by using silicon-based programming. From the obtained results, we can see a positive correlation between both. One possible application from this DNA-based model is for a decision making scheme of intelligent computer or molecular robot. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

Flood and landslide warning based on rainfall thresholds and soil moisture indexes: the HEWS (Hydrohazards Early Warning System) for Sicily

NASA Astrophysics Data System (ADS)

Brigandì, Giuseppina; Tito Aronica, Giuseppe; Bonaccorso, Brunella; Gueli, Roberto; Basile, Giuseppe

2017-09-01

The main focus of the paper is to present a flood and landslide early warning system, named HEWS (Hydrohazards Early Warning System), specifically developed for the Civil Protection Department of Sicily, based on the combined use of rainfall thresholds, soil moisture modelling and quantitative precipitation forecast (QPF). The warning system is referred to 9 different Alert Zones in which Sicily has been divided into and based on a threshold system of three different increasing critical levels: ordinary, moderate and high. In this system, for early flood warning, a Soil Moisture Accounting (SMA) model provides daily soil moisture conditions, which allow to select a specific set of three rainfall thresholds, one for each critical level considered, to be used for issue the alert bulletin. Wetness indexes, representative of the soil moisture conditions of a catchment, are calculated using a simple, spatially-lumped rainfall-streamflow model, based on the SCS-CN method, and on the unit hydrograph approach, that require daily observed and/or predicted rainfall, and temperature data as input. For the calibration of this model daily continuous time series of rainfall, streamflow and air temperature data are used. An event based lumped rainfall-runoff model has been, instead, used for the derivation of the rainfall thresholds for each catchment in Sicily characterised by an area larger than 50 km2. In particular, a Kinematic Instantaneous Unit Hydrograph based lumped rainfall-runoff model with the SCS-CN routine for net rainfall was developed for this purpose. For rainfall-induced shallow landslide warning, empirical rainfall thresholds provided by Gariano et al. (2015) have been included in the system. They were derived on an empirical basis starting from a catalogue of 265 shallow landslides in Sicily in the period 2002-2012. Finally, Delft-FEWS operational forecasting platform has been applied to link input data, SMA model and rainfall threshold models to produce warning on a daily basis for the entire region.

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.

Systems analysis techniques for annual cycle thermal energy storage solar systems

NASA Astrophysics Data System (ADS)

Baylin, F.

1980-07-01

Community-scale annual cycle thermal energy storage solar systems are options for building heat and cooling. A variety of approaches are feasible in modeling ACTES solar systems. The key parameter in such efforts, average collector efficiency, is examined, followed by several approaches for simple and effective modeling. Methods are also examined for modeling building loads for structures based on both conventional and passive architectural designs. Two simulation models for sizing solar heating systems with annual storage are presented. Validation is presented by comparison with the results of a study of seasonal storage systems based on SOLANSIM, an hour-by-hour simulation. These models are presently used to examine the economic trade-off between collector field area and storage capacity. Programs directed toward developing other system components such as improved tanks and solar ponds or design tools for ACTES solar systems are examined.

Historical Text Comprehension Reflective Tutorial Dialogue System

ERIC Educational Resources Information Center

Grigoriadou, Maria; Tsaganou, Grammatiki; Cavoura, Theodora

2005-01-01

The Reflective Tutorial Dialogue System (ReTuDiS) is a system for learner modelling historical text comprehension through reflective dialogue. The system infers learners' cognitive profiles and constructs their learner models. Based on the learner model the system plans the appropriate--personalized for learners--reflective tutorial dialogue in…

Rule-Based Simulation of Multi-Cellular Biological Systems—A Review of Modeling Techniques

PubMed Central

Hwang, Minki; Garbey, Marc; Berceli, Scott A.; Tran-Son-Tay, Roger

2011-01-01

Emergent behaviors of multi-cellular biological systems (MCBS) result from the behaviors of each individual cells and their interactions with other cells and with the environment. Modeling MCBS requires incorporating these complex interactions among the individual cells and the environment. Modeling approaches for MCBS can be grouped into two categories: continuum models and cell-based models. Continuum models usually take the form of partial differential equations, and the model equations provide insight into the relationship among the components in the system. Cell-based models simulate each individual cell behavior and interactions among them enabling the observation of the emergent system behavior. This review focuses on the cell-based models of MCBS, and especially, the technical aspect of the rule-based simulation method for MCBS is reviewed. How to implement the cell behaviors and the interactions with other cells and with the environment into the computational domain is discussed. The cell behaviors reviewed in this paper are division, migration, apoptosis/necrosis, and differentiation. The environmental factors such as extracellular matrix, chemicals, microvasculature, and forces are also discussed. Application examples of these cell behaviors and interactions are presented. PMID:21369345

THE EARTH SYSTEM PREDICTION SUITE: Toward a Coordinated U.S. Modeling Capability

PubMed Central

Theurich, Gerhard; DeLuca, C.; Campbell, T.; Liu, F.; Saint, K.; Vertenstein, M.; Chen, J.; Oehmke, R.; Doyle, J.; Whitcomb, T.; Wallcraft, A.; Iredell, M.; Black, T.; da Silva, AM; Clune, T.; Ferraro, R.; Li, P.; Kelley, M.; Aleinov, I.; Balaji, V.; Zadeh, N.; Jacob, R.; Kirtman, B.; Giraldo, F.; McCarren, D.; Sandgathe, S.; Peckham, S.; Dunlap, R.

2017-01-01

The Earth System Prediction Suite (ESPS) is a collection of flagship U.S. weather and climate models and model components that are being instrumented to conform to interoperability conventions, documented to follow metadata standards, and made available either under open source terms or to credentialed users. The ESPS represents a culmination of efforts to create a common Earth system model architecture, and the advent of increasingly coordinated model development activities in the U.S. ESPS component interfaces are based on the Earth System Modeling Framework (ESMF), community-developed software for building and coupling models, and the National Unified Operational Prediction Capability (NUOPC) Layer, a set of ESMF-based component templates and interoperability conventions. This shared infrastructure simplifies the process of model coupling by guaranteeing that components conform to a set of technical and semantic behaviors. The ESPS encourages distributed, multi-agency development of coupled modeling systems, controlled experimentation and testing, and exploration of novel model configurations, such as those motivated by research involving managed and interactive ensembles. ESPS codes include the Navy Global Environmental Model (NavGEM), HYbrid Coordinate Ocean Model (HYCOM), and Coupled Ocean Atmosphere Mesoscale Prediction System (COAMPS®); the NOAA Environmental Modeling System (NEMS) and the Modular Ocean Model (MOM); the Community Earth System Model (CESM); and the NASA ModelE climate model and GEOS-5 atmospheric general circulation model. PMID:29568125

THE EARTH SYSTEM PREDICTION SUITE: Toward a Coordinated U.S. Modeling Capability.

PubMed

Theurich, Gerhard; DeLuca, C; Campbell, T; Liu, F; Saint, K; Vertenstein, M; Chen, J; Oehmke, R; Doyle, J; Whitcomb, T; Wallcraft, A; Iredell, M; Black, T; da Silva, A M; Clune, T; Ferraro, R; Li, P; Kelley, M; Aleinov, I; Balaji, V; Zadeh, N; Jacob, R; Kirtman, B; Giraldo, F; McCarren, D; Sandgathe, S; Peckham, S; Dunlap, R

2016-07-01

The Earth System Prediction Suite (ESPS) is a collection of flagship U.S. weather and climate models and model components that are being instrumented to conform to interoperability conventions, documented to follow metadata standards, and made available either under open source terms or to credentialed users. The ESPS represents a culmination of efforts to create a common Earth system model architecture, and the advent of increasingly coordinated model development activities in the U.S. ESPS component interfaces are based on the Earth System Modeling Framework (ESMF), community-developed software for building and coupling models, and the National Unified Operational Prediction Capability (NUOPC) Layer, a set of ESMF-based component templates and interoperability conventions. This shared infrastructure simplifies the process of model coupling by guaranteeing that components conform to a set of technical and semantic behaviors. The ESPS encourages distributed, multi-agency development of coupled modeling systems, controlled experimentation and testing, and exploration of novel model configurations, such as those motivated by research involving managed and interactive ensembles. ESPS codes include the Navy Global Environmental Model (NavGEM), HYbrid Coordinate Ocean Model (HYCOM), and Coupled Ocean Atmosphere Mesoscale Prediction System (COAMPS ® ); the NOAA Environmental Modeling System (NEMS) and the Modular Ocean Model (MOM); the Community Earth System Model (CESM); and the NASA ModelE climate model and GEOS-5 atmospheric general circulation model.

The Earth System Prediction Suite: Toward a Coordinated U.S. Modeling Capability

NASA Technical Reports Server (NTRS)

Theurich, Gerhard; DeLuca, C.; Campbell, T.; Liu, F.; Saint, K.; Vertenstein, M.; Chen, J.; Oehmke, R.; Doyle, J.; Whitcomb, T.;

Data model for the collaboration between land administration systems and agricultural land parcel identification systems.

PubMed

Inan, Halil Ibrahim; Sagris, Valentina; Devos, Wim; Milenov, Pavel; van Oosterom, Peter; Zevenbergen, Jaap

2010-12-01

The Common Agricultural Policy (CAP) of the European Union (EU) has dramatically changed after 1992, and from then on the CAP focused on the management of direct income subsidies instead of production-based subsidies. For this focus, Member States (MS) are expected to establish Integrated Administration and Control System (IACS), including a Land Parcel Identification System (LPIS) as the spatial part of IACS. Different MS have chosen different solutions for their LPIS. Currently, some MS based their IACS/LPIS on data from their Land Administration Systems (LAS), and many others use purpose built special systems for their IACS/LPIS. The issue with these different IACS/LPIS is that they do not have standardized structures; rather, each represents a unique design in each MS, both in the case of LAS based or special systems. In this study, we aim at designing a core data model for those IACS/LPIS based on LAS. For this purpose, we make use of the ongoing standardization initiatives for LAS (Land Administration Domain Model: LADM) and IACS/LPIS (LPIS Core Model: LCM). The data model we propose in this study implies the collaboration between LADM and LCM and includes some extensions. Some basic issues with the collaboration model are discussed within this study: registration of farmers, land use rights and farming limitations, geometry/topology, temporal data management etc. For further explanation of the model structure, sample instance level diagrams illustrating some typical situations are also included. Copyright © 2010 Elsevier Ltd. All rights reserved.

Agent-based modeling as a tool for program design and evaluation.

PubMed

Lawlor, Jennifer A; McGirr, Sara

2017-12-01

Recently, systems thinking and systems science approaches have gained popularity in the field of evaluation; however, there has been relatively little exploration of how evaluators could use quantitative tools to assist in the implementation of systems approaches therein. The purpose of this paper is to explore potential uses of one such quantitative tool, agent-based modeling, in evaluation practice. To this end, we define agent-based modeling and offer potential uses for it in typical evaluation activities, including: engaging stakeholders, selecting an intervention, modeling program theory, setting performance targets, and interpreting evaluation results. We provide demonstrative examples from published agent-based modeling efforts both inside and outside the field of evaluation for each of the evaluative activities discussed. We further describe potential pitfalls of this tool and offer cautions for evaluators who may chose to implement it in their practice. Finally, the article concludes with a discussion of the future of agent-based modeling in evaluation practice and a call for more formal exploration of this tool as well as other approaches to simulation modeling in the field. Copyright © 2017 Elsevier Ltd. All rights reserved.

Cognitive control predicts use of model-based reinforcement learning.

PubMed

Otto, A Ross; Skatova, Anya; Madlon-Kay, Seth; Daw, Nathaniel D

2015-02-01

Accounts of decision-making and its neural substrates have long posited the operation of separate, competing valuation systems in the control of choice behavior. Recent theoretical and experimental work suggest that this classic distinction between behaviorally and neurally dissociable systems for habitual and goal-directed (or more generally, automatic and controlled) choice may arise from two computational strategies for reinforcement learning (RL), called model-free and model-based RL, but the cognitive or computational processes by which one system may dominate over the other in the control of behavior is a matter of ongoing investigation. To elucidate this question, we leverage the theoretical framework of cognitive control, demonstrating that individual differences in utilization of goal-related contextual information--in the service of overcoming habitual, stimulus-driven responses--in established cognitive control paradigms predict model-based behavior in a separate, sequential choice task. The behavioral correspondence between cognitive control and model-based RL compellingly suggests that a common set of processes may underpin the two behaviors. In particular, computational mechanisms originally proposed to underlie controlled behavior may be applicable to understanding the interactions between model-based and model-free choice behavior.

Theory and experiments in model-based space system anomaly management

NASA Astrophysics Data System (ADS)

Kitts, Christopher Adam

This research program consists of an experimental study of model-based reasoning methods for detecting, diagnosing and resolving anomalies that occur when operating a comprehensive space system. Using a first principles approach, several extensions were made to the existing field of model-based fault detection and diagnosis in order to develop a general theory of model-based anomaly management. Based on this theory, a suite of algorithms were developed and computationally implemented in order to detect, diagnose and identify resolutions for anomalous conditions occurring within an engineering system. The theory and software suite were experimentally verified and validated in the context of a simple but comprehensive, student-developed, end-to-end space system, which was developed specifically to support such demonstrations. This space system consisted of the Sapphire microsatellite which was launched in 2001, several geographically distributed and Internet-enabled communication ground stations, and a centralized mission control complex located in the Space Technology Center in the NASA Ames Research Park. Results of both ground-based and on-board experiments demonstrate the speed, accuracy, and value of the algorithms compared to human operators, and they highlight future improvements required to mature this technology.

Properties of a Formal Method to Model Emergence in Swarm-Based Systems

NASA Technical Reports Server (NTRS)

Rouff, Christopher; Vanderbilt, Amy; Truszkowski, Walt; Rash, James; Hinchey, Mike

2004-01-01

Future space missions will require cooperation between multiple satellites and/or rovers. Developers are proposing intelligent autonomous swarms for these missions, but swarm-based systems are difficult or impossible to test with current techniques. This viewgraph presentation examines the use of formal methods in testing swarm-based systems. The potential usefulness of formal methods in modeling the ANTS asteroid encounter mission is also examined.

On the accuracy of modelling the dynamics of large space structures

NASA Technical Reports Server (NTRS)

Diarra, C. M.; Bainum, P. M.

1985-01-01

Proposed space missions will require large scale, light weight, space based structural systems. Large space structure technology (LSST) systems will have to accommodate (among others): ocean data systems; electronic mail systems; large multibeam antenna systems; and, space based solar power systems. The structures are to be delivered into orbit by the space shuttle. Because of their inherent size, modelling techniques and scaling algorithms must be developed so that system performance can be predicted accurately prior to launch and assembly. When the size and weight-to-area ratio of proposed LSST systems dictate that the entire system be considered flexible, there are two basic modeling methods which can be used. The first is a continuum approach, a mathematical formulation for predicting the motion of a general orbiting flexible body, in which elastic deformations are considered small compared with characteristic body dimensions. This approach is based on an a priori knowledge of the frequencies and shape functions of all modes included within the system model. Alternatively, finite element techniques can be used to model the entire structure as a system of lumped masses connected by a series of (restoring) springs and possibly dampers. In addition, a computational algorithm was developed to evaluate the coefficients of the various coupling terms in the equations of motion as applied to the finite element model of the Hoop/Column.

Integration agent-based models and GIS as a virtual urban dynamic laboratory

NASA Astrophysics Data System (ADS)

Chen, Peng; Liu, Miaolong

2007-06-01

Based on the Agent-based Model and spatial data model, a tight-coupling integrating method of GIS and Agent-based Model (ABM) is to be discussed in this paper. The use of object-orientation for both spatial data and spatial process models facilitates their integration, which can allow exploration and explanation of spatial-temporal phenomena such as urban dynamic. In order to better understand how tight coupling might proceed and to evaluate the possible functional and efficiency gains from such a tight coupling, the agent-based model and spatial data model are discussed, and then the relationships affecting spatial data model and agent-based process models interaction. After that, a realistic crowd flow simulation experiment is presented. Using some tools provided by general GIS systems and a few specific programming languages, a new software system integrating GIS and MAS as a virtual laboratory applicable for simulating pedestrian flows in a crowd activity centre has been developed successfully. Under the environment supported by the software system, as an applicable case, a dynamic evolution process of the pedestrian's flows (dispersed process for the spectators) in a crowds' activity center - The Shanghai Stadium has been simulated successfully. At the end of the paper, some new research problems have been pointed out for the future.

The substantative knowledge base for travel and tourism: a systems model

Treesearch

David S. Solan

1992-01-01

Strategies for education and professional preparation in travel and tourism have generally been based in traditional tourism-related disciplines providing somewhat narrow perspectives of the tourism phenomenon. The need exists for models that provide comprehensive, holistic perspectives of travel and tourism. This paper presents one such systems model showing that...

EX.MAIN. Expert System Model for Maintenance and Staff Training.

ERIC Educational Resources Information Center

Masturzi, Elio R.

EX.MAIN, a model for maintenance and staff training which combines knowledge based expert systems and computer based training, was developed jointly by the Department of Production Engineering of the University of Naples and CIRCUMVESUVIANA, the largest private railroad in Italy. It is a global model in the maintenance field which contains both…

Study on Fault Diagnostics of a Turboprop Engine Using Inverse Performance Model and Artificial Intelligent Methods

NASA Astrophysics Data System (ADS)

Kong, Changduk; Lim, Semyeong

2011-12-01

Recently, the health monitoring system of major gas path components of gas turbine uses mostly the model based method like the Gas Path Analysis (GPA). This method is to find quantity changes of component performance characteristic parameters such as isentropic efficiency and mass flow parameter by comparing between measured engine performance parameters such as temperatures, pressures, rotational speeds, fuel consumption, etc. and clean engine performance parameters without any engine faults which are calculated by the base engine performance model. Currently, the expert engine diagnostic systems using the artificial intelligent methods such as Neural Networks (NNs), Fuzzy Logic and Genetic Algorithms (GAs) have been studied to improve the model based method. Among them the NNs are mostly used to the engine fault diagnostic system due to its good learning performance, but it has a drawback due to low accuracy and long learning time to build learning data base if there are large amount of learning data. In addition, it has a very complex structure for finding effectively single type faults or multiple type faults of gas path components. This work builds inversely a base performance model of a turboprop engine to be used for a high altitude operation UAV using measured performance data, and proposes a fault diagnostic system using the base engine performance model and the artificial intelligent methods such as Fuzzy logic and Neural Network. The proposed diagnostic system isolates firstly the faulted components using Fuzzy Logic, then quantifies faults of the identified components using the NN leaned by fault learning data base, which are obtained from the developed base performance model. In leaning the NN, the Feed Forward Back Propagation (FFBP) method is used. Finally, it is verified through several test examples that the component faults implanted arbitrarily in the engine are well isolated and quantified by the proposed diagnostic system.

Agent-based models in translational systems biology

PubMed Central

An, Gary; Mi, Qi; Dutta-Moscato, Joyeeta; Vodovotz, Yoram

2013-01-01

Effective translational methodologies for knowledge representation are needed in order to make strides against the constellation of diseases that affect the world today. These diseases are defined by their mechanistic complexity, redundancy, and nonlinearity. Translational systems biology aims to harness the power of computational simulation to streamline drug/device design, simulate clinical trials, and eventually to predict the effects of drugs on individuals. The ability of agent-based modeling to encompass multiple scales of biological process as well as spatial considerations, coupled with an intuitive modeling paradigm, suggests that this modeling framework is well suited for translational systems biology. This review describes agent-based modeling and gives examples of its translational applications in the context of acute inflammation and wound healing. PMID:20835989

An Exact Model-Based Method for Near-Field Sources Localization with Bistatic MIMO System.

PubMed

Singh, Parth Raj; Wang, Yide; Chargé, Pascal

2017-03-30

In this paper, we propose an exact model-based method for near-field sources localization with a bistatic multiple input, multiple output (MIMO) radar system, and compare it with an approximated model-based method. The aim of this paper is to propose an efficient way to use the exact model of the received signals of near-field sources in order to eliminate the systematic error introduced by the use of approximated model in most existing near-field sources localization techniques. The proposed method uses parallel factor (PARAFAC) decomposition to deal with the exact model. Thanks to the exact model, the proposed method has better precision and resolution than the compared approximated model-based method. The simulation results show the performance of the proposed method.

Processing speed enhances model-based over model-free reinforcement learning in the presence of high working memory functioning

PubMed Central

Schad, Daniel J.; Jünger, Elisabeth; Sebold, Miriam; Garbusow, Maria; Bernhardt, Nadine; Javadi, Amir-Homayoun; Zimmermann, Ulrich S.; Smolka, Michael N.; Heinz, Andreas; Rapp, Michael A.; Huys, Quentin J. M.

2014-01-01

Theories of decision-making and its neural substrates have long assumed the existence of two distinct and competing valuation systems, variously described as goal-directed vs. habitual, or, more recently and based on statistical arguments, as model-free vs. model-based reinforcement-learning. Though both have been shown to control choices, the cognitive abilities associated with these systems are under ongoing investigation. Here we examine the link to cognitive abilities, and find that individual differences in processing speed covary with a shift from model-free to model-based choice control in the presence of above-average working memory function. This suggests shared cognitive and neural processes; provides a bridge between literatures on intelligence and valuation; and may guide the development of process models of different valuation components. Furthermore, it provides a rationale for individual differences in the tendency to deploy valuation systems, which may be important for understanding the manifold neuropsychiatric diseases associated with malfunctions of valuation. PMID:25566131

First Principles Modeling of RFQ Cooling System and Resonant Frequency Responses for Fermilab’s PIP-II Injector Test

DOE PAGES

Edelen, J. P.; Edelen, A. L.; Bowring, D.; ...

2016-12-23

In this study we develop an a priori method for simulating dynamic resonant frequency and temperature responses in a radio frequency quadrupole (RFQ) and its associated water-based cooling system respectively. Our model provides a computationally efficient means to evaluate the transient response of the RFQ over a large range of system parameters. The model was constructed prior to the delivery of the PIP-II Injector Test RFQ and was used to aid in the design of the water-based cooling system, data acquisition system, and resonance control system. Now that the model has been validated with experimental data, it can confidently bemore » used to aid in the design of future RFQ resonance controllers and their associated water-based cooling systems. Finally, without any empirical fitting, it has demonstrated the ability to predict absolute temperature and frequency changes to 11% accuracy on average, and relative changes to 7% accuracy.« less

Systems engineering interfaces: A model based approach

NASA Astrophysics Data System (ADS)

Fosse, E.; Delp, C. L.

The engineering of interfaces is a critical function of the discipline of Systems Engineering. Included in interface engineering are instances of interaction. Interfaces provide the specifications of the relevant properties of a system or component that can be connected to other systems or components while instances of interaction are identified in order to specify the actual integration to other systems or components. Current Systems Engineering practices rely on a variety of documents and diagrams to describe interface specifications and instances of interaction. The SysML[1] specification provides a precise model based representation for interfaces and interface instance integration. This paper will describe interface engineering as implemented by the Operations Revitalization Task using SysML, starting with a generic case and culminating with a focus on a Flight System to Ground Interaction. The reusability of the interface engineering approach presented as well as its extensibility to more complex interfaces and interactions will be shown. Model-derived tables will support the case studies shown and are examples of model-based documentation products.

Optimization of life support systems and their systems reliability

NASA Technical Reports Server (NTRS)

Fan, L. T.; Hwang, C. L.; Erickson, L. E.

1971-01-01

The identification, analysis, and optimization of life support systems and subsystems have been investigated. For each system or subsystem that has been considered, the procedure involves the establishment of a set of system equations (or mathematical model) based on theory and experimental evidences; the analysis and simulation of the model; the optimization of the operation, control, and reliability; analysis of sensitivity of the system based on the model; and, if possible, experimental verification of the theoretical and computational results. Research activities include: (1) modeling of air flow in a confined space; (2) review of several different gas-liquid contactors utilizing centrifugal force: (3) review of carbon dioxide reduction contactors in space vehicles and other enclosed structures: (4) application of modern optimal control theory to environmental control of confined spaces; (5) optimal control of class of nonlinear diffusional distributed parameter systems: (6) optimization of system reliability of life support systems and sub-systems: (7) modeling, simulation and optimal control of the human thermal system: and (8) analysis and optimization of the water-vapor eletrolysis cell.

ARMAX-Based Transfer Function Model Identification Using Wide-Area Measurement for Adaptive and Coordinated Damping Control

DOE PAGES

Liu, Hesen; Zhu, Lin; Pan, Zhuohong; ...

2015-09-14

One of the main drawbacks of the existing oscillation damping controllers that are designed based on offline dynamic models is adaptivity to the power system operating condition. With the increasing availability of wide-area measurements and the rapid development of system identification techniques, it is possible to identify a measurement-based transfer function model online that can be used to tune the oscillation damping controller. Such a model could capture all dominant oscillation modes for adaptive and coordinated oscillation damping control. our paper describes a comprehensive approach to identify a low-order transfer function model of a power system using a multi-input multi-outputmore » (MIMO) autoregressive moving average exogenous (ARMAX) model. This methodology consists of five steps: 1) input selection; 2) output selection; 3) identification trigger; 4) model estimation; and 5) model validation. The proposed method is validated by using ambient data and ring-down data in the 16-machine 68-bus Northeast Power Coordinating Council system. Our results demonstrate that the measurement-based model using MIMO ARMAX can capture all the dominant oscillation modes. Compared with the MIMO subspace state space model, the MIMO ARMAX model has equivalent accuracy but lower order and improved computational efficiency. The proposed model can be applied for adaptive and coordinated oscillation damping control.« less

Automatic Generation of Customized, Model Based Information Systems for Operations Management.

DTIC Science & Technology

The paper discusses the need for developing a customized, model based system to support management decision making in the field of operations ... management . It provides a critique of the current approaches available, formulates a framework to classify logistics decisions, and suggests an approach for the automatic development of logistics systems. (Author)

The Earth System Prediction Suite: Toward a Coordinated U.S. Modeling Capability

DOE PAGES

Theurich, Gerhard; DeLuca, C.; Campbell, T.; ...

2016-08-22

The Earth System Prediction Suite (ESPS) is a collection of flagship U.S. weather and climate models and model components that are being instrumented to conform to interoperability conventions, documented to follow metadata standards, and made available either under open-source terms or to credentialed users. Furthermore, the ESPS represents a culmination of efforts to create a common Earth system model architecture, and the advent of increasingly coordinated model development activities in the United States. ESPS component interfaces are based on the Earth System Modeling Framework (ESMF), community-developed software for building and coupling models, and the National Unified Operational Prediction Capability (NUOPC)more » Layer, a set of ESMF-based component templates and interoperability conventions. Our shared infrastructure simplifies the process of model coupling by guaranteeing that components conform to a set of technical and semantic behaviors. The ESPS encourages distributed, multiagency development of coupled modeling systems; controlled experimentation and testing; and exploration of novel model configurations, such as those motivated by research involving managed and interactive ensembles. ESPS codes include the Navy Global Environmental Model (NAVGEM), the Hybrid Coordinate Ocean Model (HYCOM), and the Coupled Ocean–Atmosphere Mesoscale Prediction System (COAMPS); the NOAA Environmental Modeling System (NEMS) and the Modular Ocean Model (MOM); the Community Earth System Model (CESM); and the NASA ModelE climate model and the Goddard Earth Observing System Model, version 5 (GEOS-5), atmospheric general circulation model.« less

The Earth System Prediction Suite: Toward a Coordinated U.S. Modeling Capability

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

Theurich, Gerhard; DeLuca, C.; Campbell, T.

The Earth System Prediction Suite (ESPS) is a collection of flagship U.S. weather and climate models and model components that are being instrumented to conform to interoperability conventions, documented to follow metadata standards, and made available either under open-source terms or to credentialed users. Furthermore, the ESPS represents a culmination of efforts to create a common Earth system model architecture, and the advent of increasingly coordinated model development activities in the United States. ESPS component interfaces are based on the Earth System Modeling Framework (ESMF), community-developed software for building and coupling models, and the National Unified Operational Prediction Capability (NUOPC)more » Layer, a set of ESMF-based component templates and interoperability conventions. Our shared infrastructure simplifies the process of model coupling by guaranteeing that components conform to a set of technical and semantic behaviors. The ESPS encourages distributed, multiagency development of coupled modeling systems; controlled experimentation and testing; and exploration of novel model configurations, such as those motivated by research involving managed and interactive ensembles. ESPS codes include the Navy Global Environmental Model (NAVGEM), the Hybrid Coordinate Ocean Model (HYCOM), and the Coupled Ocean–Atmosphere Mesoscale Prediction System (COAMPS); the NOAA Environmental Modeling System (NEMS) and the Modular Ocean Model (MOM); the Community Earth System Model (CESM); and the NASA ModelE climate model and the Goddard Earth Observing System Model, version 5 (GEOS-5), atmospheric general circulation model.« less

Model Documentation of Base Case Data | Regional Energy Deployment System

Science.gov Websites

Model | Energy Analysis | NREL Documentation of Base Case Data Model Documentation of Base Case base case of the model. The base case was developed simply as a point of departure for other analyses Base Case derives many of its inputs from the Energy Information Administration's (EIA's) Annual Energy

Implementing Lumberjacks and Black Swans Into Model-Based Tools to Support Human-Automation Interaction.

PubMed

Sebok, Angelia; Wickens, Christopher D

2017-03-01

The objectives were to (a) implement theoretical perspectives regarding human-automation interaction (HAI) into model-based tools to assist designers in developing systems that support effective performance and (b) conduct validations to assess the ability of the models to predict operator performance. Two key concepts in HAI, the lumberjack analogy and black swan events, have been studied extensively. The lumberjack analogy describes the effects of imperfect automation on operator performance. In routine operations, an increased degree of automation supports performance, but in failure conditions, increased automation results in more significantly impaired performance. Black swans are the rare and unexpected failures of imperfect automation. The lumberjack analogy and black swan concepts have been implemented into three model-based tools that predict operator performance in different systems. These tools include a flight management system, a remotely controlled robotic arm, and an environmental process control system. Each modeling effort included a corresponding validation. In one validation, the software tool was used to compare three flight management system designs, which were ranked in the same order as predicted by subject matter experts. The second validation compared model-predicted operator complacency with empirical performance in the same conditions. The third validation compared model-predicted and empirically determined time to detect and repair faults in four automation conditions. The three model-based tools offer useful ways to predict operator performance in complex systems. The three tools offer ways to predict the effects of different automation designs on operator performance.

Efficient physics-based tracking of heart surface motion for beating heart surgery robotic systems.

PubMed

Bogatyrenko, Evgeniya; Pompey, Pascal; Hanebeck, Uwe D

2011-05-01

Tracking of beating heart motion in a robotic surgery system is required for complex cardiovascular interventions. A heart surface motion tracking method is developed, including a stochastic physics-based heart surface model and an efficient reconstruction algorithm. The algorithm uses the constraints provided by the model that exploits the physical characteristics of the heart. The main advantage of the model is that it is more realistic than most standard heart models. Additionally, no explicit matching between the measurements and the model is required. The application of meshless methods significantly reduces the complexity of physics-based tracking. Based on the stochastic physical model of the heart surface, this approach considers the motion of the intervention area and is robust to occlusions and reflections. The tracking algorithm is evaluated in simulations and experiments on an artificial heart. Providing higher accuracy than the standard model-based methods, it successfully copes with occlusions and provides high performance even when all measurements are not available. Combining the physical and stochastic description of the heart surface motion ensures physically correct and accurate prediction. Automatic initialization of the physics-based cardiac motion tracking enables system evaluation in a clinical environment.

Enhancing implementation science by applying best principles of systems science.

PubMed

Northridge, Mary E; Metcalf, Sara S

2016-10-04

Implementation science holds promise for better ensuring that research is translated into evidence-based policy and practice, but interventions often fail or even worsen the problems they are intended to solve due to a lack of understanding of real world structures and dynamic complexity. While systems science alone cannot possibly solve the major challenges in public health, systems-based approaches may contribute to changing the language and methods for conceptualising and acting within complex systems. The overarching goal of this paper is to improve the modelling used in dissemination and implementation research by applying best principles of systems science. Best principles, as distinct from the more customary term 'best practices', are used to underscore the need to extract the core issues from the context in which they are embedded in order to better ensure that they are transferable across settings. Toward meaningfully grappling with the complex and challenging problems faced in adopting and integrating evidence-based health interventions and changing practice patterns within specific settings, we propose and illustrate four best principles derived from our systems science experience: (1) model the problem, not the system; (2) pay attention to what is important, not just what is quantifiable; (3) leverage the utility of models as boundary objects; and (4) adopt a portfolio approach to model building. To improve our mental models of the real world, system scientists have created methodologies such as system dynamics, agent-based modelling, geographic information science and social network simulation. To understand dynamic complexity, we need the ability to simulate. Otherwise, our understanding will be limited. The practice of dynamic systems modelling, as discussed herein, is the art and science of linking system structure to behaviour for the purpose of changing structure to improve behaviour. A useful computer model creates a knowledge repository and a virtual library for internally consistent exploration of alternative assumptions. Among the benefits of systems modelling are iterative practice, participatory potential and possibility thinking. We trust that the best principles proposed here will resonate with implementation scientists; applying them to the modelling process may abet the translation of research into effective policy and practice.

ICT use for information management in healthcare system for chronic disease patient

NASA Astrophysics Data System (ADS)

Wawrzyniak, Zbigniew M.; Lisiecka-Biełanowicz, Mira

2013-10-01

Modern healthcare systems are designed to fulfill needs of the patient, his system environment and other determinants of the treatment with proper support of technical aids. A whole system of care is compatible to the technical solutions and organizational framework based on legal rules. The purpose of this study is to present how can we use Information and Communication Technology (ICT) systemic tools in a new model of patient-oriented care, improving the effectiveness of healthcare for patients with chronic diseases. The study material is the long-term process of healthcare for patients with chronic illness. Basing on the knowledge of the whole circumstances of patient's ecosystem and his needs allow us to build a new ICT model of long term care. The method used is construction, modeling and constant improvement the efficient ICT layer for the patient-centered healthcare model. We present a new constructive approach to systemic process how to use ICT for information management in healthcare system for chronic disease patient. The use of ICT tools in the model for chronic disease can improve all aspects of data management and communication, and the effectiveness of long-term complex healthcare. In conclusion: ICT based model of healthcare can be constructed basing on the interactions of ecosystem's functional parts through information feedback and the provision of services and models as well as the knowledge of the patient itself. Systematic approach to the model of long term healthcare assisted functionally by ICT tools and data management methods will increase the effectiveness of patient care and organizational efficiency.

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.

Comparison between two statistically based methods, and two physically based models developed to compute daily mean streamflow at ungaged locations in the Cedar River Basin, Iowa

USGS Publications Warehouse

Linhart, S. Mike; Nania, Jon F.; Christiansen, Daniel E.; Hutchinson, Kasey J.; Sanders, Curtis L.; Archfield, Stacey A.

2013-01-01

A variety of individuals from water resource managers to recreational users need streamflow information for planning and decisionmaking at locations where there are no streamgages. To address this problem, two statistically based methods, the Flow Duration Curve Transfer method and the Flow Anywhere method, were developed for statewide application and the two physically based models, the Precipitation Runoff Modeling-System and the Soil and Water Assessment Tool, were only developed for application for the Cedar River Basin. Observed and estimated streamflows for the two methods and models were compared for goodness of fit at 13 streamgages modeled in the Cedar River Basin by using the Nash-Sutcliffe and the percent-bias efficiency values. Based on median and mean Nash-Sutcliffe values for the 13 streamgages the Precipitation Runoff Modeling-System and Soil and Water Assessment Tool models appear to have performed similarly and better than Flow Duration Curve Transfer and Flow Anywhere methods. Based on median and mean percent bias values, the Soil and Water Assessment Tool model appears to have generally overestimated daily mean streamflows, whereas the Precipitation Runoff Modeling-System model and statistical methods appear to have underestimated daily mean streamflows. The Flow Duration Curve Transfer method produced the lowest median and mean percent bias values and appears to perform better than the other models.

Protocol for Reliability Assessment of Structural Health Monitoring Systems Incorporating Model-assisted Probability of Detection (MAPOD) Approach

DTIC Science & Technology

2011-09-01

a quality evaluation with limited data, a model -based assessment must be...that affect system performance, a multistage approach to system validation, a modeling and experimental methodology for efficiently addressing a ...affect system performance, a multistage approach to system validation, a modeling and experimental methodology for efficiently addressing a wide range

Brayton Power Conversion System Parametric Design Modelling for Nuclear Electric Propulsion

NASA Technical Reports Server (NTRS)

Ashe, Thomas L.; Otting, William D.

1993-01-01

The parametrically based closed Brayton cycle (CBC) computer design model was developed for inclusion into the NASA LeRC overall Nuclear Electric Propulsion (NEP) end-to-end systems model. The code is intended to provide greater depth to the NEP system modeling which is required to more accurately predict the impact of specific technology on system performance. The CBC model is parametrically based to allow for conducting detailed optimization studies and to provide for easy integration into an overall optimizer driver routine. The power conversion model includes the modeling of the turbines, alternators, compressors, ducting, and heat exchangers (hot-side heat exchanger and recuperator). The code predicts performance to significant detail. The system characteristics determined include estimates of mass, efficiency, and the characteristic dimensions of the major power conversion system components. These characteristics are parametrically modeled as a function of input parameters such as the aerodynamic configuration (axial or radial), turbine inlet temperature, cycle temperature ratio, power level, lifetime, materials, and redundancy.

Chance-Constrained System of Systems Based Operation of Power Systems

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

Kargarian, Amin; Fu, Yong; Wu, Hongyu

In this paper, a chance-constrained system of systems (SoS) based decision-making approach is presented for stochastic scheduling of power systems encompassing active distribution grids. Based on the concept of SoS, the independent system operator (ISO) and distribution companies (DISCOs) are modeled as self-governing systems. These systems collaborate with each other to run the entire power system in a secure and economic manner. Each self-governing system accounts for its local reserve requirements and line flow constraints with respect to the uncertainties of load and renewable energy resources. A set of chance constraints are formulated to model the interactions between the ISOmore » and DISCOs. The proposed model is solved by using analytical target cascading (ATC) method, a distributed optimization algorithm in which only a limited amount of information is exchanged between collaborative ISO and DISCOs. In this paper, a 6-bus and a modified IEEE 118-bus power systems are studied to show the effectiveness of the proposed algorithm.« less

Concept for a Satellite-Based Advanced Air Traffic Management System : Volume 9. System and Subsystem Performance Models.

DOT National Transportation Integrated Search

1973-02-01

The volume presents the models used to analyze basic features of the system, establish feasibility of techniques, and evaluate system performance. The models use analytical expressions and computer simulations to represent the relationship between sy...

A Comparison of Filter-based Approaches for Model-based Prognostics

NASA Technical Reports Server (NTRS)

Daigle, Matthew John; Saha, Bhaskar; Goebel, Kai

2012-01-01

Model-based prognostics approaches use domain knowledge about a system and its failure modes through the use of physics-based models. Model-based prognosis is generally divided into two sequential problems: a joint state-parameter estimation problem, in which, using the model, the health of a system or component is determined based on the observations; and a prediction problem, in which, using the model, the stateparameter distribution is simulated forward in time to compute end of life and remaining useful life. The first problem is typically solved through the use of a state observer, or filter. The choice of filter depends on the assumptions that may be made about the system, and on the desired algorithm performance. In this paper, we review three separate filters for the solution to the first problem: the Daum filter, an exact nonlinear filter; the unscented Kalman filter, which approximates nonlinearities through the use of a deterministic sampling method known as the unscented transform; and the particle filter, which approximates the state distribution using a finite set of discrete, weighted samples, called particles. Using a centrifugal pump as a case study, we conduct a number of simulation-based experiments investigating the performance of the different algorithms as applied to prognostics.

Minding the Cyber-Physical Gap: Model-Based Analysis and Mitigation of Systemic Perception-Induced Failure.

PubMed

Mordecai, Yaniv; Dori, Dov

2017-07-17

The cyber-physical gap (CPG) is the difference between the 'real' state of the world and the way the system perceives it. This discrepancy often stems from the limitations of sensing and data collection technologies and capabilities, and is inevitable at some degree in any cyber-physical system (CPS). Ignoring or misrepresenting such limitations during system modeling, specification, design, and analysis can potentially result in systemic misconceptions, disrupted functionality and performance, system failure, severe damage, and potential detrimental impacts on the system and its environment. We propose CPG-Aware Modeling & Engineering (CPGAME), a conceptual model-based approach to capturing, explaining, and mitigating the CPG. CPGAME enhances the systems engineer's ability to cope with CPGs, mitigate them by design, and prevent erroneous decisions and actions. We demonstrate CPGAME by applying it for modeling and analysis of the 1979 Three Miles Island 2 nuclear accident, and show how its meltdown could be mitigated. We use ISO-19450:2015-Object Process Methodology as our conceptual modeling framework.

The use of discrete-event simulation modeling to compare handwritten and electronic prescribing systems.

PubMed

Ghany, Ahmad; Vassanji, Karim; Kuziemsky, Craig; Keshavjee, Karim

2013-01-01

Electronic prescribing (e-prescribing) is expected to bring many benefits to Canadian healthcare, such as a reduction in errors and adverse drug reactions. As there currently is no functioning e-prescribing system in Canada that is completely electronic, we are unable to evaluate the performance of a live system. An alternative approach is to use simulation modeling for evaluation. We developed two discrete-event simulation models, one of the current handwritten prescribing system and one of a proposed e-prescribing system, to compare the performance of these two systems. We were able to compare the number of processes in each model, workflow efficiency, and the distribution of patients or prescriptions. Although we were able to compare these models to each other, using discrete-event simulation software was challenging. We were limited in the number of variables we could measure. We discovered non-linear processes and feedback loops in both models that could not be adequately represented using discrete-event simulation software. Finally, interactions between entities in both models could not be modeled using this type of software. We have come to the conclusion that a more appropriate approach to modeling both the handwritten and electronic prescribing systems would be to use a complex adaptive systems approach using agent-based modeling or systems-based modeling.

Improving Distributed Diagnosis Through Structural Model Decomposition

NASA Technical Reports Server (NTRS)

Bregon, Anibal; Daigle, Matthew John; Roychoudhury, Indranil; Biswas, Gautam; Koutsoukos, Xenofon; Pulido, Belarmino

2011-01-01

Complex engineering systems require efficient fault diagnosis methodologies, but centralized approaches do not scale well, and this motivates the development of distributed solutions. This work presents an event-based approach for distributed diagnosis of abrupt parametric faults in continuous systems, by using the structural model decomposition capabilities provided by Possible Conflicts. We develop a distributed diagnosis algorithm that uses residuals computed by extending Possible Conflicts to build local event-based diagnosers based on global diagnosability analysis. The proposed approach is applied to a multitank system, and results demonstrate an improvement in the design of local diagnosers. Since local diagnosers use only a subset of the residuals, and use subsystem models to compute residuals (instead of the global system model), the local diagnosers are more efficient than previously developed distributed approaches.

Research on light rail electric load forecasting based on ARMA model

NASA Astrophysics Data System (ADS)

Huang, Yifan

2018-04-01

The article compares a variety of time series models and combines the characteristics of power load forecasting. Then, a light load forecasting model based on ARMA model is established. Based on this model, a light rail system is forecasted. The prediction results show that the accuracy of the model prediction is high.

A Model to Assess the Behavioral Impacts of Consultative Knowledge Based Systems.

ERIC Educational Resources Information Center

Mak, Brenda; Lyytinen, Kalle

1997-01-01

This research model studies the behavioral impacts of consultative knowledge based systems (KBS). A study of graduate students explored to what extent their decisions were affected by user participation in updating the knowledge base; ambiguity of decision setting; routinization of usage; and source credibility of the expertise embedded in the…

Using argument notation to engineer biological simulations with increased confidence

PubMed Central

Alden, Kieran; Andrews, Paul S.; Polack, Fiona A. C.; Veiga-Fernandes, Henrique; Coles, Mark C.; Timmis, Jon

2015-01-01

The application of computational and mathematical modelling to explore the mechanics of biological systems is becoming prevalent. To significantly impact biological research, notably in developing novel therapeutics, it is critical that the model adequately represents the captured system. Confidence in adopting in silico approaches can be improved by applying a structured argumentation approach, alongside model development and results analysis. We propose an approach based on argumentation from safety-critical systems engineering, where a system is subjected to a stringent analysis of compliance against identified criteria. We show its use in examining the biological information upon which a model is based, identifying model strengths, highlighting areas requiring additional biological experimentation and providing documentation to support model publication. We demonstrate our use of structured argumentation in the development of a model of lymphoid tissue formation, specifically Peyer's Patches. The argumentation structure is captured using Artoo (www.york.ac.uk/ycil/software/artoo), our Web-based tool for constructing fitness-for-purpose arguments, using a notation based on the safety-critical goal structuring notation. We show how argumentation helps in making the design and structured analysis of a model transparent, capturing the reasoning behind the inclusion or exclusion of each biological feature and recording assumptions, as well as pointing to evidence supporting model-derived conclusions. PMID:25589574

Using argument notation to engineer biological simulations with increased confidence.

PubMed

Alden, Kieran; Andrews, Paul S; Polack, Fiona A C; Veiga-Fernandes, Henrique; Coles, Mark C; Timmis, Jon

2015-03-06

The application of computational and mathematical modelling to explore the mechanics of biological systems is becoming prevalent. To significantly impact biological research, notably in developing novel therapeutics, it is critical that the model adequately represents the captured system. Confidence in adopting in silico approaches can be improved by applying a structured argumentation approach, alongside model development and results analysis. We propose an approach based on argumentation from safety-critical systems engineering, where a system is subjected to a stringent analysis of compliance against identified criteria. We show its use in examining the biological information upon which a model is based, identifying model strengths, highlighting areas requiring additional biological experimentation and providing documentation to support model publication. We demonstrate our use of structured argumentation in the development of a model of lymphoid tissue formation, specifically Peyer's Patches. The argumentation structure is captured using Artoo (www.york.ac.uk/ycil/software/artoo), our Web-based tool for constructing fitness-for-purpose arguments, using a notation based on the safety-critical goal structuring notation. We show how argumentation helps in making the design and structured analysis of a model transparent, capturing the reasoning behind the inclusion or exclusion of each biological feature and recording assumptions, as well as pointing to evidence supporting model-derived conclusions.

A component-based system for agricultural drought monitoring by remote sensing.

PubMed

Dong, Heng; Li, Jun; Yuan, Yanbin; You, Lin; Chen, Chao

2017-01-01

In recent decades, various kinds of remote sensing-based drought indexes have been proposed and widely used in the field of drought monitoring. However, the drought-related software and platform development lag behind the theoretical research. The current drought monitoring systems focus mainly on information management and publishing, and cannot implement professional drought monitoring or parameter inversion modelling, especially the models based on multi-dimensional feature space. In view of the above problems, this paper aims at fixing this gap with a component-based system named RSDMS to facilitate the application of drought monitoring by remote sensing. The system is designed and developed based on Component Object Model (COM) to ensure the flexibility and extendibility of modules. RSDMS realizes general image-related functions such as data management, image display, spatial reference management, image processing and analysis, and further provides drought monitoring and evaluation functions based on internal and external models. Finally, China's Ningxia region is selected as the study area to validate the performance of RSDMS. The experimental results show that RSDMS provide an efficient and scalable support to agricultural drought monitoring.

A component-based system for agricultural drought monitoring by remote sensing

PubMed Central

Yuan, Yanbin; You, Lin; Chen, Chao

2017-01-01

In recent decades, various kinds of remote sensing-based drought indexes have been proposed and widely used in the field of drought monitoring. However, the drought-related software and platform development lag behind the theoretical research. The current drought monitoring systems focus mainly on information management and publishing, and cannot implement professional drought monitoring or parameter inversion modelling, especially the models based on multi-dimensional feature space. In view of the above problems, this paper aims at fixing this gap with a component-based system named RSDMS to facilitate the application of drought monitoring by remote sensing. The system is designed and developed based on Component Object Model (COM) to ensure the flexibility and extendibility of modules. RSDMS realizes general image-related functions such as data management, image display, spatial reference management, image processing and analysis, and further provides drought monitoring and evaluation functions based on internal and external models. Finally, China’s Ningxia region is selected as the study area to validate the performance of RSDMS. The experimental results show that RSDMS provide an efficient and scalable support to agricultural drought monitoring. PMID:29236700

10 Steps to Building an Architecture for Space Surveillance Projects

NASA Astrophysics Data System (ADS)

Gyorko, E.; Barnhart, E.; Gans, H.

Space surveillance is an increasingly complex task, requiring the coordination of a multitude of organizations and systems, while dealing with competing capabilities, proprietary processes, differing standards, and compliance issues. In order to fully understand space surveillance operations, analysts and engineers need to analyze and break down their operations and systems using what are essentially enterprise architecture processes and techniques. These techniques can be daunting to the first- time architect. This paper provides a summary of simplified steps to analyze a space surveillance system at the enterprise level in order to determine capabilities, services, and systems. These steps form the core of an initial Model-Based Architecting process. For new systems, a well defined, or well architected, space surveillance enterprise leads to an easier transition from model-based architecture to model-based design and provides a greater likelihood that requirements are fulfilled the first time. Both new and existing systems benefit from being easier to manage, and can be sustained more easily using portfolio management techniques, based around capabilities documented in the model repository. The resulting enterprise model helps an architect avoid 1) costly, faulty portfolio decisions; 2) wasteful technology refresh efforts; 3) upgrade and transition nightmares; and 4) non-compliance with DoDAF directives. The Model-Based Architecting steps are based on a process that Harris Corporation has developed from practical experience architecting space surveillance systems and ground systems. Examples are drawn from current work on documenting space situational awareness enterprises. The process is centered on DoDAF 2 and its corresponding meta-model so that terminology is standardized and communicable across any disciplines that know DoDAF architecting, including acquisition, engineering and sustainment disciplines. Each step provides a guideline for the type of data to collect, and also the appropriate views to generate. The steps include 1) determining the context of the enterprise, including active elements and high level capabilities or goals; 2) determining the desired effects of the capabilities and mapping capabilities against the project plan; 3) determining operational performers and their inter-relationships; 4) building information and data dictionaries; 5) defining resources associated with capabilities; 6) determining the operational behavior necessary to achieve each capability; 7) analyzing existing or planned implementations to determine systems, services and software; 8) cross-referencing system behavior to operational behavioral; 9) documenting system threads and functional implementations; and 10) creating any required textual documentation from the model.

Remaining lifetime modeling using State-of-Health estimation

NASA Astrophysics Data System (ADS)

Beganovic, Nejra; Söffker, Dirk

2017-08-01

Technical systems and system's components undergo gradual degradation over time. Continuous degradation occurred in system is reflected in decreased system's reliability and unavoidably lead to a system failure. Therefore, continuous evaluation of State-of-Health (SoH) is inevitable to provide at least predefined lifetime of the system defined by manufacturer, or even better, to extend the lifetime given by manufacturer. However, precondition for lifetime extension is accurate estimation of SoH as well as the estimation and prediction of Remaining Useful Lifetime (RUL). For this purpose, lifetime models describing the relation between system/component degradation and consumed lifetime have to be established. In this contribution modeling and selection of suitable lifetime models from database based on current SoH conditions are discussed. Main contribution of this paper is the development of new modeling strategies capable to describe complex relations between measurable system variables, related system degradation, and RUL. Two approaches with accompanying advantages and disadvantages are introduced and compared. Both approaches are capable to model stochastic aging processes of a system by simultaneous adaption of RUL models to current SoH. The first approach requires a priori knowledge about aging processes in the system and accurate estimation of SoH. An estimation of SoH here is conditioned by tracking actual accumulated damage into the system, so that particular model parameters are defined according to a priori known assumptions about system's aging. Prediction accuracy in this case is highly dependent on accurate estimation of SoH but includes high number of degrees of freedom. The second approach in this contribution does not require a priori knowledge about system's aging as particular model parameters are defined in accordance to multi-objective optimization procedure. Prediction accuracy of this model does not highly depend on estimated SoH. This model has lower degrees of freedom. Both approaches rely on previously developed lifetime models each of them corresponding to predefined SoH. Concerning first approach, model selection is aided by state-machine-based algorithm. In the second approach, model selection conditioned by tracking an exceedance of predefined thresholds is concerned. The approach is applied to data generated from tribological systems. By calculating Root Squared Error (RSE), Mean Squared Error (MSE), and Absolute Error (ABE) the accuracy of proposed models/approaches is discussed along with related advantages and disadvantages. Verification of the approach is done using cross-fold validation, exchanging training and test data. It can be stated that the newly introduced approach based on data (denoted as data-based or data-driven) parametric models can be easily established providing detailed information about remaining useful/consumed lifetime valid for systems with constant load but stochastically occurred damage.

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

PubMed Central

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

2014-01-01

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

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

PubMed

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

2014-01-01

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

A real-time spiking cerebellum model for learning robot control.

PubMed

Carrillo, Richard R; Ros, Eduardo; Boucheny, Christian; Coenen, Olivier J-M D

2008-01-01

We describe a neural network model of the cerebellum based on integrate-and-fire spiking neurons with conductance-based synapses. The neuron characteristics are derived from our earlier detailed models of the different cerebellar neurons. We tested the cerebellum model in a real-time control application with a robotic platform. Delays were introduced in the different sensorimotor pathways according to the biological system. The main plasticity in the cerebellar model is a spike-timing dependent plasticity (STDP) at the parallel fiber to Purkinje cell connections. This STDP is driven by the inferior olive (IO) activity, which encodes an error signal using a novel probabilistic low frequency model. We demonstrate the cerebellar model in a robot control system using a target-reaching task. We test whether the system learns to reach different target positions in a non-destructive way, therefore abstracting a general dynamics model. To test the system's ability to self-adapt to different dynamical situations, we present results obtained after changing the dynamics of the robotic platform significantly (its friction and load). The experimental results show that the cerebellar-based system is able to adapt dynamically to different contexts.

PID-based error signal modeling

NASA Astrophysics Data System (ADS)

Yohannes, Tesfay

1997-10-01

This paper introduces a PID based signal error modeling. The error modeling is based on the betterment process. The resulting iterative learning algorithm is introduced and a detailed proof is provided for both linear and nonlinear systems.

Unified modeling language and design of a case-based retrieval system in medical imaging.

PubMed Central

LeBozec, C.; Jaulent, M. C.; Zapletal, E.; Degoulet, P.

1998-01-01

One goal of artificial intelligence research into case-based reasoning (CBR) systems is to develop approaches for designing useful and practical interactive case-based environments. Explaining each step of the design of the case-base and of the retrieval process is critical for the application of case-based systems to the real world. We describe herein our approach to the design of IDEM--Images and Diagnosis from Examples in Medicine--a medical image case-based retrieval system for pathologists. Our approach is based on the expressiveness of an object-oriented modeling language standard: the Unified Modeling Language (UML). We created a set of diagrams in UML notation illustrating the steps of the CBR methodology we used. The key aspect of this approach was selecting the relevant objects of the system according to user requirements and making visualization of cases and of the components of the case retrieval process. Further evaluation of the expressiveness of the design document is required but UML seems to be a promising formalism, improving the communication between the developers and users. Images Figure 6 Figure 7 PMID:9929346

Unified modeling language and design of a case-based retrieval system in medical imaging.

PubMed

LeBozec, C; Jaulent, M C; Zapletal, E; Degoulet, P

1998-01-01

One goal of artificial intelligence research into case-based reasoning (CBR) systems is to develop approaches for designing useful and practical interactive case-based environments. Explaining each step of the design of the case-base and of the retrieval process is critical for the application of case-based systems to the real world. We describe herein our approach to the design of IDEM--Images and Diagnosis from Examples in Medicine--a medical image case-based retrieval system for pathologists. Our approach is based on the expressiveness of an object-oriented modeling language standard: the Unified Modeling Language (UML). We created a set of diagrams in UML notation illustrating the steps of the CBR methodology we used. The key aspect of this approach was selecting the relevant objects of the system according to user requirements and making visualization of cases and of the components of the case retrieval process. Further evaluation of the expressiveness of the design document is required but UML seems to be a promising formalism, improving the communication between the developers and users.

Implementation of a Goal-Based Systems Engineering Process Using the Systems Modeling Language (SysML)

NASA Technical Reports Server (NTRS)

Breckenridge, Jonathan T.; Johnson, Stephen B.

2013-01-01

This paper describes the core framework used to implement a Goal-Function Tree (GFT) based systems engineering process using the Systems Modeling Language. It defines a set of principles built upon by the theoretical approach described in the InfoTech 2013 ISHM paper titled "Goal-Function Tree Modeling for Systems Engineering and Fault Management" presented by Dr. Stephen B. Johnson. Using the SysML language, the principles in this paper describe the expansion of the SysML language as a baseline in order to: hierarchically describe a system, describe that system functionally within success space, and allocate detection mechanisms to success functions for system protection.

Systems biology by the rules: hybrid intelligent systems for pathway modeling and discovery.

PubMed

Bosl, William J

2007-02-15

Expert knowledge in journal articles is an important source of data for reconstructing biological pathways and creating new hypotheses. An important need for medical research is to integrate this data with high throughput sources to build useful models that span several scales. Researchers traditionally use mental models of pathways to integrate information and development new hypotheses. Unfortunately, the amount of information is often overwhelming and these are inadequate for predicting the dynamic response of complex pathways. Hierarchical computational models that allow exploration of semi-quantitative dynamics are useful systems biology tools for theoreticians, experimentalists and clinicians and may provide a means for cross-communication. A novel approach for biological pathway modeling based on hybrid intelligent systems or soft computing technologies is presented here. Intelligent hybrid systems, which refers to several related computing methods such as fuzzy logic, neural nets, genetic algorithms, and statistical analysis, has become ubiquitous in engineering applications for complex control system modeling and design. Biological pathways may be considered to be complex control systems, which medicine tries to manipulate to achieve desired results. Thus, hybrid intelligent systems may provide a useful tool for modeling biological system dynamics and computational exploration of new drug targets. A new modeling approach based on these methods is presented in the context of hedgehog regulation of the cell cycle in granule cells. Code and input files can be found at the Bionet website: www.chip.ord/~wbosl/Software/Bionet. This paper presents the algorithmic methods needed for modeling complicated biochemical dynamics using rule-based models to represent expert knowledge in the context of cell cycle regulation and tumor growth. A notable feature of this modeling approach is that it allows biologists to build complex models from their knowledge base without the need to translate that knowledge into mathematical form. Dynamics on several levels, from molecular pathways to tissue growth, are seamlessly integrated. A number of common network motifs are examined and used to build a model of hedgehog regulation of the cell cycle in cerebellar neurons, which is believed to play a key role in the etiology of medulloblastoma, a devastating childhood brain cancer.

Interpreting experimental data on egg production--applications of dynamic differential equations.

PubMed

France, J; Lopez, S; Kebreab, E; Dijkstra, J

2013-09-01

This contribution focuses on applying mathematical models based on systems of ordinary first-order differential equations to synthesize and interpret data from egg production experiments. Models based on linear systems of differential equations are contrasted with those based on nonlinear systems. Regression equations arising from analytical solutions to linear compartmental schemes are considered as candidate functions for describing egg production curves, together with aspects of parameter estimation. Extant candidate functions are reviewed, a role for growth functions such as the Gompertz equation suggested, and a function based on a simple new model outlined. Structurally, the new model comprises a single pool with an inflow and an outflow. Compartmental simulation models based on nonlinear systems of differential equations, and thus requiring numerical solution, are next discussed, and aspects of parameter estimation considered. This type of model is illustrated in relation to development and evaluation of a dynamic model of calcium and phosphorus flows in layers. The model consists of 8 state variables representing calcium and phosphorus pools in the crop, stomachs, plasma, and bone. The flow equations are described by Michaelis-Menten or mass action forms. Experiments that measure Ca and P uptake in layers fed different calcium concentrations during shell-forming days are used to evaluate the model. In addition to providing a useful management tool, such a simulation model also provides a means to evaluate feeding strategies aimed at reducing excretion of potential pollutants in poultry manure to the environment.

Urban stormwater inundation simulation based on SWMM and diffusive overland-flow model.

PubMed

Chen, Wenjie; Huang, Guoru; Zhang, Han

2017-12-01

With rapid urbanization, inundation-induced property losses have become more and more severe. Urban inundation modeling is an effective way to reduce these losses. This paper introduces a simplified urban stormwater inundation simulation model based on the United States Environmental Protection Agency Storm Water Management Model (SWMM) and a geographic information system (GIS)-based diffusive overland-flow model. SWMM is applied for computation of flows in storm sewer systems and flooding flows at junctions, while the GIS-based diffusive overland-flow model simulates surface runoff and inundation. One observed rainfall scenario on Haidian Island, Hainan Province, China was chosen to calibrate the model and the other two were used for validation. Comparisons of the model results with field-surveyed data and InfoWorks ICM (Integrated Catchment Modeling) modeled results indicated the inundation model in this paper can provide inundation extents and reasonable inundation depths even in a large study area.

A systems-based approach for integrated design of materials, products and design process chains

NASA Astrophysics Data System (ADS)

Panchal, Jitesh H.; Choi, Hae-Jin; Allen, Janet K.; McDowell, David L.; Mistree, Farrokh

2007-12-01

The concurrent design of materials and products provides designers with flexibility to achieve design objectives that were not previously accessible. However, the improved flexibility comes at a cost of increased complexity of the design process chains and the materials simulation models used for executing the design chains. Efforts to reduce the complexity generally result in increased uncertainty. We contend that a systems based approach is essential for managing both the complexity and the uncertainty in design process chains and simulation models in concurrent material and product design. Our approach is based on simplifying the design process chains systematically such that the resulting uncertainty does not significantly affect the overall system performance. Similarly, instead of striving for accurate models for multiscale systems (that are inherently complex), we rely on making design decisions that are robust to uncertainties in the models. Accordingly, we pursue hierarchical modeling in the context of design of multiscale systems. In this paper our focus is on design process chains. We present a systems based approach, premised on the assumption that complex systems can be designed efficiently by managing the complexity of design process chains. The approach relies on (a) the use of reusable interaction patterns to model design process chains, and (b) consideration of design process decisions using value-of-information based metrics. The approach is illustrated using a Multifunctional Energetic Structural Material (MESM) design example. Energetic materials store considerable energy which can be released through shock-induced detonation; conventionally, they are not engineered for strength properties. The design objectives for the MESM in this paper include both sufficient strength and energy release characteristics. The design is carried out by using models at different length and time scales that simulate different aspects of the system. Finally, by applying the method to the MESM design problem, we show that the integrated design of materials and products can be carried out more efficiently by explicitly accounting for design process decisions with the hierarchy of models.

Modeling of a 5-cell direct methanol fuel cell using adaptive-network-based fuzzy inference systems

NASA Astrophysics Data System (ADS)

Wang, Rongrong; Qi, Liang; Xie, Xiaofeng; Ding, Qingqing; Li, Chunwen; Ma, ChenChi M.

The methanol concentrations, temperature and current were considered as inputs, the cell voltage was taken as output, and the performance of a direct methanol fuel cell (DMFC) was modeled by adaptive-network-based fuzzy inference systems (ANFIS). The artificial neural network (ANN) and polynomial-based models were selected to be compared with the ANFIS in respect of quality and accuracy. Based on the ANFIS model obtained, the characteristics of the DMFC were studied. The results show that temperature and methanol concentration greatly affect the performance of the DMFC. Within a restricted current range, the methanol concentration does not greatly affect the stack voltage. In order to obtain higher fuel utilization efficiency, the methanol concentrations and temperatures should be adjusted according to the load on the system.

Modeling nurses' attitude toward using automated unit-based medication storage and distribution systems: an extension of the technology acceptance model.

PubMed

Escobar-Rodríguez, Tomás; Romero-Alonso, María Mercedes

2013-05-01

This article analyzes the attitude of nurses toward the use of automated unit-based medication storage and distribution systems and identifies influencing factors. Understanding these factors provides an opportunity to explore actions that might be taken to boost adoption by potential users. The theoretical grounding for this research is the Technology Acceptance Model. The Technology Acceptance Model specifies the causal relationships between perceived usefulness, perceived ease of use, attitude toward using, and actual usage behavior. The research model has six constructs, and nine hypotheses were generated from connections between these six constructs. These constructs include perceived risks, experience level, and training. The findings indicate that these three external variables are related to the perceived ease of use and perceived usefulness of automated unit-based medication storage and distribution systems, and therefore, they have a significant influence on attitude toward the use of these systems.

Universal block diagram based modeling and simulation schemes for fractional-order control systems.

PubMed

Bai, Lu; Xue, Dingyü

2017-05-08

Universal block diagram based schemes are proposed for modeling and simulating the fractional-order control systems in this paper. A fractional operator block in Simulink is designed to evaluate the fractional-order derivative and integral. Based on the block, the fractional-order control systems with zero initial conditions can be modeled conveniently. For modeling the system with nonzero initial conditions, the auxiliary signal is constructed in the compensation scheme. Since the compensation scheme is very complicated, therefore the integrator chain scheme is further proposed to simplify the modeling procedures. The accuracy and effectiveness of the schemes are assessed in the examples, the computation results testify the block diagram scheme is efficient for all Caputo fractional-order ordinary differential equations (FODEs) of any complexity, including the implicit Caputo FODEs. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

Cyanobacterial Biofuels: Strategies and Developments on Network and Modeling.

PubMed

Klanchui, Amornpan; Raethong, Nachon; Prommeenate, Peerada; Vongsangnak, Wanwipa; Meechai, Asawin

Cyanobacteria, the phototrophic microorganisms, have attracted much attention recently as a promising source for environmentally sustainable biofuels production. However, barriers for commercial markets of cyanobacteria-based biofuels concern the economic feasibility. Miscellaneous strategies for improving the production performance of cyanobacteria have thus been developed. Among these, the simple ad hoc strategies resulting in failure to optimize fully cell growth coupled with desired product yield are explored. With the advancement of genomics and systems biology, a new paradigm toward systems metabolic engineering has been recognized. In particular, a genome-scale metabolic network reconstruction and modeling is a crucial systems-based tool for whole-cell-wide investigation and prediction. In this review, the cyanobacterial genome-scale metabolic models, which offer a system-level understanding of cyanobacterial metabolism, are described. The main process of metabolic network reconstruction and modeling of cyanobacteria are summarized. Strategies and developments on genome-scale network and modeling through the systems metabolic engineering approach are advanced and employed for efficient cyanobacterial-based biofuels production.

A 3D Model Based Imdoor Navigation System for Hubei Provincial Museum

NASA Astrophysics Data System (ADS)

Xu, W.; Kruminaite, M.; Onrust, B.; Liu, H.; Xiong, Q.; Zlatanova, S.

2013-11-01

3D models are more powerful than 2D maps for indoor navigation in a complicate space like Hubei Provincial Museum because they can provide accurate descriptions of locations of indoor objects (e.g., doors, windows, tables) and context information of these objects. In addition, the 3D model is the preferred navigation environment by the user according to the survey. Therefore a 3D model based indoor navigation system is developed for Hubei Provincial Museum to guide the visitors of museum. The system consists of three layers: application, web service and navigation, which is built to support localization, navigation and visualization functions of the system. There are three main strengths of this system: it stores all data needed in one database and processes most calculations on the webserver which make the mobile client very lightweight, the network used for navigation is extracted semi-automatically and renewable, the graphic user interface (GUI), which is based on a game engine, has high performance of visualizing 3D model on a mobile display.

Frequency Response Function Expansion for Unmeasured Translation and Rotation Dofs for Impedance Modelling Applications

NASA Astrophysics Data System (ADS)

Avitabile, P.; O'Callahan, J.

2003-07-01

Inclusion of rotational effects is critical for the accuracy of the predicted system characteristics, in almost all system modelling studies. However, experimentally derived information for the description of one or more of the components for the system will generally not have any rotational effects included in the description of the component. The lack of rotational effects has long affected the results from any system model development whether using a modal-based approach or an impedance-based approach. Several new expansion processes are described herein for the development of FRFs needed for impedance-based system models. These techniques expand experimentally derived mode shapes, residual modes from the modal parameter estimation process and FRFs directly to allow for the inclusion of the necessary rotational dof. The FRFs involving translational to rotational dofs are developed as well as the rotational to rotational dof. Examples are provided to show the use of these techniques.

New York State energy-analytic information system: first-stage implementation

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

Allentuck, J.; Carroll, O.; Fiore, L.

1979-09-01

So that energy policy by state government may be formulated within the constraints imposed by policy determined at the national level - yet reflect the diverse interests of its citizens - large quantities of data and sophisticated analytic capabilities are required. This report presents the design of an energy-information/analytic system for New York State, the data for a base year, 1976, and projections of these data. At the county level, 1976 energy-supply demand data and electric generating plant data are provided as well. Data-base management is based on System 2000. Three computerized models provide the system's basic analytic capacity. Themore » Brookhaven Energy System Network Simulator provides an integrating framework while a price-response model and a weather sensitive energy demand model furnished a short-term energy response estimation capability. The operation of these computerized models is described. 62 references, 25 figures, 39 tables.« less

Integration of Evidence into a Detailed Clinical Model-based Electronic Nursing Record System

PubMed Central

Park, Hyeoun-Ae; Jeon, Eunjoo; Chung, Eunja

2012-01-01

Objectives The purpose of this study was to test the feasibility of an electronic nursing record system for perinatal care that is based on detailed clinical models and clinical practice guidelines in perinatal care. Methods This study was carried out in five phases: 1) generating nursing statements using detailed clinical models; 2) identifying the relevant evidence; 3) linking nursing statements with the evidence; 4) developing a prototype electronic nursing record system based on detailed clinical models and clinical practice guidelines; and 5) evaluating the prototype system. Results We first generated 799 nursing statements describing nursing assessments, diagnoses, interventions, and outcomes using entities, attributes, and value sets of detailed clinical models for perinatal care which we developed in a previous study. We then extracted 506 recommendations from nine clinical practice guidelines and created sets of nursing statements to be used for nursing documentation by grouping nursing statements according to these recommendations. Finally, we developed and evaluated a prototype electronic nursing record system that can provide nurses with recommendations for nursing practice and sets of nursing statements based on the recommendations for guiding nursing documentation. Conclusions The prototype system was found to be sufficiently complete, relevant, useful, and applicable in terms of content, and easy to use and useful in terms of system user interface. This study has revealed the feasibility of developing such an ENR system. PMID:22844649

System Identification of a Heaving Point Absorber: Design of Experiment and Device Modeling

DOE PAGES

Bacelli, Giorgio; Coe, Ryan; Patterson, David; ...

2017-04-01

Empirically based modeling is an essential aspect of design for a wave energy converter. These models are used in structural, mechanical and control design processes, as well as for performance prediction. The design of experiments and methods used to produce models from collected data have a strong impact on the quality of the model. This study considers the system identification and model validation process based on data collected from a wave tank test of a model-scale wave energy converter. Experimental design and data processing techniques based on general system identification procedures are discussed and compared with the practices often followedmore » for wave tank testing. The general system identification processes are shown to have a number of advantages. The experimental data is then used to produce multiple models for the dynamics of the device. These models are validated and their performance is compared against one and other. Furthermore, while most models of wave energy converters use a formulation with wave elevation as an input, this study shows that a model using a hull pressure sensor to incorporate the wave excitation phenomenon has better accuracy.« less

System Identification of a Heaving Point Absorber: Design of Experiment and Device Modeling

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

Bacelli, Giorgio; Coe, Ryan; Patterson, David

Empirically based modeling is an essential aspect of design for a wave energy converter. These models are used in structural, mechanical and control design processes, as well as for performance prediction. The design of experiments and methods used to produce models from collected data have a strong impact on the quality of the model. This study considers the system identification and model validation process based on data collected from a wave tank test of a model-scale wave energy converter. Experimental design and data processing techniques based on general system identification procedures are discussed and compared with the practices often followedmore » for wave tank testing. The general system identification processes are shown to have a number of advantages. The experimental data is then used to produce multiple models for the dynamics of the device. These models are validated and their performance is compared against one and other. Furthermore, while most models of wave energy converters use a formulation with wave elevation as an input, this study shows that a model using a hull pressure sensor to incorporate the wave excitation phenomenon has better accuracy.« less

Model-based system engineering approach for the Euclid mission to manage scientific and technical complexity

NASA Astrophysics Data System (ADS)

Lorenzo Alvarez, Jose; Metselaar, Harold; Amiaux, Jerome; Saavedra Criado, Gonzalo; Gaspar Venancio, Luis M.; Salvignol, Jean-Christophe; Laureijs, René J.; Vavrek, Roland

2016-08-01

In the last years, the system engineering field is coming to terms with a paradigm change in the approach for complexity management. Different strategies have been proposed to cope with highly interrelated systems, system of systems and collaborative system engineering have been proposed and a significant effort is being invested into standardization and ontology definition. In particular, Model Based System Engineering (MBSE) intends to introduce methodologies for a systematic system definition, development, validation, deployment, operation and decommission, based on logical and visual relationship mapping, rather than traditional 'document based' information management. The practical implementation in real large-scale projects is not uniform across fields. In space science missions, the usage has been limited to subsystems or sample projects with modeling being performed 'a-posteriori' in many instances. The main hurdle for the introduction of MBSE practices in new projects is still the difficulty to demonstrate their added value to a project and whether their benefit is commensurate with the level of effort required to put them in place. In this paper we present the implemented Euclid system modeling activities, and an analysis of the benefits and limitations identified to support in particular requirement break-down and allocation, and verification planning at mission level.

Use of Model-Based Design Methods for Enhancing Resiliency Analysis of Unmanned Aerial Vehicles

NASA Astrophysics Data System (ADS)

Knox, Lenora A.

The most common traditional non-functional requirement analysis is reliability. With systems becoming more complex, networked, and adaptive to environmental uncertainties, system resiliency has recently become the non-functional requirement analysis of choice. Analysis of system resiliency has challenges; which include, defining resilience for domain areas, identifying resilience metrics, determining resilience modeling strategies, and understanding how to best integrate the concepts of risk and reliability into resiliency. Formal methods that integrate all of these concepts do not currently exist in specific domain areas. Leveraging RAMSoS, a model-based reliability analysis methodology for Systems of Systems (SoS), we propose an extension that accounts for resiliency analysis through evaluation of mission performance, risk, and cost using multi-criteria decision-making (MCDM) modeling and design trade study variability modeling evaluation techniques. This proposed methodology, coined RAMSoS-RESIL, is applied to a case study in the multi-agent unmanned aerial vehicle (UAV) domain to investigate the potential benefits of a mission architecture where functionality to complete a mission is disseminated across multiple UAVs (distributed) opposed to being contained in a single UAV (monolithic). The case study based research demonstrates proof of concept for the proposed model-based technique and provides sufficient preliminary evidence to conclude which architectural design (distributed vs. monolithic) is most resilient based on insight into mission resilience performance, risk, and cost in addition to the traditional analysis of reliability.

A control-oriented lithium-ion battery pack model for plug-in hybrid electric vehicle cycle-life studies and system design with consideration of health management

NASA Astrophysics Data System (ADS)

Cordoba-Arenas, Andrea; Onori, Simona; Rizzoni, Giorgio

2015-04-01

A crucial step towards the large-scale introduction of plug-in hybrid electric vehicles (PHEVs) in the market is to reduce the cost of its battery systems. Currently, battery cycle- and calendar-life represents one of the greatest uncertainties in the total life-cycle cost of battery systems. The field of battery aging modeling and prognosis has seen progress with respect to model-based and data-driven approaches to describe the aging of battery cells. However, in real world applications cells are interconnected and aging propagates. The propagation of aging from one cell to others exhibits itself in a reduced battery system life. This paper proposes a control-oriented battery pack model that describes the propagation of aging and its effect on the life span of battery systems. The modeling approach is such that it is able to predict pack aging, thermal, and electrical dynamics under actual PHEV operation, and includes consideration of random variability of the cells, electrical topology and thermal management. The modeling approach is based on the interaction between dynamic system models of the electrical and thermal dynamics, and dynamic models of cell aging. The system-level state-of-health (SOH) is assessed based on knowledge of individual cells SOH, pack electrical topology and voltage equalization approach.

Space weather forecasting with a Multimodel Ensemble Prediction System (MEPS)

NASA Astrophysics Data System (ADS)

Schunk, R. W.; Scherliess, L.; Eccles, V.; Gardner, L. C.; Sojka, J. J.; Zhu, L.; Pi, X.; Mannucci, A. J.; Butala, M.; Wilson, B. D.; Komjathy, A.; Wang, C.; Rosen, G.

2016-07-01

The goal of the Multimodel Ensemble Prediction System (MEPS) program is to improve space weather specification and forecasting with ensemble modeling. Space weather can have detrimental effects on a variety of civilian and military systems and operations, and many of the applications pertain to the ionosphere and upper atmosphere. Space weather can affect over-the-horizon radars, HF communications, surveying and navigation systems, surveillance, spacecraft charging, power grids, pipelines, and the Federal Aviation Administration (FAA's) Wide Area Augmentation System (WAAS). Because of its importance, numerous space weather forecasting approaches are being pursued, including those involving empirical, physics-based, and data assimilation models. Clearly, if there are sufficient data, the data assimilation modeling approach is expected to be the most reliable, but different data assimilation models can produce different results. Therefore, like the meteorology community, we created a Multimodel Ensemble Prediction System (MEPS) for the Ionosphere-Thermosphere-Electrodynamics (ITE) system that is based on different data assimilation models. The MEPS ensemble is composed of seven physics-based data assimilation models for the ionosphere, ionosphere-plasmasphere, thermosphere, high-latitude ionosphere-electrodynamics, and middle to low latitude ionosphere-electrodynamics. Hence, multiple data assimilation models can be used to describe each region. A selected storm event that was reconstructed with four different data assimilation models covering the middle and low latitude ionosphere is presented and discussed. In addition, the effect of different data types on the reconstructions is shown.

A Simulation Study Comparing Incineration and Composting in a Mars-Based Advanced Life Support System

NASA Technical Reports Server (NTRS)

Hogan, John; Kang, Sukwon; Cavazzoni, Jim; Levri, Julie; Finn, Cory; Luna, Bernadette (Technical Monitor)

2000-01-01

The objective of this study is to compare incineration and composting in a Mars-based advanced life support (ALS) system. The variables explored include waste pre-processing requirements, reactor sizing and buffer capacities. The study incorporates detailed mathematical models of biomass production and waste processing into an existing dynamic ALS system model. The ALS system and incineration models (written in MATLAB/SIMULINK(c)) were developed at the NASA Ames Research Center. The composting process is modeled using first order kinetics, with different degradation rates for individual waste components (carbohydrates, proteins, fats, cellulose and lignin). The biomass waste streams are generated using modified "Eneray Cascade" crop models, which use light- and dark-cycle temperatures, irradiance, photoperiod, [CO2], planting density, and relative humidity as model inputs. The study also includes an evaluation of equivalent system mass (ESM).

Application of optimization technique for flood damage modeling in river system

NASA Astrophysics Data System (ADS)

Barman, Sangita Deb; Choudhury, Parthasarathi

2018-04-01

A river system is defined as a network of channels that drains different parts of a basin uniting downstream to form a common outflow. An application of various models found in literatures, to a river system having multiple upstream flows is not always straight forward, involves a lengthy procedure; and with non-availability of data sets model calibration and applications may become difficult. In the case of a river system the flow modeling can be simplified to a large extent if the channel network is replaced by an equivalent single channel. In the present work optimization model formulations based on equivalent flow and applications of the mixed integer programming based pre-emptive goal programming model in evaluating flood control alternatives for a real life river system in India are proposed to be covered in the study.

Modeling convection-diffusion-reaction systems for microfluidic molecular communications with surface-based receivers in Internet of Bio-Nano Things

PubMed Central

Akan, Ozgur B.

2018-01-01

We consider a microfluidic molecular communication (MC) system, where the concentration-encoded molecular messages are transported via fluid flow-induced convection and diffusion, and detected by a surface-based MC receiver with ligand receptors placed at the bottom of the microfluidic channel. The overall system is a convection-diffusion-reaction system that can only be solved by numerical methods, e.g., finite element analysis (FEA). However, analytical models are key for the information and communication technology (ICT), as they enable an optimisation framework to develop advanced communication techniques, such as optimum detection methods and reliable transmission schemes. In this direction, we develop an analytical model to approximate the expected time course of bound receptor concentration, i.e., the received signal used to decode the transmitted messages. The model obviates the need for computationally expensive numerical methods by capturing the nonlinearities caused by laminar flow resulting in parabolic velocity profile, and finite number of ligand receptors leading to receiver saturation. The model also captures the effects of reactive surface depletion layer resulting from the mass transport limitations and moving reaction boundary originated from the passage of finite-duration molecular concentration pulse over the receiver surface. Based on the proposed model, we derive closed form analytical expressions that approximate the received pulse width, pulse delay and pulse amplitude, which can be used to optimize the system from an ICT perspective. We evaluate the accuracy of the proposed model by comparing model-based analytical results to the numerical results obtained by solving the exact system model with COMSOL Multiphysics. PMID:29415019

Modeling convection-diffusion-reaction systems for microfluidic molecular communications with surface-based receivers in Internet of Bio-Nano Things.

PubMed

Kuscu, Murat; Akan, Ozgur B

2018-01-01

We consider a microfluidic molecular communication (MC) system, where the concentration-encoded molecular messages are transported via fluid flow-induced convection and diffusion, and detected by a surface-based MC receiver with ligand receptors placed at the bottom of the microfluidic channel. The overall system is a convection-diffusion-reaction system that can only be solved by numerical methods, e.g., finite element analysis (FEA). However, analytical models are key for the information and communication technology (ICT), as they enable an optimisation framework to develop advanced communication techniques, such as optimum detection methods and reliable transmission schemes. In this direction, we develop an analytical model to approximate the expected time course of bound receptor concentration, i.e., the received signal used to decode the transmitted messages. The model obviates the need for computationally expensive numerical methods by capturing the nonlinearities caused by laminar flow resulting in parabolic velocity profile, and finite number of ligand receptors leading to receiver saturation. The model also captures the effects of reactive surface depletion layer resulting from the mass transport limitations and moving reaction boundary originated from the passage of finite-duration molecular concentration pulse over the receiver surface. Based on the proposed model, we derive closed form analytical expressions that approximate the received pulse width, pulse delay and pulse amplitude, which can be used to optimize the system from an ICT perspective. We evaluate the accuracy of the proposed model by comparing model-based analytical results to the numerical results obtained by solving the exact system model with COMSOL Multiphysics.

Wet scrubbing of biomass producer gas tars using vegetable oil

NASA Astrophysics Data System (ADS)

Bhoi, Prakashbhai Ramabhai

The overall aims of this research study were to generate novel design data and to develop an equilibrium stage-based thermodynamic model of a vegetable oil based wet scrubbing system for the removal of model tar compounds (benzene, toluene and ethylbenzene) found in biomass producer gas. The specific objectives were to design, fabricate and evaluate a vegetable oil based wet scrubbing system and to optimize the design and operating variables; i.e., packed bed height, vegetable oil type, solvent temperature, and solvent flow rate. The experimental wet packed bed scrubbing system includes a liquid distributor specifically designed to distribute a high viscous vegetable oil uniformly and a mixing section, which was designed to generate a desired concentration of tar compounds in a simulated air stream. A method and calibration protocol of gas chromatography/mass spectroscopy was developed to quantify tar compounds. Experimental data were analyzed statistically using analysis of variance (ANOVA) procedure. Statistical analysis showed that both soybean and canola oils are potential solvents, providing comparable removal efficiency of tar compounds. The experimental height equivalent to a theoretical plate (HETP) was determined as 0.11 m for vegetable oil based scrubbing system. Packed bed height and solvent temperature had highly significant effect (p0.05) effect on the removal of model tar compounds. The packing specific constants, Ch and CP,0, for the Billet and Schultes pressure drop correlation were determined as 2.52 and 2.93, respectively. The equilibrium stage based thermodynamic model predicted the removal efficiency of model tar compounds in the range of 1-6%, 1-4% and 1-2% of experimental data for benzene, toluene and ethylbenzene, respectively, for the solvent temperature of 30° C. The NRTL-PR property model and UNIFAC for estimating binary interaction parameters are recommended for modeling absorption of tar compounds in vegetable oils. Bench scale experimental data from the wet scrubbing system would be useful in the design and operation of a pilot scale vegetable oil based system. The process model, validated using experimental data, would be a key design tool for the design and optimization of a pilot scale vegetable oil based system.

A Risk-Based Approach for Aerothermal/TPS Analysis and Testing

NASA Technical Reports Server (NTRS)

Wright, Michael J.; Grinstead, Jay H.; Bose, Deepak

2007-01-01

The current status of aerothermal and thermal protection system modeling for civilian entry missions is reviewed. For most such missions, the accuracy of our simulations is limited not by the tools and processes currently employed, but rather by reducible deficiencies in the underlying physical models. Improving the accuracy of and reducing the uncertainties in these models will enable a greater understanding of the system level impacts of a particular thermal protection system and of the system operation and risk over the operational life of the system. A strategic plan will be laid out by which key modeling deficiencies can be identified via mission-specific gap analysis. Once these gaps have been identified, the driving component uncertainties are determined via sensitivity analyses. A Monte-Carlo based methodology is presented for physics-based probabilistic uncertainty analysis of aerothermodynamics and thermal protection system material response modeling. These data are then used to advocate for and plan focused testing aimed at reducing key uncertainties. The results of these tests are used to validate or modify existing physical models. Concurrently, a testing methodology is outlined for thermal protection materials. The proposed approach is based on using the results of uncertainty/sensitivity analyses discussed above to tailor ground testing so as to best identify and quantify system performance and risk drivers. A key component of this testing is understanding the relationship between the test and flight environments. No existing ground test facility can simultaneously replicate all aspects of the flight environment, and therefore good models for traceability to flight are critical to ensure a low risk, high reliability thermal protection system design. Finally, the role of flight testing in the overall thermal protection system development strategy is discussed.

Automatic human body modeling for vision-based motion capture system using B-spline parameterization of the silhouette

NASA Astrophysics Data System (ADS)

Jaume-i-Capó, Antoni; Varona, Javier; González-Hidalgo, Manuel; Mas, Ramon; Perales, Francisco J.

2012-02-01

Human motion capture has a wide variety of applications, and in vision-based motion capture systems a major issue is the human body model and its initialization. We present a computer vision algorithm for building a human body model skeleton in an automatic way. The algorithm is based on the analysis of the human shape. We decompose the body into its main parts by computing the curvature of a B-spline parameterization of the human contour. This algorithm has been applied in a context where the user is standing in front of a camera stereo pair. The process is completed after the user assumes a predefined initial posture so as to identify the main joints and construct the human model. Using this model, the initialization problem of a vision-based markerless motion capture system of the human body is solved.

Model-based object classification using unification grammars and abstract representations

NASA Astrophysics Data System (ADS)

Liburdy, Kathleen A.; Schalkoff, Robert J.

1993-04-01

The design and implementation of a high level computer vision system which performs object classification is described. General object labelling and functional analysis require models of classes which display a wide range of geometric variations. A large representational gap exists between abstract criteria such as `graspable' and current geometric image descriptions. The vision system developed and described in this work addresses this problem and implements solutions based on a fusion of semantics, unification, and formal language theory. Object models are represented using unification grammars, which provide a framework for the integration of structure and semantics. A methodology for the derivation of symbolic image descriptions capable of interacting with the grammar-based models is described and implemented. A unification-based parser developed for this system achieves object classification by determining if the symbolic image description can be unified with the abstract criteria of an object model. Future research directions are indicated.

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.

Design, fabrication and test of a trace contaminant control system

NASA Technical Reports Server (NTRS)

1975-01-01

A trace contaminant control system was designed, fabricated, and evaluated to determine suitability of the system concept to future manned spacecraft. Two different models were considered. The load model initially required by the contract was based on the Space Station Prototype (SSP) general specifications SVSK HS4655, reflecting a change from a 9 man crew to a 6 man crew of the model developed in previous phases of this effort. Trade studies and a system preliminary design were accomplished based on this contaminant load, including computer analyses to define the optimum system configuration in terms of component arrangements, flow rates and component sizing. At the completion of the preliminary design effort a revised contaminant load model was developed for the SSP. Additional analyses were then conducted to define the impact of this new contaminant load model on the system configuration. A full scale foam-core mock-up with the appropriate SSP system interfaces was also fabricated.

Using Model-Based Systems Engineering to Provide Artifacts for NASA Project Life-cycle and Technical Reviews

NASA Technical Reports Server (NTRS)

Parrott, Edith L.; Weiland, Karen J.

2017-01-01

This paper is for the AIAA Space Conference. The ability of systems engineers to use model-based systems engineering (MBSE) to generate self-consistent, up-to-date systems engineering products for project life-cycle and technical reviews is an important aspect for the continued and accelerated acceptance of MBSE. Currently, many review products are generated using labor-intensive, error-prone approaches based on documents, spreadsheets, and chart sets; a promised benefit of MBSE is that users will experience reductions in inconsistencies and errors. This work examines features of SysML that can be used to generate systems engineering products. Model elements, relationships, tables, and diagrams are identified for a large number of the typical systems engineering artifacts. A SysML system model can contain and generate most systems engineering products to a significant extent and this paper provides a guide on how to use MBSE to generate products for project life-cycle and technical reviews. The use of MBSE can reduce the schedule impact usually experienced for review preparation, as in many cases the review products can be auto-generated directly from the system model. These approaches are useful to systems engineers, project managers, review board members, and other key project stakeholders.

A Knowledge-Based and Model-Driven Requirements Engineering Approach to Conceptual Satellite Design

NASA Astrophysics Data System (ADS)

Dos Santos, Walter A.; Leonor, Bruno B. F.; Stephany, Stephan

Satellite systems are becoming even more complex, making technical issues a significant cost driver. The increasing complexity of these systems makes requirements engineering activities both more important and difficult. Additionally, today's competitive pressures and other market forces drive manufacturing companies to improve the efficiency with which they design and manufacture space products and systems. This imposes a heavy burden on systems-of-systems engineering skills and particularly on requirements engineering which is an important phase in a system's life cycle. When this is poorly performed, various problems may occur, such as failures, cost overruns and delays. One solution is to underpin the preliminary conceptual satellite design with computer-based information reuse and integration to deal with the interdisciplinary nature of this problem domain. This can be attained by taking a model-driven engineering approach (MDE), in which models are the main artifacts during system development. MDE is an emergent approach that tries to address system complexity by the intense use of models. This work outlines the use of SysML (Systems Modeling Language) and a novel knowledge-based software tool, named SatBudgets, to deal with these and other challenges confronted during the conceptual phase of a university satellite system, called ITASAT, currently being developed by INPE and some Brazilian universities.

A new extranodal scoring system based on the prognostically relevant extranodal sites in diffuse large B-cell lymphoma, not otherwise specified treated with chemoimmunotherapy.

PubMed

Hwang, Hee Sang; Yoon, Dok Hyun; Suh, Cheolwon; Huh, Jooryung

2016-08-01

Extranodal involvement is a well-known prognostic factor in patients with diffuse large B-cell lymphomas (DLBCL). Nevertheless, the prognostic impact of the extranodal scoring system included in the conventional international prognostic index (IPI) has been questioned in an era where rituximab treatment has become widespread. We investigated the prognostic impacts of individual sites of extranodal involvement in 761 patients with DLBCL who received rituximab-based chemoimmunotherapy. Subsequently, we established a new extranodal scoring system based on extranodal sites, showing significant prognostic correlation, and compared this system with conventional scoring systems, such as the IPI and the National Comprehensive Cancer Network-IPI (NCCN-IPI). An internal validation procedure, using bootstrapped samples, was also performed for both univariate and multivariate models. Using multivariate analysis with a backward variable selection, we found nine extranodal sites (the liver, lung, spleen, central nervous system, bone marrow, kidney, skin, adrenal glands, and peritoneum) that remained significant for use in the final model. Our newly established extranodal scoring system, based on these sites, was better correlated with patient survival than standard scoring systems, such as the IPI and the NCCN-IPI. Internal validation by bootstrapping demonstrated an improvement in model performance of our modified extranodal scoring system. Our new extranodal scoring system, based on the prognostically relevant sites, may improve the performance of conventional prognostic models of DLBCL in the rituximab era and warrants further external validation using large study populations.

Development of an EVA systems cost model. Volume 3: EVA systems cost model

NASA Technical Reports Server (NTRS)

1975-01-01

The EVA systems cost model presented is based on proposed EVA equipment for the space shuttle program. General information on EVA crewman requirements in a weightless environment and an EVA capabilities overview are provided.

Modeling of circulating fluised beds for post-combustion carbon capture

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

Lee, A.; Shadle, L.; Miller, D.

2011-01-01

A compartment based model for a circulating fluidized bed reactor has been developed based on experimental observations of riser hydrodynamics. The model uses a cluster based approach to describe the two-phase behavior of circulating fluidized beds. Fundamental mass balance equations have been derived to describe the movement of both gas and solids though the system. Additional work is being performed to develop the correlations required to describe the hydrodynamics of the system. Initial testing of the model with experimental data shows promising results and highlights the importance of including end effects within the model.

The AgESGUI geospatial simulation system for environmental model application and evaluation

USDA-ARS?s Scientific Manuscript database

Practical decision making in spatially-distributed environmental assessment and management is increasingly being based on environmental process-based models linked to geographical information systems (GIS). Furthermore, powerful computers and Internet-accessible assessment tools are providing much g...

A quality-based cost model for new electronic systems and products

NASA Astrophysics Data System (ADS)

Shina, Sammy G.; Saigal, Anil

1998-04-01

This article outlines a method for developing a quality-based cost model for the design of new electronic systems and products. The model incorporates a methodology for determining a cost-effective design margin allocation for electronic products and systems and its impact on manufacturing quality and cost. A spreadsheet-based cost estimating tool was developed to help implement this methodology in order for the system design engineers to quickly estimate the effect of design decisions and tradeoffs on the quality and cost of new products. The tool was developed with automatic spreadsheet connectivity to current process capability and with provisions to consider the impact of capital equipment and tooling purchases to reduce the product cost.

Category-theoretic models of algebraic computer systems

NASA Astrophysics Data System (ADS)

Kovalyov, S. P.

2016-01-01

A computer system is said to be algebraic if it contains nodes that implement unconventional computation paradigms based on universal algebra. A category-based approach to modeling such systems that provides a theoretical basis for mapping tasks to these systems' architecture is proposed. The construction of algebraic models of general-purpose computations involving conditional statements and overflow control is formally described by a reflector in an appropriate category of algebras. It is proved that this reflector takes the modulo ring whose operations are implemented in the conventional arithmetic processors to the Łukasiewicz logic matrix. Enrichments of the set of ring operations that form bases in the Łukasiewicz logic matrix are found.

INDUCTIVE SYSTEM HEALTH MONITORING WITH STATISTICAL METRICS

NASA Technical Reports Server (NTRS)

Iverson, David L.

2005-01-01

Model-based reasoning is a powerful method for performing system monitoring and diagnosis. Building models for model-based reasoning is often a difficult and time consuming process. The Inductive Monitoring System (IMS) software was developed to provide a technique to automatically produce health monitoring knowledge bases for systems that are either difficult to model (simulate) with a computer or which require computer models that are too complex to use for real time monitoring. IMS processes nominal data sets collected either directly from the system or from simulations to build a knowledge base that can be used to detect anomalous behavior in the system. Machine learning and data mining techniques are used to characterize typical system behavior by extracting general classes of nominal data from archived data sets. In particular, a clustering algorithm forms groups of nominal values for sets of related parameters. This establishes constraints on those parameter values that should hold during nominal operation. During monitoring, IMS provides a statistically weighted measure of the deviation of current system behavior from the established normal baseline. If the deviation increases beyond the expected level, an anomaly is suspected, prompting further investigation by an operator or automated system. IMS has shown potential to be an effective, low cost technique to produce system monitoring capability for a variety of applications. We describe the training and system health monitoring techniques of IMS. We also present the application of IMS to a data set from the Space Shuttle Columbia STS-107 flight. IMS was able to detect an anomaly in the launch telemetry shortly after a foam impact damaged Columbia's thermal protection system.

Applying Service-Oriented Architecture on The Development of Groundwater Modeling Support System

NASA Astrophysics Data System (ADS)

Li, C. Y.; WANG, Y.; Chang, L. C.; Tsai, J. P.; Hsiao, C. T.

2016-12-01

Groundwater simulation has become an essential step on the groundwater resources management and assessment. There are many stand-alone pre- and post-processing software packages to alleviate the model simulation loading, but the stand-alone software do not consider centralized management of data and simulation results neither do they provide network sharing functions. Hence, it is difficult to share and reuse the data and knowledge (simulation cases) systematically within or across companies. Therefore, this study develops a centralized and network based groundwater modeling support system to assist model construction. The system is based on service-oriented architecture and allows remote user to develop their modeling cases on internet. The data and cases (knowledge) are thus easy to manage centralized. MODFLOW is the modeling engine of the system, which is the most popular groundwater model in the world. The system provides a data warehouse to restore groundwater observations, MODFLOW Support Service, MODFLOW Input File & Shapefile Convert Service, MODFLOW Service, and Expert System Service to assist researchers to build models. Since the system architecture is service-oriented, it is scalable and flexible. The system can be easily extended to include the scenarios analysis and knowledge management to facilitate the reuse of groundwater modeling knowledge.

Modeling IoT-Based Solutions Using Human-Centric Wireless Sensor Networks

PubMed Central

Monares, Álvaro; Ochoa, Sergio F.; Santos, Rodrigo; Orozco, Javier; Meseguer, Roc

2014-01-01

The Internet of Things (IoT) has inspired solutions that are already available for addressing problems in various application scenarios, such as healthcare, security, emergency support and tourism. However, there is no clear approach to modeling these systems and envisioning their capabilities at the design time. Therefore, the process of designing these systems is ad hoc and its real impact is evaluated once the solution is already implemented, which is risky and expensive. This paper proposes a modeling approach that uses human-centric wireless sensor networks to specify and evaluate models of IoT-based systems at the time of design, avoiding the need to spend time and effort on early implementations of immature designs. It allows designers to focus on the system design, leaving the implementation decisions for a next phase. The article illustrates the usefulness of this proposal through a running example, showing the design of an IoT-based solution to support the first responses during medium-sized or large urban incidents. The case study used in the proposal evaluation is based on a real train crash. The proposed modeling approach can be used to design IoT-based systems for other application scenarios, e.g., to support security operatives or monitor chronic patients in their homes. PMID:25157549

Modeling IoT-based solutions using human-centric wireless sensor networks.

PubMed

Monares, Álvaro; Ochoa, Sergio F; Santos, Rodrigo; Orozco, Javier; Meseguer, Roc

2014-08-25

The Internet of Things (IoT) has inspired solutions that are already available for addressing problems in various application scenarios, such as healthcare, security, emergency support and tourism. However, there is no clear approach to modeling these systems and envisioning their capabilities at the design time. Therefore, the process of designing these systems is ad hoc and its real impact is evaluated once the solution is already implemented, which is risky and expensive. This paper proposes a modeling approach that uses human-centric wireless sensor networks to specify and evaluate models of IoT-based systems at the time of design, avoiding the need to spend time and effort on early implementations of immature designs. It allows designers to focus on the system design, leaving the implementation decisions for a next phase. The article illustrates the usefulness of this proposal through a running example, showing the design of an IoT-based solution to support the first responses during medium-sized or large urban incidents. The case study used in the proposal evaluation is based on a real train crash. The proposed modeling approach can be used to design IoT-based systems for other application scenarios, e.g., to support security operatives or monitor chronic patients in their homes.

Controlling Microbial Byproducts using Model-Based Substrate Monitoring and Control Strategies

NASA Technical Reports Server (NTRS)

Smernoff, David T.; Blackwell, Charles; Mancinelli, Rocco L.; DeVincenzi, Donald (Technical Monitor)

2000-01-01

We have developed a computer-controlled bioreactor system to study various aspects of microbially-mediated nitrogen cycling. The system has been used to investigate methods for controlling microbial denitrification (the dissimilatory reduction of nitrate to N2O and N2) in hydroponic plant growth chambers. Such chambers are key elements of advanced life support systems being designed for use on long duration space missions, but nitrogen use efficiency in them is reduced by denitrification. Control software architecture was designed which permits the heterogeneous control of system hardware using traditional feedback control, and quantitative and qualitative models of various system features. Model-based feed forward control entails prediction of future systems in states and automated regulation of system parameters to achieve desired and avoid undesirable system states. A bacterial growth rate model based on the classic Monod model of saturation kinetics was used to evaluate the response of several individual denitrifying species to varying environmental conditions. The system and models are now being applied to mixed microbial communities harvested from the root zone of a hydroponic growth chamber. The use of a modified Monod organism interaction model was evaluated as a means of achieving more accurate description of the dynamic behavior of the communities. A minimum variance parameter estimation routine was also' used to calibrate the constant parameters in the model by iterative evaluation of substrate (nitrate) uptake and growth kinetics. This representation of processes and interactions aids in the formulation of control laws. The feed forward control strategy being developed will increase system autonomy, reduce crew intervention and limit the accumulation of undesirable waste products (NOx).

Tools and techniques for developing policies for complex and uncertain systems.

PubMed

Bankes, Steven C

2002-05-14

Agent-based models (ABM) are examples of complex adaptive systems, which can be characterized as those systems for which no model less complex than the system itself can accurately predict in detail how the system will behave at future times. Consequently, the standard tools of policy analysis, based as they are on devising policies that perform well on some best estimate model of the system, cannot be reliably used for ABM. This paper argues that policy analysis by using ABM requires an alternative approach to decision theory. The general characteristics of such an approach are described, and examples are provided of its application to policy analysis.

Automated method for the systematic interpretation of resonance peaks in spectrum data

DOEpatents

Damiano, B.; Wood, R.T.

1997-04-22

A method is described for spectral signature interpretation. The method includes the creation of a mathematical model of a system or process. A neural network training set is then developed based upon the mathematical model. The neural network training set is developed by using the mathematical model to generate measurable phenomena of the system or process based upon model input parameter that correspond to the physical condition of the system or process. The neural network training set is then used to adjust internal parameters of a neural network. The physical condition of an actual system or process represented by the mathematical model is then monitored by extracting spectral features from measured spectra of the actual process or system. The spectral features are then input into said neural network to determine the physical condition of the system or process represented by the mathematical model. More specifically, the neural network correlates the spectral features (i.e. measurable phenomena) of the actual process or system with the corresponding model input parameters. The model input parameters relate to specific components of the system or process, and, consequently, correspond to the physical condition of the process or system. 1 fig.

TEXSYS. [a knowledge based system for the Space Station Freedom thermal control system test-bed

NASA Technical Reports Server (NTRS)

Bull, John

1990-01-01

The Systems Autonomy Demonstration Project has recently completed a major test and evaluation of TEXSYS, a knowledge-based system (KBS) which demonstrates real-time control and FDIR for the Space Station Freedom thermal control system test-bed. TEXSYS is the largest KBS ever developed by NASA and offers a unique opportunity for the study of technical issues associated with the use of advanced KBS concepts including: model-based reasoning and diagnosis, quantitative and qualitative reasoning, integrated use of model-based and rule-based representations, temporal reasoning, and scale-up performance issues. TEXSYS represents a major achievement in advanced automation that has the potential to significantly influence Space Station Freedom's design for the thermal control system. An overview of the Systems Autonomy Demonstration Project, the thermal control system test-bed, the TEXSYS architecture, preliminary test results, and thermal domain expert feedback are presented.

Model-based learning and the contribution of the orbitofrontal cortex to the model-free world

PubMed Central

McDannald, Michael A.; Takahashi, Yuji K.; Lopatina, Nina; Pietras, Brad W.; Jones, Josh L.; Schoenbaum, Geoffrey

2012-01-01

Learning is proposed to occur when there is a discrepancy between reward prediction and reward receipt. At least two separate systems are thought to exist: one in which predictions are proposed to be based on model-free or cached values; and another in which predictions are model-based. A basic neural circuit for model-free reinforcement learning has already been described. In the model-free circuit the ventral striatum (VS) is thought to supply a common-currency reward prediction to midbrain dopamine neurons that compute prediction errors and drive learning. In a model-based system, predictions can include more information about an expected reward, such as its sensory attributes or current, unique value. This detailed prediction allows for both behavioral flexibility and learning driven by changes in sensory features of rewards alone. Recent evidence from animal learning and human imaging suggests that, in addition to model-free information, the VS also signals model-based information. Further, there is evidence that the orbitofrontal cortex (OFC) signals model-based information. Here we review these data and suggest that the OFC provides model-based information to this traditional model-free circuitry and offer possibilities as to how this interaction might occur. PMID:22487030

Flutter suppression via piezoelectric actuation

NASA Technical Reports Server (NTRS)

Heeg, Jennifer

1991-01-01

Experimental flutter results obtained from wind tunnel tests of a two degree of freedom wind tunnel model are presented for the open and closed loop systems. The wind tunnel model is a two degree of freedom system which is actuated by piezoelectric plates configured as bimorphs. The model design was based on finite element structural analyses and flutter analyses. A control law was designed based on a discrete system model; gain feedback of strain measurements was utilized in the control task. The results show a 21 pct. increase in the flutter speed.

Introducing Model-Based System Engineering Transforming System Engineering through Model-Based Systems Engineering

DTIC Science & Technology

2014-03-31

BPMN ).  This  is  when  the   MITRE  Acquisition  Guidance  Model  (AGM)  model  effort  was...developed   using   the   iGrafx6   tool   with   BPMN   [12].   The   AGM   provides   a   high-­‐level   characterization  of...the  activities,  events  and  messages  using  a   BPMN  notation  as  shown  in  Figure  14.  It

Multilayer Insulation Ascent Venting Model

NASA Technical Reports Server (NTRS)

Tramel, R. W.; Sutherlin, S. G.; Johnson, W. L.

2017-01-01

The thermal and venting transient experienced by tank-applied multilayer insulation (MLI) in the Earth-to-orbit environment is very dynamic and not well characterized. This new predictive code is a first principles-based engineering model which tracks the time history of the mass and temperature (internal energy) of the gas in each MLI layer. A continuum-based model is used for early portions of the trajectory while a kinetic theory-based model is used for the later portions of the trajectory, and the models are blended based on a reference mean free path. This new capability should improve understanding of the Earth-to-orbit transient and enable better insulation system designs for in-space cryogenic propellant systems.

A Comparison of Exposure Control Procedures in CAT Systems Based on Different Measurement Models for Testlets

ERIC Educational Resources Information Center

Boyd, Aimee M.; Dodd, Barbara; Fitzpatrick, Steven

2013-01-01

This study compared several exposure control procedures for CAT systems based on the three-parameter logistic testlet response theory model (Wang, Bradlow, & Wainer, 2002) and Masters' (1982) partial credit model when applied to a pool consisting entirely of testlets. The exposure control procedures studied were the modified within 0.10 logits…

A Computer-Assisted Learning Model Based on the Digital Game Exponential Reward System

ERIC Educational Resources Information Center

Moon, Man-Ki; Jahng, Surng-Gahb; Kim, Tae-Yong

2011-01-01

The aim of this research was to construct a motivational model which would stimulate voluntary and proactive learning using digital game methods offering players more freedom and control. The theoretical framework of this research lays the foundation for a pedagogical learning model based on digital games. We analyzed the game reward system, which…

Retrosynthetic Reaction Prediction Using Neural Sequence-to-Sequence Models

PubMed Central

2017-01-01

We describe a fully data driven model that learns to perform a retrosynthetic reaction prediction task, which is treated as a sequence-to-sequence mapping problem. The end-to-end trained model has an encoder–decoder architecture that consists of two recurrent neural networks, which has previously shown great success in solving other sequence-to-sequence prediction tasks such as machine translation. The model is trained on 50,000 experimental reaction examples from the United States patent literature, which span 10 broad reaction types that are commonly used by medicinal chemists. We find that our model performs comparably with a rule-based expert system baseline model, and also overcomes certain limitations associated with rule-based expert systems and with any machine learning approach that contains a rule-based expert system component. Our model provides an important first step toward solving the challenging problem of computational retrosynthetic analysis. PMID:29104927

Wind Energy Conversion System Analysis Model (WECSAM) computer program documentation

NASA Astrophysics Data System (ADS)

Downey, W. T.; Hendrick, P. L.

1982-07-01

Described is a computer-based wind energy conversion system analysis model (WECSAM) developed to predict the technical and economic performance of wind energy conversion systems (WECS). The model is written in CDC FORTRAN V. The version described accesses a data base containing wind resource data, application loads, WECS performance characteristics, utility rates, state taxes, and state subsidies for a six state region (Minnesota, Michigan, Wisconsin, Illinois, Ohio, and Indiana). The model is designed for analysis at the county level. The computer model includes a technical performance module and an economic evaluation module. The modules can be run separately or together. The model can be run for any single user-selected county within the region or looped automatically through all counties within the region. In addition, the model has a restart capability that allows the user to modify any data-base value written to a scratch file prior to the technical or economic evaluation.

Advancing Physically-Based Flow Simulations of Alluvial Systems Through Atmospheric Noble Gases and the Novel 37Ar Tracer Method

NASA Astrophysics Data System (ADS)

Schilling, Oliver S.; Gerber, Christoph; Partington, Daniel J.; Purtschert, Roland; Brennwald, Matthias S.; Kipfer, Rolf; Hunkeler, Daniel; Brunner, Philip

2017-12-01

To provide a sound understanding of the sources, pathways, and residence times of groundwater water in alluvial river-aquifer systems, a combined multitracer and modeling experiment was carried out in an important alluvial drinking water wellfield in Switzerland. 222Rn, 3H/3He, atmospheric noble gases, and the novel 37Ar-method were used to quantify residence times and mixing ratios of water from different sources. With a half-life of 35.1 days, 37Ar allowed to successfully close a critical observational time gap between 222Rn and 3H/3He for residence times of weeks to months. Covering the entire range of residence times of groundwater in alluvial systems revealed that, to quantify the fractions of water from different sources in such systems, atmospheric noble gases and helium isotopes are tracers suited for end-member mixing analysis. A comparison between the tracer-based mixing ratios and mixing ratios simulated with a fully-integrated, physically-based flow model showed that models, which are only calibrated against hydraulic heads, cannot reliably reproduce mixing ratios or residence times of alluvial river-aquifer systems. However, the tracer-based mixing ratios allowed the identification of an appropriate flow model parametrization. Consequently, for alluvial systems, we recommend the combination of multitracer studies that cover all relevant residence times with fully-coupled, physically-based flow modeling to better characterize the complex interactions of river-aquifer systems.

Classifying the Indication for Colonoscopy Procedures: A Comparison of NLP Approaches in a Diverse National Healthcare System.

PubMed

Patterson, Olga V; Forbush, Tyler B; Saini, Sameer D; Moser, Stephanie E; DuVall, Scott L

2015-01-01

In order to measure the level of utilization of colonoscopy procedures, identifying the primary indication for the procedure is required. Colonoscopies may be utilized not only for screening, but also for diagnostic or therapeutic purposes. To determine whether a colonoscopy was performed for screening, we created a natural language processing system to identify colonoscopy reports in the electronic medical record system and extract indications for the procedure. A rule-based model and three machine-learning models were created using 2,000 manually annotated clinical notes of patients cared for in the Department of Veterans Affairs. Performance of the models was measured and compared. Analysis of the models on a test set of 1,000 documents indicates that the rule-based system performance stays fairly constant as evaluated on training and testing sets. However, the machine learning model without feature selection showed significant decrease in performance. Therefore, rule-based classification system appears to be more robust than a machine-learning system in cases when no feature selection is performed.

Integrating Intracellular Dynamics Using CompuCell3D and Bionetsolver: Applications to Multiscale Modelling of Cancer Cell Growth and Invasion

PubMed Central

Andasari, Vivi; Roper, Ryan T.; Swat, Maciej H.; Chaplain, Mark A. J.

2012-01-01

In this paper we present a multiscale, individual-based simulation environment that integrates CompuCell3D for lattice-based modelling on the cellular level and Bionetsolver for intracellular modelling. CompuCell3D or CC3D provides an implementation of the lattice-based Cellular Potts Model or CPM (also known as the Glazier-Graner-Hogeweg or GGH model) and a Monte Carlo method based on the metropolis algorithm for system evolution. The integration of CC3D for cellular systems with Bionetsolver for subcellular systems enables us to develop a multiscale mathematical model and to study the evolution of cell behaviour due to the dynamics inside of the cells, capturing aspects of cell behaviour and interaction that is not possible using continuum approaches. We then apply this multiscale modelling technique to a model of cancer growth and invasion, based on a previously published model of Ramis-Conde et al. (2008) where individual cell behaviour is driven by a molecular network describing the dynamics of E-cadherin and -catenin. In this model, which we refer to as the centre-based model, an alternative individual-based modelling technique was used, namely, a lattice-free approach. In many respects, the GGH or CPM methodology and the approach of the centre-based model have the same overall goal, that is to mimic behaviours and interactions of biological cells. Although the mathematical foundations and computational implementations of the two approaches are very different, the results of the presented simulations are compatible with each other, suggesting that by using individual-based approaches we can formulate a natural way of describing complex multi-cell, multiscale models. The ability to easily reproduce results of one modelling approach using an alternative approach is also essential from a model cross-validation standpoint and also helps to identify any modelling artefacts specific to a given computational approach. PMID:22461894

Archetype-based conversion of EHR content models: pilot experience with a regional EHR system

PubMed Central

2009-01-01

Background Exchange of Electronic Health Record (EHR) data between systems from different suppliers is a major challenge. EHR communication based on archetype methodology has been developed by openEHR and CEN/ISO. The experience of using archetypes in deployed EHR systems is quite limited today. Currently deployed EHR systems with large user bases have their own proprietary way of representing clinical content using various models. This study was designed to investigate the feasibility of representing EHR content models from a regional EHR system as openEHR archetypes and inversely to convert archetypes to the proprietary format. Methods The openEHR EHR Reference Model (RM) and Archetype Model (AM) specifications were used. The template model of the Cambio COSMIC, a regional EHR product from Sweden, was analyzed and compared to the openEHR RM and AM. This study was focused on the convertibility of the EHR semantic models. A semantic mapping between the openEHR RM/AM and the COSMIC template model was produced and used as the basis for developing prototype software that performs automated bi-directional conversion between openEHR archetypes and COSMIC templates. Results Automated bi-directional conversion between openEHR archetype format and COSMIC template format has been achieved. Several archetypes from the openEHR Clinical Knowledge Repository have been imported into COSMIC, preserving most of the structural and terminology related constraints. COSMIC templates from a large regional installation were successfully converted into the openEHR archetype format. The conversion from the COSMIC templates into archetype format preserves nearly all structural and semantic definitions of the original content models. A strategy of gradually adding archetype support to legacy EHR systems was formulated in order to allow sharing of clinical content models defined using different formats. Conclusion The openEHR RM and AM are expressive enough to represent the existing clinical content models from the template based EHR system tested and legacy content models can automatically be converted to archetype format for sharing of knowledge. With some limitations, internationally available archetypes could be converted to the legacy EHR models. Archetype support can be added to legacy EHR systems in an incremental way allowing a migration path to interoperability based on standards. PMID:19570196

A Corrosion Risk Assessment Model for Underground Piping

NASA Technical Reports Server (NTRS)

Datta, Koushik; Fraser, Douglas R.

2009-01-01

The Pressure Systems Manager at NASA Ames Research Center (ARC) has embarked on a project to collect data and develop risk assessment models to support risk-informed decision making regarding future inspections of underground pipes at ARC. This paper shows progress in one area of this project - a corrosion risk assessment model for the underground high-pressure air distribution piping system at ARC. It consists of a Corrosion Model of pipe-segments, a Pipe Wrap Protection Model; and a Pipe Stress Model for a pipe segment. A Monte Carlo simulation of the combined models provides a distribution of the failure probabilities. Sensitivity study results show that the model uncertainty, or lack of knowledge, is the dominant contributor to the calculated unreliability of the underground piping system. As a result, the Pressure Systems Manager may consider investing resources specifically focused on reducing these uncertainties. Future work includes completing the data collection effort for the existing ground based pressure systems and applying the risk models to risk-based inspection strategies of the underground pipes at ARC.

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

Modelling water uptake efficiency of root systems

NASA Astrophysics Data System (ADS)

Leitner, Daniel; Tron, Stefania; Schröder, Natalie; Bodner, Gernot; Javaux, Mathieu; Vanderborght, Jan; Vereecken, Harry; Schnepf, Andrea

2016-04-01

Water uptake is crucial for plant productivity. Trait based breeding for more water efficient crops will enable a sustainable agricultural management under specific pedoclimatic conditions, and can increase drought resistance of plants. Mathematical modelling can be used to find suitable root system traits for better water uptake efficiency defined as amount of water taken up per unit of root biomass. This approach requires large simulation times and large number of simulation runs, since we test different root systems under different pedoclimatic conditions. In this work, we model water movement by the 1-dimensional Richards equation with the soil hydraulic properties described according to the van Genuchten model. Climatic conditions serve as the upper boundary condition. The root system grows during the simulation period and water uptake is calculated via a sink term (after Tron et al. 2015). The goal of this work is to compare different free software tools based on different numerical schemes to solve the model. We compare implementations using DUMUX (based on finite volumes), Hydrus 1D (based on finite elements), and a Matlab implementation of Van Dam, J. C., & Feddes 2000 (based on finite differences). We analyse the methods for accuracy, speed and flexibility. Using this model case study, we can clearly show the impact of various root system traits on water uptake efficiency. Furthermore, we can quantify frequent simplifications that are introduced in the modelling step like considering a static root system instead of a growing one, or considering a sink term based on root density instead of considering the full root hydraulic model (Javaux et al. 2008). References Tron, S., Bodner, G., Laio, F., Ridolfi, L., & Leitner, D. (2015). Can diversity in root architecture explain plant water use efficiency? A modeling study. Ecological modelling, 312, 200-210. Van Dam, J. C., & Feddes, R. A. (2000). Numerical simulation of infiltration, evaporation and shallow groundwater levels with the Richards equation. Journal of Hydrology, 233(1), 72-85. Javaux, M., Schröder, T., Vanderborght, J., & Vereecken, H. (2008). Use of a three-dimensional detailed modeling approach for predicting root water uptake. Vadose Zone Journal, 7(3), 1079-1088.

Yet Another Adaptive Learning Management System Based on Felder and Silverman's Learning Styles and Mashup

ERIC Educational Resources Information Center

Chang, Yi-Hsing; Chen, Yen-Yi; Chen, Nian-Shing; Lu, You-Te; Fang, Rong-Jyue

2016-01-01

This study designs and implements an adaptive learning management system based on Felder and Silverman's Learning Style Model and the Mashup technology. In this system, Felder and Silverman's Learning Style model is used to assess students' learning styles, in order to provide adaptive learning to leverage learners' learning preferences.…

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.

Systems engineering in the Large Synoptic Survey Telescope project: an application of model based systems engineering

NASA Astrophysics Data System (ADS)

Claver, C. F.; Selvy, Brian M.; Angeli, George; Delgado, Francisco; Dubois-Felsmann, Gregory; Hascall, Patrick; Lotz, Paul; Marshall, Stuart; Schumacher, German; Sebag, Jacques

2014-08-01

The Large Synoptic Survey Telescope project was an early adopter of SysML and Model Based Systems Engineering practices. The LSST project began using MBSE for requirements engineering beginning in 2006 shortly after the initial release of the first SysML standard. Out of this early work the LSST's MBSE effort has grown to include system requirements, operational use cases, physical system definition, interfaces, and system states along with behavior sequences and activities. In this paper we describe our approach and methodology for cross-linking these system elements over the three classical systems engineering domains - requirement, functional and physical - into the LSST System Architecture model. We also show how this model is used as the central element to the overall project systems engineering effort. More recently we have begun to use the cross-linked modeled system architecture to develop and plan the system verification and test process. In presenting this work we also describe "lessons learned" from several missteps the project has had with MBSE. Lastly, we conclude by summarizing the overall status of the LSST's System Architecture model and our plans for the future as the LSST heads toward construction.

Creating system engineering products with executable models in a model-based engineering environment

NASA Astrophysics Data System (ADS)

Karban, Robert; Dekens, Frank G.; Herzig, Sebastian; Elaasar, Maged; Jankevičius, Nerijus

2016-08-01

Applying systems engineering across the life-cycle results in a number of products built from interdependent sources of information using different kinds of system level analysis. This paper focuses on leveraging the Executable System Engineering Method (ESEM) [1] [2], which automates requirements verification (e.g. power and mass budget margins and duration analysis of operational modes) using executable SysML [3] models. The particular value proposition is to integrate requirements, and executable behavior and performance models for certain types of system level analysis. The models are created with modeling patterns that involve structural, behavioral and parametric diagrams, and are managed by an open source Model Based Engineering Environment (named OpenMBEE [4]). This paper demonstrates how the ESEM is applied in conjunction with OpenMBEE to create key engineering products (e.g. operational concept document) for the Alignment and Phasing System (APS) within the Thirty Meter Telescope (TMT) project [5], which is under development by the TMT International Observatory (TIO) [5].

Analysis hierarchical model for discrete event systems

NASA Astrophysics Data System (ADS)

Ciortea, E. M.

2015-11-01

The This paper presents the hierarchical model based on discrete event network for robotic systems. Based on the hierarchical approach, Petri network is analysed as a network of the highest conceptual level and the lowest level of local control. For modelling and control of complex robotic systems using extended Petri nets. Such a system is structured, controlled and analysed in this paper by using Visual Object Net ++ package that is relatively simple and easy to use, and the results are shown as representations easy to interpret. The hierarchical structure of the robotic system is implemented on computers analysed using specialized programs. Implementation of hierarchical model discrete event systems, as a real-time operating system on a computer network connected via a serial bus is possible, where each computer is dedicated to local and Petri model of a subsystem global robotic system. Since Petri models are simplified to apply general computers, analysis, modelling, complex manufacturing systems control can be achieved using Petri nets. Discrete event systems is a pragmatic tool for modelling industrial systems. For system modelling using Petri nets because we have our system where discrete event. To highlight the auxiliary time Petri model using transport stream divided into hierarchical levels and sections are analysed successively. Proposed robotic system simulation using timed Petri, offers the opportunity to view the robotic time. Application of goods or robotic and transmission times obtained by measuring spot is obtained graphics showing the average time for transport activity, using the parameters sets of finished products. individually.

Measurement-based reliability prediction methodology. M.S. Thesis

NASA Technical Reports Server (NTRS)

Linn, Linda Shen

1991-01-01

In the past, analytical and measurement based models were developed to characterize computer system behavior. An open issue is how these models can be used, if at all, for system design improvement. The issue is addressed here. A combined statistical/analytical approach to use measurements from one environment to model the system failure behavior in a new environment is proposed. A comparison of the predicted results with the actual data from the new environment shows a close correspondence.

Structural Stability of Mathematical Models of National Economy

NASA Astrophysics Data System (ADS)

Ashimov, Abdykappar A.; Sultanov, Bahyt T.; Borovskiy, Yuriy V.; Adilov, Zheksenbek M.; Ashimov, Askar A.

2011-12-01

In the paper we test robustness of particular dynamic systems in a compact regions of a plane and a weak structural stability of one dynamic system of high order in a compact region of its phase space. The test was carried out based on the fundamental theory of dynamical systems on a plane and based on the conditions for weak structural stability of high order dynamic systems. A numerical algorithm for testing the weak structural stability of high order dynamic systems has been proposed. Based on this algorithm we assess the weak structural stability of one computable general equilibrium model.

Next Generation Community Based Unified Global Modeling System Development and Operational Implementation Strategies at NCEP

NASA Astrophysics Data System (ADS)

Tallapragada, V.

2017-12-01

NOAA's Next Generation Global Prediction System (NGGPS) has provided the unique opportunity to develop and implement a non-hydrostatic global model based on Geophysical Fluid Dynamics Laboratory (GFDL) Finite Volume Cubed Sphere (FV3) Dynamic Core at National Centers for Environmental Prediction (NCEP), making a leap-step advancement in seamless prediction capabilities across all spatial and temporal scales. Model development efforts are centralized with unified model development in the NOAA Environmental Modeling System (NEMS) infrastructure based on Earth System Modeling Framework (ESMF). A more sophisticated coupling among various earth system components is being enabled within NEMS following National Unified Operational Prediction Capability (NUOPC) standards. The eventual goal of unifying global and regional models will enable operational global models operating at convective resolving scales. Apart from the advanced non-hydrostatic dynamic core and coupling to various earth system components, advanced physics and data assimilation techniques are essential for improved forecast skill. NGGPS is spearheading ambitious physics and data assimilation strategies, concentrating on creation of a Common Community Physics Package (CCPP) and Joint Effort for Data Assimilation Integration (JEDI). Both initiatives are expected to be community developed, with emphasis on research transitioning to operations (R2O). The unified modeling system is being built to support the needs of both operations and research. Different layers of community partners are also established with specific roles/responsibilities for researchers, core development partners, trusted super-users, and operations. Stakeholders are engaged at all stages to help drive the direction of development, resources allocations and prioritization. This talk presents the current and future plans of unified model development at NCEP for weather, sub-seasonal, and seasonal climate prediction applications with special emphasis on implementation of NCEP FV3 Global Forecast System (GFS) and Global Ensemble Forecast System (GEFS) into operations by 2019.

Paraboloid magnetospheric magnetic field model and the status of the model as an ISO standard

NASA Astrophysics Data System (ADS)

Alexeev, I.

A reliable representation of the magnetic field is crucial in the framework of radiation belt modelling especially for disturbed conditions The empirical model developed by Tsyganenko T96 is constructed by minimizing the rms deviation from the large magnetospheric data base The applicability of the T96 model is limited mainly by quiet conditions in the solar wind along the Earth orbit But contrary to the internal planet s field the external magnetospheric magnetic field sources are much more time-dependent A reliable representation of the magnetic field is crucial in the framework of radiation belt modelling especially for disturbed conditions It is a reason why the method of the paraboloid magnetospheric model construction based on the more accurate and physically consistent approach in which each source of the magnetic field would have its own relaxation timescale and a driving function based on an individual best fit combination of the solar wind and IMF parameters Such approach is based on a priori information about the global magnetospheric current systems structure Each current system is included as a separate block module in the magnetospheric model As it was shown by the spacecraft magnetometer data there are three current systems which are the main contributors to the external magnetospheric magnetic field magnetopause currents ring current and tail current sheet Paraboloid model is based on an analytical solution of the Laplace equation for each of these large-scale current systems in the magnetosphere with a

The Curse of Planning: Dissecting multiple reinforcement learning systems by taxing the central executive

PubMed Central

Otto, A. Ross; Gershman, Samuel J.; Markman, Arthur B.; Daw, Nathaniel D.

2013-01-01

A number of accounts of human and animal behavior posit the operation of parallel and competing valuation systems in the control of choice behavior. Along these lines, a flexible but computationally expensive model-based reinforcement learning system has been contrasted with a less flexible but more efficient model-free reinforcement learning system. The factors governing which system controls behavior—and under what circumstances—are still unclear. Based on the hypothesis that model-based reinforcement learning requires cognitive resources, we demonstrate that having human decision-makers perform a demanding secondary task engenders increased reliance on a model-free reinforcement learning strategy. Further, we show that across trials, people negotiate this tradeoff dynamically as a function of concurrent executive function demands and their choice latencies reflect the computational expenses of the strategy employed. These results demonstrate that competition between multiple learning systems can be controlled on a trial-by-trial basis by modulating the availability of cognitive resources. PMID:23558545

A Petri Net-Based Software Process Model for Developing Process-Oriented Information Systems

NASA Astrophysics Data System (ADS)

Li, Yu; Oberweis, Andreas

Aiming at increasing flexibility, efficiency, effectiveness, and transparency of information processing and resource deployment in organizations to ensure customer satisfaction and high quality of products and services, process-oriented information systems (POIS) represent a promising realization form of computerized business information systems. Due to the complexity of POIS, explicit and specialized software process models are required to guide POIS development. In this chapter we characterize POIS with an architecture framework and present a Petri net-based software process model tailored for POIS development with consideration of organizational roles. As integrated parts of the software process model, we also introduce XML nets, a variant of high-level Petri nets as basic methodology for business processes modeling, and an XML net-based software toolset providing comprehensive functionalities for POIS development.

Application of a passivity based control methodology for flexible joint robots to a simplified Space Shuttle RMS

NASA Technical Reports Server (NTRS)

Sicard, Pierre; Wen, John T.

1992-01-01

A passivity approach for the control design of flexible joint robots is applied to the rate control of a three-link arm modeled after the shoulder yaw joint of the Space Shuttle Remote Manipulator System (RMS). The system model includes friction and elastic joint couplings modeled as nonlinear springs. The basic structure of the proposed controller is the sum of a model-based feedforward and a model-independent feedback. A regulator approach with link state feedback is employed to define the desired motor state. Passivity theory is used to design a motor state-based controller to stabilize the error system formed by the feedforward. Simulation results show that greatly improved performance was obtained by using the proposed controller over the existing RMS controller.

A System-Science Approach towards Model Construction for Curriculum Development.

ERIC Educational Resources Information Center

Chang, Ren-Jung; Yang, Hui-Chin

A new morphological model based on modern system science and engineering is constructed and proposed for curriculum research and development. A curriculum system is recognized as an engineering system that constitutes three components: clients, resources, and knowledge. Unlike the objective models that are purely rational and neatly sequential in…

The NASA Space Radiobiology Risk Assessment Project

NASA Astrophysics Data System (ADS)

Cucinotta, Francis A.; Huff, Janice; Ponomarev, Artem; Patel, Zarana; Kim, Myung-Hee

The current first phase (2006-2011) has the three major goals of: 1) optimizing the conventional cancer risk models currently used based on the double-detriment life-table and radiation quality functions; 2) the integration of biophysical models of acute radiation syndromes; and 3) the development of new systems radiation biology models of cancer processes. The first-phase also includes continued uncertainty assessment of space radiation environmental models and transport codes, and relative biological effectiveness factors (RBE) based on flight data and NSRL results, respectively. The second phase of the (2012-2016) will: 1) develop biophysical models of central nervous system risks (CNS); 2) achieve comphrensive systems biology models of cancer processes using data from proton and heavy ion studies performed at NSRL; and 3) begin to identify computational models of biological countermeasures. Goals for the third phase (2017-2021) include: 1) the development of a systems biology model of cancer risks for operational use at NASA; 2) development of models of degenerative risks, 2) quantitative models of counter-measure impacts on cancer risks; and 3) indiviudal based risk assessments. Finally, we will support a decision point to continue NSRL research in support of NASA's exploration goals beyond 2021, and create an archival of NSRL research results for continued analysis. Details on near term goals, plans for a WEB based data resource of NSRL results, and a space radiation Wikepedia are described.

New activity-based funding model for Australian private sector overnight rehabilitation cases: the rehabilitation Australian National Sub-Acute and Non-Acute Patient (AN-SNAP) model.

PubMed

Hanning, Brian; Predl, Nicolle

2015-09-01

Traditional overnight rehabilitation payment models in the private sector are not based on a rigorous classification system and vary greatly between contracts with no consideration of patient complexity. The payment rates are not based on relative cost and the length-of-stay (LOS) point at which a reduced rate applies (step downs) varies markedly. The rehabilitation Australian National Sub-Acute and Non-Acute Patient (AN-SNAP) model (RAM), which has been in place for over 2 years in some private hospitals, bases payment on a rigorous classification system, relative cost and industry LOS. RAM is in the process of being rolled out more widely. This paper compares and contrasts RAM with traditional overnight rehabilitation payment models. It considers the advantages of RAM for hospitals and Australian Health Service Alliance. It also considers payment model changes in the context of maintaining industry consistency with Electronic Claims Lodgement and Information Processing System Environment (ECLIPSE) and health reform generally.

Model-based control strategies for systems with constraints of the program type

NASA Astrophysics Data System (ADS)

Jarzębowska, Elżbieta

2006-08-01

The paper presents a model-based tracking control strategy for constrained mechanical systems. Constraints we consider can be material and non-material ones referred to as program constraints. The program constraint equations represent tasks put upon system motions and they can be differential equations of orders higher than one or two, and be non-integrable. The tracking control strategy relies upon two dynamic models: a reference model, which is a dynamic model of a system with arbitrary order differential constraints and a dynamic control model. The reference model serves as a motion planner, which generates inputs to the dynamic control model. It is based upon a generalized program motion equations (GPME) method. The method enables to combine material and program constraints and merge them both into the motion equations. Lagrange's equations with multipliers are the peculiar case of the GPME, since they can be applied to systems with constraints of first orders. Our tracking strategy referred to as a model reference program motion tracking control strategy enables tracking of any program motion predefined by the program constraints. It extends the "trajectory tracking" to the "program motion tracking". We also demonstrate that our tracking strategy can be extended to a hybrid program motion/force tracking.

Model-based reasoning for system and software engineering: The Knowledge From Pictures (KFP) environment

NASA Technical Reports Server (NTRS)

Bailin, Sydney; Paterra, Frank; Henderson, Scott; Truszkowski, Walt

1993-01-01

This paper presents a discussion of current work in the area of graphical modeling and model-based reasoning being undertaken by the Automation Technology Section, Code 522.3, at Goddard. The work was initially motivated by the growing realization that the knowledge acquisition process was a major bottleneck in the generation of fault detection, isolation, and repair (FDIR) systems for application in automated Mission Operations. As with most research activities this work started out with a simple objective: to develop a proof-of-concept system demonstrating that a draft rule-base for a FDIR system could be automatically realized by reasoning from a graphical representation of the system to be monitored. This work was called Knowledge From Pictures (KFP) (Truszkowski et. al. 1992). As the work has successfully progressed the KFP tool has become an environment populated by a set of tools that support a more comprehensive approach to model-based reasoning. This paper continues by giving an overview of the graphical modeling objectives of the work, describing the three tools that now populate the KFP environment, briefly presenting a discussion of related work in the field, and by indicating future directions for the KFP environment.

Data-based virtual unmodeled dynamics driven multivariable nonlinear adaptive switching control.

PubMed

Chai, Tianyou; Zhang, Yajun; Wang, Hong; Su, Chun-Yi; Sun, Jing

2011-12-01

For a complex industrial system, its multivariable and nonlinear nature generally make it very difficult, if not impossible, to obtain an accurate model, especially when the model structure is unknown. The control of this class of complex systems is difficult to handle by the traditional controller designs around their operating points. This paper, however, explores the concepts of controller-driven model and virtual unmodeled dynamics to propose a new design framework. The design consists of two controllers with distinct functions. First, using input and output data, a self-tuning controller is constructed based on a linear controller-driven model. Then the output signals of the controller-driven model are compared with the true outputs of the system to produce so-called virtual unmodeled dynamics. Based on the compensator of the virtual unmodeled dynamics, the second controller based on a nonlinear controller-driven model is proposed. Those two controllers are integrated by an adaptive switching control algorithm to take advantage of their complementary features: one offers stabilization function and another provides improved performance. The conditions on the stability and convergence of the closed-loop system are analyzed. Both simulation and experimental tests on a heavily coupled nonlinear twin-tank system are carried out to confirm the effectiveness of the proposed method.

Applying knowledge compilation techniques to model-based reasoning

NASA Technical Reports Server (NTRS)

Keller, Richard M.

1991-01-01

Researchers in the area of knowledge compilation are developing general purpose techniques for improving the efficiency of knowledge-based systems. In this article, an attempt is made to define knowledge compilation, to characterize several classes of knowledge compilation techniques, and to illustrate how some of these techniques can be applied to improve the performance of model-based reasoning systems.

Continued use of an interactive computer game-based visual perception learning system in children with developmental delay.

PubMed

Lin, Hsien-Cheng; Chiu, Yu-Hsien; Chen, Yenming J; Wuang, Yee-Pay; Chen, Chiu-Ping; Wang, Chih-Chung; Huang, Chien-Ling; Wu, Tang-Meng; Ho, Wen-Hsien

2017-11-01

This study developed an interactive computer game-based visual perception learning system for special education children with developmental delay. To investigate whether perceived interactivity affects continued use of the system, this study developed a theoretical model of the process in which learners decide whether to continue using an interactive computer game-based visual perception learning system. The technology acceptance model, which considers perceived ease of use, perceived usefulness, and perceived playfulness, was extended by integrating perceived interaction (i.e., learner-instructor interaction and learner-system interaction) and then analyzing the effects of these perceptions on satisfaction and continued use. Data were collected from 150 participants (rehabilitation therapists, medical paraprofessionals, and parents of children with developmental delay) recruited from a single medical center in Taiwan. Structural equation modeling and partial-least-squares techniques were used to evaluate relationships within the model. The modeling results indicated that both perceived ease of use and perceived usefulness were positively associated with both learner-instructor interaction and learner-system interaction. However, perceived playfulness only had a positive association with learner-system interaction and not with learner-instructor interaction. Moreover, satisfaction was positively affected by perceived ease of use, perceived usefulness, and perceived playfulness. Thus, satisfaction positively affects continued use of the system. The data obtained by this study can be applied by researchers, designers of computer game-based learning systems, special education workers, and medical professionals. Copyright © 2017 Elsevier B.V. All rights reserved.

Maximum flow-based resilience analysis: From component to system

PubMed Central

Jin, Chong; Li, Ruiying; Kang, Rui

2017-01-01

Resilience, the ability to withstand disruptions and recover quickly, must be considered during system design because any disruption of the system may cause considerable loss, including economic and societal. This work develops analytic maximum flow-based resilience models for series and parallel systems using Zobel’s resilience measure. The two analytic models can be used to evaluate quantitatively and compare the resilience of the systems with the corresponding performance structures. For systems with identical components, the resilience of the parallel system increases with increasing number of components, while the resilience remains constant in the series system. A Monte Carlo-based simulation method is also provided to verify the correctness of our analytic resilience models and to analyze the resilience of networked systems based on that of components. A road network example is used to illustrate the analysis process, and the resilience comparison among networks with different topologies but the same components indicates that a system with redundant performance is usually more resilient than one without redundant performance. However, not all redundant capacities of components can improve the system resilience, the effectiveness of the capacity redundancy depends on where the redundant capacity is located. PMID:28545135

A Collaborative Location Based Travel Recommendation System through Enhanced Rating Prediction for the Group of Users.

PubMed

Ravi, Logesh; Vairavasundaram, Subramaniyaswamy

2016-01-01

Rapid growth of web and its applications has created a colossal importance for recommender systems. Being applied in various domains, recommender systems were designed to generate suggestions such as items or services based on user interests. Basically, recommender systems experience many issues which reflects dwindled effectiveness. Integrating powerful data management techniques to recommender systems can address such issues and the recommendations quality can be increased significantly. Recent research on recommender systems reveals an idea of utilizing social network data to enhance traditional recommender system with better prediction and improved accuracy. This paper expresses views on social network data based recommender systems by considering usage of various recommendation algorithms, functionalities of systems, different types of interfaces, filtering techniques, and artificial intelligence techniques. After examining the depths of objectives, methodologies, and data sources of the existing models, the paper helps anyone interested in the development of travel recommendation systems and facilitates future research direction. We have also proposed a location recommendation system based on social pertinent trust walker (SPTW) and compared the results with the existing baseline random walk models. Later, we have enhanced the SPTW model for group of users recommendations. The results obtained from the experiments have been presented.

Systems, methods and apparatus for modeling, specifying and deploying policies in autonomous and autonomic systems using agent-oriented software engineering

NASA Technical Reports Server (NTRS)

Sterritt, Roy (Inventor); Hinchey, Michael G. (Inventor); Penn, Joaquin (Inventor)

2011-01-01

Systems, methods and apparatus are provided through which in some embodiments, an agent-oriented specification modeled with MaCMAS, is analyzed, flaws in the agent-oriented specification modeled with MaCMAS are corrected, and an implementation is derived from the corrected agent-oriented specification. Described herein are systems, method and apparatus that produce fully (mathematically) tractable development of agent-oriented specification(s) modeled with methodology fragment for analyzing complex multiagent systems (MaCMAS) and policies for autonomic systems from requirements through to code generation. The systems, method and apparatus described herein are illustrated through an example showing how user formulated policies can be translated into a formal mode which can then be converted to code. The requirements-based programming systems, method and apparatus described herein may provide faster, higher quality development and maintenance of autonomic systems based on user formulation of policies.

Hydrologic and Water Quality System (HAWQS)

EPA Science Inventory

The Hydrologic and Water Quality System (HAWQS) is a web-based interactive water quantity and quality modeling system that employs as its core modeling engine the Soil and Water Assessment Tool (SWAT), an internationally-recognized public domain model. HAWQS provides users with i...

Evidence for Model-based Computations in the Human Amygdala during Pavlovian Conditioning

PubMed Central

Prévost, Charlotte; McNamee, Daniel; Jessup, Ryan K.; Bossaerts, Peter; O'Doherty, John P.

2013-01-01

Contemporary computational accounts of instrumental conditioning have emphasized a role for a model-based system in which values are computed with reference to a rich model of the structure of the world, and a model-free system in which values are updated without encoding such structure. Much less studied is the possibility of a similar distinction operating at the level of Pavlovian conditioning. In the present study, we scanned human participants while they participated in a Pavlovian conditioning task with a simple structure while measuring activity in the human amygdala using a high-resolution fMRI protocol. After fitting a model-based algorithm and a variety of model-free algorithms to the fMRI data, we found evidence for the superiority of a model-based algorithm in accounting for activity in the amygdala compared to the model-free counterparts. These findings support an important role for model-based algorithms in describing the processes underpinning Pavlovian conditioning, as well as providing evidence of a role for the human amygdala in model-based inference. PMID:23436990

A WWW-Based Archive and Retrieval System for Multimedia

NASA Technical Reports Server (NTRS)

Hyon, J.; Sorensen, S.; Martin, M.; Kawasaki, K.; Takacs, M.

1996-01-01

This paper describes the Data Distribution Laboratory (DDL) and discusses issues involved in building multimedia CD-ROMs. It describes the modeling philosophy for cataloging multimedia products and the worldwide-web (WWW)-based multimedia archive and retrieval system (Webcat) built on that model.

Using Model-Based System Engineering to Provide Artifacts for NASA Project Life-Cycle and Technical Reviews Presentation

NASA Technical Reports Server (NTRS)

Parrott, Edith L.; Weiland, Karen J.

2017-01-01

This is the presentation for the AIAA Space conference in September 2017. It highlights key information from Using Model-Based Systems Engineering to Provide Artifacts for NASA Project Life-cycle and Technical Reviews paper.

DEVELOPMENT OF A RATIONALLY BASED DESIGN PROTOCOL FOR THE ULTRAVIOLET LIGHT DISINFECTION PROCESS

EPA Science Inventory

A protocol is demonstrated for the design and evaluation of ultraviolet (UV) disinfection systems based on a mathematical model. The disinfection model incorporates the system's physical dimensions, the residence time distribution of the reactor and dispersion characteristics, th...

Modelling Teaching Strategies.

ERIC Educational Resources Information Center

Major, Nigel

1995-01-01

Describes a modelling language for representing teaching strategies, based in the context of the COCA intelligent tutoring system. Examines work on meta-reasoning in knowledge-based systems and describes COCA's architecture, giving details of the language used for representing teaching knowledge. Discusses implications for future work. (AEF)

Integrated modelling of stormwater treatment systems uptake.

PubMed

Castonguay, A C; Iftekhar, M S; Urich, C; Bach, P M; Deletic, A

2018-05-24

Nature-based solutions provide a variety of benefits in growing cities, ranging from stormwater treatment to amenity provision such as aesthetics. However, the decision-making process involved in the installation of such green infrastructure is not straightforward, as much uncertainty around the location, size, costs and benefits impedes systematic decision-making. We developed a model to simulate decision rules used by local municipalities to install nature-based stormwater treatment systems, namely constructed wetlands, ponds/basins and raingardens. The model was used to test twenty-four scenarios of policy-making, by combining four asset selection, two location selection and three budget constraint decision rules. Based on the case study of a local municipality in Metropolitan Melbourne, Australia, the modelled uptake of stormwater treatment systems was compared with attributes of real-world systems for the simulation period. Results show that the actual budgeted funding is not reliable to predict systems' uptake and that policy-makers are more likely to plan expenditures based on installation costs. The model was able to replicate the cumulative treatment capacity and the location of systems. As such, it offers a novel approach to investigate the impact of using different decision rules to provide environmental services considering biophysical and economic factors. Copyright © 2018 Elsevier Ltd. All rights reserved.

System Behavior Models: A Survey of Approaches

DTIC Science & Technology

2016-06-01

MODELS: A SURVEY OF APPROACHES by Scott R. Ruppel June 2016 Thesis Advisor: Kristin Giammarco Second Reader: John M. Green THIS PAGE...Thesis 4. TITLE AND SUBTITLE SYSTEM BEHAVIOR MODELS: A SURVEY OF APPROACHES 5. FUNDING NUMBERS 6. AUTHOR(S) Scott R. Ruppel 7. PERFORMING...Monterey Phoenix, Petri nets, behavior modeling, model-based systems engineering, modeling approaches, modeling survey 15. NUMBER OF PAGES 85 16

A demonstrative model of a lunar base simulation on a personal computer

NASA Technical Reports Server (NTRS)

1985-01-01

The initial demonstration model of a lunar base simulation is described. This initial model was developed on the personal computer level to demonstrate feasibility and technique before proceeding to a larger computer-based model. Lotus Symphony Version 1.1 software was used to base the demonstration model on an personal computer with an MS-DOS operating system. The personal computer-based model determined the applicability of lunar base modeling techniques developed at an LSPI/NASA workshop. In addition, the personnal computer-based demonstration model defined a modeling structure that could be employed on a larger, more comprehensive VAX-based lunar base simulation. Refinement of this personal computer model and the development of a VAX-based model is planned in the near future.

The organization of an autonomous learning system

NASA Technical Reports Server (NTRS)

Kanerva, Pentti

1988-01-01

The organization of systems that learn from experience is examined, human beings and animals being prime examples of such systems. How is their information processing organized. They build an internal model of the world and base their actions on the model. The model is dynamic and predictive, and it includes the systems' own actions and their effects. In modeling such systems, a large pattern of features represents a moment of the system's experience. Some of the features are provided by the system's senses, some control the system's motors, and the rest have no immediate external significance. A sequence of such patterns then represents the system's experience over time. By storing such sequences appropriately in memory, the system builds a world model based on experience. In addition to the essential function of memory, fundamental roles are played by a sensory system that makes raw information about the world suitable for memory storage and by a motor system that affects the world. The relation of sensory and motor systems to the memory is discussed, together with how favorable actions can be learned and unfavorable actions can be avoided. Results in classical learning theory are explained in terms of the model, more advanced forms of learning are discussed, and the relevance of the model to the frame problem of robotics is examined.

An ontology-based semantic configuration approach to constructing Data as a Service for enterprises

NASA Astrophysics Data System (ADS)

Cai, Hongming; Xie, Cheng; Jiang, Lihong; Fang, Lu; Huang, Chenxi

2016-03-01

To align business strategies with IT systems, enterprises should rapidly implement new applications based on existing information with complex associations to adapt to the continually changing external business environment. Thus, Data as a Service (DaaS) has become an enabling technology for enterprise through information integration and the configuration of existing distributed enterprise systems and heterogonous data sources. However, business modelling, system configuration and model alignment face challenges at the design and execution stages. To provide a comprehensive solution to facilitate data-centric application design in a highly complex and large-scale situation, a configurable ontology-based service integrated platform (COSIP) is proposed to support business modelling, system configuration and execution management. First, a meta-resource model is constructed and used to describe and encapsulate information resources by way of multi-view business modelling. Then, based on ontologies, three semantic configuration patterns, namely composite resource configuration, business scene configuration and runtime environment configuration, are designed to systematically connect business goals with executable applications. Finally, a software architecture based on model-view-controller (MVC) is provided and used to assemble components for software implementation. The result of the case study demonstrates that the proposed approach provides a flexible method of implementing data-centric applications.

Analysis of the possibility of SysML and BPMN application in formal data acquisition system description

NASA Astrophysics Data System (ADS)

Ćwikła, G.; Gwiazda, A.; Banaś, W.; Monica, Z.; Foit, K.

2017-08-01

The article presents the study of possible application of selected methods of complex description, that can be used as a support of the Manufacturing Information Acquisition System (MIAS) methodology, describing how to design a data acquisition system, allowing for collecting and processing real-time data on the functioning of a production system, necessary for management of a company. MIAS can allow conversion into Cyber-Physical Production System. MIAS is gathering and pre-processing data on the state of production system, including e.g. realisation of production orders, state of machines, materials and human resources. Systematised approach and model-based development is proposed for improving the quality of the design of MIAS methodology-based complex systems supporting data acquisition in various types of companies. Graphical specification can be the baseline for any model-based development in specified areas. The possibility of application of SysML and BPMN, both being UML-based languages, representing different approaches to modelling of requirements, architecture and implementation of the data acquisition system, as a tools supporting description of required features of MIAS, were considered.

Stochastic modelling of temperatures affecting the in situ performance of a solar-assisted heat pump: The multivariate approach and physical interpretation

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

Loveday, D.L.; Craggs, C.

Box-Jenkins-based multivariate stochastic modeling is carried out using data recorded from a domestic heating system. The system comprises an air-source heat pump sited in the roof space of a house, solar assistance being provided by the conventional tile roof acting as a radiation absorber. Multivariate models are presented which illustrate the time-dependent relationships between three air temperatures - at external ambient, at entry to, and at exit from, the heat pump evaporator. Using a deterministic modeling approach, physical interpretations are placed on the results of the multivariate technique. It is concluded that the multivariate Box-Jenkins approach is a suitable techniquemore » for building thermal analysis. Application to multivariate Box-Jenkins approach is a suitable technique for building thermal analysis. Application to multivariate model-based control is discussed, with particular reference to building energy management systems. It is further concluded that stochastic modeling of data drawn from a short monitoring period offers a means of retrofitting an advanced model-based control system in existing buildings, which could be used to optimize energy savings. An approach to system simulation is suggested.« less

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.

Sandboxes for Model-Based Inquiry

NASA Astrophysics Data System (ADS)

Brady, Corey; Holbert, Nathan; Soylu, Firat; Novak, Michael; Wilensky, Uri

2015-04-01

In this article, we introduce a class of constructionist learning environments that we call Emergent Systems Sandboxes ( ESSs), which have served as a centerpiece of our recent work in developing curriculum to support scalable model-based learning in classroom settings. ESSs are a carefully specified form of virtual construction environment that support students in creating, exploring, and sharing computational models of dynamic systems that exhibit emergent phenomena. They provide learners with "entity"-level construction primitives that reflect an underlying scientific model. These primitives can be directly "painted" into a sandbox space, where they can then be combined, arranged, and manipulated to construct complex systems and explore the emergent properties of those systems. We argue that ESSs offer a means of addressing some of the key barriers to adopting rich, constructionist model-based inquiry approaches in science classrooms at scale. Situating the ESS in a large-scale science modeling curriculum we are implementing across the USA, we describe how the unique "entity-level" primitive design of an ESS facilitates knowledge system refinement at both an individual and social level, we describe how it supports flexible modeling practices by providing both continuous and discrete modes of executability, and we illustrate how it offers students a variety of opportunities for validating their qualitative understandings of emergent systems as they develop.

CrowdMapping: A Crowdsourcing-Based Terminology Mapping Method for Medical Data Standardization.

PubMed

Mao, Huajian; Chi, Chenyang; Huang, Boyu; Meng, Haibin; Yu, Jinghui; Zhao, Dongsheng

2017-01-01

Standardized terminology is the prerequisite of data exchange in analysis of clinical processes. However, data from different electronic health record systems are based on idiosyncratic terminology systems, especially when the data is from different hospitals and healthcare organizations. Terminology standardization is necessary for the medical data analysis. We propose a crowdsourcing-based terminology mapping method, CrowdMapping, to standardize the terminology in medical data. CrowdMapping uses a confidential model to determine how terminologies are mapped to a standard system, like ICD-10. The model uses mappings from different health care organizations and evaluates the diversity of the mapping to determine a more sophisticated mapping rule. Further, the CrowdMapping model enables users to rate the mapping result and interact with the model evaluation. CrowdMapping is a work-in-progress system, we present initial results mapping terminologies.

A global parallel model based design of experiments method to minimize model output uncertainty.

PubMed

Bazil, Jason N; Buzzard, Gregory T; Rundell, Ann E

2012-03-01

Model-based experiment design specifies the data to be collected that will most effectively characterize the biological system under study. Existing model-based design of experiment algorithms have primarily relied on Fisher Information Matrix-based methods to choose the best experiment in a sequential manner. However, these are largely local methods that require an initial estimate of the parameter values, which are often highly uncertain, particularly when data is limited. In this paper, we provide an approach to specify an informative sequence of multiple design points (parallel design) that will constrain the dynamical uncertainty of the biological system responses to within experimentally detectable limits as specified by the estimated experimental noise. The method is based upon computationally efficient sparse grids and requires only a bounded uncertain parameter space; it does not rely upon initial parameter estimates. The design sequence emerges through the use of scenario trees with experimental design points chosen to minimize the uncertainty in the predicted dynamics of the measurable responses of the system. The algorithm was illustrated herein using a T cell activation model for three problems that ranged in dimension from 2D to 19D. The results demonstrate that it is possible to extract useful information from a mathematical model where traditional model-based design of experiments approaches most certainly fail. The experiments designed via this method fully constrain the model output dynamics to within experimentally resolvable limits. The method is effective for highly uncertain biological systems characterized by deterministic mathematical models with limited data sets. Also, it is highly modular and can be modified to include a variety of methodologies such as input design and model discrimination.

Testability analysis on a hydraulic system in a certain equipment based on simulation model

NASA Astrophysics Data System (ADS)

Zhang, Rui; Cong, Hua; Liu, Yuanhong; Feng, Fuzhou

2018-03-01

Aiming at the problem that the complicated structure and the shortage of fault statistics information in hydraulic systems, a multi value testability analysis method based on simulation model is proposed. Based on the simulation model of AMESim, this method injects the simulated faults and records variation of test parameters ,such as pressure, flow rate, at each test point compared with those under normal conditions .Thus a multi-value fault-test dependency matrix is established. Then the fault detection rate (FDR) and fault isolation rate (FIR) are calculated based on the dependency matrix. Finally the system of testability and fault diagnosis capability are analyzed and evaluated, which can only reach a lower 54%(FDR) and 23%(FIR). In order to improve testability performance of the system,. number and position of the test points are optimized on the system. Results show the proposed test placement scheme can be used to solve the problems that difficulty, inefficiency and high cost in the system maintenance.

A Resource Service Model in the Industrial IoT System Based on Transparent Computing.

PubMed

Li, Weimin; Wang, Bin; Sheng, Jinfang; Dong, Ke; Li, Zitong; Hu, Yixiang

2018-03-26

The Internet of Things (IoT) has received a lot of attention, especially in industrial scenarios. One of the typical applications is the intelligent mine, which actually constructs the Six-Hedge underground systems with IoT platforms. Based on a case study of the Six Systems in the underground metal mine, this paper summarizes the main challenges of industrial IoT from the aspects of heterogeneity in devices and resources, security, reliability, deployment and maintenance costs. Then, a novel resource service model for the industrial IoT applications based on Transparent Computing (TC) is presented, which supports centralized management of all resources including operating system (OS), programs and data on the server-side for the IoT devices, thus offering an effective, reliable, secure and cross-OS IoT service and reducing the costs of IoT system deployment and maintenance. The model has five layers: sensing layer, aggregation layer, network layer, service and storage layer and interface and management layer. We also present a detailed analysis on the system architecture and key technologies of the model. Finally, the efficiency of the model is shown by an experiment prototype system.

A Resource Service Model in the Industrial IoT System Based on Transparent Computing

PubMed Central

Wang, Bin; Sheng, Jinfang; Dong, Ke; Li, Zitong; Hu, Yixiang

2018-01-01

The Internet of Things (IoT) has received a lot of attention, especially in industrial scenarios. One of the typical applications is the intelligent mine, which actually constructs the Six-Hedge underground systems with IoT platforms. Based on a case study of the Six Systems in the underground metal mine, this paper summarizes the main challenges of industrial IoT from the aspects of heterogeneity in devices and resources, security, reliability, deployment and maintenance costs. Then, a novel resource service model for the industrial IoT applications based on Transparent Computing (TC) is presented, which supports centralized management of all resources including operating system (OS), programs and data on the server-side for the IoT devices, thus offering an effective, reliable, secure and cross-OS IoT service and reducing the costs of IoT system deployment and maintenance. The model has five layers: sensing layer, aggregation layer, network layer, service and storage layer and interface and management layer. We also present a detailed analysis on the system architecture and key technologies of the model. Finally, the efficiency of the model is shown by an experiment prototype system. PMID:29587450

Controlled cooling of an electronic system based on projected conditions

DOEpatents

David, Milnes P.; Iyengar, Madhusudan K.; Schmidt, Roger R.

2016-05-17

Energy efficient control of a cooling system cooling an electronic system is provided based, in part, on projected conditions. The control includes automatically determining an adjusted control setting(s) for an adjustable cooling component(s) of the cooling system. The automatically determining is based, at least in part, on projected power consumed by the electronic system at a future time and projected temperature at the future time of a heat sink to which heat extracted is rejected. The automatically determining operates to reduce power consumption of the cooling system and/or the electronic system while ensuring that at least one targeted temperature associated with the cooling system or the electronic system is within a desired range. The automatically determining may be based, at least in part, on an experimentally obtained model(s) relating the targeted temperature and power consumption of the adjustable cooling component(s) of the cooling system.

Controlled cooling of an electronic system based on projected conditions

DOEpatents

David, Milnes P.; Iyengar, Madhusudan K.; Schmidt, Roger R.

2015-08-18

Energy efficient control of a cooling system cooling an electronic system is provided based, in part, on projected conditions. The control includes automatically determining an adjusted control setting(s) for an adjustable cooling component(s) of the cooling system. The automatically determining is based, at least in part, on projected power consumed by the electronic system at a future time and projected temperature at the future time of a heat sink to which heat extracted is rejected. The automatically determining operates to reduce power consumption of the cooling system and/or the electronic system while ensuring that at least one targeted temperature associated with the cooling system or the electronic system is within a desired range. The automatically determining may be based, at least in part, on an experimentally obtained model(s) relating the targeted temperature and power consumption of the adjustable cooling component(s) of the cooling system.

Induced Pluripotent Stem Cell Models to Enable In Vitro Models for Screening in the Central Nervous System.

PubMed

Hunsberger, Joshua G; Efthymiou, Anastasia G; Malik, Nasir; Behl, Mamta; Mead, Ivy L; Zeng, Xianmin; Simeonov, Anton; Rao, Mahendra

2015-08-15

There is great need to develop more predictive drug discovery tools to identify new therapies to treat diseases of the central nervous system (CNS). Current nonpluripotent stem cell-based models often utilize non-CNS immortalized cell lines and do not enable the development of personalized models of disease. In this review, we discuss why in vitro models are necessary for translational research and outline the unique advantages of induced pluripotent stem cell (iPSC)-based models over those of current systems. We suggest that iPSC-based models can be patient specific and isogenic lines can be differentiated into many neural cell types for detailed comparisons. iPSC-derived cells can be combined to form small organoids, or large panels of lines can be developed that enable new forms of analysis. iPSC and embryonic stem cell-derived cells can be readily engineered to develop reporters for lineage studies or mechanism of action experiments further extending the utility of iPSC-based systems. We conclude by describing novel technologies that include strategies for the development of diversity panels, novel genomic engineering tools, new three-dimensional organoid systems, and modified high-content screens that may bring toxicology into the 21st century. The strategic integration of these technologies with the advantages of iPSC-derived cell technology, we believe, will be a paradigm shift for toxicology and drug discovery efforts.

Variable cycle control model for intersection based on multi-source information

NASA Astrophysics Data System (ADS)

Sun, Zhi-Yuan; Li, Yue; Qu, Wen-Cong; Chen, Yan-Yan

2018-05-01

In order to improve the efficiency of traffic control system in the era of big data, a new variable cycle control model based on multi-source information is presented for intersection in this paper. Firstly, with consideration of multi-source information, a unified framework based on cyber-physical system is proposed. Secondly, taking into account the variable length of cell, hysteresis phenomenon of traffic flow and the characteristics of lane group, a Lane group-based Cell Transmission Model is established to describe the physical properties of traffic flow under different traffic signal control schemes. Thirdly, the variable cycle control problem is abstracted into a bi-level programming model. The upper level model is put forward for cycle length optimization considering traffic capacity and delay. The lower level model is a dynamic signal control decision model based on fairness analysis. Then, a Hybrid Intelligent Optimization Algorithm is raised to solve the proposed model. Finally, a case study shows the efficiency and applicability of the proposed model and algorithm.

Study on Practical Application of Turboprop Engine Condition Monitoring and Fault Diagnostic System Using Fuzzy-Neuro Algorithms

NASA Astrophysics Data System (ADS)

Kong, Changduk; Lim, Semyeong; Kim, Keunwoo

2013-03-01

The Neural Networks is mostly used to engine fault diagnostic system due to its good learning performance, but it has a drawback due to low accuracy and long learning time to build learning data base. This work builds inversely a base performance model of a turboprop engine to be used for a high altitude operation UAV using measuring performance data, and proposes a fault diagnostic system using the base performance model and artificial intelligent methods such as Fuzzy and Neural Networks. Each real engine performance model, which is named as the base performance model that can simulate a new engine performance, is inversely made using its performance test data. Therefore the condition monitoring of each engine can be more precisely carried out through comparison with measuring performance data. The proposed diagnostic system identifies firstly the faulted components using Fuzzy Logic, and then quantifies faults of the identified components using Neural Networks leaned by fault learning data base obtained from the developed base performance model. In leaning the measuring performance data of the faulted components, the FFBP (Feed Forward Back Propagation) is used. In order to user's friendly purpose, the proposed diagnostic program is coded by the GUI type using MATLAB.

Student Cognitive Difficulties and Mental Model Development of Complex Earth and Environmental Systems

NASA Astrophysics Data System (ADS)

Sell, K.; Herbert, B.; Schielack, J.

2004-05-01

Students organize scientific knowledge and reason about environmental issues through manipulation of mental models. The nature of the environmental sciences, which are focused on the study of complex, dynamic systems, may present cognitive difficulties to students in their development of authentic, accurate mental models of environmental systems. The inquiry project seeks to develop and assess the coupling of information technology (IT)-based learning with physical models in order to foster rich mental model development of environmental systems in geoscience undergraduate students. The manipulation of multiple representations, the development and testing of conceptual models based on available evidence, and exposure to authentic, complex and ill-constrained problems were the components of investigation utilized to reach the learning goals. Upper-level undergraduate students enrolled in an environmental geology course at Texas A&M University participated in this research which served as a pilot study. Data based on rubric evaluations interpreted by principal component analyses suggest students' understanding of the nature of scientific inquiry is limited and the ability to cross scales and link systems proved problematic. Results categorized into content knowledge and cognition processes where reasoning, critical thinking and cognitive load were driving factors behind difficulties in student learning. Student mental model development revealed multiple misconceptions and lacked complexity and completeness to represent the studied systems. Further, the positive learning impacts of the implemented modules favored the physical model over the IT-based learning projects, likely due to cognitive load issues. This study illustrates the need to better understand student difficulties in solving complex problems when using IT, where the appropriate scaffolding can then be implemented to enhance student learning of the earth system sciences.

Hybrid feedforward and feedback controller design for nuclear steam generators over wide range operation using genetic algorithm

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

Zhao, Y.; Edwards, R.M.; Lee, K.Y.

1997-03-01

In this paper, a simplified model with a lower order is first developed for a nuclear steam generator system and verified against some realistic environments. Based on this simplified model, a hybrid multi-input and multi-out (MIMO) control system, consisting of feedforward control (FFC) and feedback control (FBC), is designed for wide range conditions by using the genetic algorithm (GA) technique. The FFC control, obtained by the GA optimization method, injects an a priori command input into the system to achieve an optimal performance for the designed system, while the GA-based FBC control provides the necessary compensation for any disturbances ormore » uncertainties in a real steam generator. The FBC control is an optimal design of a PI-based control system which would be more acceptable for industrial practices and power plant control system upgrades. The designed hybrid MIMO FFC/FBC control system is first applied to the simplified model and then to a more complicated model with a higher order which is used as a substitute of the real system to test the efficacy of the designed control system. Results from computer simulations show that the designed GA-based hybrid MIMO FFC/FBC control can achieve good responses and robust performances. Hence, it can be considered as a viable alternative to the current control system upgrade.« less

A CSP-Based Agent Modeling Framework for the Cougaar Agent-Based Architecture

NASA Technical Reports Server (NTRS)

Gracanin, Denis; Singh, H. Lally; Eltoweissy, Mohamed; Hinchey, Michael G.; Bohner, Shawn A.

2005-01-01

Cognitive Agent Architecture (Cougaar) is a Java-based architecture for large-scale distributed agent-based applications. A Cougaar agent is an autonomous software entity with behaviors that represent a real-world entity (e.g., a business process). A Cougaar-based Model Driven Architecture approach, currently under development, uses a description of system's functionality (requirements) to automatically implement the system in Cougaar. The Communicating Sequential Processes (CSP) formalism is used for the formal validation of the generated system. Two main agent components, a blackboard and a plugin, are modeled as CSP processes. A set of channels represents communications between the blackboard and individual plugins. The blackboard is represented as a CSP process that communicates with every agent in the collection. The developed CSP-based Cougaar modeling framework provides a starting point for a more complete formal verification of the automatically generated Cougaar code. Currently it is used to verify the behavior of an individual agent in terms of CSP properties and to analyze the corresponding Cougaar society.

Evaluation and modeling of HIV based on communication theory in biological systems.

PubMed

Dong, Miaowu; Li, Wenrong; Xu, Xi

2016-12-01

Some forms of communication are used in biological systems such as HIV transmission in human beings. In this paper, we plan to get a unique insight into biological communication systems generally through the analogy between HIV infection and electrical communication system. The model established in this paper can be used to test and simulate various communication systems since it provides researchers with an opportunity. We interpret biological communication systems by using telecommunications exemplification from a layered communication protocol developed before and use the model to indicate HIV spreading. We also implement a simulation of HIV infection based on the layered communication protocol to predict the development of this disease and the results prove the validity of the model. Copyright © 2016 Elsevier B.V. All rights reserved.

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

Bringing Back the Social Affordances of the Paper Memo to Aerospace Systems Engineering Work

NASA Technical Reports Server (NTRS)

Davidoff, Scott; Holloway, Alexandra

2014-01-01

Model-based systems engineering (MBSE) is a relatively new field that brings together the interdisciplinary study of technological components of a project (systems engineering) with a model-based ontology to express the hierarchical and behavioral relationships between the components (computational modeling). Despite the compelling promises of the benefits of MBSE, such as improved communication and productivity due to an underlying language and data model, we observed hesitation to its adoption at the NASA Jet Propulsion Laboratory. To investigate, we conducted a six-month ethnographic field investigation and needs validation with 19 systems engineers. This paper contributes our observations of a generational shift in one of JPL's core technologies. We report on a cultural misunderstanding between communities of practice that bolsters the existing technology drag. Given the high cost of failure, we springboard our observations into a design hypothesis - an intervention that blends the social affordances of the narrative-based work flow with the rich technological advantages of explicit data references and relationships of the model-based approach. We provide a design rationale, and the results of our evaluation.

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

A Cybernetic Approach to the Modeling of Agent Communities

NASA Technical Reports Server (NTRS)

Truszkowski, Walt; Karlin, Jay

2000-01-01

In an earlier paper [1] examples of agent technology in a NASA context were presented. Both groundbased and space-based applications were addressed. This paper continues the discussion of one aspect of the Goddard Space Flight Center's continuing efforts to develop a community of agents that can support both ground-based and space-based systems autonomy. The paper focuses on an approach to agent-community modeling based on the theory of viable systems developed by Stafford Beer. It gives the status of an initial attempt to capture some of the agent-community behaviors in a viable system context. This paper is expository in nature and focuses on a discussion of the modeling of some of the underlying concepts and infrastructure that will serve as the basis of more detailed investigative work into the behavior of agent communities. The paper is organized as follows. First, a general introduction to agent community requirements is presented. Secondly, a brief introduction to the cybernetic concept of a viable system is given. This concept forms the foundation of the modeling approach. Then the concept of an agent community is modeled in the cybernetic context.

IS Success Model in E-Learning Context Based on Students' Perceptions

ERIC Educational Resources Information Center

Freeze, Ronald D.; Alshare, Khaled A.; Lane, Peggy L.; Wen, H. Joseph

2010-01-01

This study utilized the Information Systems Success (ISS) model in examining e-learning systems success. The study was built on the premise that system quality (SQ) and information quality (IQ) influence system use and user satisfaction, which in turn impact system success. A structural equation model (SEM), using LISREL, was used to test the…

Model-Based Systems Engineering With the Architecture Analysis and Design Language (AADL) Applied to NASA Mission Operations

NASA Technical Reports Server (NTRS)

Munoz Fernandez, Michela Miche

2014-01-01

The potential of Model Model Systems Engineering (MBSE) using the Architecture Analysis and Design Language (AADL) applied to space systems will be described. AADL modeling is applicable to real-time embedded systems- the types of systems NASA builds. A case study with the Juno mission to Jupiter showcases how this work would enable future missions to benefit from using these models throughout their life cycle from design to flight operations.

Experiences Integrating Transmission and Distribution Simulations for DERs with the Integrated Grid Modeling System (IGMS)

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

Palmintier, Bryan; Hale, Elaine; Hodge, Bri-Mathias

2016-08-11

This paper discusses the development of, approaches for, experiences with, and some results from a large-scale, high-performance-computer-based (HPC-based) co-simulation of electric power transmission and distribution systems using the Integrated Grid Modeling System (IGMS). IGMS was developed at the National Renewable Energy Laboratory (NREL) as a novel Independent System Operator (ISO)-to-appliance scale electric power system modeling platform that combines off-the-shelf tools to simultaneously model 100s to 1000s of distribution systems in co-simulation with detailed ISO markets, transmission power flows, and AGC-level reserve deployment. Lessons learned from the co-simulation architecture development are shared, along with a case study that explores the reactivemore » power impacts of PV inverter voltage support on the bulk power system.« less