Sample records for multiple model systems
-
NASA Astrophysics Data System (ADS)
Jonrinaldi; Rahman, T.; Henmaidi; Wirdianto, E.; Zhang, D. Z.
2018-03-01
This paper proposed a mathematical model for multiple items Economic Production and Order Quantity (EPQ/EOQ) with considering continuous and discrete demand simultaneously in a system consisting of a vendor and multiple buyers. This model is used to investigate the optimal production lot size of the vendor and the number of shipments policy of orders to multiple buyers. The model considers the multiple buyers’ holding cost as well as transportation cost, which minimize the total production and inventory costs of the system. The continuous demand from any other customers can be fulfilled anytime by the vendor while the discrete demand from multiple buyers can be fulfilled by the vendor using the multiple delivery policy with a number of shipments of items in the production cycle time. A mathematical model is developed to illustrate the system based on EPQ and EOQ model. Solution procedures are proposed to solve the model using a Mixed Integer Non Linear Programming (MINLP) and algorithm methods. Then, the numerical example is provided to illustrate the system and results are discussed.
-
Synthetic observations of protostellar multiple systems
NASA Astrophysics Data System (ADS)
Lomax, O.; Whitworth, A. P.
2018-04-01
Observations of protostars are often compared with synthetic observations of models in order to infer the underlying physical properties of the protostars. The majority of these models have a single protostar, attended by a disc and an envelope. However, observational and numerical evidence suggests that a large fraction of protostars form as multiple systems. This means that fitting models of single protostars to observations may be inappropriate. We produce synthetic observations of protostellar multiple systems undergoing realistic, non-continuous accretion. These systems consist of multiple protostars with episodic luminosities, embedded self-consistently in discs and envelopes. We model the gas dynamics of these systems using smoothed particle hydrodynamics and we generate synthetic observations by post-processing the snapshots using the SPAMCART Monte Carlo radiative transfer code. We present simulation results of three model protostellar multiple systems. For each of these, we generate 4 × 104 synthetic spectra at different points in time and from different viewing angles. We propose a Bayesian method, using similar calculations to those presented here, but in greater numbers, to infer the physical properties of protostellar multiple systems from observations.
-
A Methodology for Multiple Rule System Integration and Resolution Within a Singular Knowledge Base
NASA Technical Reports Server (NTRS)
Kautzmann, Frank N., III
1988-01-01
Expert Systems which support knowledge representation by qualitative modeling techniques experience problems, when called upon to support integrated views embodying description and explanation, especially when other factors such as multiple causality, competing rule model resolution, and multiple uses of knowledge representation are included. A series of prototypes are being developed to demonstrate the feasibility of automating the process of systems engineering, design and configuration, and diagnosis and fault management. A study involves not only a generic knowledge representation; it must also support multiple views at varying levels of description and interaction between physical elements, systems, and subsystems. Moreover, it will involve models of description and explanation for each level. This multiple model feature requires the development of control methods between rule systems and heuristics on a meta-level for each expert system involved in an integrated and larger class of expert system. The broadest possible category of interacting expert systems is described along with a general methodology for the knowledge representation and control of mutually exclusive rule systems.
-
A Model for Communications Satellite System Architecture Assessment
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
-
Validity and Realibility of Chemistry Systemic Multiple Choices Questions (CSMCQs)
ERIC Educational Resources Information Center
Priyambodo, Erfan; Marfuatun
2016-01-01
Nowadays, Rasch model analysis is used widely in social research, moreover in educational research. In this research, Rasch model is used to determine the validation and the reliability of systemic multiple choices question in chemistry teaching and learning. There were 30 multiple choices question with systemic approach for high school student…
-
Petri net modelling of buffers in automated manufacturing systems.
Zhou, M; Dicesare, F
1996-01-01
This paper presents Petri net models of buffers and a methodology by which buffers can be included in a system without introducing deadlocks or overflows. The context is automated manufacturing. The buffers and models are classified as random order or order preserved (first-in-first-out or last-in-first-out), single-input-single-output or multiple-input-multiple-output, part type and/or space distinguishable or indistinguishable, and bounded or safe. Theoretical results for the development of Petri net models which include buffer modules are developed. This theory provides the conditions under which the system properties of boundedness, liveness, and reversibility are preserved. The results are illustrated through two manufacturing system examples: a multiple machine and multiple buffer production line and an automatic storage and retrieval system in the context of flexible manufacturing.
-
NASA Astrophysics Data System (ADS)
Yang, Xiaojun; Lu, Dun; Liu, Hui; Zhao, Wanhua
2018-06-01
The complicated electromechanical coupling phenomena due to different kinds of causes have significant influences on the dynamic precision of the direct driven feed system in machine tools. In this paper, a novel integrated modeling and analysis method of the multiple electromechanical couplings for the direct driven feed system in machine tools is presented. At first, four different kinds of electromechanical coupling phenomena in the direct driven feed system are analyzed systematically. Then a novel integrated modeling and analysis method of the electromechanical coupling which is influenced by multiple factors is put forward. In addition, the effects of multiple electromechanical couplings on the dynamic precision of the feed system and their main influencing factors are compared and discussed, respectively. Finally, the results of modeling and analysis are verified by the experiments. It finds out that multiple electromechanical coupling loops, which are overlapped and influenced by each other, are the main reasons of the displacement fluctuations in the direct driven feed system.
-
Optimized production planning model for a multi-plant cultivation system under uncertainty
NASA Astrophysics Data System (ADS)
Ke, Shunkui; Guo, Doudou; Niu, Qingliang; Huang, Danfeng
2015-02-01
An inexact multi-constraint programming model under uncertainty was developed by incorporating a production plan algorithm into the crop production optimization framework under the multi-plant collaborative cultivation system. In the production plan, orders from the customers are assigned to a suitable plant under the constraints of plant capabilities and uncertainty parameters to maximize profit and achieve customer satisfaction. The developed model and solution method were applied to a case study of a multi-plant collaborative cultivation system to verify its applicability. As determined in the case analysis involving different orders from customers, the period of plant production planning and the interval between orders can significantly affect system benefits. Through the analysis of uncertain parameters, reliable and practical decisions can be generated using the suggested model of a multi-plant collaborative cultivation system.
-
Using multi-criteria analysis of simulation models to understand complex biological systems
Maureen C. Kennedy; E. David Ford
2011-01-01
Scientists frequently use computer-simulation models to help solve complex biological problems. Typically, such models are highly integrated, they produce multiple outputs, and standard methods of model analysis are ill suited for evaluating them. We show how multi-criteria optimization with Pareto optimality allows for model outputs to be compared to multiple system...
-
Treatment of Fragile X Syndrome with a Neuroactive Steroid
2015-08-01
in the fragile X mouse model and the Drosophila (fruit fly) models of FXS that the GABAA system, including multiple receptors, is dramatically down... Drosophila (fruit fly) models of FXS that the GABAA system, including multiple receptors, is dramatically down-regulated. Ganaxolone is a drug that
-
NASA Astrophysics Data System (ADS)
Murillo, N. M.; van Dishoeck, E. F.; Tobin, J. J.; Fedele, D.
2016-07-01
Context. Multiplicity is common in field stars and among protostellar systems. Models suggest two paths of formation: turbulent fragmentation and protostellar disk fragmentation. Aims: We attempt to find whether or not the coevality frequency of multiple protostellar systems can help to better understand their formation mechanism. The coevality frequency is determined by constraining the relative evolutionary stages of the components in a multiple system. Methods: Spectral energy distributions (SEDs) for known multiple protostars in Perseus were constructed from literature data. Herschel PACS photometric maps were used to sample the peak of the SED for systems with separations ≥7″, a crucial aspect in determining the evolutionary stage of a protostellar system. Inclination effects and the surrounding envelope and outflows were considered to decouple source geometry from evolution. This together with the shape and derived properties from the SED was used to determine each system's coevality as accurately as possible. SED models were used to examine the frequency of non-coevality that is due to geometry. Results: We find a non-coevality frequency of 33 ± 10% from the comparison of SED shapes of resolved multiple systems. Other source parameters suggest a somewhat lower frequency of non-coevality. The frequency of apparent non-coevality that is due to random inclination angle pairings of model SEDs is 17 ± 0.5%. Observations of the outflow of resolved multiple systems do not suggest significant misalignments within multiple systems. Effects of unresolved multiples on the SED shape are also investigated. Conclusions: We find that one-third of the multiple protostellar systems sampled here are non-coeval, which is more than expected from random geometric orientations. The other two-thirds are found to be coeval. Higher order multiples show a tendency to be non-coeval. The frequency of non-coevality found here is most likely due to formation and enhanced by dynamical evolution.
-
Fuzzy neural network technique for system state forecasting.
Li, Dezhi; Wang, Wilson; Ismail, Fathy
2013-10-01
In many system state forecasting applications, the prediction is performed based on multiple datasets, each corresponding to a distinct system condition. The traditional methods dealing with multiple datasets (e.g., vector autoregressive moving average models and neural networks) have some shortcomings, such as limited modeling capability and opaque reasoning operations. To tackle these problems, a novel fuzzy neural network (FNN) is proposed in this paper to effectively extract information from multiple datasets, so as to improve forecasting accuracy. The proposed predictor consists of both autoregressive (AR) nodes modeling and nonlinear nodes modeling; AR models/nodes are used to capture the linear correlation of the datasets, and the nonlinear correlation of the datasets are modeled with nonlinear neuron nodes. A novel particle swarm technique [i.e., Laplace particle swarm (LPS) method] is proposed to facilitate parameters estimation of the predictor and improve modeling accuracy. The effectiveness of the developed FNN predictor and the associated LPS method is verified by a series of tests related to Mackey-Glass data forecast, exchange rate data prediction, and gear system prognosis. Test results show that the developed FNN predictor and the LPS method can capture the dynamics of multiple datasets effectively and track system characteristics accurately.
-
Multiple model self-tuning control for a class of nonlinear systems
NASA Astrophysics Data System (ADS)
Huang, Miao; Wang, Xin; Wang, Zhenlei
2015-10-01
This study develops a novel nonlinear multiple model self-tuning control method for a class of nonlinear discrete-time systems. An increment system model and a modified robust adaptive law are proposed to expand the application range, thus eliminating the assumption that either the nonlinear term of the nonlinear system or its differential term is global-bounded. The nonlinear self-tuning control method can address the situation wherein the nonlinear system is not subject to a globally uniformly asymptotically stable zero dynamics by incorporating the pole-placement scheme. A novel, nonlinear control structure based on this scheme is presented to improve control precision. Stability and convergence can be confirmed when the proposed multiple model self-tuning control method is applied. Furthermore, simulation results demonstrate the effectiveness of the proposed method.
-
Dynamical modelling of coordinated multiple robot systems
NASA Technical Reports Server (NTRS)
Hayati, Samad
1987-01-01
The state of the art in the modeling of the dynamics of coordinated multiple robot manipulators is summarized and various problems related to this subject are discussed. It is recognized that dynamics modeling is a component used in the design of controllers for multiple cooperating robots. As such, the discussion addresses some problems related to the control of multiple robots. The techniques used to date in the modeling of closed kinematic chains are summarized. Various efforts made to date for the control of coordinated multiple manipulators is summarized.
-
Theoretical Foundation of Copernicus: A Unified System for Trajectory Design and Optimization
NASA Technical Reports Server (NTRS)
Ocampo, Cesar; Senent, Juan S.; Williams, Jacob
2010-01-01
The fundamental methods are described for the general spacecraft trajectory design and optimization software system called Copernicus. The methods rely on a unified framework that is used to model, design, and optimize spacecraft trajectories that may operate in complex gravitational force fields, use multiple propulsion systems, and involve multiple spacecraft. The trajectory model, with its associated equations of motion and maneuver models, are discussed.
-
A quantitative model of application slow-down in multi-resource shared systems
Lim, Seung-Hwan; Kim, Youngjae
2016-12-26
Scheduling multiple jobs onto a platform enhances system utilization by sharing resources. The benefits from higher resource utilization include reduced cost to construct, operate, and maintain a system, which often include energy consumption. Maximizing these benefits comes at a price-resource contention among jobs increases job completion time. In this study, we analyze slow-downs of jobs due to contention for multiple resources in a system; referred to as dilation factor. We observe that multiple-resource contention creates non-linear dilation factors of jobs. From this observation, we establish a general quantitative model for dilation factors of jobs in multi-resource systems. A job ismore » characterized by a vector-valued loading statistics and dilation factors of a job set are given by a quadratic function of their loading vectors. We demonstrate how to systematically characterize a job, maintain the data structure to calculate the dilation factor (loading matrix), and calculate the dilation factor of each job. We validate the accuracy of the model with multiple processes running on a native Linux server, virtualized servers, and with multiple MapReduce workloads co-scheduled in a cluster. Evaluation with measured data shows that the D-factor model has an error margin of less than 16%. We extended the D-factor model to capture the slow-down of applications when multiple identical resources exist such as multi-core environments and multi-disks environments. Finally, validation results of the extended D-factor model with HPC checkpoint applications on the parallel file systems show that D-factor accurately captures the slow down of concurrent applications in such environments.« less
-
A quantitative model of application slow-down in multi-resource shared systems
DOE Office of Scientific and Technical Information (OSTI.GOV)
Lim, Seung-Hwan; Kim, Youngjae
Scheduling multiple jobs onto a platform enhances system utilization by sharing resources. The benefits from higher resource utilization include reduced cost to construct, operate, and maintain a system, which often include energy consumption. Maximizing these benefits comes at a price-resource contention among jobs increases job completion time. In this study, we analyze slow-downs of jobs due to contention for multiple resources in a system; referred to as dilation factor. We observe that multiple-resource contention creates non-linear dilation factors of jobs. From this observation, we establish a general quantitative model for dilation factors of jobs in multi-resource systems. A job ismore » characterized by a vector-valued loading statistics and dilation factors of a job set are given by a quadratic function of their loading vectors. We demonstrate how to systematically characterize a job, maintain the data structure to calculate the dilation factor (loading matrix), and calculate the dilation factor of each job. We validate the accuracy of the model with multiple processes running on a native Linux server, virtualized servers, and with multiple MapReduce workloads co-scheduled in a cluster. Evaluation with measured data shows that the D-factor model has an error margin of less than 16%. We extended the D-factor model to capture the slow-down of applications when multiple identical resources exist such as multi-core environments and multi-disks environments. Finally, validation results of the extended D-factor model with HPC checkpoint applications on the parallel file systems show that D-factor accurately captures the slow down of concurrent applications in such environments.« less
-
Improving Multiple Fault Diagnosability using Possible Conflicts
NASA Technical Reports Server (NTRS)
Daigle, Matthew J.; Bregon, Anibal; Biswas, Gautam; Koutsoukos, Xenofon; Pulido, Belarmino
2012-01-01
Multiple fault diagnosis is a difficult problem for dynamic systems. Due to fault masking, compensation, and relative time of fault occurrence, multiple faults can manifest in many different ways as observable fault signature sequences. This decreases diagnosability of multiple faults, and therefore leads to a loss in effectiveness of the fault isolation step. We develop a qualitative, event-based, multiple fault isolation framework, and derive several notions of multiple fault diagnosability. We show that using Possible Conflicts, a model decomposition technique that decouples faults from residuals, we can significantly improve the diagnosability of multiple faults compared to an approach using a single global model. We demonstrate these concepts and provide results using a multi-tank system as a case study.
-
Multiple memory systems as substrates for multiple decision systems
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
-
2015-12-01
Multiple Sclerosis ? PRINCIPAL INVESTIGATOR: David Pleasure MD CONTRACTING ORGANIZATION: University of California Davis, CA 95618 REPORT DATE...Murine Model of Progressive Multiple Sclerosis ? 5b. GRANT NUMBER W81XWH-12-1-0566 5c. PROGRAM ELEMENT NUMBER 6. AUTHOR(S) David Pleasure MD 5d...enhance central nervous system (CNS) remyelination and preserve CNS axons in mouse models of multiple sclerosis models. After determining the dosage of
-
Ren, Jingzheng; Manzardo, Alessandro; Toniolo, Sara; Scipioni, Antonio; Tan, Shiyu; Dong, Lichun; Gao, Suzhao
2013-10-01
The purpose of this paper is to develop a model for designing the most sustainable bioethanol supply chain. Taking into consideration of the possibility of multiple-feedstock, multiple transportation modes, multiple alternative technologies, multiple transport patterns and multiple waste disposal manners in bioethanol systems, this study developed a model for designing the most sustainable bioethanol supply chain by minimizing the total ecological footprint under some prerequisite constraints including satisfying the goal of the stakeholders', the limitation of resources and energy, the capacity of warehouses, the market demand and some technological constraints. And an illustrative case of multiple-feedstock bioethanol system has been studied by the proposed method, and a global best solution by which the total ecological footprint is the minimal has been obtained. Copyright © 2013 Elsevier Ltd. All rights reserved.
-
Applications of active adaptive noise control to jet engines
NASA Technical Reports Server (NTRS)
Shoureshi, Rahmat; Brackney, Larry
1993-01-01
During phase 2 research on the application of active noise control to jet engines, the development of multiple-input/multiple-output (MIMO) active adaptive noise control algorithms and acoustic/controls models for turbofan engines were considered. Specific goals for this research phase included: (1) implementation of a MIMO adaptive minimum variance active noise controller; and (2) turbofan engine model development. A minimum variance control law for adaptive active noise control has been developed, simulated, and implemented for single-input/single-output (SISO) systems. Since acoustic systems tend to be distributed, multiple sensors, and actuators are more appropriate. As such, the SISO minimum variance controller was extended to the MIMO case. Simulation and experimental results are presented. A state-space model of a simplified gas turbine engine is developed using the bond graph technique. The model retains important system behavior, yet is of low enough order to be useful for controller design. Expansion of the model to include multiple stages and spools is also discussed.
-
Care delivery for Filipino Americans using the Neuman systems model.
Angosta, Alona D; Ceria-Ulep, Clementina D; Tse, Alice M
2014-04-01
Filipino Americans are at risk of coronary heart disease due to the presence of multiple cardiometabolic factors. Selecting a framework that addresses the factors leading to coronary heart disease is vital when providing care for this population. The Neuman systems model is a comprehensive and wholistic framework that offers an innovative method of viewing clients, their families, and the healthcare system across multiple dimensions. Using the Neuman systems model, advanced practice nurses can develop and implement interventions that will help reduce the potential cardiovascular problems of clients with multiple risk factors. The authors in this article provides insight into the cardiovascular health of Filipino Americans and has implications for nurses and other healthcare providers working with various Southeast Asian groups in the United States.
-
Jones, James W; Antle, John M; Basso, Bruno; Boote, Kenneth J; Conant, Richard T; Foster, Ian; Godfray, H Charles J; Herrero, Mario; Howitt, Richard E; Janssen, Sander; Keating, Brian A; Munoz-Carpena, Rafael; Porter, Cheryl H; Rosenzweig, Cynthia; Wheeler, Tim R
2017-07-01
We review the current state of agricultural systems science, focusing in particular on the capabilities and limitations of agricultural systems models. We discuss the state of models relative to five different Use Cases spanning field, farm, landscape, regional, and global spatial scales and engaging questions in past, current, and future time periods. Contributions from multiple disciplines have made major advances relevant to a wide range of agricultural system model applications at various spatial and temporal scales. Although current agricultural systems models have features that are needed for the Use Cases, we found that all of them have limitations and need to be improved. We identified common limitations across all Use Cases, namely 1) a scarcity of data for developing, evaluating, and applying agricultural system models and 2) inadequate knowledge systems that effectively communicate model results to society. We argue that these limitations are greater obstacles to progress than gaps in conceptual theory or available methods for using system models. New initiatives on open data show promise for addressing the data problem, but there also needs to be a cultural change among agricultural researchers to ensure that data for addressing the range of Use Cases are available for future model improvements and applications. We conclude that multiple platforms and multiple models are needed for model applications for different purposes. The Use Cases provide a useful framework for considering capabilities and limitations of existing models and data.
-
NASA Technical Reports Server (NTRS)
Jones, James W.; Antle, John M.; Basso, Bruno; Boote, Kenneth J.; Conant, Richard T.; Foster, Ian; Godfray, H. Charles J.; Herrero, Mario; Howitt, Richard E.; Janssen, Sander;
2016-01-01
We review the current state of agricultural systems science, focusing in particular on the capabilities and limitations of agricultural systems models. We discuss the state of models relative to five different Use Cases spanning field, farm, landscape, regional, and global spatial scales and engaging questions in past, current, and future time periods. Contributions from multiple disciplines have made major advances relevant to a wide range of agricultural system model applications at various spatial and temporal scales. Although current agricultural systems models have features that are needed for the Use Cases, we found that all of them have limitations and need to be improved. We identified common limitations across all Use Cases, namely 1) a scarcity of data for developing, evaluating, and applying agricultural system models and 2) inadequate knowledge systems that effectively communicate model results to society. We argue that these limitations are greater obstacles to progress than gaps in conceptual theory or available methods for using system models. New initiatives on open data show promise for addressing the data problem, but there also needs to be a cultural change among agricultural researchers to ensure that data for addressing the range of Use Cases are available for future model improvements and applications. We conclude that multiple platforms and multiple models are needed for model applications for different purposes. The Use Cases provide a useful framework for considering capabilities and limitations of existing models and data.
-
DOE Office of Scientific and Technical Information (OSTI.GOV)
Jones, James W.; Antle, John M.; Basso, Bruno
We review the current state of agricultural systems science, focusing in particular on the capabilities and limitations of agricultural systems models. We discuss the state of models relative to five different Use Cases spanning field, farm, landscape, regional, and global spatial scales and engaging questions in past, current, and future time periods. Contributions from multiple disciplines have made major advances relevant to a wide range of agricultural system model applications at various spatial and temporal scales. Although current agricultural systems models have features that are needed for the Use Cases, we found that all of them have limitations and needmore » to be improved. We identified common limitations across all Use Cases, namely 1) a scarcity of data for developing, evaluating, and applying agricultural system models and 2) inadequate knowledge systems that effectively communicate model results to society. We argue that these limitations are greater obstacles to progress than gaps in conceptual theory or available methods for using system models. New initiatives on open data show promise for addressing the data problem, but there also needs to be a cultural change among agricultural researchers to ensure that data for addressing the range of Use Cases are available for future model improvements and applications. We conclude that multiple platforms and multiple models are needed for model applications for different purposes. The Use Cases provide a useful framework for considering capabilities and limitations of existing models and data.« less
-
From bench to patient: model systems in drug discovery
Breyer, Matthew D.; Look, A. Thomas; Cifra, Alessandra
2015-01-01
ABSTRACT Model systems, including laboratory animals, microorganisms, and cell- and tissue-based systems, are central to the discovery and development of new and better drugs for the treatment of human disease. In this issue, Disease Models & Mechanisms launches a Special Collection that illustrates the contribution of model systems to drug discovery and optimisation across multiple disease areas. This collection includes reviews, Editorials, interviews with leading scientists with a foot in both academia and industry, and original research articles reporting new and important insights into disease therapeutics. This Editorial provides a summary of the collection's current contents, highlighting the impact of multiple model systems in moving new discoveries from the laboratory bench to the patients' bedsides. PMID:26438689
-
Generation of animation sequences of three dimensional models
NASA Technical Reports Server (NTRS)
Poi, Sharon (Inventor); Bell, Brad N. (Inventor)
1990-01-01
The invention is directed toward a method and apparatus for generating an animated sequence through the movement of three-dimensional graphical models. A plurality of pre-defined graphical models are stored and manipulated in response to interactive commands or by means of a pre-defined command file. The models may be combined as part of a hierarchical structure to represent physical systems without need to create a separate model which represents the combined system. System motion is simulated through the introduction of translation, rotation and scaling parameters upon a model within the system. The motion is then transmitted down through the system hierarchy of models in accordance with hierarchical definitions and joint movement limitations. The present invention also calls for a method of editing hierarchical structure in response to interactive commands or a command file such that a model may be included, deleted, copied or moved within multiple system model hierarchies. The present invention also calls for the definition of multiple viewpoints or cameras which may exist as part of a system hierarchy or as an independent camera. The simulated movement of the models and systems is graphically displayed on a monitor and a frame is recorded by means of a video controller. Multiple movement and hierarchy manipulations are then recorded as a sequence of frames which may be played back as an animation sequence on a video cassette recorder.
-
He, Xinhua; Hu, Wenfa
2014-01-01
This paper presents a multiple-rescue model for an emergency supply chain system under uncertainties in large-scale affected area of disasters. The proposed methodology takes into consideration that the rescue demands caused by a large-scale disaster are scattered in several locations; the servers are arranged in multiple echelons (resource depots, distribution centers, and rescue center sites) located in different places but are coordinated within one emergency supply chain system; depending on the types of rescue demands, one or more distinct servers dispatch emergency resources in different vehicle routes, and emergency rescue services queue in multiple rescue-demand locations. This emergency system is modeled as a minimal queuing response time model of location and allocation. A solution to this complex mathematical problem is developed based on genetic algorithm. Finally, a case study of an emergency supply chain system operating in Shanghai is discussed. The results demonstrate the robustness and applicability of the proposed model.
-
He, Xinhua
2014-01-01
This paper presents a multiple-rescue model for an emergency supply chain system under uncertainties in large-scale affected area of disasters. The proposed methodology takes into consideration that the rescue demands caused by a large-scale disaster are scattered in several locations; the servers are arranged in multiple echelons (resource depots, distribution centers, and rescue center sites) located in different places but are coordinated within one emergency supply chain system; depending on the types of rescue demands, one or more distinct servers dispatch emergency resources in different vehicle routes, and emergency rescue services queue in multiple rescue-demand locations. This emergency system is modeled as a minimal queuing response time model of location and allocation. A solution to this complex mathematical problem is developed based on genetic algorithm. Finally, a case study of an emergency supply chain system operating in Shanghai is discussed. The results demonstrate the robustness and applicability of the proposed model. PMID:24688367
-
Normalized Metadata Generation for Human Retrieval Using Multiple Video Surveillance Cameras.
Jung, Jaehoon; Yoon, Inhye; Lee, Seungwon; Paik, Joonki
2016-06-24
Since it is impossible for surveillance personnel to keep monitoring videos from a multiple camera-based surveillance system, an efficient technique is needed to help recognize important situations by retrieving the metadata of an object-of-interest. In a multiple camera-based surveillance system, an object detected in a camera has a different shape in another camera, which is a critical issue of wide-range, real-time surveillance systems. In order to address the problem, this paper presents an object retrieval method by extracting the normalized metadata of an object-of-interest from multiple, heterogeneous cameras. The proposed metadata generation algorithm consists of three steps: (i) generation of a three-dimensional (3D) human model; (ii) human object-based automatic scene calibration; and (iii) metadata generation. More specifically, an appropriately-generated 3D human model provides the foot-to-head direction information that is used as the input of the automatic calibration of each camera. The normalized object information is used to retrieve an object-of-interest in a wide-range, multiple-camera surveillance system in the form of metadata. Experimental results show that the 3D human model matches the ground truth, and automatic calibration-based normalization of metadata enables a successful retrieval and tracking of a human object in the multiple-camera video surveillance system.
-
Normalized Metadata Generation for Human Retrieval Using Multiple Video Surveillance Cameras
Jung, Jaehoon; Yoon, Inhye; Lee, Seungwon; Paik, Joonki
2016-01-01
Since it is impossible for surveillance personnel to keep monitoring videos from a multiple camera-based surveillance system, an efficient technique is needed to help recognize important situations by retrieving the metadata of an object-of-interest. In a multiple camera-based surveillance system, an object detected in a camera has a different shape in another camera, which is a critical issue of wide-range, real-time surveillance systems. In order to address the problem, this paper presents an object retrieval method by extracting the normalized metadata of an object-of-interest from multiple, heterogeneous cameras. The proposed metadata generation algorithm consists of three steps: (i) generation of a three-dimensional (3D) human model; (ii) human object-based automatic scene calibration; and (iii) metadata generation. More specifically, an appropriately-generated 3D human model provides the foot-to-head direction information that is used as the input of the automatic calibration of each camera. The normalized object information is used to retrieve an object-of-interest in a wide-range, multiple-camera surveillance system in the form of metadata. Experimental results show that the 3D human model matches the ground truth, and automatic calibration-based normalization of metadata enables a successful retrieval and tracking of a human object in the multiple-camera video surveillance system. PMID:27347961
-
NASA Technical Reports Server (NTRS)
Hoang, Triem T.; OConnell, Tamara; Ku, Jentung
2004-01-01
Loop Heat Pipes (LHPs) have proven themselves as reliable and robust heat transport devices for spacecraft thermal control systems. So far, the LHPs in earth-orbit satellites perform very well as expected. Conventional LHPs usually consist of a single capillary pump for heat acquisition and a single condenser for heat rejection. Multiple pump/multiple condenser LHPs have shown to function very well in ground testing. Nevertheless, the test results of a dual pump/condenser LHP also revealed that the dual LHP behaved in a complicated manner due to the interaction between the pumps and condensers. Thus it is redundant to say that more research is needed before they are ready for 0-g deployment. One research area that perhaps compels immediate attention is the analytical modeling of LHPs, particularly the transient phenomena. Modeling a single pump/single condenser LHP is difficult enough. Only a handful of computer codes are available for both steady state and transient simulations of conventional LHPs. No previous effort was made to develop an analytical model (or even a complete theory) to predict the operational behavior of the multiple pump/multiple condenser LHP systems. The current research project offered a basic theory of the multiple pump/multiple condenser LHP operation. From it, a computer code was developed to predict the LHP saturation temperature in accordance with the system operating and environmental conditions.
-
NASA Astrophysics Data System (ADS)
Ding, Zhe; Li, Li; Hu, Yujin
2018-01-01
Sophisticated engineering systems are usually assembled by subcomponents with significantly different levels of energy dissipation. Therefore, these damping systems often contain multiple damping models and lead to great difficulties in analyzing. This paper aims at developing a time integration method for structural systems with multiple damping models. The dynamical system is first represented by a generally damped model. Based on this, a new extended state-space method for the damped system is derived. A modified precise integration method with Gauss-Legendre quadrature is then proposed. The numerical stability and accuracy of the proposed integration method are discussed in detail. It is verified that the method is conditionally stable and has inherent algorithmic damping, period error and amplitude decay. Numerical examples are provided to assess the performance of the proposed method compared with other methods. It is demonstrated that the method is more accurate than other methods with rather good efficiency and the stable condition is easy to be satisfied in practice.
-
Predictive Multiple Model Switching Control with the Self-Organizing Map
NASA Technical Reports Server (NTRS)
Motter, Mark A.
2000-01-01
A predictive, multiple model control strategy is developed by extension of self-organizing map (SOM) local dynamic modeling of nonlinear autonomous systems to a control framework. Multiple SOMs collectively model the global response of a nonautonomous system to a finite set of representative prototype controls. Each SOM provides a codebook representation of the dynamics corresponding to a prototype control. Different dynamic regimes are organized into topological neighborhoods where the adjacent entries in the codebook represent the global minimization of a similarity metric. The SOM is additionally employed to identify the local dynamical regime, and consequently implements a switching scheme that selects the best available model for the applied control. SOM based linear models are used to predict the response to a larger family of control sequences which are clustered on the representative prototypes. The control sequence which corresponds to the prediction that best satisfies the requirements on the system output is applied as the external driving signal.
-
Minimizing energy dissipation of matrix multiplication kernel on Virtex-II
NASA Astrophysics Data System (ADS)
Choi, Seonil; Prasanna, Viktor K.; Jang, Ju-wook
2002-07-01
In this paper, we develop energy-efficient designs for matrix multiplication on FPGAs. To analyze the energy dissipation, we develop a high-level model using domain-specific modeling techniques. In this model, we identify architecture parameters that significantly affect the total energy (system-wide energy) dissipation. Then, we explore design trade-offs by varying these parameters to minimize the system-wide energy. For matrix multiplication, we consider a uniprocessor architecture and a linear array architecture to develop energy-efficient designs. For the uniprocessor architecture, the cache size is a parameter that affects the I/O complexity and the system-wide energy. For the linear array architecture, the amount of storage per processing element is a parameter affecting the system-wide energy. By using maximum amount of storage per processing element and minimum number of multipliers, we obtain a design that minimizes the system-wide energy. We develop several energy-efficient designs for matrix multiplication. For example, for 6×6 matrix multiplication, energy savings of upto 52% for the uniprocessor architecture and 36% for the linear arrary architecture is achieved over an optimized library for Virtex-II FPGA from Xilinx.
-
Optimal design of compact and connected nature reserves for multiple species.
Wang, Yicheng; Önal, Hayri
2016-04-01
When designing a conservation reserve system for multiple species, spatial attributes of the reserves must be taken into account at species level. The existing optimal reserve design literature considers either one spatial attribute or when multiple attributes are considered the analysis is restricted only to one species. We built a linear integer programing model that incorporates compactness and connectivity of the landscape reserved for multiple species. The model identifies multiple reserves that each serve a subset of target species with a specified coverage probability threshold to ensure the species' long-term survival in the reserve, and each target species is covered (protected) with another probability threshold at the reserve system level. We modeled compactness by minimizing the total distance between selected sites and central sites, and we modeled connectivity of a selected site to its designated central site by selecting at least one of its adjacent sites that has a nearer distance to the central site. We considered structural distance and functional distances that incorporated site quality between sites. We tested the model using randomly generated data on 2 species, one ground species that required structural connectivity and the other an avian species that required functional connectivity. We applied the model to 10 bird species listed as endangered by the state of Illinois (U.S.A.). Spatial coherence and selection cost of the reserves differed substantially depending on the weights assigned to these 2 criteria. The model can be used to design a reserve system for multiple species, especially species whose habitats are far apart in which case multiple disjunct but compact and connected reserves are advantageous. The model can be modified to increase or decrease the distance between reserves to reduce or promote population connectivity. © 2015 Society for Conservation Biology.
-
NASA Astrophysics Data System (ADS)
Yuan, Cadmus C. A.
2015-12-01
Optical ray tracing modeling applied Beer-Lambert method in the single luminescence material system to model the white light pattern from blue LED light source. This paper extends such algorithm to a mixed multiple luminescence material system by introducing the equivalent excitation and emission spectrum of individual luminescence materials. The quantum efficiency numbers of individual material and self-absorption of the multiple luminescence material system are considered as well. By this combination, researchers are able to model the luminescence characteristics of LED chip-scaled packaging (CSP), which provides simple process steps and the freedom of the luminescence material geometrical dimension. The method will be first validated by the experimental results. Afterward, a further parametric investigation has been then conducted.
-
Care Delivery for Filipino Americans Using the Neuman Systems Model
Angosta, Alona D.; Ceria-Ulep, Clementina D.; Tse, Alice M.
2016-01-01
Filipino Americans are at risk of coronary heart disease due to the presence of multiple cardiometabolic factors. Selecting a framework that addresses the factors leading to coronary heart disease is vital when providing care for this population. The Neuman systems model is a comprehensive and wholistic framework that offers an innovative method of viewing clients, their families, and the healthcare system across multiple dimensions. Using the Neuman systems model, advanced practice nurses can develop and implement interventions that will help reduce the potential cardiovascular problems of clients with multiple risk factors. The authors in this article provides insight into the cardiovascular health of Filipino Americans and has implications for nurses and other healthcare providers working with various Southeast Asian groups in the United States. PMID:24740949
-
System design in an evolving system-of-systems architecture and concept of operations
NASA Astrophysics Data System (ADS)
Rovekamp, Roger N., Jr.
Proposals for space exploration architectures have increased in complexity and scope. Constituent systems (e.g., rovers, habitats, in-situ resource utilization facilities, transfer vehicles, etc) must meet the needs of these architectures by performing in multiple operational environments and across multiple phases of the architecture's evolution. This thesis proposes an approach for using system-of-systems engineering principles in conjunction with system design methods (e.g., Multi-objective optimization, genetic algorithms, etc) to create system design options that perform effectively at both the system and system-of-systems levels, across multiple concepts of operations, and over multiple architectural phases. The framework is presented by way of an application problem that investigates the design of power systems within a power sharing architecture for use in a human Lunar Surface Exploration Campaign. A computer model has been developed that uses candidate power grid distribution solutions for a notional lunar base. The agent-based model utilizes virtual control agents to manage the interactions of various exploration and infrastructure agents. The philosophy behind the model is based both on lunar power supply strategies proposed in literature, as well as on the author's own approaches for power distribution strategies of future lunar bases. In addition to proposing a framework for system design, further implications of system-of-systems engineering principles are briefly explored, specifically as they relate to producing more robust cross-cultural system-of-systems architecture solutions.
-
From bench to patient: model systems in drug discovery.
Breyer, Matthew D; Look, A Thomas; Cifra, Alessandra
2015-10-01
Model systems, including laboratory animals, microorganisms, and cell- and tissue-based systems, are central to the discovery and development of new and better drugs for the treatment of human disease. In this issue, Disease Models & Mechanisms launches a Special Collection that illustrates the contribution of model systems to drug discovery and optimisation across multiple disease areas. This collection includes reviews, Editorials, interviews with leading scientists with a foot in both academia and industry, and original research articles reporting new and important insights into disease therapeutics. This Editorial provides a summary of the collection's current contents, highlighting the impact of multiple model systems in moving new discoveries from the laboratory bench to the patients' bedsides. © 2015. Published by The Company of Biologists Ltd.
-
Epidemic Spreading in a Multi-compartment System
NASA Astrophysics Data System (ADS)
Gao, Zong-Mao; Gu, Jiao; Li, Wei
2012-02-01
We introduce the variant rate and white noise into the susceptible-infected-removed (SIR) model for epidemics, discuss the epidemic dynamics of a multiple-compartment system, and describe this system by using master equations. For both the local epidemic spreading system and the whole multiple-compartment system, we find that a threshold could be useful in forecasting when the epidemic vanishes. Furthermore, numerical simulations show that a model with the variant infection rate and white noise can improve fitting with real SARS data.
-
Multiple-Group Analysis Using the sem Package in the R System
ERIC Educational Resources Information Center
Evermann, Joerg
2010-01-01
Multiple-group analysis in covariance-based structural equation modeling (SEM) is an important technique to ensure the invariance of latent construct measurements and the validity of theoretical models across different subpopulations. However, not all SEM software packages provide multiple-group analysis capabilities. The sem package for the R…
-
Quantitative Predictive Models for Systemic Toxicity (SOT)
Models to identify systemic and specific target organ toxicity were developed to help transition the field of toxicology towards computational models. By leveraging multiple data sources to incorporate read-across and machine learning approaches, a quantitative model of systemic ...
-
Effort to Accelerate MBSE Adoption and Usage at JSC
NASA Technical Reports Server (NTRS)
Wang, Lui; Izygon, Michel; Okron, Shira; Garner, Larry; Wagner, Howard
2016-01-01
This paper describes the authors' experience in adopting Model Based System Engineering (MBSE) at the NASA/Johnson Space Center (JSC). Since 2009, NASA/JSC has been applying MBSE using the Systems Modeling Language (SysML) to a number of advanced projects. Models integrate views of the system from multiple perspectives, capturing the system design information for multiple stakeholders. This method has allowed engineers to better control changes, improve traceability from requirements to design and manage the numerous interactions between components. As the project progresses, the models become the official source of information and used by multiple stakeholders. Three major types of challenges that hamper the adoption of the MBSE technology are described. These challenges are addressed by a multipronged approach that includes educating the main stakeholders, implementing an organizational infrastructure that supports the adoption effort, defining a set of modeling guidelines to help engineers in their modeling effort, providing a toolset that support the generation of valuable products, and providing a library of reusable models. JSC project case studies are presented to illustrate how the proposed approach has been successfully applied.
-
Reliability model of a monopropellant auxiliary propulsion system
NASA Technical Reports Server (NTRS)
Greenberg, J. S.
1971-01-01
A mathematical model and associated computer code has been developed which computes the reliability of a monopropellant blowdown hydrazine spacecraft auxiliary propulsion system as a function of time. The propulsion system is used to adjust or modify the spacecraft orbit over an extended period of time. The multiple orbit corrections are the multiple objectives which the auxiliary propulsion system is designed to achieve. Thus the reliability model computes the probability of successfully accomplishing each of the desired orbit corrections. To accomplish this, the reliability model interfaces with a computer code that models the performance of a blowdown (unregulated) monopropellant auxiliary propulsion system. The computer code acts as a performance model and as such gives an accurate time history of the system operating parameters. The basic timing and status information is passed on to and utilized by the reliability model which establishes the probability of successfully accomplishing the orbit corrections.
-
Unified tensor model for space-frequency spreading-multiplexing (SFSM) MIMO communication systems
NASA Astrophysics Data System (ADS)
de Almeida, André LF; Favier, Gérard
2013-12-01
This paper presents a unified tensor model for space-frequency spreading-multiplexing (SFSM) multiple-input multiple-output (MIMO) wireless communication systems that combine space- and frequency-domain spreadings, followed by a space-frequency multiplexing. Spreading across space (transmit antennas) and frequency (subcarriers) adds resilience against deep channel fades and provides space and frequency diversities, while orthogonal space-frequency multiplexing enables multi-stream transmission. We adopt a tensor-based formulation for the proposed SFSM MIMO system that incorporates space, frequency, time, and code dimensions by means of the parallel factor model. The developed SFSM tensor model unifies the tensorial formulation of some existing multiple-access/multicarrier MIMO signaling schemes as special cases, while revealing interesting tradeoffs due to combined space, frequency, and time diversities which are of practical relevance for joint symbol-channel-code estimation. The performance of the proposed SFSM MIMO system using either a zero forcing receiver or a semi-blind tensor-based receiver is illustrated by means of computer simulation results under realistic channel and system parameters.
-
Technique Selectively Represses Immune System
... from attacking myelin in a mouse model of multiple sclerosis. Dr David Furness, Wellcome Images. All rights reserved ... devised a way to successfully treat symptoms resembling multiple sclerosis in a mouse model. With further development, the ...
-
Hierarchical modeling and robust synthesis for the preliminary design of large scale complex systems
NASA Astrophysics Data System (ADS)
Koch, Patrick Nathan
Large-scale complex systems are characterized by multiple interacting subsystems and the analysis of multiple disciplines. The design and development of such systems inevitably requires the resolution of multiple conflicting objectives. The size of complex systems, however, prohibits the development of comprehensive system models, and thus these systems must be partitioned into their constituent parts. Because simultaneous solution of individual subsystem models is often not manageable iteration is inevitable and often excessive. In this dissertation these issues are addressed through the development of a method for hierarchical robust preliminary design exploration to facilitate concurrent system and subsystem design exploration, for the concurrent generation of robust system and subsystem specifications for the preliminary design of multi-level, multi-objective, large-scale complex systems. This method is developed through the integration and expansion of current design techniques: (1) Hierarchical partitioning and modeling techniques for partitioning large-scale complex systems into more tractable parts, and allowing integration of subproblems for system synthesis, (2) Statistical experimentation and approximation techniques for increasing both the efficiency and the comprehensiveness of preliminary design exploration, and (3) Noise modeling techniques for implementing robust preliminary design when approximate models are employed. The method developed and associated approaches are illustrated through their application to the preliminary design of a commercial turbofan turbine propulsion system; the turbofan system-level problem is partitioned into engine cycle and configuration design and a compressor module is integrated for more detailed subsystem-level design exploration, improving system evaluation.
-
Detection of abrupt changes in dynamic systems
NASA Technical Reports Server (NTRS)
Willsky, A. S.
1984-01-01
Some of the basic ideas associated with the detection of abrupt changes in dynamic systems are presented. Multiple filter-based techniques and residual-based method and the multiple model and generalized likelihood ratio methods are considered. Issues such as the effect of unknown onset time on algorithm complexity and structure and robustness to model uncertainty are discussed.
-
Multitask TSK fuzzy system modeling by mining intertask common hidden structure.
Jiang, Yizhang; Chung, Fu-Lai; Ishibuchi, Hisao; Deng, Zhaohong; Wang, Shitong
2015-03-01
The classical fuzzy system modeling methods implicitly assume data generated from a single task, which is essentially not in accordance with many practical scenarios where data can be acquired from the perspective of multiple tasks. Although one can build an individual fuzzy system model for each task, the result indeed tells us that the individual modeling approach will get poor generalization ability due to ignoring the intertask hidden correlation. In order to circumvent this shortcoming, we consider a general framework for preserving the independent information among different tasks and mining hidden correlation information among all tasks in multitask fuzzy modeling. In this framework, a low-dimensional subspace (structure) is assumed to be shared among all tasks and hence be the hidden correlation information among all tasks. Under this framework, a multitask Takagi-Sugeno-Kang (TSK) fuzzy system model called MTCS-TSK-FS (TSK-FS for multiple tasks with common hidden structure), based on the classical L2-norm TSK fuzzy system, is proposed in this paper. The proposed model can not only take advantage of independent sample information from the original space for each task, but also effectively use the intertask common hidden structure among multiple tasks to enhance the generalization performance of the built fuzzy systems. Experiments on synthetic and real-world datasets demonstrate the applicability and distinctive performance of the proposed multitask fuzzy system model in multitask regression learning scenarios.
-
DOE Office of Scientific and Technical Information (OSTI.GOV)
Geist, William H.
2015-12-01
This set of slides begins by giving background and a review of neutron counting; three attributes of a verification item are discussed: 240Pu eff mass; α, the ratio of (α,n) neutrons to spontaneous fission neutrons; and leakage multiplication. It then takes up neutron detector systems – theory & concepts (coincidence counting, moderation, die-away time); detector systems – some important details (deadtime, corrections); introduction to multiplicity counting; multiplicity electronics and example distributions; singles, doubles, and triples from measured multiplicity distributions; and the point model: multiplicity mathematics.
-
Modeling joint restoration strategies for interdependent infrastructure systems.
Zhang, Chao; Kong, Jingjing; Simonovic, Slobodan P
2018-01-01
Life in the modern world depends on multiple critical services provided by infrastructure systems which are interdependent at multiple levels. To effectively respond to infrastructure failures, this paper proposes a model for developing optimal joint restoration strategy for interdependent infrastructure systems following a disruptive event. First, models for (i) describing structure of interdependent infrastructure system and (ii) their interaction process, are presented. Both models are considering the failure types, infrastructure operating rules and interdependencies among systems. Second, an optimization model for determining an optimal joint restoration strategy at infrastructure component level by minimizing the economic loss from the infrastructure failures, is proposed. The utility of the model is illustrated using a case study of electric-water systems. Results show that a small number of failed infrastructure components can trigger high level failures in interdependent systems; the optimal joint restoration strategy varies with failure occurrence time. The proposed models can help decision makers to understand the mechanisms of infrastructure interactions and search for optimal joint restoration strategy, which can significantly enhance safety of infrastructure systems.
-
NASA Astrophysics Data System (ADS)
Zhang, Jie; Ding, Lan; Liang, Changneng; Xiao, Yiming; Xu, Wen
2017-11-01
We develop a multiple reflection model (MRM) for the examination of infrared transmission properties of a graphene/substrate system. The incident angle and the multiple reflection beams in the substrate with finite thickness are taken into consideration. The model can be applied to predict the optical responses of graphene/substrate systems or to extract the real part of the optical conductance of graphene from the experimental measurement. As an example, we calculate the relative transmittance of graphene/quartz and graphene/sapphire systems by using MRM and provide an experimental verification in the near-infrared range. The measured results show good agreement with the calculated ones. Our method can be easily extended to accurately and non-invasively identify the layer numbers of other 2D materials, and assess the quality of them.
-
NASA Astrophysics Data System (ADS)
Liu, Chun; Jiang, Bin; Zhang, Ke
2018-03-01
This paper investigates the attitude and position tracking control problem for Lead-Wing close formation systems in the presence of loss of effectiveness and lock-in-place or hardover failure. In close formation flight, Wing unmanned aerial vehicle movements are influenced by vortex effects of the neighbouring Lead unmanned aerial vehicle. This situation allows modelling of aerodynamic coupling vortex-effects and linearisation based on optimal close formation geometry. Linearised Lead-Wing close formation model is transformed into nominal robust H-infinity models with respect to Mach hold, Heading hold, and Altitude hold autopilots; static feedback H-infinity controller is designed to guarantee effective tracking of attitude and position while manoeuvring Lead unmanned aerial vehicle. Based on H-infinity control design, an integrated multiple-model adaptive fault identification and reconfigurable fault-tolerant control scheme is developed to guarantee asymptotic stability of close-loop systems, error signal boundedness, and attitude and position tracking properties. Simulation results for Lead-Wing close formation systems validate the efficiency of the proposed integrated multiple-model adaptive control algorithm.
-
DOE Office of Scientific and Technical Information (OSTI.GOV)
Shipman, Galen M.
These are the slides for a presentation on programming models in HPC, at the Los Alamos National Laboratory's Parallel Computing Summer School. The following topics are covered: Flynn's Taxonomy of computer architectures; single instruction single data; single instruction multiple data; multiple instruction multiple data; address space organization; definition of Trinity (Intel Xeon-Phi is a MIMD architecture); single program multiple data; multiple program multiple data; ExMatEx workflow overview; definition of a programming model, programming languages, runtime systems; programming model and environments; MPI (Message Passing Interface); OpenMP; Kokkos (Performance Portable Thread-Parallel Programming Model); Kokkos abstractions, patterns, policies, and spaces; RAJA, a systematicmore » approach to node-level portability and tuning; overview of the Legion Programming Model; mapping tasks and data to hardware resources; interoperability: supporting task-level models; Legion S3D execution and performance details; workflow, integration of external resources into the programming model.« less
-
Dynamic Modeling of Systemic Risk in Financial Networks
NASA Astrophysics Data System (ADS)
Avakian, Adam
Modern financial networks are complicated structures that can contain multiple types of nodes and connections between those nodes. Banks, governments and even individual people weave into an intricate network of debt, risk correlations and many other forms of interconnectedness. We explore multiple types of financial network models with a focus on understanding the dynamics and causes of cascading failures in such systems. In particular, we apply real-world data from multiple sources to these models to better understand real-world financial networks. We use the results of the Federal Reserve "Banking Organization Systemic Risk Report" (FR Y-15), which surveys the largest US banks on their level of interconnectedness, to find relationships between various measures of network connectivity and systemic risk in the US financial sector. This network model is then stress-tested under a number of scenarios to determine systemic risks inherent in the various network structures. We also use detailed historical balance sheet data from the Venezuelan banking system to build a bipartite network model and find relationships between the changing network structure over time and the response of the system to various shocks. We find that the relationship between interconnectedness and systemic risk is highly dependent on the system and model but that it is always a significant one. These models are useful tools that add value to regulators in creating new measurements of systemic risk in financial networks. These models could be used as macroprudential tools for monitoring the health of the entire banking system as a whole rather than only of individual banks.
-
Fealy, Gerard M; Carney, Marie; Drennan, Jonathan; Treacy, Margaret; Burke, Jacqueline; O'Connell, Dympna; Howley, Breeda; Clancy, Alison; McHugh, Aine; Patton, Declan; Sheerin, Fintan
2009-09-01
To provide a synthesis of literature on international policy concerning professional regulation in nursing and midwifery, with reference to routes of entry into training and pathways to licensure. Internationally, there is evidence of multiple points of entry into initial training, multiple divisions of the professional register and multiple pathways to licensure. Policy documents and commentary articles concerned with models of initial training and pathways to licensure were reviewed. Item selection, quality appraisal and data extraction were undertaken and documentary analysis was performed on all retrieved texts. Case studies of five Western countries indicate no single uniform system of routes of entry into initial training and no overall consensus regarding the optimal model of initial training. Multiple regulatory systems, with multiple routes of entry into initial training and multiple pathways to licensure pose challenges, in terms of achieving commonly-agreed understandings of practice competence. The variety of models of initial training present nursing managers with challenges in the recruitment and deployment of personnel trained in many different jurisdictions. Nursing managers need to consider the potential for considerable variation in competency repertoires among nurses trained in generic and specialist initial training models.
-
Multiple transient memories in sheared suspensions: Robustness, structure, and routes to plasticity
NASA Astrophysics Data System (ADS)
Keim, Nathan C.; Paulsen, Joseph D.; Nagel, Sidney R.
2013-09-01
Multiple transient memories, originally discovered in charge-density-wave conductors, are a remarkable and initially counterintuitive example of how a system can store information about its driving. In this class of memories, a system can learn multiple driving inputs, nearly all of which are eventually forgotten despite their continual input. If sufficient noise is present, the system regains plasticity so that it can continue to learn new memories indefinitely. Recently, Keim and Nagel [Phys. Rev. Lett.PRLTAO0031-900710.1103/PhysRevLett.107.010603 107, 010603 (2011)] showed how multiple transient memories could be generalized to a generic driven disordered system with noise, giving as an example simulations of a simple model of a sheared non-Brownian suspension. Here, we further explore simulation models of suspensions under cyclic shear, focusing on three main themes: robustness, structure, and overdriving. We show that multiple transient memories are a robust feature independent of many details of the model. The steady-state spatial distribution of the particles is sensitive to the driving algorithm; nonetheless, the memory formation is independent of such a change in particle correlations. Finally, we demonstrate that overdriving provides another means for controlling memory formation and retention.
-
Stochastic nature of Landsat MSS data
NASA Technical Reports Server (NTRS)
Labovitz, M. L.; Masuoka, E. J.
1987-01-01
A multiple series generalization of the ARIMA models is used to model Landsat MSS scan lines as sequences of vectors, each vector having four elements (bands). The purpose of this work is to investigate if Landsat scan lines can be described by a general multiple series linear stochastic model and if the coefficients of such a model vary as a function of satellite system and target attributes. To accomplish this objective, an exploratory experimental design was set up incorporating six factors, four representing target attributes - location, cloud cover, row (within location), and column (within location) - and two factors representing system attributes - satellite number and detector bank. Each factor was included in the design at two levels and, with two replicates per treatment, 128 scan lines were analyzed. The results of the analysis suggests that a multiple AR(4) model is an adequate representation across all scan lines. Furthermore, the coefficients of the AR(4) model vary with location, particularly changes in physiography (slope regimes), and with percent cloud cover, but are insensitive to changes in system attributes.
-
Theoretical Models of Protostellar Binary and Multiple Systems with AMR Simulations
NASA Astrophysics Data System (ADS)
Matsumoto, Tomoaki; Tokuda, Kazuki; Onishi, Toshikazu; Inutsuka, Shu-ichiro; Saigo, Kazuya; Takakuwa, Shigehisa
2017-05-01
We present theoretical models for protostellar binary and multiple systems based on the high-resolution numerical simulation with an adaptive mesh refinement (AMR) code, SFUMATO. The recent ALMA observations have revealed early phases of the binary and multiple star formation with high spatial resolutions. These observations should be compared with theoretical models with high spatial resolutions. We present two theoretical models for (1) a high density molecular cloud core, MC27/L1521F, and (2) a protobinary system, L1551 NE. For the model for MC27, we performed numerical simulations for gravitational collapse of a turbulent cloud core. The cloud core exhibits fragmentation during the collapse, and dynamical interaction between the fragments produces an arc-like structure, which is one of the prominent structures observed by ALMA. For the model for L1551 NE, we performed numerical simulations of gas accretion onto protobinary. The simulations exhibit asymmetry of a circumbinary disk. Such asymmetry has been also observed by ALMA in the circumbinary disk of L1551 NE.
-
Equivalent ZF precoding scheme for downlink indoor MU-MIMO VLC systems
NASA Astrophysics Data System (ADS)
Fan, YangYu; Zhao, Qiong; Kang, BoChao; Deng, LiJun
2018-01-01
In indoor visible light communication (VLC) systems, the channels of photo detectors (PDs) at one user are highly correlated, which determines the choice of spatial diversity model for individual users. In a spatial diversity model, the signals received by PDs belonging to one user carry the same information, and can be combined directly. Based on the above, we propose an equivalent zero-forcing (ZF) precoding scheme for multiple-user multiple-input single-output (MU-MIMO) VLC systems by transforming an indoor MU-MIMO VLC system into an indoor multiple-user multiple-input single-output (MU-MISO) VLC system through simply processing. The power constraints of light emitting diodes (LEDs) are also taken into account. Comprehensive computer simulations in three scenarios indicate that our scheme can not only reduce the computational complexity, but also guarantee the system performance. Furthermore, the proposed scheme does not require noise information in the calculating of the precoding weights, and has no restrictions on the numbers of APs and PDs.
-
An open source web interface for linking models to infrastructure system databases
NASA Astrophysics Data System (ADS)
Knox, S.; Mohamed, K.; Harou, J. J.; Rheinheimer, D. E.; Medellin-Azuara, J.; Meier, P.; Tilmant, A.; Rosenberg, D. E.
2016-12-01
Models of networked engineered resource systems such as water or energy systems are often built collaboratively with developers from different domains working at different locations. These models can be linked to large scale real world databases, and they are constantly being improved and extended. As the development and application of these models becomes more sophisticated, and the computing power required for simulations and/or optimisations increases, so has the need for online services and tools which enable the efficient development and deployment of these models. Hydra Platform is an open source, web-based data management system, which allows modellers of network-based models to remotely store network topology and associated data in a generalised manner, allowing it to serve multiple disciplines. Hydra Platform uses a web API using JSON to allow external programs (referred to as `Apps') to interact with its stored networks and perform actions such as importing data, running models, or exporting the networks to different formats. Hydra Platform supports multiple users accessing the same network and has a suite of functions for managing users and data. We present ongoing development in Hydra Platform, the Hydra Web User Interface, through which users can collaboratively manage network data and models in a web browser. The web interface allows multiple users to graphically access, edit and share their networks, run apps and view results. Through apps, which are located on the server, the web interface can give users access to external data sources and models without the need to install or configure any software. This also ensures model results can be reproduced by removing platform or version dependence. Managing data and deploying models via the web interface provides a way for multiple modellers to collaboratively manage data, deploy and monitor model runs and analyse results.
-
How to induce multiple delays in coupled chaotic oscillators?
NASA Astrophysics Data System (ADS)
Bhowmick, Sourav K.; Ghosh, Dibakar; Roy, Prodyot K.; Kurths, Jürgen; Dana, Syamal K.
2013-12-01
Lag synchronization is a basic phenomenon in mismatched coupled systems, delay coupled systems, and time-delayed systems. It is characterized by a lag configuration that identifies a unique time shift between all pairs of similar state variables of the coupled systems. In this report, an attempt is made how to induce multiple lag configurations in coupled systems when different pairs of state variables attain different time shift. A design of coupling is presented to realize this multiple lag synchronization. Numerical illustration is given using examples of the Rössler system and the slow-fast Hindmarsh-Rose neuron model. The multiple lag scenario is physically realized in an electronic circuit of two Sprott systems.
-
A model for diagnosing and explaining multiple disorders.
Jamieson, P W
1991-08-01
The ability to diagnose multiple interacting disorders and explain them in a coherent causal framework has only partially been achieved in medical expert systems. This paper proposes a causal model for diagnosing and explaining multiple disorders whose key elements are: physician-directed hypotheses generation, object-oriented knowledge representation, and novel explanation heuristics. The heuristics modify and link the explanations to make the physician aware of diagnostic complexities. A computer program incorporating the model currently is in use for diagnosing peripheral nerve and muscle disorders. The program successfully diagnoses and explains interactions between diseases in terms of underlying pathophysiologic concepts. The model offers a new architecture for medical domains where reasoning from first principles is difficult but explanation of disease interactions is crucial for the system's operation.
-
A Cognitive System Model for Human/Automation Dynamics in Airspace Management
NASA Technical Reports Server (NTRS)
Corker, Kevin M.; Pisanich, Gregory; Lebacqz, J. Victor (Technical Monitor)
1997-01-01
NASA has initiated a significant thrust of research and development focused on providing the flight crew and air traffic managers automation aids to increase capacity in en route and terminal area operations through the use of flexible, more fuel-efficient routing, while improving the level of safety in commercial carrier operations. In that system development, definition of cognitive requirements for integrated multi-operator dynamic aiding systems is fundamental. In order to support that cognitive function definition, we have extended the Man Machine Integrated Design and Analysis System (MIDAS) to include representation of multiple cognitive agents (both human operators and intelligent aiding systems) operating aircraft, airline operations centers and air traffic control centers in the evolving airspace. The demands of this application require representation of many intelligent agents sharing world-models, and coordinating action/intention with cooperative scheduling of goals and actions in a potentially unpredictable world of operations. The MIDAS operator models have undergone significant development in order to understand the requirements for operator aiding and the impact of that aiding in the complex nondeterminate system of national airspace operations. The operator model's structure has been modified to include attention functions, action priority, and situation assessment. The cognitive function model has been expanded to include working memory operations including retrieval from long-term store, interference, visual-motor and verbal articulatory loop functions, and time-based losses. The operator's activity structures have been developed to include prioritization and interruption of multiple parallel activities among multiple operators, to provide for anticipation (knowledge of the intention and action of remote operators), and to respond to failures of the system and other operators in the system in situation-specific paradigms. The model's internal representation has been be modified so that multiple, autonomous sets of equipment will function in a scenario as the single equipment sets do now. In order to support the analysis requirements with multiple items of equipment, it is necessary for equipment to access the state of other equipment objects at initialization time (a radar object may need to access the position and speed of aircraft in its area, for example), and as a function of perception and sensor system interaction. The model has been improved to include multiple world-states as a function of equipment am operator interaction. The model has been used -1o predict the impact of warning and alert zones in aircraft operation, and, more critic-ally, the interaction of flight-deck based warning mechanisms and air traffic controller action in response to ground-based conflict prediction and alerting systems. In this operation, two operating systems provide alerting to two autonomous, but linked sets of operators, whose view of the system and whose dynamics in response are radically different. System stability and operator action was predicted using the MIDAS model.
-
Anatomy and Physiology of Multiscale Modeling and Simulation in Systems Medicine.
Mizeranschi, Alexandru; Groen, Derek; Borgdorff, Joris; Hoekstra, Alfons G; Chopard, Bastien; Dubitzky, Werner
2016-01-01
Systems medicine is the application of systems biology concepts, methods, and tools to medical research and practice. It aims to integrate data and knowledge from different disciplines into biomedical models and simulations for the understanding, prevention, cure, and management of complex diseases. Complex diseases arise from the interactions among disease-influencing factors across multiple levels of biological organization from the environment to molecules. To tackle the enormous challenges posed by complex diseases, we need a modeling and simulation framework capable of capturing and integrating information originating from multiple spatiotemporal and organizational scales. Multiscale modeling and simulation in systems medicine is an emerging methodology and discipline that has already demonstrated its potential in becoming this framework. The aim of this chapter is to present some of the main concepts, requirements, and challenges of multiscale modeling and simulation in systems medicine.
-
Modeling Environment for Total Risk-4M
MENTOR-4M uses an integrated, mechanistically consistent, source-to-dose modeling framework to quantify simultaneous exposures and doses of individuals and populations to multiple contaminants. It is an implementation of the MENTOR system for exposures to Multiple contaminants fr...
-
The blackboard model - A framework for integrating multiple cooperating expert systems
NASA Technical Reports Server (NTRS)
Erickson, W. K.
1985-01-01
The use of an artificial intelligence (AI) architecture known as the blackboard model is examined as a framework for designing and building distributed systems requiring the integration of multiple cooperating expert systems (MCXS). Aerospace vehicles provide many examples of potential systems, ranging from commercial and military aircraft to spacecraft such as satellites, the Space Shuttle, and the Space Station. One such system, free-flying, spaceborne telerobots to be used in construction, servicing, inspection, and repair tasks around NASA's Space Station, is examined. The major difficulties found in designing and integrating the individual expert system components necessary to implement such a robot are outlined. The blackboard model, a general expert system architecture which seems to address many of the problems found in designing and building such a system, is discussed. A progress report on a prototype system under development called DBB (Distributed BlackBoard model) is given. The prototype will act as a testbed for investigating the feasibility, utility, and efficiency of MCXS-based designs developed under the blackboard model.
-
De-noising of 3D multiple-coil MR images using modified LMMSE estimator.
Yaghoobi, Nima; Hasanzadeh, Reza P R
2018-06-20
De-noising is a crucial topic in Magnetic Resonance Imaging (MRI) which focuses on less loss of Magnetic Resonance (MR) image information and details preservation during the noise suppression. Nowadays multiple-coil MRI system is preferred to single one due to its acceleration in the imaging process. Due to the fact that the model of noise in single-coil and multiple-coil MRI systems are different, the de-noising methods that mostly are adapted to single-coil MRI systems, do not work appropriately with multiple-coil one. The model of noise in single-coil MRI systems is Rician while in multiple-coil one (if no subsampling occurs in k-space or GRAPPA reconstruction process is being done in the coils), it obeys noncentral Chi (nc-χ). In this paper, a new filtering method based on the Linear Minimum Mean Square Error (LMMSE) estimator is proposed for multiple-coil MR Images ruined by nc-χ noise. In the presented method, to have an optimum similarity selection of voxels, the Bayesian Mean Square Error (BMSE) criterion is used and proved for nc-χ noise model and also a nonlocal voxel selection methodology is proposed for nc-χ distribution. The results illustrate robust and accurate performance compared to the related state-of-the-art methods, either on ideal nc-χ images or GRAPPA reconstructed ones. Copyright © 2018. Published by Elsevier Inc.
-
NASA Astrophysics Data System (ADS)
Hamers, Adrian S.
2018-05-01
We extend the formalism of a previous paper to include the effects of flybys and instantaneous perturbations such as supernovae on the long-term secular evolution of hierarchical multiple systems with an arbitrary number of bodies and hierarchy, provided that the system is composed of nested binary orbits. To model secular encounters, we expand the Hamiltonian in terms of the ratio of the separation of the perturber with respect to the barycentre of the multiple system, to the separation of the widest orbit. Subsequently, we integrate over the perturber orbit numerically or analytically. We verify our method for secular encounters and illustrate it with an example. Furthermore, we describe a method to compute instantaneous orbital changes to multiple systems, such as asymmetric supernovae and impulsive encounters. The secular code, with implementation of the extensions described in this paper, is publicly available within AMUSE, and we provide a number of simple example scripts to illustrate its usage for secular and impulsive encounters and asymmetric supernovae. The extensions presented in this paper are a next step towards efficiently modelling the evolution of complex multiple systems embedded in star clusters.
-
Modeling joint restoration strategies for interdependent infrastructure systems
Simonovic, Slobodan P.
2018-01-01
Life in the modern world depends on multiple critical services provided by infrastructure systems which are interdependent at multiple levels. To effectively respond to infrastructure failures, this paper proposes a model for developing optimal joint restoration strategy for interdependent infrastructure systems following a disruptive event. First, models for (i) describing structure of interdependent infrastructure system and (ii) their interaction process, are presented. Both models are considering the failure types, infrastructure operating rules and interdependencies among systems. Second, an optimization model for determining an optimal joint restoration strategy at infrastructure component level by minimizing the economic loss from the infrastructure failures, is proposed. The utility of the model is illustrated using a case study of electric-water systems. Results show that a small number of failed infrastructure components can trigger high level failures in interdependent systems; the optimal joint restoration strategy varies with failure occurrence time. The proposed models can help decision makers to understand the mechanisms of infrastructure interactions and search for optimal joint restoration strategy, which can significantly enhance safety of infrastructure systems. PMID:29649300
-
A modeling framework for exposing risks in complex systems.
Sharit, J
2000-08-01
This article introduces and develops a modeling framework for exposing risks in the form of human errors and adverse consequences in high-risk systems. The modeling framework is based on two components: a two-dimensional theory of accidents in systems developed by Perrow in 1984, and the concept of multiple system perspectives. The theory of accidents differentiates systems on the basis of two sets of attributes. One set characterizes the degree to which systems are interactively complex; the other emphasizes the extent to which systems are tightly coupled. The concept of multiple perspectives provides alternative descriptions of the entire system that serve to enhance insight into system processes. The usefulness of these two model components derives from a modeling framework that cross-links them, enabling a variety of work contexts to be exposed and understood that would otherwise be very difficult or impossible to identify. The model components and the modeling framework are illustrated in the case of a large and comprehensive trauma care system. In addition to its general utility in the area of risk analysis, this methodology may be valuable in applications of current methods of human and system reliability analysis in complex and continually evolving high-risk systems.
-
2017-05-30
including analysis, control and management of the systems across their multiple scopes . These difficulties will become more significant in near future...behaviors of the systems , it tends to cover their many scopes . Accordingly, we may obtain better models for the simulations in a data-driven manner...to capture variety of the instance distribution in a given data set for covering multiple scopes of our objective system in a seamless manner. (2
-
Virtual Systems Pharmacology (ViSP) software for simulation from mechanistic systems-level models.
Ermakov, Sergey; Forster, Peter; Pagidala, Jyotsna; Miladinov, Marko; Wang, Albert; Baillie, Rebecca; Bartlett, Derek; Reed, Mike; Leil, Tarek A
2014-01-01
Multiple software programs are available for designing and running large scale system-level pharmacology models used in the drug development process. Depending on the problem, scientists may be forced to use several modeling tools that could increase model development time, IT costs and so on. Therefore, it is desirable to have a single platform that allows setting up and running large-scale simulations for the models that have been developed with different modeling tools. We developed a workflow and a software platform in which a model file is compiled into a self-contained executable that is no longer dependent on the software that was used to create the model. At the same time the full model specifics is preserved by presenting all model parameters as input parameters for the executable. This platform was implemented as a model agnostic, therapeutic area agnostic and web-based application with a database back-end that can be used to configure, manage and execute large-scale simulations for multiple models by multiple users. The user interface is designed to be easily configurable to reflect the specifics of the model and the user's particular needs and the back-end database has been implemented to store and manage all aspects of the systems, such as Models, Virtual Patients, User Interface Settings, and Results. The platform can be adapted and deployed on an existing cluster or cloud computing environment. Its use was demonstrated with a metabolic disease systems pharmacology model that simulates the effects of two antidiabetic drugs, metformin and fasiglifam, in type 2 diabetes mellitus patients.
-
Virtual Systems Pharmacology (ViSP) software for simulation from mechanistic systems-level models
Ermakov, Sergey; Forster, Peter; Pagidala, Jyotsna; Miladinov, Marko; Wang, Albert; Baillie, Rebecca; Bartlett, Derek; Reed, Mike; Leil, Tarek A.
2014-01-01
Multiple software programs are available for designing and running large scale system-level pharmacology models used in the drug development process. Depending on the problem, scientists may be forced to use several modeling tools that could increase model development time, IT costs and so on. Therefore, it is desirable to have a single platform that allows setting up and running large-scale simulations for the models that have been developed with different modeling tools. We developed a workflow and a software platform in which a model file is compiled into a self-contained executable that is no longer dependent on the software that was used to create the model. At the same time the full model specifics is preserved by presenting all model parameters as input parameters for the executable. This platform was implemented as a model agnostic, therapeutic area agnostic and web-based application with a database back-end that can be used to configure, manage and execute large-scale simulations for multiple models by multiple users. The user interface is designed to be easily configurable to reflect the specifics of the model and the user's particular needs and the back-end database has been implemented to store and manage all aspects of the systems, such as Models, Virtual Patients, User Interface Settings, and Results. The platform can be adapted and deployed on an existing cluster or cloud computing environment. Its use was demonstrated with a metabolic disease systems pharmacology model that simulates the effects of two antidiabetic drugs, metformin and fasiglifam, in type 2 diabetes mellitus patients. PMID:25374542
-
A single predator multiple prey model with prey mutation
NASA Astrophysics Data System (ADS)
Mullan, Rory; Abernethy, Gavin M.; Glass, David H.; McCartney, Mark
2016-11-01
A multiple species predator-prey model is expanded with the introduction of a coupled map lattice for the prey, allowing the prey to mutate discretely into other prey species. The model is examined in its single predator, multiple mutating prey form. Two unimodal maps are used for the underlying dynamics of the prey species, with different predation strategies being used. Conclusions are drawn on how varying the control parameters of the model governs the overall behaviour and survival of the species. It is observed that in such a complex system, with multiple mutating prey, a large range of non-linear dynamics is possible.
-
Maruyama, Rika; Echigoya, Yusuke; Caluseriu, Oana; Aoki, Yoshitsugu; Takeda, Shin'ichi; Yokota, Toshifumi
2017-01-01
Exon-skipping therapy is an emerging approach that uses synthetic DNA-like molecules called antisense oligonucleotides (AONs) to splice out frame-disrupting parts of mRNA, restore the reading frame, and produce truncated yet functional proteins. Multiple exon skipping utilizing a cocktail of AONs can theoretically treat 80-90% of patients with Duchenne muscular dystrophy (DMD). The success of multiple exon skipping by the systemic delivery of a cocktail of AONs called phosphorodiamidate morpholino oligomers (PMOs) in a DMD dog model has made a significant impact on the development of therapeutics for DMD, leading to clinical trials of PMO-based drugs. Here, we describe the systemic delivery of a cocktail of PMOs to skip multiple exons in dystrophic dogs and the evaluation of the efficacies and toxicity in vivo.
-
Multiple Access Interference Reduction Using Received Response Code Sequence for DS-CDMA UWB System
NASA Astrophysics Data System (ADS)
Toh, Keat Beng; Tachikawa, Shin'ichi
This paper proposes a combination of novel Received Response (RR) sequence at the transmitter and a Matched Filter-RAKE (MF-RAKE) combining scheme receiver system for the Direct Sequence-Code Division Multiple Access Ultra Wideband (DS-CDMA UWB) multipath channel model. This paper also demonstrates the effectiveness of the RR sequence in Multiple Access Interference (MAI) reduction for the DS-CDMA UWB system. It suggests that by using conventional binary code sequence such as the M sequence or the Gold sequence, there is a possibility of generating extra MAI in the UWB system. Therefore, it is quite difficult to collect the energy efficiently although the RAKE reception method is applied at the receiver. The main purpose of the proposed system is to overcome the performance degradation for UWB transmission due to the occurrence of MAI during multiple accessing in the DS-CDMA UWB system. The proposed system improves the system performance by improving the RAKE reception performance using the RR sequence which can reduce the MAI effect significantly. Simulation results verify that significant improvement can be obtained by the proposed system in the UWB multipath channel models.
-
Li, Yan
2017-05-25
The efficiency evaluation model of integrated energy system, involving many influencing factors, and the attribute values are heterogeneous and non-deterministic, usually cannot give specific numerical or accurate probability distribution characteristics, making the final evaluation result deviation. According to the characteristics of the integrated energy system, a hybrid multi-attribute decision-making model is constructed. The evaluation model considers the decision maker's risk preference. In the evaluation of the efficiency of the integrated energy system, the evaluation value of some evaluation indexes is linguistic value, or the evaluation value of the evaluation experts is not consistent. These reasons lead to ambiguity in the decision information, usually in the form of uncertain linguistic values and numerical interval values. In this paper, the risk preference of decision maker is considered when constructing the evaluation model. Interval-valued multiple-attribute decision-making method and fuzzy linguistic multiple-attribute decision-making model are proposed. Finally, the mathematical model of efficiency evaluation of integrated energy system is constructed.
-
Adaptive Transmission and Channel Modeling for Frequency Hopping Communications
2009-09-21
proposed adaptive transmission method has much greater system capacity than conventional non-adaptive MC direct- sequence ( DS )- CDMA system. • We...several mobile radio systems. First, a new improved allocation algorithm was proposed for multicarrier code-division multiple access (MC- CDMA ) system...Multicarrier code-division multiple access (MC- CDMA ) system with adaptive frequency hopping (AFH) has attracted attention of researchers due to its
-
Entropy Measurement for Biometric Verification Systems.
Lim, Meng-Hui; Yuen, Pong C
2016-05-01
Biometric verification systems are designed to accept multiple similar biometric measurements per user due to inherent intrauser variations in the biometric data. This is important to preserve reasonable acceptance rate of genuine queries and the overall feasibility of the recognition system. However, such acceptance of multiple similar measurements decreases the imposter's difficulty of obtaining a system-acceptable measurement, thus resulting in a degraded security level. This deteriorated security needs to be measurable to provide truthful security assurance to the users. Entropy is a standard measure of security. However, the entropy formula is applicable only when there is a single acceptable possibility. In this paper, we develop an entropy-measuring model for biometric systems that accepts multiple similar measurements per user. Based on the idea of guessing entropy, the proposed model quantifies biometric system security in terms of adversarial guessing effort for two practical attacks. Excellent agreement between analytic and experimental simulation-based measurement results on a synthetic and a benchmark face dataset justify the correctness of our model and thus the feasibility of the proposed entropy-measuring approach.
-
The Modeling Environment for Total Risks studies (MENTOR) system, combined with an extension of the SHEDS (Stochastic Human Exposure and Dose Simulation) methodology, provide a mechanistically consistent framework for conducting source-to-dose exposure assessments of multiple pol...
-
Multiple attribute decision making model and application to food safety risk evaluation.
Ma, Lihua; Chen, Hong; Yan, Huizhe; Yang, Lifeng; Wu, Lifeng
2017-01-01
Decision making for supermarket food purchase decisions are characterized by network relationships. This paper analyzed factors that influence supermarket food selection and proposes a supplier evaluation index system based on the whole process of food production. The author established the intuitive interval value fuzzy set evaluation model based on characteristics of the network relationship among decision makers, and validated for a multiple attribute decision making case study. Thus, the proposed model provides a reliable, accurate method for multiple attribute decision making.
-
Acoustic 3D modeling by the method of integral equations
NASA Astrophysics Data System (ADS)
Malovichko, M.; Khokhlov, N.; Yavich, N.; Zhdanov, M.
2018-02-01
This paper presents a parallel algorithm for frequency-domain acoustic modeling by the method of integral equations (IE). The algorithm is applied to seismic simulation. The IE method reduces the size of the problem but leads to a dense system matrix. A tolerable memory consumption and numerical complexity were achieved by applying an iterative solver, accompanied by an effective matrix-vector multiplication operation, based on the fast Fourier transform (FFT). We demonstrate that, the IE system matrix is better conditioned than that of the finite-difference (FD) method, and discuss its relation to a specially preconditioned FD matrix. We considered several methods of matrix-vector multiplication for the free-space and layered host models. The developed algorithm and computer code were benchmarked against the FD time-domain solution. It was demonstrated that, the method could accurately calculate the seismic field for the models with sharp material boundaries and a point source and receiver located close to the free surface. We used OpenMP to speed up the matrix-vector multiplication, while MPI was used to speed up the solution of the system equations, and also for parallelizing across multiple sources. The practical examples and efficiency tests are presented as well.
-
Power-law Exponent in Multiplicative Langevin Equation with Temporally Correlated Noise
NASA Astrophysics Data System (ADS)
Morita, Satoru
2018-05-01
Power-law distributions are ubiquitous in nature. Random multiplicative processes are a basic model for the generation of power-law distributions. For discrete-time systems, the power-law exponent is known to decrease as the autocorrelation time of the multiplier increases. However, for continuous-time systems, it is not yet clear how the temporal correlation affects the power-law behavior. Herein, we analytically investigated a multiplicative Langevin equation with colored noise. We show that the power-law exponent depends on the details of the multiplicative noise, in contrast to the case of discrete-time systems.
-
Analysis of SI models with multiple interacting populations using subpopulations.
Thomas, Evelyn K; Gurski, Katharine F; Hoffman, Kathleen A
2015-02-01
Computing endemic equilibria and basic reproductive numbers for systems of differential equations describing epidemiological systems with multiple connections between subpopulations is often algebraically intractable. We present an alternative method which deconstructs the larger system into smaller subsystems and captures the interactions between the smaller systems as external forces using an approximate model. We bound the basic reproductive numbers of the full system in terms of the basic reproductive numbers of the smaller systems and use the alternate model to provide approximations for the endemic equilibrium. In addition to creating algebraically tractable reproductive numbers and endemic equilibria, we can demonstrate the influence of the interactions between subpopulations on the basic reproductive number of the full system. The focus of this paper is to provide analytical tools to help guide public health decisions with limited intervention resources.
-
A new fault diagnosis algorithm for AUV cooperative localization system
NASA Astrophysics Data System (ADS)
Shi, Hongyang; Miao, Zhiyong; Zhang, Yi
2017-10-01
Multiple AUVs cooperative localization as a new kind of underwater positioning technology, not only can improve the positioning accuracy, but also has many advantages the single AUV does not have. It is necessary to detect and isolate the fault to increase the reliability and availability of the AUVs cooperative localization system. In this paper, the Extended Multiple Model Adaptive Cubature Kalmam Filter (EMMACKF) method is presented to detect the fault. The sensor failures are simulated based on the off-line experimental data. Experimental results have shown that the faulty apparatus can be diagnosed effectively using the proposed method. Compared with Multiple Model Adaptive Extended Kalman Filter and Multi-Model Adaptive Unscented Kalman Filter, both accuracy and timelines have been improved to some extent.
-
NASA Astrophysics Data System (ADS)
Bhakti, Satria Seto; Samsudin, Achmad; Chandra, Didi Teguh; Siahaan, Parsaoran
2017-05-01
The aim of research is developing multiple-choices test items as tools for measuring the scientific of generic skills on solar system. To achieve the aim that the researchers used the ADDIE model consisting Of: Analyzing, Design, Development, Implementation, dan Evaluation, all of this as a method research. While The scientific of generic skills limited research to five indicator including: (1) indirect observation, (2) awareness of the scale, (3) inference logic, (4) a causal relation, and (5) mathematical modeling. The participants are 32 students at one of junior high schools in Bandung. The result shown that multiple-choices that are constructed test items have been declared valid by the expert validator, and after the tests show that the matter of developing multiple-choices test items be able to measuring the scientific of generic skills on solar system.
-
Liu, Hua; Wu, Wen
2017-01-01
For improving the tracking accuracy and model switching speed of maneuvering target tracking in nonlinear systems, a new algorithm named the interacting multiple model fifth-degree spherical simplex-radial cubature Kalman filter (IMM5thSSRCKF) is proposed in this paper. The new algorithm is a combination of the interacting multiple model (IMM) filter and the fifth-degree spherical simplex-radial cubature Kalman filter (5thSSRCKF). The proposed algorithm makes use of Markov process to describe the switching probability among the models, and uses 5thSSRCKF to deal with the state estimation of each model. The 5thSSRCKF is an improved filter algorithm, which utilizes the fifth-degree spherical simplex-radial rule to improve the filtering accuracy. Finally, the tracking performance of the IMM5thSSRCKF is evaluated by simulation in a typical maneuvering target tracking scenario. Simulation results show that the proposed algorithm has better tracking performance and quicker model switching speed when disposing maneuver models compared with the interacting multiple model unscented Kalman filter (IMMUKF), the interacting multiple model cubature Kalman filter (IMMCKF) and the interacting multiple model fifth-degree cubature Kalman filter (IMM5thCKF). PMID:28608843
-
Liu, Hua; Wu, Wen
2017-06-13
For improving the tracking accuracy and model switching speed of maneuvering target tracking in nonlinear systems, a new algorithm named the interacting multiple model fifth-degree spherical simplex-radial cubature Kalman filter (IMM5thSSRCKF) is proposed in this paper. The new algorithm is a combination of the interacting multiple model (IMM) filter and the fifth-degree spherical simplex-radial cubature Kalman filter (5thSSRCKF). The proposed algorithm makes use of Markov process to describe the switching probability among the models, and uses 5thSSRCKF to deal with the state estimation of each model. The 5thSSRCKF is an improved filter algorithm, which utilizes the fifth-degree spherical simplex-radial rule to improve the filtering accuracy. Finally, the tracking performance of the IMM5thSSRCKF is evaluated by simulation in a typical maneuvering target tracking scenario. Simulation results show that the proposed algorithm has better tracking performance and quicker model switching speed when disposing maneuver models compared with the interacting multiple model unscented Kalman filter (IMMUKF), the interacting multiple model cubature Kalman filter (IMMCKF) and the interacting multiple model fifth-degree cubature Kalman filter (IMM5thCKF).
-
Managing data from multiple disciplines, scales, and sites to support synthesis and modeling
Olson, R. J.; Briggs, J. M.; Porter, J.H.; Mah, Grant R.; Stafford, S.G.
1999-01-01
The synthesis and modeling of ecological processes at multiple spatial and temporal scales involves bringing together and sharing data from numerous sources. This article describes a data and information system model that facilitates assembling, managing, and sharing diverse data from multiple disciplines, scales, and sites to support integrated ecological studies. Cross-site scientific-domain working groups coordinate the development of data associated with their particular scientific working group, including decisions about data requirements, data to be compiled, data formats, derived data products, and schedules across the sites. The Web-based data and information system consists of nodes for each working group plus a central node that provides data access, project information, data query, and other functionality. The approach incorporates scientists and computer experts in the working groups and provides incentives for individuals to submit documented data to the data and information system.
-
Pandey, Vinay Kumar; Kar, Indrani; Mahanta, Chitralekha
2017-07-01
In this paper, an adaptive control method using multiple models with second level adaptation is proposed for a class of nonlinear multi-input multi-output (MIMO) coupled systems. Multiple estimation models are used to tune the unknown parameters at the first level. The second level adaptation provides a single parameter vector for the controller. A feedback linearization technique is used to design a state feedback control. The efficacy of the designed controller is validated by conducting real time experiment on a laboratory setup of twin rotor MIMO system (TRMS). The TRMS setup is discussed in detail and the experiments were performed for regulation and tracking problem for pitch and yaw control using different reference signals. An Extended Kalman Filter (EKF) has been used to observe the unavailable states of the TRMS. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.
-
Using stable isotopes and models to explore estuarine linkages at multiple scales
Estuarine managers need tools to respond to dynamic stressors that occur in three linked environments – coastal ocean, estuaries and watersheds. Models have been the tool of choice for examining these dynamic systems because they simplify processes and integrate over multiple sc...
-
ERIC Educational Resources Information Center
Rovee-Collier, Carolyn; Cuevas, Kimberly
2009-01-01
How the memory of adults evolves from the memory abilities of infants is a central problem in cognitive development. The popular solution holds that the multiple memory systems of adults mature at different rates during infancy. The "early-maturing system" (implicit or nondeclarative memory) functions automatically from birth, whereas the…
-
ERIC Educational Resources Information Center
Yang, Tzu-Chi; Hwang, Gwo-Jen; Yang, Stephen Jen-Hwa
2013-01-01
In this study, an adaptive learning system is developed by taking multiple dimensions of personalized features into account. A personalized presentation module is proposed for developing adaptive learning systems based on the field dependent/independent cognitive style model and the eight dimensions of Felder-Silverman's learning style. An…
-
Nomura, Emi M.; Reber, Paul J.
2012-01-01
Considerable evidence has argued in favor of multiple neural systems supporting human category learning, one based on conscious rule inference and one based on implicit information integration. However, there have been few attempts to study potential system interactions during category learning. The PINNACLE (Parallel Interactive Neural Networks Active in Category Learning) model incorporates multiple categorization systems that compete to provide categorization judgments about visual stimuli. Incorporating competing systems requires inclusion of cognitive mechanisms associated with resolving this competition and creates a potential credit assignment problem in handling feedback. The hypothesized mechanisms make predictions about internal mental states that are not always reflected in choice behavior, but may be reflected in neural activity. Two prior functional magnetic resonance imaging (fMRI) studies of category learning were re-analyzed using PINNACLE to identify neural correlates of internal cognitive states on each trial. These analyses identified additional brain regions supporting the two types of category learning, regions particularly active when the systems are hypothesized to be in maximal competition, and found evidence of covert learning activity in the “off system” (the category learning system not currently driving behavior). These results suggest that PINNACLE provides a plausible framework for how competing multiple category learning systems are organized in the brain and shows how computational modeling approaches and fMRI can be used synergistically to gain access to cognitive processes that support complex decision-making machinery. PMID:24962771
-
Sensor fusion V; Proceedings of the Meeting, Boston, MA, Nov. 15-17, 1992
NASA Technical Reports Server (NTRS)
Schenker, Paul S. (Editor)
1992-01-01
Topics addressed include 3D object perception, human-machine interface in multisensor systems, sensor fusion architecture, fusion of multiple and distributed sensors, interface and decision models for sensor fusion, computational networks, simple sensing for complex action, multisensor-based control, and metrology and calibration of multisensor systems. Particular attention is given to controlling 3D objects by sketching 2D views, the graphical simulation and animation environment for flexible structure robots, designing robotic systems from sensorimotor modules, cylindrical object reconstruction from a sequence of images, an accurate estimation of surface properties by integrating information using Bayesian networks, an adaptive fusion model for a distributed detection system, multiple concurrent object descriptions in support of autonomous navigation, robot control with multiple sensors and heuristic knowledge, and optical array detectors for image sensors calibration. (No individual items are abstracted in this volume)
-
DOE Office of Scientific and Technical Information (OSTI.GOV)
Arion is a library and tool set that enables researchers to holistically define test system models. To define a complex system for testing an algorithm or control requires expertise across multiple domains. Simulating a complex system requires the integration of multiple simulators and test hardware, each with their own specification languages and concepts. This requires extensive set of knowledge and capabilities. Arion was developed to alleviate this challenge. Arion is a library of Java libraries that abstracts the concepts from supported simulators into a cohesive model language that allows someone to build models to their needed level of fidelity andmore » expertise. Arion is also a software tool that translates the users model back into the specification languages of the simulators and test hardware needed for execution.« less
-
Infrasound-array-element frequency response: in-situ measurement and modeling
NASA Astrophysics Data System (ADS)
Gabrielson, T.
2011-12-01
Most array elements at the infrasound stations of the International Monitoring System use some variant of a multiple-inlet pipe system for wind-noise suppression. These pipe systems have a significant impact on the overall frequency response of the element. The spatial distribution of acoustic inlets introduces a response dependence that is a function of frequency and of vertical and horizontal arrival angle; the system of inlets, pipes, and summing junctions further shapes that response as the signal is ducted to the transducer. In-situ measurements, using a co-located reference microphone, can determine the overall frequency response and diagnose problems with the system. As of July 2011, the in-situ frequency responses for 25 individual elements at 6 operational stations (I10, I53, I55, I56, I57, and I99) have been measured. In support of these measurements, a fully thermo-viscous model for the acoustics of these multiple-inlet pipe systems has been developed. In addition to measurements at operational stations, comparative analyses have been done on experimental systems: a multiple-inlet radial-pipe system with varying inlet hole size; a one-quarter scale model of a 70-meter rosette system; and vertical directionality of a small rosette system using aircraft flyovers. [Funded by the US Army Space and Missile Defense Command
-
Systems Epidemiology: What’s in a Name?
Dammann, O.; Gray, P.; Gressens, P.; Wolkenhauer, O.; Leviton, A.
2014-01-01
Systems biology is an interdisciplinary effort to integrate molecular, cellular, tissue, organ, and organism levels of function into computational models that facilitate the identification of general principles. Systems medicine adds a disease focus. Systems epidemiology adds yet another level consisting of antecedents that might contribute to the disease process in populations. In etiologic and prevention research, systems-type thinking about multiple levels of causation will allow epidemiologists to identify contributors to disease at multiple levels as well as their interactions. In public health, systems epidemiology will contribute to the improvement of syndromic surveillance methods. We encourage the creation of computational simulation models that integrate information about disease etiology, pathogenetic data, and the expertise of investigators from different disciplines. PMID:25598870
-
Elenchezhiyan, M; Prakash, J
2015-09-01
In this work, state estimation schemes for non-linear hybrid dynamic systems subjected to stochastic state disturbances and random errors in measurements using interacting multiple-model (IMM) algorithms are formulated. In order to compute both discrete modes and continuous state estimates of a hybrid dynamic system either an IMM extended Kalman filter (IMM-EKF) or an IMM based derivative-free Kalman filters is proposed in this study. The efficacy of the proposed IMM based state estimation schemes is demonstrated by conducting Monte-Carlo simulation studies on the two-tank hybrid system and switched non-isothermal continuous stirred tank reactor system. Extensive simulation studies reveal that the proposed IMM based state estimation schemes are able to generate fairly accurate continuous state estimates and discrete modes. In the presence and absence of sensor bias, the simulation studies reveal that the proposed IMM unscented Kalman filter (IMM-UKF) based simultaneous state and parameter estimation scheme outperforms multiple-model UKF (MM-UKF) based simultaneous state and parameter estimation scheme. Copyright © 2015 ISA. Published by Elsevier Ltd. All rights reserved.
-
Rovee-Collier, Carolyn; Cuevas, Kimberly
2009-01-01
How the memory of adults evolves from the memory abilities of infants is a central problem in cognitive development. The popular solution holds that the multiple memory systems of adults mature at different rates during infancy. The early-maturing system (implicit or nondeclarative memory) functions automatically from birth, whereas the late-maturing system (explicit or declarative memory) functions intentionally, with awareness, from late in the first year. Data are presented from research on deferred imitation, sensory preconditioning, potentiation, and context for which this solution cannot account and present an alternative model that eschews the need for multiple memory systems. The ecological model of infant memory development (N. E. Spear, 1984) holds that members of all species are perfectly adapted to their niche at each point in ontogeny and exhibit effective, evolutionarily selected solutions to whatever challenges each new niche poses. Because adults and infants occupy different niches, what they perceive, learn, and remember about the same event differs, but their raw capacity to learn and remember does not. PMID:19209999
-
System and method for optimal load and source scheduling in context aware homes
DOE Office of Scientific and Technical Information (OSTI.GOV)
Shetty, Pradeep; Foslien Graber, Wendy; Mangsuli, Purnaprajna R.
A controller for controlling energy consumption in a home includes a constraints engine to define variables for multiple appliances in the home corresponding to various home modes and persona of an occupant of the home. A modeling engine models multiple paths of energy utilization of the multiple appliances to place the home into a desired state from a current context. An optimal scheduler receives the multiple paths of energy utilization and generates a schedule as a function of the multiple paths and a selected persona to place the home in a desired state.
-
Motion control of musculoskeletal systems with redundancy.
Park, Hyunjoo; Durand, Dominique M
2008-12-01
Motion control of musculoskeletal systems for functional electrical stimulation (FES) is a challenging problem due to the inherent complexity of the systems. These include being highly nonlinear, strongly coupled, time-varying, time-delayed, and redundant. The redundancy in particular makes it difficult to find an inverse model of the system for control purposes. We have developed a control system for multiple input multiple output (MIMO) redundant musculoskeletal systems with little prior information. The proposed method separates the steady-state properties from the dynamic properties. The dynamic control uses a steady-state inverse model and is implemented with both a PID controller for disturbance rejection and an artificial neural network (ANN) feedforward controller for fast trajectory tracking. A mechanism to control the sum of the muscle excitation levels is also included. To test the performance of the proposed control system, a two degree of freedom ankle-subtalar joint model with eight muscles was used. The simulation results show that separation of steady-state and dynamic control allow small output tracking errors for different reference trajectories such as pseudo-step, sinusoidal and filtered random signals. The proposed control method also demonstrated robustness against system parameter and controller parameter variations. A possible application of this control algorithm is FES control using multiple contact cuff electrodes where mathematical modeling is not feasible and the redundancy makes the control of dynamic movement difficult.
-
Linking Multiple Databases: Term Project Using "Sentences" DBMS.
ERIC Educational Resources Information Center
King, Ronald S.; Rainwater, Stephen B.
This paper describes a methodology for use in teaching an introductory Database Management System (DBMS) course. Students master basic database concepts through the use of a multiple component project implemented in both relational and associative data models. The associative data model is a new approach for designing multi-user, Web-enabled…
-
The primary goal was to asess Hg cycling within a small coastal plain watershed (McTier Creek) using multiple watershed models with distinct mathematical frameworks that emphasize different system dynamics; a secondary goal was to identify current needs in watershed-scale Hg mode...
-
Experimental models of demyelination and remyelination.
Torre-Fuentes, L; Moreno-Jiménez, L; Pytel, V; Matías-Guiu, J A; Gómez-Pinedo, U; Matías-Guiu, J
2017-08-29
Experimental animal models constitute a useful tool to deepen our knowledge of central nervous system disorders. In the case of multiple sclerosis, however, there is no such specific model able to provide an overview of the disease; multiple models covering the different pathophysiological features of the disease are therefore necessary. We reviewed the different in vitro and in vivo experimental models used in multiple sclerosis research. Concerning in vitro models, we analysed cell cultures and slice models. As for in vivo models, we examined such models of autoimmunity and inflammation as experimental allergic encephalitis in different animals and virus-induced demyelinating diseases. Furthermore, we analysed models of demyelination and remyelination, including chemical lesions caused by cuprizone, lysolecithin, and ethidium bromide; zebrafish; and transgenic models. Experimental models provide a deeper understanding of the different pathogenic mechanisms involved in multiple sclerosis. Choosing one model or another depends on the specific aims of the study. Copyright © 2017 Sociedad Española de Neurología. Publicado por Elsevier España, S.L.U. All rights reserved.
-
Otto, A Ross; Gershman, Samuel J; Markman, Arthur B; Daw, Nathaniel D
2013-05-01
A number of accounts of human and animal behavior posit the operation of parallel and competing valuation systems in the control of choice behavior. In these accounts, 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. Following the hypothesis that model-based reinforcement learning requires cognitive resources, we demonstrated that having human decision makers perform a demanding secondary task engenders increased reliance on a model-free reinforcement-learning strategy. Further, we showed that, across trials, people negotiate the trade-off between the two systems dynamically as a function of concurrent executive-function demands, and people's choice latencies reflect the computational expenses of the strategy they employ. 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.
-
A new adaptive multiple modelling approach for non-linear and non-stationary systems
NASA Astrophysics Data System (ADS)
Chen, Hao; Gong, Yu; Hong, Xia
2016-07-01
This paper proposes a novel adaptive multiple modelling algorithm for non-linear and non-stationary systems. This simple modelling paradigm comprises K candidate sub-models which are all linear. With data available in an online fashion, the performance of all candidate sub-models are monitored based on the most recent data window, and M best sub-models are selected from the K candidates. The weight coefficients of the selected sub-model are adapted via the recursive least square (RLS) algorithm, while the coefficients of the remaining sub-models are unchanged. These M model predictions are then optimally combined to produce the multi-model output. We propose to minimise the mean square error based on a recent data window, and apply the sum to one constraint to the combination parameters, leading to a closed-form solution, so that maximal computational efficiency can be achieved. In addition, at each time step, the model prediction is chosen from either the resultant multiple model or the best sub-model, whichever is the best. Simulation results are given in comparison with some typical alternatives, including the linear RLS algorithm and a number of online non-linear approaches, in terms of modelling performance and time consumption.
-
Coelho, Antonio Augusto Rodrigues
2016-01-01
This paper introduces the Fuzzy Logic Hypercube Interpolator (FLHI) and demonstrates applications in control of multiple-input single-output (MISO) and multiple-input multiple-output (MIMO) processes with Hammerstein nonlinearities. FLHI consists of a Takagi-Sugeno fuzzy inference system where membership functions act as kernel functions of an interpolator. Conjunction of membership functions in an unitary hypercube space enables multivariable interpolation of N-dimensions. Membership functions act as interpolation kernels, such that choice of membership functions determines interpolation characteristics, allowing FLHI to behave as a nearest-neighbor, linear, cubic, spline or Lanczos interpolator, to name a few. The proposed interpolator is presented as a solution to the modeling problem of static nonlinearities since it is capable of modeling both a function and its inverse function. Three study cases from literature are presented, a single-input single-output (SISO) system, a MISO and a MIMO system. Good results are obtained regarding performance metrics such as set-point tracking, control variation and robustness. Results demonstrate applicability of the proposed method in modeling Hammerstein nonlinearities and their inverse functions for implementation of an output compensator with Model Based Predictive Control (MBPC), in particular Dynamic Matrix Control (DMC). PMID:27657723
-
Experimental Uncertainty Associated with Traveling Wave Excitation
2014-09-15
20 2.9 Schematic of the Lumped Model [6] . . . . . . . . . . . . . . . . . . . . . . . 21 2.10 Multiple Coupled Pendulum [7...model to describe the physical system, the authors chose to employ a coupled pendulum model to represent a rotor. This system is shown in Figure 2.10...System mistuning is introduced by altering pendulum lengths. All other system parameters are equal. A linear viscous proportional damping force is
-
Chang, Wen-Jer; Huang, Bo-Jyun
2014-11-01
The multi-constrained robust fuzzy control problem is investigated in this paper for perturbed continuous-time nonlinear stochastic systems. The nonlinear system considered in this paper is represented by a Takagi-Sugeno fuzzy model with perturbations and state multiplicative noises. The multiple performance constraints considered in this paper include stability, passivity and individual state variance constraints. The Lyapunov stability theory is employed to derive sufficient conditions to achieve the above performance constraints. By solving these sufficient conditions, the contribution of this paper is to develop a parallel distributed compensation based robust fuzzy control approach to satisfy multiple performance constraints for perturbed nonlinear systems with multiplicative noises. At last, a numerical example for the control of perturbed inverted pendulum system is provided to illustrate the applicability and effectiveness of the proposed multi-constrained robust fuzzy control method. Copyright © 2014 ISA. Published by Elsevier Ltd. All rights reserved.
-
Training Systems Modelers through the Development of a Multi-scale Chagas Disease Risk Model
NASA Astrophysics Data System (ADS)
Hanley, J.; Stevens-Goodnight, S.; Kulkarni, S.; Bustamante, D.; Fytilis, N.; Goff, P.; Monroy, C.; Morrissey, L. A.; Orantes, L.; Stevens, L.; Dorn, P.; Lucero, D.; Rios, J.; Rizzo, D. M.
2012-12-01
The goal of our NSF-sponsored Division of Behavioral and Cognitive Sciences grant is to create a multidisciplinary approach to develop spatially explicit models of vector-borne disease risk using Chagas disease as our model. Chagas disease is a parasitic disease endemic to Latin America that afflicts an estimated 10 million people. The causative agent (Trypanosoma cruzi) is most commonly transmitted to humans by blood feeding triatomine insect vectors. Our objectives are: (1) advance knowledge on the multiple interacting factors affecting the transmission of Chagas disease, and (2) provide next generation genomic and spatial analysis tools applicable to the study of other vector-borne diseases worldwide. This funding is a collaborative effort between the RSENR (UVM), the School of Engineering (UVM), the Department of Biology (UVM), the Department of Biological Sciences (Loyola (New Orleans)) and the Laboratory of Applied Entomology and Parasitology (Universidad de San Carlos). Throughout this five-year study, multi-educational groups (i.e., high school, undergraduate, graduate, and postdoctoral) will be trained in systems modeling. This systems approach challenges students to incorporate environmental, social, and economic as well as technical aspects and enables modelers to simulate and visualize topics that would either be too expensive, complex or difficult to study directly (Yasar and Landau 2003). We launch this research by developing a set of multi-scale, epidemiological models of Chagas disease risk using STELLA® software v.9.1.3 (isee systems, inc., Lebanon, NH). We use this particular system dynamics software as a starting point because of its simple graphical user interface (e.g., behavior-over-time graphs, stock/flow diagrams, and causal loops). To date, high school and undergraduate students have created a set of multi-scale (i.e., homestead, village, and regional) disease models. Modeling the system at multiple spatial scales forces recognition that the system's structure generates its behavior; and STELLA®'s graphical interface allows researchers at multiple educational levels to observe patterns and trends as the system changes over time. Graduate students and postdoctoral researchers will utilize these initial models to more efficiently communicate and transfer knowledge across disciplines prior to generating more novel and complex disease risk models. The hope is that these models will improve causal viewpoints, understanding of the system patterns, and how to best mitigate disease risk across multiple spatial scales. Yasar O, Landau RH (2003) Elements of computational science and engineering education. Siam Review 45(4): 787-805.
-
An Exact Model-Based Method for Near-Field Sources Localization with Bistatic MIMO System.
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.
-
Cost-effective solutions to maintaining smart grid reliability
NASA Astrophysics Data System (ADS)
Qin, Qiu
As the aging power systems are increasingly working closer to the capacity and thermal limits, maintaining an sufficient reliability has been of great concern to the government agency, utility companies and users. This dissertation focuses on improving the reliability of transmission and distribution systems. Based on the wide area measurements, multiple model algorithms are developed to diagnose transmission line three-phase short to ground faults in the presence of protection misoperations. The multiple model algorithms utilize the electric network dynamics to provide prompt and reliable diagnosis outcomes. Computational complexity of the diagnosis algorithm is reduced by using a two-step heuristic. The multiple model algorithm is incorporated into a hybrid simulation framework, which consist of both continuous state simulation and discrete event simulation, to study the operation of transmission systems. With hybrid simulation, line switching strategy for enhancing the tolerance to protection misoperations is studied based on the concept of security index, which involves the faulted mode probability and stability coverage. Local measurements are used to track the generator state and faulty mode probabilities are calculated in the multiple model algorithms. FACTS devices are considered as controllers for the transmission system. The placement of FACTS devices into power systems is investigated with a criterion of maintaining a prescribed level of control reconfigurability. Control reconfigurability measures the small signal combined controllability and observability of a power system with an additional requirement on fault tolerance. For the distribution systems, a hierarchical framework, including a high level recloser allocation scheme and a low level recloser placement scheme, is presented. The impacts of recloser placement on the reliability indices is analyzed. Evaluation of reliability indices in the placement process is carried out via discrete event simulation. The reliability requirements are described with probabilities and evaluated from the empirical distributions of reliability indices.
-
Rowat, S C
1998-01-01
The central nervous, immune, and endocrine systems communicate through multiple common messengers. Over evolutionary time, what may be termed integrated defense system(s) (IDS) have developed to coordinate these communications for specific contexts; these include the stress response, acute-phase response, nonspecific immune response, immune response to antigen, kindling, tolerance, time-dependent sensitization, neurogenic switching, and traumatic dissociation (TD). These IDSs are described and their overlap is examined. Three models of disease production are generated: damage, in which IDSs function incorrectly; inadequate/inappropriate, in which IDS response is outstripped by a changing context; and evolving/learning, in which the IDS learned response to a context is deemed pathologic. Mechanisms of multiple chemical sensitivity (MCS) are developed from several IDS disease models. Model 1A is pesticide damage to the central nervous system, overlapping with body chemical burdens, TD, and chronic zinc deficiency; model 1B is benzene disruption of interleukin-1, overlapping with childhood developmental windows and hapten-antigenic spreading; and model 1C is autoimmunity to immunoglobulin-G (IgG), overlapping with spreading to other IgG-inducers, sudden spreading of inciters, and food-contaminating chemicals. Model 2A is chemical and stress overload, including comparison with the susceptibility/sensitization/triggering/spreading model; model 2B is genetic mercury allergy, overlapping with: heavy metals/zinc displacement and childhood/gestational mercury exposures; and model 3 is MCS as evolution and learning. Remarks are offered on current MCS research. Problems with clinical measurement are suggested on the basis of IDS models. Large-sample patient self-report epidemiology is described as an alternative or addition to clinical biomarker and animal testing. Images Figure 1 Figure 2 Figure 3 Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 PMID:9539008
-
Intelligent multiagent coordination based on reinforcement hierarchical neuro-fuzzy models.
Mendoza, Leonardo Forero; Vellasco, Marley; Figueiredo, Karla
2014-12-01
This paper presents the research and development of two hybrid neuro-fuzzy models for the hierarchical coordination of multiple intelligent agents. The main objective of the models is to have multiple agents interact intelligently with each other in complex systems. We developed two new models of coordination for intelligent multiagent systems, which integrates the Reinforcement Learning Hierarchical Neuro-Fuzzy model with two proposed coordination mechanisms: the MultiAgent Reinforcement Learning Hierarchical Neuro-Fuzzy with a market-driven coordination mechanism (MA-RL-HNFP-MD) and the MultiAgent Reinforcement Learning Hierarchical Neuro-Fuzzy with graph coordination (MA-RL-HNFP-CG). In order to evaluate the proposed models and verify the contribution of the proposed coordination mechanisms, two multiagent benchmark applications were developed: the pursuit game and the robot soccer simulation. The results obtained demonstrated that the proposed coordination mechanisms greatly improve the performance of the multiagent system when compared with other strategies.
-
Controlled Ecological Life Support System (CELSS) modeling
NASA Technical Reports Server (NTRS)
Drysdale, Alan; Thomas, Mark; Fresa, Mark; Wheeler, Ray
1992-01-01
Attention is given to CELSS, a critical technology for the Space Exploration Initiative. OCAM (object-oriented CELSS analysis and modeling) models carbon, hydrogen, and oxygen recycling. Multiple crops and plant types can be simulated. Resource recovery options from inedible biomass include leaching, enzyme treatment, aerobic digestion, and mushroom and fish growth. The benefit of using many small crops overlapping in time, instead of a single large crop, is demonstrated. Unanticipated results include startup transients which reduce the benefit of multiple small crops. The relative contributions of mass, energy, and manpower to system cost are analyzed in order to determine appropriate research directions.
-
ERIC Educational Resources Information Center
Wholeben, Brent Edward
This report describing the use of operations research techniques to determine which courseware packages or what microcomputer systems best address varied instructional objectives focuses on the MICROPIK model, a highly structured evaluation technique for making such complex instructional decisions. MICROPIK is a multiple alternatives model (MAA)…
-
NASA Astrophysics Data System (ADS)
Kim, S. H.; Lim, C. H.; Kim, J.; Lee, W. K.; Kafatos, M.
2016-12-01
The Korean Peninsula has unique agricultural environment due to the differences of political and socio-economical system between Republic of Korea (SK, hereafter) and Democratic Peoples' Republic of Korea (NK, hereafter). NK has been suffering lack of food supplies caused by natural disasters, land degradation and political failure. The neighboring developed country SK has better agricultural system but very low food self-sufficiency rate. Maize is an important crop in both countries since it is staple food for NK and SK is No. 2 maize importing country in the world after Japan. Therefore, evaluating maize yield potential (Yp) in the two distinct regions is essential to assess food security under climate change and variability. In this study, we utilized multiple process-based crop models, having ability of regional scale assessment, to evaluate maize Yp and assess the model uncertainties -EPIC, GEPIC, DSSAT, and APSIM model that has capability of regional scale expansion (apsimRegions). First we evaluated each crop model for 3 years from 2012 to 2014 using reanalysis data (RDAPS; Regional Data Assimilation and Prediction System produced by Korea Meteorological Agency) and observed yield data. Each model performances were compared over the different regions in the Korean Peninsula having different local climate characteristics. To quantify of the major influence of at each climate variables, we also conducted sensitivity test using 20 years of climatology in historical period from 1981 to 2000. Lastly, the multi-crop model ensemble analysis was performed for future period from 2031 to 2050. The required weather variables projected for mid-century were employed from COordinated Regional climate Downscaling EXperiment (CORDEX) East Asia. The high-resolution climate data were obtained from multiple regional climate models (RCM) driven by multiple climate scenarios projected from multiple global climate models (GCMs) in conjunction with multiple greenhouse gas concentration pathways. The results indicate that the projected Yp in the Korean peninsula is significantly changed comparing to the historical period and proper adaptation strategies such as optimized planting dates can considerably alleviate Yp decrease.
-
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
-
General Methodology for Designing Spacecraft Trajectories
NASA Technical Reports Server (NTRS)
Condon, Gerald; Ocampo, Cesar; Mathur, Ravishankar; Morcos, Fady; Senent, Juan; Williams, Jacob; Davis, Elizabeth C.
2012-01-01
A methodology for designing spacecraft trajectories in any gravitational environment within the solar system has been developed. The methodology facilitates modeling and optimization for problems ranging from that of a single spacecraft orbiting a single celestial body to that of a mission involving multiple spacecraft and multiple propulsion systems operating in gravitational fields of multiple celestial bodies. The methodology consolidates almost all spacecraft trajectory design and optimization problems into a single conceptual framework requiring solution of either a system of nonlinear equations or a parameter-optimization problem with equality and/or inequality constraints.
-
Rope Hadronization and Strange Particle Production
NASA Astrophysics Data System (ADS)
Bierlich, Christian
2018-02-01
Rope Hadronization is a model extending the Lund string hadronization model to describe environments with many overlapping strings, such as high multiplicity pp collisions or AA collisions. Including effects of Rope Hadronization drastically improves description of strange/non-strange hadron ratios as function of event multiplicity in all systems from e+e- to AA. Implementation of Rope Hadronization in the MC event generators Dipsy and PYTHIA8 is discussed, as well as future prospects for jet studies and studies of small systems.
-
Hwang, Wonjun; Wang, Haitao; Kim, Hyunwoo; Kee, Seok-Cheol; Kim, Junmo
2011-04-01
The authors present a robust face recognition system for large-scale data sets taken under uncontrolled illumination variations. The proposed face recognition system consists of a novel illumination-insensitive preprocessing method, a hybrid Fourier-based facial feature extraction, and a score fusion scheme. First, in the preprocessing stage, a face image is transformed into an illumination-insensitive image, called an "integral normalized gradient image," by normalizing and integrating the smoothed gradients of a facial image. Then, for feature extraction of complementary classifiers, multiple face models based upon hybrid Fourier features are applied. The hybrid Fourier features are extracted from different Fourier domains in different frequency bandwidths, and then each feature is individually classified by linear discriminant analysis. In addition, multiple face models are generated by plural normalized face images that have different eye distances. Finally, to combine scores from multiple complementary classifiers, a log likelihood ratio-based score fusion scheme is applied. The proposed system using the face recognition grand challenge (FRGC) experimental protocols is evaluated; FRGC is a large available data set. Experimental results on the FRGC version 2.0 data sets have shown that the proposed method shows an average of 81.49% verification rate on 2-D face images under various environmental variations such as illumination changes, expression changes, and time elapses.
-
Parallel Computing Using Web Servers and "Servlets".
ERIC Educational Resources Information Center
Lo, Alfred; Bloor, Chris; Choi, Y. K.
2000-01-01
Describes parallel computing and presents inexpensive ways to implement a virtual parallel computer with multiple Web servers. Highlights include performance measurement of parallel systems; models for using Java and intranet technology including single server, multiple clients and multiple servers, single client; and a comparison of CGI (common…
-
Power optimization of wireless media systems with space-time block codes.
Yousefi'zadeh, Homayoun; Jafarkhani, Hamid; Moshfeghi, Mehran
2004-07-01
We present analytical and numerical solutions to the problem of power control in wireless media systems with multiple antennas. We formulate a set of optimization problems aimed at minimizing total power consumption of wireless media systems subject to a given level of QoS and an available bit rate. Our formulation takes into consideration the power consumption related to source coding, channel coding, and transmission of multiple-transmit antennas. In our study, we consider Gauss-Markov and video source models, Rayleigh fading channels along with the Bernoulli/Gilbert-Elliott loss models, and space-time block codes.
-
NASA Astrophysics Data System (ADS)
Brandeker, Alexis; Liseau, René; Artymowicz, Pawel; Jayawardhana, Ray
2001-11-01
Since a majority of young low-mass stars are members of multiple systems, the study of their stellar and disk configurations is crucial to our understanding of both star and planet formation processes. Here we present near-infrared adaptive optics observations of the young multiple star system VW Chamaeleon. The previously known 0.7" binary is clearly resolved already in our raw J- and K-band images. We report the discovery of a new faint companion to the secondary, at an apparent separation of only 0.1", or 16 AU. Our high-resolution photometric observations also make it possible to measure the J-K colors of each of the three components individually. We detect an infrared excess in the primary, consistent with theoretical models of a circumprimary disk. Analytical and numerical calculations of orbital stability show that VW Cha may be a stable triple system. Using models for the age and total mass of the secondary pair, we estimate the orbital period to be 74 yr. Thus, follow-up astrometric observations might yield direct dynamical masses within a few years and constrain evolutionary models of low-mass stars. Our results demonstrate that adaptive optics imaging in conjunction with deconvolution techniques is a powerful tool for probing close multiple systems. Based on observations collected at the European Southern Observatory, Chile.
-
An Integrated Crustal Dynamics Simulator
NASA Astrophysics Data System (ADS)
Xing, H. L.; Mora, P.
2007-12-01
Numerical modelling offers an outstanding opportunity to gain an understanding of the crustal dynamics and complex crustal system behaviour. This presentation provides our long-term and ongoing effort on finite element based computational model and software development to simulate the interacting fault system for earthquake forecasting. A R-minimum strategy based finite-element computational model and software tool, PANDAS, for modelling 3-dimensional nonlinear frictional contact behaviour between multiple deformable bodies with the arbitrarily-shaped contact element strategy has been developed by the authors, which builds up a virtual laboratory to simulate interacting fault systems including crustal boundary conditions and various nonlinearities (e.g. from frictional contact, materials, geometry and thermal coupling). It has been successfully applied to large scale computing of the complex nonlinear phenomena in the non-continuum media involving the nonlinear frictional instability, multiple material properties and complex geometries on supercomputers, such as the South Australia (SA) interacting fault system, South California fault model and Sumatra subduction model. It has been also extended and to simulate the hot fractured rock (HFR) geothermal reservoir system in collaboration of Geodynamics Ltd which is constructing the first geothermal reservoir system in Australia and to model the tsunami generation induced by earthquakes. Both are supported by Australian Research Council.
-
Neuroprotection in a Novel Mouse Model of Multiple Sclerosis
Lidster, Katie; Jackson, Samuel J.; Ahmed, Zubair; Munro, Peter; Coffey, Pete; Giovannoni, Gavin; Baker, Mark D.; Baker, David
2013-01-01
Multiple sclerosis is an immune-mediated, demyelinating and neurodegenerative disease that currently lacks any neuroprotective treatments. Innovative neuroprotective trial designs are required to hasten the translational process of drug development. An ideal target to monitor the efficacy of strategies aimed at treating multiple sclerosis is the visual system, which is the most accessible part of the human central nervous system. A novel C57BL/6 mouse line was generated that expressed transgenes for a myelin oligodendrocyte glycoprotein-specific T cell receptor and a retinal ganglion cell restricted-Thy1 promoter-controlled cyan fluorescent protein. This model develops spontaneous or induced optic neuritis, in the absence of paralytic disease normally associated with most rodent autoimmune models of multiple sclerosis. Demyelination and neurodegeneration could be monitored longitudinally in the living animal using electrophysiology, visual sensitivity, confocal scanning laser ophthalmoscopy and optical coherence tomography all of which are relevant to human trials. This model offers many advantages, from a 3Rs, economic and scientific perspective, over classical experimental autoimmune encephalomyelitis models that are associated with substantial suffering of animals. Optic neuritis in this model led to inflammatory damage of axons in the optic nerve and subsequent loss of retinal ganglion cells in the retina. This was inhibited by the systemic administration of a sodium channel blocker (oxcarbazepine) or intraocular treatment with siRNA targeting caspase-2. These novel approaches have relevance to the future treatment of neurodegeneration of MS, which has so far evaded treatment. PMID:24223903
-
Multiplicity in public health supply systems: a learning agenda.
Bornbusch, Alan; Bates, James
2013-08-01
Supply chain integration-merging products for health programs into a single supply chain-tends to be the dominant model in health sector reform. However, multiplicity in a supply system may be justified as a risk management strategy that can better ensure product availability, advance specific health program objectives, and increase efficiency.
-
Inferring Binary and Trinary Stellar Populations in Photometric and Astrometric Surveys
NASA Astrophysics Data System (ADS)
Widmark, Axel; Leistedt, Boris; Hogg, David W.
2018-04-01
Multiple stellar systems are ubiquitous in the Milky Way but are often unresolved and seen as single objects in spectroscopic, photometric, and astrometric surveys. However, modeling them is essential for developing a full understanding of large surveys such as Gaia and connecting them to stellar and Galactic models. In this paper, we address this problem by jointly fitting the Gaia and Two Micron All Sky Survey photometric and astrometric data using a data-driven Bayesian hierarchical model that includes populations of binary and trinary systems. This allows us to classify observations into singles, binaries, and trinaries, in a robust and efficient manner, without resorting to external models. We are able to identify multiple systems and, in some cases, make strong predictions for the properties of their unresolved stars. We will be able to compare such predictions with Gaia Data Release 4, which will contain astrometric identification and analysis of binary systems.
-
NASA Astrophysics Data System (ADS)
Pyne, Moinak
This thesis aspires to model and control, the flow of power in a DC microgrid. Specifically, the energy sources are a photovoltaic system and the utility grid, a lead acid battery based energy storage system and twenty PEV charging stations as the loads. Theoretical principles of large scale state space modeling are applied to model the considerable number of power electronic converters needed for controlling voltage and current thresholds. The energy storage system is developed using principles of neural networks to facilitate a stable and uncomplicated model of the lead acid battery. Power flow control is structured as a hierarchical problem with multiple interactions between individual components of the microgrid. The implementation is done using fuzzy logic with scheduling the maximum use of available solar energy and compensating demand or excess power with the energy storage system, and minimizing utility grid use, while providing multiple speeds of charging the PEVs.
-
Clinical time series prediction: Toward a hierarchical dynamical system framework.
Liu, Zitao; Hauskrecht, Milos
2015-09-01
Developing machine learning and data mining algorithms for building temporal models of clinical time series is important for understanding of the patient condition, the dynamics of a disease, effect of various patient management interventions and clinical decision making. In this work, we propose and develop a novel hierarchical framework for modeling clinical time series data of varied length and with irregularly sampled observations. Our hierarchical dynamical system framework for modeling clinical time series combines advantages of the two temporal modeling approaches: the linear dynamical system and the Gaussian process. We model the irregularly sampled clinical time series by using multiple Gaussian process sequences in the lower level of our hierarchical framework and capture the transitions between Gaussian processes by utilizing the linear dynamical system. The experiments are conducted on the complete blood count (CBC) panel data of 1000 post-surgical cardiac patients during their hospitalization. Our framework is evaluated and compared to multiple baseline approaches in terms of the mean absolute prediction error and the absolute percentage error. We tested our framework by first learning the time series model from data for the patients in the training set, and then using it to predict future time series values for the patients in the test set. We show that our model outperforms multiple existing models in terms of its predictive accuracy. Our method achieved a 3.13% average prediction accuracy improvement on ten CBC lab time series when it was compared against the best performing baseline. A 5.25% average accuracy improvement was observed when only short-term predictions were considered. A new hierarchical dynamical system framework that lets us model irregularly sampled time series data is a promising new direction for modeling clinical time series and for improving their predictive performance. Copyright © 2014 Elsevier B.V. All rights reserved.
-
Modeling Students' Memory for Application in Adaptive Educational Systems
ERIC Educational Resources Information Center
Pelánek, Radek
2015-01-01
Human memory has been thoroughly studied and modeled in psychology, but mainly in laboratory setting under simplified conditions. For application in practical adaptive educational systems we need simple and robust models which can cope with aspects like varied prior knowledge or multiple-choice questions. We discuss and evaluate several models of…
-
Advancing Ecological Models to Compare Scale in Multi-Level Educational Change
ERIC Educational Resources Information Center
Woo, David James
2016-01-01
Education systems as units of analysis have been metaphorically likened to ecologies to model change. However, ecological models to date have been ineffective in modelling educational change that is multi-scale and occurs across multiple levels of an education system. Thus, this paper advances two innovative, ecological frameworks that improve on…
-
NASA Astrophysics Data System (ADS)
Crowther, Ashley R.; Singh, Rajendra; Zhang, Nong; Chapman, Chris
2007-10-01
Impulsive responses in geared systems with multiple clearances are studied when the mean torque excitation and system load change abruptly, with application to a vehicle driveline with an automatic transmission. First, torsional lumped-mass models of the planetary and differential gear sets are formulated using matrix elements. The model is then reduced to address tractable nonlinear problems while successfully retaining the main modes of interest. Second, numerical simulations for the nonlinear model are performed for transient conditions and a typical driving situation that induces an impulsive behaviour simulated. However, initial conditions and excitation and load profiles have to be carefully defined before the model can be numerically solved. It is shown that the impacts within the planetary or differential gears may occur under combinations of engine, braking and vehicle load transients. Our analysis shows that the shaping of the engine transient by the torque converter before reaching the clearance locations is more critical. Third, a free vibration experiment is developed for an analogous driveline with multiple clearances and three experiments that excite different response regimes have been carried out. Good correlations validate the proposed methodology.
-
A Space Weather Forecasting System with Multiple Satellites Based on a Self-Recognizing Network
Tokumitsu, Masahiro; Ishida, Yoshiteru
2014-01-01
This paper proposes a space weather forecasting system at geostationary orbit for high-energy electron flux (>2 MeV). The forecasting model involves multiple sensors on multiple satellites. The sensors interconnect and evaluate each other to predict future conditions at geostationary orbit. The proposed forecasting model is constructed using a dynamic relational network for sensor diagnosis and event monitoring. The sensors of the proposed model are located at different positions in space. The satellites for solar monitoring equip with monitoring devices for the interplanetary magnetic field and solar wind speed. The satellites orbit near the Earth monitoring high-energy electron flux. We investigate forecasting for typical two examples by comparing the performance of two models with different numbers of sensors. We demonstrate the prediction by the proposed model against coronal mass ejections and a coronal hole. This paper aims to investigate a possibility of space weather forecasting based on the satellite network with in-situ sensing. PMID:24803190
-
A space weather forecasting system with multiple satellites based on a self-recognizing network.
Tokumitsu, Masahiro; Ishida, Yoshiteru
2014-05-05
This paper proposes a space weather forecasting system at geostationary orbit for high-energy electron flux (>2 MeV). The forecasting model involves multiple sensors on multiple satellites. The sensors interconnect and evaluate each other to predict future conditions at geostationary orbit. The proposed forecasting model is constructed using a dynamic relational network for sensor diagnosis and event monitoring. The sensors of the proposed model are located at different positions in space. The satellites for solar monitoring equip with monitoring devices for the interplanetary magnetic field and solar wind speed. The satellites orbit near the Earth monitoring high-energy electron flux. We investigate forecasting for typical two examples by comparing the performance of two models with different numbers of sensors. We demonstrate the prediction by the proposed model against coronal mass ejections and a coronal hole. This paper aims to investigate a possibility of space weather forecasting based on the satellite network with in-situ sensing.
-
The Industrial Process System Assessment (IPSA) methodology is a multiple step allocation approach for connecting information from the production line level up to the facility level and vice versa using a multiscale model of process systems. The allocation procedure assigns inpu...
-
SPARK: A Framework for Multi-Scale Agent-Based Biomedical Modeling.
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.
-
Latent Class Models for Teacher Observation Data
ERIC Educational Resources Information Center
Halpin, Peter F.
2016-01-01
Recent research on multiple measures of teaching effectiveness has redefined the role of in-classroom observations in teacher evaluation systems. In particular, most states now mandate that teachers are observed on multiple occasions during the school year, and it is increasingly common that multiple raters are utilized across the different rating…
-
NASA Astrophysics Data System (ADS)
Voorhoeve, Robbert; van der Maas, Annemiek; Oomen, Tom
2018-05-01
Frequency response function (FRF) identification is often used as a basis for control systems design and as a starting point for subsequent parametric system identification. The aim of this paper is to develop a multiple-input multiple-output (MIMO) local parametric modeling approach for FRF identification of lightly damped mechanical systems with improved speed and accuracy. The proposed method is based on local rational models, which can efficiently handle the lightly-damped resonant dynamics. A key aspect herein is the freedom in the multivariable rational model parametrizations. Several choices for such multivariable rational model parametrizations are proposed and investigated. For systems with many inputs and outputs the required number of model parameters can rapidly increase, adversely affecting the performance of the local modeling approach. Therefore, low-order model structures are investigated. The structure of these low-order parametrizations leads to an undesired directionality in the identification problem. To address this, an iterative local rational modeling algorithm is proposed. As a special case recently developed SISO algorithms are recovered. The proposed approach is successfully demonstrated on simulations and on an active vibration isolation system benchmark, confirming good performance of the method using significantly less parameters compared with alternative approaches.
-
Multiscale modeling of mucosal immune responses
2015-01-01
Computational modeling techniques are playing increasingly important roles in advancing a systems-level mechanistic understanding of biological processes. Computer simulations guide and underpin experimental and clinical efforts. This study presents ENteric Immune Simulator (ENISI), a multiscale modeling tool for modeling the mucosal immune responses. ENISI's modeling environment can simulate in silico experiments from molecular signaling pathways to tissue level events such as tissue lesion formation. ENISI's architecture integrates multiple modeling technologies including ABM (agent-based modeling), ODE (ordinary differential equations), SDE (stochastic modeling equations), and PDE (partial differential equations). This paper focuses on the implementation and developmental challenges of ENISI. A multiscale model of mucosal immune responses during colonic inflammation, including CD4+ T cell differentiation and tissue level cell-cell interactions was developed to illustrate the capabilities, power and scope of ENISI MSM. Background Computational techniques are becoming increasingly powerful and modeling tools for biological systems are of greater needs. Biological systems are inherently multiscale, from molecules to tissues and from nano-seconds to a lifespan of several years or decades. ENISI MSM integrates multiple modeling technologies to understand immunological processes from signaling pathways within cells to lesion formation at the tissue level. This paper examines and summarizes the technical details of ENISI, from its initial version to its latest cutting-edge implementation. Implementation Object-oriented programming approach is adopted to develop a suite of tools based on ENISI. Multiple modeling technologies are integrated to visualize tissues, cells as well as proteins; furthermore, performance matching between the scales is addressed. Conclusion We used ENISI MSM for developing predictive multiscale models of the mucosal immune system during gut inflammation. Our modeling predictions dissect the mechanisms by which effector CD4+ T cell responses contribute to tissue damage in the gut mucosa following immune dysregulation. PMID:26329787
-
Multiscale modeling of mucosal immune responses.
Mei, Yongguo; Abedi, Vida; Carbo, Adria; Zhang, Xiaoying; Lu, Pinyi; Philipson, Casandra; Hontecillas, Raquel; Hoops, Stefan; Liles, Nathan; Bassaganya-Riera, Josep
2015-01-01
Computational techniques are becoming increasingly powerful and modeling tools for biological systems are of greater needs. Biological systems are inherently multiscale, from molecules to tissues and from nano-seconds to a lifespan of several years or decades. ENISI MSM integrates multiple modeling technologies to understand immunological processes from signaling pathways within cells to lesion formation at the tissue level. This paper examines and summarizes the technical details of ENISI, from its initial version to its latest cutting-edge implementation. Object-oriented programming approach is adopted to develop a suite of tools based on ENISI. Multiple modeling technologies are integrated to visualize tissues, cells as well as proteins; furthermore, performance matching between the scales is addressed. We used ENISI MSM for developing predictive multiscale models of the mucosal immune system during gut inflammation. Our modeling predictions dissect the mechanisms by which effector CD4+ T cell responses contribute to tissue damage in the gut mucosa following immune dysregulation.Computational modeling techniques are playing increasingly important roles in advancing a systems-level mechanistic understanding of biological processes. Computer simulations guide and underpin experimental and clinical efforts. This study presents ENteric Immune Simulator (ENISI), a multiscale modeling tool for modeling the mucosal immune responses. ENISI's modeling environment can simulate in silico experiments from molecular signaling pathways to tissue level events such as tissue lesion formation. ENISI's architecture integrates multiple modeling technologies including ABM (agent-based modeling), ODE (ordinary differential equations), SDE (stochastic modeling equations), and PDE (partial differential equations). This paper focuses on the implementation and developmental challenges of ENISI. A multiscale model of mucosal immune responses during colonic inflammation, including CD4+ T cell differentiation and tissue level cell-cell interactions was developed to illustrate the capabilities, power and scope of ENISI MSM.
-
User needs for propagation data
NASA Technical Reports Server (NTRS)
Sullivan, Thomas M.
1993-01-01
New and refined models of radio signal propagation phenomena are needed to support studies of evolving satellite services and systems. Taking an engineering perspective, applications for propagation measurements and models in the context of various types of analyses that are of ongoing interest are reviewed. Problems that were encountered in the signal propagation aspects of these analyses are reviewed, and potential solutions to these problems are discussed. The focus is on propagation measurements and models needed to support design and performance analyses of systems in the Mobile-Satellite Service (MSS) operating in the 1-3 GHz range. These systems may use geostationary or non-geostationary satellites and Frequency Division Multiple Access (FDMA), Time Division Multiple Access Digital (TDMA), or Code Division Multiple Access (CDMA) techniques. Many of the propagation issues raised in relation to MSS are also pertinent to other services such as broadcasting-satellite (sound) at 2310-2360 MHz. In particular, services involving mobile terminals or terminals with low gain antennas are of concern.
-
DOE Office of Scientific and Technical Information (OSTI.GOV)
Gering, Kevin L.
A method, system, and computer-readable medium are described for characterizing performance loss of an object undergoing an arbitrary aging condition. Baseline aging data may be collected from the object for at least one known baseline aging condition over time, determining baseline multiple sigmoid model parameters from the baseline data, and performance loss of the object may be determined over time through multiple sigmoid model parameters associated with the object undergoing the arbitrary aging condition using a differential deviation-from-baseline approach from the baseline multiple sigmoid model parameters. The system may include an object, monitoring hardware configured to sample performance characteristics ofmore » the object, and a processor coupled to the monitoring hardware. The processor is configured to determine performance loss for the arbitrary aging condition from a comparison of the performance characteristics of the object deviating from baseline performance characteristics associated with a baseline aging condition.« less
-
Electromagnetic fields in small systems from a multiphase transport model
NASA Astrophysics Data System (ADS)
Zhao, Xin-Li; Ma, Yu-Gang; Ma, Guo-Liang
2018-02-01
We calculate the electromagnetic fields generated in small systems by using a multiphase transport (AMPT) model. Compared to A +A collisions, we find that the absolute electric and magnetic fields are not small in p +Au and d +Au collisions at energies available at the BNL Relativistic Heavy Ion Collider and in p +Pb collisions at energies available at the CERN Large Hadron Collider. We study the centrality dependencies and the spatial distributions of electromagnetic fields. We further investigate the azimuthal fluctuations of the magnetic field and its correlation with the fluctuating geometry using event-by-event simulations. We find that the azimuthal correlation 〈" close="〉cos(ϕα+ϕβ-2 ΨRP)〉">cos2 (ΨB-Ψ2) between the magnetic field direction and the second-harmonic participant plane is almost zero in small systems with high multiplicities, but not in those with low multiplicities. This indicates that the charge azimuthal correlation is not a valid probe to study the chiral magnetic effect (CME) in small systems with high multiplicities. However, we suggest searching for possible CME effects in small systems with low multiplicities.
-
Stochastic modeling of a lava-flow aquifer system
Cronkite-Ratcliff, Collin; Phelps, Geoffrey A.
2014-01-01
This report describes preliminary three-dimensional geostatistical modeling of a lava-flow aquifer system using a multiple-point geostatistical model. The purpose of this study is to provide a proof-of-concept for this modeling approach. An example of the method is demonstrated using a subset of borehole geologic data and aquifer test data from a portion of the Calico Hills Formation, a lava-flow aquifer system that partially underlies Pahute Mesa, Nevada. Groundwater movement in this aquifer system is assumed to be controlled by the spatial distribution of two geologic units—rhyolite lava flows and zeolitized tuffs. The configuration of subsurface lava flows and tuffs is largely unknown because of limited data. The spatial configuration of the lava flows and tuffs is modeled by using a multiple-point geostatistical simulation algorithm that generates a large number of alternative realizations, each honoring the available geologic data and drawn from a geologic conceptual model of the lava-flow aquifer system as represented by a training image. In order to demonstrate how results from the geostatistical model could be analyzed in terms of available hydrologic data, a numerical simulation of part of an aquifer test was applied to the realizations of the geostatistical model.
-
Fuzzy adaptive interacting multiple model nonlinear filter for integrated navigation sensor fusion.
Tseng, Chien-Hao; Chang, Chih-Wen; Jwo, Dah-Jing
2011-01-01
In this paper, the application of the fuzzy interacting multiple model unscented Kalman filter (FUZZY-IMMUKF) approach to integrated navigation processing for the maneuvering vehicle is presented. The unscented Kalman filter (UKF) employs a set of sigma points through deterministic sampling, such that a linearization process is not necessary, and therefore the errors caused by linearization as in the traditional extended Kalman filter (EKF) can be avoided. The nonlinear filters naturally suffer, to some extent, the same problem as the EKF for which the uncertainty of the process noise and measurement noise will degrade the performance. As a structural adaptation (model switching) mechanism, the interacting multiple model (IMM), which describes a set of switching models, can be utilized for determining the adequate value of process noise covariance. The fuzzy logic adaptive system (FLAS) is employed to determine the lower and upper bounds of the system noise through the fuzzy inference system (FIS). The resulting sensor fusion strategy can efficiently deal with the nonlinear problem for the vehicle navigation. The proposed FUZZY-IMMUKF algorithm shows remarkable improvement in the navigation estimation accuracy as compared to the relatively conventional approaches such as the UKF and IMMUKF.
-
2013-06-01
Miridakis and D. D. Vergados, “A survey on the successive interference cancellation performance for single-antenna and multiple-antenna OFDM ...in this thesis. Follow on work that focuses on SIC for multi-carrier and MIMO systems would be most beneficial. Other estimation methods exist that...antenna and multiple-antenna OFDM systems,” IEEE Comms. Surveys & Tutorials, vol.15, no. 1, pp. 312–335, 2013. [2] J. G. Andrews, “Interference
-
Satellite switched FDMA advanced communication technology satellite program
NASA Technical Reports Server (NTRS)
Atwood, S.; Higton, G. H.; Wood, K.; Kline, A.; Furiga, A.; Rausch, M.; Jan, Y.
1982-01-01
The satellite switched frequency division multiple access system provided a detailed system architecture that supports a point to point communication system for long haul voice, video and data traffic between small Earth terminals at Ka band frequencies at 30/20 GHz. A detailed system design is presented for the space segment, small terminal/trunking segment at network control segment for domestic traffic model A or B, each totaling 3.8 Gb/s of small terminal traffic and 6.2 Gb/s trunk traffic. The small terminal traffic (3.8 Gb/s) is emphasized, for the satellite router portion of the system design, which is a composite of thousands of Earth stations with digital traffic ranging from a single 32 Kb/s CVSD voice channel to thousands of channels containing voice, video and data with a data rate as high as 33 Mb/s. The system design concept presented, effectively optimizes a unique frequency and channelization plan for both traffic models A and B with minimum reorganization of the satellite payload transponder subsystem hardware design. The unique zoning concept allows multiple beam antennas while maximizing multiple carrier frequency reuse. Detailed hardware design estimates for an FDMA router (part of the satellite transponder subsystem) indicate a weight and dc power budget of 353 lbs, 195 watts for traffic model A and 498 lbs, 244 watts for traffic model B.
-
Working Memory, Age, Crew Downsizing, System Design and Training
2000-08-01
Radvansky and Zacks, 1997). As authors have noted perceived demand. Accurate "Situation Models " (Johnson- when attempting to make sense of a... models of cognitive function and workload (cf. Baddeley bodies of information to be processed or multiple results and Gathercole, 1993). The ability to...major bottleneck in human performance. Some models of multiple traces from different headings and the human information processing (Pashler, 1998) place
-
NASA Technical Reports Server (NTRS)
Chen, Ping-Chih (Inventor)
2013-01-01
This invention is a ground flutter testing system without a wind tunnel, called Dry Wind Tunnel (DWT) System. The DWT system consists of a Ground Vibration Test (GVT) hardware system, a multiple input multiple output (MIMO) force controller software, and a real-time unsteady aerodynamic force generation software, that is developed from an aerodynamic reduced order model (ROM). The ground flutter test using the DWT System operates on a real structural model, therefore no scaled-down structural model, which is required by the conventional wind tunnel flutter test, is involved. Furthermore, the impact of the structural nonlinearities on the aeroelastic stability can be included automatically. Moreover, the aeroservoelastic characteristics of the aircraft can be easily measured by simply including the flight control system in-the-loop. In addition, the unsteady aerodynamics generated computationally is interference-free from the wind tunnel walls. Finally, the DWT System can be conveniently and inexpensively carried out as a post GVT test with the same hardware, only with some possible rearrangement of the shakers and the inclusion of additional sensors.
-
Analysis of dynamic behavior of multiple-stage planetary gear train used in wind driven generator.
Wang, Jungang; Wang, Yong; Huo, Zhipu
2014-01-01
A dynamic model of multiple-stage planetary gear train composed of a two-stage planetary gear train and a one-stage parallel axis gear is proposed to be used in wind driven generator to analyze the influence of revolution speed and mesh error on dynamic load sharing characteristic based on the lumped parameter theory. Dynamic equation of the model is solved using numerical method to analyze the uniform load distribution of the system. It is shown that the load sharing property of the system is significantly affected by mesh error and rotational speed; load sharing coefficient and change rate of internal and external meshing of the system are of obvious difference from each other. The study provides useful theoretical guideline for the design of the multiple-stage planetary gear train of wind driven generator.
-
Analysis of Dynamic Behavior of Multiple-Stage Planetary Gear Train Used in Wind Driven Generator
Wang, Jungang; Wang, Yong; Huo, Zhipu
2014-01-01
A dynamic model of multiple-stage planetary gear train composed of a two-stage planetary gear train and a one-stage parallel axis gear is proposed to be used in wind driven generator to analyze the influence of revolution speed and mesh error on dynamic load sharing characteristic based on the lumped parameter theory. Dynamic equation of the model is solved using numerical method to analyze the uniform load distribution of the system. It is shown that the load sharing property of the system is significantly affected by mesh error and rotational speed; load sharing coefficient and change rate of internal and external meshing of the system are of obvious difference from each other. The study provides useful theoretical guideline for the design of the multiple-stage planetary gear train of wind driven generator. PMID:24511295
-
Statechart Analysis with Symbolic PathFinder
NASA Technical Reports Server (NTRS)
Pasareanu, Corina S.
2012-01-01
We report here on our on-going work that addresses the automated analysis and test case generation for software systems modeled using multiple Statechart formalisms. The work is motivated by large programs such as NASA Exploration, that involve multiple systems that interact via safety-critical protocols and are designed with different Statechart variants. To verify these safety-critical systems, we have developed Polyglot, a framework for modeling and analysis of model-based software written using different Statechart formalisms. Polyglot uses a common intermediate representation with customizable Statechart semantics and leverages the analysis and test generation capabilities of the Symbolic PathFinder tool. Polyglot is used as follows: First, the structure of the Statechart model (expressed in Matlab Stateflow or Rational Rhapsody) is translated into a common intermediate representation (IR). The IR is then translated into Java code that represents the structure of the model. The semantics are provided as "pluggable" modules.
-
Nonlinear engine model for idle speed control
DOE Office of Scientific and Technical Information (OSTI.GOV)
Livshiz, M.; Sanvido, D.J.; Stiles, S.D.
1994-12-31
This paper describes a nonlinear model of an engine used for the design of idle speed control and prediction in a broad range of idle speeds and operational conditions. Idle speed control systems make use of both spark advance and the idle air actuator to control engine speed for improved response relative to variations in the target idle speed due to load disturbances. The control system at idle can be presented by a multiple input multiple output (MIMO) nonlinear model. Information of nonlinearities helps to improve performance of the system over the whole range of engine speeds. A proposed simplemore » nonlinear model of the engine at idle was applied for design of optimal controllers and predictors for improved steady state, load rejection and transition from and to idle. This paper describes vehicle results of engine speed prediction based on the described model.« less
-
NASA Astrophysics Data System (ADS)
Wagner, Jenny; Liesenborgs, Jori; Tessore, Nicolas
2018-04-01
Context. Local gravitational lensing properties, such as convergence and shear, determined at the positions of multiply imaged background objects, yield valuable information on the smaller-scale lensing matter distribution in the central part of galaxy clusters. Highly distorted multiple images with resolved brightness features like the ones observed in CL0024 allow us to study these local lensing properties and to tighten the constraints on the properties of dark matter on sub-cluster scale. Aim. We investigate to what precision local magnification ratios, J, ratios of convergences, f, and reduced shears, g = (g1, g2), can be determined independently of a lens model for the five resolved multiple images of the source at zs = 1.675 in CL0024. We also determine if a comparison to the respective results obtained by the parametric modelling tool Lenstool and by the non-parametric modelling tool Grale can detect biases in the models. For these lens models, we analyse the influence of the number and location of the constraints from multiple images on the lens properties at the positions of the five multiple images of the source at zs = 1.675. Methods: Our model-independent approach uses a linear mapping between the five resolved multiple images to determine the magnification ratios, ratios of convergences, and reduced shears at their positions. With constraints from up to six multiple image systems, we generate Lenstool and Grale models using the same image positions, cosmological parameters, and number of generated convergence and shear maps to determine the local values of J, f, and g at the same positions across all methods. Results: All approaches show strong agreement on the local values of J, f, and g. We find that Lenstool obtains the tightest confidence bounds even for convergences around one using constraints from six multiple-image systems, while the best Grale model is generated only using constraints from all multiple images with resolved brightness features and adding limited small-scale mass corrections. Yet, confidence bounds as large as the values themselves can occur for convergences close to one in all approaches. Conclusions: Our results agree with previous findings, support the light-traces-mass assumption, and the merger hypothesis for CL0024. Comparing the different approaches can detect model biases. The model-independent approach determines the local lens properties to a comparable precision in less than one second.
-
Systems of Selves: the Construction of Meaning in Multiple Personality Disorder
NASA Astrophysics Data System (ADS)
Hughes, Dureen Jean
Current models for understanding both Multiple Personality Disorder and human mentation in general are both linear in nature and self-perpetuating insofar as most research in this area has been informed and shaped by extant psychological concepts, paradigms and methods. The research for this dissertation made use of anthropological concepts and methods in an attempt to gain a richer understanding of both multiple personality and fundamental universal processes of the mind. Intensive fieldwork using in-depth, open-ended interviewing techniques was conducted with people diagnosed with Multiple Personality Disorder with the purpose of mapping their personality systems in order to discover the nature of the relationships between the various alternate personalities and subsystems comprising the overall personality systems. These data were then analyzed in terms of dynamical systems theory ("Chaos Theory") as a way of understanding various phenomena of multiple personality disorder as well as the overall structure of each system. It was found that the application of the formal characteristics of nonlinear models and equations to multiple personality systems provided a number of new perspectives on mental phenomena. The underlying organizational structure of multiple personality systems can be understood as a phenomenon of spontaneous self-organization in far-from -equilibrium states which characterizes dissipative structures. Chaos Theory allows the perspective that the nature of the process of the self and the nature of relationship are one and the same, and that both can be conceived as ideas in struggle at a fractal boundary. Further, such application makes it possible to postulate an iterative process which would have as one of its consequences the formation of a processural self who is conscious of self as separate self. Finally, given that the iterative application of a few simple rules (or instructions) can result in complex systems, an attempt was made to discern what the rules pertaining to human mentation might be.
-
Multiple Model Adaptive Attitude Control of LEO Satellite with Angular Velocity Constraints
NASA Astrophysics Data System (ADS)
Shahrooei, Abolfazl; Kazemi, Mohammad Hosein
2018-04-01
In this paper, the multiple model adaptive control is utilized to improve the transient response of attitude control system for a rigid spacecraft. An adaptive output feedback control law is proposed for attitude control under angular velocity constraints and its almost global asymptotic stability is proved. The multiple model adaptive control approach is employed to counteract large uncertainty in parameter space of the inertia matrix. The nonlinear dynamics of a low earth orbit satellite is simulated and the proposed control algorithm is implemented. The reported results show the effectiveness of the suggested scheme.
-
Development of an integrated semi-automated system for in vitro pharmacodynamic modelling.
Wang, Liangsu; Wismer, Michael K; Racine, Fred; Conway, Donald; Giacobbe, Robert A; Berejnaia, Olga; Kath, Gary S
2008-11-01
The aim of this study was to develop an integrated system for in vitro pharmacodynamic modelling of antimicrobials with greater flexibility, easier control and better accuracy than existing in vitro models. Custom-made bottle caps, fittings, valve controllers and a modified bench-top shaking incubator were used. A temperature-controlled automated sample collector was built. Computer software was developed to manage experiments and to control the entire system including solenoid pinch valves, peristaltic pumps and the sample collector. The system was validated by pharmacokinetic simulations of linezolid 600 mg infusion. The antibacterial effect of linezolid against multiple Staphylococcus aureus strains was also studied in this system. An integrated semi-automated bench-top system was built and validated. The temperature-controlled automated sample collector allowed unattended collection and temporary storage of samples. The system software reduced the labour necessary for many tasks and also improved the timing accuracy for performing simultaneous actions in multiple parallel experiments. The system was able to simulate human pharmacokinetics of linezolid 600 mg intravenous infusion accurately. A pharmacodynamic study of linezolid against multiple S. aureus strains with a range of MICs showed that the required 24 h free drug AUC/MIC ratio was approximately 30 in order to keep the organism counts at the same level as their initial inoculum and was about > or = 68 in order to achieve > 2 log(10) cfu/mL reduction in the in vitro model. The integrated semi-automated bench-top system provided the ability to overcome many of the drawbacks of existing in vitro models. It can be used for various simple or complicated pharmacokinetic/pharmacodynamic studies efficiently and conveniently.
-
Decoupling suspension controller based on magnetic flux feedback.
Zhang, Wenqing; Li, Jie; Zhang, Kun; Cui, Peng
2013-01-01
The suspension module control system model has been established based on MIMO (multiple input and multiple output) state feedback linearization. We have completed decoupling between double suspension points, and the new decoupling method has been applied to CMS04 magnetic suspension vehicle in national mid-low-speed maglev experiment field of Tangshan city in China. Double suspension system model is very accurate for investigating stability property of maglev control system. When magnetic flux signal is taken back to the suspension control system, the suspension module's antijamming capacity for resisting suspension load variety has been proved. Also, the external force interference has been enhanced. As a result, the robustness and stability properties of double-electromagnet suspension control system have been enhanced.
-
Decoupling Suspension Controller Based on Magnetic Flux Feedback
Zhang, Wenqing; Li, Jie; Zhang, Kun; Cui, Peng
2013-01-01
The suspension module control system model has been established based on MIMO (multiple input and multiple output) state feedback linearization. We have completed decoupling between double suspension points, and the new decoupling method has been applied to CMS04 magnetic suspension vehicle in national mid-low-speed maglev experiment field of Tangshan city in China. Double suspension system model is very accurate for investigating stability property of maglev control system. When magnetic flux signal is taken back to the suspension control system, the suspension module's antijamming capacity for resisting suspension load variety has been proved. Also, the external force interference has been enhanced. As a result, the robustness and stability properties of double-electromagnet suspension control system have been enhanced. PMID:23844415
-
Akimoto, Yuki; Yugi, Katsuyuki; Uda, Shinsuke; Kudo, Takamasa; Komori, Yasunori; Kubota, Hiroyuki; Kuroda, Shinya
2013-01-01
Cells use common signaling molecules for the selective control of downstream gene expression and cell-fate decisions. The relationship between signaling molecules and downstream gene expression and cellular phenotypes is a multiple-input and multiple-output (MIMO) system and is difficult to understand due to its complexity. For example, it has been reported that, in PC12 cells, different types of growth factors activate MAP kinases (MAPKs) including ERK, JNK, and p38, and CREB, for selective protein expression of immediate early genes (IEGs) such as c-FOS, c-JUN, EGR1, JUNB, and FOSB, leading to cell differentiation, proliferation and cell death; however, how multiple-inputs such as MAPKs and CREB regulate multiple-outputs such as expression of the IEGs and cellular phenotypes remains unclear. To address this issue, we employed a statistical method called partial least squares (PLS) regression, which involves a reduction of the dimensionality of the inputs and outputs into latent variables and a linear regression between these latent variables. We measured 1,200 data points for MAPKs and CREB as the inputs and 1,900 data points for IEGs and cellular phenotypes as the outputs, and we constructed the PLS model from these data. The PLS model highlighted the complexity of the MIMO system and growth factor-specific input-output relationships of cell-fate decisions in PC12 cells. Furthermore, to reduce the complexity, we applied a backward elimination method to the PLS regression, in which 60 input variables were reduced to 5 variables, including the phosphorylation of ERK at 10 min, CREB at 5 min and 60 min, AKT at 5 min and JNK at 30 min. The simple PLS model with only 5 input variables demonstrated a predictive ability comparable to that of the full PLS model. The 5 input variables effectively extracted the growth factor-specific simple relationships within the MIMO system in cell-fate decisions in PC12 cells.
-
A Bayesian model averaging method for improving SMT phrase table
NASA Astrophysics Data System (ADS)
Duan, Nan
2013-03-01
Previous methods on improving translation quality by employing multiple SMT models usually carry out as a second-pass decision procedure on hypotheses from multiple systems using extra features instead of using features in existing models in more depth. In this paper, we propose translation model generalization (TMG), an approach that updates probability feature values for the translation model being used based on the model itself and a set of auxiliary models, aiming to alleviate the over-estimation problem and enhance translation quality in the first-pass decoding phase. We validate our approach for translation models based on auxiliary models built by two different ways. We also introduce novel probability variance features into the log-linear models for further improvements. We conclude our approach can be developed independently and integrated into current SMT pipeline directly. We demonstrate BLEU improvements on the NIST Chinese-to-English MT tasks for single-system decodings.
-
Models of Recognition, Repetition Priming, and Fluency : Exploring a New Framework
ERIC Educational Resources Information Center
Berry, Christopher J.; Shanks, David R.; Speekenbrink, Maarten; Henson, Richard N. A.
2012-01-01
We present a new modeling framework for recognition memory and repetition priming based on signal detection theory. We use this framework to specify and test the predictions of 4 models: (a) a single-system (SS) model, in which one continuous memory signal drives recognition and priming; (b) a multiple-systems-1 (MS1) model, in which completely…
-
Middle Rio Grande Cooperative Water Model
DOE Office of Scientific and Technical Information (OSTI.GOV)
Tidwell, Vince; Passell, Howard
2005-11-01
This is computer simulation model built in a commercial modeling product Called Studio Expert, developed by Powersim, Inc. The simulation model is built in a system dynamics environment, allowing the simulation of the interaction among multiple systems that are all changing over time. The model focuses on hydrology, ecology, demography, and economy of the Middle Rio Grande, with Water as the unifying feature.
-
Systems thinking: what business modeling can do for public health.
Williams, Warren; Lyalin, David; Wingo, Phyllis A
2005-01-01
Today's public health programs are complex business systems with multiple levels of collaborating federal, state, and local entities. The use of proven systems engineering modeling techniques to analyze, align, and streamline public health operations is in the beginning stages. The authors review the initial business modeling efforts in immunization and cancer registries and present a case to broadly apply business modeling approaches to analyze and improve public health processes.
-
Ocampo, Cesar
2004-05-01
The modeling, design, and optimization of finite burn maneuvers for a generalized trajectory design and optimization system is presented. A generalized trajectory design and optimization system is a system that uses a single unified framework that facilitates the modeling and optimization of complex spacecraft trajectories that may operate in complex gravitational force fields, use multiple propulsion systems, and involve multiple spacecraft. The modeling and optimization issues associated with the use of controlled engine burn maneuvers of finite thrust magnitude and duration are presented in the context of designing and optimizing a wide class of finite thrust trajectories. Optimal control theory is used examine the optimization of these maneuvers in arbitrary force fields that are generally position, velocity, mass, and are time dependent. The associated numerical methods used to obtain these solutions involve either, the solution to a system of nonlinear equations, an explicit parameter optimization method, or a hybrid parameter optimization that combines certain aspects of both. The theoretical and numerical methods presented here have been implemented in copernicus, a prototype trajectory design and optimization system under development at the University of Texas at Austin.
-
ISA-97 Compliant Architecture Testbed (ICAT) Projectry Organizations
1992-03-30
by the System Integracion Directorate of the USAISEC, August 29, 1992. The report discusses the refinement of the ISA-97 Compliant Architecture Model...browser and iconic representations of system objects and resources. When the user is interacting with an application which has multiple compo- nents, it is...computer communications, it is not uncommon for large information systems to be shared by users on multiple machines. The trend towards the desktop
-
Chylek, Lily A.; Harris, Leonard A.; Tung, Chang-Shung; Faeder, James R.; Lopez, Carlos F.
2013-01-01
Rule-based modeling was developed to address the limitations of traditional approaches for modeling chemical kinetics in cell signaling systems. These systems consist of multiple interacting biomolecules (e.g., proteins), which themselves consist of multiple parts (e.g., domains, linear motifs, and sites of phosphorylation). Consequently, biomolecules that mediate information processing generally have the potential to interact in multiple ways, with the number of possible complexes and post-translational modification states tending to grow exponentially with the number of binary interactions considered. As a result, only large reaction networks capture all possible consequences of the molecular interactions that occur in a cell signaling system, which is problematic because traditional modeling approaches for chemical kinetics (e.g., ordinary differential equations) require explicit network specification. This problem is circumvented through representation of interactions in terms of local rules. With this approach, network specification is implicit and model specification is concise. Concise representation results in a coarse graining of chemical kinetics, which is introduced because all reactions implied by a rule inherit the rate law associated with that rule. Coarse graining can be appropriate if interactions are modular, and the coarseness of a model can be adjusted as needed. Rules can be specified using specialized model-specification languages, and recently developed tools designed for specification of rule-based models allow one to leverage powerful software engineering capabilities. A rule-based model comprises a set of rules, which can be processed by general-purpose simulation and analysis tools to achieve different objectives (e.g., to perform either a deterministic or stochastic simulation). PMID:24123887
-
Simic, Vladimir
2016-06-01
As the number of end-of-life vehicles (ELVs) is estimated to increase to 79.3 million units per year by 2020 (e.g., 40 million units were generated in 2010), there is strong motivation to effectively manage this fast-growing waste flow. Intensive work on management of ELVs is necessary in order to more successfully tackle this important environmental challenge. This paper proposes an interval-parameter chance-constraint programming model for end-of-life vehicles management under rigorous environmental regulations. The proposed model can incorporate various uncertainty information in the modeling process. The complex relationships between different ELV management sub-systems are successfully addressed. Particularly, the formulated model can help identify optimal patterns of procurement from multiple sources of ELV supply, production and inventory planning in multiple vehicle recycling factories, and allocation of sorted material flows to multiple final destinations under rigorous environmental regulations. A case study is conducted in order to demonstrate the potentials and applicability of the proposed model. Various constraint-violation probability levels are examined in detail. Influences of parameter uncertainty on model solutions are thoroughly investigated. Useful solutions for the management of ELVs are obtained under different probabilities of violating system constraints. The formulated model is able to tackle a hard, uncertainty existing ELV management problem. The presented model has advantages in providing bases for determining long-term ELV management plans with desired compromises between economic efficiency of vehicle recycling system and system-reliability considerations. The results are helpful for supporting generation and improvement of ELV management plans. Copyright © 2016 Elsevier Ltd. All rights reserved.
-
Rong, Qiangqiang; Cai, Yanpeng; Chen, Bing; Yue, Wencong; Yin, Xin'an; Tan, Qian
2017-02-15
In this research, an export coefficient based dual inexact two-stage stochastic credibility constrained programming (ECDITSCCP) model was developed through integrating an improved export coefficient model (ECM), interval linear programming (ILP), fuzzy credibility constrained programming (FCCP) and a fuzzy expected value equation within a general two stage programming (TSP) framework. The proposed ECDITSCCP model can effectively address multiple uncertainties expressed as random variables, fuzzy numbers, pure and dual intervals. Also, the model can provide a direct linkage between pre-regulated management policies and the associated economic implications. Moreover, the solutions under multiple credibility levels can be obtained for providing potential decision alternatives for decision makers. The proposed model was then applied to identify optimal land use structures for agricultural NPS pollution mitigation in a representative upstream subcatchment of the Miyun Reservoir watershed in north China. Optimal solutions of the model were successfully obtained, indicating desired land use patterns and nutrient discharge schemes to get a maximum agricultural system benefits under a limited discharge permit. Also, numerous results under multiple credibility levels could provide policy makers with several options, which could help get an appropriate balance between system benefits and pollution mitigation. The developed ECDITSCCP model can be effectively applied to addressing the uncertain information in agricultural systems and shows great applicability to the land use adjustment for agricultural NPS pollution mitigation. Copyright © 2016 Elsevier B.V. All rights reserved.
-
Gruetzner, Frank; Ashley, Terry; Rowell, David M; Marshall Graves, Jennifer A
2006-04-01
The duck-billed platypus is an extraordinary mammal. Its chromosome complement is no less extraordinary, for it includes a system in which ten sex chromosomes form an extensive meiotic chain in males. Such meiotic multiples are unprecedented in vertebrates but occur sporadically in plant and invertebrate species. In this paper, we review the evolution and formation of meiotic multiples in plants and invertebrates to try to gain insights into the origin of the platypus meiotic multiple. We describe the meiotic hurdles that translocated mammalian chromosomes face, which make longer chains disadvantageous in mammals, and we discuss how sex chromosomes and dosage compensation might have affected the evolution of sex-linked meiotic multiples. We conclude that the evolutionary conservation of the chain in monotremes, the structural properties of the translocated chromosomes and the highly accurate segregation at meiosis make the platypus system remarkably different from meiotic multiples in other species. We discuss alternative evolutionary models, which fall broadly into two categories: either the chain is the result of a sequence of translocation events from an ancestral pair of sex chromosomes (Model I) or the entire chain came into being at once by hybridization of two populations with different chromosomal rearrangements sharing monobrachial homology (Model II).
-
Kerckhoffs, Roy C. P.; Neal, Maxwell L.; Gu, Quan; Bassingthwaighte, James B.; Omens, Jeff H.; McCulloch, Andrew D.
2010-01-01
In this study we present a novel, robust method to couple finite element (FE) models of cardiac mechanics to systems models of the circulation (CIRC), independent of cardiac phase. For each time step through a cardiac cycle, left and right ventricular pressures were calculated using ventricular compliances from the FE and CIRC models. These pressures served as boundary conditions in the FE and CIRC models. In succeeding steps, pressures were updated to minimize cavity volume error (FE minus CIRC volume) using Newton iterations. Coupling was achieved when a predefined criterion for the volume error was satisfied. Initial conditions for the multi-scale model were obtained by replacing the FE model with a varying elastance model, which takes into account direct ventricular interactions. Applying the coupling, a novel multi-scale model of the canine cardiovascular system was developed. Global hemodynamics and regional mechanics were calculated for multiple beats in two separate simulations with a left ventricular ischemic region and pulmonary artery constriction, respectively. After the interventions, global hemodynamics changed due to direct and indirect ventricular interactions, in agreement with previously published experimental results. The coupling method allows for simulations of multiple cardiac cycles for normal and pathophysiology, encompassing levels from cell to system. PMID:17111210
-
Pattern-oriented modelling: a ‘multi-scope’ for predictive systems ecology
Grimm, Volker; Railsback, Steven F.
2012-01-01
Modern ecology recognizes that modelling systems across scales and at multiple levels—especially to link population and ecosystem dynamics to individual adaptive behaviour—is essential for making the science predictive. ‘Pattern-oriented modelling’ (POM) is a strategy for doing just this. POM is the multi-criteria design, selection and calibration of models of complex systems. POM starts with identifying a set of patterns observed at multiple scales and levels that characterize a system with respect to the particular problem being modelled; a model from which the patterns emerge should contain the right mechanisms to address the problem. These patterns are then used to (i) determine what scales, entities, variables and processes the model needs, (ii) test and select submodels to represent key low-level processes such as adaptive behaviour, and (iii) find useful parameter values during calibration. Patterns are already often used in these ways, but a mini-review of applications of POM confirms that making the selection and use of patterns more explicit and rigorous can facilitate the development of models with the right level of complexity to understand ecological systems and predict their response to novel conditions. PMID:22144392
-
Peppas, Kostas P; Lazarakis, Fotis; Alexandridis, Antonis; Dangakis, Kostas
2012-08-01
In this Letter we investigate the error performance of multiple-input multiple-output free-space optical communication systems employing intensity modulation/direct detection and operating over strong atmospheric turbulence channels. Atmospheric-induced strong turbulence fading is modeled using the negative exponential distribution. For the considered system, an approximate yet accurate analytical expression for the average bit error probability is derived and an efficient method for its numerical evaluation is proposed. Numerically evaluated and computer simulation results are further provided to demonstrate the validity of the proposed mathematical analysis.
-
Advanced Collaborative Environments Supporting Systems Integration and Design
2003-03-01
concurrently view a virtual system or product model while maintaining natural, human communication . These virtual systems operate within a computer-generated...These environments allow multiple individuals to concurrently view a virtual system or product model while simultaneously maintaining natural, human ... communication . As a result, TARDEC researchers and system developers are using this advanced high-end visualization technology to develop future
-
Hybrid approaches for multiple-species stochastic reaction–diffusion models
DOE Office of Scientific and Technical Information (OSTI.GOV)
Spill, Fabian, E-mail: fspill@bu.edu; Department of Mechanical Engineering, Massachusetts Institute of Technology, 77 Massachusetts Avenue, Cambridge, MA 02139; Guerrero, Pilar
2015-10-15
Reaction–diffusion models are used to describe systems in fields as diverse as physics, chemistry, ecology and biology. The fundamental quantities in such models are individual entities such as atoms and molecules, bacteria, cells or animals, which move and/or react in a stochastic manner. If the number of entities is large, accounting for each individual is inefficient, and often partial differential equation (PDE) models are used in which the stochastic behaviour of individuals is replaced by a description of the averaged, or mean behaviour of the system. In some situations the number of individuals is large in certain regions and smallmore » in others. In such cases, a stochastic model may be inefficient in one region, and a PDE model inaccurate in another. To overcome this problem, we develop a scheme which couples a stochastic reaction–diffusion system in one part of the domain with its mean field analogue, i.e. a discretised PDE model, in the other part of the domain. The interface in between the two domains occupies exactly one lattice site and is chosen such that the mean field description is still accurate there. In this way errors due to the flux between the domains are small. Our scheme can account for multiple dynamic interfaces separating multiple stochastic and deterministic domains, and the coupling between the domains conserves the total number of particles. The method preserves stochastic features such as extinction not observable in the mean field description, and is significantly faster to simulate on a computer than the pure stochastic model. - Highlights: • A novel hybrid stochastic/deterministic reaction–diffusion simulation method is given. • Can massively speed up stochastic simulations while preserving stochastic effects. • Can handle multiple reacting species. • Can handle moving boundaries.« less
-
Zhu, Q.; Riley, W. J.; Tang, J.; ...
2016-01-18
Soil is a complex system where biotic (e.g., plant roots, micro-organisms) and abiotic (e.g., mineral surfaces) consumers compete for resources necessary for life (e.g., nitrogen, phosphorus). This competition is ecologically significant, since it regulates the dynamics of soil nutrients and controls aboveground plant productivity. Here we develop, calibrate and test a nutrient competition model that accounts for multiple soil nutrients interacting with multiple biotic and abiotic consumers. As applied here for tropical forests, the Nutrient COMpetition model (N-COM) includes three primary soil nutrients (NH 4 +, NO 3 − and PO x; representing the sum of PO 4 3−, HPOmore » 4 2− and H 2PO 4 −) and five potential competitors (plant roots, decomposing microbes, nitrifiers, denitrifiers and mineral surfaces). The competition is formulated with a quasi-steady-state chemical equilibrium approximation to account for substrate (multiple substrates share one consumer) and consumer (multiple consumers compete for one substrate) effects. N-COM successfully reproduced observed soil heterotrophic respiration, N 2O emissions, free phosphorus, sorbed phosphorus and NH 4 + pools at a tropical forest site (Tapajos). The overall model uncertainty was moderately well constrained. Our sensitivity analysis revealed that soil nutrient competition was primarily regulated by consumer–substrate affinity rather than environmental factors such as soil temperature or soil moisture. Our results also imply that under strong nutrient limitation, relative competitiveness depends strongly on the competitor functional traits (affinity and nutrient carrier enzyme abundance). We then applied the N-COM model to analyze field nitrogen and phosphorus perturbation experiments in two tropical forest sites (in Hawaii and Puerto Rico) not used in model development or calibration. Under soil inorganic nitrogen and phosphorus elevated conditions, the model accurately replicated the experimentally observed competition among nutrient consumers. Although we used as many observations as we could obtain, more nutrient addition experiments in tropical systems would greatly benefit model testing and calibration. In summary, the N-COM model provides an ecologically consistent representation of nutrient competition appropriate for land BGC models integrated in Earth System Models.« less
-
DOE Office of Scientific and Technical Information (OSTI.GOV)
Zhu, Q.; Riley, W. J.; Tang, J.
Soil is a complex system where biotic (e.g., plant roots, micro-organisms) and abiotic (e.g., mineral surfaces) consumers compete for resources necessary for life (e.g., nitrogen, phosphorus). This competition is ecologically significant, since it regulates the dynamics of soil nutrients and controls aboveground plant productivity. Here we develop, calibrate and test a nutrient competition model that accounts for multiple soil nutrients interacting with multiple biotic and abiotic consumers. As applied here for tropical forests, the Nutrient COMpetition model (N-COM) includes three primary soil nutrients (NH 4 +, NO 3 − and PO x; representing the sum of PO 4 3−, HPOmore » 4 2− and H 2PO 4 −) and five potential competitors (plant roots, decomposing microbes, nitrifiers, denitrifiers and mineral surfaces). The competition is formulated with a quasi-steady-state chemical equilibrium approximation to account for substrate (multiple substrates share one consumer) and consumer (multiple consumers compete for one substrate) effects. N-COM successfully reproduced observed soil heterotrophic respiration, N 2O emissions, free phosphorus, sorbed phosphorus and NH 4 + pools at a tropical forest site (Tapajos). The overall model uncertainty was moderately well constrained. Our sensitivity analysis revealed that soil nutrient competition was primarily regulated by consumer–substrate affinity rather than environmental factors such as soil temperature or soil moisture. Our results also imply that under strong nutrient limitation, relative competitiveness depends strongly on the competitor functional traits (affinity and nutrient carrier enzyme abundance). We then applied the N-COM model to analyze field nitrogen and phosphorus perturbation experiments in two tropical forest sites (in Hawaii and Puerto Rico) not used in model development or calibration. Under soil inorganic nitrogen and phosphorus elevated conditions, the model accurately replicated the experimentally observed competition among nutrient consumers. Although we used as many observations as we could obtain, more nutrient addition experiments in tropical systems would greatly benefit model testing and calibration. In summary, the N-COM model provides an ecologically consistent representation of nutrient competition appropriate for land BGC models integrated in Earth System Models.« less
-
NASA Astrophysics Data System (ADS)
Zhu, Q.; Riley, W. J.; Tang, J.; Koven, C. D.
2016-01-01
Soil is a complex system where biotic (e.g., plant roots, micro-organisms) and abiotic (e.g., mineral surfaces) consumers compete for resources necessary for life (e.g., nitrogen, phosphorus). This competition is ecologically significant, since it regulates the dynamics of soil nutrients and controls aboveground plant productivity. Here we develop, calibrate and test a nutrient competition model that accounts for multiple soil nutrients interacting with multiple biotic and abiotic consumers. As applied here for tropical forests, the Nutrient COMpetition model (N-COM) includes three primary soil nutrients (NH4+, NO3- and POx; representing the sum of PO43-, HPO42- and H2PO4-) and five potential competitors (plant roots, decomposing microbes, nitrifiers, denitrifiers and mineral surfaces). The competition is formulated with a quasi-steady-state chemical equilibrium approximation to account for substrate (multiple substrates share one consumer) and consumer (multiple consumers compete for one substrate) effects. N-COM successfully reproduced observed soil heterotrophic respiration, N2O emissions, free phosphorus, sorbed phosphorus and NH4+ pools at a tropical forest site (Tapajos). The overall model uncertainty was moderately well constrained. Our sensitivity analysis revealed that soil nutrient competition was primarily regulated by consumer-substrate affinity rather than environmental factors such as soil temperature or soil moisture. Our results also imply that under strong nutrient limitation, relative competitiveness depends strongly on the competitor functional traits (affinity and nutrient carrier enzyme abundance). We then applied the N-COM model to analyze field nitrogen and phosphorus perturbation experiments in two tropical forest sites (in Hawaii and Puerto Rico) not used in model development or calibration. Under soil inorganic nitrogen and phosphorus elevated conditions, the model accurately replicated the experimentally observed competition among nutrient consumers. Although we used as many observations as we could obtain, more nutrient addition experiments in tropical systems would greatly benefit model testing and calibration. In summary, the N-COM model provides an ecologically consistent representation of nutrient competition appropriate for land BGC models integrated in Earth System Models.
-
Making the Invisible Visible: A Model for Delivery Systems in Adult Education
ERIC Educational Resources Information Center
Alex, Jennifer L.; Miller, Elizabeth A.; Platt, R. Eric; Rachal, John R.; Gammill, Deidra M.
2007-01-01
Delivery systems are not well defined in adult education. Therefore, this article reviews the multiple components that overlap to affect the adult learner and uses them to create a model for a comprehensive delivery system in adult education with these individual components as sub-systems that are interrelated and inter-locked. These components…
-
Effects of multiple scattering on time- and depth-resolved signals in airborne lidar systems
NASA Technical Reports Server (NTRS)
Punjabi, A.; Venable, D. D.
1986-01-01
A semianalytic Monte Carlo radiative transfer model (SALMON) is employed to probe the effects of multiple-scattering events on the time- and depth-resolved lidar signals from homogeneous aqueous media. The effective total attenuation coefficients in the single-scattering approximation are determined as functions of dimensionless parameters characterizing the lidar system and the medium. Results show that single-scattering events dominate when these parameters are close to their lower bounds and that when their values exceed unity multiple-scattering events dominate.
-
The relational database model and multiple multicenter clinical trials.
Blumenstein, B A
1989-12-01
The Southwest Oncology Group (SWOG) chose to use a relational database management system (RDBMS) for the management of data from multiple clinical trials because of the underlying relational model's inherent flexibility and the natural way multiple entity types (patients, studies, and participants) can be accommodated. The tradeoffs to using the relational model as compared to using the hierarchical model include added computing cycles due to deferred data linkages and added procedural complexity due to the necessity of implementing protections against referential integrity violations. The SWOG uses its RDBMS as a platform on which to build data operations software. This data operations software, which is written in a compiled computer language, allows multiple users to simultaneously update the database and is interactive with respect to the detection of conditions requiring action and the presentation of options for dealing with those conditions. The relational model facilitates the development and maintenance of data operations software.
-
A View on Future Building System Modeling and Simulation
DOE Office of Scientific and Technical Information (OSTI.GOV)
Wetter, Michael
This chapter presents what a future environment for building system modeling and simulation may look like. As buildings continue to require increased performance and better comfort, their energy and control systems are becoming more integrated and complex. We therefore focus in this chapter on the modeling, simulation and analysis of building energy and control systems. Such systems can be classified as heterogeneous systems because they involve multiple domains, such as thermodynamics, fluid dynamics, heat and mass transfer, electrical systems, control systems and communication systems. Also, they typically involve multiple temporal and spatial scales, and their evolution can be described bymore » coupled differential equations, discrete equations and events. Modeling and simulating such systems requires a higher level of abstraction and modularisation to manage the increased complexity compared to what is used in today's building simulation programs. Therefore, the trend towards more integrated building systems is likely to be a driving force for changing the status quo of today's building simulation programs. Thischapter discusses evolving modeling requirements and outlines a path toward a future environment for modeling and simulation of heterogeneous building systems.A range of topics that would require many additional pages of discussion has been omitted. Examples include computational fluid dynamics for air and particle flow in and around buildings, people movement, daylight simulation, uncertainty propagation and optimisation methods for building design and controls. For different discussions and perspectives on the future of building modeling and simulation, we refer to Sahlin (2000), Augenbroe (2001) and Malkawi and Augenbroe (2004).« less
-
Exoplanet orbital eccentricity: multiplicity relation and the Solar System.
Limbach, Mary Anne; Turner, Edwin L
2015-01-06
The known population of exoplanets exhibits a much wider range of orbital eccentricities than Solar System planets and has a much higher average eccentricity. These facts have been widely interpreted to indicate that the Solar System is an atypical member of the overall population of planetary systems. We report here on a strong anticorrelation of orbital eccentricity with multiplicity (number of planets in the system) among cataloged radial velocity (RV) systems. The mean, median, and rough distribution of eccentricities of Solar System planets fits an extrapolation of this anticorrelation to the eight-planet case rather precisely despite the fact that no more than two Solar System planets would be detectable with RV data comparable to that in the exoplanet sample. Moreover, even if regarded as a single or double planetary system, the Solar System lies in a reasonably heavily populated region of eccentricity-multiplicity space. Thus, the Solar System is not anomalous among known exoplanetary systems with respect to eccentricities when its multiplicity is taken into account. Specifically, as the multiplicity of a system increases, the eccentricity decreases roughly as a power law of index -1.20. A simple and plausible but ad hoc and model-dependent interpretation of this relationship implies that ∼ 80% of the one-planet and 25% of the two-planet systems in our sample have additional, as yet undiscovered, members but that systems of higher observed multiplicity are largely complete (i.e., relatively rarely contain additional undiscovered planets). If low eccentricities indeed favor high multiplicities, habitability may be more common in systems with a larger number of planets.
-
Exoplanet orbital eccentricity: Multiplicity relation and the Solar System
Limbach, Mary Anne; Turner, Edwin L.
2015-01-01
The known population of exoplanets exhibits a much wider range of orbital eccentricities than Solar System planets and has a much higher average eccentricity. These facts have been widely interpreted to indicate that the Solar System is an atypical member of the overall population of planetary systems. We report here on a strong anticorrelation of orbital eccentricity with multiplicity (number of planets in the system) among cataloged radial velocity (RV) systems. The mean, median, and rough distribution of eccentricities of Solar System planets fits an extrapolation of this anticorrelation to the eight-planet case rather precisely despite the fact that no more than two Solar System planets would be detectable with RV data comparable to that in the exoplanet sample. Moreover, even if regarded as a single or double planetary system, the Solar System lies in a reasonably heavily populated region of eccentricity−multiplicity space. Thus, the Solar System is not anomalous among known exoplanetary systems with respect to eccentricities when its multiplicity is taken into account. Specifically, as the multiplicity of a system increases, the eccentricity decreases roughly as a power law of index –1.20. A simple and plausible but ad hoc and model-dependent interpretation of this relationship implies that ∼80% of the one-planet and 25% of the two-planet systems in our sample have additional, as yet undiscovered, members but that systems of higher observed multiplicity are largely complete (i.e., relatively rarely contain additional undiscovered planets). If low eccentricities indeed favor high multiplicities, habitability may be more common in systems with a larger number of planets. PMID:25512527
-
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.
-
Multiple-Objective Stepwise Calibration Using Luca
Hay, Lauren E.; Umemoto, Makiko
2007-01-01
This report documents Luca (Let us calibrate), a multiple-objective, stepwise, automated procedure for hydrologic model calibration and the associated graphical user interface (GUI). Luca is a wizard-style user-friendly GUI that provides an easy systematic way of building and executing a calibration procedure. The calibration procedure uses the Shuffled Complex Evolution global search algorithm to calibrate any model compiled with the U.S. Geological Survey's Modular Modeling System. This process assures that intermediate and final states of the model are simulated consistently with measured values.
-
Modeling financial markets by the multiplicative sequence of trades
NASA Astrophysics Data System (ADS)
Gontis, V.; Kaulakys, B.
2004-12-01
We introduce the stochastic multiplicative point process modeling trading activity of financial markets. Such a model system exhibits power-law spectral density S(f)∝1/fβ, scaled as power of frequency for various values of β between 0.5 and 2. Furthermore, we analyze the relation between the power-law autocorrelations and the origin of the power-law probability distribution of the trading activity. The model reproduces the spectral properties of trading activity and explains the mechanism of power-law distribution in real markets.
-
Cannabinoids inhibit neurodegeneration in models of multiple sclerosis.
Pryce, Gareth; Ahmed, Zubair; Hankey, Deborah J R; Jackson, Samuel J; Croxford, J Ludovic; Pocock, Jennifer M; Ledent, Catherine; Petzold, Axel; Thompson, Alan J; Giovannoni, Gavin; Cuzner, M Louise; Baker, David
2003-10-01
Multiple sclerosis is increasingly being recognized as a neurodegenerative disease that is triggered by inflammatory attack of the CNS. As yet there is no satisfactory treatment. Using experimental allergic encephalo myelitis (EAE), an animal model of multiple sclerosis, we demonstrate that the cannabinoid system is neuroprotective during EAE. Mice deficient in the cannabinoid receptor CB1 tolerate inflammatory and excitotoxic insults poorly and develop substantial neurodegeneration following immune attack in EAE. In addition, exogenous CB1 agonists can provide significant neuroprotection from the consequences of inflammatory CNS disease in an experimental allergic uveitis model. Therefore, in addition to symptom management, cannabis may also slow the neurodegenerative processes that ultimately lead to chronic disability in multiple sclerosis and probably other diseases.
-
Rocket engine diagnostics using qualitative modeling techniques
NASA Technical Reports Server (NTRS)
Binder, Michael; Maul, William; Meyer, Claudia; Sovie, Amy
1992-01-01
Researchers at NASA Lewis Research Center are presently developing qualitative modeling techniques for automated rocket engine diagnostics. A qualitative model of a turbopump interpropellant seal system has been created. The qualitative model describes the effects of seal failures on the system steady-state behavior. This model is able to diagnose the failure of particular seals in the system based on anomalous temperature and pressure values. The anomalous values input to the qualitative model are generated using numerical simulations. Diagnostic test cases include both single and multiple seal failures.
-
Rocket engine diagnostics using qualitative modeling techniques
NASA Technical Reports Server (NTRS)
Binder, Michael; Maul, William; Meyer, Claudia; Sovie, Amy
1992-01-01
Researchers at NASA Lewis Research Center are presently developing qualitative modeling techniques for automated rocket engine diagnostics. A qualitative model of a turbopump interpropellant seal system was created. The qualitative model describes the effects of seal failures on the system steady state behavior. This model is able to diagnose the failure of particular seals in the system based on anomalous temperature and pressure values. The anomalous values input to the qualitative model are generated using numerical simulations. Diagnostic test cases include both single and multiple seal failures.
-
Two-Electron Transfer Pathways.
Lin, Jiaxing; Balamurugan, D; Zhang, Peng; Skourtis, Spiros S; Beratan, David N
2015-06-18
The frontiers of electron-transfer chemistry demand that we develop theoretical frameworks to describe the delivery of multiple electrons, atoms, and ions in molecular systems. When electrons move over long distances through high barriers, where the probability for thermal population of oxidized or reduced bridge-localized states is very small, the electrons will tunnel from the donor (D) to acceptor (A), facilitated by bridge-mediated superexchange interactions. If the stable donor and acceptor redox states on D and A differ by two electrons, it is possible that the electrons will propagate coherently from D to A. While structure-function relations for single-electron superexchange in molecules are well established, strategies to manipulate the coherent flow of multiple electrons are largely unknown. In contrast to one-electron superexchange, two-electron superexchange involves both one- and two-electron virtual intermediate states, the number of virtual intermediates increases very rapidly with system size, and multiple classes of pathways interfere with one another. In the study described here, we developed simple superexchange models for two-electron transfer. We explored how the bridge structure and energetics influence multielectron superexchange, and we compared two-electron superexchange interactions to single-electron superexchange. Multielectron superexchange introduces interference between singly and doubly oxidized (or reduced) bridge virtual states, so that even simple linear donor-bridge-acceptor systems have pathway topologies that resemble those seen for one-electron superexchange through bridges with multiple parallel pathways. The simple model systems studied here exhibit a richness that is amenable to experimental exploration by manipulating the multiple pathways, pathway crosstalk, and changes in the number of donor and acceptor species. The features that emerge from these studies may assist in developing new strategies to deliver multiple electrons in condensed-phase redox systems, including multiple-electron redox species, multimetallic/multielectron redox catalysts, and multiexciton excited states.
-
Shock spectra applications to a class of multiple degree-of-freedom structures system
NASA Technical Reports Server (NTRS)
Hwang, Shoi Y.
1988-01-01
The demand on safety performance of launching structure and equipment system from impulsive excitations necessitates a study which predicts the maximum response of the system as well as the maximum stresses in the system. A method to extract higher modes and frequencies for a class of multiple degree-of-freedom (MDOF) Structure system is proposed. And, along with the shock spectra derived from a linear oscillator model, a procedure to obtain upper bound solutions for maximum displacement and maximum stresses in the MDOF system is presented.
-
Ultrasound image filtering using the mutiplicative model
NASA Astrophysics Data System (ADS)
Navarrete, Hugo; Frery, Alejandro C.; Sanchez, Fermin; Anto, Joan
2002-04-01
Ultrasound images, as a special case of coherent images, are normally corrupted with multiplicative noise i.e. speckle noise. Speckle noise reduction is a difficult task due to its multiplicative nature, but good statistical models of speckle formation are useful to design adaptive speckle reduction filters. In this article a new statistical model, emerging from the Multiplicative Model framework, is presented and compared to previous models (Rayleigh, Rice and K laws). It is shown that the proposed model gives the best performance when modeling the statistics of ultrasound images. Finally, the parameters of the model can be used to quantify the extent of speckle formation; this quantification is applied to adaptive speckle reduction filter design. The effectiveness of the filter is demonstrated on typical in-vivo log-compressed B-scan images obtained by a clinical ultrasound system.
-
A Transactional Systems Model of Autism Services
Cuvo, Anthony J; Vallelunga, Lori R
2007-01-01
There has been an escalation in the number of children identified with autism spectrum disorders in recent years. To increase the likelihood that treatments for these children are effective, interventions should be derived from sound theory and research evidence. Absent this supportive foundation, intervention programs could be inconsequential if not harmful. Although atypical, the development of children with autism should be considered initially from the perspective of the same variables that affect the development of typical children. In addition, the developmental deviations that characterize autism must be considered when developing intervention programs. Behavioral systems models describe both typical and atypical development and emphasize dynamic multidirectional person–environment transactions. The environment is viewed as having multiple levels, from the individuals with autism themselves, to larger societal and cultural levels. Behavioral systems models of human development can be generalized to a transactional systems model of services for children with autism. This model is the foundational theoretical position of the Southern Illinois University Center for Autism Spectrum Disorders. The center's programs are described to illustrate the application of the model to multiple levels of the social ecology. PMID:22478495
-
A three-level atomicity model for decentralized workflow management systems
NASA Astrophysics Data System (ADS)
Ben-Shaul, Israel Z.; Heineman, George T.
1996-12-01
A workflow management system (WFMS) employs a workflow manager (WM) to execute and automate the various activities within a workflow. To protect the consistency of data, the WM encapsulates each activity with a transaction; a transaction manager (TM) then guarantees the atomicity of activities. Since workflows often group several activities together, the TM is responsible for guaranteeing the atomicity of these units. There are scalability issues, however, with centralized WFMSs. Decentralized WFMSs provide an architecture for multiple autonomous WFMSs to interoperate, thus accommodating multiple workflows and geographically-dispersed teams. When atomic units are composed of activities spread across multiple WFMSs, however, there is a conflict between global atomicity and local autonomy of each WFMS. This paper describes a decentralized atomicity model that enables workflow administrators to specify the scope of multi-site atomicity based upon the desired semantics of multi-site tasks in the decentralized WFMS. We describe an architecture that realizes our model and execution paradigm.
-
Fuzzy Neural Network-Based Interacting Multiple Model for Multi-Node Target Tracking Algorithm
Sun, Baoliang; Jiang, Chunlan; Li, Ming
2016-01-01
An interacting multiple model for multi-node target tracking algorithm was proposed based on a fuzzy neural network (FNN) to solve the multi-node target tracking problem of wireless sensor networks (WSNs). Measured error variance was adaptively adjusted during the multiple model interacting output stage using the difference between the theoretical and estimated values of the measured error covariance matrix. The FNN fusion system was established during multi-node fusion to integrate with the target state estimated data from different nodes and consequently obtain network target state estimation. The feasibility of the algorithm was verified based on a network of nine detection nodes. Experimental results indicated that the proposed algorithm could trace the maneuvering target effectively under sensor failure and unknown system measurement errors. The proposed algorithm exhibited great practicability in the multi-node target tracking of WSNs. PMID:27809271
-
ERIC Educational Resources Information Center
Li, Yi
2012-01-01
This study focuses on the issue of learning equity in colleges and universities where teaching and learning have come to depend heavily on computer technologies. The study uses the Multiple Indicators Multiple Causes (MIMIC) latent variable model to quantitatively investigate whether there is a gender /ethnicity difference in using computer based…
-
Modeling Multiple Human-Automation Distributed Systems using Network-form Games
NASA Technical Reports Server (NTRS)
Brat, Guillaume
2012-01-01
The paper describes at a high-level the network-form game framework (based on Bayes net and game theory), which can be used to model and analyze safety issues in large, distributed, mixed human-automation systems such as NextGen.
-
Programming model for distributed intelligent systems
NASA Technical Reports Server (NTRS)
Sztipanovits, J.; Biegl, C.; Karsai, G.; Bogunovic, N.; Purves, B.; Williams, R.; Christiansen, T.
1988-01-01
A programming model and architecture which was developed for the design and implementation of complex, heterogeneous measurement and control systems is described. The Multigraph Architecture integrates artificial intelligence techniques with conventional software technologies, offers a unified framework for distributed and shared memory based parallel computational models and supports multiple programming paradigms. The system can be implemented on different hardware architectures and can be adapted to strongly different applications.
-
Li, YuHui; Jin, FeiTeng
2017-01-01
The inversion design approach is a very useful tool for the complex multiple-input-multiple-output nonlinear systems to implement the decoupling control goal, such as the airplane model and spacecraft model. In this work, the flight control law is proposed using the neural-based inversion design method associated with the nonlinear compensation for a general longitudinal model of the airplane. First, the nonlinear mathematic model is converted to the equivalent linear model based on the feedback linearization theory. Then, the flight control law integrated with this inversion model is developed to stabilize the nonlinear system and relieve the coupling effect. Afterwards, the inversion control combined with the neural network and nonlinear portion is presented to improve the transient performance and attenuate the uncertain effects on both external disturbances and model errors. Finally, the simulation results demonstrate the effectiveness of this controller. PMID:29410680
-
Multiplicity in Early Stellar Evolution
NASA Astrophysics Data System (ADS)
Reipurth, B.; Clarke, C. J.; Boss, A. P.; Goodwin, S. P.; Rodríguez, L. F.; Stassun, K. G.; Tokovinin, A.; Zinnecker, H.
Observations from optical to centimeter wavelengths have demonstrated that multiple systems of two or more bodies is the norm at all stellar evolutionary stages. Multiple systems are widely agreed to result from the collapse and fragmentation of cloud cores, despite the inhibiting influence of magnetic fields. Surveys of class 0 protostars with millimeter interferometers have revealed a very high multiplicity frequency of about 2/3, even though there are observational difficulties in resolving close protobinaries, thus supporting the possibility that all stars could be born in multiple systems. Near-infrared adaptive optics observations of class I protostars show a lower binary frequency relative to the class 0 phase, a declining trend that continues through the class II/III stages to the field population. This loss of companions is a natural consequence of dynamical interplay in small multiple systems, leading to ejection of members. We discuss observational consequences of this dynamical evolution, and its influence on circumstellar disks, and we review the evolution of circumbinary disks and their role in defining binary mass ratios. Special attention is paid to eclipsing PMS binaries, which allow for observational tests of evolutionary models of early stellar evolution. Many stars are born in clusters and small groups, and we discuss how interactions in dense stellar environments can significantly alter the distribution of binary separations through dissolution of wider binaries. The binaries and multiples we find in the field are the survivors of these internal and external destructive processes, and we provide a detailed overview of the multiplicity statistics of the field, which form a boundary condition for all models of binary evolution. Finally, we discuss various formation mechanisms for massive binaries, and the properties of massive trapezia.
-
New nonlinear control algorithms for multiple robot arms
NASA Technical Reports Server (NTRS)
Tarn, T. J.; Bejczy, A. K.; Yun, X.
1988-01-01
Multiple coordinated robot arms are modeled by considering the arms as closed kinematic chains and as a force-constrained mechanical system working on the same object simultaneously. In both formulations, a novel dynamic control method is discussed. It is based on feedback linearization and simultaneous output decoupling technique. By applying a nonlinear feedback and a nonlinear coordinate transformation, the complicated model of the multiple robot arms in either formulation is converted into a linear and output decoupled system. The linear system control theory and optimal control theory are used to design robust controllers in the task space. The first formulation has the advantage of automatically handling the coordination and load distribution among the robot arms. In the second formulation, it was found that by choosing a general output equation it became possible simultaneously to superimpose the position and velocity error feedback with the force-torque error feedback in the task space.
-
Modelling and stability analysis of switching impulsive power systems with multiple equilibria
NASA Astrophysics Data System (ADS)
Zhu, Liying; Qiu, Jianbin; Chadli, Mohammed
2017-12-01
This paper tries to model power systems accompanied with a series of faults in the form of switched impulsive Hamiltonian systems (SIHSs) with multiple equilibria (ME) and unstable subsystems (US), and then analyze long-term stability issues of the power systems from the viewpoint of mathematics. According to the complex phenomena of switching actions of stages and generators, impulses of state, and existence of multiple equilibria, this paper first introduces an SIHS with ME and US to formulate a switching impulsive power system composed of an active generator, a standby generator, and an infinite load. Then, based on special system structures, a unique compact region containing all ME is determined, and novel stability concepts of region stability (RS), asymptotic region stability (ARS), and exponential region stability (ERS) are defined for such SIHS with respect to the region. Third, based on the introduced stability concepts, this paper proposes a necessary and sufficient condition of RS and ARS and a sufficient condition of ERS for the power system with respect to the region via the maximum energy function method. Finally, numerical simulations are carried out for a power system to show the effectiveness and practicality of the obained novel results.
-
Intrinsic Variability in Multiple Systems and Clusters: Open Questions
NASA Astrophysics Data System (ADS)
Lampens, P.
2006-04-01
It is most interesting and rewarding to probe the stellar structure of stars which belong to a system originating from the same parent cloud as this provides additional and more accurate constraints for the models. New results on pulsating components in multiple systems and clusters are beginning to emerge regularly. Based on concrete studies, I will present still unsolved problems and discuss some of the issues which may affect our understanding of the pulsation physics in such systems but also in general.
-
An automation simulation testbed
NASA Technical Reports Server (NTRS)
Cook, George E.; Sztipanovits, Janos; Biegl, Csaba; Karsai, Gabor; Springfield, James F.; Mutammara, Atheel
1988-01-01
The work being done in porting ROBOSIM (a graphical simulation system developed jointly by NASA-MSFC and Vanderbilt University) to the HP350SRX graphics workstation is described. New additional ROBOSIM features, like collision detection and new kinematics simulation methods are also discussed. Based on the experiences of the work on ROBOSIM, a new graphics structural modeling environment is suggested which is intended to be a part of a new knowledge-based multiple aspect modeling testbed. The knowledge-based modeling methodologies and tools already available are described. Three case studies in the area of Space Station automation are also reported. First a geometrical structural model of the station is presented. This model was developed using the ROBOSIM package. Next the possible application areas of an integrated modeling environment in the testing of different Space Station operations are discussed. One of these possible application areas is the modeling of the Environmental Control and Life Support System (ECLSS), which is one of the most complex subsystems of the station. Using the multiple aspect modeling methodology, a fault propagation model of this system is being built and is described.
-
Computer simulation of a multiple-aperture coherent laser radar
NASA Astrophysics Data System (ADS)
Gamble, Kevin J.; Weeks, Arthur R.
1996-06-01
This paper presents the construction of a 2D multiple aperture coherent laser radar simulation that is capable of including the effects of the time evolution of speckle on the laser radar output. Every portion of a laser radar system is modeled in software, including quarter and half wave plates, beamsplitters (polarizing and non-polarizing), the detector, the laser source, and all necessary lenses. Free space propagation is implemented using the Rayleigh- Sommerfeld integral for both orthogonal polarizations. Atmospheric turbulence is also included in the simulation and is modeled using time correlated Kolmogorov phase screens. The simulation itself can be configured to simulate both monostatic and bistatic systems. The simulation allows the user to specify component level parameters such as extinction ratios for polarizing beam splitters, detector sizes and shapes. orientation of the slow axis for quarter/half wave plates and other components used in the system. This is useful from a standpoint of being a tool in the design of a multiple aperture laser radar system.
-
NASA Astrophysics Data System (ADS)
Kollet, S. J.; Goergen, K.; Gasper, F.; Shresta, P.; Sulis, M.; Rihani, J.; Simmer, C.; Vereecken, H.
2013-12-01
In studies of the terrestrial hydrologic, energy and biogeochemical cycles, integrated multi-physics simulation platforms take a central role in characterizing non-linear interactions, variances and uncertainties of system states and fluxes in reciprocity with observations. Recently developed integrated simulation platforms attempt to honor the complexity of the terrestrial system across multiple time and space scales from the deeper subsurface including groundwater dynamics into the atmosphere. Technically, this requires the coupling of atmospheric, land surface, and subsurface-surface flow models in supercomputing environments, while ensuring a high-degree of efficiency in the utilization of e.g., standard Linux clusters and massively parallel resources. A systematic performance analysis including profiling and tracing in such an application is crucial in the understanding of the runtime behavior, to identify optimum model settings, and is an efficient way to distinguish potential parallel deficiencies. On sophisticated leadership-class supercomputers, such as the 28-rack 5.9 petaFLOP IBM Blue Gene/Q 'JUQUEEN' of the Jülich Supercomputing Centre (JSC), this is a challenging task, but even more so important, when complex coupled component models are to be analysed. Here we want to present our experience from coupling, application tuning (e.g. 5-times speedup through compiler optimizations), parallel scaling and performance monitoring of the parallel Terrestrial Systems Modeling Platform TerrSysMP. The modeling platform consists of the weather prediction system COSMO of the German Weather Service; the Community Land Model, CLM of NCAR; and the variably saturated surface-subsurface flow code ParFlow. The model system relies on the Multiple Program Multiple Data (MPMD) execution model where the external Ocean-Atmosphere-Sea-Ice-Soil coupler (OASIS3) links the component models. TerrSysMP has been instrumented with the performance analysis tool Scalasca and analyzed on JUQUEEN with processor counts on the order of 10,000. The instrumentation is used in weak and strong scaling studies with real data cases and hypothetical idealized numerical experiments for detailed profiling and tracing analysis. The profiling is not only useful in identifying wait states that are due to the MPMD execution model, but also in fine-tuning resource allocation to the component models in search of the most suitable load balancing. This is especially necessary, as with numerical experiments that cover multiple (high resolution) spatial scales, the time stepping, coupling frequencies, and communication overheads are constantly shifting, which makes it necessary to re-determine the model setup with each new experimental design.
-
A method for integrating multiple components in a decision support system
Donald Nute; Walter D. Potter; Zhiyuan Cheng; Mayukh Dass; Astrid Glende; Frederick Maierv; Cy Routh; Hajime Uchiyama; Jin Wang; Sarah Witzig; Mark Twery; Peter Knopp; Scott Thomasma; H. Michael Rauscher
2005-01-01
We present a flexible, extensible method for integrating multiple tools into a single large decision support system (DSS) using a forest ecosystem management DSS (NED-2) as an example. In our approach, a rich ontology for the target domain is developed and implemented in the internal data model for the DSS. Semi-autonomous agents control external components and...
-
PeTTSy: a computational tool for perturbation analysis of complex systems biology models.
Domijan, Mirela; Brown, Paul E; Shulgin, Boris V; Rand, David A
2016-03-10
Over the last decade sensitivity analysis techniques have been shown to be very useful to analyse complex and high dimensional Systems Biology models. However, many of the currently available toolboxes have either used parameter sampling, been focused on a restricted set of model observables of interest, studied optimisation of a objective function, or have not dealt with multiple simultaneous model parameter changes where the changes can be permanent or temporary. Here we introduce our new, freely downloadable toolbox, PeTTSy (Perturbation Theory Toolbox for Systems). PeTTSy is a package for MATLAB which implements a wide array of techniques for the perturbation theory and sensitivity analysis of large and complex ordinary differential equation (ODE) based models. PeTTSy is a comprehensive modelling framework that introduces a number of new approaches and that fully addresses analysis of oscillatory systems. It examines sensitivity analysis of the models to perturbations of parameters, where the perturbation timing, strength, length and overall shape can be controlled by the user. This can be done in a system-global setting, namely, the user can determine how many parameters to perturb, by how much and for how long. PeTTSy also offers the user the ability to explore the effect of the parameter perturbations on many different types of outputs: period, phase (timing of peak) and model solutions. PeTTSy can be employed on a wide range of mathematical models including free-running and forced oscillators and signalling systems. To enable experimental optimisation using the Fisher Information Matrix it efficiently allows one to combine multiple variants of a model (i.e. a model with multiple experimental conditions) in order to determine the value of new experiments. It is especially useful in the analysis of large and complex models involving many variables and parameters. PeTTSy is a comprehensive tool for analysing large and complex models of regulatory and signalling systems. It allows for simulation and analysis of models under a variety of environmental conditions and for experimental optimisation of complex combined experiments. With its unique set of tools it makes a valuable addition to the current library of sensitivity analysis toolboxes. We believe that this software will be of great use to the wider biological, systems biology and modelling communities.
-
Integrated urban systems model with multiple transportation supply agents.
DOT National Transportation Integrated Search
2012-10-01
This project demonstrates the feasibility of developing quantitative models that can forecast future networks under : current and alternative transportation planning processes. The current transportation planning process is modeled : based on empiric...
-
Validation of Multiple Tools for Flat Plate Photovoltaic Modeling Against Measured Data
DOE Office of Scientific and Technical Information (OSTI.GOV)
Freeman, J.; Whitmore, J.; Blair, N.
2014-08-01
This report expands upon a previous work by the same authors, published in the 40th IEEE Photovoltaic Specialists conference. In this validation study, comprehensive analysis is performed on nine photovoltaic systems for which NREL could obtain detailed performance data and specifications, including three utility-scale systems and six commercial scale systems. Multiple photovoltaic performance modeling tools were used to model these nine systems, and the error of each tool was analyzed compared to quality-controlled measured performance data. This study shows that, excluding identified outliers, all tools achieve annual errors within +/-8% and hourly root mean squared errors less than 7% formore » all systems. It is further shown using SAM that module model and irradiance input choices can change the annual error with respect to measured data by as much as 6.6% for these nine systems, although all combinations examined still fall within an annual error range of +/-8.5%. Additionally, a seasonal variation in monthly error is shown for all tools. Finally, the effects of irradiance data uncertainty and the use of default loss assumptions on annual error are explored, and two approaches to reduce the error inherent in photovoltaic modeling are proposed.« less
-
Filtering Meteoroid Flights Using Multiple Unscented Kalman Filters
NASA Astrophysics Data System (ADS)
Sansom, E. K.; Bland, P. A.; Rutten, M. G.; Paxman, J.; Towner, M. C.
2016-11-01
Estimator algorithms are immensely versatile and powerful tools that can be applied to any problem where a dynamic system can be modeled by a set of equations and where observations are available. A well designed estimator enables system states to be optimally predicted and errors to be rigorously quantified. Unscented Kalman filters (UKFs) and interactive multiple models can be found in methods from satellite tracking to self-driving cars. The luminous trajectory of the Bunburra Rockhole fireball was observed by the Desert Fireball Network in mid-2007. The recorded data set is used in this paper to examine the application of these two techniques as a viable approach to characterizing fireball dynamics. The nonlinear, single-body system of equations, used to model meteoroid entry through the atmosphere, is challenged by gross fragmentation events that may occur. The incorporation of the UKF within an interactive multiple model smoother provides a likely solution for when fragmentation events may occur as well as providing a statistical analysis of the state uncertainties. In addition to these benefits, another advantage of this approach is its automatability for use within an image processing pipeline to facilitate large fireball data analyses and meteorite recoveries.
-
Cooperating Expert Systems For Space Station Power Distribution Management
NASA Astrophysics Data System (ADS)
Nguyen, T. A.; Chiou, W. C.
1987-02-01
In a complex system such as the manned Space Station, it is deem necessary that many expert systems must perform tasks in a concurrent and cooperative manner. An important question arise is: what cooperative-task-performing models are appropriate for multiple expert systems to jointly perform tasks. The solution to this question will provide a crucial automation design criteria for the Space Station complex systems architecture. Based on a client/server model for performing tasks, we have developed a system that acts as a front-end to support loosely-coupled communications between expert systems running on multiple Symbolics machines. As an example, we use two ART*-based expert systems to demonstrate the concept of parallel symbolic manipulation for power distribution management and dynamic load planner/scheduler in the simulated Space Station environment. This on-going work will also explore other cooperative-task-performing models as alternatives which can evaluate inter and intra expert system communication mechanisms. It will be served as a testbed and a bench-marking tool for other Space Station expert subsystem communication and information exchange.
-
Measuring the Performance and Intelligence of Systems: Proceedings of the 2002 PerMIS Workshop
NASA Technical Reports Server (NTRS)
Messina, E. R.; Meystel, A. M.
2002-01-01
Contents include the following: Performance Metrics; Performance of Multiple Agents; Performance of Mobility Systems; Performance of Planning Systems; General Discussion Panel 1; Uncertainty of Representation I; Performance of Robots in Hazardous Domains; Modeling Intelligence; Modeling of Mind; Measuring Intelligence; Grouping: A Core Procedure of Intelligence; Uncertainty in Representation II; Towards Universal Planning/Control Systems.
-
A Cognitive-System Model for En Route Air Traffic Management
NASA Technical Reports Server (NTRS)
Corker, Kevin M.; Pisanich, Gregory; Lebacqz, J. Victor (Technical Monitor)
1998-01-01
NASA Ames Research Center has been engaged in the development of advanced air traffic management technologies whose basic form is cognitive aiding systems for air traffic controller and flight deck operations. In the design and evaluation of such systems the dynamic interaction between the airborne aiding system and the ground-based aiding systems forms a critical coupling for control. The human operator is an integral control element in the system and the optimal integration of human decision and performance parameters with those of the automation aiding systems offers a significant challenge to cognitive engineering. This paper presents a study in full mission simulation and the development of a predictive computational model of human performance. We have found that this combination of methodologies provide a powerful design-aiding process. We have extended the computational model Man Machine Integrated Design and Analysis System (N13DAS) to include representation of multiple cognitive agents (both human operators and intelligent aiding systems), operating aircraft airline operations centers and air traffic control centers in the evolving airspace. The demands of this application require the representation of many intelligent agents sharing world-models, and coordinating action/intention with cooperative scheduling of goals and actions in a potentially unpredictable world of operations. The operator's activity structures have been developed to include prioritization and interruption of multiple parallel activities among multiple operators, to provide for anticipation (knowledge of the intention and action of remote operators), and to respond to failures of the system and other operators in the system in situation-specific paradigms. We have exercised this model in a multi-air traffic sector scenario with potential conflict among aircraft at and across sector boundaries. We have modeled the control situation as a multiple closed loop system. The inner and outer loop alerting structure of air traffic management has many implications that need to be investigated to assure adequate design. First, there are control and stability factors implicit in the design. As the inner loop response time approaches that of the outer loop, system stability may be compromised in that controllers may be solving a problem the nature of which has already been changed by pilot action. Second, information exchange and information presentation for both air and ground must be designed to complement as opposed to compete with each other. Third, the level of individual and shared awareness in trajectory modification and flight conformance needs to be defined. Fourth, the level of required awareness and performance impact of mixed fleet operations and failed-mode recovery must be explored.
-
Developing Access Control Model of Web OLAP over Trusted and Collaborative Data Warehouses
NASA Astrophysics Data System (ADS)
Fugkeaw, Somchart; Mitrpanont, Jarernsri L.; Manpanpanich, Piyawit; Juntapremjitt, Sekpon
This paper proposes the design and development of Role- based Access Control (RBAC) model for the Single Sign-On (SSO) Web-OLAP query spanning over multiple data warehouses (DWs). The model is based on PKI Authentication and Privilege Management Infrastructure (PMI); it presents a binding model of RBAC authorization based on dimension privilege specified in attribute certificate (AC) and user identification. Particularly, the way of attribute mapping between DW user authentication and privilege of dimensional access is illustrated. In our approach, we apply the multi-agent system to automate flexible and effective management of user authentication, role delegation as well as system accountability. Finally, the paper culminates in the prototype system A-COLD (Access Control of web-OLAP over multiple DWs) that incorporates the OLAP features and authentication and authorization enforcement in the multi-user and multi-data warehouse environment.
-
Preparation and impact of multiple (water-in-oil-in-water) emulsions in meat systems.
Cofrades, S; Antoniou, I; Solas, M T; Herrero, A M; Jiménez-Colmenero, F
2013-11-01
The aim of this paper was to prepare and characterise multiple emulsions and assess their utility as pork backfat replacers in meat gel/emulsion model systems. In order to improve the fat content (in quantitative and qualitative terms) pork backfat was replaced by a water-in-oil-in-water emulsion (W1/O/W2) prepared with olive oil (as lipid phase), polyglycerol ester of polyricinoleic acid (PGPR) as a lipophilic emulsifier, and sodium caseinate (SC) and whey protein concentrate (WP) as hydrophilic emulsifiers. The emulsion properties (particle size and distribution, stability, microstructure) and meat model system characteristics (composition, texture, fat and water binding properties, and colour) of the W1/O/W2, as affected by reformulation, were evaluated. Multiple emulsions showed a well-defined monomodal distribution. Freshly prepared multiple emulsions showed good thermal stability (better using SC) with no creaming. The meat systems had good water and fat binding properties irrespective of formulation. The effect on texture by replacement of pork backfat by W1/O/W2 emulsions generally depends on the type of double emulsion (associated with the hydrophilic emulsifier used in its formulation) and the fat level in the meat system. Copyright © 2013 Elsevier Ltd. All rights reserved.
-
A model for plant lighting system selection.
Ciolkosz, D E; Albright, L D; Sager, J C; Langhans, R W
2002-01-01
A decision model is presented that compares lighting systems for a plant growth scenario and chooses the most appropriate system from a given set of possible choices. The model utilizes a Multiple Attribute Utility Theory approach, and incorporates expert input and performance simulations to calculate a utility value for each lighting system being considered. The system with the highest utility is deemed the most appropriate system. The model was applied to a greenhouse scenario, and analyses were conducted to test the model's output for validity. Parameter variation indicates that the model performed as expected. Analysis of model output indicates that differences in utility among the candidate lighting systems were sufficiently large to give confidence that the model's order of selection was valid.
-
Why is CDMA the solution for mobile satellite communication
NASA Technical Reports Server (NTRS)
Gilhousen, Klein S.; Jacobs, Irwin M.; Padovani, Roberto; Weaver, Lindsay A.
1989-01-01
It is demonstrated that spread spectrum Code Division Multiple Access (CDMA) systems provide an economically superior solution to satellite mobile communications by increasing the system maximum capacity with respect to single channel per carrier Frequency Division Multiple Access (FDMA) systems. Following the comparative analysis of CDMA and FDMA systems, the design of a model that was developed to test the feasibility of the approach and the performance of a spread spectrum system in a mobile environment. Results of extensive computer simulations as well as laboratory and field tests results are presented.
-
A support vector machine based control application to the experimental three-tank system.
Iplikci, Serdar
2010-07-01
This paper presents a support vector machine (SVM) approach to generalized predictive control (GPC) of multiple-input multiple-output (MIMO) nonlinear systems. The possession of higher generalization potential and at the same time avoidance of getting stuck into the local minima have motivated us to employ SVM algorithms for modeling MIMO systems. Based on the SVM model, detailed and compact formulations for calculating predictions and gradient information, which are used in the computation of the optimal control action, are given in the paper. The proposed MIMO SVM-based GPC method has been verified on an experimental three-tank liquid level control system. Experimental results have shown that the proposed method can handle the control task successfully for different reference trajectories. Moreover, a detailed discussion on data gathering, model selection and effects of the control parameters have been given in this paper. 2010 ISA. Published by Elsevier Ltd. All rights reserved.
-
Soranno, Patricia A.; Cheruvelil, Kendra Spence; Webster, Katherine E.; Bremigan, Mary T.; Wagner, Tyler; Stow, Craig A.
2010-01-01
Governmental entities are responsible for managing and conserving large numbers of lake, river, and wetland ecosystems that can be addressed only rarely on a case-by-case basis. We present a system for predictive classification modeling, grounded in the theoretical foundation of landscape limnology, that creates a tractable number of ecosystem classes to which management actions may be tailored. We demonstrate our system by applying two types of predictive classification modeling approaches to develop nutrient criteria for eutrophication management in 1998 north temperate lakes. Our predictive classification system promotes the effective management of multiple ecosystems across broad geographic scales by explicitly connecting management and conservation goals to the classification modeling approach, considering multiple spatial scales as drivers of ecosystem dynamics, and acknowledging the hierarchical structure of freshwater ecosystems. Such a system is critical for adaptive management of complex mosaics of freshwater ecosystems and for balancing competing needs for ecosystem services in a changing world.
-
Clinical time series prediction: towards a hierarchical dynamical system framework
Liu, Zitao; Hauskrecht, Milos
2014-01-01
Objective Developing machine learning and data mining algorithms for building temporal models of clinical time series is important for understanding of the patient condition, the dynamics of a disease, effect of various patient management interventions and clinical decision making. In this work, we propose and develop a novel hierarchical framework for modeling clinical time series data of varied length and with irregularly sampled observations. Materials and methods Our hierarchical dynamical system framework for modeling clinical time series combines advantages of the two temporal modeling approaches: the linear dynamical system and the Gaussian process. We model the irregularly sampled clinical time series by using multiple Gaussian process sequences in the lower level of our hierarchical framework and capture the transitions between Gaussian processes by utilizing the linear dynamical system. The experiments are conducted on the complete blood count (CBC) panel data of 1000 post-surgical cardiac patients during their hospitalization. Our framework is evaluated and compared to multiple baseline approaches in terms of the mean absolute prediction error and the absolute percentage error. Results We tested our framework by first learning the time series model from data for the patient in the training set, and then applying the model in order to predict future time series values on the patients in the test set. We show that our model outperforms multiple existing models in terms of its predictive accuracy. Our method achieved a 3.13% average prediction accuracy improvement on ten CBC lab time series when it was compared against the best performing baseline. A 5.25% average accuracy improvement was observed when only short-term predictions were considered. Conclusion A new hierarchical dynamical system framework that lets us model irregularly sampled time series data is a promising new direction for modeling clinical time series and for improving their predictive performance. PMID:25534671
-
Nonlinear aeroservoelastic analysis of a controlled multiple-actuated-wing model with free-play
NASA Astrophysics Data System (ADS)
Huang, Rui; Hu, Haiyan; Zhao, Yonghui
2013-10-01
In this paper, the effects of structural nonlinearity due to free-play in both leading-edge and trailing-edge outboard control surfaces on the linear flutter control system are analyzed for an aeroelastic model of three-dimensional multiple-actuated-wing. The free-play nonlinearities in the control surfaces are modeled theoretically by using the fictitious mass approach. The nonlinear aeroelastic equations of the presented model can be divided into nine sub-linear modal-based aeroelastic equations according to the different combinations of deflections of the leading-edge and trailing-edge outboard control surfaces. The nonlinear aeroelastic responses can be computed based on these sub-linear aeroelastic systems. To demonstrate the effects of nonlinearity on the linear flutter control system, a single-input and single-output controller and a multi-input and multi-output controller are designed based on the unconstrained optimization techniques. The numerical results indicate that the free-play nonlinearity can lead to either limit cycle oscillations or divergent motions when the linear control system is implemented.
-
Pumping Optimization Model for Pump and Treat Systems - 15091
DOE Office of Scientific and Technical Information (OSTI.GOV)
Baker, S.; Ivarson, Kristine A.; Karanovic, M.
2015-01-15
Pump and Treat systems are being utilized to remediate contaminated groundwater in the Hanford 100 Areas adjacent to the Columbia River in Eastern Washington. Design of the systems was supported by a three-dimensional (3D) fate and transport model. This model provided sophisticated simulation capabilities but requires many hours to calculate results for each simulation considered. Many simulations are required to optimize system performance, so a two-dimensional (2D) model was created to reduce run time. The 2D model was developed as a equivalent-property version of the 3D model that derives boundary conditions and aquifer properties from the 3D model. It producesmore » predictions that are very close to the 3D model predictions, allowing it to be used for comparative remedy analyses. Any potential system modifications identified by using the 2D version are verified for use by running the 3D model to confirm performance. The 2D model was incorporated into a comprehensive analysis system (the Pumping Optimization Model, POM) to simplify analysis of multiple simulations. It allows rapid turnaround by utilizing a graphical user interface that: 1 allows operators to create hypothetical scenarios for system operation, 2 feeds the input to the 2D fate and transport model, and 3 displays the scenario results to evaluate performance improvement. All of the above is accomplished within the user interface. Complex analyses can be completed within a few hours and multiple simulations can be compared side-by-side. The POM utilizes standard office computing equipment and established groundwater modeling software.« less
-
Fuzzy linear model for production optimization of mining systems with multiple entities
NASA Astrophysics Data System (ADS)
Vujic, Slobodan; Benovic, Tomo; Miljanovic, Igor; Hudej, Marjan; Milutinovic, Aleksandar; Pavlovic, Petar
2011-12-01
Planning and production optimization within multiple mines or several work sites (entities) mining systems by using fuzzy linear programming (LP) was studied. LP is the most commonly used operations research methods in mining engineering. After the introductory review of properties and limitations of applying LP, short reviews of the general settings of deterministic and fuzzy LP models are presented. With the purpose of comparative analysis, the application of both LP models is presented using the example of the Bauxite Basin Niksic with five mines. After the assessment, LP is an efficient mathematical modeling tool in production planning and solving many other single-criteria optimization problems of mining engineering. After the comparison of advantages and deficiencies of both deterministic and fuzzy LP models, the conclusion presents benefits of the fuzzy LP model but is also stating that seeking the optimal plan of production means to accomplish the overall analysis that will encompass the LP model approaches.
-
Information Retrieval: A Sequential Learning Process.
ERIC Educational Resources Information Center
Bookstein, Abraham
1983-01-01
Presents decision-theoretic models which intrinsically include retrieval of multiple documents whereby system responds to request by presenting documents to patron in sequence, gathering feedback, and using information to modify future retrievals. Document independence model, set retrieval model, sequential retrieval model, learning model,…
-
NASA Astrophysics Data System (ADS)
Murphy, J.; Lammers, R. B.; Proussevitch, A. A.; Ozik, J.; Altaweel, M.; Collier, N. T.; Alessa, L.; Kliskey, A. D.
2014-12-01
The global hydrological cycle intersects with human decision making at multiple scales, from dams and irrigation works to the taps in individuals' homes. Residential water consumers are commonly encouraged to conserve; these messages are heard against a background of individual values and conceptions about water quality, uses, and availability. The degree to which these values impact the larger-hydrological dynamics, the way that changes in those values have impacts on the hydrological cycle through time, and the feedbacks by which water availability and quality in turn shape those values, are not well explored. To investigate this domain we employ a global-scale water balance model (WBM) coupled with a social-science-grounded agent-based model (ABM). The integration of a hydrological model with an agent-based model allows us to explore driving factors in the dynamics in coupled human-natural systems. From the perspective of the physical hydrologist, the ABM offers a richer means of incorporating the human decisions that drive the hydrological system; from the view of the social scientist, a physically-based hydrological model allows the decisions of the agents to play out against constraints faithful to the real world. We apply the interconnected models to a study of Tucson, Arizona, USA, and its role in the larger Colorado River system. Our core concept is Technology-Induced Environmental Distancing (TIED), which posits that layers of technology can insulate consumers from direct knowledge of a resource. In Tucson, multiple infrastructure and institutional layers have arguably increased the conceptual distance between individuals and their water supply, offering a test case of the TIED framework. Our coupled simulation allows us to show how the larger system transforms a resource with high temporal and spatial variability into a consumer constant, and the effects of this transformation on the regional system. We use this to explore how pricing, messaging, and social dynamics impact demand, how changes in demand affect the regional water system, and under what system challenges the values of the individuals are likely to change. This study is a preamble to modeling multiple regionally connected cities and larger systems with impacts on hydrology at the continental and global scales.
-
Multiple Input Design for Real-Time Parameter Estimation in the Frequency Domain
NASA Technical Reports Server (NTRS)
Morelli, Eugene
2003-01-01
A method for designing multiple inputs for real-time dynamic system identification in the frequency domain was developed and demonstrated. The designed inputs are mutually orthogonal in both the time and frequency domains, with reduced peak factors to provide good information content for relatively small amplitude excursions. The inputs are designed for selected frequency ranges, and therefore do not require a priori models. The experiment design approach was applied to identify linear dynamic models for the F-15 ACTIVE aircraft, which has multiple control effectors.
-
Collectivity without plasma in hadronic collisions
NASA Astrophysics Data System (ADS)
Bierlich, Christian; Gustafson, Gösta; Lönnblad, Leif
2018-04-01
We present a microscopic model for collective effects in high multiplicity proton-proton collisions, where multiple partonic subcollisions give rise to a dense system of strings. From lattice calculations we know that QCD strings are transversely extended, and we argue that this should result in a transverse pressure and expansion, similar to the flow in a deconfined plasma. The model is implemented in the PYTHIA8 Monte Carlo event generator, and we find that it can qualitatively reproduce the long range azimuthal correlations forming a near-side ridge in high multiplicity proton-proton events at LHC energies.
-
Multisite EPR oximetry from multiple quadrature harmonics.
Ahmad, R; Som, S; Johnson, D H; Zweier, J L; Kuppusamy, P; Potter, L C
2012-01-01
Multisite continuous wave (CW) electron paramagnetic resonance (EPR) oximetry using multiple quadrature field modulation harmonics is presented. First, a recently developed digital receiver is used to extract multiple harmonics of field modulated projection data. Second, a forward model is presented that relates the projection data to unknown parameters, including linewidth at each site. Third, a maximum likelihood estimator of unknown parameters is reported using an iterative algorithm capable of jointly processing multiple quadrature harmonics. The data modeling and processing are applicable for parametric lineshapes under nonsaturating conditions. Joint processing of multiple harmonics leads to 2-3-fold acceleration of EPR data acquisition. For demonstration in two spatial dimensions, both simulations and phantom studies on an L-band system are reported. Copyright © 2011 Elsevier Inc. All rights reserved.
-
Hydrological modelling in forested systems
This chapter provides a brief overview of forest hydrology modelling approaches for answering important global research and management questions. Many hundreds of hydrological models have been applied globally across multiple decades to represent and predict forest hydrological p...
-
Laser Pulse-Stretching Using Multiple Optical Ring-Cavities
NASA Technical Reports Server (NTRS)
Kojima, Jun; Nguyen, Quang-Viet; Lee, Chi-Ming (Technical Monitor)
2002-01-01
We describe a simple and passive nanosecond-long (ns-long) laser 'pulse-stretcher' using multiple optical ring-cavities. We present a model of the pulse-stretching process for an arbitrary number of optical ring-cavities. Using the model, we optimize the design of a pulse-stretcher for use in a spontaneous Raman scattering excitation system that avoids laser-induced plasma spark problems. From the optimized design, we then experimentally demonstrate and verify the model with a 3-cavity pulse-stretcher system that converts a 1000 mJ, 8.4 ns-long input laser pulse into an approximately 75 ns-long (FWHM) output laser pulse with a peak power reduction of 0.10X, and an 83% efficiency.
-
NASA Astrophysics Data System (ADS)
Lucifredi, A.; Mazzieri, C.; Rossi, M.
2000-05-01
Since the operational conditions of a hydroelectric unit can vary within a wide range, the monitoring system must be able to distinguish between the variations of the monitored variable caused by variations of the operation conditions and those due to arising and progressing of failures and misoperations. The paper aims to identify the best technique to be adopted for the monitoring system. Three different methods have been implemented and compared. Two of them use statistical techniques: the first, the linear multiple regression, expresses the monitored variable as a linear function of the process parameters (independent variables), while the second, the dynamic kriging technique, is a modified technique of multiple linear regression representing the monitored variable as a linear combination of the process variables in such a way as to minimize the variance of the estimate error. The third is based on neural networks. Tests have shown that the monitoring system based on the kriging technique is not affected by some problems common to the other two models e.g. the requirement of a large amount of data for their tuning, both for training the neural network and defining the optimum plane for the multiple regression, not only in the system starting phase but also after a trivial operation of maintenance involving the substitution of machinery components having a direct impact on the observed variable. Or, in addition, the necessity of different models to describe in a satisfactory way the different ranges of operation of the plant. The monitoring system based on the kriging statistical technique overrides the previous difficulties: it does not require a large amount of data to be tuned and is immediately operational: given two points, the third can be immediately estimated; in addition the model follows the system without adapting itself to it. The results of the experimentation performed seem to indicate that a model based on a neural network or on a linear multiple regression is not optimal, and that a different approach is necessary to reduce the amount of work during the learning phase using, when available, all the information stored during the initial phase of the plant to build the reference baseline, elaborating, if it is the case, the raw information available. A mixed approach using the kriging statistical technique and neural network techniques could optimise the result.
-
DOE Office of Scientific and Technical Information (OSTI.GOV)
Sig Drellack, Lance Prothro
2007-12-01
The Underground Test Area (UGTA) Project of the U.S. Department of Energy, National Nuclear Security Administration Nevada Site Office is in the process of assessing and developing regulatory decision options based on modeling predictions of contaminant transport from underground testing of nuclear weapons at the Nevada Test Site (NTS). The UGTA Project is attempting to develop an effective modeling strategy that addresses and quantifies multiple components of uncertainty including natural variability, parameter uncertainty, conceptual/model uncertainty, and decision uncertainty in translating model results into regulatory requirements. The modeling task presents multiple unique challenges to the hydrological sciences as a result ofmore » the complex fractured and faulted hydrostratigraphy, the distributed locations of sources, the suite of reactive and non-reactive radionuclides, and uncertainty in conceptual models. Characterization of the hydrogeologic system is difficult and expensive because of deep groundwater in the arid desert setting and the large spatial setting of the NTS. Therefore, conceptual model uncertainty is partially addressed through the development of multiple alternative conceptual models of the hydrostratigraphic framework and multiple alternative models of recharge and discharge. Uncertainty in boundary conditions is assessed through development of alternative groundwater fluxes through multiple simulations using the regional groundwater flow model. Calibration of alternative models to heads and measured or inferred fluxes has not proven to provide clear measures of model quality. Therefore, model screening by comparison to independently-derived natural geochemical mixing targets through cluster analysis has also been invoked to evaluate differences between alternative conceptual models. Advancing multiple alternative flow models, sensitivity of transport predictions to parameter uncertainty is assessed through Monte Carlo simulations. The simulations are challenged by the distributed sources in each of the Corrective Action Units, by complex mass transfer processes, and by the size and complexity of the field-scale flow models. An efficient methodology utilizing particle tracking results and convolution integrals provides in situ concentrations appropriate for Monte Carlo analysis. Uncertainty in source releases and transport parameters including effective porosity, fracture apertures and spacing, matrix diffusion coefficients, sorption coefficients, and colloid load and mobility are considered. With the distributions of input uncertainties and output plume volumes, global analysis methods including stepwise regression, contingency table analysis, and classification tree analysis are used to develop sensitivity rankings of parameter uncertainties for each model considered, thus assisting a variety of decisions.« less
-
Lattice Entertain You: Paper Modeling of the 14 Bravais Lattices on Youtube
ERIC Educational Resources Information Center
Sein, Lawrence T., Jr.; Sein, Sarajane E.
2015-01-01
A system for the construction of double-sided paper models of the 14 Bravais lattices, and important crystal structures derived from them, is described. The system allows the combination of multiple unit cells, so as to better represent the overall three-dimensional structure. Students and instructors can view the models in use on the popular…
-
Optimal allocation model of construction land based on two-level system optimization theory
NASA Astrophysics Data System (ADS)
Liu, Min; Liu, Yanfang; Xia, Yuping; Lei, Qihong
2007-06-01
The allocation of construction land is an important task in land-use planning. Whether implementation of planning decisions is a success or not, usually depends on a reasonable and scientific distribution method. Considering the constitution of land-use planning system and planning process in China, multiple levels and multiple objective decision problems is its essence. Also, planning quantity decomposition is a two-level system optimization problem and an optimal resource allocation decision problem between a decision-maker in the topper and a number of parallel decision-makers in the lower. According the characteristics of the decision-making process of two-level decision-making system, this paper develops an optimal allocation model of construction land based on two-level linear planning. In order to verify the rationality and the validity of our model, Baoan district of Shenzhen City has been taken as a test case. Under the assistance of the allocation model, construction land is allocated to ten townships of Baoan district. The result obtained from our model is compared to that of traditional method, and results show that our model is reasonable and usable. In the end, the paper points out the shortcomings of the model and further research directions.
-
Wind Power Forecasting Error Distributions over Multiple Timescales: Preprint
DOE Office of Scientific and Technical Information (OSTI.GOV)
Hodge, B. M.; Milligan, M.
2011-03-01
In this paper, we examine the shape of the persistence model error distribution for ten different wind plants in the ERCOT system over multiple timescales. Comparisons are made between the experimental distribution shape and that of the normal distribution.
-
Real-time separation of multineuron recordings with a DSP32C signal processor.
Gädicke, R; Albus, K
1995-04-01
We have developed a hardware and software package for real-time discrimination of multiple-unit activities recorded simultaneously from multiple microelectrodes using a VME-Bus system. Compared with other systems cited in literature or commercially available, our system has the following advantages. (1) Each electrode is served by its own preprocessor (DSP32C); (2) On-line spike discrimination is performed independently for each electrode. (3) The VME-bus allows processing of data received from 16 electrodes. The digitized (62.5 kHz) spike form is itself used as the model spike; the algorithm allows for comparing and sorting complete wave forms in real time into 8 different models per electrode.
-
A multi-scale approach to designing therapeutics for tuberculosis
DOE Office of Scientific and Technical Information (OSTI.GOV)
Linderman, Jennifer J.; Cilfone, Nicholas A.; Pienaar, Elsje
Approximately one third of the world’s population is infected with Mycobacterium tuberculosis. Limited information about how the immune system fights M. tuberculosis and what constitutes protection from the bacteria impact our ability to develop effective therapies for tuberculosis. We present an in vivo systems biology approach that integrates data from multiple model systems and over multiple length and time scales into a comprehensive multi-scale and multi-compartment view of the in vivo immune response to M. tuberculosis. Lastly, we describe computational models that can be used to study (a) immunomodulation with the cytokines tumor necrosis factor and interleukin 10, (b) oralmore » and inhaled antibiotics, and (c) the effect of vaccination.« less
-
Simulation and analysis of main steam control system based on heat transfer calculation
NASA Astrophysics Data System (ADS)
Huang, Zhenqun; Li, Ruyan; Feng, Zhongbao; Wang, Songhan; Li, Wenbo; Cheng, Jiwei; Jin, Yingai
2018-05-01
In this paper, after thermal power plant 300MW boiler was studied, mat lab was used to write calculation program about heat transfer process between the main steam and boiler flue gas and amount of water was calculated to ensure the main steam temperature keeping in target temperature. Then heat transfer calculation program was introduced into Simulink simulation platform based on control system multiple models switching and heat transfer calculation. The results show that multiple models switching control system based on heat transfer calculation not only overcome the large inertia of main stream temperature, a large hysteresis characteristic of main stream temperature, but also adapted to the boiler load changing.
-
A multi-scale approach to designing therapeutics for tuberculosis
Linderman, Jennifer J.; Cilfone, Nicholas A.; Pienaar, Elsje; ...
2015-04-20
Approximately one third of the world’s population is infected with Mycobacterium tuberculosis. Limited information about how the immune system fights M. tuberculosis and what constitutes protection from the bacteria impact our ability to develop effective therapies for tuberculosis. We present an in vivo systems biology approach that integrates data from multiple model systems and over multiple length and time scales into a comprehensive multi-scale and multi-compartment view of the in vivo immune response to M. tuberculosis. Lastly, we describe computational models that can be used to study (a) immunomodulation with the cytokines tumor necrosis factor and interleukin 10, (b) oralmore » and inhaled antibiotics, and (c) the effect of vaccination.« less
-
ERIC Educational Resources Information Center
Brethower, Karen S.; Rummler, Geary A.
1979-01-01
Presents general systems models (ballistic system, guided system, and adaptive system) and an evaluation matrix to help in examining training evaluation alternatives and in deciding what evaluation is appropriate. Includes some guidelines for conducting evaluation studies using four designs (control group, reversal, multiple baseline, and…
-
A Single-System Account of the Relationship between Priming, Recognition, and Fluency
ERIC Educational Resources Information Center
Berry, Christopher J.; Shanks, David R.; Henson, Richard N. A.
2008-01-01
A single-system computational model of priming and recognition was applied to studies that have looked at the relationship between priming, recognition, and fluency in continuous identification paradigms. The model was applied to 3 findings that have been interpreted as evidence for a multiple-systems account: (a) priming can occur for items not…
-
The Relationship Between Diversity and Accuracy in Multiple Classifier Systems
2012-03-22
Density plot of Residuals, Accuracy + Diversity model resids de ns ity 0 5 10 15 20 25 −0.3 −0.2 −0.1 0.0 0.1 other main assumption that must be met is that...The Relationship Between Diversity and Accuracy in Multiple Classifier Systems THESIS Harris K. Butler, Second Lieutenant, USAF AFIT-OR-MS-ENS-12-05...be used to imply or infer actual mission capability or limitations. AFIT-OR-MS-ENS-12-05 THE RELATIONSHIP BETWEEN DIVERSITY AND ACCURACY IN MULTIPLE
-
A COMPARISON OF INTERCELL METRICS ON DISCRETE GLOBAL GRID SYSTEMS
A discrete global grid system (DGGS) is a spatial data model that aids in global research by serving as a framework for environmental modeling, monitoring and sampling across the earth at multiple spatial scales. Topological and geometric criteria have been proposed to evaluate a...
-
The Money-Creation Model: Another Pedagogy.
ERIC Educational Resources Information Center
Gamble, Ralph C., Jr.
1991-01-01
Describes graphical techniques to help explain the multiple creation of deposits that accompany lending in a fractional reserve banking system. Presents a model that emphasizes the banking system, the interaction of total permitted, required, and excess reserves and deposits. Argues that the approach simplifies information to examining a slope…
-
The EPA's Office of Research and Development is embarking on a long term project to develop a Multimedia Integrated Modeling System (MIMS). The system will have capabilities to represent the transport and fate of nutrients and chemical stressors over multiple scales. MIMS will ...
-
Diffusion of multiple species with excluded-volume effects.
Bruna, Maria; Chapman, S Jonathan
2012-11-28
Stochastic models of diffusion with excluded-volume effects are used to model many biological and physical systems at a discrete level. The average properties of the population may be described by a continuum model based on partial differential equations. In this paper we consider multiple interacting subpopulations/species and study how the inter-species competition emerges at the population level. Each individual is described as a finite-size hard core interacting particle undergoing brownian motion. The link between the discrete stochastic equations of motion and the continuum model is considered systematically using the method of matched asymptotic expansions. The system for two species leads to a nonlinear cross-diffusion system for each subpopulation, which captures the enhancement of the effective diffusion rate due to excluded-volume interactions between particles of the same species, and the diminishment due to particles of the other species. This model can explain two alternative notions of the diffusion coefficient that are often confounded, namely collective diffusion and self-diffusion. Simulations of the discrete system show good agreement with the analytic results.
-
Markov chains for testing redundant software
NASA Technical Reports Server (NTRS)
White, Allan L.; Sjogren, Jon A.
1988-01-01
A preliminary design for a validation experiment has been developed that addresses several problems unique to assuring the extremely high quality of multiple-version programs in process-control software. The procedure uses Markov chains to model the error states of the multiple version programs. The programs are observed during simulated process-control testing, and estimates are obtained for the transition probabilities between the states of the Markov chain. The experimental Markov chain model is then expanded into a reliability model that takes into account the inertia of the system being controlled. The reliability of the multiple version software is computed from this reliability model at a given confidence level using confidence intervals obtained for the transition probabilities during the experiment. An example demonstrating the method is provided.
-
Multiple-time scales analysis of physiological time series under neural control
NASA Technical Reports Server (NTRS)
Peng, C. K.; Hausdorff, J. M.; Havlin, S.; Mietus, J. E.; Stanley, H. E.; Goldberger, A. L.
1998-01-01
We discuss multiple-time scale properties of neurophysiological control mechanisms, using heart rate and gait regulation as model systems. We find that scaling exponents can be used as prognostic indicators. Furthermore, detection of more subtle degradation of scaling properties may provide a novel early warning system in subjects with a variety of pathologies including those at high risk of sudden death.
-
A video, text, and speech-driven realistic 3-d virtual head for human-machine interface.
Yu, Jun; Wang, Zeng-Fu
2015-05-01
A multiple inputs-driven realistic facial animation system based on 3-D virtual head for human-machine interface is proposed. The system can be driven independently by video, text, and speech, thus can interact with humans through diverse interfaces. The combination of parameterized model and muscular model is used to obtain a tradeoff between computational efficiency and high realism of 3-D facial animation. The online appearance model is used to track 3-D facial motion from video in the framework of particle filtering, and multiple measurements, i.e., pixel color value of input image and Gabor wavelet coefficient of illumination ratio image, are infused to reduce the influence of lighting and person dependence for the construction of online appearance model. The tri-phone model is used to reduce the computational consumption of visual co-articulation in speech synchronized viseme synthesis without sacrificing any performance. The objective and subjective experiments show that the system is suitable for human-machine interaction.
-
Simultaneous Excitation of Multiple-Input Multiple-Output CFD-Based Unsteady Aerodynamic Systems
NASA Technical Reports Server (NTRS)
Silva, Walter A.
2008-01-01
A significant improvement to the development of CFD-based unsteady aerodynamic reduced-order models (ROMs) is presented. This improvement involves the simultaneous excitation of the structural modes of the CFD-based unsteady aerodynamic system that enables the computation of the unsteady aerodynamic state-space model using a single CFD execution, independent of the number of structural modes. Four different types of inputs are presented that can be used for the simultaneous excitation of the structural modes. Results are presented for a flexible, supersonic semi-span configuration using the CFL3Dv6.4 code.
-
Simultaneous Excitation of Multiple-Input Multiple-Output CFD-Based Unsteady Aerodynamic Systems
NASA Technical Reports Server (NTRS)
Silva, Walter A.
2007-01-01
A significant improvement to the development of CFD-based unsteady aerodynamic reduced-order models (ROMs) is presented. This improvement involves the simultaneous excitation of the structural modes of the CFD-based unsteady aerodynamic system that enables the computation of the unsteady aerodynamic state-space model using a single CFD execution, independent of the number of structural modes. Four different types of inputs are presented that can be used for the simultaneous excitation of the structural modes. Results are presented for a flexible, supersonic semi-span configuration using the CFL3Dv6.4 code.
-
NASA Technical Reports Server (NTRS)
Berrier, B. L.; Leavitt, L. D.; Bangert, L. S.
1985-01-01
An investigation has been conducted in the Langley 16 Foot Transonic Tunnel to determine the weight flow measurement characteristics of a multiple critical Venturi system and the nozzle discharge coefficient characteristics of a series of convergent calibration nozzles. The effects on model discharge coefficient of nozzle throat area, model choke plate open area, nozzle pressure ratio, jet total temperature, and number and combination of operating Venturis were investigated. Tests were conducted at static conditions (tunnel wind off) at nozzle pressure ratios from 1.3 to 7.0.
-
NASA Astrophysics Data System (ADS)
Si, Y.; Cai, X.
2017-12-01
The large-scale reservoir system built on the upper Yellow River serves multiple purposes. The generated hydropower supplies over 60% of the entire electricity for the regional power grid while the irrigated crop production feeds almost one-third of the total population throughout the whole river basin. Moreover, the reservoir system also bears the responsibility for controlling ice flood, which occurs during the non-flood season due to winter ice freezing followed by spring thawing process, and could be even more disastrous than the summer flood. The contradiction of water allocation to satisfy multi-sector demands while mitigating ice flood risk has been longstanding. However, few researchers endeavor to employ the nexus thinking to addressing the complexities involved in all the interlinked purposes. In this study, we develop an integrated hydro-economic model that can be used to explore both the tradeoffs and synergies between the multiple purposes, based on which the water infrastructures (e.g., reservoir, diversion canal, pumping well) can be coordinated for maximizing the co-benefits of multiple sectors. The model is based on a node-link schematic of multiple operations including hydropower generation, irrigation scheduling, and the conjunctive use of surface and ground water resources. In particular, the model depicts some details regarding reservoir operation rules during the ice season using two indicators, i.e., flow control period and flow control level. The rules are obtained from historical records using data mining techniques under different climate conditions, and they are added to the model as part of the system constraints. Future reservoir inflow series are generated by a hydrological model with future climate scenarios projected by General Circulation Model (GCM). By analyzing the model results under the various climate scenarios, the future possible shifting trajectory of the food-energy-water system characteristics will be derived compared to the baseline scenario (i.e., the status-quo condition). Thus the model and the results are expected to be useful for enlightening economically efficient water allocation policy coping with climate change.
-
An efficient approach to ARMA modeling of biological systems with multiple inputs and delays
NASA Technical Reports Server (NTRS)
Perrott, M. H.; Cohen, R. J.
1996-01-01
This paper presents a new approach to AutoRegressive Moving Average (ARMA or ARX) modeling which automatically seeks the best model order to represent investigated linear, time invariant systems using their input/output data. The algorithm seeks the ARMA parameterization which accounts for variability in the output of the system due to input activity and contains the fewest number of parameters required to do so. The unique characteristics of the proposed system identification algorithm are its simplicity and efficiency in handling systems with delays and multiple inputs. We present results of applying the algorithm to simulated data and experimental biological data In addition, a technique for assessing the error associated with the impulse responses calculated from estimated ARMA parameterizations is presented. The mapping from ARMA coefficients to impulse response estimates is nonlinear, which complicates any effort to construct confidence bounds for the obtained impulse responses. Here a method for obtaining a linearization of this mapping is derived, which leads to a simple procedure to approximate the confidence bounds.
-
Protein (multi-)location prediction: utilizing interdependencies via a generative model
Shatkay, Hagit
2015-01-01
Motivation: Proteins are responsible for a multitude of vital tasks in all living organisms. Given that a protein’s function and role are strongly related to its subcellular location, protein location prediction is an important research area. While proteins move from one location to another and can localize to multiple locations, most existing location prediction systems assign only a single location per protein. A few recent systems attempt to predict multiple locations for proteins, however, their performance leaves much room for improvement. Moreover, such systems do not capture dependencies among locations and usually consider locations as independent. We hypothesize that a multi-location predictor that captures location inter-dependencies can improve location predictions for proteins. Results: We introduce a probabilistic generative model for protein localization, and develop a system based on it—which we call MDLoc—that utilizes inter-dependencies among locations to predict multiple locations for proteins. The model captures location inter-dependencies using Bayesian networks and represents dependency between features and locations using a mixture model. We use iterative processes for learning model parameters and for estimating protein locations. We evaluate our classifier MDLoc, on a dataset of single- and multi-localized proteins derived from the DBMLoc dataset, which is the most comprehensive protein multi-localization dataset currently available. Our results, obtained by using MDLoc, significantly improve upon results obtained by an initial simpler classifier, as well as on results reported by other top systems. Availability and implementation: MDLoc is available at: http://www.eecis.udel.edu/∼compbio/mdloc. Contact: shatkay@udel.edu. PMID:26072505
-
Protein (multi-)location prediction: utilizing interdependencies via a generative model.
Simha, Ramanuja; Briesemeister, Sebastian; Kohlbacher, Oliver; Shatkay, Hagit
2015-06-15
Proteins are responsible for a multitude of vital tasks in all living organisms. Given that a protein's function and role are strongly related to its subcellular location, protein location prediction is an important research area. While proteins move from one location to another and can localize to multiple locations, most existing location prediction systems assign only a single location per protein. A few recent systems attempt to predict multiple locations for proteins, however, their performance leaves much room for improvement. Moreover, such systems do not capture dependencies among locations and usually consider locations as independent. We hypothesize that a multi-location predictor that captures location inter-dependencies can improve location predictions for proteins. We introduce a probabilistic generative model for protein localization, and develop a system based on it-which we call MDLoc-that utilizes inter-dependencies among locations to predict multiple locations for proteins. The model captures location inter-dependencies using Bayesian networks and represents dependency between features and locations using a mixture model. We use iterative processes for learning model parameters and for estimating protein locations. We evaluate our classifier MDLoc, on a dataset of single- and multi-localized proteins derived from the DBMLoc dataset, which is the most comprehensive protein multi-localization dataset currently available. Our results, obtained by using MDLoc, significantly improve upon results obtained by an initial simpler classifier, as well as on results reported by other top systems. MDLoc is available at: http://www.eecis.udel.edu/∼compbio/mdloc. © The Author 2015. Published by Oxford University Press.
-
Are Binary Separations related to their System Mass?
NASA Astrophysics Data System (ADS)
Sterzik, M. F.; Durisen, R. H.
2004-08-01
We compile most recent multiplicity fractions and binary separation distributions for different primary masses, including very low-mass and brown dwarf primaries, and compare them with dynamical decay models of small-N clusters. The model predictions are based on detailed numerical calculations of the internal cluster dynamics, as well as on Monte-Carlo methods. Both observations and models reflect the same trends: (1) The multiplicity fraction is an increasing function of the primary mass. (2) The mean binary separations are increasing with the system mass in the sense that very low-mass binaries have average separations around ≈ 4AU, while the binary separation distribution for solar-type primaries peaks at ≈ 40AU. M-type binary systems apparently preferentially populate intermediate separations. Similar specific energy at the time of cluster formation for all cluster masses can possibly explain this trend.
-
Efstathiou, Christos; Isukapalli, Sastry
2011-01-01
Allergic airway diseases represent a complex health problem which can be exacerbated by the synergistic action of pollen particles and air pollutants such as ozone. Understanding human exposures to aeroallergens requires accurate estimates of the spatial distribution of airborne pollen levels as well as of various air pollutants at different times. However, currently there are no established methods for estimating allergenic pollen emissions and concentrations over large geographic areas such as the United States. A mechanistic modeling system for describing pollen emissions and transport over extensive domains has been developed by adapting components of existing regional scale air quality models and vegetation databases. First, components of the Biogenic Emissions Inventory System (BEIS) were adapted to predict pollen emission patterns. Subsequently, the transport module of the Community Multiscale Air Quality (CMAQ) modeling system was modified to incorporate description of pollen transport. The combined model, CMAQ-pollen, allows for simultaneous prediction of multiple air pollutants and pollen levels in a single model simulation, and uses consistent assumptions related to the transport of multiple chemicals and pollen species. Application case studies for evaluating the combined modeling system included the simulation of birch and ragweed pollen levels for the year 2002, during their corresponding peak pollination periods (April for birch and September for ragweed). The model simulations were driven by previously evaluated meteorological model outputs and emissions inventories for the eastern United States for the simulation period. A semi-quantitative evaluation of CMAQ-pollen was performed using tree and ragweed pollen counts in Newark, NJ for the same time periods. The peak birch pollen concentrations were predicted to occur within two days of the peak measurements, while the temporal patterns closely followed the measured profiles of overall tree pollen. For the case of ragweed pollen, the model was able to capture the patterns observed during September 2002, but did not predict an early peak; this can be associated with a wider species pollination window and inadequate spatial information in current land cover databases. An additional sensitivity simulation was performed to comparatively evaluate the dispersion patterns predicted by CMAQ-pollen with those predicted by the Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) model, which is used extensively in aerobiological studies. The CMAQ estimated concentration plumes matched the equivalent pollen scenario modeled with HYSPLIT. The novel pollen modeling approach presented here allows simultaneous estimation of multiple airborne allergens and other air pollutants, and is being developed as a central component of an integrated population exposure modeling system, the Modeling Environment for Total Risk studies (MENTOR) for multiple, co-occurring contaminants that include aeroallergens and irritants. PMID:21516207
-
NASA Astrophysics Data System (ADS)
Efstathiou, Christos; Isukapalli, Sastry; Georgopoulos, Panos
2011-04-01
Allergic airway diseases represent a complex health problem which can be exacerbated by the synergistic action of pollen particles and air pollutants such as ozone. Understanding human exposures to aeroallergens requires accurate estimates of the spatial distribution of airborne pollen levels as well as of various air pollutants at different times. However, currently there are no established methods for estimating allergenic pollen emissions and concentrations over large geographic areas such as the United States. A mechanistic modeling system for describing pollen emissions and transport over extensive domains has been developed by adapting components of existing regional scale air quality models and vegetation databases. First, components of the Biogenic Emissions Inventory System (BEIS) were adapted to predict pollen emission patterns. Subsequently, the transport module of the Community Multiscale Air Quality (CMAQ) modeling system was modified to incorporate description of pollen transport. The combined model, CMAQ-pollen, allows for simultaneous prediction of multiple air pollutants and pollen levels in a single model simulation, and uses consistent assumptions related to the transport of multiple chemicals and pollen species. Application case studies for evaluating the combined modeling system included the simulation of birch and ragweed pollen levels for the year 2002, during their corresponding peak pollination periods (April for birch and September for ragweed). The model simulations were driven by previously evaluated meteorological model outputs and emissions inventories for the eastern United States for the simulation period. A semi-quantitative evaluation of CMAQ-pollen was performed using tree and ragweed pollen counts in Newark, NJ for the same time periods. The peak birch pollen concentrations were predicted to occur within two days of the peak measurements, while the temporal patterns closely followed the measured profiles of overall tree pollen. For the case of ragweed pollen, the model was able to capture the patterns observed during September 2002, but did not predict an early peak; this can be associated with a wider species pollination window and inadequate spatial information in current land cover databases. An additional sensitivity simulation was performed to comparatively evaluate the dispersion patterns predicted by CMAQ-pollen with those predicted by the Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) model, which is used extensively in aerobiological studies. The CMAQ estimated concentration plumes matched the equivalent pollen scenario modeled with HYSPLIT. The novel pollen modeling approach presented here allows simultaneous estimation of multiple airborne allergens and other air pollutants, and is being developed as a central component of an integrated population exposure modeling system, the Modeling Environment for Total Risk studies (MENTOR) for multiple, co-occurring contaminants that include aeroallergens and irritants.
-
Collaborative Research: Robust Climate Projections and Stochastic Stability of Dynamical Systems
DOE Office of Scientific and Technical Information (OSTI.GOV)
Ilya Zaliapin
This project focused on conceptual exploration of El Nino/Southern Oscillation (ENSO) variability and sensitivity using a Delay Differential Equation developed in the project. We have (i) established the existence and continuous dependence of solutions of the model (ii) explored multiple models solutions, and the distribution of solutions extrema, and (iii) established and explored the phase locking phenomenon and the existence of multiple solutions for the same values of model parameters. In addition, we have applied to our model the concept of pullback attractor, which greatly facilitated predictive understanding of the nonlinear model's behavior.
-
Spacecraft Multiple Array Communication System Performance Analysis
NASA Technical Reports Server (NTRS)
Hwu, Shian U.; Desilva, Kanishka; Sham, Catherine C.
2010-01-01
The Communication Systems Simulation Laboratory (CSSL) at the NASA Johnson Space Center is tasked to perform spacecraft and ground network communication system simulations, design validation, and performance verification. The CSSL has developed simulation tools that model spacecraft communication systems and the space and ground environment in which the tools operate. In this paper, a spacecraft communication system with multiple arrays is simulated. Multiple array combined technique is used to increase the radio frequency coverage and data rate performance. The technique is to achieve phase coherence among the phased arrays to combine the signals at the targeting receiver constructively. There are many technical challenges in spacecraft integration with a high transmit power communication system. The array combining technique can improve the communication system data rate and coverage performances without increasing the system transmit power requirements. Example simulation results indicate significant performance improvement can be achieved with phase coherence implementation.
-
NASA Astrophysics Data System (ADS)
Ferreira, David; Marshall, John; Ito, Takamitsu; McGee, David; Moreno-Chamarro, Eduardo
2017-04-01
The dynamics regulating large climatic transitions such as glacial-interglacial cycles or DO events remains a puzzle. Forcings behind these transitions are not robustly identified and potential candidates (e.g. Milankovitch cycles, freshwater perturbations) often appear too weak to explain such dramatic transitions. A potential solution to this long-standing puzzle is that Earth's climate is endowed with multiple equilibrium states of global extent. Such states are commonly found in low-order or conceptual climate models, but it is unclear whether a system as complex as Earth's climate can sustain multiple equilibrium states. Here we report that multiple equilibrium states of the climate system are also possible in a complex, fully dynamical coupled ocean-atmosphere-sea ice GCM with idealized Earth-like geometry, resolved weather systems and a hydrological cycle. In our model, two equilibrium states coexist for the same parameters and external forcings: a Warm climate with a small Northern hemisphere sea ice cap and a large southern one and a Cold climate with large ice caps at both poles. The dynamical states of the Warm and Cold solutions exhibit striking similarities with our present-day climate and the climate of the Last Glacial Maximum, respectively. A carbon cycle model driven by the two dynamical states produces an atmospheric pCO2 draw-down of about 110 pm between the Warm and Cold states, close to Glacial-Interglacial differences found in ice cores. Mechanism controlling the existence of the multiple states and changes in the atmospheric CO2 will be briefly presented. Finally we willdescribe transition experiments from the Cold to the Warm state, focusing on the lead-lags in the system, notably between the Northern and Southern Hemispheres climates.
-
Zhu; Dale
2000-10-01
/ Regional resource use planning relies on key regional stakeholder groups using and having equitable access to appropriate social, economic, and environmental information and assessment tools. Decision support systems (DSS) can improve stakeholder access to such information and analysis tools. Regional resource use planning, however, is a complex process involving multiple issues, multiple assessment criteria, multiple stakeholders, and multiple values. There is a need for an approach to DSS development that can assist in understanding and modeling complex problem situations in regional resource use so that areas where DSSs could provide effective support can be identified, and the user requirements can be well established. This paper presents an approach based on the soft systems methodology for identifying DSS opportunities for regional resource use planning, taking the Central Highlands Region of Queensland, Australia, as a case study.
-
NASA Technical Reports Server (NTRS)
Wang, C.-W.; Stark, W.
2005-01-01
This article considers a quaternary direct-sequence code-division multiple-access (DS-CDMA) communication system with asymmetric quadrature phase-shift-keying (AQPSK) modulation for unequal error protection (UEP) capability. Both time synchronous and asynchronous cases are investigated. An expression for the probability distribution of the multiple-access interference is derived. The exact bit-error performance and the approximate performance using a Gaussian approximation and random signature sequences are evaluated by extending the techniques used for uniform quadrature phase-shift-keying (QPSK) and binary phase-shift-keying (BPSK) DS-CDMA systems. Finally, a general system model with unequal user power and the near-far problem is considered and analyzed. The results show that, for a system with UEP capability, the less protected data bits are more sensitive to the near-far effect that occurs in a multiple-access environment than are the more protected bits.
-
ERIC Educational Resources Information Center
Fuller, C. A.
A breadboard model of a laser display system is described in detail and its operating procedure is outlined. The system consists of: a Model 52 argon krypton ion laser and power supply; an optical breadboard comprising a pocket cell light modulator, a galvonmeter beam deflector for vertical scanning, a unique multiple reflection beam steerer for…
-
We demonstrate a novel, spatially explicit assessment of the current condition of aquatic ecosystem services, with limited sensitivity analysis for the atmospheric contaminant mercury. The Integrated Ecological Modeling System (IEMS) forecasts water quality and quantity, habitat ...
-
TOWARD A DETERMINISTIC MODEL OF PLANETARY FORMATION. VII. ECCENTRICITY DISTRIBUTION OF GAS GIANTS
DOE Office of Scientific and Technical Information (OSTI.GOV)
Ida, S.; Lin, D. N. C.; Nagasawa, M., E-mail: ida@geo.titech.ac.jp, E-mail: lin@ucolick.org, E-mail: nagasawa.m.ad@m.titech.ac.jp
2013-09-20
The ubiquity of planets and diversity of planetary systems reveal that planet formation encompasses many complex and competing processes. In this series of papers, we develop and upgrade a population synthesis model as a tool to identify the dominant physical effects and to calibrate the range of physical conditions. Recent planet searches have led to the discovery of many multiple-planet systems. Any theoretical models of their origins must take into account dynamical interactions between emerging protoplanets. Here, we introduce a prescription to approximate the close encounters between multiple planets. We apply this method to simulate the growth, migration, and dynamicalmore » interaction of planetary systems. Our models show that in relatively massive disks, several gas giants and rocky/icy planets emerge, migrate, and undergo dynamical instability. Secular perturbation between planets leads to orbital crossings, eccentricity excitation, and planetary ejection. In disks with modest masses, two or less gas giants form with multiple super-Earths. Orbital stability in these systems is generally maintained and they retain the kinematic structure after gas in their natal disks is depleted. These results reproduce the observed planetary mass-eccentricity and semimajor axis-eccentricity correlations. They also suggest that emerging gas giants can scatter residual cores to the outer disk regions. Subsequent in situ gas accretion onto these cores can lead to the formation of distant (∼> 30 AU) gas giants with nearly circular orbits.« less
-
Building Mental Models by Dissecting Physical Models
ERIC Educational Resources Information Center
Srivastava, Anveshna
2016-01-01
When students build physical models from prefabricated components to learn about model systems, there is an implicit trade-off between the physical degrees of freedom in building the model and the intensity of instructor supervision needed. Models that are too flexible, permitting multiple possible constructions require greater supervision to…
-
Mutual Coupling and Compensation in FMCW MIMO Radar Systems
NASA Astrophysics Data System (ADS)
Schmid, Christian M.; Feger, Reinhard; Wagner, Christoph; Stelzer, Andreas
2011-09-01
This paper deals with mutual coupling, its effects and the compensation thereof in frequency-modulated continuous-wave (FMCW) multiple-input multiple-output (MIMO) array radar systems. Starting with a signal model we introduce mutual coupling and its primary sources in FMCW MIMO systems. We also give a worst-case boundary of the effects that mutual coupling can have on the side lobe level of an array. A method of dealing with and compensating for these effects is covered in this paper and verified by measurements from a 77-GHz FMCW radar system.
-
Multi-objective optimization for generating a weighted multi-model ensemble
NASA Astrophysics Data System (ADS)
Lee, H.
2017-12-01
Many studies have demonstrated that multi-model ensembles generally show better skill than each ensemble member. When generating weighted multi-model ensembles, the first step is measuring the performance of individual model simulations using observations. There is a consensus on the assignment of weighting factors based on a single evaluation metric. When considering only one evaluation metric, the weighting factor for each model is proportional to a performance score or inversely proportional to an error for the model. While this conventional approach can provide appropriate combinations of multiple models, the approach confronts a big challenge when there are multiple metrics under consideration. When considering multiple evaluation metrics, it is obvious that a simple averaging of multiple performance scores or model ranks does not address the trade-off problem between conflicting metrics. So far, there seems to be no best method to generate weighted multi-model ensembles based on multiple performance metrics. The current study applies the multi-objective optimization, a mathematical process that provides a set of optimal trade-off solutions based on a range of evaluation metrics, to combining multiple performance metrics for the global climate models and their dynamically downscaled regional climate simulations over North America and generating a weighted multi-model ensemble. NASA satellite data and the Regional Climate Model Evaluation System (RCMES) software toolkit are used for assessment of the climate simulations. Overall, the performance of each model differs markedly with strong seasonal dependence. Because of the considerable variability across the climate simulations, it is important to evaluate models systematically and make future projections by assigning optimized weighting factors to the models with relatively good performance. Our results indicate that the optimally weighted multi-model ensemble always shows better performance than an arithmetic ensemble mean and may provide reliable future projections.
-
Tang, Ai-Hui; Wang, Shi-Qiang
2009-01-01
Spiral patterns have been found in various nonequilibrium systems. The Ca2+-induced Ca2+ release system in single cardiac cells is unique for highly discrete reaction elements, each giving rise to a Ca2+ spark upon excitation. We imaged the spiral Ca2+ waves in isolated cardiac cells and numerically studied the effect of system excitability on spiral patterns using a two-dimensional fire-diffuse-fire model. We found that under certain conditions, the system was able to display multiple stable patterns of spiral waves, each exhibiting different periods and distinct routines of spiral tips. Transition between these different patterns could be triggered by an internal fluctuation in the form of a single Ca2+ spark. PMID:19792039
-
Tang, Ai-Hui; Wang, Shi-Qiang
2009-09-01
Spiral patterns have been found in various nonequilibrium systems. The Ca(2+)-induced Ca(2+) release system in single cardiac cells is unique for highly discrete reaction elements, each giving rise to a Ca(2+) spark upon excitation. We imaged the spiral Ca(2+) waves in isolated cardiac cells and numerically studied the effect of system excitability on spiral patterns using a two-dimensional fire-diffuse-fire model. We found that under certain conditions, the system was able to display multiple stable patterns of spiral waves, each exhibiting different periods and distinct routines of spiral tips. Transition between these different patterns could be triggered by an internal fluctuation in the form of a single Ca(2+) spark.
-
Performance analysis of cross-seeding WDM-PON system using transfer matrix method
NASA Astrophysics Data System (ADS)
Simatupang, Joni Welman; Pukhrambam, Puspa Devi; Huang, Yen-Ru
2016-12-01
In this paper, a model based on the transfer matrix method is adopted to analyze the effects of Rayleigh backscattering and Fresnel multiple reflections on a cross-seeding WDM-PON system. As part of analytical approximation methods, this time-independent model is quite simple but very efficient when it is applied to various WDM-PON transmission systems, including the cross-seeding scheme. The cross seeding scheme is most beneficial for systems with low loop-back ONU gain or low reflection loss at the drop fiber for upstream data in bidirectional transmission. However for downstream data transmission, multiple reflections power could destroy the usefulness of the cross-seeding scheme when the reflectivity is high enough and the RN is positioned near OLT or close to ONU.
-
Gain-scheduling multivariable LPV control of an irrigation canal system.
Bolea, Yolanda; Puig, Vicenç
2016-07-01
The purpose of this paper is to present a multivariable linear parameter varying (LPV) controller with a gain scheduling Smith Predictor (SP) scheme applicable to open-flow canal systems. This LPV controller based on SP is designed taking into account the uncertainty in the estimation of delay and the variation of plant parameters according to the operating point. This new methodology can be applied to a class of delay systems that can be represented by a set of models that can be factorized into a rational multivariable model in series with left/right diagonal (multiple) delays, such as, the case of irrigation canals. A multiple pool canal system is used to test and validate the proposed control approach. Copyright © 2016 ISA. Published by Elsevier Ltd. All rights reserved.
-
NASA Astrophysics Data System (ADS)
Tatomir, Alexandru Bogdan A. C.; Flemisch, Bernd; Class, Holger; Helmig, Rainer; Sauter, Martin
2017-04-01
Geological storage of CO2 represents one viable solution to reduce greenhouse gas emission in the atmosphere. Potential leakage of CO2 storage can occur through networks of interconnected fractures. The geometrical complexity of these networks is often very high involving fractures occurring at various scales and having hierarchical structures. Such multiphase flow systems are usually hard to solve with a discrete fracture modelling (DFM) approach. Therefore, continuum fracture models assuming average properties are usually preferred. The multiple interacting continua (MINC) model is an extension of the classic double porosity model (Warren and Root, 1963) which accounts for the non-linear behaviour of the matrix-fracture interactions. For CO2 storage applications the transient representation of the inter-porosity two phase flow plays an important role. This study tests the accuracy and computational efficiency of the MINC method complemented with the multiple sub-region (MSR) upscaling procedure versus the DFM. The two phase flow MINC simulator is implemented in the free-open source numerical toolbox DuMux (www.dumux.org). The MSR (Gong et al., 2009) determines the inter-porosity terms by solving simplified local single-phase flow problems. The DFM is considered as the reference solution. The numerical examples consider a quasi-1D reservoir with a quadratic fracture system , a five-spot radial symmetric reservoir, and a completely random generated fracture system. Keywords: MINC, upscaling, two-phase flow, fractured porous media, discrete fracture model, continuum fracture model
-
NASA Astrophysics Data System (ADS)
Zhu, Q.; Riley, W. J.; Tang, J.; Koven, C. D.
2015-03-01
Soil is a complex system where biotic (e.g., plant roots, micro-organisms) and abiotic (e.g., mineral surfaces) consumers compete for resources necessary for life (e.g., nitrogen, phosphorus). This competition is ecologically significant, since it regulates the dynamics of soil nutrients and controls aboveground plant productivity. Here we develop, calibrate, and test a nutrient competition model that accounts for multiple soil nutrients interacting with multiple biotic and abiotic consumers. As applied here for tropical forests, the Nutrient COMpetition model (N-COM) includes three primary soil nutrients (NH4+, NO3-, and POx (representing the sum of PO43-, HPO42-, and H2PO4-)) and five potential competitors (plant roots, decomposing microbes, nitrifiers, denitrifiers, and mineral surfaces). The competition is formulated with a quasi-steady-state chemical equilibrium approximation to account for substrate (multiple substrates share one consumer) and consumer (multiple consumers compete for one substrate) effects. N-COM successfully reproduced observed soil heterotrophic respiration, N2O emissions, free phosphorus, sorbed phosphorus, and free NH4+ at a tropical forest site (Tapajos). The overall model posterior uncertainty was moderately well constrained. Our sensitivity analysis revealed that soil nutrient competition was primarily regulated by consumer-substrate affinity rather than environmental factors such as soil temperature or soil moisture. Our results imply that the competitiveness (from most to least competitive) followed this order: (1) for NH4+, nitrifiers ~ decomposing microbes > plant roots, (2) for NO3-, denitrifiers ~ decomposing microbes > plant roots, (3) for POx, mineral surfaces > decomposing microbes ~ plant roots. Although smaller, plant relative competitiveness is of the same order of magnitude as microbes. We then applied the N-COM model to analyze field nitrogen and phosphorus perturbation experiments in two tropical forest sites (in Hawaii and Puerto Rico) not used in model development or calibration. Under soil inorganic nitrogen and phosphorus elevated conditions, the model accurately replicated the experimentally observed competition among different nutrient consumers. Although we used as many observations as we could obtain, more nutrient addition experiments in tropical systems would greatly benefit model testing and calibration. In summary, the N-COM model provides an ecologically consistent representation of nutrient competition appropriate for land BGC models integrated in Earth System Models.
-
Representation and presentation of requirements knowledge
NASA Technical Reports Server (NTRS)
Johnson, W. L.; Feather, Martin S.; Harris, David R.
1992-01-01
An approach to representation and presentation of knowledge used in the ARIES, an experimental requirements/specification environment, is described. The approach applies the notion of a representation architecture to the domain of software engineering and incorporates a strong coupling to a transformation system. It is characterized by a single highly expressive underlying representation, interfaced simultaneously to multiple presentations, each with notations of differing degrees of expressivity. This enables analysts to use multiple languages for describing systems and have these descriptions yield a single consistent model of the system.
-
Do Recognition and Priming Index a Unitary Knowledge Base? Comment on Shanks et al. (2003)
ERIC Educational Resources Information Center
Runger, Dennis; Nagy, Gabriel; Frensch, Peter A.
2009-01-01
Whether sequence learning entails a single or multiple memory systems is a moot issue. Recently, D. R. Shanks, L. Wilkinson, and S. Channon advanced a single-system model that predicts a perfect correlation between true (i.e., error free) response time priming and recognition. The Shanks model is contrasted with a dual-process model that…
-
Ando, Tatsuya; Suguro, Miyuki; Kobayashi, Takeshi; Seto, Masao; Honda, Hiroyuki
2003-10-01
A fuzzy neural network (FNN) using gene expression profile data can select combinations of genes from thousands of genes, and is applicable to predict outcome for cancer patients after chemotherapy. However, wide clinical heterogeneity reduces the accuracy of prediction. To overcome this problem, we have proposed an FNN system based on majoritarian decision using multiple noninferior models. We used transcriptional profiling data, which were obtained from "Lymphochip" DNA microarrays (http://llmpp.nih.gov/DLBCL), reported by Rosenwald (N Engl J Med 2002; 346: 1937-47). When the data were analyzed by our FNN system, accuracy (73.4%) of outcome prediction using only 1 FNN model with 4 genes was higher than that (68.5%) of the Cox model using 17 genes. Higher accuracy (91%) was obtained when an FNN system with 9 noninferior models, consisting of 35 independent genes, was used. The genes selected by the system included genes that are informative in the prognosis of Diffuse large B-cell lymphoma (DLBCL), such as genes showing an expression pattern similar to that of CD10 and BCL-6 or similar to that of IRF-4 and BCL-4. We classified 220 DLBCL patients into 5 groups using the prediction results of 9 FNN models. These groups may correspond to DLBCL subtypes. In group A containing half of the 220 patients, patients with poor outcome were found to satisfy 2 rules, i.e., high expression of MAX dimerization with high expression of unknown A (LC_26146), or high expression of MAX dimerization with low expression of unknown B (LC_33144). The present paper is the first to describe the multiple noninferior FNN modeling system. This system is a powerful tool for predicting outcome and classifying patients, and is applicable to other heterogeneous diseases.
-
Automatic image database generation from CAD for 3D object recognition
NASA Astrophysics Data System (ADS)
Sardana, Harish K.; Daemi, Mohammad F.; Ibrahim, Mohammad K.
1993-06-01
The development and evaluation of Multiple-View 3-D object recognition systems is based on a large set of model images. Due to the various advantages of using CAD, it is becoming more and more practical to use existing CAD data in computer vision systems. Current PC- level CAD systems are capable of providing physical image modelling and rendering involving positional variations in cameras, light sources etc. We have formulated a modular scheme for automatic generation of various aspects (views) of the objects in a model based 3-D object recognition system. These views are generated at desired orientations on the unit Gaussian sphere. With a suitable network file sharing system (NFS), the images can directly be stored on a database located on a file server. This paper presents the image modelling solutions using CAD in relation to multiple-view approach. Our modular scheme for data conversion and automatic image database storage for such a system is discussed. We have used this approach in 3-D polyhedron recognition. An overview of the results, advantages and limitations of using CAD data and conclusions using such as scheme are also presented.
-
Life and light: exotic photosynthesis in binary and multiple-star systems.
O'Malley-James, J T; Raven, J A; Cockell, C S; Greaves, J S
2012-02-01
The potential for Earth-like planets within binary/multiple-star systems to host photosynthetic life was evaluated by modeling the levels of photosynthetically active radiation (PAR) such planets receive. Combinations of M and G stars in (i) close-binary systems; (ii) wide-binary systems, and (iii) three-star systems were investigated, and a range of stable radiation environments were found to be possible. These environmental conditions allow for the possibility of familiar, but also more exotic, forms of photosynthetic life, such as IR photosynthesizers and organisms that are specialized for specific spectral niches.
-
2014-04-01
WRF ) model is a numerical weather prediction system designed for operational forecasting and atmospheric research. This report examined WRF model... WRF , weather research and forecasting, atmospheric effects 16. SECURITY CLASSIFICATION OF: 17. LIMITATION OF ABSTRACT SAR 18. NUMBER OF...and Forecasting ( WRF ) model. The authors would also like to thank Ms. Sherry Larson, STS Systems Integration, LLC, ARL Technical Publishing Branch
-
Ralph L. Amateis; Harold E. Burkhart
2012-01-01
Demand for traditional wood products from southern forests continues to increase even as demand for woody biomass for uses such as biofuels is on the rise. How to manage the plantation resource to meet demand for multiple products from a shrinking land base is of critical importance. Nontraditional plantation systems comprised of two populations planted on the same...
-
NASA Astrophysics Data System (ADS)
Benedict, K. K.; Scott, S.
2013-12-01
While there has been a convergence towards a limited number of standards for representing knowledge (metadata) about geospatial (and other) data objects and collections, there exist a variety of community conventions around the specific use of those standards and within specific data discovery and access systems. This combination of limited (but multiple) standards and conventions creates a challenge for system developers that aspire to participate in multiple data infrastrucutres, each of which may use a different combination of standards and conventions. While Extensible Markup Language (XML) is a shared standard for encoding most metadata, traditional direct XML transformations (XSLT) from one standard to another often result in an imperfect transfer of information due to incomplete mapping from one standard's content model to another. This paper presents the work at the University of New Mexico's Earth Data Analysis Center (EDAC) in which a unified data and metadata management system has been developed in support of the storage, discovery and access of heterogeneous data products. This system, the Geographic Storage, Transformation and Retrieval Engine (GSTORE) platform has adopted a polyglot database model in which a combination of relational and document-based databases are used to store both data and metadata, with some metadata stored in a custom XML schema designed as a superset of the requirements for multiple target metadata standards: ISO 19115-2/19139/19110/19119, FGCD CSDGM (both with and without remote sensing extensions) and Dublin Core. Metadata stored within this schema is complemented by additional service, format and publisher information that is dynamically "injected" into produced metadata documents when they are requested from the system. While mapping from the underlying common metadata schema is relatively straightforward, the generation of valid metadata within each target standard is necessary but not sufficient for integration into multiple data infrastructures, as has been demonstrated through EDAC's testing and deployment of metadata into multiple external systems: Data.Gov, the GEOSS Registry, the DataONE network, the DSpace based institutional repository at UNM and semantic mediation systems developed as part of the NASA ACCESS ELSeWEB project. Each of these systems requires valid metadata as a first step, but to make most effective use of the delivered metadata each also has a set of conventions that are specific to the system. This presentation will provide an overview of the underlying metadata management model, the processes and web services that have been developed to automatically generate metadata in a variety of standard formats and highlight some of the specific modifications made to the output metadata content to support the different conventions used by the multiple metadata integration endpoints.
-
DOE Office of Scientific and Technical Information (OSTI.GOV)
Curchod, Basile F. E.; Martínez, Todd J., E-mail: toddjmartinez@gmail.com; SLAC National Accelerator Laboratory, Menlo Park, California 94025
2016-03-14
Full multiple spawning is a formally exact method to describe the excited-state dynamics of molecular systems beyond the Born-Oppenheimer approximation. However, it has been limited until now to the description of radiationless transitions taking place between electronic states with the same spin multiplicity. This Communication presents a generalization of the full and ab initio multiple spawning methods to both internal conversion (mediated by nonadiabatic coupling terms) and intersystem crossing events (triggered by spin-orbit coupling matrix elements) based on a spin-diabatic representation. The results of two numerical applications, a model system and the deactivation of thioformaldehyde, validate the presented formalism andmore » its implementation.« less
-
Curchod, Basile F. E.; Rauer, Clemens; Marquetand, Philipp; ...
2016-03-11
Full Multiple Spawning is a formally exact method to describe the excited-state dynamics of molecular systems beyond the Born-Oppenheimer approximation. However, it has been limited until now to the description of radiationless transitions taking place between electronic states with the same spin multiplicity. This Communication presents a generalization of the full and ab initio Multiple Spawning methods to both internal conversion (mediated by nonadiabatic coupling terms) and intersystem crossing events (triggered by spin-orbit coupling matrix elements) based on a spin-diabatic representation. Lastly, the results of two numerical applications, a model system and the deactivation of thioformaldehyde, validate the presented formalismmore » and its implementation.« less
-
Multiple-Parameter, Low-False-Alarm Fire-Detection Systems
NASA Technical Reports Server (NTRS)
Hunter, Gary W.; Greensburg, Paul; McKnight, Robert; Xu, Jennifer C.; Liu, C. C.; Dutta, Prabir; Makel, Darby; Blake, D.; Sue-Antillio, Jill
2007-01-01
Fire-detection systems incorporating multiple sensors that measure multiple parameters are being developed for use in storage depots, cargo bays of ships and aircraft, and other locations not amenable to frequent, direct visual inspection. These systems are intended to improve upon conventional smoke detectors, now used in such locations, that reliably detect fires but also frequently generate false alarms: for example, conventional smoke detectors based on the blockage of light by smoke particles are also affected by dust particles and water droplets and, thus, are often susceptible to false alarms. In contrast, by utilizing multiple parameters associated with fires, i.e. not only obscuration by smoke particles but also concentrations of multiple chemical species that are commonly generated in combustion, false alarms can be significantly decreased while still detecting fires as reliably as older smoke-detector systems do. The present development includes fabrication of sensors that have, variously, micrometer- or nanometer-sized features so that such multiple sensors can be integrated into arrays that have sizes, weights, and power demands smaller than those of older macroscopic sensors. The sensors include resistors, electrochemical cells, and Schottky diodes that exhibit different sensitivities to the various airborne chemicals of interest. In a system of this type, the sensor readings are digitized and processed by advanced signal-processing hardware and software to extract such chemical indications of fires as abnormally high concentrations of CO and CO2, possibly in combination with H2 and/or hydrocarbons. The system also includes a microelectromechanical systems (MEMS)-based particle detector and classifier device to increase the reliability of measurements of chemical species and particulates. In parallel research, software for modeling the evolution of a fire within an aircraft cargo bay has been developed. The model implemented in the software can describe the concentrations of chemical species and of particulate matter as functions of time. A system of the present developmental type and a conventional fire detector were tested under both fire and false-alarm conditions in a Federal Aviation Administration cargo-compartment- testing facility. Both systems consistently detected fires. However, the conventional fire detector consistently generated false alarms, whereas the developmental system did not generate any false alarms.
-
Automated optimal coordination of multiple-DOF neuromuscular actions in feedforward neuroprostheses.
Lujan, J Luis; Crago, Patrick E
2009-01-01
This paper describes a new method for designing feedforward controllers for multiple-muscle, multiple-DOF, motor system neural prostheses. The design process is based on experimental measurement of the forward input/output properties of the neuromechanical system and numerical optimization of stimulation patterns to meet muscle coactivation criteria, thus resolving the muscle redundancy (i.e., overcontrol) and the coupled DOF problems inherent in neuromechanical systems. We designed feedforward controllers to control the isometric forces at the tip of the thumb in two directions during stimulation of three thumb muscles as a model system. We tested the method experimentally in ten able-bodied individuals and one patient with spinal cord injury. Good control of isometric force in both DOFs was observed, with rms errors less than 10% of the force range in seven experiments and statistically significant correlations between the actual and target forces in all ten experiments. Systematic bias and slope errors were observed in a few experiments, likely due to the neuromuscular fatigue. Overall, the tests demonstrated the ability of a general design approach to satisfy both control and coactivation criteria in multiple-muscle, multiple-axis neuromechanical systems, which is applicable to a wide range of neuromechanical systems and stimulation electrodes.
-
System Dynamics Modeling for Public Health: Background and Opportunities
Homer, Jack B.; Hirsch, Gary B.
2006-01-01
The systems modeling methodology of system dynamics is well suited to address the dynamic complexity that characterizes many public health issues. The system dynamics approach involves the development of computer simulation models that portray processes of accumulation and feedback and that may be tested systematically to find effective policies for overcoming policy resistance. System dynamics modeling of chronic disease prevention should seek to incorporate all the basic elements of a modern ecological approach, including disease outcomes, health and risk behaviors, environmental factors, and health-related resources and delivery systems. System dynamics shows promise as a means of modeling multiple interacting diseases and risks, the interaction of delivery systems and diseased populations, and matters of national and state policy. PMID:16449591
-
NASA Astrophysics Data System (ADS)
Moodie, A. J.; Nittrouer, J. A.; Ma, H.; Carlson, B.; Parker, G.
2016-12-01
The autogenic "life cycle" of a lowland fluvial channel building a deltaic lobe typically follows a temporal sequence that includes: channel initiation, progradation and aggradation, and abandonment via avulsion. In terms of modeling these processes, it is possible to use a one-dimensional (1D) morphodynamic scheme to capture the magnitude of the prograding and aggrading processes. These models can include algorithms to predict the timing and location of avulsions for a channel lobe. However, this framework falls short in its ability to evaluate the deltaic system beyond the time scale of a single channel, and assess sedimentation processes occurring on the floodplain, which is important for lobe building. Herein, we adapt a 1D model to explicitly account for multiple avulsions and therefore replicate a deltaic system that includes many lobe cycles. Following an avulsion, sediment on the floodplain and beyond the radially-averaged shoreline is redistributed across the delta topset and along the shoreline, respectively, simultaneously prograding and aggrading the delta. Over time this framework produces net shoreline progradation and forward-stepping of subsequent avulsions. Testing this model using modern systems is inherently difficult due to a lack of data: most modern delta lobes are active for timescales of centuries to millennia, and so observing multiple iterations of the channel-lobe cycle is impossible. However, the Yellow River delta (China) is unique because the lobe cycles here occur within years to decades. Therefore it is possible to measure shoreline evolution through multiple lobe cycles, based on satellite imagery and historical records. These data are used to validate the model outcomes. Our findings confirm that the explicit accounting of avulsion processes in a quasi-2D model framework is capable of capturing shoreline development patterns that otherwise are not resolvable based on previously published delta building models.
-
DOE Office of Scientific and Technical Information (OSTI.GOV)
Webb, Carol F., E-mail: carol-webb@omrf.org; Immunobiology and Cancer Research, Oklahoma Medical Research Foundation, Oklahoma City, OK; Department of Microbiology and Immunology, University of Oklahoma Health Sciences Center, Oklahoma City, OK
Despite exciting new possibilities for regenerative therapy posed by the ability to induce pluripotent stem cells, recapitulation of three-dimensional kidneys for repair or replacement has not been possible. ARID3a-deficient mouse tissues generated multipotent, developmentally plastic cells. Therefore, we assessed the adult mouse ARID3a−/− kidney cell line, KKPS5, which expresses renal progenitor surface markers as an alternative cell source for modeling kidney development. Remarkably, these cells spontaneously developed into multicellular nephron-like structures in vitro, and engrafted into immunocompromised medaka mesonephros, where they formed mouse nephron structures. These data implicate KKPS5 cells as a new model system for studying kidney development. - Highlights:more » • An ARID3a-deficient mouse kidney cell line expresses multiple progenitor markers. • This cell line spontaneously forms multiple nephron-like structures in vitro. • This cell line formed mouse kidney structures in immunocompromised medaka fish kidneys. • Our data identify a novel model system for studying kidney development.« less
-
A Systems Approach to Exposure Modeling (ExpoCast)(FutureTox3)
Systems Biology might be described as the understanding of how interactions on multiple scales integrate into a homeostatic system. Systems Toxicology could then be the study of the impact of chemical perturbations of homeostasis. Systems exposure might then be the study of the i...
-
NASA Astrophysics Data System (ADS)
Li, D.
2016-12-01
Sudden water pollution accidents are unavoidable risk events that we must learn to co-exist with. In China's Taihu River Basin, the river flow conditions are complicated with frequently artificial interference. Sudden water pollution accident occurs mainly in the form of a large number of abnormal discharge of wastewater, and has the characteristics with the sudden occurrence, the uncontrollable scope, the uncertainty object and the concentrated distribution of many risk sources. Effective prevention of pollution accidents that may occur is of great significance for the water quality safety management. Bayesian networks can be applied to represent the relationship between pollution sources and river water quality intuitively. Using the time sequential Monte Carlo algorithm, the pollution sources state switching model, water quality model for river network and Bayesian reasoning is integrated together, and the sudden water pollution risk assessment model for river network is developed to quantify the water quality risk under the collective influence of multiple pollution sources. Based on the isotope water transport mechanism, a dynamic tracing model of multiple pollution sources is established, which can describe the relationship between the excessive risk of the system and the multiple risk sources. Finally, the diagnostic reasoning algorithm based on Bayesian network is coupled with the multi-source tracing model, which can identify the contribution of each risk source to the system risk under the complex flow conditions. Taking Taihu Lake water system as the research object, the model is applied to obtain the reasonable results under the three typical years. Studies have shown that the water quality risk at critical sections are influenced by the pollution risk source, the boundary water quality, the hydrological conditions and self -purification capacity, and the multiple pollution sources have obvious effect on water quality risk of the receiving water body. The water quality risk assessment approach developed in this study offers a effective tool for systematically quantifying the random uncertainty in plain river network system, and it also provides the technical support for the decision-making of controlling the sudden water pollution through identification of critical pollution sources.
-
Olsen, Aaron M; Camp, Ariel L; Brainerd, Elizabeth L
2017-12-15
The planar, one degree of freedom (1-DoF) four-bar linkage is an important model for understanding the function, performance and evolution of numerous biomechanical systems. One such system is the opercular mechanism in fishes, which is thought to function like a four-bar linkage to depress the lower jaw. While anatomical and behavioral observations suggest some form of mechanical coupling, previous attempts to model the opercular mechanism as a planar four-bar have consistently produced poor model fits relative to observed kinematics. Using newly developed, open source mechanism fitting software, we fitted multiple three-dimensional (3D) four-bar models with varying DoF to in vivo kinematics in largemouth bass to test whether the opercular mechanism functions instead as a 3D four-bar with one or more DoF. We examined link position error, link rotation error and the ratio of output to input link rotation to identify a best-fit model at two different levels of variation: for each feeding strike and across all strikes from the same individual. A 3D, 3-DoF four-bar linkage was the best-fit model for the opercular mechanism, achieving link rotational errors of less than 5%. We also found that the opercular mechanism moves with multiple degrees of freedom at the level of each strike and across multiple strikes. These results suggest that active motor control may be needed to direct the force input to the mechanism by the axial muscles and achieve a particular mouth-opening trajectory. Our results also expand the versatility of four-bar models in simulating biomechanical systems and extend their utility beyond planar or single-DoF systems. © 2017. Published by The Company of Biologists Ltd.
-
Learning the organization: a model for health system analysis for new nurse administrators.
Clark, Mary Jo
2004-01-01
Health systems are large and complex organizations in which multiple components and processes influence system outcomes. In order to effectively position themselves in such organizations, nurse administrators new to a system must gain a rapid understanding of overall system operation. Such understanding is facilitated by use of a model for system analysis. The model presented here examines the dynamic interrelationships between and among internal and external elements as they affect system performance. External elements to be analyzed include environmental factors and characteristics of system clientele. Internal elements flow from the mission and goals of the system and include system culture, services, resources, and outcomes.
-
NASA Astrophysics Data System (ADS)
Johnson, Traci L.; Sharon, Keren
2016-11-01
Until now, systematic errors in strong gravitational lens modeling have been acknowledged but have never been fully quantified. Here, we launch an investigation into the systematics induced by constraint selection. We model the simulated cluster Ares 362 times using random selections of image systems with and without spectroscopic redshifts and quantify the systematics using several diagnostics: image predictability, accuracy of model-predicted redshifts, enclosed mass, and magnification. We find that for models with >15 image systems, the image plane rms does not decrease significantly when more systems are added; however, the rms values quoted in the literature may be misleading as to the ability of a model to predict new multiple images. The mass is well constrained near the Einstein radius in all cases, and systematic error drops to <2% for models using >10 image systems. Magnification errors are smallest along the straight portions of the critical curve, and the value of the magnification is systematically lower near curved portions. For >15 systems, the systematic error on magnification is ∼2%. We report no trend in magnification error with the fraction of spectroscopic image systems when selecting constraints at random; however, when using the same selection of constraints, increasing this fraction up to ∼0.5 will increase model accuracy. The results suggest that the selection of constraints, rather than quantity alone, determines the accuracy of the magnification. We note that spectroscopic follow-up of at least a few image systems is crucial because models without any spectroscopic redshifts are inaccurate across all of our diagnostics.
-
USDA-ARS?s Scientific Manuscript database
This paper provides an overview of the GMI (Geospatial Modeling Interface) simulation framework for environmental model deployment and assessment. GMI currently provides access to multiple environmental models including AgroEcoSystem-Watershed (AgES-W), Nitrate Leaching and Economic Analysis 2 (NLEA...
-
Optimizing Irrigation Water Allocation under Multiple Sources of Uncertainty in an Arid River Basin
NASA Astrophysics Data System (ADS)
Wei, Y.; Tang, D.; Gao, H.; Ding, Y.
2015-12-01
Population growth and climate change add additional pressures affecting water resources management strategies for meeting demands from different economic sectors. It is especially challenging in arid regions where fresh water is limited. For instance, in the Tailanhe River Basin (Xinjiang, China), a compromise must be made between water suppliers and users during drought years. This study presents a multi-objective irrigation water allocation model to cope with water scarcity in arid river basins. To deal with the uncertainties from multiple sources in the water allocation system (e.g., variations of available water amount, crop yield, crop prices, and water price), the model employs a interval linear programming approach. The multi-objective optimization model developed from this study is characterized by integrating eco-system service theory into water-saving measures. For evaluation purposes, the model is used to construct an optimal allocation system for irrigation areas fed by the Tailan River (Xinjiang Province, China). The objective functions to be optimized are formulated based on these irrigation areas' economic, social, and ecological benefits. The optimal irrigation water allocation plans are made under different hydroclimate conditions (wet year, normal year, and dry year), with multiple sources of uncertainty represented. The modeling tool and results are valuable for advising decision making by the local water authority—and the agricultural community—especially on measures for coping with water scarcity (by incorporating uncertain factors associated with crop production planning).
-
NASA Astrophysics Data System (ADS)
Jin, Yongmei
In recent years, theoretical modeling and computational simulation of microstructure evolution and materials property has been attracting much attention. While significant advances have been made, two major challenges remain. One is the integration of multiple physical phenomena for simulation of complex materials behavior, the other is the bridging over multiple length and time scales in materials modeling and simulation. The research presented in this Thesis is focused mainly on tackling the first major challenge. In this Thesis, a unified Phase Field Microelasticity (PFM) approach is developed. This approach is an advanced version of the phase field method that takes into account the exact elasticity of arbitrarily anisotropic, elastically and structurally inhomogeneous systems. The proposed theory and models are applicable to infinite solids, elastic half-space, and finite bodies with arbitrary-shaped free surfaces, which may undergo various concomitant physical processes. The Phase Field Microelasticity approach is employed to formulate the theories and models of martensitic transformation, dislocation dynamics, and crack evolution in single crystal and polycrystalline solids. It is also used to study strain relaxation in heteroepitaxial thin films through misfit dislocation and surface roughening. Magnetic domain evolution in nanocrystalline thin films is also investigated. Numerous simulation studies are performed. Comparison with analytical predictions and experimental observations are presented. Agreement verities the theory and models as realistic simulation tools for computational materials science and engineering. The same Phase Field Microelasticity formalism of individual models of different physical phenomena makes it easy to integrate multiple physical processes into one unified simulation model, where multiple phenomena are treated as various relaxation modes that together act as one common cooperative phenomenon. The model does not impose a priori constraints on possible microstructure evolution paths. This gives the model predicting power, where material system itself "chooses" the optimal path for multiple processes. The advances made in this Thesis present a significant step forward to overcome the first challenge, mesoscale multi-physics modeling and simulation of materials. At the end of this Thesis, the way to tackle the second challenge, bridging over multiple length and time scales in materials modeling and simulation, is discussed based on connection between the mesoscale Phase Field Microelasticity modeling and microscopic atomistic calculation as well as macroscopic continuum theory.
-
Logistics system design for biomass-to-bioenergy industry with multiple types of feedstocks.
Zhu, Xiaoyan; Yao, Qingzhu
2011-12-01
It is technologically possible for a biorefinery to use a variety of biomass as feedstock including native perennial grasses (e.g., switchgrass) and agricultural residues (e.g., corn stalk and wheat straw). Incorporating the distinct characteristics of various types of biomass feedstocks and taking into account their interaction in supplying the bioenergy production, this paper proposed a multi-commodity network flow model to design the logistics system for a multiple-feedstock biomass-to-bioenergy industry. The model was formulated as a mixed integer linear programming, determining the locations of warehouses, the size of harvesting team, the types and amounts of biomass harvested/purchased, stored, and processed in each month, the transportation of biomass in the system, and so on. This paper demonstrated the advantages of using multiple types of biomass feedstocks by comparing with the case of using a single feedstock (switchgrass) and analyzed the relationship of the supply capacity of biomass feedstocks to the output and cost of biofuel. Copyright © 2011 Elsevier Ltd. All rights reserved.
-
NASA Astrophysics Data System (ADS)
Shi, Pei-Ming; Li, Qun; Han, Dong-Ying
2017-06-01
This paper investigates a new asymmetric bistable model driven by correlated multiplicative colored noise and additive white noise. The mean first-passage time (MFPT) and the signal-to-noise ratio (SNR) as the indexes of evaluating the model are researched. Based on the two-state theory and the adiabatic approximation theory, the expressions of MFPT and SNR have been obtained for the asymmetric bistable system driven by a periodic signal, correlated multiplicative colored noise and additive noise. Simulation results show that it is easier to generate stochastic resonance (SR) to adjust the intensity of correlation strength λ. Meanwhile, the decrease of asymmetric coefficient r2 and the increase of noise intensity are beneficial to realize the transition between the two steady states in the system. At the same time, the twice SR phenomena can be observed by adjusting additive white noise and correlation strength. The influence of asymmetry of potential function on the MFPTs in two different directions is different.
-
NASA Technical Reports Server (NTRS)
Xiao, Yegao; Bhat, Ishwara; Abedin, M. Nurul
2005-01-01
InP/InGaAs avalanche photodiodes (APDs) are being widely utilized in optical receivers for modern long haul and high bit-rate optical fiber communication systems. The separate absorption, grading, charge, and multiplication (SAGCM) structure is an important design consideration for APDs with high performance characteristics. Time domain modeling techniques have been previously developed to provide better understanding and optimize design issues by saving time and cost for the APD research and development. In this work, performance dependences on multiplication layer thickness have been investigated by time domain modeling. These performance characteristics include breakdown field and breakdown voltage, multiplication gain, excess noise factor, frequency response and bandwidth etc. The simulations are performed versus various multiplication layer thicknesses with certain fixed values for the areal charge sheet density whereas the values for the other structure and material parameters are kept unchanged. The frequency response is obtained from the impulse response by fast Fourier transformation. The modeling results are presented and discussed, and design considerations, especially for high speed operation at 10 Gbit/s, are further analyzed.
-
Zhang, Yajun; Chai, Tianyou; Wang, Hong
2011-11-01
This paper presents a novel nonlinear control strategy for a class of uncertain single-input and single-output discrete-time nonlinear systems with unstable zero-dynamics. The proposed method combines adaptive-network-based fuzzy inference system (ANFIS) with multiple models, where a linear robust controller, an ANFIS-based nonlinear controller and a switching mechanism are integrated using multiple models technique. It has been shown that the linear controller can ensure the boundedness of the input and output signals and the nonlinear controller can improve the dynamic performance of the closed loop system. Moreover, it has also been shown that the use of the switching mechanism can simultaneously guarantee the closed loop stability and improve its performance. As a result, the controller has the following three outstanding features compared with existing control strategies. First, this method relaxes the assumption of commonly-used uniform boundedness on the unmodeled dynamics and thus enhances its applicability. Second, since ANFIS is used to estimate and compensate the effect caused by the unmodeled dynamics, the convergence rate of neural network learning has been increased. Third, a "one-to-one mapping" technique is adapted to guarantee the universal approximation property of ANFIS. The proposed controller is applied to a numerical example and a pulverizing process of an alumina sintering system, respectively, where its effectiveness has been justified.
-
Hybrid approaches for multiple-species stochastic reaction-diffusion models
NASA Astrophysics Data System (ADS)
Spill, Fabian; Guerrero, Pilar; Alarcon, Tomas; Maini, Philip K.; Byrne, Helen
2015-10-01
Reaction-diffusion models are used to describe systems in fields as diverse as physics, chemistry, ecology and biology. The fundamental quantities in such models are individual entities such as atoms and molecules, bacteria, cells or animals, which move and/or react in a stochastic manner. If the number of entities is large, accounting for each individual is inefficient, and often partial differential equation (PDE) models are used in which the stochastic behaviour of individuals is replaced by a description of the averaged, or mean behaviour of the system. In some situations the number of individuals is large in certain regions and small in others. In such cases, a stochastic model may be inefficient in one region, and a PDE model inaccurate in another. To overcome this problem, we develop a scheme which couples a stochastic reaction-diffusion system in one part of the domain with its mean field analogue, i.e. a discretised PDE model, in the other part of the domain. The interface in between the two domains occupies exactly one lattice site and is chosen such that the mean field description is still accurate there. In this way errors due to the flux between the domains are small. Our scheme can account for multiple dynamic interfaces separating multiple stochastic and deterministic domains, and the coupling between the domains conserves the total number of particles. The method preserves stochastic features such as extinction not observable in the mean field description, and is significantly faster to simulate on a computer than the pure stochastic model.
-
Hybrid approaches for multiple-species stochastic reaction-diffusion models.
Spill, Fabian; Guerrero, Pilar; Alarcon, Tomas; Maini, Philip K; Byrne, Helen
2015-10-15
Reaction-diffusion models are used to describe systems in fields as diverse as physics, chemistry, ecology and biology. The fundamental quantities in such models are individual entities such as atoms and molecules, bacteria, cells or animals, which move and/or react in a stochastic manner. If the number of entities is large, accounting for each individual is inefficient, and often partial differential equation (PDE) models are used in which the stochastic behaviour of individuals is replaced by a description of the averaged, or mean behaviour of the system. In some situations the number of individuals is large in certain regions and small in others. In such cases, a stochastic model may be inefficient in one region, and a PDE model inaccurate in another. To overcome this problem, we develop a scheme which couples a stochastic reaction-diffusion system in one part of the domain with its mean field analogue, i.e. a discretised PDE model, in the other part of the domain. The interface in between the two domains occupies exactly one lattice site and is chosen such that the mean field description is still accurate there. In this way errors due to the flux between the domains are small. Our scheme can account for multiple dynamic interfaces separating multiple stochastic and deterministic domains, and the coupling between the domains conserves the total number of particles. The method preserves stochastic features such as extinction not observable in the mean field description, and is significantly faster to simulate on a computer than the pure stochastic model.
-
Hybrid approaches for multiple-species stochastic reaction–diffusion models
Spill, Fabian; Guerrero, Pilar; Alarcon, Tomas; Maini, Philip K.; Byrne, Helen
2015-01-01
Reaction–diffusion models are used to describe systems in fields as diverse as physics, chemistry, ecology and biology. The fundamental quantities in such models are individual entities such as atoms and molecules, bacteria, cells or animals, which move and/or react in a stochastic manner. If the number of entities is large, accounting for each individual is inefficient, and often partial differential equation (PDE) models are used in which the stochastic behaviour of individuals is replaced by a description of the averaged, or mean behaviour of the system. In some situations the number of individuals is large in certain regions and small in others. In such cases, a stochastic model may be inefficient in one region, and a PDE model inaccurate in another. To overcome this problem, we develop a scheme which couples a stochastic reaction–diffusion system in one part of the domain with its mean field analogue, i.e. a discretised PDE model, in the other part of the domain. The interface in between the two domains occupies exactly one lattice site and is chosen such that the mean field description is still accurate there. In this way errors due to the flux between the domains are small. Our scheme can account for multiple dynamic interfaces separating multiple stochastic and deterministic domains, and the coupling between the domains conserves the total number of particles. The method preserves stochastic features such as extinction not observable in the mean field description, and is significantly faster to simulate on a computer than the pure stochastic model. PMID:26478601
-
Ji, Zhiwei; Su, Jing; Wu, Dan; Peng, Huiming; Zhao, Weiling; Nlong Zhao, Brian; Zhou, Xiaobo
2017-01-31
Multiple myeloma is a malignant still incurable plasma cell disorder. This is due to refractory disease relapse, immune impairment, and development of multi-drug resistance. The growth of malignant plasma cells is dependent on the bone marrow (BM) microenvironment and evasion of the host's anti-tumor immune response. Hence, we hypothesized that targeting tumor-stromal cell interaction and endogenous immune system in BM will potentially improve the response of multiple myeloma (MM). Therefore, we proposed a computational simulation of the myeloma development in the complicated microenvironment which includes immune cell components and bone marrow stromal cells and predicted the effects of combined treatment with multi-drugs on myeloma cell growth. We constructed a hybrid multi-scale agent-based model (HABM) that combines an ODE system and Agent-based model (ABM). The ODEs was used for modeling the dynamic changes of intracellular signal transductions and ABM for modeling the cell-cell interactions between stromal cells, tumor, and immune components in the BM. This model simulated myeloma growth in the bone marrow microenvironment and revealed the important role of immune system in this process. The predicted outcomes were consistent with the experimental observations from previous studies. Moreover, we applied this model to predict the treatment effects of three key therapeutic drugs used for MM, and found that the combination of these three drugs potentially suppress the growth of myeloma cells and reactivate the immune response. In summary, the proposed model may serve as a novel computational platform for simulating the formation of MM and evaluating the treatment response of MM to multiple drugs.
-
Attitude determination using an adaptive multiple model filtering Scheme
NASA Technical Reports Server (NTRS)
Lam, Quang; Ray, Surendra N.
1995-01-01
Attitude determination has been considered as a permanent topic of active research and perhaps remaining as a forever-lasting interest for spacecraft system designers. Its role is to provide a reference for controls such as pointing the directional antennas or solar panels, stabilizing the spacecraft or maneuvering the spacecraft to a new orbit. Least Square Estimation (LSE) technique was utilized to provide attitude determination for the Nimbus 6 and G. Despite its poor performance (estimation accuracy consideration), LSE was considered as an effective and practical approach to meet the urgent need and requirement back in the 70's. One reason for this poor performance associated with the LSE scheme is the lack of dynamic filtering or 'compensation'. In other words, the scheme is based totally on the measurements and no attempts were made to model the dynamic equations of motion of the spacecraft. We propose an adaptive filtering approach which employs a bank of Kalman filters to perform robust attitude estimation. The proposed approach, whose architecture is depicted, is essentially based on the latest proof on the interactive multiple model design framework to handle the unknown of the system noise characteristics or statistics. The concept fundamentally employs a bank of Kalman filter or submodel, instead of using fixed values for the system noise statistics for each submodel (per operating condition) as the traditional multiple model approach does, we use an on-line dynamic system noise identifier to 'identify' the system noise level (statistics) and update the filter noise statistics using 'live' information from the sensor model. The advanced noise identifier, whose architecture is also shown, is implemented using an advanced system identifier. To insure the robust performance for the proposed advanced system identifier, it is also further reinforced by a learning system which is implemented (in the outer loop) using neural networks to identify other unknown quantities such as spacecraft dynamics parameters, gyro biases, dynamic disturbances, or environment variations.
-
Attitude determination using an adaptive multiple model filtering Scheme
NASA Astrophysics Data System (ADS)
Lam, Quang; Ray, Surendra N.
1995-05-01
Attitude determination has been considered as a permanent topic of active research and perhaps remaining as a forever-lasting interest for spacecraft system designers. Its role is to provide a reference for controls such as pointing the directional antennas or solar panels, stabilizing the spacecraft or maneuvering the spacecraft to a new orbit. Least Square Estimation (LSE) technique was utilized to provide attitude determination for the Nimbus 6 and G. Despite its poor performance (estimation accuracy consideration), LSE was considered as an effective and practical approach to meet the urgent need and requirement back in the 70's. One reason for this poor performance associated with the LSE scheme is the lack of dynamic filtering or 'compensation'. In other words, the scheme is based totally on the measurements and no attempts were made to model the dynamic equations of motion of the spacecraft. We propose an adaptive filtering approach which employs a bank of Kalman filters to perform robust attitude estimation. The proposed approach, whose architecture is depicted, is essentially based on the latest proof on the interactive multiple model design framework to handle the unknown of the system noise characteristics or statistics. The concept fundamentally employs a bank of Kalman filter or submodel, instead of using fixed values for the system noise statistics for each submodel (per operating condition) as the traditional multiple model approach does, we use an on-line dynamic system noise identifier to 'identify' the system noise level (statistics) and update the filter noise statistics using 'live' information from the sensor model. The advanced noise identifier, whose architecture is also shown, is implemented using an advanced system identifier. To insure the robust performance for the proposed advanced system identifier, it is also further reinforced by a learning system which is implemented (in the outer loop) using neural networks to identify other unknown quantities such as spacecraft dynamics parameters, gyro biases, dynamic disturbances, or environment variations.
-
Bioerodible System for Sequential Release of Multiple Drugs
Sundararaj, Sharath C.; Thomas, Mark V.; Dziubla, Thomas D.; Puleo, David A.
2013-01-01
Because many complex physiological processes are controlled by multiple biomolecules, comprehensive treatment of certain disease conditions may be more effectively achieved by administration of more than one type of drug. Thus, the objective of the present research was to develop a multilayered, polymer-based system for sequential delivery of multiple drugs. The polymers used were cellulose acetate phthalate (CAP) complexed with Pluronic F-127 (P). After evaluating morphology of the resulting CAPP system, in vitro release of small molecule drugs and a model protein was studied from both single and multilayered devices. Drug release from single-layered CAPP films followed zero-order kinetics related to surface erosion of the association polymer. Release studies from multilayered CAPP devices showed the possibility of achieving intermittent release of one type of drug as well as sequential release of more than one type of drug. Mathematical modeling accurately predicted the release profiles for both single layer and multilayered devices. The present CAPP association polymer-based multilayer devices can be used for localized, sequential delivery of multiple drugs for the possible treatment of complex disease conditions, and perhaps for tissue engineering applications, that require delivery of more than one type of biomolecule. PMID:24096151
-
Vasiljevic, Dragana; Parojcic, Jelena; Primorac, Marija; Vuleta, Gordana
2006-02-17
Multiple W/O/W emulsions with high content of inner phase (Phi1=Phi2=0.8) were prepared using relatively low concentrations of lipophilic polymeric primary emulsifier, PEG 30-dipolyhydroxystearate, and diclofenac diethylamine (DDA) as a model drug. The investigated formulations were characterized and their stability over the time was evaluated by dynamic and oscillatory rheological measurements, microscopic analysis and in vitro drug release study. In vitro release profiles of the selected model drug were evaluated in terms of the effective diffusion coefficients and flux of the released drug. The multiple emulsion samples exhibited good stability during the ageing time. Concentration of the lipophilic primary emulsifier markedly affected rheological behaviour as well as the droplet size and in vitro drug release kinetics of the investigated systems. The multiple emulsion systems with highest concentration (2.4%, w/w) of the primary emulsifier had the lowest droplet size and the highest apparent viscosity and highest elastic characteristics. Drug release data indicated predominately diffusional drug release mechanism with sustained and prolonged drug release accomplished with 2.4% (w/w) of lipophilic emulsifier employed.
-
Dynamic fuzzy modeling of storm water infiltration in urban fractured aquifers
Hong, Y.-S.; Rosen, Michael R.; Reeves, R.R.
2002-01-01
In an urban fractured-rock aquifer in the Mt. Eden area of Auckland, New Zealand, disposal of storm water is via "soakholes" drilled directly into the top of the fractured basalt rock. The dynamic response of the groundwater level due to the storm water infiltration shows characteristics of a strongly time-varying system. A dynamic fuzzy modeling approach, which is based on multiple local models that are weighted using fuzzy membership functions, has been developed to identify and predict groundwater level fluctuations caused by storm water infiltration. The dynamic fuzzy model is initialized by the fuzzy clustering algorithm and optimized by the gradient-descent algorithm in order to effectively derive the multiple local models-each of which is associated with a locally valid model that represents the groundwater level state as a response to different intensities of rainfall events. The results have shown that even if the number of fuzzy local models derived is small, the fuzzy modeling approach developed provides good prediction results despite the highly time-varying nature of this urban fractured-rock aquifer system. Further, it allows interpretable representations of the dynamic behavior of the groundwater system due to storm water infiltration.
-
Data Modeling Challenges of Advanced Interoperability.
Blobel, Bernd; Oemig, Frank; Ruotsalainen, Pekka
2018-01-01
Progressive health paradigms, involving many different disciplines and combining multiple policy domains, requires advanced interoperability solutions. This results in special challenges for modeling health systems. The paper discusses classification systems for data models and enterprise business architectures and compares them with the ISO Reference Architecture. On that basis, existing definitions, specifications and standards of data models for interoperability are evaluated and their limitations are discussed. Amendments to correctly use those models and to better meet the aforementioned challenges are offered.
-
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.
-
Perturbative stability of SFT-based cosmological models
DOE Office of Scientific and Technical Information (OSTI.GOV)
Galli, Federico; Koshelev, Alexey S., E-mail: fgalli@tena4.vub.ac.be, E-mail: alexey.koshelev@vub.ac.be
2011-05-01
We review the appearance of multiple scalar fields in linearized SFT based cosmological models with a single non-local scalar field. Some of these local fields are canonical real scalar fields and some are complex fields with unusual coupling. These systems only admit numerical or approximate analysis. We introduce a modified potential for multiple scalar fields that makes the system exactly solvable in the cosmological context of Friedmann equations and at the same time preserves the asymptotic behavior expected from SFT. The main part of the paper consists of the analysis of inhomogeneous cosmological perturbations in this system. We show numericallymore » that perturbations corresponding to the new type of complex fields always vanish. As an example of application of this model we consider an explicit construction of the phantom divide crossing and prove the perturbative stability of this process at the linear order. The issue of ghosts and ways to resolve it are briefly discussed.« less
-
Yang, Weichao; Xu, Kui; Lian, Jijian; Bin, Lingling; Ma, Chao
2018-05-01
Flood is a serious challenge that increasingly affects the residents as well as policymakers. Flood vulnerability assessment is becoming gradually relevant in the world. The purpose of this study is to develop an approach to reveal the relationship between exposure, sensitivity and adaptive capacity for better flood vulnerability assessment, based on the fuzzy comprehensive evaluation method (FCEM) and coordinated development degree model (CDDM). The approach is organized into three parts: establishment of index system, assessment of exposure, sensitivity and adaptive capacity, and multiple flood vulnerability assessment. Hydrodynamic model and statistical data are employed for the establishment of index system; FCEM is used to evaluate exposure, sensitivity and adaptive capacity; and CDDM is applied to express the relationship of the three components of vulnerability. Six multiple flood vulnerability types and four levels are proposed to assess flood vulnerability from multiple perspectives. Then the approach is applied to assess the spatiality of flood vulnerability in Hainan's eastern area, China. Based on the results of multiple flood vulnerability, a decision-making process for rational allocation of limited resources is proposed and applied to the study area. The study shows that multiple flood vulnerability assessment can evaluate vulnerability more completely, and help decision makers learn more information about making decisions in a more comprehensive way. In summary, this study provides a new way for flood vulnerability assessment and disaster prevention decision. Copyright © 2018 Elsevier Ltd. All rights reserved.
-
NASA Astrophysics Data System (ADS)
Srinivasan, Veena; Gorelick, Steven M.; Goulder, Lawrence
2010-07-01
In this paper, we discuss a challenging water resources problem in a developing world city, Chennai, India. The goal is to reconstruct past system behavior and diagnose the causes of a major water crisis. In order to do this, we develop a hydrologic-engineering-economic model to address the complexity of urban water supply arising from consumers' dependence on multiple interconnected sources of water. We integrate different components of the urban water system: water flowing into the reservoir system; diversion and distribution by the public water utility; groundwater flow in the aquifer beneath the city; supply, demand, and prices in the informal tanker-truck-based water market; and consumer behavior. Both the economic and physical impacts of consumers' dependence on multiple sources of water are quantified. The model is calibrated over the period 2002-2006 using a range of hydrologic and socio-economic data. The model's results highlight the inadequacy of the reservoir system and the buffering role played by the urban aquifer and consumers' coping investments during multiyear droughts.
-
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.
-
RooStatsCms: A tool for analysis modelling, combination and statistical studies
NASA Astrophysics Data System (ADS)
Piparo, D.; Schott, G.; Quast, G.
2010-04-01
RooStatsCms is an object oriented statistical framework based on the RooFit technology. Its scope is to allow the modelling, statistical analysis and combination of multiple search channels for new phenomena in High Energy Physics. It provides a variety of methods described in literature implemented as classes, whose design is oriented to the execution of multiple CPU intensive jobs on batch systems or on the Grid.
-
Garcia, F; Arruda-Neto, J D; Manso, M V; Helene, O M; Vanin, V R; Rodriguez, O; Mesa, J; Likhachev, V P; Filho, J W; Deppman, A; Perez, G; Guzman, F; de Camargo, S P
1999-10-01
A new and simple statistical procedure (STATFLUX) for the calculation of transfer coefficients of radionuclide transport to animals and plants is proposed. The method is based on the general multiple-compartment model, which uses a system of linear equations involving geometrical volume considerations. By using experimentally available curves of radionuclide concentrations versus time, for each animal compartment (organs), flow parameters were estimated by employing a least-squares procedure, whose consistency is tested. Some numerical results are presented in order to compare the STATFLUX transfer coefficients with those from other works and experimental data.
-
Estimation of Finger Joint Angles Based on Electromechanical Sensing of Wrist Shape.
Kawaguchi, Junki; Yoshimoto, Shunsuke; Kuroda, Yoshihiro; Oshiro, Osamu
2017-09-01
An approach to finger motion capture that places fewer restrictions on the usage environment and actions of the user is an important research topic in biomechanics and human-computer interaction. We proposed a system that electrically detects finger motion from the associated deformation of the wrist and estimates the finger joint angles using multiple regression models. A wrist-mounted sensing device with 16 electrodes detects deformation of the wrist from changes in electrical contact resistance at the skin. In this study, we experimentally investigated the accuracy of finger joint angle estimation, the adequacy of two multiple regression models, and the resolution of the estimation of total finger joint angles. In experiments, both the finger joint angles and the system output voltage were recorded as subjects performed flexion/extension of the fingers. These data were used for calibration using the least-squares method. The system was found to be capable of estimating the total finger joint angle with a root-mean-square error of 29-34 degrees. A multiple regression model with a second-order polynomial basis function was shown to be suitable for the estimation of all total finger joint angles, but not those of the thumb.
-
2006-08-01
Force Research Laboratory This report is published in the interest of scientific and technical information exchange, and its publication does not...SYSTEM SJ SYSTEM INTERACTIONS AND INFLUENCES SOCIAL ORGANIZATIONAL SYSTEM SYSTEM I Multiple actors egaglng In comunities of Commrunitles of Interest
-
Adaptive Estimation of Multiple Fading Factors for GPS/INS Integrated Navigation Systems.
Jiang, Chen; Zhang, Shu-Bi; Zhang, Qiu-Zhao
2017-06-01
The Kalman filter has been widely applied in the field of dynamic navigation and positioning. However, its performance will be degraded in the presence of significant model errors and uncertain interferences. In the literature, the fading filter was proposed to control the influences of the model errors, and the H-infinity filter can be adopted to address the uncertainties by minimizing the estimation error in the worst case. In this paper, a new multiple fading factor, suitable for the Global Positioning System (GPS) and the Inertial Navigation System (INS) integrated navigation system, is proposed based on the optimization of the filter, and a comprehensive filtering algorithm is constructed by integrating the advantages of the H-infinity filter and the proposed multiple fading filter. Measurement data of the GPS/INS integrated navigation system are collected under actual conditions. Stability and robustness of the proposed filtering algorithm are tested with various experiments and contrastive analysis are performed with the measurement data. Results demonstrate that both the filter divergence and the influences of outliers are restrained effectively with the proposed filtering algorithm, and precision of the filtering results are improved simultaneously.
-
Stability of the Martian climate system under the seasonal change condition of solar radiation
NASA Astrophysics Data System (ADS)
Nakamura, Takasumi; Tajika, Eiichi
2002-11-01
Previous studies on stability of the Martian climate system used essentially zero-dimensional energy balance climate models (EBMs) under the condition of annual mean solar radiation income. However, areal extent of polar ice caps should affect the Martian climate through the energy balance and the CO2 budget, and results under the seasonal change condition of solar radiation will be different from those under the annual mean condition. We therefore construct a one-dimensional energy balance climate model with CO2-dependent outgoing radiation, seasonal changes of solar radiation income, changes of areal extent of CO2 ice caps, and adsorption of CO2 by regolith. We have investigated behaviors of the Martian climate system and, in particular, examined the effect of the seasonal changes of solar radiation by comparing the results of previous studies under the condition of annual mean solar radiation. One of the major discrepancies between them is the condition for multiple solutions of the Martian climate system. Although the Martian climate system always has multiple solutions under the annual mean condition, under the seasonal change condition, existence of multiple solutions depends on the present amounts of CO2 in the ice caps and the regolith.
-
NASA Technical Reports Server (NTRS)
Hoadley, Sherwood T.; Mcgraw, Sandra M.
1992-01-01
A real time multiple-function digital controller system was developed for the Active Flexible Wing (AFW) Program. The digital controller system (DCS) allowed simultaneous execution of two control laws: flutter suppression and either roll trim or a rolling maneuver load control. The DCS operated within, but independently of, a slower host operating system environment, at regulated speeds up to 200 Hz. It also coordinated the acquisition, storage, and transfer of data for near real time controller performance evaluation and both open- and closed-loop plant estimation. It synchronized the operation of four different processing units, allowing flexibility in the number, form, functionality, and order of control laws, and variability in the selection of the sensors and actuators employed. Most importantly, the DCS allowed for the successful demonstration of active flutter suppression to conditions approximately 26 percent (in dynamic pressure) above the open-loop boundary in cases when the model was fixed in roll and up to 23 percent when it was free to roll. Aggressive roll maneuvers with load control were achieved above the flutter boundary. The purpose here is to present the development, validation, and wind tunnel testing of this multiple-function digital controller system.
-
Simulation of Attitude and Trajectory Dynamics and Control of Multiple Spacecraft
NASA Technical Reports Server (NTRS)
Stoneking, Eric T.
2009-01-01
Agora software is a simulation of spacecraft attitude and orbit dynamics. It supports spacecraft models composed of multiple rigid bodies or flexible structural models. Agora simulates multiple spacecraft simultaneously, supporting rendezvous, proximity operations, and precision formation flying studies. The Agora environment includes ephemerides for all planets and major moons in the solar system, supporting design studies for deep space as well as geocentric missions. The environment also contains standard models for gravity, atmospheric density, and magnetic fields. Disturbance force and torque models include aerodynamic, gravity-gradient, solar radiation pressure, and third-body gravitation. In addition to the dynamic and environmental models, Agora supports geometrical visualization through an OpenGL interface. Prototype models are provided for common sensors, actuators, and control laws. A clean interface accommodates linking in actual flight code in place of the prototype control laws. The same simulation may be used for rapid feasibility studies, and then used for flight software validation as the design matures. Agora is open-source and portable across computing platforms, making it customizable and extensible. It is written to support the entire GNC (guidance, navigation, and control) design cycle, from rapid prototyping and design analysis, to high-fidelity flight code verification. As a top-down design, Agora is intended to accommodate a large range of missions, anywhere in the solar system. Both two-body and three-body flight regimes are supported, as well as seamless transition between them. Multiple spacecraft may be simultaneously simulated, enabling simulation of rendezvous scenarios, as well as formation flying. Built-in reference frames and orbit perturbation dynamics provide accurate modeling of precision formation control.
-
NASA Astrophysics Data System (ADS)
Walker, Ernest L.
1994-05-01
This paper presents results of a theoretical investigation to evaluate the performance of code division multiple access communications over multimode optical fiber channels in an asynchronous, multiuser communication network environment. The system is evaluated using Gold sequences for spectral spreading of the baseband signal from each user employing direct-sequence biphase shift keying and intensity modulation techniques. The transmission channel model employed is a lossless linear system approximation of the field transfer function for the alpha -profile multimode optical fiber. Due to channel model complexity, a correlation receiver model employing a suboptimal receive filter was used in calculating the peak output signal at the ith receiver. In Part 1, the performance measures for the system, i.e., signal-to-noise ratio and bit error probability for the ith receiver, are derived as functions of channel characteristics, spectral spreading, number of active users, and the bit energy to noise (white) spectral density ratio. In Part 2, the overall system performance is evaluated.
-
Multi-muscle FES force control of the human arm for arbitrary goals.
Schearer, Eric M; Liao, Yu-Wei; Perreault, Eric J; Tresch, Matthew C; Memberg, William D; Kirsch, Robert F; Lynch, Kevin M
2014-05-01
We present a method for controlling a neuroprosthesis for a paralyzed human arm using functional electrical stimulation (FES) and characterize the errors of the controller. The subject has surgically implanted electrodes for stimulating muscles in her shoulder and arm. Using input/output data, a model mapping muscle stimulations to isometric endpoint forces measured at the subject's hand was identified. We inverted the model of this redundant and coupled multiple-input multiple-output system by minimizing muscle activations and used this inverse for feedforward control. The magnitude of the total root mean square error over a grid in the volume of achievable isometric endpoint force targets was 11% of the total range of achievable forces. Major sources of error were random error due to trial-to-trial variability and model bias due to nonstationary system properties. Because the muscles working collectively are the actuators of the skeletal system, the quantification of errors in force control guides designs of motion controllers for multi-joint, multi-muscle FES systems that can achieve arbitrary goals.
-
NASA Astrophysics Data System (ADS)
Qiu, Junchao; Zhang, Lin; Li, Diyang; Liu, Xingcheng
2016-06-01
Chaotic sequences can be applied to realize multiple user access and improve the system security for a visible light communication (VLC) system. However, since the map patterns of chaotic sequences are usually well known, eavesdroppers can possibly derive the key parameters of chaotic sequences and subsequently retrieve the information. We design an advanced encryption standard (AES) interleaving aided multiple user access scheme to enhance the security of a chaotic code division multiple access-based visible light communication (C-CDMA-VLC) system. We propose to spread the information with chaotic sequences, and then the spread information is interleaved by an AES algorithm and transmitted over VLC channels. Since the computation complexity of performing inverse operations to deinterleave the information is high, the eavesdroppers in a high speed VLC system cannot retrieve the information in real time; thus, the system security will be enhanced. Moreover, we build a mathematical model for the AES-aided VLC system and derive the theoretical information leakage to analyze the system security. The simulations are performed over VLC channels, and the results demonstrate the effectiveness and high security of our presented AES interleaving aided chaotic CDMA-VLC system.
-
An improved car-following model with multiple preceding cars' velocity fluctuation feedback
NASA Astrophysics Data System (ADS)
Guo, Lantian; Zhao, Xiangmo; Yu, Shaowei; Li, Xiuhai; Shi, Zhongke
2017-04-01
In order to explore and evaluate the effects of velocity variation trend of multiple preceding cars used in the Cooperative Adaptive Cruise Control (CACC) strategy on the dynamic characteristic, fuel economy and emission of the corresponding traffic flow, we conduct a study as follows: firstly, with the real-time car-following (CF) data, the close relationship between multiple preceding cars' velocity fluctuation feedback and the host car's behaviors is explored, the evaluation results clearly show that multiple preceding cars' velocity fluctuation with different time window-width are highly correlated to the host car's acceleration/deceleration. Then, a microscopic traffic flow model is proposed to evaluate the effects of multiple preceding cars' velocity fluctuation feedback in the CACC strategy on the traffic flow evolution process. Finally, numerical simulations on fuel economy and exhaust emission of the traffic flow are also implemented by utilizing VT-micro model. Simulation results prove that considering multiple preceding cars' velocity fluctuation feedback in the control strategy of the CACC system can improve roadway traffic mobility, fuel economy and exhaust emission performance.
-
Modeling of Explorative Procedures for Remote Object Identification
1991-09-01
haptic sensory system and the simulated foveal component of the visual system. Eventually it will allow multiple applications in remote sensing and...superposition of sensory channels. The use of a force reflecting telemanipulator and computer simulated visual foveal component are the tools which...representation of human search models is achieved by using the proprioceptive component of the haptic sensory system and the simulated foveal component of the
-
NASA Astrophysics Data System (ADS)
Leskiw, Donald M.; Zhau, Junmei
2000-06-01
This paper reports on results from an ongoing project to develop methodologies for representing and managing multiple, concurrent levels of detail and enabling high performance computing using parallel arrays within distributed object-based simulation frameworks. At this time we present the methodology for representing and managing multiple, concurrent levels of detail and modeling accuracy by using a representation based on the Kalman approach for estimation. The Kalman System Model equations are used to represent model accuracy, Kalman Measurement Model equations provide transformations between heterogeneous levels of detail, and interoperability among disparate abstractions is provided using a form of the Kalman Update equations.
-
Automatic Visual Tracking and Social Behaviour Analysis with Multiple Mice
Giancardo, Luca; Sona, Diego; Huang, Huiping; Sannino, Sara; Managò, Francesca; Scheggia, Diego; Papaleo, Francesco; Murino, Vittorio
2013-01-01
Social interactions are made of complex behavioural actions that might be found in all mammalians, including humans and rodents. Recently, mouse models are increasingly being used in preclinical research to understand the biological basis of social-related pathologies or abnormalities. However, reliable and flexible automatic systems able to precisely quantify social behavioural interactions of multiple mice are still missing. Here, we present a system built on two components. A module able to accurately track the position of multiple interacting mice from videos, regardless of their fur colour or light settings, and a module that automatically characterise social and non-social behaviours. The behavioural analysis is obtained by deriving a new set of specialised spatio-temporal features from the tracker output. These features are further employed by a learning-by-example classifier, which predicts for each frame and for each mouse in the cage one of the behaviours learnt from the examples given by the experimenters. The system is validated on an extensive set of experimental trials involving multiple mice in an open arena. In a first evaluation we compare the classifier output with the independent evaluation of two human graders, obtaining comparable results. Then, we show the applicability of our technique to multiple mice settings, using up to four interacting mice. The system is also compared with a solution recently proposed in the literature that, similarly to us, addresses the problem with a learning-by-examples approach. Finally, we further validated our automatic system to differentiate between C57B/6J (a commonly used reference inbred strain) and BTBR T+tf/J (a mouse model for autism spectrum disorders). Overall, these data demonstrate the validity and effectiveness of this new machine learning system in the detection of social and non-social behaviours in multiple (>2) interacting mice, and its versatility to deal with different experimental settings and scenarios. PMID:24066146
-
NASA Technical Reports Server (NTRS)
Hall, Laverne
1995-01-01
Modeling of the Multi-mission Image Processing System (MIPS) will be described as an example of the use of a modeling tool to design a distributed system that supports multiple application scenarios. This paper examines: (a) modeling tool selection, capabilities, and operation (namely NETWORK 2.5 by CACl), (b) pointers for building or constructing a model and how the MIPS model was developed, (c) the importance of benchmarking or testing the performance of equipment/subsystems being considered for incorporation the design/architecture, (d) the essential step of model validation and/or calibration using the benchmark results, (e) sample simulation results from the MIPS model, and (f) how modeling and simulation analysis affected the MIPS design process by having a supportive and informative impact.
-
Emergence of scale-free characteristics in socio-ecological systems with bounded rationality
Kasthurirathna, Dharshana; Piraveenan, Mahendra
2015-01-01
Socio–ecological systems are increasingly modelled by games played on complex networks. While the concept of Nash equilibrium assumes perfect rationality, in reality players display heterogeneous bounded rationality. Here we present a topological model of bounded rationality in socio-ecological systems, using the rationality parameter of the Quantal Response Equilibrium. We argue that system rationality could be measured by the average Kullback–-Leibler divergence between Nash and Quantal Response Equilibria, and that the convergence towards Nash equilibria on average corresponds to increased system rationality. Using this model, we show that when a randomly connected socio-ecological system is topologically optimised to converge towards Nash equilibria, scale-free and small world features emerge. Therefore, optimising system rationality is an evolutionary reason for the emergence of scale-free and small-world features in socio-ecological systems. Further, we show that in games where multiple equilibria are possible, the correlation between the scale-freeness of the system and the fraction of links with multiple equilibria goes through a rapid transition when the average system rationality increases. Our results explain the influence of the topological structure of socio–ecological systems in shaping their collective cognitive behaviour, and provide an explanation for the prevalence of scale-free and small-world characteristics in such systems. PMID:26065713
-
Emergence of scale-free characteristics in socio-ecological systems with bounded rationality.
Kasthurirathna, Dharshana; Piraveenan, Mahendra
2015-06-11
Socio-ecological systems are increasingly modelled by games played on complex networks. While the concept of Nash equilibrium assumes perfect rationality, in reality players display heterogeneous bounded rationality. Here we present a topological model of bounded rationality in socio-ecological systems, using the rationality parameter of the Quantal Response Equilibrium. We argue that system rationality could be measured by the average Kullback--Leibler divergence between Nash and Quantal Response Equilibria, and that the convergence towards Nash equilibria on average corresponds to increased system rationality. Using this model, we show that when a randomly connected socio-ecological system is topologically optimised to converge towards Nash equilibria, scale-free and small world features emerge. Therefore, optimising system rationality is an evolutionary reason for the emergence of scale-free and small-world features in socio-ecological systems. Further, we show that in games where multiple equilibria are possible, the correlation between the scale-freeness of the system and the fraction of links with multiple equilibria goes through a rapid transition when the average system rationality increases. Our results explain the influence of the topological structure of socio-ecological systems in shaping their collective cognitive behaviour, and provide an explanation for the prevalence of scale-free and small-world characteristics in such systems.
-
Exploring Contextual Models in Chemical Patent Search
NASA Astrophysics Data System (ADS)
Urbain, Jay; Frieder, Ophir
We explore the development of probabilistic retrieval models for integrating term statistics with entity search using multiple levels of document context to improve the performance of chemical patent search. A distributed indexing model was developed to enable efficient named entity search and aggregation of term statistics at multiple levels of patent structure including individual words, sentences, claims, descriptions, abstracts, and titles. The system can be scaled to an arbitrary number of compute instances in a cloud computing environment to support concurrent indexing and query processing operations on large patent collections.
-
The Impact of Prophage on the Equilibria and Stability of Phage and Host
NASA Astrophysics Data System (ADS)
Yu, Pei; Nadeem, Alina; Wahl, Lindi M.
2017-06-01
In this paper, we present a bacteriophage model that includes prophage, that is, phage genomes that are incorporated into the host cell genome. The general model is described by an 18-dimensional system of ordinary differential equations. This study focuses on asymptotic behaviour of the model, and thus the system is reduced to a simple six-dimensional model, involving uninfected host cells, infected host cells and phage. We use dynamical system theory to explore the dynamic behaviour of the model, studying in particular the impact of prophage on the equilibria and stability of phage and host. We employ bifurcation and stability theory, centre manifold and normal form theory to show that the system has multiple equilibrium solutions which undergo a series of bifurcations, finally leading to oscillating motions. Numerical simulations are presented to illustrate and confirm the analytical predictions. The results of this study indicate that in some parameter regimes, the host cell population may drive the phage to extinction through diversification, that is, if multiple types of host emerge; this prediction holds even if the phage population is likewise diverse. This parameter regime is restricted, however, if infecting phage are able to recombine with prophage sequences in the host cell genome.
-
1984-09-01
IN SOFTWARE DESIGN ......... .................... 39 P. PROCESS DESCRIPTIONS 43.............3 1. Model Euilding .............. 43 2. M1odel Management ... manager to model a wide variety of technology, price and cost situations without the associated overhead imposed by multiple application-specific systems...The Manager of the National Communications System (NCS) has been tasked by the National Security Telecommunications Policy of 3 August 1983 with
-
Dynamics of coarsening in multicomponent lipid vesicles with non-uniform mechanical properties
NASA Astrophysics Data System (ADS)
Funkhouser, Chloe M.; Solis, Francisco J.; Thornton, K.
2014-04-01
Multicomponent lipid vesicles are commonly used as a model system for the complex plasma membrane. One phenomenon that is studied using such model systems is phase separation. Vesicles composed of simple lipid mixtures can phase-separate into liquid-ordered and liquid-disordered phases, and since these phases can have different mechanical properties, this separation can lead to changes in the shape of the vesicle. In this work, we investigate the dynamics of phase separation in multicomponent lipid vesicles, using a model that couples composition to mechanical properties such as bending rigidity and spontaneous curvature. The model allows the vesicle surface to deform while conserving surface area and composition. For vesicles initialized as spheres, we study the effects of phase fraction and spontaneous curvature. We additionally initialize two systems with elongated, spheroidal shapes. Dynamic behavior is contrasted in systems where only one phase has a spontaneous curvature similar to the overall vesicle surface curvature and systems where the spontaneous curvatures of both phases are similar to the overall curvature. The bending energy contribution is typically found to slow the dynamics by stabilizing configurations with multiple domains. Such multiple-domain configurations are found more often in vesicles with spheroidal shapes than in nearly spherical vesicles.
-
NASA Astrophysics Data System (ADS)
Pozzi, W.; Fekete, B.; Piasecki, M.; McGuinness, D.; Fox, P.; Lawford, R.; Vorosmarty, C.; Houser, P.; Imam, B.
2008-12-01
The inadequacies of water cycle observations for monitoring long-term changes in the global water system, as well as their feedback into the climate system, poses a major constraint on sustainable development of water resources and improvement of water management practices. Hence, The Group on Earth Observations (GEO) has established Task WA-08-01, "Integration of in situ and satellite data for water cycle monitoring," an integrative initiative combining different types of satellite and in situ observations related to key variables of the water cycle with model outputs for improved accuracy and global coverage. This presentation proposes development of the Rapid, Integrated Monitoring System for the Water Cycle (Global-RIMS)--already employed by the GEO Global Terrestrial Network for Hydrology (GTN-H)--as either one of the main components or linked with the Asian system to constitute the modeling system of GEOSS for water cycle monitoring. We further propose expanded, augmented capability to run multiple grids to embrace some of the heterogeneous methods and formats of the Earth Science, Hydrology, and Hydraulic Engineering communities. Different methodologies are employed by the Earth Science (land surface modeling), the Hydrological (GIS), and the Hydraulic Engineering Communities; with each community employing models that require different input data. Data will be routed as input variables to the models through web services, allowing satellite and in situ data to be integrated together within the modeling framework. Semantic data integration will provide the automation to enable this system to operate in near-real-time. Multiple data collections for ground water, precipitation, soil moisture satellite data, such as SMAP, and lake data will require multiple low level ontologies, and an upper level ontology will permit user-friendly water management knowledge to be synthesized. These ontologies will have to have overlapping terms mapped and linked together. so that they can cover an even wider net of data sources. The goal is to develop the means to link together the upper level and lower level ontologies and to have these registered within the GEOSS Registry. Actual operational ontologies that would link to models or link to data collections containing input variables required by models would have to be nested underneath this top level ontology, analogous to the mapping that has been carried out among ontologies within GEON.
-
DOE Office of Scientific and Technical Information (OSTI.GOV)
Tweardy, Matthew C.; McConchie, Seth; Hayward, Jason P.
An extension of the point kinetics model is developed in this paper to describe the neutron multiplicity response of a bare uranium object under interrogation by an associated particle imaging deuterium-tritium (D-T) measurement system. This extended model is used to estimate the total neutron multiplication of the uranium. Both MCNPX-PoliMi simulations and data from active interrogation measurements of highly enriched and depleted uranium geometries are used to evaluate the potential of this method and to identify the sources of systematic error. The detection efficiency correction for measured coincidence response is identified as a large source of systematic error. If themore » detection process is not considered, results suggest that the method can estimate total multiplication to within 13% of the simulated value. Values for multiplicity constants in the point kinetics equations are sensitive to enrichment due to (n, xn) interactions by D-T neutrons and can introduce another significant source of systematic bias. This can theoretically be corrected if isotopic composition is known a priori. Finally, the spatial dependence of multiplication is also suspected of introducing further systematic bias for high multiplication uranium objects.« less
-
Tweardy, Matthew C.; McConchie, Seth; Hayward, Jason P.
2017-06-13
An extension of the point kinetics model is developed in this paper to describe the neutron multiplicity response of a bare uranium object under interrogation by an associated particle imaging deuterium-tritium (D-T) measurement system. This extended model is used to estimate the total neutron multiplication of the uranium. Both MCNPX-PoliMi simulations and data from active interrogation measurements of highly enriched and depleted uranium geometries are used to evaluate the potential of this method and to identify the sources of systematic error. The detection efficiency correction for measured coincidence response is identified as a large source of systematic error. If themore » detection process is not considered, results suggest that the method can estimate total multiplication to within 13% of the simulated value. Values for multiplicity constants in the point kinetics equations are sensitive to enrichment due to (n, xn) interactions by D-T neutrons and can introduce another significant source of systematic bias. This can theoretically be corrected if isotopic composition is known a priori. Finally, the spatial dependence of multiplication is also suspected of introducing further systematic bias for high multiplication uranium objects.« less
-
Li, Guo; Lv, Fei; Guan, Xu
2014-01-01
This paper investigates a collaborative scheduling model in the assembly system, wherein multiple suppliers have to deliver their components to the multiple manufacturers under the operation of Supply-Hub. We first develop two different scenarios to examine the impact of Supply-Hub. One is that suppliers and manufacturers make their decisions separately, and the other is that the Supply-Hub makes joint decisions with collaborative scheduling. The results show that our scheduling model with the Supply-Hub is a NP-complete problem, therefore, we propose an auto-adapted differential evolution algorithm to solve this problem. Moreover, we illustrate that the performance of collaborative scheduling by the Supply-Hub is superior to separate decision made by each manufacturer and supplier. Furthermore, we also show that the algorithm proposed has good convergence and reliability, which can be applicable to more complicated supply chain environment.
-
Lv, Fei; Guan, Xu
2014-01-01
This paper investigates a collaborative scheduling model in the assembly system, wherein multiple suppliers have to deliver their components to the multiple manufacturers under the operation of Supply-Hub. We first develop two different scenarios to examine the impact of Supply-Hub. One is that suppliers and manufacturers make their decisions separately, and the other is that the Supply-Hub makes joint decisions with collaborative scheduling. The results show that our scheduling model with the Supply-Hub is a NP-complete problem, therefore, we propose an auto-adapted differential evolution algorithm to solve this problem. Moreover, we illustrate that the performance of collaborative scheduling by the Supply-Hub is superior to separate decision made by each manufacturer and supplier. Furthermore, we also show that the algorithm proposed has good convergence and reliability, which can be applicable to more complicated supply chain environment. PMID:24892104
-
The quest for solvable multistate Landau-Zener models
Sinitsyn, Nikolai A.; Chernyak, Vladimir Y.
2017-05-24
Recently, integrability conditions (ICs) in mutistate Landau-Zener (MLZ) theory were proposed. They describe common properties of all known solved systems with linearly time-dependent Hamiltonians. Here we show that ICs enable efficient computer assisted search for new solvable MLZ models that span complexity range from several interacting states to mesoscopic systems with many-body dynamics and combinatorially large phase space. This diversity suggests that nontrivial solvable MLZ models are numerous. Additionally, we refine the formulation of ICs and extend the class of solvable systems to models with points of multiple diabatic level crossing.
-
Modeling the lake eutrophication stochastic ecosystem and the research of its stability.
Wang, Bo; Qi, Qianqian
2018-06-01
In the reality, the lake system will be disturbed by stochastic factors including the external and internal factors. By adding the additive noise and the multiplicative noise to the right-hand sides of the model equation, the additive stochastic model and the multiplicative stochastic model are established respectively in order to reduce model errors induced by the absence of some physical processes. For both the two kinds of stochastic ecosystems, the authors studied the bifurcation characteristics with the FPK equation and the Lyapunov exponent method based on the Stratonovich-Khasminiskii stochastic average principle. Results show that, for the additive stochastic model, when control parameter (i.e., nutrient loading rate) falls into the interval [0.388644, 0.66003825], there exists bistability for the ecosystem and the additive noise intensities cannot make the bifurcation point drift. In the region of the bistability, the external stochastic disturbance which is one of the main triggers causing the lake eutrophication, may make the ecosystem unstable and induce a transition. When control parameter (nutrient loading rate) falls into the interval (0, 0.388644) and (0.66003825, 1.0), there only exists a stable equilibrium state and the additive noise intensity could not change it. For the multiplicative stochastic model, there exists more complex bifurcation performance and the multiplicative ecosystem will be broken by the multiplicative noise. Also, the multiplicative noise could reduce the extent of the bistable region, ultimately, the bistable region vanishes for sufficiently large noise. What's more, both the nutrient loading rate and the multiplicative noise will make the ecosystem have a regime shift. On the other hand, for the two kinds of stochastic ecosystems, the authors also discussed the evolution of the ecological variable in detail by using the Four-stage Runge-Kutta method of strong order γ=1.5. The numerical method was found to be capable of effectively explaining the regime shift theory and agreed with the realistic analyze. These conclusions also confirms the two paths for the system to move from one stable state to another proposed by Beisner et al. [3], which may help understand the occurrence mechanism related to the lake eutrophication from the view point of the stochastic model and mathematical analysis. Copyright © 2018 Elsevier Inc. All rights reserved.
-
NASA Astrophysics Data System (ADS)
Zhou, J.; Zeng, X.; Mo, L.; Chen, L.; Jiang, Z.; Feng, Z.; Yuan, L.; He, Z.
2017-12-01
Generally, the adaptive utilization and regulation of runoff in the source region of China's southwest rivers is classified as a typical multi-objective collaborative optimization problem. There are grim competitions and incidence relation in the subsystems of water supply, electricity generation and environment, which leads to a series of complex problems represented by hydrological process variation, blocked electricity output and water environment risk. Mathematically, the difficulties of multi-objective collaborative optimization focus on the description of reciprocal relationships and the establishment of evolving model of adaptive systems. Thus, based on the theory of complex systems science, this project tries to carry out the research from the following aspects: the changing trend of coupled water resource, the covariant factor and driving mechanism, the dynamic evolution law of mutual feedback dynamic process in the supply-generation-environment coupled system, the environmental response and influence mechanism of coupled mutual feedback water resource system, the relationship between leading risk factor and multiple risk based on evolutionary stability and dynamic balance, the transfer mechanism of multiple risk response with the variation of the leading risk factor, the multidimensional coupled feedback system of multiple risk assessment index system and optimized decision theory. Based on the above-mentioned research results, the dynamic method balancing the efficiency of multiple objectives in the coupled feedback system and optimized regulation model of water resources is proposed, and the adaptive scheduling mode considering the internal characteristics and external response of coupled mutual feedback system of water resource is established. In this way, the project can make a contribution to the optimal scheduling theory and methodology of water resource management under uncertainty in the source region of Southwest River.
-
A multiple pointing-mount control strategy for space platforms
NASA Technical Reports Server (NTRS)
Johnson, C. D.
1992-01-01
A new disturbance-adaptive control strategy for multiple pointing-mount space platforms is proposed and illustrated by consideration of a simplified 3-link dynamic model of a multiple pointing-mount space platform. Simulation results demonstrate the effectiveness of the new platform control strategy. The simulation results also reveal a system 'destabilization phenomena' that can occur if the set of individual platform-mounted experiment controllers are 'too responsive.'
-
Liu, Shuguang; Tan, Zhengxi; Chen, Mingshi; Liu, Jinxun; Wein, Anne; Li, Zhengpeng; Huang, Shengli; Oeding, Jennifer; Young, Claudia; Verma, Shashi B.; Suyker, Andrew E.; Faulkner, Stephen P.
2012-01-01
The General Ensemble Biogeochemical Modeling System (GEMS) was es in individual models, it uses multiple site-scale biogeochemical models to perform model simulations. Second, it adopts Monte Carlo ensemble simulations of each simulation unit (one site/pixel or group of sites/pixels with similar biophysical conditions) to incorporate uncertainties and variability (as measured by variances and covariance) of input variables into model simulations. In this chapter, we illustrate the applications of GEMS at the site and regional scales with an emphasis on incorporating agricultural practices. Challenges in modeling soil carbon dynamics and greenhouse emissions are also discussed.
-
Function modeling improves the efficiency of spatial modeling using big data from remote sensing
John Hogland; Nathaniel Anderson
2017-01-01
Spatial modeling is an integral component of most geographic information systems (GISs). However, conventional GIS modeling techniques can require substantial processing time and storage space and have limited statistical and machine learning functionality. To address these limitations, many have parallelized spatial models using multiple coding libraries and have...
-
Short-term electric power demand forecasting based on economic-electricity transmission model
NASA Astrophysics Data System (ADS)
Li, Wenfeng; Bai, Hongkun; Liu, Wei; Liu, Yongmin; Wang, Yubin Mao; Wang, Jiangbo; He, Dandan
2018-04-01
Short-term electricity demand forecasting is the basic work to ensure safe operation of the power system. In this paper, a practical economic electricity transmission model (EETM) is built. With the intelligent adaptive modeling capabilities of Prognoz Platform 7.2, the econometric model consists of three industrial added value and income levels is firstly built, the electricity demand transmission model is also built. By multiple regression, moving averages and seasonal decomposition, the problem of multiple correlations between variables is effectively overcome in EETM. The validity of EETM is proved by comparison with the actual value of Henan Province. Finally, EETM model is used to forecast the electricity consumption of the 1-4 quarter of 2018.
-
IEA Wind Task 37: Systems Modeling Framework and Ontology for Wind Turbines and Plants
DOE Office of Scientific and Technical Information (OSTI.GOV)
Dykes, Katherine L; Zahle, Frederik; Merz, Karl
This presentation will provide an overview of progress to date in the development of a system modeling framework and ontology for wind turbines and plants as part of the larger IEA Wind Task 37 on wind energy systems engineering. The goals of the effort are to create a set of guidelines for a common conceptual architecture for wind turbines and plants so that practitioners can more easily share descriptions of wind turbines and plants across multiple parties and reduce the effort for translating descriptions between models; integrate different models together and collaborate on model development; and translate models among differentmore » levels of fidelity in the system.« less
-
Multi-objective optimization of GENIE Earth system models.
Price, Andrew R; Myerscough, Richard J; Voutchkov, Ivan I; Marsh, Robert; Cox, Simon J
2009-07-13
The tuning of parameters in climate models is essential to provide reliable long-term forecasts of Earth system behaviour. We apply a multi-objective optimization algorithm to the problem of parameter estimation in climate models. This optimization process involves the iterative evaluation of response surface models (RSMs), followed by the execution of multiple Earth system simulations. These computations require an infrastructure that provides high-performance computing for building and searching the RSMs and high-throughput computing for the concurrent evaluation of a large number of models. Grid computing technology is therefore essential to make this algorithm practical for members of the GENIE project.
-
3D cloud detection and tracking system for solar forecast using multiple sky imagers
Peng, Zhenzhou; Yu, Dantong; Huang, Dong; ...
2015-06-23
We propose a system for forecasting short-term solar irradiance based on multiple total sky imagers (TSIs). The system utilizes a novel method of identifying and tracking clouds in three-dimensional space and an innovative pipeline for forecasting surface solar irradiance based on the image features of clouds. First, we develop a supervised classifier to detect clouds at the pixel level and output cloud mask. In the next step, we design intelligent algorithms to estimate the block-wise base height and motion of each cloud layer based on images from multiple TSIs. Thus, this information is then applied to stitch images together intomore » larger views, which are then used for solar forecasting. We examine the system’s ability to track clouds under various cloud conditions and investigate different irradiance forecast models at various sites. We confirm that this system can 1) robustly detect clouds and track layers, and 2) extract the significant global and local features for obtaining stable irradiance forecasts with short forecast horizons from the obtained images. Finally, we vet our forecasting system at the 32-megawatt Long Island Solar Farm (LISF). Compared with the persistent model, our system achieves at least a 26% improvement for all irradiance forecasts between one and fifteen minutes.« less
-
Noise Modeling From Conductive Shields Using Kirchhoff Equations.
Sandin, Henrik J; Volegov, Petr L; Espy, Michelle A; Matlashov, Andrei N; Savukov, Igor M; Schultz, Larry J
2010-10-09
Progress in the development of high-sensitivity magnetic-field measurements has stimulated interest in understanding the magnetic noise of conductive materials, especially of magnetic shields based on high-permeability materials and/or high-conductivity materials. For example, SQUIDs and atomic magnetometers have been used in many experiments with mu-metal shields, and additionally SQUID systems frequently have radio frequency shielding based on thin conductive materials. Typical existing approaches to modeling noise only work with simple shield and sensor geometries while common experimental setups today consist of multiple sensor systems with complex shield geometries. With complex sensor arrays used in, for example, MEG and Ultra Low Field MRI studies, knowledge of the noise correlation between sensors is as important as knowledge of the noise itself. This is crucial for incorporating efficient noise cancelation schemes for the system. We developed an approach that allows us to calculate the Johnson noise for arbitrary shaped shields and multiple sensor systems. The approach is efficient enough to be able to run on a single PC system and return results on a minute scale. With a multiple sensor system our approach calculates not only the noise for each sensor but also the noise correlation matrix between sensors. Here we will show how the algorithm can be implemented.
-
Deciding the liveness for a subclass of weighted Petri nets based on structurally circular wait
NASA Astrophysics Data System (ADS)
Liu, GuanJun; Chen, LiJing
2016-05-01
Weighted Petri nets as a kind of formal language are widely used to model and verify discrete event systems related to resource allocation like flexible manufacturing systems. System of Simple Sequential Processes with Multi-Resources (S3PMR, a subclass of weighted Petri nets and an important extension to the well-known System of Simple Sequential Processes with Resources, can model many discrete event systems in which (1) multiple processes may run in parallel and (2) each execution step of each process may use multiple units from multiple resource types. This paper gives a necessary and sufficient condition for the liveness of S3PMR. A new structural concept called Structurally Circular Wait (SCW) is proposed for S3PMR. Blocking Marking (BM) associated with an SCW is defined. It is proven that a marked S3PMR is live if and only if each SCW has no BM. We use an example of multi-processor system-on-chip to show that SCW and BM can precisely characterise the (partial) deadlocks for S3PMR. Simultaneously, two examples are used to show the advantages of SCW in preventing deadlocks of S3PMR. These results are significant for the further research on dealing with the deadlock problem.
-
NASA Astrophysics Data System (ADS)
Satyanarayana, S.; Indrakanti, S.; Kim, J.; Kim, C.; Pamidi, S.
2017-12-01
Benefits of an integrated high temperature superconducting (HTS) power system and the associated cryogenic systems on board an electric ship or aircraft are discussed. A versatile modelling methodology developed to assess the cryogenic thermal behavior of the integrated system with multiple HTS devices and the various potential configurations are introduced. The utility and effectiveness of the developed modelling methodology is demonstrated using a case study involving a hypothetical system including an HTS propulsion motor, an HTS generator and an HTS power cable cooled by an integrated cryogenic helium circulation system. Using the methodology, multiple configurations are studied. The required total cooling power and the ability to maintain each HTS device at the required operating temperatures are considered for each configuration and the trade-offs are discussed for each configuration. Transient analysis of temperature evolution in the cryogenic helium circulation loop in case of a system failure is carried out to arrive at the required critical response time. The analysis was also performed for a similar liquid nitrogen circulation for an isobaric condition and the cooling capacity ratio is used to compare the relative merits of the two cryogens.
-
Blinov, Michael L.; Moraru, Ion I.
2011-01-01
Multi-state molecules and multi-component complexes are commonly involved in cellular signaling. Accounting for molecules that have multiple potential states, such as a protein that may be phosphorylated on multiple residues, and molecules that combine to form heterogeneous complexes located among multiple compartments, generates an effect of combinatorial complexity. Models involving relatively few signaling molecules can include thousands of distinct chemical species. Several software tools (StochSim, BioNetGen) are already available to deal with combinatorial complexity. Such tools need information standards if models are to be shared, jointly evaluated and developed. Here we discuss XML conventions that can be adopted for modeling biochemical reaction networks described by user-specified reaction rules. These could form a basis for possible future extensions of the Systems Biology Markup Language (SBML). PMID:21464833
-
The big data-big model (BDBM) challenges in ecological research
NASA Astrophysics Data System (ADS)
Luo, Y.
2015-12-01
The field of ecology has become a big-data science in the past decades due to development of new sensors used in numerous studies in the ecological community. Many sensor networks have been established to collect data. For example, satellites, such as Terra and OCO-2 among others, have collected data relevant on global carbon cycle. Thousands of field manipulative experiments have been conducted to examine feedback of terrestrial carbon cycle to global changes. Networks of observations, such as FLUXNET, have measured land processes. In particular, the implementation of the National Ecological Observatory Network (NEON), which is designed to network different kinds of sensors at many locations over the nation, will generate large volumes of ecological data every day. The raw data from sensors from those networks offer an unprecedented opportunity for accelerating advances in our knowledge of ecological processes, educating teachers and students, supporting decision-making, testing ecological theory, and forecasting changes in ecosystem services. Currently, ecologists do not have the infrastructure in place to synthesize massive yet heterogeneous data into resources for decision support. It is urgent to develop an ecological forecasting system that can make the best use of multiple sources of data to assess long-term biosphere change and anticipate future states of ecosystem services at regional and continental scales. Forecasting relies on big models that describe major processes that underlie complex system dynamics. Ecological system models, despite great simplification of the real systems, are still complex in order to address real-world problems. For example, Community Land Model (CLM) incorporates thousands of processes related to energy balance, hydrology, and biogeochemistry. Integration of massive data from multiple big data sources with complex models has to tackle Big Data-Big Model (BDBM) challenges. Those challenges include interoperability of multiple, heterogeneous data sets; intractability of structural complexity of big models; equifinality of model structure selection and parameter estimation; and computational demand of global optimization with Big Models.
-
Interfacing a General Purpose Fluid Network Flow Program with the SINDA/G Thermal Analysis Program
NASA Technical Reports Server (NTRS)
Schallhorn, Paul; Popok, Daniel
1999-01-01
A general purpose, one dimensional fluid flow code is currently being interfaced with the thermal analysis program Systems Improved Numerical Differencing Analyzer/Gaski (SINDA/G). The flow code, Generalized Fluid System Simulation Program (GFSSP), is capable of analyzing steady state and transient flow in a complex network. The flow code is capable of modeling several physical phenomena including compressibility effects, phase changes, body forces (such as gravity and centrifugal) and mixture thermodynamics for multiple species. The addition of GFSSP to SINDA/G provides a significant improvement in convective heat transfer modeling for SINDA/G. The interface development is conducted in multiple phases. This paper describes the first phase of the interface which allows for steady and quasi-steady (unsteady solid, steady fluid) conjugate heat transfer modeling.
-
High-resolution imaging using a wideband MIMO radar system with two distributed arrays.
Wang, Dang-wei; Ma, Xiao-yan; Chen, A-Lei; Su, Yi
2010-05-01
Imaging a fast maneuvering target has been an active research area in past decades. Usually, an array antenna with multiple elements is implemented to avoid the motion compensations involved in the inverse synthetic aperture radar (ISAR) imaging. Nevertheless, there is a price dilemma due to the high level of hardware complexity compared to complex algorithm implemented in the ISAR imaging system with only one antenna. In this paper, a wideband multiple-input multiple-output (MIMO) radar system with two distributed arrays is proposed to reduce the hardware complexity of the system. Furthermore, the system model, the equivalent array production method and the imaging procedure are presented. As compared with the classical real aperture radar (RAR) imaging system, there is a very important contribution in our method that the lower hardware complexity can be involved in the imaging system since many additive virtual array elements can be obtained. Numerical simulations are provided for testing our system and imaging method.
-
NASA Technical Reports Server (NTRS)
Ho, P. T.; Coban, E.; Pelose, J.
1983-01-01
The design and development of a unique coupler crossbar 20 x 20 microwave switch matrix are described. The test results of the proof of concept model that meets the requirements for a high speed satellite switched, time division multiple access (SS-TDMA) system are presented.
-
A probabilistic process model for pelagic marine ecosystems informed by Bayesian inverse analysis
Marine ecosystems are complex systems with multiple pathways that produce feedback cycles, which may lead to unanticipated effects. Models abstract this complexity and allow us to predict, understand, and hypothesize. In ecological models, however, the paucity of empirical data...
-
2013-10-21
depend on the quality of allocating resources. This work uses a reliability model of system and environmental covariates incorporating information at...state space. Further, the use of condition variables allows for the direct modeling of maintenance impact with the assumption that a nominal value ... value ), the model in the application of aviation maintenance can provide a useful estimation of reliability at multiple levels. Adjusted survival
-
Tree root systems competing for soil moisture in a 3D soil–plant model
Gabriele Manoli; Sara Bonetti; Jean-Christophe Domec; Mario Putti; Gabriel Katul; Marco Marani
2014-01-01
Competition for water among multiple tree rooting systems is investigated using a soilâplant model that accounts for soil moisture dynamics and root water uptake (RWU), whole plant transpiration, and leaflevel photosynthesis. The model is based on a numerical solution to the 3D Richards equation modified to account for a 3D RWU, trunk xylem, and stomatal conductances....
-
Validation of a Sensor-Driven Modeling Paradigm for Multiple Source Reconstruction with FFT-07 Data
2009-05-01
operational warning and reporting (information) systems that combine automated data acquisition, analysis , source reconstruction, display and distribution of...report and to incorporate this operational ca- pability into the integrative multiscale urban modeling system implemented in the com- putational...Journal of Fluid Mechanics, 180, 529–556. [27] Flesch, T., Wilson, J. D., and Yee, E. (1995), Backward- time Lagrangian stochastic dispersion models
-
Dai, Heng; Ye, Ming; Walker, Anthony P.; ...
2017-03-28
A hydrological model consists of multiple process level submodels, and each submodel represents a process key to the operation of the simulated system. Global sensitivity analysis methods have been widely used to identify important processes for system model development and improvement. The existing methods of global sensitivity analysis only consider parametric uncertainty, and are not capable of handling model uncertainty caused by multiple process models that arise from competing hypotheses about one or more processes. To address this problem, this study develops a new method to probe model output sensitivity to competing process models by integrating model averaging methods withmore » variance-based global sensitivity analysis. A process sensitivity index is derived as a single summary measure of relative process importance, and the index includes variance in model outputs caused by uncertainty in both process models and their parameters. Here, for demonstration, the new index is used to assign importance to the processes of recharge and geology in a synthetic study of groundwater reactive transport modeling. The recharge process is simulated by two models that convert precipitation to recharge, and the geology process is simulated by two models of hydraulic conductivity. Each process model has its own random parameters. Finally, the new process sensitivity index is mathematically general, and can be applied to a wide range of problems in hydrology and beyond.« less
-
DOE Office of Scientific and Technical Information (OSTI.GOV)
Dai, Heng; Ye, Ming; Walker, Anthony P.
A hydrological model consists of multiple process level submodels, and each submodel represents a process key to the operation of the simulated system. Global sensitivity analysis methods have been widely used to identify important processes for system model development and improvement. The existing methods of global sensitivity analysis only consider parametric uncertainty, and are not capable of handling model uncertainty caused by multiple process models that arise from competing hypotheses about one or more processes. To address this problem, this study develops a new method to probe model output sensitivity to competing process models by integrating model averaging methods withmore » variance-based global sensitivity analysis. A process sensitivity index is derived as a single summary measure of relative process importance, and the index includes variance in model outputs caused by uncertainty in both process models and their parameters. Here, for demonstration, the new index is used to assign importance to the processes of recharge and geology in a synthetic study of groundwater reactive transport modeling. The recharge process is simulated by two models that convert precipitation to recharge, and the geology process is simulated by two models of hydraulic conductivity. Each process model has its own random parameters. Finally, the new process sensitivity index is mathematically general, and can be applied to a wide range of problems in hydrology and beyond.« less
-
An integrative model of evolutionary covariance: a symposium on body shape in fishes.
Walker, Jeffrey A
2010-12-01
A major direction of current and future biological research is to understand how multiple, interacting functional systems coordinate in producing a body that works. This understanding is complicated by the fact that organisms need to work well in multiple environments, with both predictable and unpredictable environmental perturbations. Furthermore, organismal design reflects a history of past environments and not a plan for future environments. How complex, interacting functional systems evolve, then, is a truly grand challenge. In accepting the challenge, an integrative model of evolutionary covariance is developed. The model combines quantitative genetics, functional morphology/physiology, and functional ecology. The model is used to convene scientists ranging from geneticists, to physiologists, to ecologists, to engineers to facilitate the emergence of body shape in fishes as a model system for understanding how complex, interacting functional systems develop and evolve. Body shape of fish is a complex morphology that (1) results from many developmental paths and (2) functions in many different behaviors. Understanding the coordination and evolution of the many paths from genes to body shape, body shape to function, and function to a working fish body in a dynamic environment is now possible given new technologies from genetics to engineering and new theoretical models that integrate the different levels of biological organization (from genes to ecology).
-
DOE Office of Scientific and Technical Information (OSTI.GOV)
Johnson, Traci L.; Sharon, Keren, E-mail: tljohn@umich.edu
Until now, systematic errors in strong gravitational lens modeling have been acknowledged but have never been fully quantified. Here, we launch an investigation into the systematics induced by constraint selection. We model the simulated cluster Ares 362 times using random selections of image systems with and without spectroscopic redshifts and quantify the systematics using several diagnostics: image predictability, accuracy of model-predicted redshifts, enclosed mass, and magnification. We find that for models with >15 image systems, the image plane rms does not decrease significantly when more systems are added; however, the rms values quoted in the literature may be misleading asmore » to the ability of a model to predict new multiple images. The mass is well constrained near the Einstein radius in all cases, and systematic error drops to <2% for models using >10 image systems. Magnification errors are smallest along the straight portions of the critical curve, and the value of the magnification is systematically lower near curved portions. For >15 systems, the systematic error on magnification is ∼2%. We report no trend in magnification error with the fraction of spectroscopic image systems when selecting constraints at random; however, when using the same selection of constraints, increasing this fraction up to ∼0.5 will increase model accuracy. The results suggest that the selection of constraints, rather than quantity alone, determines the accuracy of the magnification. We note that spectroscopic follow-up of at least a few image systems is crucial because models without any spectroscopic redshifts are inaccurate across all of our diagnostics.« less
-
The Development of the Speaker Independent ARM Continuous Speech Recognition System
1992-01-01
spokeTi airborne reconnaissance reports u-ing a speech recognition system based on phoneme-level hidden Markov models (HMMs). Previous versions of the ARM...will involve automatic selection from multiple model sets, corresponding to different speaker types, and that the most rudimen- tary partition of a...The vocabulary size for the ARM task is 497 words. These words are related to the phoneme-level symbols corresponding to the models in the model set
-
Marmarelis, Vasilis Z.; Zanos, Theodoros P.; Berger, Theodore W.
2010-01-01
This paper presents a new modeling approach for neural systems with point-process (spike) inputs and outputs that utilizes Boolean operators (i.e. modulo 2 multiplication and addition that correspond to the logical AND and OR operations respectively, as well as the AND_NOT logical operation representing inhibitory effects). The form of the employed mathematical models is akin to a “Boolean-Volterra” model that contains the product terms of all relevant input lags in a hierarchical order, where terms of order higher than first represent nonlinear interactions among the various lagged values of each input point-process or among lagged values of various inputs (if multiple inputs exist) as they reflect on the output. The coefficients of this Boolean-Volterra model are also binary variables that indicate the presence or absence of the respective term in each specific model/system. Simulations are used to explore the properties of such models and the feasibility of their accurate estimation from short data-records in the presence of noise (i.e. spurious spikes). The results demonstrate the feasibility of obtaining reliable estimates of such models, with excitatory and inhibitory terms, in the presence of considerable noise (spurious spikes) in the outputs and/or the inputs in a computationally efficient manner. A pilot application of this approach to an actual neural system is presented in the companion paper (Part II). PMID:19517238
-
Adam, Jennifer C.; Stephens, Jennie C.; Chung, Serena H.; ...
2014-04-24
Uncertainties in global change impacts, the complexities associated with the interconnected cycling of nitrogen, carbon, and water present daunting management challenges. Existing models provide detailed information on specific sub-systems (e.g., land, air, water, and economics). An increasing awareness of the unintended consequences of management decisions resulting from interconnectedness of these sub-systems, however, necessitates coupled regional earth system models (EaSMs). Decision makers’ needs and priorities can be integrated into the model design and development processes to enhance decision-making relevance and “usability” of EaSMs. BioEarth is a research initiative currently under development with a focus on the U.S. Pacific Northwest region thatmore » explores the coupling of multiple stand-alone EaSMs to generate usable information for resource decision-making. Direct engagement between model developers and non-academic stakeholders involved in resource and environmental management decisions throughout the model development process is a critical component of this effort. BioEarth utilizes a bottom-up approach for its land surface model that preserves fine spatial-scale sensitivities and lateral hydrologic connectivity, which makes it unique among many regional EaSMs. Here, we describe the BioEarth initiative and highlights opportunities and challenges associated with coupling multiple stand-alone models to generate usable information for agricultural and natural resource decision-making.« less
-
Reducing the net torque and flow ripple effects of multiple hydraulic piston motor drives
NASA Technical Reports Server (NTRS)
Bartos, R. D.
1992-01-01
The torque and flow ripple effects which result when multiple hydraulic motors are used to drive a single motion of a mechanical device can significantly affect the way in which the device performs. This article presents a mathematical model describing the torque and flow ripple effects of a bent-axis hydraulic piston motor. The model is used to show how the ripple magnitude can be reduced when multiple motors are used to drive a motion. A discussion of the hydraulic servo system of the 70-m antennas located with the Deep Space Network is included to demonstrate the application of the concepts presented.
-
Federal Register 2010, 2011, 2012, 2013, 2014
2010-12-13
... Unusual Design Features The GVI will have a fly-by-wire electronic flight control system. This system... the design of the flight control system has multiple modes of operation, a means must be provided to... Control System Mode Annunciation AGENCY: Federal Aviation Administration (FAA), DOT. ACTION: Notice of...
-
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.
-
NASA Astrophysics Data System (ADS)
Vilhelmsen, Troels N.; Ferré, Ty P. A.
2016-04-01
Hydrological models are often developed to forecasting future behavior in response due to natural or human induced changes in stresses affecting hydrologic systems. Commonly, these models are conceptualized and calibrated based on existing data/information about the hydrological conditions. However, most hydrologic systems lack sufficient data to constrain models with adequate certainty to support robust decision making. Therefore, a key element of a hydrologic study is the selection of additional data to improve model performance. Given the nature of hydrologic investigations, it is not practical to select data sequentially, i.e. to choose the next observation, collect it, refine the model, and then repeat the process. Rather, for timing and financial reasons, measurement campaigns include multiple wells or sampling points. There is a growing body of literature aimed at defining the expected data worth based on existing models. However, these are almost all limited to identifying single additional observations. In this study, we present a methodology for simultaneously selecting multiple potential new observations based on their expected ability to reduce the uncertainty of the forecasts of interest. This methodology is based on linear estimates of the predictive uncertainty, and it can be used to determine the optimal combinations of measurements (location and number) established to reduce the uncertainty of multiple predictions. The outcome of the analysis is an estimate of the optimal sampling locations; the optimal number of samples; as well as a probability map showing the locations within the investigated area that are most likely to provide useful information about the forecasting of interest.
-
Aviation Safety Risk Modeling: Lessons Learned From Multiple Knowledge Elicitation Sessions
NASA Technical Reports Server (NTRS)
Luxhoj, J. T.; Ancel, E.; Green, L. L.; Shih, A. T.; Jones, S. M.; Reveley, M. S.
2014-01-01
Aviation safety risk modeling has elements of both art and science. In a complex domain, such as the National Airspace System (NAS), it is essential that knowledge elicitation (KE) sessions with domain experts be performed to facilitate the making of plausible inferences about the possible impacts of future technologies and procedures. This study discusses lessons learned throughout the multiple KE sessions held with domain experts to construct probabilistic safety risk models for a Loss of Control Accident Framework (LOCAF), FLightdeck Automation Problems (FLAP), and Runway Incursion (RI) mishap scenarios. The intent of these safety risk models is to support a portfolio analysis of NASA's Aviation Safety Program (AvSP). These models use the flexible, probabilistic approach of Bayesian Belief Networks (BBNs) and influence diagrams to model the complex interactions of aviation system risk factors. Each KE session had a different set of experts with diverse expertise, such as pilot, air traffic controller, certification, and/or human factors knowledge that was elicited to construct a composite, systems-level risk model. There were numerous "lessons learned" from these KE sessions that deal with behavioral aggregation, conditional probability modeling, object-oriented construction, interpretation of the safety risk results, and model verification/validation that are presented in this paper.
-
NASA Technical Reports Server (NTRS)
Simmons, J.; Erlich, D.; Shockey, D.
2009-01-01
A team consisting of Arizona State University, Honeywell Engines, Systems & Services, the National Aeronautics and Space Administration Glenn Research Center, and SRI International collaborated to develop computational models and verification testing for designing and evaluating turbine engine fan blade fabric containment structures. This research was conducted under the Federal Aviation Administration Airworthiness Assurance Center of Excellence and was sponsored by the Aircraft Catastrophic Failure Prevention Program. The research was directed toward improving the modeling of a turbine engine fabric containment structure for an engine blade-out containment demonstration test required for certification of aircraft engines. The research conducted in Phase II began a new level of capability to design and develop fan blade containment systems for turbine engines. Significant progress was made in three areas: (1) further development of the ballistic fabric model to increase confidence and robustness in the material models for the Kevlar(TradeName) and Zylon(TradeName) material models developed in Phase I, (2) the capability was improved for finite element modeling of multiple layers of fabric using multiple layers of shell elements, and (3) large-scale simulations were performed. This report concentrates on the material model development and simulations of the impact tests.
-
Impact of nonzero boresight pointing error on ergodic capacity of MIMO FSO communication systems.
Boluda-Ruiz, Rubén; García-Zambrana, Antonio; Castillo-Vázquez, Beatriz; Castillo-Vázquez, Carmen
2016-02-22
A thorough investigation of the impact of nonzero boresight pointing errors on the ergodic capacity of multiple-input/multiple-output (MIMO) free-space optical (FSO) systems with equal gain combining (EGC) reception under different turbulence models, which are modeled as statistically independent, but not necessarily identically distributed (i.n.i.d.) is addressed in this paper. Novel closed-form asymptotic expressions at high signal-to-noise ratio (SNR) for the ergodic capacity of MIMO FSO systems are derived when different geometric arrangements of the receive apertures at the receiver are considered in order to reduce the effect of nonzero inherent boresight displacement, which is inevitably present when more than one receive aperture is considered. As a result, the asymptotic ergodic capacity of MIMO FSO systems is evaluated over log-normal (LN), gamma-gamma (GG) and exponentiated Weibull (EW) atmospheric turbulence in order to study different turbulence conditions, different sizes of receive apertures as well as different aperture averaging conditions. It is concluded that the use of single-input/multiple-output (SIMO) and MIMO techniques can significantly increase the ergodic capacity respect to the direct path link when the inherent boresight displacement takes small values, i.e. when the spacing among receive apertures is not too big. The effect of nonzero additional boresight errors, which is due to the thermal expansion of the building, is evaluated in multiple-input/single-output (MISO) and single-input/single-output (SISO) FSO systems. Simulation results are further included to confirm the analytical results.
-
Hierarchical Modeling and Robust Synthesis for the Preliminary Design of Large Scale Complex Systems
NASA Technical Reports Server (NTRS)
Koch, Patrick N.
1997-01-01
Large-scale complex systems are characterized by multiple interacting subsystems and the analysis of multiple disciplines. The design and development of such systems inevitably requires the resolution of multiple conflicting objectives. The size of complex systems, however, prohibits the development of comprehensive system models, and thus these systems must be partitioned into their constituent parts. Because simultaneous solution of individual subsystem models is often not manageable iteration is inevitable and often excessive. In this dissertation these issues are addressed through the development of a method for hierarchical robust preliminary design exploration to facilitate concurrent system and subsystem design exploration, for the concurrent generation of robust system and subsystem specifications for the preliminary design of multi-level, multi-objective, large-scale complex systems. This method is developed through the integration and expansion of current design techniques: Hierarchical partitioning and modeling techniques for partitioning large-scale complex systems into more tractable parts, and allowing integration of subproblems for system synthesis; Statistical experimentation and approximation techniques for increasing both the efficiency and the comprehensiveness of preliminary design exploration; and Noise modeling techniques for implementing robust preliminary design when approximate models are employed. Hierarchical partitioning and modeling techniques including intermediate responses, linking variables, and compatibility constraints are incorporated within a hierarchical compromise decision support problem formulation for synthesizing subproblem solutions for a partitioned system. Experimentation and approximation techniques are employed for concurrent investigations and modeling of partitioned subproblems. A modified composite experiment is introduced for fitting better predictive models across the ranges of the factors, and an approach for constructing partitioned response surfaces is developed to reduce the computational expense of experimentation for fitting models in a large number of factors. Noise modeling techniques are compared and recommendations are offered for the implementation of robust design when approximate models are sought. These techniques, approaches, and recommendations are incorporated within the method developed for hierarchical robust preliminary design exploration. This method as well as the associated approaches are illustrated through their application to the preliminary design of a commercial turbofan turbine propulsion system. The case study is developed in collaboration with Allison Engine Company, Rolls Royce Aerospace, and is based on the Allison AE3007 existing engine designed for midsize commercial, regional business jets. For this case study, the turbofan system-level problem is partitioned into engine cycle design and configuration design and a compressor modules integrated for more detailed subsystem-level design exploration, improving system evaluation. The fan and low pressure turbine subsystems are also modeled, but in less detail. Given the defined partitioning, these subproblems are investigated independently and concurrently, and response surface models are constructed to approximate the responses of each. These response models are then incorporated within a commercial turbofan hierarchical compromise decision support problem formulation. Five design scenarios are investigated, and robust solutions are identified. The method and solutions identified are verified by comparison with the AE3007 engine. The solutions obtained are similar to the AE3007 cycle and configuration, but are better with respect to many of the requirements.
-
Airport Noise Prediction Model -- MOD 7
DOT National Transportation Integrated Search
1978-07-01
The MOD 7 Airport Noise Prediction Model is fully operational. The language used is Fortran, and it has been run on several different computer systems. Its capabilities include prediction of noise levels for single parameter changes, for multiple cha...
-
Circumferential distortion modeling of the TF30-P-3 compression system
NASA Technical Reports Server (NTRS)
Mazzawy, R. S.; Banks, G. A.
1977-01-01
Circumferential inlet pressure and temperature distortion testing of the TF30 P-3 turbofan engine was conducted. The compressor system at the test conditions run was modelled according to a multiple segment parallel compressor model. Aspects of engine operation and distortion configuration modelled include the effects of compressor bleeds, relative pressure-temperature distortion alignment and circumferential distortion extent. Model predictions for limiting distortion amplitudes and flow distributions within the compression system were compared with test results in order to evaluate predicted trends. Relatively good agreement was obtained. The model also identified the low pressure compressor as the stall-initiating component, which was in agreement with the data.
-
Olivier, Alicia K.; Gibson-Corley, Katherine N.
2015-01-01
Multiple organ systems, including the gastrointestinal tract, pancreas, and hepatobiliary systems, are affected by cystic fibrosis (CF). Many of these changes begin early in life and are difficult to study in young CF patients. Recent development of novel CF animal models has expanded opportunities in the field to better understand CF pathogenesis and evaluate traditional and innovative therapeutics. In this review, we discuss manifestations of CF disease in gastrointestinal, pancreatic, and hepatobiliary systems of humans and animal models. We also compare the similarities and limitations of animal models and discuss future directions for modeling CF. PMID:25591863
-
How Do Multiple-Star Systems Form? VLA Study Reveals "Smoking Gun"
NASA Astrophysics Data System (ADS)
2006-12-01
Astronomers have used the National Science Foundation's Very Large Array (VLA) radio telescope to image a young, multiple-star system with unprecedented detail, yielding important clues about how such systems are formed. Most Sun-sized or larger stars in the Universe are not single, like our Sun, but are members of multiple-star systems. Astronomers have been divided on how such systems can form, producing competing theoretical models for this process. Multiple Star Formation Graphic Proposed Formation Process for L1551 IRS5 CREDIT: Bill Saxton, NRAO/AUI/NSF Click on image for page of graphics and full information The new VLA study produced a "smoking gun" supporting one of the competing models, said Jeremy Lim, of the Institute of Astronomy & Astrophysics, Academia Sinica, in Taipei, Taiwan, whose study, done with Shigehisa Takakuwa of the National Astronomical Observatory of Japan, is published in the December 10 issue of the Astrophysical Journal. Ironically, their discovery of a third, previously-unknown, young star in the system may support a second theoretical model. "There may be more than one way to make a multiple-star system," Lim explained. The astronomers observed an object called L1551 IRS5, young, still-forming protostars enshrouded in a cloud of gas and dust, some 450 light-years from Earth in the direction of the constellation Taurus. Invisible to optical telescopes because of the gas and dust, this object was discovered in 1976 by astronomers using infrared telescopes. A VLA study in 1998 showed two young stars orbiting each other, each surrounded by a disk of dust that may, in time, congeal into a system of planets. Lim and Takakuwa re-examined the system, using improved technical capabilities that greatly boosted the quality of their images. "In the earlier VLA study, only half of the VLA's 27 antennas had receivers that could collect the radio waves, at a frequency of 43 GigaHertz (GHz), coming from the dusty disks. When we re-observed this system, all the antennas could provide data for us. In addition, we improved the level of detail by using the Pie Town, NM, antenna of the Very Long Baseline Array, as part of an expanded system," Lim said. The implementation and improvement of the 43 GHz receiving system was a collaborative program among the German Max Planck Institute, the Mexican National Autonomous University, and the U.S. National Radio Astronomy Observatory. Two popular theoretical models for the formation of multiple-star systems are, first, that the two protostars and their surrounding dusty disks fragment from a larger parent disk, and, second, that the protostars form independently and then one captures the other into a mutual orbit. "Our new study shows that the disks of the two main protostars are aligned with each other, and also are aligned with the larger, surrounding disk. In addition, their orbital motion resembles the rotation of the larger disk. This is a 'smoking gun' supporting the fragmentation model," Lim said. However, the new study also revealed a third young star with a dust disk. "The disk of this one is misaligned with those of the other two, so it may be the result of either fragmentation or capture," Takakuwa said. The misalignment of the third disk could have come through gravitational interactions with the other two, larger, protostars, the scientists said. They plan further observations to try to resolve the question. "We have a very firm indication that two of these protostars and their dust disks formed from the same, larger disk-like cloud, then broke out from it in a fragmentation process. That strongly supports one theoretical model for how multiple-star systems are formed. The misalignment of the third protostar and its disk leaves open the possibility that it could have formed elsewhere and been captured, and we'll continue to work on reconstructing the history of this fascinating system," Lim summarized. The National Radio Astronomy Observatory is a facility of the National Science Foundation, operated under cooperative agreement by Associated Universities, Inc.
-
Wiki-Based Data Management to Support Systems Toxicology
As the field of toxicology relies more heavily on systems approaches for mode of action discovery, evaluation, and modeling, the need for integrated data management is greater than ever. To meet these needs, we have developed a flexible system that assists individual or multiple...
-
Integrating neuroinformatics tools in TheVirtualBrain.
Woodman, M Marmaduke; Pezard, Laurent; Domide, Lia; Knock, Stuart A; Sanz-Leon, Paula; Mersmann, Jochen; McIntosh, Anthony R; Jirsa, Viktor
2014-01-01
TheVirtualBrain (TVB) is a neuroinformatics Python package representing the convergence of clinical, systems, and theoretical neuroscience in the analysis, visualization and modeling of neural and neuroimaging dynamics. TVB is composed of a flexible simulator for neural dynamics measured across scales from local populations to large-scale dynamics measured by electroencephalography (EEG), magnetoencephalography (MEG) and functional magnetic resonance imaging (fMRI), and core analytic and visualization functions, all accessible through a web browser user interface. A datatype system modeling neuroscientific data ties together these pieces with persistent data storage, based on a combination of SQL and HDF5. These datatypes combine with adapters allowing TVB to integrate other algorithms or computational systems. TVB provides infrastructure for multiple projects and multiple users, possibly participating under multiple roles. For example, a clinician might import patient data to identify several potential lesion points in the patient's connectome. A modeler, working on the same project, tests these points for viability through whole brain simulation, based on the patient's connectome, and subsequent analysis of dynamical features. TVB also drives research forward: the simulator itself represents the culmination of several simulation frameworks in the modeling literature. The availability of the numerical methods, set of neural mass models and forward solutions allows for the construction of a wide range of brain-scale simulation scenarios. This paper briefly outlines the history and motivation for TVB, describing the framework and simulator, giving usage examples in the web UI and Python scripting.
-
Integrating neuroinformatics tools in TheVirtualBrain
Woodman, M. Marmaduke; Pezard, Laurent; Domide, Lia; Knock, Stuart A.; Sanz-Leon, Paula; Mersmann, Jochen; McIntosh, Anthony R.; Jirsa, Viktor
2014-01-01
TheVirtualBrain (TVB) is a neuroinformatics Python package representing the convergence of clinical, systems, and theoretical neuroscience in the analysis, visualization and modeling of neural and neuroimaging dynamics. TVB is composed of a flexible simulator for neural dynamics measured across scales from local populations to large-scale dynamics measured by electroencephalography (EEG), magnetoencephalography (MEG) and functional magnetic resonance imaging (fMRI), and core analytic and visualization functions, all accessible through a web browser user interface. A datatype system modeling neuroscientific data ties together these pieces with persistent data storage, based on a combination of SQL and HDF5. These datatypes combine with adapters allowing TVB to integrate other algorithms or computational systems. TVB provides infrastructure for multiple projects and multiple users, possibly participating under multiple roles. For example, a clinician might import patient data to identify several potential lesion points in the patient's connectome. A modeler, working on the same project, tests these points for viability through whole brain simulation, based on the patient's connectome, and subsequent analysis of dynamical features. TVB also drives research forward: the simulator itself represents the culmination of several simulation frameworks in the modeling literature. The availability of the numerical methods, set of neural mass models and forward solutions allows for the construction of a wide range of brain-scale simulation scenarios. This paper briefly outlines the history and motivation for TVB, describing the framework and simulator, giving usage examples in the web UI and Python scripting. PMID:24795617
-
A data management system for engineering and scientific computing
NASA Technical Reports Server (NTRS)
Elliot, L.; Kunii, H. S.; Browne, J. C.
1978-01-01
Data elements and relationship definition capabilities for this data management system are explicitly tailored to the needs of engineering and scientific computing. System design was based upon studies of data management problems currently being handled through explicit programming. The system-defined data element types include real scalar numbers, vectors, arrays and special classes of arrays such as sparse arrays and triangular arrays. The data model is hierarchical (tree structured). Multiple views of data are provided at two levels. Subschemas provide multiple structural views of the total data base and multiple mappings for individual record types are supported through the use of a REDEFINES capability. The data definition language and the data manipulation language are designed as extensions to FORTRAN. Examples of the coding of real problems taken from existing practice in the data definition language and the data manipulation language are given.
-
Calculating the habitable zones of multiple star systems with a new interactive Web site
DOE Office of Scientific and Technical Information (OSTI.GOV)
Müller, Tobias W. A.; Haghighipour, Nader
We have developed a comprehensive methodology and an interactive Web site for calculating the habitable zone (HZ) of multiple star systems. Using the concept of spectral weight factor, as introduced in our previous studies of the calculations of HZ in and around binary star systems, we calculate the contribution of each star (based on its spectral energy distribution) to the total flux received at the top of the atmosphere of an Earth-like planet, and use the models of the HZ of the Sun to determine the boundaries of the HZ in multiple star systems. Our interactive Web site for carryingmore » out these calculations is publicly available at http://astro.twam.info/hz. We discuss the details of our methodology and present its application to some of the multiple star systems detected by the Kepler space telescope. We also present the instructions for using our interactive Web site, and demonstrate its capabilities by calculating the HZ for two interesting analytical solutions of the three-body problem.« less
-
A clustering-based fuzzy wavelet neural network model for short-term load forecasting.
Kodogiannis, Vassilis S; Amina, Mahdi; Petrounias, Ilias
2013-10-01
Load forecasting is a critical element of power system operation, involving prediction of the future level of demand to serve as the basis for supply and demand planning. This paper presents the development of a novel clustering-based fuzzy wavelet neural network (CB-FWNN) model and validates its prediction on the short-term electric load forecasting of the Power System of the Greek Island of Crete. The proposed model is obtained from the traditional Takagi-Sugeno-Kang fuzzy system by replacing the THEN part of fuzzy rules with a "multiplication" wavelet neural network (MWNN). Multidimensional Gaussian type of activation functions have been used in the IF part of the fuzzyrules. A Fuzzy Subtractive Clustering scheme is employed as a pre-processing technique to find out the initial set and adequate number of clusters and ultimately the number of multiplication nodes in MWNN, while Gaussian Mixture Models with the Expectation Maximization algorithm are utilized for the definition of the multidimensional Gaussians. The results corresponding to the minimum and maximum power load indicate that the proposed load forecasting model provides significantly accurate forecasts, compared to conventional neural networks models.
-
Foundations of the Bandera Abstraction Tools
NASA Technical Reports Server (NTRS)
Hatcliff, John; Dwyer, Matthew B.; Pasareanu, Corina S.; Robby
2003-01-01
Current research is demonstrating that model-checking and other forms of automated finite-state verification can be effective for checking properties of software systems. Due to the exponential costs associated with model-checking, multiple forms of abstraction are often necessary to obtain system models that are tractable for automated checking. The Bandera Tool Set provides multiple forms of automated support for compiling concurrent Java software systems to models that can be supplied to several different model-checking tools. In this paper, we describe the foundations of Bandera's data abstraction mechanism which is used to reduce the cardinality (and the program's state-space) of data domains in software to be model-checked. From a technical standpoint, the form of data abstraction used in Bandera is simple, and it is based on classical presentations of abstract interpretation. We describe the mechanisms that Bandera provides for declaring abstractions, for attaching abstractions to programs, and for generating abstracted programs and properties. The contributions of this work are the design and implementation of various forms of tool support required for effective application of data abstraction to software components written in a programming language like Java which has a rich set of linguistic features.
-
Integration of Multiple Data Sources to Simulate the Dynamics of Land Systems
Deng, Xiangzheng; Su, Hongbo; Zhan, Jinyan
2008-01-01
In this paper we present and develop a new model, which we have called Dynamics of Land Systems (DLS). The DLS model is capable of integrating multiple data sources to simulate the dynamics of a land system. Three main modules are incorporated in DLS: a spatial regression module, to explore the relationship between land uses and influencing factors, a scenario analysis module of the land uses of a region during the simulation period and a spatial disaggregation module, to allocate land use changes from a regional level to disaggregated grid cells. A case study on Taips County in North China is incorporated in this paper to test the functionality of DLS. The simulation results under the baseline, economic priority and environmental scenarios help to understand the land system dynamics and project near future land-use trajectories of a region, in order to focus management decisions on land uses and land use planning. PMID:27879726
-
Towards an Iterated Game Model with Multiple Adversaries in Smart-World Systems.
He, Xiaofei; Yang, Xinyu; Yu, Wei; Lin, Jie; Yang, Qingyu
2018-02-24
Diverse and varied cyber-attacks challenge the operation of the smart-world system that is supported by Internet-of-Things (IoT) (smart cities, smart grid, smart transportation, etc.) and must be carefully and thoughtfully addressed before widespread adoption of the smart-world system can be fully realized. Although a number of research efforts have been devoted to defending against these threats, a majority of existing schemes focus on the development of a specific defensive strategy to deal with specific, often singular threats. In this paper, we address the issue of coalitional attacks, which can be launched by multiple adversaries cooperatively against the smart-world system such as smart cities. Particularly, we propose a game-theory based model to capture the interaction among multiple adversaries, and quantify the capacity of the defender based on the extended Iterated Public Goods Game (IPGG) model. In the formalized game model, in each round of the attack, a participant can either cooperate by participating in the coalitional attack, or defect by standing aside. In our work, we consider the generic defensive strategy that has a probability to detect the coalitional attack. When the coalitional attack is detected, all participating adversaries are penalized. The expected payoff of each participant is derived through the equalizer strategy that provides participants with competitive benefits. The multiple adversaries with the collusive strategy are also considered. Via a combination of theoretical analysis and experimentation, our results show that no matter which strategies the adversaries choose (random strategy, win-stay-lose-shift strategy, or even the adaptive equalizer strategy), our formalized game model is capable of enabling the defender to greatly reduce the maximum value of the expected average payoff to the adversaries via provisioning sufficient defensive resources, which is reflected by setting a proper penalty factor against the adversaries. In addition, we extend our game model and analyze the extortion strategy, which can enable one participant to obtain more payoff by extorting his/her opponents. The evaluation results show that the defender can combat this strategy by encouraging competition among the adversaries, and significantly suppress the total payoff of the adversaries via setting the proper penalty factor.
-
Towards an Iterated Game Model with Multiple Adversaries in Smart-World Systems †
Yang, Xinyu; Yu, Wei; Lin, Jie; Yang, Qingyu
2018-01-01
Diverse and varied cyber-attacks challenge the operation of the smart-world system that is supported by Internet-of-Things (IoT) (smart cities, smart grid, smart transportation, etc.) and must be carefully and thoughtfully addressed before widespread adoption of the smart-world system can be fully realized. Although a number of research efforts have been devoted to defending against these threats, a majority of existing schemes focus on the development of a specific defensive strategy to deal with specific, often singular threats. In this paper, we address the issue of coalitional attacks, which can be launched by multiple adversaries cooperatively against the smart-world system such as smart cities. Particularly, we propose a game-theory based model to capture the interaction among multiple adversaries, and quantify the capacity of the defender based on the extended Iterated Public Goods Game (IPGG) model. In the formalized game model, in each round of the attack, a participant can either cooperate by participating in the coalitional attack, or defect by standing aside. In our work, we consider the generic defensive strategy that has a probability to detect the coalitional attack. When the coalitional attack is detected, all participating adversaries are penalized. The expected payoff of each participant is derived through the equalizer strategy that provides participants with competitive benefits. The multiple adversaries with the collusive strategy are also considered. Via a combination of theoretical analysis and experimentation, our results show that no matter which strategies the adversaries choose (random strategy, win-stay-lose-shift strategy, or even the adaptive equalizer strategy), our formalized game model is capable of enabling the defender to greatly reduce the maximum value of the expected average payoff to the adversaries via provisioning sufficient defensive resources, which is reflected by setting a proper penalty factor against the adversaries. In addition, we extend our game model and analyze the extortion strategy, which can enable one participant to obtain more payoff by extorting his/her opponents. The evaluation results show that the defender can combat this strategy by encouraging competition among the adversaries, and significantly suppress the total payoff of the adversaries via setting the proper penalty factor. PMID:29495291
-
NASA Astrophysics Data System (ADS)
Osorio-Murillo, C. A.; Over, M. W.; Frystacky, H.; Ames, D. P.; Rubin, Y.
2013-12-01
A new software application called MAD# has been coupled with the HTCondor high throughput computing system to aid scientists and educators with the characterization of spatial random fields and enable understanding the spatial distribution of parameters used in hydrogeologic and related modeling. MAD# is an open source desktop software application used to characterize spatial random fields using direct and indirect information through Bayesian inverse modeling technique called the Method of Anchored Distributions (MAD). MAD relates indirect information with a target spatial random field via a forward simulation model. MAD# executes inverse process running the forward model multiple times to transfer information from indirect information to the target variable. MAD# uses two parallelization profiles according to computational resources available: one computer with multiple cores and multiple computers - multiple cores through HTCondor. HTCondor is a system that manages a cluster of desktop computers for submits serial or parallel jobs using scheduling policies, resources monitoring, job queuing mechanism. This poster will show how MAD# reduces the time execution of the characterization of random fields using these two parallel approaches in different case studies. A test of the approach was conducted using 1D problem with 400 cells to characterize saturated conductivity, residual water content, and shape parameters of the Mualem-van Genuchten model in four materials via the HYDRUS model. The number of simulations evaluated in the inversion was 10 million. Using the one computer approach (eight cores) were evaluated 100,000 simulations in 12 hours (10 million - 1200 hours approximately). In the evaluation on HTCondor, 32 desktop computers (132 cores) were used, with a processing time of 60 hours non-continuous in five days. HTCondor reduced the processing time for uncertainty characterization by a factor of 20 (1200 hours reduced to 60 hours.)
-
ERIC Educational Resources Information Center
Tynan, Joshua J.; Somers, Cheryl L.; Gleason, Jamie H.; Markman, Barry S.; Yoon, Jina
2015-01-01
With Bronfenbrenner's (1977) ecological theory and other multifactor models (e.g. Pianta, 1999; Prinstein, Boergers, & Spirito, 2001) underlying this study design, the purpose was to examine, simultaneously, key variables in multiple life contexts (microsystem, mesosystem, exosystem levels) for their individual and combined roles in predicting…
-
NASA Astrophysics Data System (ADS)
Amin Bacha, Bakht; Ahmad, Iftikhar; Ullah, Arif; Ali, Hazrat
2013-10-01
We investigate the behavior of light propagation in an N-type four-level gain assisted model (Agarwal and Dasgupta 2004 Phys. Rev. A 70 023802) under poly-chromatic pump fields. The system exhibits interesting results of multiple controllable pairs of the gain doublet profile with changes in the intensity of the control field. We observe multiple anomalous dispersive regions for superluminal propagation in the medium. A negative group velocity of -37.50 m s-1 with a negative time delay of -8 ms is observed between each gain doublet in anomalous dispersive regions. This generalized model and its predictions can be tested with existing experimental setups.
-
Environmental decision-making and the influences of various stressors, such as landscape and climate changes on water quantity and quality, requires the application of environmental modeling. Spatially explicit environmental and watershed-scale models using GIS as a base framewor...
-
A Logical Account of Diagnosis with Multiple Theories
NASA Technical Reports Server (NTRS)
Pandurang, P.; Lum, Henry Jr. (Technical Monitor)
1994-01-01
Model-based diagnosis is a powerful, first-principles approach to diagnosis. The primary drawback with model-based diagnosis is that it is based on a system model, and this model might be inappropriate. The inappropriateness of models usually stems from the fundamental tradeoff between completeness and efficiency. Recently, Struss has developed an elegant proposal for diagnosis with multiple models. Struss characterizes models as relations and develops a precise notion of abstraction. He defines relations between models and analyzes the effect of a model switch on the space of possible diagnoses. In this paper we extend Struss's proposal in three ways. First, our account of diagnosis with multiple models is based on representing models as more expressive first-order theories, rather than as relations. A key technical contribution is the use of a general notion of abstraction based on interpretations between theories. Second, Struss conflates component modes with models, requiring him to define models relations such as choices which result in non-relational models. We avoid this problem by differentiating component modes from models. Third, we present a more general account of simplifications that correctly handles situations where the simplification contradicts the base theory.
-
Modeling and Control of the Redundant Parallel Adjustment Mechanism on a Deployable Antenna Panel
Tian, Lili; Bao, Hong; Wang, Meng; Duan, Xuechao
2016-01-01
With the aim of developing multiple input and multiple output (MIMO) coupling systems with a redundant parallel adjustment mechanism on the deployable antenna panel, a structural control integrated design methodology is proposed in this paper. Firstly, the modal information from the finite element model of the structure of the antenna panel is extracted, and then the mathematical model is established with the Hamilton principle; Secondly, the discrete Linear Quadratic Regulator (LQR) controller is added to the model in order to control the actuators and adjust the shape of the panel. Finally, the engineering practicality of the modeling and control method based on finite element analysis simulation is verified. PMID:27706076
-
Keough, Dwayne
2011-01-01
Research on the control of visually guided limb movements indicates that the brain learns and continuously updates an internal model that maps the relationship between motor commands and sensory feedback. A growing body of work suggests that an internal model that relates motor commands to sensory feedback also supports vocal control. There is evidence from arm-reaching studies that shows that when provided with a contextual cue, the motor system can acquire multiple internal models, which allows an animal to adapt to different perturbations in diverse contexts. In this study we show that trained singers can rapidly acquire multiple internal models regarding voice fundamental frequency (F0). These models accommodate different perturbations to ongoing auditory feedback. Participants heard three musical notes and reproduced each one in succession. The musical targets could serve as a contextual cue to indicate which direction (up or down) feedback would be altered on each trial; however, participants were not explicitly instructed to use this strategy. When participants were gradually exposed to altered feedback adaptation was observed immediately following vocal onset. Aftereffects were target specific and did not influence vocal productions on subsequent trials. When target notes were no longer a contextual cue, adaptation occurred during altered feedback trials and evidence for trial-by-trial adaptation was found. These findings indicate that the brain is exceptionally sensitive to the deviations between auditory feedback and the predicted consequence of a motor command during vocalization. Moreover, these results indicate that, with contextual cues, the vocal control system may maintain multiple internal models that are capable of independent modification during different tasks or environments. PMID:21346208
-
Aqil, Muhammad; Kita, Ichiro; Yano, Akira; Nishiyama, Soichi
2007-10-01
Traditionally, the multiple linear regression technique has been one of the most widely used models in simulating hydrological time series. However, when the nonlinear phenomenon is significant, the multiple linear will fail to develop an appropriate predictive model. Recently, neuro-fuzzy systems have gained much popularity for calibrating the nonlinear relationships. This study evaluated the potential of a neuro-fuzzy system as an alternative to the traditional statistical regression technique for the purpose of predicting flow from a local source in a river basin. The effectiveness of the proposed identification technique was demonstrated through a simulation study of the river flow time series of the Citarum River in Indonesia. Furthermore, in order to provide the uncertainty associated with the estimation of river flow, a Monte Carlo simulation was performed. As a comparison, a multiple linear regression analysis that was being used by the Citarum River Authority was also examined using various statistical indices. The simulation results using 95% confidence intervals indicated that the neuro-fuzzy model consistently underestimated the magnitude of high flow while the low and medium flow magnitudes were estimated closer to the observed data. The comparison of the prediction accuracy of the neuro-fuzzy and linear regression methods indicated that the neuro-fuzzy approach was more accurate in predicting river flow dynamics. The neuro-fuzzy model was able to improve the root mean square error (RMSE) and mean absolute percentage error (MAPE) values of the multiple linear regression forecasts by about 13.52% and 10.73%, respectively. Considering its simplicity and efficiency, the neuro-fuzzy model is recommended as an alternative tool for modeling of flow dynamics in the study area.
-
Simulations of the propagation of multiple-FM smoothing by spectral dispersion on OMEGA EP
Kelly, J. H.; Shvydky, A.; Marozas, J. A.; ...
2013-02-18
A one-dimensional (1-D) smoothing by spectral dispersion (SSD) system for smoothing focal-spot nonuniformities using multiple modulation frequencies has been commissioned on one long-pulse beamline of OMEGA EP, the first use of such a system in a high-energy laser. Frequency modulation (FM) to amplitude modulation (AM) conversion in the infrared (IR) output, frequency conversion, and final optics affected the accumulation of B-integral in that beamline. Modeling of this FM-to-AM conversion using the code Miró. was used as input to set the beamline performance limits for picket (short) pulses with multi-FM SSD applied. This article first describes that modeling. The 1-D SSDmore » analytical model of Chuang is first extended to the case of multiple modulators and then used to benchmark Miró simulations. Comparison is also made to an alternative analytic model developed by Hocquet et al. With the confidence engendered by this benchmarking, Miró results for multi-FM SSD applied on OMEGA EP are then presented. The relevant output section(s) of the OMEGA EP Laser System are described. The additional B-integral in OMEGA EP IR components upstream of the frequency converters due to AM is modeled. The importance of locating the image of the SSD dispersion grating at the frequency converters is demonstrated. In conclusion, since frequency conversion is not performed in OMEGA EP’s target chamber, the additional AM due to propagation to the target chamber’s vacuum window is modeled.« less
-
Coupled catastrophes: sudden shifts cascade and hop among interdependent systems
Barnett, George; D'Souza, Raissa M.
2015-01-01
An important challenge in several disciplines is to understand how sudden changes can propagate among coupled systems. Examples include the synchronization of business cycles, population collapse in patchy ecosystems, markets shifting to a new technology platform, collapses in prices and in confidence in financial markets, and protests erupting in multiple countries. A number of mathematical models of these phenomena have multiple equilibria separated by saddle-node bifurcations. We study this behaviour in its normal form as fast–slow ordinary differential equations. In our model, a system consists of multiple subsystems, such as countries in the global economy or patches of an ecosystem. Each subsystem is described by a scalar quantity, such as economic output or population, that undergoes sudden changes via saddle-node bifurcations. The subsystems are coupled via their scalar quantity (e.g. trade couples economic output; diffusion couples populations); that coupling moves the locations of their bifurcations. The model demonstrates two ways in which sudden changes can propagate: they can cascade (one causing the next), or they can hop over subsystems. The latter is absent from classic models of cascades. For an application, we study the Arab Spring protests. After connecting the model to sociological theories that have bistability, we use socioeconomic data to estimate relative proximities to tipping points and Facebook data to estimate couplings among countries. We find that although protests tend to spread locally, they also seem to ‘hop' over countries, like in the stylized model; this result highlights a new class of temporal motifs in longitudinal network datasets. PMID:26559684
-
Aerial cooperative transporting and assembling control using multiple quadrotor-manipulator systems
NASA Astrophysics Data System (ADS)
Qi, Yuhua; Wang, Jianan; Shan, Jiayuan
2018-02-01
In this paper, a fully distributed control scheme for aerial cooperative transporting and assembling is proposed using multiple quadrotor-manipulator systems with each quadrotor equipped with a robotic manipulator. First, the kinematic and dynamic models of a quadrotor with multi-Degree of Freedom (DOF) robotic manipulator are established together using Euler-Lagrange equations. Based on the aggregated dynamic model, the control scheme consisting of position controller, attitude controller and manipulator controller is presented. Regarding cooperative transporting and assembling, multiple quadrotor-manipulator systems should be able to form a desired formation without collision among quadrotors from any initial position. The desired formation is achieved by the distributed position controller and attitude controller, while the collision avoidance is guaranteed by an artificial potential function method. Then, the transporting and assembling tasks request the manipulators to reach the desired angles cooperatively, which is achieved by the distributed manipulator controller. The overall stability of the closed-loop system is proven by a Lyapunov method and Matrosov's theorem. In the end, the proposed control scheme is simplified for the real application and then validated by two formation flying missions of four quadrotors with 2-DOF manipulators.
-
Stochastic Erosion of Fractal Structure in Nonlinear Dynamical Systems
NASA Astrophysics Data System (ADS)
Agarwal, S.; Wettlaufer, J. S.
2014-12-01
We analyze the effects of stochastic noise on the Lorenz-63 model in the chaotic regime to demonstrate a set of general issues arising in the interpretation of data from nonlinear dynamical systems typical in geophysics. The model is forced using both additive and multiplicative, white and colored noise and it is shown that, through a suitable choice of the noise intensity, both additive and multiplicative noise can produce similar dynamics. We use a recently developed measure, histogram distance, to show the similarity between the dynamics produced by additive and multiplicative forcing. This phenomenon, in a nonlinear fractal structure with chaotic dynamics can be explained by understanding how noise affects the Unstable Periodic Orbits (UPOs) of the system. For delta-correlated noise, the UPOs erode the fractal structure. In the presence of memory in the noise forcing, the time scale of the noise starts to interact with the period of some UPO and, depending on the noise intensity, stochastic resonance may be observed. This also explains the mixing in dissipative dynamical systems in presence of white noise; as the fractal structure is smoothed, the decay of correlations is enhanced, and hence the rate of mixing increases with noise intensity.
-
NASA Astrophysics Data System (ADS)
Rai, Buddhi; McGurn, Arthur R.
2015-02-01
Photonic crystal and split ring resonator (SRR) metamaterial waveguides with Kerr nonlinear dielectric impurities are studied. The transmission coefficients for two guided modes of different frequencies scattering from the Kerr impurities are computed. The systems are shown to exhibit multiple transmission coefficient solutions arising from the Kerr nonlinearity. Multiple transmission coefficients occur when different input intensities into a waveguide result in the same transmitted output intensities past its nonlinear impurities. (In the case of a single incident guided mode the multiplicity of transmission coefficients is known as optical bistability.) The analytical conditions under which the transmission coefficients are single and multiple valued are determined, and specific examples of both single and multiple valued transmission coefficient scattering are presented. Both photonic crystal and split ring resonator systems are studied as the Kerr nonlinearity enters the photonic crystal and SRR systems in different ways. This allows for an interesting comparison of the differences in behaviors of these two types of system which are described by distinctly different mathematical structures. Both the photonic crystal and SRR models used in the calculations are based on a difference equation approach to the system dynamics. The difference equation approach has been extensively employed in previous papers to model the basic properties of these systems. The paper is a continuation of work on the optical bistability of single guided modes interacting with Kerr impurities in photonic crystals originally considered by McGurn [Chaos 13, 754 (2003), 10.1063/1.1568691] and work on the resonant scattering from Kerr impurities in photonic crystal waveguides considered by McGurn [J. Phys.: Condens. Matter 16, S5243 (2004), 10.1088/0953-8984/16/44/021]. It generalizes this work making the extension to the more complex interaction of two guided modes at different frequencies. It extends the two guided mode treatment by McGurn [Organ. Electron. 8, 227 (2007), 10.1016/j.orgel.2006.06.008] which was limited to a special case of one of the photonic crystal systems considered here.
-
Oguz, Ozgur S; Zhou, Zhehua; Glasauer, Stefan; Wollherr, Dirk
2018-04-03
Human motor control is highly efficient in generating accurate and appropriate motor behavior for a multitude of tasks. This paper examines how kinematic and dynamic properties of the musculoskeletal system are controlled to achieve such efficiency. Even though recent studies have shown that the human motor control relies on multiple models, how the central nervous system (CNS) controls this combination is not fully addressed. In this study, we utilize an Inverse Optimal Control (IOC) framework in order to find the combination of those internal models and how this combination changes for different reaching tasks. We conducted an experiment where participants executed a comprehensive set of free-space reaching motions. The results show that there is a trade-off between kinematics and dynamics based controllers depending on the reaching task. In addition, this trade-off depends on the initial and final arm configurations, which in turn affect the musculoskeletal load to be controlled. Given this insight, we further provide a discomfort metric to demonstrate its influence on the contribution of different inverse internal models. This formulation together with our analysis not only support the multiple internal models (MIMs) hypothesis but also suggest a hierarchical framework for the control of human reaching motions by the CNS.
-
Modelling consequences of change in biodiversity and ...
This chapter offers an assessment of the rapidly changing landscape of methods assessing and forecasting the benefits that people receive from nature and how these benefits are shaped by institutions and various anthropogenic assets. There has been an explosion of activity in understanding and modeling the benefits that people receive from nature, and this explosion has provided a diversity of approaches that are both complementary and contradictory. However, there remain major gaps in what current models can do. They are not well suited to estimate most types of benefits at national, regional, or global scales. they are focused on decision analysis, but have not focused on implementation, learning, or dialogue. This hap in particular means that current models are not well suited to bridging among multiple knowledge systems, however, there are initial efforts made towards this goal. Furthermore, while participatory social-ecological scenarios are able to bridge multiple knowledge systems in their assessment and analysis of multiple ecosystem series, the social-ecological scenarios community is fragmented and not well connected. Consequently, IPBES has an excellent knowledge base to build upon, but a real investment in building a more integrated modeling and scenarios community of practice is needed to produce a more complete and useful toolbox of approaches to meet the needs of IPBES assessment and other assessment of nature benefits. This Chapter describes
-
Mathematical modeling of solid cancer growth with angiogenesis
2012-01-01
Background Cancer arises when within a single cell multiple malfunctions of control systems occur, which are, broadly, the system that promote cell growth and the system that protect against erratic growth. Additional systems within the cell must be corrupted so that a cancer cell, to form a mass of any real size, produces substances that promote the growth of new blood vessels. Multiple mutations are required before a normal cell can become a cancer cell by corruption of multiple growth-promoting systems. Methods We develop a simple mathematical model to describe the solid cancer growth dynamics inducing angiogenesis in the absence of cancer controlling mechanisms. Results The initial conditions supplied to the dynamical system consist of a perturbation in form of pulse: The origin of cancer cells from normal cells of an organ of human body. Thresholds of interacting parameters were obtained from the steady states analysis. The existence of two equilibrium points determine the strong dependency of dynamical trajectories on the initial conditions. The thresholds can be used to control cancer. Conclusions Cancer can be settled in an organ if the following combination matches: better fitness of cancer cells, decrease in the efficiency of the repairing systems, increase in the capacity of sprouting from existing vascularization, and higher capacity of mounting up new vascularization. However, we show that cancer is rarely induced in organs (or tissues) displaying an efficient (numerically and functionally) reparative or regenerative mechanism. PMID:22300422
-
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.
-
DOE Office of Scientific and Technical Information (OSTI.GOV)
Adam, J. C.; Stephens, J. C.; Chung, Serena
As managers of agricultural and natural resources are confronted with uncertainties in global change impacts, the complexities associated with the interconnected cycling of nitrogen, carbon, and water present daunting management challenges. Existing models provide detailed information on specific sub-systems (land, air, water, economics, etc). An increasing awareness of the unintended consequences of management decisions resulting from interconnectedness of these sub-systems, however, necessitates coupled regional earth system models (EaSMs). Decision makers’ needs and priorities can be integrated into the model design and development processes to enhance decision-making relevance and "usability" of EaSMs. BioEarth is a current research initiative with a focusmore » on the U.S. Pacific Northwest region that explores the coupling of multiple stand-alone EaSMs to generate usable information for resource decision-making. Direct engagement between model developers and non-academic stakeholders involved in resource and environmental management decisions throughout the model development process is a critical component of this effort. BioEarth utilizes a "bottom-up" approach, upscaling a catchment-scale model to basin and regional scales, as opposed to the "top-down" approach of downscaling global models utilized by most other EaSM efforts. This paper describes the BioEarth initiative and highlights opportunities and challenges associated with coupling multiple stand-alone models to generate usable information for agricultural and natural resource decision-making.« less
-
The stochastic control of the F-8C aircraft using the Multiple Model Adaptive Control (MMAC) method
NASA Technical Reports Server (NTRS)
Athans, M.; Dunn, K. P.; Greene, E. S.; Lee, W. H.; Sandel, N. R., Jr.
1975-01-01
The purpose of this paper is to summarize results obtained for the adaptive control of the F-8C aircraft using the so-called Multiple Model Adaptive Control method. The discussion includes the selection of the performance criteria for both the lateral and the longitudinal dynamics, the design of the Kalman filters for different flight conditions, the 'identification' aspects of the design using hypothesis testing ideas, and the performance of the closed loop adaptive system.
-
Simulink/PARS Integration Support
DOE Office of Scientific and Technical Information (OSTI.GOV)
Vacaliuc, B.; Nakhaee, N.
2013-12-18
The state of the art for signal processor hardware has far out-paced the development tools for placing applications on that hardware. In addition, signal processors are available in a variety of architectures, each uniquely capable of handling specific types of signal processing efficiently. With these processors becoming smaller and demanding less power, it has become possible to group multiple processors, a heterogeneous set of processors, into single systems. Different portions of the desired problem set can be assigned to different processor types as appropriate. As software development tools do not keep pace with these processors, especially when multiple processors ofmore » different types are used, a method is needed to enable software code portability among multiple processors and multiple types of processors along with their respective software environments. Sundance DSP, Inc. has developed a software toolkit called “PARS”, whose objective is to provide a framework that uses suites of tools provided by different vendors, along with modeling tools and a real time operating system, to build an application that spans different processor types. The software language used to express the behavior of the system is a very high level modeling language, “Simulink”, a MathWorks product. ORNL has used this toolkit to effectively implement several deliverables. This CRADA describes this collaboration between ORNL and Sundance DSP, Inc.« less
-
Radac, Mircea-Bogdan; Precup, Radu-Emil; Petriu, Emil M
2015-11-01
This paper proposes a novel model-free trajectory tracking of multiple-input multiple-output (MIMO) systems by the combination of iterative learning control (ILC) and primitives. The optimal trajectory tracking solution is obtained in terms of previously learned solutions to simple tasks called primitives. The library of primitives that are stored in memory consists of pairs of reference input/controlled output signals. The reference input primitives are optimized in a model-free ILC framework without using knowledge of the controlled process. The guaranteed convergence of the learning scheme is built upon a model-free virtual reference feedback tuning design of the feedback decoupling controller. Each new complex trajectory to be tracked is decomposed into the output primitives regarded as basis functions. The optimal reference input for the control system to track the desired trajectory is next recomposed from the reference input primitives. This is advantageous because the optimal reference input is computed straightforward without the need to learn from repeated executions of the tracking task. In addition, the optimization problem specific to trajectory tracking of square MIMO systems is decomposed in a set of optimization problems assigned to each separate single-input single-output control channel that ensures a convenient model-free decoupling. The new model-free primitive-based ILC approach is capable of planning, reasoning, and learning. A case study dealing with the model-free control tuning for a nonlinear aerodynamic system is included to validate the new approach. The experimental results are given.
-
Exploring the use of multiple analogical models when teaching and learning chemical equilibrium
NASA Astrophysics Data System (ADS)
Harrison, Allan G.; de Jong, Onno
2005-12-01
This study describes the multiple analogical models used to introduce and teach Grade 12 chemical equilibrium. We examine the teacher's reasons for using models, explain each model's development during the lessons, and analyze the understandings students derived from the models. A case study approach was used and the data were drawn from the observation of three consecutive Grade 12 lessons on chemical equilibrium, pre- and post-lesson interviews, and delayed student interviews. The key analogical models used in teaching were: the school dance; the sugar in a teacup; the pot of curry; and the busy highway. The lesson and interview data were subject to multiple, independent analyses and yielded the following outcomes: The teacher planned to use the students' prior knowledge wherever possible and he responded to student questions with stories and extended and enriched analogies. He planned to discuss where each analogy broke down but did not. The students enjoyed the teaching but built variable mental models of equilibrium and some of their analogical mappings were unreliable. A female student disliked masculine analogies, other students tended to see elements of the multiple models in isolation, and some did not recognize all the analogical mappings embedded in the teaching plan. Most students learned that equilibrium reactions are dynamic, occur in closed systems, and the forward and reverse reactions are balanced. We recommend the use of multiple analogies like these and insist that teachers always show where the analogy breaks down and carefully negotiate the conceptual outcomes.
-
Morgenstern, Hai; Rafaely, Boaz; Noisternig, Markus
2017-03-01
Spherical microphone arrays (SMAs) and spherical loudspeaker arrays (SLAs) facilitate the study of room acoustics due to the three-dimensional analysis they provide. More recently, systems that combine both arrays, referred to as multiple-input multiple-output (MIMO) systems, have been proposed due to the added spatial diversity they facilitate. The literature provides frameworks for designing SMAs and SLAs separately, including error analysis from which the operating frequency range (OFR) of an array is defined. However, such a framework does not exist for the joint design of a SMA and a SLA that comprise a MIMO system. This paper develops a design framework for MIMO systems based on a model that addresses errors and highlights the importance of a matched design. Expanding on a free-field assumption, errors are incorporated separately for each array and error bounds are defined, facilitating error analysis for the system. The dependency of the error bounds on the SLA and SMA parameters is studied and it is recommended that parameters should be chosen to assure matched OFRs of the arrays in MIMO system design. A design example is provided, demonstrating the superiority of a matched system over an unmatched system in the synthesis of directional room impulse responses.
-
Real object-based 360-degree integral-floating display using multiple depth camera
NASA Astrophysics Data System (ADS)
Erdenebat, Munkh-Uchral; Dashdavaa, Erkhembaatar; Kwon, Ki-Chul; Wu, Hui-Ying; Yoo, Kwan-Hee; Kim, Young-Seok; Kim, Nam
2015-03-01
A novel 360-degree integral-floating display based on the real object is proposed. The general procedure of the display system is similar with conventional 360-degree integral-floating displays. Unlike previously presented 360-degree displays, the proposed system displays the 3D image generated from the real object in 360-degree viewing zone. In order to display real object in 360-degree viewing zone, multiple depth camera have been utilized to acquire the depth information around the object. Then, the 3D point cloud representations of the real object are reconstructed according to the acquired depth information. By using a special point cloud registration method, the multiple virtual 3D point cloud representations captured by each depth camera are combined as single synthetic 3D point cloud model, and the elemental image arrays are generated for the newly synthesized 3D point cloud model from the given anamorphic optic system's angular step. The theory has been verified experimentally, and it shows that the proposed 360-degree integral-floating display can be an excellent way to display real object in the 360-degree viewing zone.
-
Using constraints and their value for optimization of large ODE systems
Domijan, Mirela; Rand, David A.
2015-01-01
We provide analytical tools to facilitate a rigorous assessment of the quality and value of the fit of a complex model to data. We use this to provide approaches to model fitting, parameter estimation, the design of optimization functions and experimental optimization. This is in the context where multiple constraints are used to select or optimize a large model defined by differential equations. We illustrate the approach using models of circadian clocks and the NF-κB signalling system. PMID:25673300
-
Wideband Channel Modeling in Real Atmospheric Environments with Experimental Evaluation
2013-04-01
5] D. F. Gingras and P. Gerstoft. 1997. “The Effect of Propagation on Wideband DS - CDMA Systems in the Suburban Environment,” The First IEEE...are commonly used in spread spectrum communication systems such as Code Division Multiple Access ( CDMA ) systems. Narrowband interference mitigation
-
A speed guidance strategy for multiple signalized intersections based on car-following model
NASA Astrophysics Data System (ADS)
Tang, Tie-Qiao; Yi, Zhi-Yan; Zhang, Jian; Wang, Tao; Leng, Jun-Qiang
2018-04-01
Signalized intersection has great roles in urban traffic system. The signal infrastructure and the driving behavior near the intersection are paramount factors that have significant impacts on traffic flow and energy consumption. In this paper, a speed guidance strategy is introduced into a car-following model to study the driving behavior and the fuel consumption in a single-lane road with multiple signalized intersections. The numerical results indicate that the proposed model can reduce the fuel consumption and the average stop times. The findings provide insightful guidance for the eco-driving strategies near the signalized intersections.
-
System level comparison of FDMA vs. CDMA (under conference guideline constraint)
NASA Technical Reports Server (NTRS)
Renshaw, Ken
1989-01-01
The margin that is required to mitigate the near-far problem in a Code Division Multiple Access (CDMA) mobile satellite system is determined by the radio-propagation model selected, the distribution of the users in clear and shadowed environments, and implementation techniques. The use of revenue potential as a means of evaluating the relative merits of CDMA and Frequency Division Multiple Access (FDMA) systems is a convenient way to rationalize the performance of systems using high-gain and low-gain antennas. The revenue potential of CDMA is much greater than the revenue potential for FDMA for a particular satellite design considered.
-
Step wise, multiple objective calibration of a hydrologic model for a snowmelt dominated basin
Hay, L.E.; Leavesley, G.H.; Clark, M.P.; Markstrom, S.L.; Viger, R.J.; Umemoto, M.
2006-01-01
The ability to apply a hydrologic model to large numbers of basins for forecasting purposes requires a quick and effective calibration strategy. This paper presents a step wise, multiple objective, automated procedure for hydrologic model calibration. This procedure includes the sequential calibration of a model's simulation of solar radiation (SR), potential evapotranspiration (PET), water balance, and daily runoff. The procedure uses the Shuffled Complex Evolution global search algorithm to calibrate the U.S. Geological Survey's Precipitation Runoff Modeling System in the Yampa River basin of Colorado. This process assures that intermediate states of the model (SR and PET on a monthly mean basis), as well as the water balance and components of the daily hydrograph are simulated, consistently with measured values.
-
ERIC Educational Resources Information Center
Higgins, Derrick; Futagi, Yoko; Deane, Paul
2005-01-01
This paper reports on the process of modifying the ModelCreator item generation system to produce output in multiple languages. In particular, Japanese and Spanish are now supported in addition to English. The addition of multilingual functionality was considerably facilitated by the general formulation of our natural language generation system,…
-
USDA-ARS?s Scientific Manuscript database
The model pathogen Pseudomonas syringae pv. tomato DC3000 suppresses the two-tiered innate immune system of plants by injecting a complex repertoire of effector proteins into host cells via the type III secretion system. The model effector AvrPtoB has multiple domains and plant protein interactors i...
-
Wu, Naiqi; Zhou, MengChu
2005-12-01
An automated manufacturing system (AMS) contains a number of versatile machines (or workstations), buffers, an automated material handling system (MHS), and is computer-controlled. An effective and flexible alternative for implementing MHS is to use automated guided vehicle (AGV) system. The deadlock issue in AMS is very important in its operation and has extensively been studied. The deadlock problems were separately treated for parts in production and transportation and many techniques were developed for each problem. However, such treatment does not take the advantage of the flexibility offered by multiple AGVs. In general, it is intractable to obtain maximally permissive control policy for either problem. Instead, this paper investigates these two problems in an integrated way. First we model an AGV system and part processing processes by resource-oriented Petri nets, respectively. Then the two models are integrated by using macro transitions. Based on the combined model, a novel control policy for deadlock avoidance is proposed. It is shown to be maximally permissive with computational complexity of O (n2) where n is the number of machines in AMS if the complexity for controlling the part transportation by AGVs is not considered. Thus, the complexity of deadlock avoidance for the whole system is bounded by the complexity in controlling the AGV system. An illustrative example shows its application and power.
-
Unified Simulation and Analysis Framework for Deep Space Navigation Design
NASA Technical Reports Server (NTRS)
Anzalone, Evan; Chuang, Jason; Olsen, Carrie
2013-01-01
As the technology that enables advanced deep space autonomous navigation continues to develop and the requirements for such capability continues to grow, there is a clear need for a modular expandable simulation framework. This tool's purpose is to address multiple measurement and information sources in order to capture system capability. This is needed to analyze the capability of competing navigation systems as well as to develop system requirements, in order to determine its effect on the sizing of the integrated vehicle. The development for such a framework is built upon Model-Based Systems Engineering techniques to capture the architecture of the navigation system and possible state measurements and observations to feed into the simulation implementation structure. These models also allow a common environment for the capture of an increasingly complex operational architecture, involving multiple spacecraft, ground stations, and communication networks. In order to address these architectural developments, a framework of agent-based modules is implemented to capture the independent operations of individual spacecraft as well as the network interactions amongst spacecraft. This paper describes the development of this framework, and the modeling processes used to capture a deep space navigation system. Additionally, a sample implementation describing a concept of network-based navigation utilizing digitally transmitted data packets is described in detail. This developed package shows the capability of the modeling framework, including its modularity, analysis capabilities, and its unification back to the overall system requirements and definition.
-
Physiologically relevant organs on chips
Yum, Kyungsuk; Hong, Soon Gweon; Lee, Luke P.
2015-01-01
Recent advances in integrating microengineering and tissue engineering have generated promising microengineered physiological models for experimental medicine and pharmaceutical research. Here we review the recent development of microengineered physiological systems, or organs on chips, that reconstitute the physiologically critical features of specific human tissues and organs and their interactions. This technology uses microengineering approaches to construct organ-specific microenvironments, reconstituting tissue structures, tissue–tissue interactions and interfaces, and dynamic mechanical and biochemical stimuli found in specific organs, to direct cells to assemble into functional tissues. We first discuss microengineering approaches to reproduce the key elements of physiologically important, dynamic mechanical microenvironments, biochemical microenvironments, and microarchitectures of specific tissues and organs in microfluidic cell culture systems. This is followed by examples of microengineered individual organ models that incorporate the key elements of physiological microenvironments into single microfluidic cell culture systems to reproduce organ-level functions. Finally, microengineered multiple organ systems that simulate multiple organ interactions to better represent human physiology, including human responses to drugs, is covered in this review. This emerging organs-on-chips technology has the potential to become an alternative to 2D and 3D cell culture and animal models for experimental medicine, human disease modeling, drug development, and toxicology. PMID:24357624
-
NASA Astrophysics Data System (ADS)
Chan, C. H.; Brown, G.; Rikvold, P. A.
2017-05-01
A generalized approach to Wang-Landau simulations, macroscopically constrained Wang-Landau, is proposed to simulate the density of states of a system with multiple macroscopic order parameters. The method breaks a multidimensional random-walk process in phase space into many separate, one-dimensional random-walk processes in well-defined subspaces. Each of these random walks is constrained to a different set of values of the macroscopic order parameters. When the multivariable density of states is obtained for one set of values of fieldlike model parameters, the density of states for any other values of these parameters can be obtained by a simple transformation of the total system energy. All thermodynamic quantities of the system can then be rapidly calculated at any point in the phase diagram. We demonstrate how to use the multivariable density of states to draw the phase diagram, as well as order-parameter probability distributions at specific phase points, for a model spin-crossover material: an antiferromagnetic Ising model with ferromagnetic long-range interactions. The fieldlike parameters in this model are an effective magnetic field and the strength of the long-range interaction.
-
NASA Astrophysics Data System (ADS)
Maidana, Carlos Omar
As part of an accelerator based Cargo Inspection System, studies were made to develop a Cabinet Safe System by Optimization of the Beam Optics of Microwave Linear Accelerators of the IAC-Varian series working on the S-band and standing wave pi/2 mode. Measurements, modeling and simulations of the main subsystems were done and a Multiple Solenoidal System was designed. This Cabinet Safe System based on a Multiple Solenoidal System minimizes the radiation field generated by the low efficiency of the microwave accelerators by optimizing the RF waveguide system and by also trapping secondaries generated in the accelerator head. These secondaries are generated mainly due to instabilities in the exit window region and particles backscattered from the target. The electron gun was also studied and software for its right mechanical design and for its optimization was developed as well. Besides the standard design method, an optimization of the injection process is accomplished by slightly modifying the gun configuration and by placing a solenoid on the waist position while avoiding threading the cathode with the magnetic flux generated. The Multiple Solenoidal System and the electron gun optimization are the backbone of a Cabinet Safe System that could be applied not only to the 25 MeV IAC-Varian microwave accelerators but, by extension, to machines of different manufacturers as well. Thus, they constitute the main topic of this dissertation.
-
Investigation of the Multiple Method Adaptive Control (MMAC) method for flight control systems
NASA Technical Reports Server (NTRS)
Athans, M.; Baram, Y.; Castanon, D.; Dunn, K. P.; Green, C. S.; Lee, W. H.; Sandell, N. R., Jr.; Willsky, A. S.
1979-01-01
The stochastic adaptive control of the NASA F-8C digital-fly-by-wire aircraft using the multiple model adaptive control (MMAC) method is presented. The selection of the performance criteria for the lateral and the longitudinal dynamics, the design of the Kalman filters for different operating conditions, the identification algorithm associated with the MMAC method, the control system design, and simulation results obtained using the real time simulator of the F-8 aircraft at the NASA Langley Research Center are discussed.
-
Block Oriented Simulation System (BOSS)
NASA Technical Reports Server (NTRS)
Ratcliffe, Jaimie
1988-01-01
Computer simulation is assuming greater importance as a flexible and expedient approach to modeling system and subsystem behavior. Simulation has played a key role in the growth of complex, multiple access space communications such as those used by the space shuttle and the TRW-built Tracking and Data Relay Satellites (TDRS). A powerful new simulator for use in designing and modeling the communication system of NASA's planned Space Station is being developed. Progress to date on the Block (Diagram) Oriented Simulation System (BOSS) is described.
-
DOE Office of Scientific and Technical Information (OSTI.GOV)
McDeavitt, Sean; Shao, Lin; Tsvetkov, Pavel
2014-04-07
Advanced fast reactor systems being developed under the DOE's Advanced Fuel Cycle Initiative are designed to destroy TRU isotopes generated in existing and future nuclear energy systems. Over the past 40 years, multiple experiments and demonstrations have been completed using U-Zr, U-Pu-Zr, U-Mo and other metal alloys. As a result, multiple empirical and semi-empirical relationships have been established to develop empirical performance modeling codes. Many mechanistic questions about fission as mobility, bubble coalescience, and gas release have been answered through industrial experience, research, and empirical understanding. The advent of modern computational materials science, however, opens new doors of development suchmore » that physics-based multi-scale models may be developed to enable a new generation of predictive fuel performance codes that are not limited by empiricism.« less
-
NASA Astrophysics Data System (ADS)
Wood, E. F.; Yuan, X.; Sheffield, J.; Pan, M.; Roundy, J.
2013-12-01
One of the key recommendations of the WCRP Global Drought Information System (GDIS) workshop is to develop an experimental real-time global monitoring and prediction system. While great advances has been made in global drought monitoring based on satellite observations and model reanalysis data, global drought forecasting has been stranded in part due to the limited skill both in climate forecast models and global hydrologic predictions. Having been working on drought monitoring and forecasting over USA for more than a decade, the Princeton land surface hydrology group is now developing an experimental global drought early warning system that is based on multiple climate forecast models and a calibrated global hydrologic model. In this presentation, we will test its capability in seasonal forecasting of meteorological, agricultural and hydrologic droughts over global major river basins, using precipitation, soil moisture and streamflow forecasts respectively. Based on the joint probability distribution between observations using Princeton's global drought monitoring system and model hindcasts and real-time forecasts from North American Multi-Model Ensemble (NMME) project, we (i) bias correct the monthly precipitation and temperature forecasts from multiple climate forecast models, (ii) downscale them to a daily time scale, and (iii) use them to drive the calibrated VIC model to produce global drought forecasts at a 1-degree resolution. A parallel run using the ESP forecast method, which is based on resampling historical forcings, is also carried out for comparison. Analysis is being conducted over global major river basins, with multiple drought indices that have different time scales and characteristics. The meteorological drought forecast does not have uncertainty from hydrologic models and can be validated directly against observations - making the validation an 'apples-to-apples' comparison. Preliminary results for the evaluation of meteorological drought onset hindcasts indicate that climate models increase drought detectability over ESP by 31%-81%. However, less than 30% of the global drought onsets can be detected by climate models. The missed drought events are associated with weak ENSO signals and lower potential predictability. Due to the high false alarms from climate models, the reliability is more important than sharpness for a skillful probabilistic drought onset forecast. Validations and skill assessments for agricultural and hydrologic drought forecasts are carried out using soil moisture and streamflow output from the VIC land surface model (LSM) forced by a global forcing data set. Given our previous drought forecasting experiences over USA and Africa, validating the hydrologic drought forecasting is a significant challenge for a global drought early warning system.
-
NASA Technical Reports Server (NTRS)
Bekey, G. A.
1971-01-01
Studies are summarized on the application of advanced analytical and computational methods to the development of mathematical models of human controllers in multiaxis manual control systems. Specific accomplishments include the following: (1) The development of analytical and computer methods for the measurement of random parameters in linear models of human operators. (2) Discrete models of human operator behavior in a multiple display situation were developed. (3) Sensitivity techniques were developed which make possible the identification of unknown sampling intervals in linear systems. (4) The adaptive behavior of human operators following particular classes of vehicle failures was studied and a model structure proposed.
-
Díaz, J I; Hidalgo, A; Tello, L
2014-10-08
We study a climatologically important interaction of two of the main components of the geophysical system by adding an energy balance model for the averaged atmospheric temperature as dynamic boundary condition to a diagnostic ocean model having an additional spatial dimension. In this work, we give deeper insight than previous papers in the literature, mainly with respect to the 1990 pioneering model by Watts and Morantine. We are taking into consideration the latent heat for the two phase ocean as well as a possible delayed term. Non-uniqueness for the initial boundary value problem, uniqueness under a non-degeneracy condition and the existence of multiple stationary solutions are proved here. These multiplicity results suggest that an S-shaped bifurcation diagram should be expected to occur in this class of models generalizing previous energy balance models. The numerical method applied to the model is based on a finite volume scheme with nonlinear weighted essentially non-oscillatory reconstruction and Runge-Kutta total variation diminishing for time integration.
-
Díaz, J. I.; Hidalgo, A.; Tello, L.
2014-01-01
We study a climatologically important interaction of two of the main components of the geophysical system by adding an energy balance model for the averaged atmospheric temperature as dynamic boundary condition to a diagnostic ocean model having an additional spatial dimension. In this work, we give deeper insight than previous papers in the literature, mainly with respect to the 1990 pioneering model by Watts and Morantine. We are taking into consideration the latent heat for the two phase ocean as well as a possible delayed term. Non-uniqueness for the initial boundary value problem, uniqueness under a non-degeneracy condition and the existence of multiple stationary solutions are proved here. These multiplicity results suggest that an S-shaped bifurcation diagram should be expected to occur in this class of models generalizing previous energy balance models. The numerical method applied to the model is based on a finite volume scheme with nonlinear weighted essentially non-oscillatory reconstruction and Runge–Kutta total variation diminishing for time integration. PMID:25294969
-
The Capacity Gain of Orbital Angular Momentum Based Multiple-Input-Multiple-Output System
Zhang, Zhuofan; Zheng, Shilie; Chen, Yiling; Jin, Xiaofeng; Chi, Hao; Zhang, Xianmin
2016-01-01
Wireless communication using electromagnetic wave carrying orbital angular momentum (OAM) has attracted increasing interest in recent years, and its potential to increase channel capacity has been explored widely. In this paper, we compare the technique of using uniform linear array consist of circular traveling-wave OAM antennas for multiplexing with the conventional multiple-in-multiple-out (MIMO) communication method, and numerical results show that the OAM based MIMO system can increase channel capacity while communication distance is long enough. An equivalent model is proposed to illustrate that the OAM multiplexing system is equivalent to a conventional MIMO system with a larger element spacing, which means OAM waves could decrease the spatial correlation of MIMO channel. In addition, the effects of some system parameters, such as OAM state interval and element spacing, on the capacity advantage of OAM based MIMO are also investigated. Our results reveal that OAM waves are complementary with MIMO method. OAM waves multiplexing is suitable for long-distance line-of-sight (LoS) communications or communications in open area where the multi-path effect is weak and can be used in massive MIMO systems as well. PMID:27146453
-
Cantone, Martina; Santos, Guido; Wentker, Pia; Lai, Xin; Vera, Julio
2017-01-01
Even today two bacterial lung infections, namely pneumonia and tuberculosis, are among the 10 most frequent causes of death worldwide. These infections still lack effective treatments in many developing countries and in immunocompromised populations like infants, elderly people and transplanted patients. The interaction between bacteria and the host is a complex system of interlinked intercellular and the intracellular processes, enriched in regulatory structures like positive and negative feedback loops. Severe pathological condition can emerge when the immune system of the host fails to neutralize the infection. This failure can result in systemic spreading of pathogens or overwhelming immune response followed by a systemic inflammatory response. Mathematical modeling is a promising tool to dissect the complexity underlying pathogenesis of bacterial lung infection at the molecular, cellular and tissue levels, and also at the interfaces among levels. In this article, we introduce mathematical and computational modeling frameworks that can be used for investigating molecular and cellular mechanisms underlying bacterial lung infection. Then, we compile and discuss published results on the modeling of regulatory pathways and cell populations relevant for lung infection and inflammation. Finally, we discuss how to make use of this multiplicity of modeling approaches to open new avenues in the search of the molecular and cellular mechanisms underlying bacterial infection in the lung. PMID:28912729
-
Cantone, Martina; Santos, Guido; Wentker, Pia; Lai, Xin; Vera, Julio
2017-01-01
Even today two bacterial lung infections, namely pneumonia and tuberculosis, are among the 10 most frequent causes of death worldwide. These infections still lack effective treatments in many developing countries and in immunocompromised populations like infants, elderly people and transplanted patients. The interaction between bacteria and the host is a complex system of interlinked intercellular and the intracellular processes, enriched in regulatory structures like positive and negative feedback loops. Severe pathological condition can emerge when the immune system of the host fails to neutralize the infection. This failure can result in systemic spreading of pathogens or overwhelming immune response followed by a systemic inflammatory response. Mathematical modeling is a promising tool to dissect the complexity underlying pathogenesis of bacterial lung infection at the molecular, cellular and tissue levels, and also at the interfaces among levels. In this article, we introduce mathematical and computational modeling frameworks that can be used for investigating molecular and cellular mechanisms underlying bacterial lung infection. Then, we compile and discuss published results on the modeling of regulatory pathways and cell populations relevant for lung infection and inflammation. Finally, we discuss how to make use of this multiplicity of modeling approaches to open new avenues in the search of the molecular and cellular mechanisms underlying bacterial infection in the lung.
-
NASA Astrophysics Data System (ADS)
Danner, Travis W.
Developing technology systems requires all manner of investment---engineering talent, prototypes, test facilities, and more. Even for simple design problems the investment can be substantial; for complex technology systems, the development costs can be staggering. The profitability of a corporation in a technology-driven industry is crucially dependent on maximizing the effectiveness of research and development investment. Decision-makers charged with allocation of this investment are forced to choose between the further evolution of existing technologies and the pursuit of revolutionary technologies. At risk on the one hand is excessive investment in an evolutionary technology which has only limited availability for further improvement. On the other hand, the pursuit of a revolutionary technology may mean abandoning momentum and the potential for substantial evolutionary improvement resulting from the years of accumulated knowledge. The informed answer to this question, evolutionary or revolutionary, requires knowledge of the expected rate of improvement and the potential a technology offers for further improvement. This research is dedicated to formulating the assessment and forecasting tools necessary to acquire this knowledge. The same physical laws and principles that enable the development and improvement of specific technologies also limit the ultimate capability of those technologies. Researchers have long used this concept as the foundation for modeling technological advancement through extrapolation by analogy to biological growth models. These models are employed to depict technology development as it asymptotically approaches limits established by the fundamental principles on which the technological approach is based. This has proven an effective and accurate approach to modeling and forecasting simple single-attribute technologies. With increased system complexity and the introduction of multiple system objectives, however, the usefulness of this modeling technique begins to diminish. With the introduction of multiple objectives, researchers often abandon technology growth models for scoring models and technology frontiers. While both approaches possess advantages over current growth models for the assessment of multi-objective technologies, each lacks a necessary dimension for comprehensive technology assessment. By collapsing multiple system metrics into a single, non-intuitive technology measure, scoring models provide a succinct framework for multi-objective technology assessment and forecasting. Yet, with no consideration of physical limits, scoring models provide no insight as to the feasibility of a particular combination of system capabilities. They only indicate that a given combination of system capabilities yields a particular score. Conversely, technology frontiers are constructed with the distinct objective of providing insight into the feasibility of system capability combinations. Yet again, upper limits to overall system performance are ignored. Furthermore, the data required to forecast subsequent technology frontiers is often inhibitive. In an attempt to reincorporate the fundamental nature of technology advancement as bound by physical principles, researchers have sought to normalize multi-objective systems whereby the variability of a single system objective is eliminated as a result of changes in the remaining objectives. This drastically limits the applicability of the resulting technology model because it is only applicable for a single setting of all other system attributes. Attempts to maintain the interaction between the growth curves of each technical objective of a complex system have thus far been limited to qualitative and subjective consideration. This research proposes the formulation of multidimensional growth models as an approach to simulating the advancement of multi-objective technologies towards their upper limits. Multidimensional growth models were formulated by noticing and exploiting the correlation between technology growth models and technology frontiers. Both are frontiers in actuality. The technology growth curve is a frontier between capability levels of a single attribute and time, while a technology frontier is a frontier between the capability levels of two or more attributes. Multidimensional growth models are formulated by exploiting the mathematical significance of this correlation. The result is a model that can capture both the interaction between multiple system attributes and their expected rates of improvement over time. The fundamental nature of technology development is maintained, and interdependent growth curves are generated for each system metric with minimal data requirements. Being founded on the basic nature of technology advancement, relative to physical limits, the availability for further improvement can be determined for a single metric relative to other system measures of merit. A by-product of this modeling approach is a single n-dimensional technology frontier linking all n system attributes with time. This provides an environment capable of forecasting future system capability in the form of advancing technology frontiers. The ability of a multidimensional growth model to capture the expected improvement of a specific technological approach is dependent on accurately identifying the physical limitations to each pertinent attribute. This research investigates two potential approaches to identifying those physical limits, a physics-based approach and a regression-based approach. The regression-based approach has found limited acceptance among forecasters, although it does show potential for estimating upper limits with a specified degree of uncertainty. Forecasters have long favored physics-based approaches for establishing the upper limit to unidimensional growth models. The task of accurately identifying upper limits has become increasingly difficult with the extension of growth models into multiple dimensions. A lone researcher may be able to identify the physical limitation to a single attribute of a simple system; however, as system complexity and the number of attributes increases, the attention of researchers from multiple fields of study is required. Thus, limit identification is itself an area of research and development requiring some level of investment. Whether estimated by physics or regression-based approaches, predicted limits will always have some degree of uncertainty. This research takes the approach of quantifying the impact of that uncertainty on model forecasts rather than heavily endorsing a single technique to limit identification. In addition to formulating the multidimensional growth model, this research provides a systematic procedure for applying that model to specific technology architectures. Researchers and decision-makers are able to investigate the potential for additional improvement within that technology architecture and to estimate the expected cost of each incremental improvement relative to the cost of past improvements. In this manner, multidimensional growth models provide the necessary information to set reasonable program goals for the further evolution of a particular technological approach or to establish the need for revolutionary approaches in light of the constraining limits of conventional approaches.
-
Miniature Loop Heat Pipe with Multiple Evaporators for Thermal Control of Small Spacecraft
NASA Technical Reports Server (NTRS)
Ku, Jentung; Ottenstein, Laura; Douglas, Denya; Pauken, Michael; Birur, Gajanana
2005-01-01
This paper presents an advanced miniature heat transport system for thermal control of small spacecraft. The thermal system consists of a loop heat pipe (LHP) with multiple evaporators and multiple deployable radiators for heat transfer, and variable emittance coatings on the radiators for performance enhancement. Thermoelectric coolers are used to control the loop operating temperature. The thermal system combines the functions of variable conductance heat pipes, thermal switches, thermal diodes, and the state-of-the-art LHPs into a single integrated thermal system. It retains all the performance characteristics of state-of-the-art LHPs and offers additional advantages to enhance the functionality, performance, versatility, and reliability of the system. Steady state and transient analytical models have been developed, and scaling criteria have also been established. A breadboard unit has been built for functional testing in laboratory and thermal vacuum environments. Experimental results show excellent performance of the thermal system and correlate very well with theoretical predictions.
-
Probabilistic Multi-Sensor Fusion Based Indoor Positioning System on a Mobile Device
He, Xiang; Aloi, Daniel N.; Li, Jia
2015-01-01
Nowadays, smart mobile devices include more and more sensors on board, such as motion sensors (accelerometer, gyroscope, magnetometer), wireless signal strength indicators (WiFi, Bluetooth, Zigbee), and visual sensors (LiDAR, camera). People have developed various indoor positioning techniques based on these sensors. In this paper, the probabilistic fusion of multiple sensors is investigated in a hidden Markov model (HMM) framework for mobile-device user-positioning. We propose a graph structure to store the model constructed by multiple sensors during the offline training phase, and a multimodal particle filter to seamlessly fuse the information during the online tracking phase. Based on our algorithm, we develop an indoor positioning system on the iOS platform. The experiments carried out in a typical indoor environment have shown promising results for our proposed algorithm and system design. PMID:26694387
-
Probabilistic Multi-Sensor Fusion Based Indoor Positioning System on a Mobile Device.
He, Xiang; Aloi, Daniel N; Li, Jia
2015-12-14
Nowadays, smart mobile devices include more and more sensors on board, such as motion sensors (accelerometer, gyroscope, magnetometer), wireless signal strength indicators (WiFi, Bluetooth, Zigbee), and visual sensors (LiDAR, camera). People have developed various indoor positioning techniques based on these sensors. In this paper, the probabilistic fusion of multiple sensors is investigated in a hidden Markov model (HMM) framework for mobile-device user-positioning. We propose a graph structure to store the model constructed by multiple sensors during the offline training phase, and a multimodal particle filter to seamlessly fuse the information during the online tracking phase. Based on our algorithm, we develop an indoor positioning system on the iOS platform. The experiments carried out in a typical indoor environment have shown promising results for our proposed algorithm and system design.
-
Alignment and integration of complex networks by hypergraph-based spectral clustering
NASA Astrophysics Data System (ADS)
Michoel, Tom; Nachtergaele, Bruno
2012-11-01
Complex networks possess a rich, multiscale structure reflecting the dynamical and functional organization of the systems they model. Often there is a need to analyze multiple networks simultaneously, to model a system by more than one type of interaction, or to go beyond simple pairwise interactions, but currently there is a lack of theoretical and computational methods to address these problems. Here we introduce a framework for clustering and community detection in such systems using hypergraph representations. Our main result is a generalization of the Perron-Frobenius theorem from which we derive spectral clustering algorithms for directed and undirected hypergraphs. We illustrate our approach with applications for local and global alignment of protein-protein interaction networks between multiple species, for tripartite community detection in folksonomies, and for detecting clusters of overlapping regulatory pathways in directed networks.
-
Alignment and integration of complex networks by hypergraph-based spectral clustering.
Michoel, Tom; Nachtergaele, Bruno
2012-11-01
Complex networks possess a rich, multiscale structure reflecting the dynamical and functional organization of the systems they model. Often there is a need to analyze multiple networks simultaneously, to model a system by more than one type of interaction, or to go beyond simple pairwise interactions, but currently there is a lack of theoretical and computational methods to address these problems. Here we introduce a framework for clustering and community detection in such systems using hypergraph representations. Our main result is a generalization of the Perron-Frobenius theorem from which we derive spectral clustering algorithms for directed and undirected hypergraphs. We illustrate our approach with applications for local and global alignment of protein-protein interaction networks between multiple species, for tripartite community detection in folksonomies, and for detecting clusters of overlapping regulatory pathways in directed networks.
-
Experimental comparison of conventional and nonlinear model-based control of a mixing tank
DOE Office of Scientific and Technical Information (OSTI.GOV)
Haeggblom, K.E.
1993-11-01
In this case study concerning control of a laboratory-scale mixing tank, conventional multiloop single-input single-output (SISO) control is compared with model-based'' control where the nonlinearity and multivariable characteristics of the process are explicitly taken into account. It is shown, especially if the operating range of the process is large, that the two outputs (level and temperature) cannot be adequately controlled by multiloop SISO control even if gain scheduling is used. By nonlinear multiple-input multiple-output (MIMO) control, on the other hand, very good control performance is obtained. The basic approach to nonlinear control used in this study is first to transformmore » the process into a globally linear and decoupled system, and then to design controllers for this system. Because of the properties of the resulting MIMO system, the controller design is very easy. Two nonlinear control system designs based on a steady-state and a dynamic model, respectively, are considered. In the dynamic case, both setpoint tracking and disturbance rejection can be addressed separately.« less
-
Conflicting Epistemologies and Inference in Coupled Human and Natural Systems
NASA Astrophysics Data System (ADS)
Garcia, M. E.
2017-12-01
Last year, I presented a model that projects per capita water consumption based on changes in price, population, building codes, and water stress salience. This model applied methods from hydrological science and engineering to relationships both within and beyond their traditional scope. Epistemologically, the development of mathematical models of natural or engineered systems is objectivist while research examining relationships between observations, perceptions and action is commonly constructivist or subjectivist. Drawing on multiple epistemologies is common in, and perhaps central to, the growing fields of coupled human and natural systems, and socio-hydrology. Critically, these philosophical perspectives vary in their view of the nature of the system as mechanistic, adaptive or constructed, and the split between aleatory and epistemic uncertainty. Interdisciplinary research is commonly cited as a way to address the critical and domain crossing challenge of sustainability as synthesis across perspectives can offer a more comprehensive view of system dynamics. However, combining methods and concepts from multiple ontologies and epistemologies can introduce contradictions into the logic of inference. These contractions challenge the evaluation of research products and the implications for practical application of research findings are not fully understood. Reflections on the evaluation, application, and generalization of the water consumption model described above are used to ground these broader questions and offer thoughts on the way forward.
-
Intelligent reservoir operation system based on evolving artificial neural networks
NASA Astrophysics Data System (ADS)
Chaves, Paulo; Chang, Fi-John
2008-06-01
We propose a novel intelligent reservoir operation system based on an evolving artificial neural network (ANN). Evolving means the parameters of the ANN model are identified by the GA evolutionary optimization technique. Accordingly, the ANN model should represent the operational strategies of reservoir operation. The main advantages of the Evolving ANN Intelligent System (ENNIS) are as follows: (i) only a small number of parameters to be optimized even for long optimization horizons, (ii) easy to handle multiple decision variables, and (iii) the straightforward combination of the operation model with other prediction models. The developed intelligent system was applied to the operation of the Shihmen Reservoir in North Taiwan, to investigate its applicability and practicability. The proposed method is first built to a simple formulation for the operation of the Shihmen Reservoir, with single objective and single decision. Its results were compared to those obtained by dynamic programming. The constructed network proved to be a good operational strategy. The method was then built and applied to the reservoir with multiple (five) decision variables. The results demonstrated that the developed evolving neural networks improved the operation performance of the reservoir when compared to its current operational strategy. The system was capable of successfully simultaneously handling various decision variables and provided reasonable and suitable decisions.
-
Sokkar, Pandian; Mohandass, Shylajanaciyar; Ramachandran, Murugesan
2011-07-01
We present a comparative account on 3D-structures of human type-1 receptor (AT1) for angiotensin II (AngII), modeled using three different methodologies. AngII activates a wide spectrum of signaling responses via the AT1 receptor that mediates physiological control of blood pressure and diverse pathological actions in cardiovascular, renal, and other cell types. Availability of 3D-model of AT1 receptor would significantly enhance the development of new drugs for cardiovascular diseases. However, templates of AT1 receptor with low sequence similarity increase the complexity in straightforward homology modeling, and hence there is a need to evaluate different modeling methodologies in order to use the models for sensitive applications such as rational drug design. Three models were generated for AT1 receptor by, (1) homology modeling with bovine rhodopsin as template, (2) homology modeling with multiple templates and (3) threading using I-TASSER web server. Molecular dynamics (MD) simulation (15 ns) of models in explicit membrane-water system, Ramachandran plot analysis and molecular docking with antagonists led to the conclusion that multiple template-based homology modeling outweighs other methodologies for AT1 modeling.
-
Time-resolved spectroscopy at surfaces and adsorbate dynamics:insights from a model-system approach
NASA Astrophysics Data System (ADS)
Boström, Emil; Mikkelsen, Anders; Verdozzi, Claudio
We introduce a finite-system, model description of the initial stages of femtosecond laser induced desorption at surfaces. Using the exact many-body time evolution and also results from a novel time-dependent DFT description for electron-nuclear systems, we analyse the competition between several surface-response mechanisms and electronic correlations in the transient and longer time dynamics under the influence of dipole-coupled fields. Our model allows us to explore how coherent multiple-pulse protocols impact desorption in a variety of prototypical experiments.
-
Multiple switching modes and multiple level states in memristive devices
NASA Astrophysics Data System (ADS)
Miao, Feng; Yang, J. Joshua; Borghetti, Julien; Strachan, John Paul; Zhang, M.-X.; Goldfarb, Ilan; Medeiros-Ribeiro, Gilberto; Williams, R. Stanley
2011-03-01
As one of the most promising technologies for next generation non-volatile memory, metal oxide based memristive devices have demonstrated great advantages on scalability, operating speed and power consumption. Here we report the observation of multiple switching modes and multiple level states in different memristive systems. The multiple switching modes can be obtained by limiting the current during electroforming, and related transport behaviors, including ionic and electronic motions, are characterized. Such observation can be rationalized by a model of two effective switching layers adjacent to the bottom and top electrodes. Multiple level states, corresponding to different composition of the conducting channel, will also be discussed in the context of multiple-level storage for high density, non-volatile memory applications.
-
A Two-Dimensional Helmholtz Equation Solution for the Multiple Cavity Scattering Problem
2013-02-01
obtained by using the block Gauss – Seidel iterative meth- od. To show the convergence of the iterative method, we define the error between two...models to the general multiple cavity setting. Numerical examples indicate that the convergence of the Gauss – Seidel iterative method depends on the...variational approach. A block Gauss – Seidel iterative method is introduced to solve the cou- pled system of the multiple cavity scattering problem, where
-
Ni, Bing-Jie; Peng, Lai; Law, Yingyu; Guo, Jianhua; Yuan, Zhiguo
2014-04-01
Autotrophic ammonia oxidizing bacteria (AOB) have been recognized as a major contributor to N2O production in wastewater treatment systems. However, so far N2O models have been proposed based on a single N2O production pathway by AOB, and there is still a lack of effective approach for the integration of these models. In this work, an integrated mathematical model that considers multiple production pathways is developed to describe N2O production by AOB. The pathways considered include the nitrifier denitrification pathway (N2O as the final product of AOB denitrification with NO2(-) as the terminal electron acceptor) and the hydroxylamine (NH2OH) pathway (N2O as a byproduct of incomplete oxidation of NH2OH to NO2(-)). In this model, the oxidation and reduction processes are modeled separately, with intracellular electron carriers introduced to link the two types of processes. The model is calibrated and validated using experimental data obtained with two independent nitrifying cultures. The model satisfactorily describes the N2O data from both systems. The model also predicts shifts of the dominating pathway at various dissolved oxygen (DO) and nitrite levels, consistent with previous hypotheses. This unified model is expected to enhance our ability to predict N2O production by AOB in wastewater treatment systems under varying operational conditions.
-
Emergence Processes up to Consciousness Using the Multiplicity Principle and Quantum Physics
NASA Astrophysics Data System (ADS)
Ehresmann, Andrée C.; Vanbremeersch, Jean-Paul
2002-09-01
Evolution is marked by the emergence of new objects and interactions. Pursuing our preceding work on Memory Evolutive Systems (MES; cf. our Internet site), we propose a general mathematical model for this process, based on Category Theory. Its main characteristics is the Multiplicity Principle (MP) which asserts the existence of complex objects with several possible configurations. The MP entails the emergence of non-reducible more and more complex objects (emergentist reductionism). From the laws of Quantum Physics, it follows that the MP is valid for the category of particles and atoms, hence, by complexification, for any natural autonomous anticipatory complex system, such as biological systems up to neural systems, or social systems. Applying the model to the MES of neurons, we describe the emergence of higher and higher cognitive processes and of a semantic memory. Consciousness is characterized by the development of a permanent `personal' memory, the archetypal core, which allows the formation of extended landscapes with an integration of the temporal dimensions.
-
Modeling and Simulation of Lab-on-a-Chip Systems
2005-08-12
complex chip geometries (including multiple turns). Variations of sample concentration profiles in laminar diffusion-based micromixers are also derived...CHAPTER 6 MODELING OF LAMINAR DIFFUSION-BASED COMPLEX ELECTROKINETIC PASSIVE MICROMIXERS ...140 6.4.4 Multi-Stream (Inter-Digital) Micromixers
-
NREL and IBM Improve Solar Forecasting with Big Data | Energy Systems
forecasting model using deep-machine-learning technology. The multi-scale, multi-model tool, named Watt-sun the first standard suite of metrics for this purpose. Validating Watt-sun at multiple sites across the
-
Ask Systems: Interrogative Access to Multiple Ways of Thinking
ERIC Educational Resources Information Center
Jonassen, David H.
2011-01-01
The purpose of this paper is to familiarize instructional designers and researchers with a useful design and research paradigm known as "Ask Systems." Ask Systems are interrogative interfaces to information and learning environments that model conversations with a skilled, reflective practitioner (Schon, The reflective practitioner, "1983") or…
-
Non-Lipschitzian dynamics for neural net modelling
NASA Technical Reports Server (NTRS)
Zak, Michail
1989-01-01
Failure of the Lipschitz condition in unstable equilibrium points of dynamical systems leads to a multiple-choice response to an initial deterministic input. The evolution of such systems is characterized by a special type of unpredictability measured by unbounded Liapunov exponents. Possible relation of these systems to future neural networks is discussed.
-
Limit cycles in piecewise-affine gene network models with multiple interaction loops
NASA Astrophysics Data System (ADS)
Farcot, Etienne; Gouzé, Jean-Luc
2010-01-01
In this article, we consider piecewise affine differential equations modelling gene networks. We work with arbitrary decay rates, and under a local hypothesis expressed as an alignment condition of successive focal points. The interaction graph of the system may be rather complex (multiple intricate loops of any sign, multiple thresholds, etc.). Our main result is an alternative theorem showing that if a sequence of region is periodically visited by trajectories, then under our hypotheses, there exists either a unique stable periodic solution, or the origin attracts all trajectories in this sequence of regions. This result extends greatly our previous work on a single negative feedback loop. We give several examples and simulations illustrating different cases.
-
Yang, Yong
2017-11-01
Most health studies focus on one health outcome and examine the influence of one or multiple risk factors. However, in reality, various pathways, interactions, and associations exist not only between risk factors and health outcomes but also among the risk factors and among health outcomes. The advance of system science methods, Big Data, and accumulated knowledge allows us to examine how multiple risk factors influence multiple health outcomes at multiple levels (termed a 3M study). Using the study of neighborhood environment and health as an example, I elaborate on the significance of 3M studies. 3M studies may lead to a significantly deeper understanding of the dynamic interactions among risk factors and outcomes and could help us design better interventions that may be of particular relevance for upstream interventions. Agent-based modeling (ABM) is a promising method in the 3M study, although its potentials are far from being fully explored. Future challenges include the gap of epidemiologic knowledge and evidence, lack of empirical data sources, and the technical challenges of ABM. © 2017 New York Academy of Sciences.
-
Phased-array-fed antenna configuration study, volume 2
NASA Technical Reports Server (NTRS)
Sorbello, R. M.; Zaghloul, A. I.; Lee, B. S.; Siddiqi, S.; Geller, B. D.
1983-01-01
Increased capacity in future satellite systems can be achieved through antenna systems which provide multiplicity of frequency reuses at K sub a band. A number of antenna configurations which can provide multiple fixed spot beams and multiple independent spot scanning beams at 20 GHz are addressed. Each design incorporates a phased array with distributed MMIC amplifiers and phasesifters feeding a two reflector optical system. The tradeoffs required for the design of these systems and the corresponding performances are presented. Five final designs are studied. In so doing, a type of MMIC/waveguide transition is described, and measured results of the breadboard model are presented. Other hardware components developed are described. This includes a square orthomode transducer, a subarray fed with a beamforming network to measure scanning performance, and another subarray used to study mutual coupling considerations. Discussions of the advantages and disadvantages of the final design are included.
-
Integrating Engineering Data Systems for NASA Spaceflight Projects
NASA Technical Reports Server (NTRS)
Carvalho, Robert E.; Tollinger, Irene; Bell, David G.; Berrios, Daniel C.
2012-01-01
NASA has a large range of custom-built and commercial data systems to support spaceflight programs. Some of the systems are re-used by many programs and projects over time. Management and systems engineering processes require integration of data across many of these systems, a difficult problem given the widely diverse nature of system interfaces and data models. This paper describes an ongoing project to use a central data model with a web services architecture to support the integration and access of linked data across engineering functions for multiple NASA programs. The work involves the implementation of a web service-based middleware system called Data Aggregator to bring together data from a variety of systems to support space exploration. Data Aggregator includes a central data model registry for storing and managing links between the data in disparate systems. Initially developed for NASA's Constellation Program needs, Data Aggregator is currently being repurposed to support the International Space Station Program and new NASA projects with processes that involve significant aggregating and linking of data. This change in user needs led to development of a more streamlined data model registry for Data Aggregator in order to simplify adding new project application data as well as standardization of the Data Aggregator query syntax to facilitate cross-application querying by client applications. This paper documents the approach from a set of stand-alone engineering systems from which data are manually retrieved and integrated, to a web of engineering data systems from which the latest data are automatically retrieved and more quickly and accurately integrated. This paper includes the lessons learned through these efforts, including the design and development of a service-oriented architecture and the evolution of the data model registry approaches as the effort continues to evolve and adapt to support multiple NASA programs and priorities.
-
Distributed software framework and continuous integration in hydroinformatics systems
NASA Astrophysics Data System (ADS)
Zhou, Jianzhong; Zhang, Wei; Xie, Mengfei; Lu, Chengwei; Chen, Xiao
2017-08-01
When encountering multiple and complicated models, multisource structured and unstructured data, complex requirements analysis, the platform design and integration of hydroinformatics systems become a challenge. To properly solve these problems, we describe a distributed software framework and it’s continuous integration process in hydroinformatics systems. This distributed framework mainly consists of server cluster for models, distributed database, GIS (Geographic Information System) servers, master node and clients. Based on it, a GIS - based decision support system for joint regulating of water quantity and water quality of group lakes in Wuhan China is established.
-
Implementing a trustworthy cost-accounting model.
Spence, Jay; Seargeant, Dan
2015-03-01
Hospitals and health systems can develop an effective cost-accounting model and maximize the effectiveness of their cost-accounting teams by focusing on six key areas: Implementing an enhanced data model. Reconciling data efficiently. Accommodating multiple cost-modeling techniques. Improving transparency of cost allocations. Securing department manager participation. Providing essential education and training to staff members and stakeholders.
-
Rating knowledge sharing in cross-domain collaborative filtering.
Li, Bin; Zhu, Xingquan; Li, Ruijiang; Zhang, Chengqi
2015-05-01
Cross-domain collaborative filtering (CF) aims to share common rating knowledge across multiple related CF domains to boost the CF performance. In this paper, we view CF domains as a 2-D site-time coordinate system, on which multiple related domains, such as similar recommender sites or successive time-slices, can share group-level rating patterns. We propose a unified framework for cross-domain CF over the site-time coordinate system by sharing group-level rating patterns and imposing user/item dependence across domains. A generative model, say ratings over site-time (ROST), which can generate and predict ratings for multiple related CF domains, is developed as the basic model for the framework. We further introduce cross-domain user/item dependence into ROST and extend it to two real-world cross-domain CF scenarios: 1) ROST (sites) for alleviating rating sparsity in the target domain, where multiple similar sites are viewed as related CF domains and some items in the target domain depend on their correspondences in the related ones; and 2) ROST (time) for modeling user-interest drift over time, where a series of time-slices are viewed as related CF domains and a user at current time-slice depends on herself in the previous time-slice. All these ROST models are instances of the proposed unified framework. The experimental results show that ROST (sites) can effectively alleviate the sparsity problem to improve rating prediction performance and ROST (time) can clearly track and visualize user-interest drift over time.
-
Modeling the lateral load distribution for multiple concrete crossties and fastening systems.
DOT National Transportation Integrated Search
2017-01-31
The objective of this project was to further investigate the performance of concrete crosstie and : fastening system under vertical and lateral wheel load using finite element analysis, and explore : possible improvement for current track design stan...
-
ECONOMIC ASSESSMENT OF WASTE WATER AQUACULTURE TREATMENT SYSTEMS
This study attempted to ascertain the economic viability of aquaculture as an alternative to conventional waste water treatment systems for small municipalities in the Southwestern region of the United States. A multiple water quality objective level cost-effectiveness model was ...
-
Optimum Vehicle Component Integration with InVeST (Integrated Vehicle Simulation Testbed)
DOE Office of Scientific and Technical Information (OSTI.GOV)
Ng, W; Paddack, E; Aceves, S
2001-12-27
We have developed an Integrated Vehicle Simulation Testbed (InVeST). InVeST is based on the concept of Co-simulation, and it allows the development of virtual vehicles that can be analyzed and optimized as an overall integrated system. The virtual vehicle is defined by selecting different vehicle components from a component library. Vehicle component models can be written in multiple programming languages running on different computer platforms. At the same time, InVeST provides full protection for proprietary models. Co-simulation is a cost-effective alternative to competing methodologies, such as developing a translator or selecting a single programming language for all vehicle components. InVeSTmore » has been recently demonstrated using a transmission model and a transmission controller model. The transmission model was written in SABER and ran on a Sun/Solaris workstation, while the transmission controller was written in MATRIXx and ran on a PC running Windows NT. The demonstration was successfully performed. Future plans include the applicability of Co-simulation and InVeST to analysis and optimization of multiple complex systems, including those of Intelligent Transportation Systems.« less
-
Protein structure modeling for CASP10 by multiple layers of global optimization.
Joo, Keehyoung; Lee, Juyong; Sim, Sangjin; Lee, Sun Young; Lee, Kiho; Heo, Seungryong; Lee, In-Ho; Lee, Sung Jong; Lee, Jooyoung
2014-02-01
In the template-based modeling (TBM) category of CASP10 experiment, we introduced a new protocol called protein modeling system (PMS) to generate accurate protein structures in terms of side-chains as well as backbone trace. In the new protocol, a global optimization algorithm, called conformational space annealing (CSA), is applied to the three layers of TBM procedure: multiple sequence-structure alignment, 3D chain building, and side-chain re-modeling. For 3D chain building, we developed a new energy function which includes new distance restraint terms of Lorentzian type (derived from multiple templates), and new energy terms that combine (physical) energy terms such as dynamic fragment assembly (DFA) energy, DFIRE statistical potential energy, hydrogen bonding term, etc. These physical energy terms are expected to guide the structure modeling especially for loop regions where no template structures are available. In addition, we developed a new quality assessment method based on random forest machine learning algorithm to screen templates, multiple alignments, and final models. For TBM targets of CASP10, we find that, due to the combination of three stages of CSA global optimizations and quality assessment, the modeling accuracy of PMS improves at each additional stage of the protocol. It is especially noteworthy that the side-chains of the final PMS models are far more accurate than the models in the intermediate steps. Copyright © 2013 Wiley Periodicals, Inc.
-
NASA Astrophysics Data System (ADS)
Yahyaei, Mohsen; Bashiri, Mahdi
2017-12-01
The hub location problem arises in a variety of domains such as transportation and telecommunication systems. In many real-world situations, hub facilities are subject to disruption. This paper deals with the multiple allocation hub location problem in the presence of facilities failure. To model the problem, a two-stage stochastic formulation is developed. In the proposed model, the number of scenarios grows exponentially with the number of facilities. To alleviate this issue, two approaches are applied simultaneously. The first approach is to apply sample average approximation to approximate the two stochastic problem via sampling. Then, by applying the multiple cuts Benders decomposition approach, computational performance is enhanced. Numerical studies show the effective performance of the SAA in terms of optimality gap for small problem instances with numerous scenarios. Moreover, performance of multi-cut Benders decomposition is assessed through comparison with the classic version and the computational results reveal the superiority of the multi-cut approach regarding the computational time and number of iterations.
-
Exciton multiplication from first principles.
Jaeger, Heather M; Hyeon-Deuk, Kim; Prezhdo, Oleg V
2013-06-18
Third-generation photovolatics require demanding cost and power conversion efficiency standards, which may be achieved through efficient exciton multiplication. Therefore, generating more than one electron-hole pair from the absorption of a single photon has vast ramifications on solar power conversion technology. Unlike their bulk counterparts, irradiated semiconductor quantum dots exhibit efficient exciton multiplication, due to confinement-enhanced Coulomb interactions and slower nonradiative losses. The exact characterization of the complicated photoexcited processes within quantum-dot photovoltaics is a work in progress. In this Account, we focus on the photophysics of nanocrystals and investigate three constituent processes of exciton multiplication, including photoexcitation, phonon-induced dephasing, and impact ionization. We quantify the role of each process in exciton multiplication through ab initio computation and analysis of many-electron wave functions. The probability of observing a multiple exciton in a photoexcited state is proportional to the magnitude of electron correlation, where correlated electrons can be simultaneously promoted across the band gap. Energies of multiple excitons are determined directly from the excited state wave functions, defining the threshold for multiple exciton generation. This threshold is strongly perturbed in the presence of surface defects, dopants, and ionization. Within a few femtoseconds following photoexcitation, the quantum state loses coherence through interactions with the vibrating atomic lattice. The phase relationship between single excitons and multiple excitons dissipates first, followed by multiple exciton fission. Single excitons are coupled to multiple excitons through Coulomb and electron-phonon interactions, and as a consequence, single excitons convert to multiple excitons and vice versa. Here, exciton multiplication depends on the initial energy and coupling magnitude and competes with electron-phonon energy relaxation. Multiple excitons are generated through impact ionization within picoseconds. The basis of exciton multiplication in quantum dots is the collective result of photoexcitation, dephasing, and nonadiabatic evolution. Each process is characterized by a distinct time-scale, and the overall multiple exciton generation dynamics is complete by about 10 ps. Without relying on semiempirical parameters, we computed quantum mechanical probabilities of multiple excitons for small model systems. Because exciton correlations and coherences are microscopic, quantum properties, results for small model systems can be extrapolated to larger, realistic quantum dots.
-
A seasonal hydrologic ensemble prediction system for water resource management
NASA Astrophysics Data System (ADS)
Luo, L.; Wood, E. F.
2006-12-01
A seasonal hydrologic ensemble prediction system, developed for the Ohio River basin, has been improved and expanded to several other regions including the Eastern U.S., Africa and East Asia. The prediction system adopts the traditional Extended Streamflow Prediction (ESP) approach, utilizing the VIC (Variable Infiltration Capacity) hydrological model as the central tool for producing ensemble prediction of soil moisture, snow and streamflow with lead times up to 6-month. VIC is forced by observed meteorology to estimate the hydrological initial condition prior to the forecast, but during the forecast period the atmospheric forcing comes from statistically downscaled, seasonal forecast from dynamic climate models. The seasonal hydrologic ensemble prediction system is currently producing realtime seasonal hydrologic forecast for these regions on a monthly basis. Using hindcasts from a 19-year period (1981-1999), during which seasonal hindcasts from NCEP Climate Forecast System (CFS) and European Union DEMETER project are available, we evaluate the performance of the forecast system over our forecast regions. The evaluation shows that the prediction system using the current forecast approach is able to produce reliable and accurate precipitation, soil moisture and streamflow predictions. The overall skill is much higher then the traditional ESP. In particular, forecasts based on multiple climate model forecast are more skillful than single model-based forecast. This emphasizes the significant need for producing seasonal climate forecast with multiple climate models for hydrologic applications. Forecast from this system is expected to provide very valuable information about future hydrologic states and associated risks for end users, including water resource management and financial sectors.
-
Multiplicity fluctuations and collective flow in small colliding systems
NASA Astrophysics Data System (ADS)
Kawaguchi, Koji; Murase, Koichi; Hirano, Tetsufumi
2017-11-01
Recent observation of collective-flow-like behaviours in small colliding systems attracts significant theoretical and experimental interests. In large colliding systems, large collective flow has been interpreted as manifestation of almost-perfect fluidity of the quark gluon plasma (QGP). So it is quite intriguing to explore how small the QGP can be as a fluid. Multiplicity fluctuations play a crucial role in centrality definition of the events in small colliding systems since the fluctuations are, in general, more important as the system size is getting smaller. To consider the correct multiplicity fluctuations, we employ PYTHIA which naturally describes multiplicity distribution in p+p collisions. We superpose p+p collisions by taking into account the number of participants and that of binary collisions from Monte-Carlo version of Glauber model and evaluate initial entropy density distributions which contain not only multiplicity fluctuations but also fluctuations of longitudinal profiles. Solving hydrodynamic equations followed by the hadronic afterburner, we calculate transverse momentum spectra, elliptic and triangular flow parameters in p+Au, d+Au and 3He+Au collisions at the RHIC energy and p+Pb collisions at the LHC energy. Although a large fraction of final anisotropic flow parameters comes from the fluid-dynamical stage, the effects of hadronic rescatterings turn out to be also important as well in understanding of the flow data in small colliding systems.
-
NASA Astrophysics Data System (ADS)
Sell, K. S.; Heather, M. R.; Herbert, B. E.
2004-12-01
Exposing earth system science (ESS) concepts into introductory geoscience courses may present new and unique cognitive learning issues for students including understanding the role of positive and negative feedbacks in system responses to perturbations, spatial heterogeneity, and temporal dynamics, especially when systems exhibit complex behavior. Implicit learning goals of typical introductory undergraduate geoscience courses are more focused on building skill-sets and didactic knowledge in learners than developing a deeper understanding of the dynamics and processes of complex earth systems through authentic inquiry. Didactic teaching coupled with summative assessment of factual knowledge tends to limit student¡¦s understanding of the nature of science, their belief in the relevancy of science to their lives, and encourages memorization and regurgitation; this is especially true among the non-science majors who compose the majority of students in introductory courses within the large university setting. Students organize scientific knowledge and reason about earth systems by manipulating internally constructed mental models. This pilot study focuses on characterizing the impact of inquiry-based learning with multiple representations to foster critical thinking and mental model development about authentic environmental issues of coastal systems in an introductory geoscience course. The research was conducted in nine introductory physical geology laboratory sections (N ˜ 150) at Texas A&M University as part of research connected with the Information Technology in Science (ITS) Center. Participants were randomly placed into experimental and control groups. Experimental groups were exposed to multiple representations including both web-based learning materials (i.e. technology-supported visualizations and analysis of multiple datasets) and physical models, whereas control groups were provided with the traditional ¡workbook style¡" laboratory assignments. Assessment of pre- and post-test results was performed to provide indications of content knowledge and mental model expression improvements between groups. A rubric was used as the assessment instrument to evaluate student products (Cronbach alpha: 0.84 ¡V 0.98). Characterization of student performance based on a Student¡¦s t-test indicates that significant differences (p < 0.05) in pre-post achievement occurred primarily within the experimental group; this illustrates that the use of multiple representations had an impact on student learning of ESS concepts, particularly in regard to mental model constructions. Analysis of variance also suggests that student mental model constructions were significantly different (p < 0.10) between test groups. Factor analysis extracted three principle components (eigenvalue > 1) which show similar clustering of variables that influence cognition, indicating that the cognitive processes driving student understanding of geoscience do not vary among student test groups. Categories of cognition include critical thinking skills (percent variance = 22.16%), understanding of the nature of science (percent variance = 25.16%), and ability to interpret results (percent variance = 28.89%). Lower numbers of students completed all of the required assignments of this research than expected (65.3%), restricting the quality of the results and therefore the ability to make more significant interpretations; this was likely due to the non-supportive learning environment in which the research was implemented.
-
Maturity of hospital information systems: Most important influencing factors.
Vidal Carvalho, João; Rocha, Álvaro; Abreu, António
2017-07-01
Maturity models facilitate organizational management, including information systems management, with hospital organizations no exception. This article puts forth a study carried out with a group of experts in the field of hospital information systems management with a view to identifying the main influencing factors to be included in an encompassing maturity model for hospital information systems management. This study is based on the results of a literature review, which identified maturity models in the health field and relevant influencing factors. The development of this model is justified to the extent that the available maturity models for the hospital information systems management field reveal multiple limitations, including lack of detail, absence of tools to determine their maturity and lack of characterization for stages of maturity structured by different influencing factors.
-
Shared mental models of integrated care: aligning multiple stakeholder perspectives.
Evans, Jenna M; Baker, G Ross
2012-01-01
Health service organizations and professionals are under increasing pressure to work together to deliver integrated patient care. A common understanding of integration strategies may facilitate the delivery of integrated care across inter-organizational and inter-professional boundaries. This paper aims to build a framework for exploring and potentially aligning multiple stakeholder perspectives of systems integration. The authors draw from the literature on shared mental models, strategic management and change, framing, stakeholder management, and systems theory to develop a new construct, Mental Models of Integrated Care (MMIC), which consists of three types of mental models, i.e. integration-task, system-role, and integration-belief. The MMIC construct encompasses many of the known barriers and enablers to integrating care while also providing a comprehensive, theory-based framework of psychological factors that may influence inter-organizational and inter-professional relations. While the existing literature on integration focuses on optimizing structures and processes, the MMIC construct emphasizes the convergence and divergence of stakeholders' knowledge and beliefs, and how these underlying cognitions influence interactions (or lack thereof) across the continuum of care. MMIC may help to: explain what differentiates effective from ineffective integration initiatives; determine system readiness to integrate; diagnose integration problems; and develop interventions for enhancing integrative processes and ultimately the delivery of integrated care. Global interest and ongoing challenges in integrating care underline the need for research on the mental models that characterize the behaviors of actors within health systems; the proposed framework offers a starting point for applying a cognitive perspective to health systems integration.
-
NASA Astrophysics Data System (ADS)
Harkrider, Curtis Jason
2000-08-01
The incorporation of gradient-index (GRIN) material into optical systems offers novel and practical solutions to lens design problems. However, widespread use of gradient-index optics has been limited by poor correlation between gradient-index designs and the refractive index profiles produced by ion exchange between glass and molten salt. Previously, a design-for- manufacture model was introduced that connected the design and fabrication processes through use of diffusion modeling linked with lens design software. This project extends the design-for-manufacture model into a time- varying boundary condition (TVBC) diffusion model. TVBC incorporates the time-dependent phenomenon of melt poisoning and introduces a new index profile control method, multiple-step diffusion. The ions displaced from the glass during the ion exchange fabrication process can reduce the total change in refractive index (Δn). Chemical equilibrium is used to model this melt poisoning process. Equilibrium experiments are performed in a titania silicate glass and chemically analyzed. The equilibrium model is fit to ion concentration data that is used to calculate ion exchange boundary conditions. The boundary conditions are changed purposely to control the refractive index profile in multiple-step TVBC diffusion. The glass sample is alternated between ion exchange with a molten salt bath and annealing. The time of each diffusion step can be used to exert control on the index profile. The TVBC computer model is experimentally verified and incorporated into the design- for-manufacture subroutine that runs in lens design software. The TVBC design-for-manufacture model is useful for fabrication-based tolerance analysis of gradient-index lenses and for the design of manufactureable GRIN lenses. Several optical elements are designed and fabricated using multiple-step diffusion, verifying the accuracy of the model. The strength of multiple-step diffusion process lies in its versatility. An axicon, imaging lens, and curved radial lens, all with different index profile requirements, are designed out of a single glass composition.
-
Coilgun Acceleration Model Containing Interactions Between Multiple Coils
NASA Technical Reports Server (NTRS)
Liu, Connie; Polzin, Kurt; Martin, Adam
2017-01-01
Electromagnetic (EM) accelerators have the potential to fill a performance range not currently being met by conventional chemical and electric propulsion systems by providing a specific impulse of 600-1000 seconds and a thrust-to-power ratio greater than 200 mN/kW. A propulsion system based on EM acceleration of small projectiles has the traditional advantages of using a pulsed system, including precise control over a range of thrust and power levels as well as rapid response and repetition rates. Furthermore, EM accelerators have lower power requirements than conventional electric propulsion systems since no plasma creation is necessary. A coilgun is a specific type of EM device where a high-current pulse through a coil of wire interacts with a conductive projectile via an induced magnetic field to accelerate the projectile. There are no physical or electrical connections to the projectile, which leads to less system degradation and a longer life expectancy. Multi-staging a coilgun by adding multiple turns on a single coil or on the projectile increases the inductance, thus permitting acceleration of the projectile to higher velocities. Previously, a simplified problem of modeling an inductively-coupled, single-coil coilgun using a circuit-based analysis coupled to the one-dimensional momentum equation through Lenz's law was solved; however, the analysis was only conducted on uncoupled coils. The problem is significantly more complicated when multiple, independently-powered coils simultaneously operate and interact with each other and the projectile through induced magnetic fields. This paper presents a multi-coil model developed with the magnetostatic finite element solver QuickField. In the model, mutual inductance values between pairs of conductors were found by first computing the magnetic field energy for different cases where individual coils or multiple coils carry current, then integrating over the entire finite element domain for each case, and finally using the definition of inductive energy storage to solve for the self and mutual inductance. The electric circuit model is coupled to the projectile through Lenz's law, with the coils coupled through mutual inductance but able to be independently triggered at different times to optimize the acceleration profile. This initial model to predict the behavior of a projectile's acceleration through a coupled, multi-coil coilgun increases the potential of building a highly efficient coilgun thruster with key advantages over other EM thruster systems, thus making it a promising candidate for satellite main propulsion or attitude control thrusters.
-
NASA Astrophysics Data System (ADS)
Yang, Jingyu; Lin, Jiahui; Liu, Yuejun; Yang, Kang; Zhou, Lanwei; Chen, Guoping
2017-08-01
It is well known that intelligent control theory has been used in many research fields, novel modeling method (DROMM) is used for flexible rectangular active vibration control, and then the validity of new model is confirmed by comparing finite element model with new model. In this paper, taking advantage of the dynamics of flexible rectangular plate, a two-loop sliding mode (TSM) MIMO approach is introduced for designing multiple-input multiple-output continuous vibration control system, which can overcome uncertainties, disturbances or unstable dynamics. An illustrative example is given in order to show the feasibility of the method. Numerical simulations and experiment confirm the effectiveness of the proposed TSM MIMO controller.
-
Generating Models of Surgical Procedures using UMLS Concepts and Multiple Sequence Alignment
Meng, Frank; D’Avolio, Leonard W.; Chen, Andrew A.; Taira, Ricky K.; Kangarloo, Hooshang
2005-01-01
Surgical procedures can be viewed as a process composed of a sequence of steps performed on, by, or with the patient’s anatomy. This sequence is typically the pattern followed by surgeons when generating surgical report narratives for documenting surgical procedures. This paper describes a methodology for semi-automatically deriving a model of conducted surgeries, utilizing a sequence of derived Unified Medical Language System (UMLS) concepts for representing surgical procedures. A multiple sequence alignment was computed from a collection of such sequences and was used for generating the model. These models have the potential of being useful in a variety of informatics applications such as information retrieval and automatic document generation. PMID:16779094
-
Theoretical modeling of the MILES hit profiles in military weapon low-data rate simulators
NASA Astrophysics Data System (ADS)
Andrews, L. C.; Phillips, R. L.; Smith, C. A.; Belichki, S. B.; Crabbs, R.; Cofarro, J. T.; Fountain, W.; Tucker, F. M.; Parrish, B. J.
2016-09-01
Math modeling of a low-data-rate optical communication system is presented and compared with recent testing results over ranges up to 100 m in an indoor tunnel at Kennedy Space Center. Additional modeling of outdoor testing results at longer ranges in the open atmosphere is also presented. The system modeled is the Army's Multiple Integrated Laser Engagement System (MILES) that has been used as a tactical training system since the early 1980s. The objective of the current modeling and testing is to obtain target hit zone profiles for the M16A2/M4 rifles and establish a data baseline for MILES that will aid in its upgrade using more recently developed lasers and detectors.
-
Model-Based Reasoning in the Detection of Satellite Anomalies
1990-12-01
Conference on Artificial Intellegence . 1363-1368. Detroit, Michigan, August 89. Chu, Wei-Hai. "Generic Expert System Shell for Diagnostic Reasoning... Intellegence . 1324-1330. Detroit, Michigan, August 89. de Kleer, Johan and Brian C. Williams. "Diagnosing Multiple Faults," Artificial Intellegence , 32(1): 97...Benjamin Kuipers. "Model-Based Monitoring of Dynamic Systems," Proceedings of the Eleventh Intematianal Joint Conference on Artificial Intellegence . 1238
-
Multiradar tracking for theater missile defense
NASA Astrophysics Data System (ADS)
Sviestins, Egils
1995-09-01
A prototype system for tracking tactical ballistic missiles using multiple radars has been developed. The tracking is based on measurement level fusion (`true' multi-radar) tracking. Strobes from passive sensors can also be used. We describe various features of the system with some emphasis on the filtering technique. This is based on the Interacting Multiple Model framework where the states are Free Flight, Drag, Boost, and Auxiliary. Measurement error modeling includes the signal to noise ratio dependence; outliers and miscorrelations are handled in the same way. The launch point is calculated within one minute from the detection of the missile. The impact point, and its uncertainty region, is calculated continually by extrapolating the track state vector using the equations of planetary motion.
-
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.
-
NASA Astrophysics Data System (ADS)
Madden, E. H.; McBeck, J.; Cooke, M. L.
2013-12-01
Over multiple earthquake cycles, strike-slip faults link to form through-going structures, as demonstrated by the continuous nature of the mature San Andreas fault system in California relative to the younger and more segmented San Jacinto fault system nearby. Despite its immaturity, the San Jacinto system accommodates between one third and one half of the slip along the boundary between the North American and Pacific plates. It therefore poses a significant seismic threat to southern California. Better understanding of how the San Jacinto system has evolved over geologic time and of current interactions between faults within the system is critical to assessing this seismic hazard accurately. Numerical models are well suited to simulating kilometer-scale processes, but models of fault system development are challenged by the multiple physical mechanisms involved. For example, laboratory experiments on brittle materials show that faults propagate and eventually join (hard-linkage) by both opening-mode and shear failure. In addition, faults interact prior to linkage through stress transfer (soft-linkage). The new algorithm GROW (GRowth by Optimization of Work) accounts for this complex array of behaviors by taking a global approach to fault propagation while adhering to the principals of linear elastic fracture mechanics. This makes GROW a powerful tool for studying fault interactions and fault system development over geologic time. In GROW, faults evolve to minimize the work (or energy) expended during deformation, thereby maximizing the mechanical efficiency of the entire system. Furthermore, the incorporation of both static and dynamic friction allows GROW models to capture fault slip and fault propagation in single earthquakes as well as over consecutive earthquake cycles. GROW models with idealized faults reveal that the initial fault spacing and the applied stress orientation control fault linkage propensity and linkage patterns. These models allow the gains in efficiency provided by both hard-linkage and soft-linkage to be quantified and compared. Specialized models of interactions over the past 1 Ma between the Clark and Coyote Creek faults within the San Jacinto system reveal increasing mechanical efficiency as these fault structures change over time. Alongside this increasing efficiency is an increasing likelihood for single, larger earthquakes that rupture multiple fault segments. These models reinforce the sensitivity of mechanical efficiency to both fault structure and the regional tectonic stress orientation controlled by plate motions and provide insight into how slip may have been partitioned between the San Andreas and San Jacinto systems over the past 1 Ma.
-
Kumar, M Praveen; Patil, Suneel G; Dheeraj, Bhandari; Reddy, Keshav; Goel, Dinker; Krishna, Gopi
2015-06-01
The difficulty in obtaining an acceptable impression increases exponentially as the number of abutments increases. Accuracy of the impression material and the use of a suitable impression technique are of utmost importance in the fabrication of a fixed partial denture. This study compared the accuracy of the matrix impression system with conventional putty reline and multiple mix technique for individual dies by comparing the inter-abutment distance in the casts obtained from the impressions. Three groups, 10 impressions each with three impression techniques (matrix impression system, putty reline technique and multiple mix technique) were made of a master die. Typodont teeth were embedded in a maxillary frasaco model base. The left first premolar was removed to create a three-unit fixed partial denture situation and the left canine and second premolar were prepared conservatively, and hatch marks were made on the abutment teeth. The final casts obtained from the impressions were examined under a profile projector and the inter-abutment distance was calculated for all the casts and compared. The results from this study showed that in the mesiodistal dimensions the percentage deviation from master model in Group I was 0.1 and 0.2, in Group II was 0.9 and 0.3, and Group III was 1.6 and 1.5, respectively. In the labio-palatal dimensions the percentage deviation from master model in Group I was 0.01 and 0.4, Group II was 1.9 and 1.3, and Group III was 2.2 and 2.0, respectively. In the cervico-incisal dimensions the percentage deviation from the master model in Group I was 1.1 and 0.2, Group II was 3.9 and 1.7, and Group III was 1.9 and 3.0, respectively. In the inter-abutment dimension of dies, percentage deviation from master model in Group I was 0.1, Group II was 0.6, and Group III was 1.0. The matrix impression system showed more accuracy of reproduction for individual dies when compared with putty reline technique and multiple mix technique in all the three directions, as well as the inter-abutment distance.
-
Multiple-hypothesis multiple-model line tracking
NASA Astrophysics Data System (ADS)
Pace, Donald W.; Owen, Mark W.; Cox, Henry
2000-07-01
Passive sonar signal processing generally includes tracking of narrowband and/or broadband signature components observed on a Lofargram or on a Bearing-Time-Record (BTR) display. Fielded line tracking approaches to date have been recursive and single-hypthesis-oriented Kalman- or alpha-beta filters, with no mechanism for considering tracking alternatives beyond the most recent scan of measurements. While adaptivity is often built into the filter to handle changing track dynamics, these approaches are still extensions of single target tracking solutions to multiple target tracking environment. This paper describes an application of multiple-hypothesis, multiple target tracking technology to the sonar line tracking problem. A Multiple Hypothesis Line Tracker (MHLT) is developed which retains the recursive minimum-mean-square-error tracking behavior of a Kalman Filter in a maximum-a-posteriori delayed-decision multiple hypothesis context. Multiple line track filter states are developed and maintained using the interacting multiple model (IMM) state representation. Further, the data association and assignment problem is enhanced by considering line attribute information (line bandwidth and SNR) in addition to beam/bearing and frequency fit. MHLT results on real sonar data are presented to demonstrate the benefits of the multiple hypothesis approach. The utility of the system in cluttered environments and particularly in crossing line situations is shown.
-
Design of a transportable high efficiency fast neutron spectrometer
Roecker, C.; Bernstein, A.; Bowden, N. S.; ...
2016-04-12
A transportable fast neutron detection system has been designed and constructed for measuring neutron energy spectra and flux ranging from tens to hundreds of MeV. The transportability of the spectrometer reduces the detector-related systematic bias between different neutron spectra and flux measurements, which allows for the comparison of measurements above or below ground. The spectrometer will measure neutron fluxes that are of prohibitively low intensity compared to the site-specific background rates targeted by other transportable fast neutron detection systems. To measure low intensity high-energy neutron fluxes, a conventional capture-gating technique is used for measuring neutron energies above 20 MeV andmore » a novel multiplicity technique is used for measuring neutron energies above 100 MeV. The spectrometer is composed of two Gd containing plastic scintillator detectors arranged around a lead spallation target. To calibrate and characterize the position dependent response of the spectrometer, a Monte Carlo model was developed and used in conjunction with experimental data from gamma ray sources. Multiplicity event identification algorithms were developed and used with a Cf-252 neutron multiplicity source to validate the Monte Carlo model Gd concentration and secondary neutron capture efficiency. The validated Monte Carlo model was used to predict an effective area for the multiplicity and capture gating analyses. For incident neutron energies between 100 MeV and 1000 MeV with an isotropic angular distribution, the multiplicity analysis predicted an effective area of 500 cm 2 rising to 5000 cm 2. For neutron energies above 20 MeV, the capture-gating analysis predicted an effective area between 1800 cm 2 and 2500 cm 2. As a result, the multiplicity mode was found to be sensitive to the incident neutron angular distribution.« less
-
DOE Office of Scientific and Technical Information (OSTI.GOV)
Roecker, C.; Bernstein, A.; Bowden, N. S.
A transportable fast neutron detection system has been designed and constructed for measuring neutron energy spectra and flux ranging from tens to hundreds of MeV. The transportability of the spectrometer reduces the detector-related systematic bias between different neutron spectra and flux measurements, which allows for the comparison of measurements above or below ground. The spectrometer will measure neutron fluxes that are of prohibitively low intensity compared to the site-specific background rates targeted by other transportable fast neutron detection systems. To measure low intensity high-energy neutron fluxes, a conventional capture-gating technique is used for measuring neutron energies above 20 MeV andmore » a novel multiplicity technique is used for measuring neutron energies above 100 MeV. The spectrometer is composed of two Gd containing plastic scintillator detectors arranged around a lead spallation target. To calibrate and characterize the position dependent response of the spectrometer, a Monte Carlo model was developed and used in conjunction with experimental data from gamma ray sources. Multiplicity event identification algorithms were developed and used with a Cf-252 neutron multiplicity source to validate the Monte Carlo model Gd concentration and secondary neutron capture efficiency. The validated Monte Carlo model was used to predict an effective area for the multiplicity and capture gating analyses. For incident neutron energies between 100 MeV and 1000 MeV with an isotropic angular distribution, the multiplicity analysis predicted an effective area of 500 cm 2 rising to 5000 cm 2. For neutron energies above 20 MeV, the capture-gating analysis predicted an effective area between 1800 cm 2 and 2500 cm 2. As a result, the multiplicity mode was found to be sensitive to the incident neutron angular distribution.« less
-
Wide coverage biomedical event extraction using multiple partially overlapping corpora
2013-01-01
Background Biomedical events are key to understanding physiological processes and disease, and wide coverage extraction is required for comprehensive automatic analysis of statements describing biomedical systems in the literature. In turn, the training and evaluation of extraction methods requires manually annotated corpora. However, as manual annotation is time-consuming and expensive, any single event-annotated corpus can only cover a limited number of semantic types. Although combined use of several such corpora could potentially allow an extraction system to achieve broad semantic coverage, there has been little research into learning from multiple corpora with partially overlapping semantic annotation scopes. Results We propose a method for learning from multiple corpora with partial semantic annotation overlap, and implement this method to improve our existing event extraction system, EventMine. An evaluation using seven event annotated corpora, including 65 event types in total, shows that learning from overlapping corpora can produce a single, corpus-independent, wide coverage extraction system that outperforms systems trained on single corpora and exceeds previously reported results on two established event extraction tasks from the BioNLP Shared Task 2011. Conclusions The proposed method allows the training of a wide-coverage, state-of-the-art event extraction system from multiple corpora with partial semantic annotation overlap. The resulting single model makes broad-coverage extraction straightforward in practice by removing the need to either select a subset of compatible corpora or semantic types, or to merge results from several models trained on different individual corpora. Multi-corpus learning also allows annotation efforts to focus on covering additional semantic types, rather than aiming for exhaustive coverage in any single annotation effort, or extending the coverage of semantic types annotated in existing corpora. PMID:23731785