Statistical Methodology for the Analysis of Repeated Duration Data in Behavioral Studies.

PubMed

Letué, Frédérique; Martinez, Marie-José; Samson, Adeline; Vilain, Anne; Vilain, Coriandre

2018-03-15

Repeated duration data are frequently used in behavioral studies. Classical linear or log-linear mixed models are often inadequate to analyze such data, because they usually consist of nonnegative and skew-distributed variables. Therefore, we recommend use of a statistical methodology specific to duration data. We propose a methodology based on Cox mixed models and written under the R language. This semiparametric model is indeed flexible enough to fit duration data. To compare log-linear and Cox mixed models in terms of goodness-of-fit on real data sets, we also provide a procedure based on simulations and quantile-quantile plots. We present two examples from a data set of speech and gesture interactions, which illustrate the limitations of linear and log-linear mixed models, as compared to Cox models. The linear models are not validated on our data, whereas Cox models are. Moreover, in the second example, the Cox model exhibits a significant effect that the linear model does not. We provide methods to select the best-fitting models for repeated duration data and to compare statistical methodologies. In this study, we show that Cox models are best suited to the analysis of our data set.

An improved approach for flight readiness certification: Probabilistic models for flaw propagation and turbine blade failure. Volume 1: Methodology and applications

NASA Technical Reports Server (NTRS)

Moore, N. R.; Ebbeler, D. H.; Newlin, L. E.; Sutharshana, S.; Creager, M.

1992-01-01

An improved methodology for quantitatively evaluating failure risk of spaceflight systems to assess flight readiness and identify risk control measures is presented. This methodology, called Probabilistic Failure Assessment (PFA), combines operating experience from tests and flights with analytical modeling of failure phenomena to estimate failure risk. The PFA methodology is of particular value when information on which to base an assessment of failure risk, including test experience and knowledge of parameters used in analytical modeling, is expensive or difficult to acquire. The PFA methodology is a prescribed statistical structure in which analytical models that characterize failure phenomena are used conjointly with uncertainties about analysis parameters and/or modeling accuracy to estimate failure probability distributions for specific failure modes. These distributions can then be modified, by means of statistical procedures of the PFA methodology, to reflect any test or flight experience. State-of-the-art analytical models currently employed for designs failure prediction, or performance analysis are used in this methodology. The rationale for the statistical approach taken in the PFA methodology is discussed, the PFA methodology is described, and examples of its application to structural failure modes are presented. The engineering models and computer software used in fatigue crack growth and fatigue crack initiation applications are thoroughly documented.

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

NASA Technical Reports Server (NTRS)

1986-01-01

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

Sensor-based activity recognition using extended belief rule-based inference methodology.

PubMed

Calzada, A; Liu, J; Nugent, C D; Wang, H; Martinez, L

2014-01-01

The recently developed extended belief rule-based inference methodology (RIMER+) recognizes the need of modeling different types of information and uncertainty that usually coexist in real environments. A home setting with sensors located in different rooms and on different appliances can be considered as a particularly relevant example of such an environment, which brings a range of challenges for sensor-based activity recognition. Although RIMER+ has been designed as a generic decision model that could be applied in a wide range of situations, this paper discusses how this methodology can be adapted to recognize human activities using binary sensors within smart environments. The evaluation of RIMER+ against other state-of-the-art classifiers in terms of accuracy, efficiency and applicability was found to be significantly relevant, specially in situations of input data incompleteness, and it demonstrates the potential of this methodology and underpins the basis to develop further research on the topic.

Knowledge-based and model-based hybrid methodology for comprehensive waste minimization in electroplating plants

NASA Astrophysics Data System (ADS)

Luo, Keqin

1999-11-01

The electroplating industry of over 10,000 planting plants nationwide is one of the major waste generators in the industry. Large quantities of wastewater, spent solvents, spent process solutions, and sludge are the major wastes generated daily in plants, which costs the industry tremendously for waste treatment and disposal and hinders the further development of the industry. It becomes, therefore, an urgent need for the industry to identify technically most effective and economically most attractive methodologies and technologies to minimize the waste, while the production competitiveness can be still maintained. This dissertation aims at developing a novel WM methodology using artificial intelligence, fuzzy logic, and fundamental knowledge in chemical engineering, and an intelligent decision support tool. The WM methodology consists of two parts: the heuristic knowledge-based qualitative WM decision analysis and support methodology and fundamental knowledge-based quantitative process analysis methodology for waste reduction. In the former, a large number of WM strategies are represented as fuzzy rules. This becomes the main part of the knowledge base in the decision support tool, WMEP-Advisor. In the latter, various first-principles-based process dynamic models are developed. These models can characterize all three major types of operations in an electroplating plant, i.e., cleaning, rinsing, and plating. This development allows us to perform a thorough process analysis on bath efficiency, chemical consumption, wastewater generation, sludge generation, etc. Additional models are developed for quantifying drag-out and evaporation that are critical for waste reduction. The models are validated through numerous industrial experiments in a typical plating line of an industrial partner. The unique contribution of this research is that it is the first time for the electroplating industry to (i) use systematically available WM strategies, (ii) know quantitatively and accurately what is going on in each tank, and (iii) identify all WM opportunities through process improvement. This work has formed a solid foundation for the further development of powerful WM technologies for comprehensive WM in the following decade.

A modular inverse elastostatics approach to resolve the pressure-induced stress state for in vivo imaging based cardiovascular modeling.

PubMed

Peirlinck, Mathias; De Beule, Matthieu; Segers, Patrick; Rebelo, Nuno

2018-05-28

Patient-specific biomechanical modeling of the cardiovascular system is complicated by the presence of a physiological pressure load given that the imaged tissue is in a pre-stressed and -strained state. Neglect of this prestressed state into solid tissue mechanics models leads to erroneous metrics (e.g. wall deformation, peak stress, wall shear stress) which in their turn are used for device design choices, risk assessment (e.g. procedure, rupture) and surgery planning. It is thus of utmost importance to incorporate this deformed and loaded tissue state into the computational models, which implies solving an inverse problem (calculating an undeformed geometry given the load and the deformed geometry). Methodologies to solve this inverse problem can be categorized into iterative and direct methodologies, both having their inherent advantages and disadvantages. Direct methodologies are typically based on the inverse elastostatics (IE) approach and offer a computationally efficient single shot methodology to compute the in vivo stress state. However, cumbersome and problem-specific derivations of the formulations and non-trivial access to the finite element analysis (FEA) code, especially for commercial products, refrain a broad implementation of these methodologies. For that reason, we developed a novel, modular IE approach and implemented this methodology in a commercial FEA solver with minor user subroutine interventions. The accuracy of this methodology was demonstrated in an arterial tube and porcine biventricular myocardium model. The computational power and efficiency of the methodology was shown by computing the in vivo stress and strain state, and the corresponding unloaded geometry, for two models containing multiple interacting incompressible, anisotropic (fiber-embedded) and hyperelastic material behaviors: a patient-specific abdominal aortic aneurysm and a full 4-chamber heart model. Copyright © 2018 Elsevier Ltd. All rights reserved.

Critical success factors for achieving superior m-health success.

PubMed

Dwivedi, A; Wickramasinghe, N; Bali, R K; Naguib, R N G

2007-01-01

Recent healthcare trends clearly show significant investment by healthcare institutions into various types of wired and wireless technologies to facilitate and support superior healthcare delivery. This trend has been spurred by the shift in the concept and growing importance of the role of health information and the influence of fields such as bio-informatics, biomedical and genetic engineering. The demand is currently for integrated healthcare information systems; however for such initiatives to be successful it is necessary to adopt a macro model and appropriate methodology with respect to wireless initiatives. The key contribution of this paper is the presentation of one such integrative model for mobile health (m-health) known as the Wi-INET Business Model, along with a detailed Adaptive Mapping to Realisation (AMR) methodology. The AMR methodology details how the Wi-INET Business Model can be implemented. Further validation on the concepts detailed in the Wi-INET Business Model and the AMR methodology is offered via a short vignette on a toolkit based on a leading UK-based healthcare information technology solution.

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

PubMed

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

2004-01-01

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

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

NASA Technical Reports Server (NTRS)

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

2004-01-01

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

Model-Based Thermal System Design Optimization for the James Webb Space Telescope

NASA Technical Reports Server (NTRS)

Cataldo, Giuseppe; Niedner, Malcolm B.; Fixsen, Dale J.; Moseley, Samuel H.

2017-01-01

Spacecraft thermal model validation is normally performed by comparing model predictions with thermal test data and reducing their discrepancies to meet the mission requirements. Based on thermal engineering expertise, the model input parameters are adjusted to tune the model output response to the test data. The end result is not guaranteed to be the best solution in terms of reduced discrepancy and the process requires months to complete. A model-based methodology was developed to perform the validation process in a fully automated fashion and provide mathematical bases to the search for the optimal parameter set that minimizes the discrepancies between model and data. The methodology was successfully applied to several thermal subsystems of the James Webb Space Telescope (JWST). Global or quasiglobal optimal solutions were found and the total execution time of the model validation process was reduced to about two weeks. The model sensitivities to the parameters, which are required to solve the optimization problem, can be calculated automatically before the test begins and provide a library for sensitivity studies. This methodology represents a crucial commodity when testing complex, large-scale systems under time and budget constraints. Here, results for the JWST Core thermal system will be presented in detail.

Model-based thermal system design optimization for the James Webb Space Telescope

NASA Astrophysics Data System (ADS)

Cataldo, Giuseppe; Niedner, Malcolm B.; Fixsen, Dale J.; Moseley, Samuel H.

2017-10-01

Spacecraft thermal model validation is normally performed by comparing model predictions with thermal test data and reducing their discrepancies to meet the mission requirements. Based on thermal engineering expertise, the model input parameters are adjusted to tune the model output response to the test data. The end result is not guaranteed to be the best solution in terms of reduced discrepancy and the process requires months to complete. A model-based methodology was developed to perform the validation process in a fully automated fashion and provide mathematical bases to the search for the optimal parameter set that minimizes the discrepancies between model and data. The methodology was successfully applied to several thermal subsystems of the James Webb Space Telescope (JWST). Global or quasiglobal optimal solutions were found and the total execution time of the model validation process was reduced to about two weeks. The model sensitivities to the parameters, which are required to solve the optimization problem, can be calculated automatically before the test begins and provide a library for sensitivity studies. This methodology represents a crucial commodity when testing complex, large-scale systems under time and budget constraints. Here, results for the JWST Core thermal system will be presented in detail.

Surrogate based wind farm layout optimization using manifold mapping

NASA Astrophysics Data System (ADS)

Kaja Kamaludeen, Shaafi M.; van Zuijle, Alexander; Bijl, Hester

2016-09-01

High computational cost associated with the high fidelity wake models such as RANS or LES serves as a primary bottleneck to perform a direct high fidelity wind farm layout optimization (WFLO) using accurate CFD based wake models. Therefore, a surrogate based multi-fidelity WFLO methodology (SWFLO) is proposed. The surrogate model is built using an SBO method referred as manifold mapping (MM). As a verification, optimization of spacing between two staggered wind turbines was performed using the proposed surrogate based methodology and the performance was compared with that of direct optimization using high fidelity model. Significant reduction in computational cost was achieved using MM: a maximum computational cost reduction of 65%, while arriving at the same optima as that of direct high fidelity optimization. The similarity between the response of models, the number of mapping points and its position, highly influences the computational efficiency of the proposed method. As a proof of concept, realistic WFLO of a small 7-turbine wind farm is performed using the proposed surrogate based methodology. Two variants of Jensen wake model with different decay coefficients were used as the fine and coarse model. The proposed SWFLO method arrived at the same optima as that of the fine model with very less number of fine model simulations.

A methodology for least-squares local quasi-geoid modelling using a noisy satellite-only gravity field model

NASA Astrophysics Data System (ADS)

Klees, R.; Slobbe, D. C.; Farahani, H. H.

2018-04-01

The paper is about a methodology to combine a noisy satellite-only global gravity field model (GGM) with other noisy datasets to estimate a local quasi-geoid model using weighted least-squares techniques. In this way, we attempt to improve the quality of the estimated quasi-geoid model and to complement it with a full noise covariance matrix for quality control and further data processing. The methodology goes beyond the classical remove-compute-restore approach, which does not account for the noise in the satellite-only GGM. We suggest and analyse three different approaches of data combination. Two of them are based on a local single-scale spherical radial basis function (SRBF) model of the disturbing potential, and one is based on a two-scale SRBF model. Using numerical experiments, we show that a single-scale SRBF model does not fully exploit the information in the satellite-only GGM. We explain this by a lack of flexibility of a single-scale SRBF model to deal with datasets of significantly different bandwidths. The two-scale SRBF model performs well in this respect, provided that the model coefficients representing the two scales are estimated separately. The corresponding methodology is developed in this paper. Using the statistics of the least-squares residuals and the statistics of the errors in the estimated two-scale quasi-geoid model, we demonstrate that the developed methodology provides a two-scale quasi-geoid model, which exploits the information in all datasets.

Fundamental Algorithms of the Goddard Battery Model

NASA Technical Reports Server (NTRS)

Jagielski, J. M.

1985-01-01

The Goddard Space Flight Center (GSFC) is currently producing a computer model to predict Nickel Cadmium (NiCd) performance in a Low Earth Orbit (LEO) cycling regime. The model proper is currently still in development, but the inherent, fundamental algorithms (or methodologies) of the model are defined. At present, the model is closely dependent on empirical data and the data base currently used is of questionable accuracy. Even so, very good correlations have been determined between model predictions and actual cycling data. A more accurate and encompassing data base has been generated to serve dual functions: show the limitations of the current data base, and be inbred in the model properly for more accurate predictions. The fundamental algorithms of the model, and the present data base and its limitations, are described and a brief preliminary analysis of the new data base and its verification of the model's methodology are presented.

State Analysis Database Tool

NASA Technical Reports Server (NTRS)

Rasmussen, Robert; Bennett, Matthew

2006-01-01

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

System Dynamics Aviation Readiness Modeling Demonstration

DTIC Science & Technology

2005-08-31

requirements. It is recommended that the Naval Aviation Enterprise take a close look at the requirements i.e., performance measures, methodology ...unit’s capability to perform specific Joint Mission Essential Task List (JMETL) requirements now and in the future. This assessment methodology must...the time-associated costs. The new methodology must base decisions on currently available data and databases. A “useful” readiness model should be

Methodology for Physics and Engineering of Reliable Products

NASA Technical Reports Server (NTRS)

Cornford, Steven L.; Gibbel, Mark

1996-01-01

Physics of failure approaches have gained wide spread acceptance within the electronic reliability community. These methodologies involve identifying root cause failure mechanisms, developing associated models, and utilizing these models to inprove time to market, lower development and build costs and higher reliability. The methodology outlined herein sets forth a process, based on integration of both physics and engineering principles, for achieving the same goals.

An improved approach for flight readiness certification: Probabilistic models for flaw propagation and turbine blade failure. Volume 2: Software documentation

NASA Technical Reports Server (NTRS)

Moore, N. R.; Ebbeler, D. H.; Newlin, L. E.; Sutharshana, S.; Creager, M.

1992-01-01

An improved methodology for quantitatively evaluating failure risk of spaceflights systems to assess flight readiness and identify risk control measures is presented. This methodology, called Probabilistic Failure Assessment (PFA), combines operating experience from tests and flights with analytical modeling of failure phenomena to estimate failure risk. The PFA methodology is of particular value when information on which to base an assessment of failure risk, including test experience and knowledge of parameters used in analytical modeling, is expensive or difficult to acquire. The PFA methodology is a prescribed statistical structure in which analytical models that characterize failure phenomena are used conjointly with uncertainties about analysis parameters and/or modeling accuracy to estimate failure probability distributions for specific failure modes. These distributions can then be modified, by means of statistical procedures of the PFA methodology, to reflect any test or flight experience. State-of-the-art analytical models currently employed for design, failure prediction, or performance analysis are used in this methodology. The rationale for the statistical approach taken in the PFA methodology is discussed, the PFA methodology is described, and examples of its application to structural failure modes are presented. The engineering models and computer software used in fatigue crack growth and fatigue crack initiation applications are thoroughly documented.

Enhancing the Front-End Phase of Design Methodology

ERIC Educational Resources Information Center

Elias, Erasto

2006-01-01

Design methodology (DM) is defined by the procedural path, expressed in design models, and techniques or methods used to untangle the various activities within a design model. Design education in universities is mainly based on descriptive design models. Much knowledge and organization have been built into DM to facilitate design teaching.…

A Model-based Prognostics Methodology for Electrolytic Capacitors Based on Electrical Overstress Accelerated Aging

NASA Technical Reports Server (NTRS)

Celaya, Jose; Kulkarni, Chetan; Biswas, Gautam; Saha, Sankalita; Goebel, Kai

2011-01-01

A remaining useful life prediction methodology for electrolytic capacitors is presented. This methodology is based on the Kalman filter framework and an empirical degradation model. Electrolytic capacitors are used in several applications ranging from power supplies on critical avionics equipment to power drivers for electro-mechanical actuators. These devices are known for their comparatively low reliability and given their criticality in electronics subsystems they are a good candidate for component level prognostics and health management. Prognostics provides a way to assess remaining useful life of a capacitor based on its current state of health and its anticipated future usage and operational conditions. We present here also, experimental results of an accelerated aging test under electrical stresses. The data obtained in this test form the basis for a remaining life prediction algorithm where a model of the degradation process is suggested. This preliminary remaining life prediction algorithm serves as a demonstration of how prognostics methodologies could be used for electrolytic capacitors. In addition, the use degradation progression data from accelerated aging, provides an avenue for validation of applications of the Kalman filter based prognostics methods typically used for remaining useful life predictions in other applications.

Towards A Model-Based Prognostics Methodology for Electrolytic Capacitors: A Case Study Based on Electrical Overstress Accelerated Aging

NASA Technical Reports Server (NTRS)

Celaya, Jose R.; Kulkarni, Chetan S.; Biswas, Gautam; Goebel, Kai

2012-01-01

A remaining useful life prediction methodology for electrolytic capacitors is presented. This methodology is based on the Kalman filter framework and an empirical degradation model. Electrolytic capacitors are used in several applications ranging from power supplies on critical avionics equipment to power drivers for electro-mechanical actuators. These devices are known for their comparatively low reliability and given their criticality in electronics subsystems they are a good candidate for component level prognostics and health management. Prognostics provides a way to assess remaining useful life of a capacitor based on its current state of health and its anticipated future usage and operational conditions. We present here also, experimental results of an accelerated aging test under electrical stresses. The data obtained in this test form the basis for a remaining life prediction algorithm where a model of the degradation process is suggested. This preliminary remaining life prediction algorithm serves as a demonstration of how prognostics methodologies could be used for electrolytic capacitors. In addition, the use degradation progression data from accelerated aging, provides an avenue for validation of applications of the Kalman filter based prognostics methods typically used for remaining useful life predictions in other applications.

Optimized planning methodologies of ASON implementation

NASA Astrophysics Data System (ADS)

Zhou, Michael M.; Tamil, Lakshman S.

2005-02-01

Advanced network planning concerns effective network-resource allocation for dynamic and open business environment. Planning methodologies of ASON implementation based on qualitative analysis and mathematical modeling are presented in this paper. The methodology includes method of rationalizing technology and architecture, building network and nodal models, and developing dynamic programming for multi-period deployment. The multi-layered nodal architecture proposed here can accommodate various nodal configurations for a multi-plane optical network and the network modeling presented here computes the required network elements for optimizing resource allocation.

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

DTIC Science & Technology

2011-09-01

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

Methodologies for validating ray-based forward model using finite element method in ultrasonic array data simulation

NASA Astrophysics Data System (ADS)

Zhang, Jie; Nixon, Andrew; Barber, Tom; Budyn, Nicolas; Bevan, Rhodri; Croxford, Anthony; Wilcox, Paul

2018-04-01

In this paper, a methodology of using finite element (FE) model to validate a ray-based model in the simulation of full matrix capture (FMC) ultrasonic array data set is proposed. The overall aim is to separate signal contributions from different interactions in FE results for easier comparing each individual component in the ray-based model results. This is achieved by combining the results from multiple FE models of the system of interest that include progressively more geometrical features while preserving the same mesh structure. It is shown that the proposed techniques allow the interactions from a large number of different ray-paths to be isolated in FE results and compared directly to the results from a ray-based forward model.

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

PubMed

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

2016-12-22

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

Developing Army Leaders through Increased Rigor in Professional Military Training and Education

DTIC Science & Technology

2017-06-09

leadership. Research Methodology An applied, exploratory, qualitative research methodology via a structured and focused case study comparison was...research methodology via a structured and focused case study comparison. Finally, it will discuss how the methodology will be conducted to make...development models; it serves as the base data for case study comparison. 48 Research Methodology and Data Analysis A qualitative research

An object-oriented approach to risk and reliability analysis : methodology and aviation safety applications.

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

Dandini, Vincent John; Duran, Felicia Angelica; Wyss, Gregory Dane

2003-09-01

This article describes how features of event tree analysis and Monte Carlo-based discrete event simulation can be combined with concepts from object-oriented analysis to develop a new risk assessment methodology, with some of the best features of each. The resultant object-based event scenario tree (OBEST) methodology enables an analyst to rapidly construct realistic models for scenarios for which an a priori discovery of event ordering is either cumbersome or impossible. Each scenario produced by OBEST is automatically associated with a likelihood estimate because probabilistic branching is integral to the object model definition. The OBEST methodology is then applied to anmore » aviation safety problem that considers mechanisms by which an aircraft might become involved in a runway incursion incident. The resulting OBEST model demonstrates how a close link between human reliability analysis and probabilistic risk assessment methods can provide important insights into aviation safety phenomenology.« less

Using semantic data modeling techniques to organize an object-oriented database for extending the mass storage model

NASA Technical Reports Server (NTRS)

Campbell, William J.; Short, Nicholas M., Jr.; Roelofs, Larry H.; Dorfman, Erik

1991-01-01

A methodology for optimizing organization of data obtained by NASA earth and space missions is discussed. The methodology uses a concept based on semantic data modeling techniques implemented in a hierarchical storage model. The modeling is used to organize objects in mass storage devices, relational database systems, and object-oriented databases. The semantic data modeling at the metadata record level is examined, including the simulation of a knowledge base and semantic metadata storage issues. The semantic data model hierarchy and its application for efficient data storage is addressed, as is the mapping of the application structure to the mass storage.

Electronic Health Management

NASA Technical Reports Server (NTRS)

Celaya, Jose R.; Saha, Sankalita; Goebel, Kai

2011-01-01

Accelerated aging methodologies for electrolytic components have been designed and accelerated aging experiments have been carried out. The methodology is based on imposing electrical and/or thermal overstresses via electrical power cycling in order to mimic the real world operation behavior. Data are collected in-situ and offline in order to periodically characterize the devices' electrical performance as it ages. The data generated through these experiments are meant to provide capability for the validation of prognostic algorithms (both model-based and data-driven). Furthermore, the data allow validation of physics-based and empirical based degradation models for this type of capacitor. A first set of models and algorithms has been designed and tested on the data.

Climate Model Diagnostic Analyzer Web Service System

NASA Astrophysics Data System (ADS)

Lee, S.; Pan, L.; Zhai, C.; Tang, B.; Kubar, T. L.; Li, J.; Zhang, J.; Wang, W.

2015-12-01

Both the National Research Council Decadal Survey and the latest Intergovernmental Panel on Climate Change Assessment Report stressed the need for the comprehensive and innovative evaluation of climate models with the synergistic use of global satellite observations in order to improve our weather and climate simulation and prediction capabilities. The abundance of satellite observations for fundamental climate parameters and the availability of coordinated model outputs from CMIP5 for the same parameters offer a great opportunity to understand and diagnose model biases in climate models. In addition, the Obs4MIPs efforts have created several key global observational datasets that are readily usable for model evaluations. However, a model diagnostic evaluation process requires physics-based multi-variable comparisons that typically involve large-volume and heterogeneous datasets, making them both computationally- and data-intensive. In response, we have developed a novel methodology to diagnose model biases in contemporary climate models and implementing the methodology as a web-service based, cloud-enabled, provenance-supported climate-model evaluation system. The evaluation system is named Climate Model Diagnostic Analyzer (CMDA), which is the product of the research and technology development investments of several current and past NASA ROSES programs. The current technologies and infrastructure of CMDA are designed and selected to address several technical challenges that the Earth science modeling and model analysis community faces in evaluating and diagnosing climate models. In particular, we have three key technology components: (1) diagnostic analysis methodology; (2) web-service based, cloud-enabled technology; (3) provenance-supported technology. The diagnostic analysis methodology includes random forest feature importance ranking, conditional probability distribution function, conditional sampling, and time-lagged correlation map. We have implemented the new methodology as web services and incorporated the system into the Cloud. We have also developed a provenance management system for CMDA where CMDA service semantics modeling, service search and recommendation, and service execution history management are designed and implemented.

Extended cooperative control synthesis

NASA Technical Reports Server (NTRS)

Davidson, John B.; Schmidt, David K.

1994-01-01

This paper reports on research for extending the Cooperative Control Synthesis methodology to include a more accurate modeling of the pilot's controller dynamics. Cooperative Control Synthesis (CCS) is a methodology that addresses the problem of how to design control laws for piloted, high-order, multivariate systems and/or non-conventional dynamic configurations in the absence of flying qualities specifications. This is accomplished by emphasizing the parallel structure inherent in any pilot-controlled, augmented vehicle. The original CCS methodology is extended to include the Modified Optimal Control Model (MOCM), which is based upon the optimal control model of the human operator developed by Kleinman, Baron, and Levison in 1970. This model provides a modeling of the pilot's compensation dynamics that is more accurate than the simplified pilot dynamic representation currently in the CCS methodology. Inclusion of the MOCM into the CCS also enables the modeling of pilot-observation perception thresholds and pilot-observation attention allocation affects. This Extended Cooperative Control Synthesis (ECCS) allows for the direct calculation of pilot and system open- and closed-loop transfer functions in pole/zero form and is readily implemented in current software capable of analysis and design for dynamic systems. Example results based upon synthesizing an augmentation control law for an acceleration command system in a compensatory tracking task using the ECCS are compared with a similar synthesis performed by using the original CCS methodology. The ECCS is shown to provide augmentation control laws that yield more favorable, predicted closed-loop flying qualities and tracking performance than those synthesized using the original CCS methodology.

Extended Axiomatic Conjoint Measurement: A Solution to a Methodological Problem in Studying Fertility-Related Behaviors.

ERIC Educational Resources Information Center

Nickerson, Carol A.; McClelland, Gary H.

1988-01-01

A methodology is developed based on axiomatic conjoint measurement to accompany a fertility decision-making model. The usefulness of the model is then demonstrated via an application to a study of contraceptive choice (N=100 male and female family-planning clinic clients). Finally, the validity of the model is evaluated. (TJH)

Developing a stochastic conflict resolution model for urban runoff quality management: Application of info-gap and bargaining theories

NASA Astrophysics Data System (ADS)

Ghodsi, Seyed Hamed; Kerachian, Reza; Estalaki, Siamak Malakpour; Nikoo, Mohammad Reza; Zahmatkesh, Zahra

2016-02-01

In this paper, two deterministic and stochastic multilateral, multi-issue, non-cooperative bargaining methodologies are proposed for urban runoff quality management. In the proposed methodologies, a calibrated Storm Water Management Model (SWMM) is used to simulate stormwater runoff quantity and quality for different urban stormwater runoff management scenarios, which have been defined considering several Low Impact Development (LID) techniques. In the deterministic methodology, the best management scenario, representing location and area of LID controls, is identified using the bargaining model. In the stochastic methodology, uncertainties of some key parameters of SWMM are analyzed using the info-gap theory. For each water quality management scenario, robustness and opportuneness criteria are determined based on utility functions of different stakeholders. Then, to find the best solution, the bargaining model is performed considering a combination of robustness and opportuneness criteria for each scenario based on utility function of each stakeholder. The results of applying the proposed methodology in the Velenjak urban watershed located in the northeastern part of Tehran, the capital city of Iran, illustrate its practical utility for conflict resolution in urban water quantity and quality management. It is shown that the solution obtained using the deterministic model cannot outperform the result of the stochastic model considering the robustness and opportuneness criteria. Therefore, it can be concluded that the stochastic model, which incorporates the main uncertainties, could provide more reliable results.

A Measurement and Simulation Based Methodology for Cache Performance Modeling and Tuning

NASA Technical Reports Server (NTRS)

Waheed, Abdul; Yan, Jerry; Saini, Subhash (Technical Monitor)

1998-01-01

We present a cache performance modeling methodology that facilitates the tuning of uniprocessor cache performance for applications executing on shared memory multiprocessors by accurately predicting the effects of source code level modifications. Measurements on a single processor are initially used for identifying parts of code where cache utilization improvements may significantly impact the overall performance. Cache simulation based on trace-driven techniques can be carried out without gathering detailed address traces. Minimal runtime information for modeling cache performance of a selected code block includes: base virtual addresses of arrays, virtual addresses of variables, and loop bounds for that code block. Rest of the information is obtained from the source code. We show that the cache performance predictions are as reliable as those obtained through trace-driven simulations. This technique is particularly helpful to the exploration of various "what-if' scenarios regarding the cache performance impact for alternative code structures. We explain and validate this methodology using a simple matrix-matrix multiplication program. We then apply this methodology to predict and tune the cache performance of two realistic scientific applications taken from the Computational Fluid Dynamics (CFD) domain.

High-Dimensional Sparse Factor Modeling: Applications in Gene Expression Genomics

PubMed Central

Carvalho, Carlos M.; Chang, Jeffrey; Lucas, Joseph E.; Nevins, Joseph R.; Wang, Quanli; West, Mike

2010-01-01

We describe studies in molecular profiling and biological pathway analysis that use sparse latent factor and regression models for microarray gene expression data. We discuss breast cancer applications and key aspects of the modeling and computational methodology. Our case studies aim to investigate and characterize heterogeneity of structure related to specific oncogenic pathways, as well as links between aggregate patterns in gene expression profiles and clinical biomarkers. Based on the metaphor of statistically derived “factors” as representing biological “subpathway” structure, we explore the decomposition of fitted sparse factor models into pathway subcomponents and investigate how these components overlay multiple aspects of known biological activity. Our methodology is based on sparsity modeling of multivariate regression, ANOVA, and latent factor models, as well as a class of models that combines all components. Hierarchical sparsity priors address questions of dimension reduction and multiple comparisons, as well as scalability of the methodology. The models include practically relevant non-Gaussian/nonparametric components for latent structure, underlying often quite complex non-Gaussianity in multivariate expression patterns. Model search and fitting are addressed through stochastic simulation and evolutionary stochastic search methods that are exemplified in the oncogenic pathway studies. Supplementary supporting material provides more details of the applications, as well as examples of the use of freely available software tools for implementing the methodology. PMID:21218139

A Methodological Review of Structural Equation Modelling in Higher Education Research

ERIC Educational Resources Information Center

Green, Teegan

2016-01-01

Despite increases in the number of articles published in higher education journals using structural equation modelling (SEM), research addressing their statistical sufficiency, methodological appropriateness and quantitative rigour is sparse. In response, this article provides a census of all covariance-based SEM articles published up until 2013…

Methodology Evaluation Framework for Component-Based System Development.

ERIC Educational Resources Information Center

Dahanayake, Ajantha; Sol, Henk; Stojanovic, Zoran

2003-01-01

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

Information security system quality assessment through the intelligent tools

NASA Astrophysics Data System (ADS)

Trapeznikov, E. V.

2018-04-01

The technology development has shown the automated system information security comprehensive analysis necessity. The subject area analysis indicates the study relevance. The research objective is to develop the information security system quality assessment methodology based on the intelligent tools. The basis of the methodology is the information security assessment model in the information system through the neural network. The paper presents the security assessment model, its algorithm. The methodology practical implementation results in the form of the software flow diagram are represented. The practical significance of the model being developed is noted in conclusions.

A Generalizable Methodology for Quantifying User Satisfaction

NASA Astrophysics Data System (ADS)

Huang, Te-Yuan; Chen, Kuan-Ta; Huang, Polly; Lei, Chin-Laung

Quantifying user satisfaction is essential, because the results can help service providers deliver better services. In this work, we propose a generalizable methodology, based on survival analysis, to quantify user satisfaction in terms of session times, i. e., the length of time users stay with an application. Unlike subjective human surveys, our methodology is based solely on passive measurement, which is more cost-efficient and better able to capture subconscious reactions. Furthermore, by using session times, rather than a specific performance indicator, such as the level of distortion of voice signals, the effects of other factors like loudness and sidetone, can also be captured by the developed models. Like survival analysis, our methodology is characterized by low complexity and a simple model-developing process. The feasibility of our methodology is demonstrated through case studies of ShenZhou Online, a commercial MMORPG in Taiwan, and the most prevalent VoIP application in the world, namely Skype. Through the model development process, we can also identify the most significant performance factors and their impacts on user satisfaction and discuss how they can be exploited to improve user experience and optimize resource allocation.

A Computational Efficient Physics Based Methodology for Modeling Ceramic Matrix Composites (Preprint)

DTIC Science & Technology

2011-11-01

elastic range, and with some simple forms of progressing damage . However, a general physics-based methodology to assess the initial and lifetime... damage evolution in the RVE for all possible load histories. Microstructural data on initial configuration and damage progression in CMCs were...the damaged elements will have changed, hence, a progressive damage model. The crack opening for each crack type in each element is stored as a

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

PubMed Central

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

2018-01-01

This paper presents a new optimal data fusion methodology based on the adaptive fading unscented Kalman filter for multi-sensor nonlinear stochastic systems. This methodology has a two-level fusion structure: at the bottom level, an adaptive fading unscented Kalman filter based on the Mahalanobis distance is developed and serves as local filters to improve the adaptability and robustness of local state estimations against process-modeling error; at the top level, an unscented transformation-based multi-sensor optimal data fusion for the case of N local filters is established according to the principle of linear minimum variance to calculate globally optimal state estimation by fusion of local estimations. The proposed methodology effectively refrains from the influence of process-modeling error on the fusion solution, leading to improved adaptability and robustness of data fusion for multi-sensor nonlinear stochastic systems. It also achieves globally optimal fusion results based on the principle of linear minimum variance. Simulation and experimental results demonstrate the efficacy of the proposed methodology for INS/GNSS/CNS (inertial navigation system/global navigation satellite system/celestial navigation system) integrated navigation. PMID:29415509

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

PubMed

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

2018-02-06

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

Infiltration modeling guidelines for commercial building energy analysis

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

Gowri, Krishnan; Winiarski, David W.; Jarnagin, Ronald E.

This report presents a methodology for modeling air infiltration in EnergyPlus to account for envelope air barrier characteristics. Based on a review of various infiltration modeling options available in EnergyPlus and sensitivity analysis, the linear wind velocity coefficient based on DOE-2 infiltration model is recommended. The methodology described in this report can be used to calculate the EnergyPlus infiltration input for any given building level infiltration rate specified at known pressure difference. The sensitivity analysis shows that EnergyPlus calculates the wind speed based on zone altitude, and the linear wind velocity coefficient represents the variation in infiltration heat loss consistentmore » with building location and weather data.« less

Analysis of pressure distortion testing

NASA Technical Reports Server (NTRS)

Koch, K. E.; Rees, R. L.

1976-01-01

The development of a distortion methodology, method D, was documented, and its application to steady state and unsteady data was demonstrated. Three methodologies based upon DIDENT, a NASA-LeRC distortion methodology based upon the parallel compressor model, were investigated by applying them to a set of steady state data. The best formulation was then applied to an independent data set. The good correlation achieved with this data set showed that method E, one of the above methodologies, is a viable concept. Unsteady data were analyzed by using the method E methodology. This analysis pointed out that the method E sensitivities are functions of pressure defect level as well as corrected speed and pattern.

Model identification methodology for fluid-based inerters

NASA Astrophysics Data System (ADS)

Liu, Xiaofu; Jiang, Jason Zheng; Titurus, Branislav; Harrison, Andrew

2018-06-01

Inerter is the mechanical dual of the capacitor via the force-current analogy. It has the property that the force across the terminals is proportional to their relative acceleration. Compared with flywheel-based inerters, fluid-based forms have advantages of improved durability, inherent damping and simplicity of design. In order to improve the understanding of the physical behaviour of this fluid-based device, especially caused by the hydraulic resistance and inertial effects in the external tube, this work proposes a comprehensive model identification methodology. Firstly, a modelling procedure is established, which allows the topological arrangement of the mechanical networks to be obtained by mapping the damping, inertance and stiffness effects directly to their respective hydraulic counterparts. Secondly, an experimental sequence is followed, which separates the identification of friction, stiffness and various damping effects. Furthermore, an experimental set-up is introduced, where two pressure gauges are used to accurately measure the pressure drop across the external tube. The theoretical models with improved confidence are obtained using the proposed methodology for a helical-tube fluid inerter prototype. The sources of remaining discrepancies are further analysed.

A Methodology for Calculating EGS Electricity Generation Potential Based on the Gringarten Model for Heat Extraction From Fractured Rock

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

Augustine, Chad

Existing methodologies for estimating the electricity generation potential of Enhanced Geothermal Systems (EGS) assume thermal recovery factors of 5% or less, resulting in relatively low volumetric electricity generation potentials for EGS reservoirs. This study proposes and develops a methodology for calculating EGS electricity generation potential based on the Gringarten conceptual model and analytical solution for heat extraction from fractured rock. The electricity generation potential of a cubic kilometer of rock as a function of temperature is calculated assuming limits on the allowed produced water temperature decline and reservoir lifetime based on surface power plant constraints. The resulting estimates of EGSmore » electricity generation potential can be one to nearly two-orders of magnitude larger than those from existing methodologies. The flow per unit fracture surface area from the Gringarten solution is found to be a key term in describing the conceptual reservoir behavior. The methodology can be applied to aid in the design of EGS reservoirs by giving minimum reservoir volume, fracture spacing, number of fractures, and flow requirements for a target reservoir power output. Limitations of the idealized model compared to actual reservoir performance and the implications on reservoir design are discussed.« less

Transaction based approach

NASA Astrophysics Data System (ADS)

Hunka, Frantisek; Matula, Jiri

2017-07-01

Transaction based approach is utilized in some methodologies in business process modeling. Essential parts of these transactions are human beings. The notion of agent or actor role is usually used for them. The paper on a particular example describes possibilities of Design Engineering Methodology for Organizations (DEMO) and Resource-Event-Agent (REA) methodology. Whereas the DEMO methodology can be regarded as a generic methodology having its foundation in the theory of Enterprise Ontology the REA methodology is regarded as the domain specific methodology and has its origin in accountancy systems. The results of these approaches is that the DEMO methodology captures everything that happens in the reality with a good empirical evidence whereas the REA methodology captures only changes connected with economic events. Economic events represent either change of the property rights to economic resource or consumption or production of economic resources. This results from the essence of economic events and their connection to economic resources.

Kalman approach to accuracy management for interoperable heterogeneous model abstraction within an HLA-compliant simulation

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.

Model-Based Economic Evaluation of Treatments for Depression: A Systematic Literature Review.

PubMed

Kolovos, Spyros; Bosmans, Judith E; Riper, Heleen; Chevreul, Karine; Coupé, Veerle M H; van Tulder, Maurits W

2017-09-01

An increasing number of model-based studies that evaluate the cost effectiveness of treatments for depression are being published. These studies have different characteristics and use different simulation methods. We aimed to systematically review model-based studies evaluating the cost effectiveness of treatments for depression and examine which modelling technique is most appropriate for simulating the natural course of depression. The literature search was conducted in the databases PubMed, EMBASE and PsycInfo between 1 January 2002 and 1 October 2016. Studies were eligible if they used a health economic model with quality-adjusted life-years or disability-adjusted life-years as an outcome measure. Data related to various methodological characteristics were extracted from the included studies. The available modelling techniques were evaluated based on 11 predefined criteria. This methodological review included 41 model-based studies, of which 21 used decision trees (DTs), 15 used cohort-based state-transition Markov models (CMMs), two used individual-based state-transition models (ISMs), and three used discrete-event simulation (DES) models. Just over half of the studies (54%) evaluated antidepressants compared with a control condition. The data sources, time horizons, cycle lengths, perspectives adopted and number of health states/events all varied widely between the included studies. DTs scored positively in four of the 11 criteria, CMMs in five, ISMs in six, and DES models in seven. There were substantial methodological differences between the studies. Since the individual history of each patient is important for the prognosis of depression, DES and ISM simulation methods may be more appropriate than the others for a pragmatic representation of the course of depression. However, direct comparisons between the available modelling techniques are necessary to yield firm conclusions.

Impact of computational structure-based methods on drug discovery.

PubMed

Reynolds, Charles H

2014-01-01

Structure-based drug design has become an indispensible tool in drug discovery. The emergence of structure-based design is due to gains in structural biology that have provided exponential growth in the number of protein crystal structures, new computational algorithms and approaches for modeling protein-ligand interactions, and the tremendous growth of raw computer power in the last 30 years. Computer modeling and simulation have made major contributions to the discovery of many groundbreaking drugs in recent years. Examples are presented that highlight the evolution of computational structure-based design methodology, and the impact of that methodology on drug discovery.

A Methodology for Modeling Nuclear Power Plant Passive Component Aging in Probabilistic Risk Assessment under the Impact of Operating Conditions, Surveillance and Maintenance Activities

NASA Astrophysics Data System (ADS)

Guler Yigitoglu, Askin

In the context of long operation of nuclear power plants (NPPs) (i.e., 60-80 years, and beyond), investigation of the aging of passive systems, structures and components (SSCs) is important to assess safety margins and to decide on reactor life extension as indicated within the U.S. Department of Energy (DOE) Light Water Reactor Sustainability (LWRS) Program. In the traditional probabilistic risk assessment (PRA) methodology, evaluating the potential significance of aging of passive SSCs on plant risk is challenging. Although passive SSC failure rates can be added as initiating event frequencies or basic event failure rates in the traditional event-tree/fault-tree methodology, these failure rates are generally based on generic plant failure data which means that the true state of a specific plant is not reflected in a realistic manner on aging effects. Dynamic PRA methodologies have gained attention recently due to their capability to account for the plant state and thus address the difficulties in the traditional PRA modeling of aging effects of passive components using physics-based models (and also in the modeling of digital instrumentation and control systems). Physics-based models can capture the impact of complex aging processes (e.g., fatigue, stress corrosion cracking, flow-accelerated corrosion, etc.) on SSCs and can be utilized to estimate passive SSC failure rates using realistic NPP data from reactor simulation, as well as considering effects of surveillance and maintenance activities. The objectives of this dissertation are twofold: The development of a methodology for the incorporation of aging modeling of passive SSC into a reactor simulation environment to provide a framework for evaluation of their risk contribution in both the dynamic and traditional PRA; and the demonstration of the methodology through its application to pressurizer surge line pipe weld and steam generator tubes in commercial nuclear power plants. In the proposed methodology, a multi-state physics based model is selected to represent the aging process. The model is modified via sojourn time approach to reflect the operational and maintenance history dependence of the transition rates. Thermal-hydraulic parameters of the model are calculated via the reactor simulation environment and uncertainties associated with both parameters and the models are assessed via a two-loop Monte Carlo approach (Latin hypercube sampling) to propagate input probability distributions through the physical model. The effort documented in this thesis towards this overall objective consists of : i) defining a process for selecting critical passive components and related aging mechanisms, ii) aging model selection, iii) calculating the probability that aging would cause the component to fail, iv) uncertainty/sensitivity analyses, v) procedure development for modifying an existing PRA to accommodate consideration of passive component failures, and, vi) including the calculated failure probability in the modified PRA. The proposed methodology is applied to pressurizer surge line pipe weld aging and steam generator tube degradation in pressurized water reactors.

Local deformation for soft tissue simulation

PubMed Central

Omar, Nadzeri; Zhong, Yongmin; Smith, Julian; Gu, Chengfan

2016-01-01

ABSTRACT This paper presents a new methodology to localize the deformation range to improve the computational efficiency for soft tissue simulation. This methodology identifies the local deformation range from the stress distribution in soft tissues due to an external force. A stress estimation method is used based on elastic theory to estimate the stress in soft tissues according to a depth from the contact surface. The proposed methodology can be used with both mass-spring and finite element modeling approaches for soft tissue deformation. Experimental results show that the proposed methodology can improve the computational efficiency while maintaining the modeling realism. PMID:27286482

On the development of a new methodology in sub-surface parameterisation on the calibration of groundwater models

NASA Astrophysics Data System (ADS)

Klaas, D. K. S. Y.; Imteaz, M. A.; Sudiayem, I.; Klaas, E. M. E.; Klaas, E. C. M.

2017-10-01

In groundwater modelling, robust parameterisation of sub-surface parameters is crucial towards obtaining an agreeable model performance. Pilot point is an alternative in parameterisation step to correctly configure the distribution of parameters into a model. However, the methodology given by the current studies are considered less practical to be applied on real catchment conditions. In this study, a practical approach of using geometric features of pilot point and distribution of hydraulic gradient over the catchment area is proposed to efficiently configure pilot point distribution in the calibration step of a groundwater model. A development of new pilot point distribution, Head Zonation-based (HZB) technique, which is based on the hydraulic gradient distribution of groundwater flow, is presented. Seven models of seven zone ratios (1, 5, 10, 15, 20, 25 and 30) using HZB technique were constructed on an eogenetic karst catchment in Rote Island, Indonesia and their performances were assessed. This study also concludes some insights into the trade-off between restricting and maximising the number of pilot points and offers a new methodology for selecting pilot point properties and distribution method in the development of a physically-based groundwater model.

An improved approach for flight readiness certification: Methodology for failure risk assessment and application examples. Volume 2: Software documentation

NASA Technical Reports Server (NTRS)

Moore, N. R.; Ebbeler, D. H.; Newlin, L. E.; Sutharshana, S.; Creager, M.

1992-01-01

An improved methodology for quantitatively evaluating failure risk of spaceflight systems to assess flight readiness and identify risk control measures is presented. This methodology, called Probabilistic Failure Assessment (PFA), combines operating experience from tests and flights with engineering analysis to estimate failure risk. The PFA methodology is of particular value when information on which to base an assessment of failure risk, including test experience and knowledge of parameters used in engineering analyses of failure phenomena, is expensive or difficult to acquire. The PFA methodology is a prescribed statistical structure in which engineering analysis models that characterize failure phenomena are used conjointly with uncertainties about analysis parameters and/or modeling accuracy to estimate failure probability distributions for specific failure modes, These distributions can then be modified, by means of statistical procedures of the PFA methodology, to reflect any test or flight experience. Conventional engineering analysis models currently employed for design of failure prediction are used in this methodology. The PFA methodology is described and examples of its application are presented. Conventional approaches to failure risk evaluation for spaceflight systems are discussed, and the rationale for the approach taken in the PFA methodology is presented. The statistical methods, engineering models, and computer software used in fatigue failure mode applications are thoroughly documented.

An improved approach for flight readiness certification: Methodology for failure risk assessment and application examples, volume 1

NASA Technical Reports Server (NTRS)

Moore, N. R.; Ebbeler, D. H.; Newlin, L. E.; Sutharshana, S.; Creager, M.

1992-01-01

An improved methodology for quantitatively evaluating failure risk of spaceflight systems to assess flight readiness and identify risk control measures is presented. This methodology, called Probabilistic Failure Assessment (PFA), combines operating experience from tests and flights with engineering analysis to estimate failure risk. The PFA methodology is of particular value when information on which to base an assessment of failure risk, including test experience and knowledge of parameters used in engineering analyses of failure phenomena, is expensive or difficult to acquire. The PFA methodology is a prescribed statistical structure in which engineering analysis models that characterize failure phenomena are used conjointly with uncertainties about analysis parameters and/or modeling accuracy to estimate failure probability distributions for specific failure modes. These distributions can then be modified, by means of statistical procedures of the PFA methodology, to reflect any test or flight experience. Conventional engineering analysis models currently employed for design of failure prediction are used in this methodology. The PFA methodology is described and examples of its application are presented. Conventional approaches to failure risk evaluation for spaceflight systems are discussed, and the rationale for the approach taken in the PFA methodology is presented. The statistical methods, engineering models, and computer software used in fatigue failure mode applications are thoroughly documented.

Integral Methodological Pluralism in Science Education Research: Valuing Multiple Perspectives

ERIC Educational Resources Information Center

Davis, Nancy T.; Callihan, Laurie P.

2013-01-01

This article examines the multiple methodologies used in educational research and proposes a model that includes all of them as contributing to understanding educational contexts and research from multiple perspectives. The model, based on integral theory (Wilber in a theory of everything. Shambhala, Boston, 2000) values all forms of research as…

Intelligent tutoring systems for systems engineering methodologies

NASA Technical Reports Server (NTRS)

Meyer, Richard J.; Toland, Joel; Decker, Louis

1991-01-01

The general goal is to provide the technology required to build systems that can provide intelligent tutoring in IDEF (Integrated Computer Aided Manufacturing Definition Method) modeling. The following subject areas are covered: intelligent tutoring systems for systems analysis methodologies; IDEF tutor architecture and components; developing cognitive skills for IDEF modeling; experimental software; and PC based prototype.

A Synthesis of a Quality Management Model for Education in Universities

ERIC Educational Resources Information Center

Srikanthan, G.; Dalrymple, John

2004-01-01

The paper attempts to synthesise the features of the model for quality management in education based on the approaches spelt out in four well-articulated methodologies for the practice of quality in higher education. Each methodology contributes to different views of education from the learners' and the institution's perspectives, providing…

Analysis of Feedback Processes in Online Group Interaction: A Methodological Model

ERIC Educational Resources Information Center

Espasa, Anna; Guasch, Teresa; Alvarez, Ibis M.

2013-01-01

The aim of this article is to present a methodological model to analyze students' group interaction to improve their essays in online learning environments, based on asynchronous and written communication. In these environments teacher and student scaffolds for discussion are essential to promote interaction. One of these scaffolds can be the…

Deciphering the complex: methodological overview of statistical models to derive OMICS-based biomarkers.

PubMed

Chadeau-Hyam, Marc; Campanella, Gianluca; Jombart, Thibaut; Bottolo, Leonardo; Portengen, Lutzen; Vineis, Paolo; Liquet, Benoit; Vermeulen, Roel C H

2013-08-01

Recent technological advances in molecular biology have given rise to numerous large-scale datasets whose analysis imposes serious methodological challenges mainly relating to the size and complex structure of the data. Considerable experience in analyzing such data has been gained over the past decade, mainly in genetics, from the Genome-Wide Association Study era, and more recently in transcriptomics and metabolomics. Building upon the corresponding literature, we provide here a nontechnical overview of well-established methods used to analyze OMICS data within three main types of regression-based approaches: univariate models including multiple testing correction strategies, dimension reduction techniques, and variable selection models. Our methodological description focuses on methods for which ready-to-use implementations are available. We describe the main underlying assumptions, the main features, and advantages and limitations of each of the models. This descriptive summary constitutes a useful tool for driving methodological choices while analyzing OMICS data, especially in environmental epidemiology, where the emergence of the exposome concept clearly calls for unified methods to analyze marginally and jointly complex exposure and OMICS datasets. Copyright © 2013 Wiley Periodicals, Inc.

Students' and Teachers' Perceptions: Initial Achievements of a Project-Based Engineering School

ERIC Educational Resources Information Center

Terrón-López, María-José; Velasco-Quintana, Paloma-Julia; García-García, María-José; Ocampo, Jared R.

2017-01-01

A unified academic model based on the project-based learning (PBL) methodology was implemented, in the 2012-2013 period, in the School of Engineering at Universidad Europea de Madrid. The purpose of this paper is to explore whether teachers and students participating in the capstone projects feel that the objectives for which this methodology was…

A methodology and supply chain management inspired reference ontology for modeling healthcare teams.

PubMed

Kuziemsky, Craig E; Yazdi, Sara

2011-01-01

Numerous studies and strategic plans are advocating more team based healthcare delivery that is facilitated by information and communication technologies (ICTs). However before we can design ICTs to support teams we need a solid conceptual model of team processes and a methodology for using such a model in healthcare settings. This paper draws upon success in the supply chain management domain to develop a reference ontology of healthcare teams and a methodology for modeling teams to instantiate the ontology in specific settings. This research can help us understand how teams function and how we can design ICTs to support teams.

Spanish methodological approach for biosphere assessment of radioactive waste disposal.

PubMed

Agüero, A; Pinedo, P; Cancio, D; Simón, I; Moraleda, M; Pérez-Sánchez, D; Trueba, C

2007-10-01

The development of radioactive waste disposal facilities requires implementation of measures that will afford protection of human health and the environment over a specific temporal frame that depends on the characteristics of the wastes. The repository design is based on a multi-barrier system: (i) the near-field or engineered barrier, (ii) far-field or geological barrier and (iii) the biosphere system. Here, the focus is on the analysis of this last system, the biosphere. A description is provided of conceptual developments, methodological aspects and software tools used to develop the Biosphere Assessment Methodology in the context of high-level waste (HLW) disposal facilities in Spain. This methodology is based on the BIOMASS "Reference Biospheres Methodology" and provides a logical and systematic approach with supplementary documentation that helps to support the decisions necessary for model development. It follows a five-stage approach, such that a coherent biosphere system description and the corresponding conceptual, mathematical and numerical models can be built. A discussion on the improvements implemented through application of the methodology to case studies in international and national projects is included. Some facets of this methodological approach still require further consideration, principally an enhanced integration of climatology, geography and ecology into models considering evolution of the environment, some aspects of the interface between the geosphere and biosphere, and an accurate quantification of environmental change processes and rates.

Evaluative methodology for comprehensive water quality management planning

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

Dyer, H. L.

Computer-based evaluative methodologies have been developed to provide for the analysis of coupled phenomena associated with natural resource comprehensive planning requirements. Provisions for planner/computer interaction have been included. Each of the simulation models developed is described in terms of its coded procedures. An application of the models for water quality management planning is presented; and the data requirements for each of the models are noted.

A Physics-Based Approach for Power Integrity in Multi-Layered PCBs

NASA Astrophysics Data System (ADS)

Zhao, Biyao

Developing a power distribution network (PDN) for ASICs and ICs to achieve the low-voltage ripple specifications for current digital designs is challenging with the high-speed and low-voltage ICs. Present methods are typically guided by best engineering practices for low impedance looking into the PDN from the IC. A pre-layout design methodology for power integrity in multi-layered PCB PDN geometry is proposed in the thesis. The PCB PDN geometry is segmented into four parts and every part is modelled using different methods based on the geometry details of the part. Physics-based circuit models are built for every part and the four parts are re-assembled into one model. The influence of geometry details is clearly revealed in this methodology. Based on the physics-based circuit mode, the procedures of using the pre-layout design methodology as a guideline during the PDN design is illustrated. Some common used geometries are used to build design space, and the design curves with the geometry details are provided to be a look up library for engineering use. The pre-layout methodology is based on the resonant cavity model of parallel planes for the cavity structures, and parallel-plane PEEC (PPP) for the irregular shaped plane inductance, and PEEC for the decoupling capacitor connection above the top most or bottom most power-return planes. PCB PDN is analyzed based on the input impedance looking into the PCB from the IC. The pre-layout design methodology can be used to obtain the best possible PCB PDN design. With the switching current profile, the target impedance can be selected to evaluate the PDN performance, and the frequency domain PDN input impedance can be used to obtain the voltage ripple in the time domain to give intuitive insight of the geometry impact on the voltage ripple.

A 3D model retrieval approach based on Bayesian networks lightfield descriptor

NASA Astrophysics Data System (ADS)

Xiao, Qinhan; Li, Yanjun

2009-12-01

A new 3D model retrieval methodology is proposed by exploiting a novel Bayesian networks lightfield descriptor (BNLD). There are two key novelties in our approach: (1) a BN-based method for building lightfield descriptor; and (2) a 3D model retrieval scheme based on the proposed BNLD. To overcome the disadvantages of the existing 3D model retrieval methods, we explore BN for building a new lightfield descriptor. Firstly, 3D model is put into lightfield, about 300 binary-views can be obtained along a sphere, then Fourier descriptors and Zernike moments descriptors can be calculated out from binaryviews. Then shape feature sequence would be learned into a BN model based on BN learning algorithm; Secondly, we propose a new 3D model retrieval method by calculating Kullback-Leibler Divergence (KLD) between BNLDs. Beneficial from the statistical learning, our BNLD is noise robustness as compared to the existing methods. The comparison between our method and the lightfield descriptor-based approach is conducted to demonstrate the effectiveness of our proposed methodology.

Sharing on Web 3d Models of Ancient Theatres. a Methodological Workflow

NASA Astrophysics Data System (ADS)

Scianna, A.; La Guardia, M.; Scaduto, M. L.

2016-06-01

In the last few years, the need to share on the Web the knowledge of Cultural Heritage (CH) through navigable 3D models has increased. This need requires the availability of Web-based virtual reality systems and 3D WEBGIS. In order to make the information available to all stakeholders, these instruments should be powerful and at the same time very user-friendly. However, research and experiments carried out so far show that a standardized methodology doesn't exist. All this is due both to complexity and dimensions of geometric models to be published, on the one hand, and to excessive costs of hardware and software tools, on the other. In light of this background, the paper describes a methodological approach for creating 3D models of CH, freely exportable on the Web, based on HTML5 and free and open source software. HTML5, supporting the WebGL standard, allows the exploration of 3D spatial models using most used Web browsers like Chrome, Firefox, Safari, Internet Explorer. The methodological workflow here described has been tested for the construction of a multimedia geo-spatial platform developed for three-dimensional exploration and documentation of the ancient theatres of Segesta and of Carthage, and the surrounding landscapes. The experimental application has allowed us to explore the potential and limitations of sharing on the Web of 3D CH models based on WebGL standard. Sharing capabilities could be extended defining suitable geospatial Web-services based on capabilities of HTML5 and WebGL technology.

Improved workflow modelling using role activity diagram-based modelling with application to a radiology service case study.

PubMed

Shukla, Nagesh; Keast, John E; Ceglarek, Darek

2014-10-01

The modelling of complex workflows is an important problem-solving technique within healthcare settings. However, currently most of the workflow models use a simplified flow chart of patient flow obtained using on-site observations, group-based debates and brainstorming sessions, together with historic patient data. This paper presents a systematic and semi-automatic methodology for knowledge acquisition with detailed process representation using sequential interviews of people in the key roles involved in the service delivery process. The proposed methodology allows the modelling of roles, interactions, actions, and decisions involved in the service delivery process. This approach is based on protocol generation and analysis techniques such as: (i) initial protocol generation based on qualitative interviews of radiology staff, (ii) extraction of key features of the service delivery process, (iii) discovering the relationships among the key features extracted, and, (iv) a graphical representation of the final structured model of the service delivery process. The methodology is demonstrated through a case study of a magnetic resonance (MR) scanning service-delivery process in the radiology department of a large hospital. A set of guidelines is also presented in this paper to visually analyze the resulting process model for identifying process vulnerabilities. A comparative analysis of different workflow models is also conducted. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

A methodology for the rigorous verification of plasma simulation codes

NASA Astrophysics Data System (ADS)

Riva, Fabio

2016-10-01

The methodology used to assess the reliability of numerical simulation codes constitutes the Verification and Validation (V&V) procedure. V&V is composed by two separate tasks: the verification, which is a mathematical issue targeted to assess that the physical model is correctly solved, and the validation, which determines the consistency of the code results, and therefore of the physical model, with experimental data. In the present talk we focus our attention on the verification, which in turn is composed by the code verification, targeted to assess that a physical model is correctly implemented in a simulation code, and the solution verification, that quantifies the numerical error affecting a simulation. Bridging the gap between plasma physics and other scientific domains, we introduced for the first time in our domain a rigorous methodology for the code verification, based on the method of manufactured solutions, as well as a solution verification based on the Richardson extrapolation. This methodology was applied to GBS, a three-dimensional fluid code based on a finite difference scheme, used to investigate the plasma turbulence in basic plasma physics experiments and in the tokamak scrape-off layer. Overcoming the difficulty of dealing with a numerical method intrinsically affected by statistical noise, we have now generalized the rigorous verification methodology to simulation codes based on the particle-in-cell algorithm, which are employed to solve Vlasov equation in the investigation of a number of plasma physics phenomena.

Developing a methodology to predict PM10 concentrations in urban areas using generalized linear models.

PubMed

Garcia, J M; Teodoro, F; Cerdeira, R; Coelho, L M R; Kumar, Prashant; Carvalho, M G

2016-09-01

A methodology to predict PM10 concentrations in urban outdoor environments is developed based on the generalized linear models (GLMs). The methodology is based on the relationship developed between atmospheric concentrations of air pollutants (i.e. CO, NO2, NOx, VOCs, SO2) and meteorological variables (i.e. ambient temperature, relative humidity (RH) and wind speed) for a city (Barreiro) of Portugal. The model uses air pollution and meteorological data from the Portuguese monitoring air quality station networks. The developed GLM considers PM10 concentrations as a dependent variable, and both the gaseous pollutants and meteorological variables as explanatory independent variables. A logarithmic link function was considered with a Poisson probability distribution. Particular attention was given to cases with air temperatures both below and above 25°C. The best performance for modelled results against the measured data was achieved for the model with values of air temperature above 25°C compared with the model considering all ranges of air temperatures and with the model considering only temperature below 25°C. The model was also tested with similar data from another Portuguese city, Oporto, and results found to behave similarly. It is concluded that this model and the methodology could be adopted for other cities to predict PM10 concentrations when these data are not available by measurements from air quality monitoring stations or other acquisition means.

Analog design optimization methodology for ultralow-power circuits using intuitive inversion-level and saturation-level parameters

NASA Astrophysics Data System (ADS)

Eimori, Takahisa; Anami, Kenji; Yoshimatsu, Norifumi; Hasebe, Tetsuya; Murakami, Kazuaki

2014-01-01

A comprehensive design optimization methodology using intuitive nondimensional parameters of inversion-level and saturation-level is proposed, especially for ultralow-power, low-voltage, and high-performance analog circuits with mixed strong, moderate, and weak inversion metal-oxide-semiconductor transistor (MOST) operations. This methodology is based on the synthesized charge-based MOST model composed of Enz-Krummenacher-Vittoz (EKV) basic concepts and advanced-compact-model (ACM) physics-based equations. The key concept of this methodology is that all circuit and system characteristics are described as some multivariate functions of inversion-level parameters, where the inversion level is used as an independent variable representative of each MOST. The analog circuit design starts from the first step of inversion-level design using universal characteristics expressed by circuit currents and inversion-level parameters without process-dependent parameters, followed by the second step of foundry-process-dependent design and the last step of verification using saturation-level criteria. This methodology also paves the way to an intuitive and comprehensive design approach for many kinds of analog circuit specifications by optimization using inversion-level log-scale diagrams and saturation-level criteria. In this paper, we introduce an example of our design methodology for a two-stage Miller amplifier.

Soft tissue deformation modelling through neural dynamics-based reaction-diffusion mechanics.

PubMed

Zhang, Jinao; Zhong, Yongmin; Gu, Chengfan

2018-05-30

Soft tissue deformation modelling forms the basis of development of surgical simulation, surgical planning and robotic-assisted minimally invasive surgery. This paper presents a new methodology for modelling of soft tissue deformation based on reaction-diffusion mechanics via neural dynamics. The potential energy stored in soft tissues due to a mechanical load to deform tissues away from their rest state is treated as the equivalent transmembrane potential energy, and it is distributed in the tissue masses in the manner of reaction-diffusion propagation of nonlinear electrical waves. The reaction-diffusion propagation of mechanical potential energy and nonrigid mechanics of motion are combined to model soft tissue deformation and its dynamics, both of which are further formulated as the dynamics of cellular neural networks to achieve real-time computational performance. The proposed methodology is implemented with a haptic device for interactive soft tissue deformation with force feedback. Experimental results demonstrate that the proposed methodology exhibits nonlinear force-displacement relationship for nonlinear soft tissue deformation. Homogeneous, anisotropic and heterogeneous soft tissue material properties can be modelled through the inherent physical properties of mass points. Graphical abstract Soft tissue deformation modelling with haptic feedback via neural dynamics-based reaction-diffusion mechanics.

Argumentation in Science Education: A Model-based Framework

NASA Astrophysics Data System (ADS)

Böttcher, Florian; Meisert, Anke

2011-02-01

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

Transportation Energy Conservation Data Book: A Selected Bibliography. Edition 3,

DTIC Science & Technology

1978-11-01

Charlottesville, VA 22901 TITLE: Couputer-Based Resource Accounting Model TT1.1: Methodology for the Design of Urban for Automobile Technology Impact...Evaluation System ACCOUNTING; INDUSTRIAL SECTOR; ENERGY tPIESi Documentation. volume 6. CONSUM PTION: PERFORANCE: DESIGN : NASTE MEAT: Methodology for... Methodology for the Design of Urban Transportation 000172 Energy Flows In the U.S., 1973 and 1974. Volume 1: Methodology * $opdate to the Fational Energy

Stochastic model for fatigue crack size and cost effective design decisions. [for aerospace structures

NASA Technical Reports Server (NTRS)

Hanagud, S.; Uppaluri, B.

1975-01-01

This paper describes a methodology for making cost effective fatigue design decisions. The methodology is based on a probabilistic model for the stochastic process of fatigue crack growth with time. The development of a particular model for the stochastic process is also discussed in the paper. The model is based on the assumption of continuous time and discrete space of crack lengths. Statistical decision theory and the developed probabilistic model are used to develop the procedure for making fatigue design decisions on the basis of minimum expected cost or risk function and reliability bounds. Selections of initial flaw size distribution, NDT, repair threshold crack lengths, and inspection intervals are discussed.

Multiple templates-based homology modeling enhances structure quality of AT1 receptor: validation by molecular dynamics and antagonist docking.

PubMed

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.

Wall jet analysis for circulation control aerodynamics. Part 1: Fundamental CFD and turbulence modeling concepts

NASA Technical Reports Server (NTRS)

Dash, S. M.; York, B. J.; Sinha, N.; Dvorak, F. A.

1987-01-01

An overview of parabolic and PNS (Parabolized Navier-Stokes) methodology developed to treat highly curved sub and supersonic wall jets is presented. The fundamental data base to which these models were applied is discussed in detail. The analysis of strong curvature effects was found to require a semi-elliptic extension of the parabolic modeling to account for turbulent contributions to the normal pressure variations, as well as an extension to the turbulence models utilized, to account for the highly enhanced mixing rates observed in situations with large convex curvature. A noniterative, pressure split procedure is shown to extend parabolic models to account for such normal pressure variations in an efficient manner, requiring minimal additional run time over a standard parabolic approach. A new PNS methodology is presented to solve this problem which extends parabolic methodology via the addition of a characteristic base wave solver. Applications of this approach to analyze the interaction of wave and turbulence processes in wall jets is presented.

Development of a methodology for assessing the safety of embedded software systems

NASA Technical Reports Server (NTRS)

Garrett, C. J.; Guarro, S. B.; Apostolakis, G. E.

1993-01-01

A Dynamic Flowgraph Methodology (DFM) based on an integrated approach to modeling and analyzing the behavior of software-driven embedded systems for assessing and verifying reliability and safety is discussed. DFM is based on an extension of the Logic Flowgraph Methodology to incorporate state transition models. System models which express the logic of the system in terms of causal relationships between physical variables and temporal characteristics of software modules are analyzed to determine how a certain state can be reached. This is done by developing timed fault trees which take the form of logical combinations of static trees relating the system parameters at different point in time. The resulting information concerning the hardware and software states can be used to eliminate unsafe execution paths and identify testing criteria for safety critical software functions.

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

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

Shen, Chen; Gupta, Vipul; Huang, Shenyan

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

A micromechanics-based strength prediction methodology for notched metal matrix composites

NASA Technical Reports Server (NTRS)

Bigelow, C. A.

1992-01-01

An analytical micromechanics based strength prediction methodology was developed to predict failure of notched metal matrix composites. The stress-strain behavior and notched strength of two metal matrix composites, boron/aluminum (B/Al) and silicon-carbide/titanium (SCS-6/Ti-15-3), were predicted. The prediction methodology combines analytical techniques ranging from a three dimensional finite element analysis of a notched specimen to a micromechanical model of a single fiber. In the B/Al laminates, a fiber failure criteria based on the axial and shear stress in the fiber accurately predicted laminate failure for a variety of layups and notch-length to specimen-width ratios with both circular holes and sharp notches when matrix plasticity was included in the analysis. For the SCS-6/Ti-15-3 laminates, a fiber failure based on the axial stress in the fiber correlated well with experimental results for static and post fatigue residual strengths when fiber matrix debonding and matrix cracking were included in the analysis. The micromechanics based strength prediction methodology offers a direct approach to strength prediction by modeling behavior and damage on a constituent level, thus, explicitly including matrix nonlinearity, fiber matrix debonding, and matrix cracking.

A micromechanics-based strength prediction methodology for notched metal-matrix composites

NASA Technical Reports Server (NTRS)

Bigelow, C. A.

1993-01-01

An analytical micromechanics-based strength prediction methodology was developed to predict failure of notched metal matrix composites. The stress-strain behavior and notched strength of two metal matrix composites, boron/aluminum (B/Al) and silicon-carbide/titanium (SCS-6/Ti-15-3), were predicted. The prediction methodology combines analytical techniques ranging from a three-dimensional finite element analysis of a notched specimen to a micromechanical model of a single fiber. In the B/Al laminates, a fiber failure criteria based on the axial and shear stress in the fiber accurately predicted laminate failure for a variety of layups and notch-length to specimen-width ratios with both circular holes and sharp notches when matrix plasticity was included in the analysis. For the SCS-6/Ti-15-3 laminates, a fiber failure based on the axial stress in the fiber correlated well with experimental results for static and postfatigue residual strengths when fiber matrix debonding and matrix cracking were included in the analysis. The micromechanics-based strength prediction methodology offers a direct approach to strength prediction by modeling behavior and damage on a constituent level, thus, explicitly including matrix nonlinearity, fiber matrix debonding, and matrix cracking.

A quality-based cost model for new electronic systems and products

NASA Astrophysics Data System (ADS)

Shina, Sammy G.; Saigal, Anil

1998-04-01

This article outlines a method for developing a quality-based cost model for the design of new electronic systems and products. The model incorporates a methodology for determining a cost-effective design margin allocation for electronic products and systems and its impact on manufacturing quality and cost. A spreadsheet-based cost estimating tool was developed to help implement this methodology in order for the system design engineers to quickly estimate the effect of design decisions and tradeoffs on the quality and cost of new products. The tool was developed with automatic spreadsheet connectivity to current process capability and with provisions to consider the impact of capital equipment and tooling purchases to reduce the product cost.

On multi-site damage identification using single-site training data

NASA Astrophysics Data System (ADS)

Barthorpe, R. J.; Manson, G.; Worden, K.

2017-11-01

This paper proposes a methodology for developing multi-site damage location systems for engineering structures that can be trained using single-site damaged state data only. The methodology involves training a sequence of binary classifiers based upon single-site damage data and combining the developed classifiers into a robust multi-class damage locator. In this way, the multi-site damage identification problem may be decomposed into a sequence of binary decisions. In this paper Support Vector Classifiers are adopted as the means of making these binary decisions. The proposed methodology represents an advancement on the state of the art in the field of multi-site damage identification which require either: (1) full damaged state data from single- and multi-site damage cases or (2) the development of a physics-based model to make multi-site model predictions. The potential benefit of the proposed methodology is that a significantly reduced number of recorded damage states may be required in order to train a multi-site damage locator without recourse to physics-based model predictions. In this paper it is first demonstrated that Support Vector Classification represents an appropriate approach to the multi-site damage location problem, with methods for combining binary classifiers discussed. Next, the proposed methodology is demonstrated and evaluated through application to a real engineering structure - a Piper Tomahawk trainer aircraft wing - with its performance compared to classifiers trained using the full damaged-state dataset.

A methodology for the assessment of manned flight simulator fidelity

NASA Technical Reports Server (NTRS)

Hess, Ronald A.; Malsbury, Terry N.

1989-01-01

A relatively simple analytical methodology for assessing the fidelity of manned flight simulators for specific vehicles and tasks is offered. The methodology is based upon an application of a structural model of the human pilot, including motion cue effects. In particular, predicted pilot/vehicle dynamic characteristics are obtained with and without simulator limitations. A procedure for selecting model parameters can be implemented, given a probable pilot control strategy. In analyzing a pair of piloting tasks for which flight and simulation data are available, the methodology correctly predicted the existence of simulator fidelity problems. The methodology permitted the analytical evaluation of a change in simulator characteristics and indicated that a major source of the fidelity problems was a visual time delay in the simulation.

Computer-Aided Sensor Development Focused on Security Issues.

PubMed

Bialas, Andrzej

2016-05-26

The paper examines intelligent sensor and sensor system development according to the Common Criteria methodology, which is the basic security assurance methodology for IT products and systems. The paper presents how the development process can be supported by software tools, design patterns and knowledge engineering. The automation of this process brings cost-, quality-, and time-related advantages, because the most difficult and most laborious activities are software-supported and the design reusability is growing. The paper includes a short introduction to the Common Criteria methodology and its sensor-related applications. In the experimental section the computer-supported and patterns-based IT security development process is presented using the example of an intelligent methane detection sensor. This process is supported by an ontology-based tool for security modeling and analyses. The verified and justified models are transferred straight to the security target specification representing security requirements for the IT product. The novelty of the paper is to provide a patterns-based and computer-aided methodology for the sensors development with a view to achieving their IT security assurance. The paper summarizes the validation experiment focused on this methodology adapted for the sensors system development, and presents directions of future research.

Computer-Aided Sensor Development Focused on Security Issues

PubMed Central

Bialas, Andrzej

2016-01-01

The paper examines intelligent sensor and sensor system development according to the Common Criteria methodology, which is the basic security assurance methodology for IT products and systems. The paper presents how the development process can be supported by software tools, design patterns and knowledge engineering. The automation of this process brings cost-, quality-, and time-related advantages, because the most difficult and most laborious activities are software-supported and the design reusability is growing. The paper includes a short introduction to the Common Criteria methodology and its sensor-related applications. In the experimental section the computer-supported and patterns-based IT security development process is presented using the example of an intelligent methane detection sensor. This process is supported by an ontology-based tool for security modeling and analyses. The verified and justified models are transferred straight to the security target specification representing security requirements for the IT product. The novelty of the paper is to provide a patterns-based and computer-aided methodology for the sensors development with a view to achieving their IT security assurance. The paper summarizes the validation experiment focused on this methodology adapted for the sensors system development, and presents directions of future research. PMID:27240360

Dynamic Decision Making under Uncertainty and Partial Information

DTIC Science & Technology

2017-01-30

order to address these problems, we investigated efficient computational methodologies for dynamic decision making under uncertainty and partial...information. In the course of this research, we developed and studied efficient simulation-based methodologies for dynamic decision making under...uncertainty and partial information; (ii) studied the application of these decision making models and methodologies to practical problems, such as those

Development of a Methodology for Predicting Forest Area for Large-Area Resource Monitoring

Treesearch

William H. Cooke

2001-01-01

The U.S. Department of Agriculture, Forest Service, Southcm Research Station, appointed a remote-sensing team to develop an image-processing methodology for mapping forest lands over large geographic areds. The team has presented a repeatable methodology, which is based on regression modeling of Advanced Very High Resolution Radiometer (AVHRR) and Landsat Thematic...

Toward the Long-Term Scientific Study of Encounter Group Phenomena: I. Methodological Considerations.

ERIC Educational Resources Information Center

Diamond, Michael Jay; Shapiro, Jerrold Lee

This paper proposes a model for the long-term scientific study of encounter, T-, and sensitivity groups. The authors see the need for overcoming major methodological and design inadequacies of such research. They discuss major methodological flaws in group outcome research as including: (1) lack of adequate base rate or pretraining measures; (2)…

An improved approach for flight readiness certification: Methodology for failure risk assessment and application examples. Volume 3: Structure and listing of programs

NASA Technical Reports Server (NTRS)

Moore, N. R.; Ebbeler, D. H.; Newlin, L. E.; Sutharshana, S.; Creager, M.

1992-01-01

An improved methodology for quantitatively evaluating failure risk of spaceflight systems to assess flight readiness and identify risk control measures is presented. This methodology, called Probabilistic Failure Assessment (PFA), combines operating experience from tests and flights with engineering analysis to estimate failure risk. The PFA methodology is of particular value when information on which to base an assessment of failure risk, including test experience and knowledge of parameters used in engineering analyses of failure phenomena, is expensive or difficult to acquire. The PFA methodology is a prescribed statistical structure in which engineering analysis models that characterize failure phenomena are used conjointly with uncertainties about analysis parameters and/or modeling accuracy to estimate failure probability distributions for specific failure modes. These distributions can then be modified, by means of statistical procedures of the PFA methodology, to reflect any test or flight experience. Conventional engineering analysis models currently employed for design of failure prediction are used in this methodology. The PFA methodology is described and examples of its application are presented. Conventional approaches to failure risk evaluation for spaceflight systems are discussed, and the rationale for the approach taken in the PFA methodology is presented. The statistical methods, engineering models, and computer software used in fatigue failure mode applications are thoroughly documented.

Measurement-based auralization methodology for the assessment of noise mitigation measures

NASA Astrophysics Data System (ADS)

Thomas, Pieter; Wei, Weigang; Van Renterghem, Timothy; Botteldooren, Dick

2016-09-01

The effect of noise mitigation measures is generally expressed by noise levels only, neglecting the listener's perception. In this study, an auralization methodology is proposed that enables an auditive preview of noise abatement measures for road traffic noise, based on the direction dependent attenuation of a priori recordings made with a dedicated 32-channel spherical microphone array. This measurement-based auralization has the advantage that all non-road traffic sounds that create the listening context are present. The potential of this auralization methodology is evaluated through the assessment of the effect of an L-shaped mound. The angular insertion loss of the mound is estimated by using the ISO 9613-2 propagation model, the Pierce barrier diffraction model and the Harmonoise point-to-point model. The realism of the auralization technique is evaluated by listening tests, indicating that listeners had great difficulty in differentiating between a posteriori recordings and auralized samples, which shows the validity of the followed approaches.

The determination of operational and support requirements and costs during the conceptual design of space systems

NASA Technical Reports Server (NTRS)

Ebeling, Charles; Beasley, Kenneth D.

1992-01-01

The first year of research to provide NASA support in predicting operational and support parameters and costs of proposed space systems is reported. Some of the specific research objectives were (1) to develop a methodology for deriving reliability and maintainability parameters and, based upon their estimates, determine the operational capability and support costs, and (2) to identify data sources and establish an initial data base to implement the methodology. Implementation of the methodology is accomplished through the development of a comprehensive computer model. While the model appears to work reasonably well when applied to aircraft systems, it was not accurate when used for space systems. The model is dynamic and should be updated as new data become available. It is particularly important to integrate the current aircraft data base with data obtained from the Space Shuttle and other space systems since subsystems unique to a space vehicle require data not available from aircraft. This research only addressed the major subsystems on the vehicle.

Automated combinatorial method for fast and robust prediction of lattice thermal conductivity

NASA Astrophysics Data System (ADS)

Plata, Jose J.; Nath, Pinku; Usanmaz, Demet; Toher, Cormac; Fornari, Marco; Buongiorno Nardelli, Marco; Curtarolo, Stefano

The lack of computationally inexpensive and accurate ab-initio based methodologies to predict lattice thermal conductivity, κl, without computing the anharmonic force constants or performing time-consuming ab-initio molecular dynamics, is one of the obstacles preventing the accelerated discovery of new high or low thermal conductivity materials. The Slack equation is the best alternative to other more expensive methodologies but is highly dependent on two variables: the acoustic Debye temperature, θa, and the Grüneisen parameter, γ. Furthermore, different definitions can be used for these two quantities depending on the model or approximation. Here, we present a combinatorial approach based on the quasi-harmonic approximation to elucidate which definitions of both variables produce the best predictions of κl. A set of 42 compounds was used to test accuracy and robustness of all possible combinations. This approach is ideal for obtaining more accurate values than fast screening models based on the Debye model, while being significantly less expensive than methodologies that solve the Boltzmann transport equation.

Leveraging the Zachman framework implementation using action - research methodology - a case study: aligning the enterprise architecture and the business goals

NASA Astrophysics Data System (ADS)

Nogueira, Juan Manuel; Romero, David; Espadas, Javier; Molina, Arturo

2013-02-01

With the emergence of new enterprise models, such as technology-based enterprises, and the large quantity of information generated through technological advances, the Zachman framework continues to represent a modelling tool of great utility and value to construct an enterprise architecture (EA) that can integrate and align the IT infrastructure and business goals. Nevertheless, implementing an EA requires an important effort within an enterprise. Small technology-based enterprises and start-ups can take advantage of EAs and frameworks but, because these enterprises have limited resources to allocate for this task, an enterprise framework implementation is not feasible in most cases. This article proposes a new methodology based on action-research for the implementation of the business, system and technology models of the Zachman framework to assist and facilitate its implementation. Following the explanation of cycles of the proposed methodology, a case study is presented to illustrate the results of implementing the Zachman framework in a technology-based enterprise: PyME CREATIVA, using action-research approach.

Bayesian Framework for Water Quality Model Uncertainty Estimation and Risk Management

EPA Science Inventory

A formal Bayesian methodology is presented for integrated model calibration and risk-based water quality management using Bayesian Monte Carlo simulation and maximum likelihood estimation (BMCML). The primary focus is on lucid integration of model calibration with risk-based wat...

The comparison of the use of holonic and agent-based methods in modelling of manufacturing systems

NASA Astrophysics Data System (ADS)

Foit, K.; Banaś, W.; Gwiazda, A.; Hryniewicz, P.

2017-08-01

The rapid evolution in the field of industrial automation and manufacturing is often called the 4th Industry Revolution. Worldwide availability of the internet access contributes to the competition between manufacturers, gives the opportunity for buying materials, parts and for creating the partnership networks, like cloud manufacturing, grid manufacturing (MGrid), virtual enterprises etc. The effect of the industry evolution is the need to search for new solutions in the field of manufacturing systems modelling and simulation. During the last decade researchers have developed the agent-based approach of modelling. This methodology have been taken from the computer science, but was adapted to the philosophy of industrial automation and robotization. The operation of the agent-based system depends on the simultaneous acting of different agents that may have different roles. On the other hand, there is the holon-based approach that uses the structures created by holons. It differs from the agent-based structure in some aspects, while the other ones are quite similar in both methodologies. The aim of this paper is to present the both methodologies and discuss the similarities and the differences. This may could help to select the optimal method of modelling, according to the considered problem and software resources.

Validating agent oriented methodology (AOM) for netlogo modelling and simulation

NASA Astrophysics Data System (ADS)

WaiShiang, Cheah; Nissom, Shane; YeeWai, Sim; Sharbini, Hamizan

2017-10-01

AOM (Agent Oriented Modeling) is a comprehensive and unified agent methodology for agent oriented software development. AOM methodology was proposed to aid developers with the introduction of technique, terminology, notation and guideline during agent systems development. Although AOM methodology is claimed to be capable of developing a complex real world system, its potential is yet to be realized and recognized by the mainstream software community and the adoption of AOM is still at its infancy. Among the reason is that there are not much case studies or success story of AOM. This paper presents two case studies on the adoption of AOM for individual based modelling and simulation. It demonstrate how the AOM is useful for epidemiology study and ecological study. Hence, it further validate the AOM in a qualitative manner.

Passivity-based Robust Control of Aerospace Systems

NASA Technical Reports Server (NTRS)

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

2000-01-01

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

AN OPTIMAL MAINTENANCE MANAGEMENT MODEL FOR AIRPORT CONCRETE PAVEMENT

NASA Astrophysics Data System (ADS)

Shimomura, Taizo; Fujimori, Yuji; Kaito, Kiyoyuki; Obama, Kengo; Kobayashi, Kiyoshi

In this paper, an optimal management model is formulated for the performance-based rehabilitation/maintenance contract for airport concrete pavement, whereby two types of life cycle cost risks, i.e., ground consolidation risk and concrete depreciation risk, are explicitly considered. The non-homogenous Markov chain model is formulated to represent the deterioration processes of concrete pavement which are conditional upon the ground consolidation processes. The optimal non-homogenous Markov decision model with multiple types of risk is presented to design the optimal rehabilitation/maintenance plans. And the methodology to revise the optimal rehabilitation/maintenance plans based upon the monitoring data by the Bayesian up-to-dating rules. The validity of the methodology presented in this paper is examined based upon the case studies carried out for the H airport.

Simulating the heterogeneity in braided channel belt deposits: 1. A geometric-based methodology and code

NASA Astrophysics Data System (ADS)

Ramanathan, Ramya; Guin, Arijit; Ritzi, Robert W.; Dominic, David F.; Freedman, Vicky L.; Scheibe, Timothy D.; Lunt, Ian A.

2010-04-01

A geometric-based simulation methodology was developed and incorporated into a computer code to model the hierarchical stratal architecture, and the corresponding spatial distribution of permeability, in braided channel belt deposits. The code creates digital models of these deposits as a three-dimensional cubic lattice, which can be used directly in numerical aquifer or reservoir models for fluid flow. The digital models have stratal units defined from the kilometer scale to the centimeter scale. These synthetic deposits are intended to be used as high-resolution base cases in various areas of computational research on multiscale flow and transport processes, including the testing of upscaling theories. The input parameters are primarily univariate statistics. These include the mean and variance for characteristic lengths of sedimentary unit types at each hierarchical level, and the mean and variance of log-permeability for unit types defined at only the lowest level (smallest scale) of the hierarchy. The code has been written for both serial and parallel execution. The methodology is described in part 1 of this paper. In part 2 (Guin et al., 2010), models generated by the code are presented and evaluated.

Simulating the Heterogeneity in Braided Channel Belt Deposits: Part 1. A Geometric-Based Methodology and Code

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

Ramanathan, Ramya; Guin, Arijit; Ritzi, Robert W.

A geometric-based simulation methodology was developed and incorporated into a computer code to model the hierarchical stratal architecture, and the corresponding spatial distribution of permeability, in braided channel belt deposits. The code creates digital models of these deposits as a three-dimensional cubic lattice, which can be used directly in numerical aquifer or reservoir models for fluid flow. The digital models have stratal units defined from the km scale to the cm scale. These synthetic deposits are intended to be used as high-resolution base cases in various areas of computational research on multiscale flow and transport processes, including the testing ofmore » upscaling theories. The input parameters are primarily univariate statistics. These include the mean and variance for characteristic lengths of sedimentary unit types at each hierarchical level, and the mean and variance of log-permeability for unit types defined at only the lowest level (smallest scale) of the hierarchy. The code has been written for both serial and parallel execution. The methodology is described in Part 1 of this series. In Part 2, models generated by the code are presented and evaluated.« less

Modeling ground-based timber harvesting systems using computer simulation

Treesearch

Jingxin Wang; Chris B. LeDoux

2001-01-01

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

The methodology of database design in organization management systems

NASA Astrophysics Data System (ADS)

Chudinov, I. L.; Osipova, V. V.; Bobrova, Y. V.

2017-01-01

The paper describes the unified methodology of database design for management information systems. Designing the conceptual information model for the domain area is the most important and labor-intensive stage in database design. Basing on the proposed integrated approach to design, the conceptual information model, the main principles of developing the relation databases are provided and user’s information needs are considered. According to the methodology, the process of designing the conceptual information model includes three basic stages, which are defined in detail. Finally, the article describes the process of performing the results of analyzing user’s information needs and the rationale for use of classifiers.

Probabilistic Based Modeling and Simulation Assessment

DTIC Science & Technology

2010-06-01

different crash and blast scenarios. With the integration of the high fidelity neck and head model, a methodology to calculate the probability of injury...variability, correlation, and multiple (often competing) failure metrics. Important scenarios include vehicular collisions, blast /fragment impact, and...first area of focus is to develop a methodology to integrate probabilistic analysis into finite element analysis of vehicle collisions and blast . The

Nuclear power plant life extension using subsize surveillance specimens. Performance report (4/15/92 - 4/14/98)

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

Kumar, Arvind S.

2001-03-05

A new methodology to predict the Upper Shelf Energy (USE) of standard Charpy specimens (Full size) based on subsize specimens has been developed. The prediction methodology uses Finite Element Modeling (FEM) to model the fracture behavior. The inputs to FEM are the tensile properties of material and subsize Charpy specimen test data.

A dynamic multi-scale Markov model based methodology for remaining life prediction

NASA Astrophysics Data System (ADS)

Yan, Jihong; Guo, Chaozhong; Wang, Xing

2011-05-01

The ability to accurately predict the remaining life of partially degraded components is crucial in prognostics. In this paper, a performance degradation index is designed using multi-feature fusion techniques to represent deterioration severities of facilities. Based on this indicator, an improved Markov model is proposed for remaining life prediction. Fuzzy C-Means (FCM) algorithm is employed to perform state division for Markov model in order to avoid the uncertainty of state division caused by the hard division approach. Considering the influence of both historical and real time data, a dynamic prediction method is introduced into Markov model by a weighted coefficient. Multi-scale theory is employed to solve the state division problem of multi-sample prediction. Consequently, a dynamic multi-scale Markov model is constructed. An experiment is designed based on a Bently-RK4 rotor testbed to validate the dynamic multi-scale Markov model, experimental results illustrate the effectiveness of the methodology.

OWL references in ORM conceptual modelling

NASA Astrophysics Data System (ADS)

Matula, Jiri; Belunek, Roman; Hunka, Frantisek

2017-07-01

Object Role Modelling methodology is the fact-based type of conceptual modelling. The aim of the paper is to emphasize a close connection to OWL documents and its possible mutual cooperation. The definition of entities or domain values is an indispensable part of the conceptual schema design procedure defined by the ORM methodology. Many of these entities are already defined in OWL documents. Therefore, it is not necessary to declare entities again, whereas it is possible to utilize references from OWL documents during modelling of information systems.

A methodology for the design and evaluation of user interfaces for interactive information systems. Ph.D. Thesis Final Report, 1 Jul. 1985 - 31 Dec. 1987

NASA Technical Reports Server (NTRS)

Dominick, Wayne D. (Editor); Farooq, Mohammad U.

1986-01-01

The definition of proposed research addressing the development and validation of a methodology for the design and evaluation of user interfaces for interactive information systems is given. The major objectives of this research are: the development of a comprehensive, objective, and generalizable methodology for the design and evaluation of user interfaces for information systems; the development of equations and/or analytical models to characterize user behavior and the performance of a designed interface; the design of a prototype system for the development and administration of user interfaces; and the design and use of controlled experiments to support the research and test/validate the proposed methodology. The proposed design methodology views the user interface as a virtual machine composed of three layers: an interactive layer, a dialogue manager layer, and an application interface layer. A command language model of user system interactions is presented because of its inherent simplicity and structured approach based on interaction events. All interaction events have a common structure based on common generic elements necessary for a successful dialogue. It is shown that, using this model, various types of interfaces could be designed and implemented to accommodate various categories of users. The implementation methodology is discussed in terms of how to store and organize the information.

Model-based testing with UML applied to a roaming algorithm for bluetooth devices.

PubMed

Dai, Zhen Ru; Grabowski, Jens; Neukirchen, Helmut; Pals, Holger

2004-11-01

In late 2001, the Object Management Group issued a Request for Proposal to develop a testing profile for UML 2.0. In June 2003, the work on the UML 2.0 Testing Profile was finally adopted by the OMG. Since March 2004, it has become an official standard of the OMG. The UML 2.0 Testing Profile provides support for UML based model-driven testing. This paper introduces a methodology on how to use the testing profile in order to modify and extend an existing UML design model for test issues. The application of the methodology will be explained by applying it to an existing UML Model for a Bluetooth device.

Preliminary comparative assessment of PM10 hourly measurement results from new monitoring stations type using stochastic and exploratory methodology and models

NASA Astrophysics Data System (ADS)

Czechowski, Piotr Oskar; Owczarek, Tomasz; Badyda, Artur; Majewski, Grzegorz; Rogulski, Mariusz; Ogrodnik, Paweł

2018-01-01

The paper presents selected preliminary stage key issues proposed extended equivalence measurement results assessment for new portable devices - the comparability PM10 concentration results hourly series with reference station measurement results with statistical methods. In article presented new portable meters technical aspects. The emphasis was placed on the comparability the results using the stochastic and exploratory methods methodology concept. The concept is based on notice that results series simple comparability in the time domain is insufficient. The comparison of regularity should be done in three complementary fields of statistical modeling: time, frequency and space. The proposal is based on model's results of five annual series measurement results new mobile devices and WIOS (Provincial Environmental Protection Inspectorate) reference station located in Nowy Sacz city. The obtained results indicate both the comparison methodology completeness and the high correspondence obtained new measurements results devices with reference.

A comparison of life prediction methodologies for titanium matrix composites subjected to thermomechanical fatigue

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

Calcaterra, J.R.; Johnson, W.S.; Neu, R.W.

1997-12-31

Several methodologies have been developed to predict the lives of titanium matrix composites (TMCs) subjected to thermomechanical fatigue (TMF). This paper reviews and compares five life prediction models developed at NASA-LaRC. Wright Laboratories, based on a dingle parameter, the fiber stress in the load-carrying, or 0{degree}, direction. The two other models, both developed at Wright Labs. are multi-parameter models. These can account for long-term damage, which is beyond the scope of the single-parameter models, but this benefit is offset by the additional complexity of the methodologies. Each of the methodologies was used to model data generated at NASA-LeRC. Wright Labs.more » and Georgia Tech for the SCS-6/Timetal 21-S material system. VISCOPLY, a micromechanical stress analysis code, was used to determine the constituent stress state for each test and was used for each model to maintain consistency. The predictive capabilities of the models are compared, and the ability of each model to accurately predict the responses of tests dominated by differing damage mechanisms is addressed.« less

Model-based Small Area Estimates of Cancer Risk Factors and Screening Behaviors - Small Area Estimates

Cancer.gov

These model-based estimates use two surveys, the Behavioral Risk Factor Surveillance System (BRFSS) and the National Health Interview Survey (NHIS). The two surveys are combined using novel statistical methodology.

Tidal current energy potential of Nalón river estuary assessment using a high precision flow model

NASA Astrophysics Data System (ADS)

Badano, Nicolás; Valdés, Rodolfo Espina; Álvarez, Eduardo Álvarez

2018-05-01

Obtaining energy from tide currents in onshore locations is of great interest due to the proximity to the points of consumption. This opens the door to the feasibility of new installations based on hydrokinetic microturbines even in zones of moderate speed. In this context, the accuracy of energy predictions based on hydrodynamic models is of paramount importance. This research presents a high precision methodology based on a multidimensional hydrodynamic model that is used to study the energetic potential in estuaries. Moreover, it is able to estimate the flow variations caused by microturbine installations. The paper also shows the results obtained from the application of the methodology in a study of the Nalón river mouth (Asturias, Spain).

System cost/performance analysis (study 2.3). Volume 1: Executive summary

NASA Technical Reports Server (NTRS)

Kazangey, T.

1973-01-01

The relationships between performance, safety, cost, and schedule parameters were identified and quantified in support of an overall effort to generate program models and methodology that provide insight into a total space vehicle program. A specific space vehicle system, the attitude control system (ACS), was used, and a modeling methodology was selected that develops a consistent set of quantitative relationships among performance, safety, cost, and schedule, based on the characteristics of the components utilized in candidate mechanisms. These descriptive equations were developed for a three-axis, earth-pointing, mass expulsion ACS. A data base describing typical candidate ACS components was implemented, along with a computer program to perform sample calculations. This approach, implemented on a computer, is capable of determining the effect of a change in functional requirements to the ACS mechanization and the resulting cost and schedule. By a simple extension of this modeling methodology to the other systems in a space vehicle, a complete space vehicle model can be developed. Study results and recommendations are presented.

Teaching Note--An Exploration of Team-Based Learning and Social Work Education: A Natural Fit

ERIC Educational Resources Information Center

Robinson, Michael A.; Robinson, Michelle Bachelor; McCaskill, Gina M.

2013-01-01

The literature on team-based learning (TBL) as a pedagogical methodology in social work education is limited; however, TBL, which was developed as a model for business, has been successfully used as a teaching methodology in nursing, business, engineering, medical school, and many other disciplines in academia. This project examines the use of TBL…

Multiphysics Thrust Chamber Modeling for Nuclear Thermal Propulsion

NASA Technical Reports Server (NTRS)

Wang, Ten-See; Cheng, Gary; Chen, Yen-Sen

2006-01-01

The objective of this effort is to develop an efficient and accurate thermo-fluid computational methodology to predict environments for a solid-core, nuclear thermal engine thrust chamber. The computational methodology is based on an unstructured-grid, pressure-based computational fluid dynamics formulation. A two-pronged approach is employed in this effort: A detailed thermo-fluid analysis on a multi-channel flow element for mid-section corrosion investigation; and a global modeling of the thrust chamber to understand the effect of heat transfer on thrust performance. Preliminary results on both aspects are presented.

One Small Step for Creo Modelers, One Giant Leap for "Grey Beards": Using MBD Methodologies to Launch Astronauts and Hardware to Near-Earth Objects such as Asteroids, the Moon and Mars

NASA Technical Reports Server (NTRS)

Jones, Corey; LaPha, Steven

2013-01-01

This presentation will focus on the modernization of design and engineering practices through the use of Model Based Definition methodology. By gathering important engineering data into one 3D digital data set, applying model annotations, and setting up model view states directly in the 3D CAD model, model-specific information can be published to Windchill and CreoView for use during the Design Review Process. This presentation will describe the methods that have been incorporated into the modeling.

[Methodological novelties applied to the anthropology of food: agent-based models and social networks analysis].

PubMed

Díaz Córdova, Diego

2016-01-01

The aim of this article is to introduce two methodological strategies that have not often been utilized in the anthropology of food: agent-based models and social networks analysis. In order to illustrate these methods in action, two cases based in materials typical of the anthropology of food are presented. For the first strategy, fieldwork carried out in Quebrada de Humahuaca (province of Jujuy, Argentina) regarding meal recall was used, and for the second, elements of the concept of "domestic consumption strategies" applied by Aguirre were employed. The underlying idea is that, given that eating is recognized as a "total social fact" and, therefore, as a complex phenomenon, the methodological approach must also be characterized by complexity. The greater the number of methods utilized (with the appropriate rigor), the better able we will be to understand the dynamics of feeding in the social environment.

Model methodology for estimating pesticide concentration extremes based on sparse monitoring data

USGS Publications Warehouse

Vecchia, Aldo V.

2018-03-22

This report describes a new methodology for using sparse (weekly or less frequent observations) and potentially highly censored pesticide monitoring data to simulate daily pesticide concentrations and associated quantities used for acute and chronic exposure assessments, such as the annual maximum daily concentration. The new methodology is based on a statistical model that expresses log-transformed daily pesticide concentration in terms of a seasonal wave, flow-related variability, long-term trend, and serially correlated errors. Methods are described for estimating the model parameters, generating conditional simulations of daily pesticide concentration given sparse (weekly or less frequent) and potentially highly censored observations, and estimating concentration extremes based on the conditional simulations. The model can be applied to datasets with as few as 3 years of record, as few as 30 total observations, and as few as 10 uncensored observations. The model was applied to atrazine, carbaryl, chlorpyrifos, and fipronil data for U.S. Geological Survey pesticide sampling sites with sufficient data for applying the model. A total of 112 sites were analyzed for atrazine, 38 for carbaryl, 34 for chlorpyrifos, and 33 for fipronil. The results are summarized in this report; and, R functions, described in this report and provided in an accompanying model archive, can be used to fit the model parameters and generate conditional simulations of daily concentrations for use in investigations involving pesticide exposure risk and uncertainty.

Modeling Web-Based Educational Systems: Process Design Teaching Model

ERIC Educational Resources Information Center

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

2004-01-01

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

Artificial Intelligence-Based Models for the Optimal and Sustainable Use of Groundwater in Coastal Aquifers

NASA Astrophysics Data System (ADS)

Sreekanth, J.; Datta, Bithin

2011-07-01

Overexploitation of the coastal aquifers results in saltwater intrusion. Once saltwater intrusion occurs, it involves huge cost and long-term remediation measures to remediate these contaminated aquifers. Hence, it is important to have strategies for the sustainable use of coastal aquifers. This study develops a methodology for the optimal management of saltwater intrusion prone aquifers. A linked simulation-optimization-based management strategy is developed. The methodology uses genetic-programming-based models for simulating the aquifer processes, which is then linked to a multi-objective genetic algorithm to obtain optimal management strategies in terms of groundwater extraction from potential well locations in the aquifer.

Observational attachment theory-based parenting measures predict children's attachment narratives independently from social learning theory-based measures.

PubMed

Matias, Carla; O'Connor, Thomas G; Futh, Annabel; Scott, Stephen

2014-01-01

Conceptually and methodologically distinct models exist for assessing quality of parent-child relationships, but few studies contrast competing models or assess their overlap in predicting developmental outcomes. Using observational methodology, the current study examined the distinctiveness of attachment theory-based and social learning theory-based measures of parenting in predicting two key measures of child adjustment: security of attachment narratives and social acceptance in peer nominations. A total of 113 5-6-year-old children from ethnically diverse families participated. Parent-child relationships were rated using standard paradigms. Measures derived from attachment theory included sensitive responding and mutuality; measures derived from social learning theory included positive attending, directives, and criticism. Child outcomes were independently-rated attachment narrative representations and peer nominations. Results indicated that Attachment theory-based and Social Learning theory-based measures were modestly correlated; nonetheless, parent-child mutuality predicted secure child attachment narratives independently of social learning theory-based measures; in contrast, criticism predicted peer-nominated fighting independently of attachment theory-based measures. In young children, there is some evidence that attachment theory-based measures may be particularly predictive of attachment narratives; however, no single model of measuring parent-child relationships is likely to best predict multiple developmental outcomes. Assessment in research and applied settings may benefit from integration of different theoretical and methodological paradigms.

Contributions of Model-Based Learning to the Restructuring of Graduation Students' Mental Models on Natural Hazards

ERIC Educational Resources Information Center

Moutinho, Sara; Moura, Rui; Vasconcelos, Clara

2017-01-01

Model-Based learning is a methodology that facilitates students' construction of scientific knowledge, which, sometimes, includes restructuring their mental models. Taking into consideration students' learning process, its aim is to promote a deeper understanding of phenomena's dynamics through the manipulation of models. Our aim was to ascertain…

Architectural approaches for HL7-based health information systems implementation.

PubMed

López, D M; Blobel, B

2010-01-01

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

A Model for Ubiquitous Serious Games Development Focused on Problem Based Learning

ERIC Educational Resources Information Center

Dorneles, Sandro Oliveira; da Costa, Cristiano André; Rigo, Sandro José

2015-01-01

The possibility of using serious games with problem-based learning opens up huge opportunities to connect the experiences of daily life of students with learning. In this context, this article presents a model for serious and ubiquitous games development, focusing on problem based learning methodology. The model allows teachers to create games…

Community-Based Rehabilitation (CBR): Problems and Possibilities.

ERIC Educational Resources Information Center

O'Toole, Brian

1987-01-01

The institution-based model for providing services to individuals with disabilities has limitations in both developing and developed countries. The community-based rehabilitation model was positively evaluated by the World Health Organization as an alternative approach, but the evaluation is questioned on methodological and philosophical grounds.…

Finite element model updating and damage detection for bridges using vibration measurement.

DOT National Transportation Integrated Search

2013-12-01

In this report, the results of a study on developing a damage detection methodology based on Statistical Pattern Recognition are : presented. This methodology uses a new damage sensitive feature developed in this study that relies entirely on modal :...

Calibration methodology for proportional counters applied to yield measurements of a neutron burst.

PubMed

Tarifeño-Saldivia, Ariel; Mayer, Roberto E; Pavez, Cristian; Soto, Leopoldo

2014-01-01

This paper introduces a methodology for the yield measurement of a neutron burst using neutron proportional counters. This methodology is to be applied when single neutron events cannot be resolved in time by nuclear standard electronics, or when a continuous current cannot be measured at the output of the counter. The methodology is based on the calibration of the counter in pulse mode, and the use of a statistical model to estimate the number of detected events from the accumulated charge resulting from the detection of the burst of neutrons. The model is developed and presented in full detail. For the measurement of fast neutron yields generated from plasma focus experiments using a moderated proportional counter, the implementation of the methodology is herein discussed. An experimental verification of the accuracy of the methodology is presented. An improvement of more than one order of magnitude in the accuracy of the detection system is obtained by using this methodology with respect to previous calibration methods.

A decomposition model and voxel selection framework for fMRI analysis to predict neural response of visual stimuli.

PubMed

Raut, Savita V; Yadav, Dinkar M

2018-03-28

This paper presents an fMRI signal analysis methodology using geometric mean curve decomposition (GMCD) and mutual information-based voxel selection framework. Previously, the fMRI signal analysis has been conducted using empirical mean curve decomposition (EMCD) model and voxel selection on raw fMRI signal. The erstwhile methodology loses frequency component, while the latter methodology suffers from signal redundancy. Both challenges are addressed by our methodology in which the frequency component is considered by decomposing the raw fMRI signal using geometric mean rather than arithmetic mean and the voxels are selected from EMCD signal using GMCD components, rather than raw fMRI signal. The proposed methodologies are adopted for predicting the neural response. Experimentations are conducted in the openly available fMRI data of six subjects, and comparisons are made with existing decomposition models and voxel selection frameworks. Subsequently, the effect of degree of selected voxels and the selection constraints are analyzed. The comparative results and the analysis demonstrate the superiority and the reliability of the proposed methodology.

Semicompeting risks in aging research: methods, issues and needs

PubMed Central

Varadhan, Ravi; Xue, Qian-Li; Bandeen-Roche, Karen

2015-01-01

A semicompeting risks problem involves two-types of events: a nonterminal and a terminal event (death). Typically, the nonterminal event is the focus of the study, but the terminal event can preclude the occurrence of the nonterminal event. Semicompeting risks are ubiquitous in studies of aging. Examples of semicompeting risk dyads include: dementia and death, frailty syndrome and death, disability and death, and nursing home placement and death. Semicompeting risk models can be divided into two broad classes: models based only on observables quantities (class O) and those based on potential (latent) failure times (class L). The classical illness-death model belongs to class O. This model is a special case of the multistate models, which has been an active area of methodology development. During the past decade and a half, there has also been a flurry of methodological activity on semicompeting risks based on latent failure times (L models). These advances notwithstanding, the semi-competing risks methodology has not penetrated biomedical research, in general, and gerontological research, in particular. Some possible reasons for this lack of uptake are: the methods are relatively new and sophisticated, conceptual problems associated with potential failure time models are difficult to overcome, paucity of expository articles aimed at educating practitioners, and non-availability of readily usable software. The main goals of this review article are: (i) to describe the major types of semicompeting risks problems arising in aging research, (ii) to provide a brief survey of the semicompeting risks methods, (iii) to suggest appropriate methods for addressing the problems in aging research, (iv) to highlight areas where more work is needed, and (v) to suggest ways to facilitate the uptake of the semicompeting risks methodology by the broader biomedical research community. PMID:24729136

A PDE-based methodology for modeling, parameter estimation and feedback control in structural and structural acoustic systems

NASA Technical Reports Server (NTRS)

Banks, H. T.; Brown, D. E.; Metcalf, Vern L.; Silcox, R. J.; Smith, Ralph C.; Wang, Yun

1994-01-01

A problem of continued interest concerns the control of vibrations in a flexible structure and the related problem of reducing structure-borne noise in structural acoustic systems. In both cases, piezoceramic patches bonded to the structures have been successfully used as control actuators. Through the application of a controlling voltage, the patches can be used to reduce structural vibrations which in turn lead to methods for reducing structure-borne noise. A PDE-based methodology for modeling, estimating physical parameters, and implementing a feedback control scheme for problems of this type is discussed. While the illustrating example is a circular plate, the methodology is sufficiently general so as to be applicable in a variety of structural and structural acoustic systems.

A multi-criteria decision aid methodology to design electric vehicles public charging networks

NASA Astrophysics Data System (ADS)

Raposo, João; Rodrigues, Ana; Silva, Carlos; Dentinho, Tomaz

2015-05-01

This article presents a new multi-criteria decision aid methodology, dynamic-PROMETHEE, here used to design electric vehicle charging networks. In applying this methodology to a Portuguese city, results suggest that it is effective in designing electric vehicle charging networks, generating time and policy based scenarios, considering offer and demand and the city's urban structure. Dynamic-PROMETHE adds to the already known PROMETHEE's characteristics other useful features, such as decision memory over time, versatility and adaptability. The case study, used here to present the dynamic-PROMETHEE, served as inspiration and base to create this new methodology. It can be used to model different problems and scenarios that may present similar requirement characteristics.

Methodology for estimating helicopter performance and weights using limited data

NASA Technical Reports Server (NTRS)

Baserga, Claudio; Ingalls, Charles; Lee, Henry; Peyran, Richard

1990-01-01

Methodology is developed and described for estimating the flight performance and weights of a helicopter for which limited data are available. The methodology is based on assumptions which couple knowledge of the technology of the helicopter under study with detailed data from well documented helicopters thought to be of similar technology. The approach, analysis assumptions, technology modeling, and the use of reference helicopter data are discussed. Application of the methodology is illustrated with an investigation of the Agusta A129 Mangusta.

On the importance of methods in hydrological modelling. Perspectives from a case study

NASA Astrophysics Data System (ADS)

Fenicia, Fabrizio; Kavetski, Dmitri

2017-04-01

The hydrological community generally appreciates that developing any non-trivial hydrological model requires a multitude of modelling choices. These choices may range from a (seemingly) straightforward application of mass conservation, to the (often) guesswork-like selection of constitutive functions, parameter values, etc. The application of a model itself requires a myriad of methodological choices - the selection of numerical solvers, objective functions for model calibration, validation approaches, performance metrics, etc. Not unreasonably, hydrologists embarking on ever ambitious projects prioritize hydrological insight over the morass of methodological choices. Perhaps to emphasize "ideas" over "methods", some journals have even reduced the fontsize of the methodology sections of its articles. However, the very nature of modelling is that seemingly routine methodological choices can significantly affect the conclusions of case studies and investigations - making it dangerous to skimp over methodological details in an enthusiastic rush towards the next great hydrological idea. This talk shares modelling insights from a hydrological study of a 300 km2 catchment in Luxembourg, where the diversity of hydrograph dynamics observed at 10 locations begs the question of whether external forcings or internal catchment properties act as dominant controls on streamflow generation. The hydrological insights are fascinating (at least to us), but in this talk we emphasize the impact of modelling methodology on case study conclusions and recommendations. How did we construct our prior set of hydrological model hypotheses? What numerical solver was implemented and why was an objective function based on Bayesian theory deployed? And what would have happened had we omitted model cross-validation, or not used a systematic hypothesis testing approach?

Information security system based on virtual-optics imaging methodology and public key infrastructure

NASA Astrophysics Data System (ADS)

Peng, Xiang; Zhang, Peng; Cai, Lilong

In this paper, we present a virtual-optical based information security system model with the aid of public-key-infrastructure (PKI) techniques. The proposed model employs a hybrid architecture in which our previously published encryption algorithm based on virtual-optics imaging methodology (VOIM) can be used to encipher and decipher data while an asymmetric algorithm, for example RSA, is applied for enciphering and deciphering the session key(s). For an asymmetric system, given an encryption key, it is computationally infeasible to determine the decryption key and vice versa. The whole information security model is run under the framework of PKI, which is on basis of public-key cryptography and digital signatures. This PKI-based VOIM security approach has additional features like confidentiality, authentication, and integrity for the purpose of data encryption under the environment of network.

An object-oriented approach for harmonization of multimedia markup languages

NASA Astrophysics Data System (ADS)

Chen, Yih-Feng; Kuo, May-Chen; Sun, Xiaoming; Kuo, C.-C. Jay

2003-12-01

An object-oriented methodology is proposed to harmonize several different markup languages in this research. First, we adopt the Unified Modelling Language (UML) as the data model to formalize the concept and the process of the harmonization process between the eXtensible Markup Language (XML) applications. Then, we design the Harmonization eXtensible Markup Language (HXML) based on the data model and formalize the transformation between the Document Type Definitions (DTDs) of the original XML applications and HXML. The transformation between instances is also discussed. We use the harmonization of SMIL and X3D as an example to demonstrate the proposed methodology. This methodology can be generalized to various application domains.

Revisiting the 'Low BirthWeight paradox' using a model-based definition.

PubMed

Juárez, Sol; Ploubidis, George B; Clarke, Lynda

2014-01-01

Immigrant mothers in Spain have a lower risk of delivering Low BirthWeight (LBW) babies in comparison to Spaniards (LBW paradox). This study aimed at revisiting this finding by applying a model-based threshold as an alternative to the conventional definition of LBW. Vital information data from Madrid was used (2005-2006). LBW was defined in two ways (less than 2500g and Wilcox's proposal). Logistic and linear regression models were run. According to common definition of LBW (less than 2500g) there is evidence to support the LBW paradox in Spain. Nevertheless, when an alternative model-based definition of LBW is used, the paradox is only clearly present in mothers from the rest of Southern America, suggesting a possible methodological bias effect. In the future, any examination of the existence of the LBW paradox should incorporate model-based definitions of LBW in order to avoid methodological bias. Copyright © 2013 SESPAS. Published by Elsevier Espana. All rights reserved.

Distributive Education Competency-Based Curriculum Models by Occupational Clusters. Final Report.

ERIC Educational Resources Information Center

Davis, Rodney E.; Husted, Stewart W.

To meet the needs of distributive education teachers and students, a project was initiated to develop competency-based curriculum models for marketing and distributive education clusters. The models which were developed incorporate competencies, materials and resources, teaching methodologies/learning activities, and evaluative criteria for the…

Creating Needs-Based Tiered Models for Assisted Living Reimbursement

ERIC Educational Resources Information Center

Howell-White, Sandra; Gaboda, Dorothy; Rosato, Nancy Scotto; Lucas, Judith A.

2006-01-01

Purpose: This research provides state policy makers and others interested in developing needs-based reimbursement models for Medicaid-funded assisted living with an evaluation of different methodologies that affect the structure and outcomes of these models. Design and Methods: We used assessment data from Medicaid-enrolled assisted living…

Ligand and structure-based methodologies for the prediction of the activity of G protein-coupled receptor ligands

NASA Astrophysics Data System (ADS)

Costanzi, Stefano; Tikhonova, Irina G.; Harden, T. Kendall; Jacobson, Kenneth A.

2009-11-01

Accurate in silico models for the quantitative prediction of the activity of G protein-coupled receptor (GPCR) ligands would greatly facilitate the process of drug discovery and development. Several methodologies have been developed based on the properties of the ligands, the direct study of the receptor-ligand interactions, or a combination of both approaches. Ligand-based three-dimensional quantitative structure-activity relationships (3D-QSAR) techniques, not requiring knowledge of the receptor structure, have been historically the first to be applied to the prediction of the activity of GPCR ligands. They are generally endowed with robustness and good ranking ability; however they are highly dependent on training sets. Structure-based techniques generally do not provide the level of accuracy necessary to yield meaningful rankings when applied to GPCR homology models. However, they are essentially independent from training sets and have a sufficient level of accuracy to allow an effective discrimination between binders and nonbinders, thus qualifying as viable lead discovery tools. The combination of ligand and structure-based methodologies in the form of receptor-based 3D-QSAR and ligand and structure-based consensus models results in robust and accurate quantitative predictions. The contribution of the structure-based component to these combined approaches is expected to become more substantial and effective in the future, as more sophisticated scoring functions are developed and more detailed structural information on GPCRs is gathered.

A novel methodology for interpreting air quality measurements from urban streets using CFD modelling

NASA Astrophysics Data System (ADS)

Solazzo, Efisio; Vardoulakis, Sotiris; Cai, Xiaoming

2011-09-01

In this study, a novel computational fluid dynamics (CFD) based methodology has been developed to interpret long-term averaged measurements of pollutant concentrations collected at roadside locations. The methodology is applied to the analysis of pollutant dispersion in Stratford Road (SR), a busy street canyon in Birmingham (UK), where a one-year sampling campaign was carried out between August 2005 and July 2006. Firstly, a number of dispersion scenarios are defined by combining sets of synoptic wind velocity and direction. Assuming neutral atmospheric stability, CFD simulations are conducted for all the scenarios, by applying the standard k-ɛ turbulence model, with the aim of creating a database of normalised pollutant concentrations at specific locations within the street. Modelled concentration for all wind scenarios were compared with hourly observed NO x data. In order to compare with long-term averaged measurements, a weighted average of the CFD-calculated concentration fields was derived, with the weighting coefficients being proportional to the frequency of each scenario observed during the examined period (either monthly or annually). In summary the methodology consists of (i) identifying the main dispersion scenarios for the street based on wind speed and directions data, (ii) creating a database of CFD-calculated concentration fields for the identified dispersion scenarios, and (iii) combining the CFD results based on the frequency of occurrence of each dispersion scenario during the examined period. The methodology has been applied to calculate monthly and annually averaged benzene concentration at several locations within the street canyon so that a direct comparison with observations could be made. The results of this study indicate that, within the simplifying assumption of non-buoyant flow, CFD modelling can aid understanding of long-term air quality measurements, and help assessing the representativeness of monitoring locations for population exposure studies.

Variability aware compact model characterization for statistical circuit design optimization

NASA Astrophysics Data System (ADS)

Qiao, Ying; Qian, Kun; Spanos, Costas J.

2012-03-01

Variability modeling at the compact transistor model level can enable statistically optimized designs in view of limitations imposed by the fabrication technology. In this work we propose an efficient variabilityaware compact model characterization methodology based on the linear propagation of variance. Hierarchical spatial variability patterns of selected compact model parameters are directly calculated from transistor array test structures. This methodology has been implemented and tested using transistor I-V measurements and the EKV-EPFL compact model. Calculation results compare well to full-wafer direct model parameter extractions. Further studies are done on the proper selection of both compact model parameters and electrical measurement metrics used in the method.

Modelling Aṣṭādhyāyī: An Approach Based on the Methodology of Ancillary Disciplines (Vedāṅga)

NASA Astrophysics Data System (ADS)

Mishra, Anand

This article proposes a general model based on the common methodological approach of the ancillary disciplines (Vedāṅga) associated with the Vedas taking examples from Śikṣā, Chandas, Vyākaraṇa and Prātiśā khya texts. It develops and elaborates this model further to represent the contents and processes of Aṣṭādhyāyī. Certain key features are added to my earlier modelling of Pāṇinian system of Sanskrit grammar. This includes broader coverage of the Pāṇinian meta-language, mechanism for automatic application of rules and positioning the grammatical system within the procedural complexes of ancillary disciplines.

A Practical, Robust Methodology for Acquiring New Observation Data Using Computationally Expensive Groundwater Models

NASA Astrophysics Data System (ADS)

Siade, Adam J.; Hall, Joel; Karelse, Robert N.

2017-11-01

Regional groundwater flow models play an important role in decision making regarding water resources; however, the uncertainty embedded in model parameters and model assumptions can significantly hinder the reliability of model predictions. One way to reduce this uncertainty is to collect new observation data from the field. However, determining where and when to obtain such data is not straightforward. There exist a number of data-worth and experimental design strategies developed for this purpose. However, these studies often ignore issues related to real-world groundwater models such as computational expense, existing observation data, high-parameter dimension, etc. In this study, we propose a methodology, based on existing methods and software, to efficiently conduct such analyses for large-scale, complex regional groundwater flow systems for which there is a wealth of available observation data. The method utilizes the well-established d-optimality criterion, and the minimax criterion for robust sampling strategies. The so-called Null-Space Monte Carlo method is used to reduce the computational burden associated with uncertainty quantification. And, a heuristic methodology, based on the concept of the greedy algorithm, is proposed for developing robust designs with subsets of the posterior parameter samples. The proposed methodology is tested on a synthetic regional groundwater model, and subsequently applied to an existing, complex, regional groundwater system in the Perth region of Western Australia. The results indicate that robust designs can be obtained efficiently, within reasonable computational resources, for making regional decisions regarding groundwater level sampling.

Report on an Assessment of the Application of EPP Results from the Strain Limit Evaluation Procedure to the Prediction of Cyclic Life Based on the SMT Methodology

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

Jetter, R. I.; Messner, M. C.; Sham, T. -L.

The goal of the proposed integrated Elastic Perfectly-Plastic (EPP) and Simplified Model Test (SMT) methodology is to incorporate an SMT data based approach for creep-fatigue damage evaluation into the EPP methodology to avoid the separate evaluation of creep and fatigue damage and eliminate the requirement for stress classification in current methods; thus greatly simplifying evaluation of elevated temperature cyclic service. This methodology should minimize over-conservatism while properly accounting for localized defects and stress risers. To support the implementation of the proposed methodology and to verify the applicability of the code rules, analytical studies and evaluation of thermomechanical test results continuedmore » in FY17. This report presents the results of those studies. An EPP strain limits methodology assessment was based on recent two-bar thermal ratcheting test results on 316H stainless steel in the temperature range of 405 to 7050C. Strain range predictions from the EPP evaluation of the two-bar tests were also evaluated and compared with the experimental results. The role of sustained primary loading on cyclic life was assessed using the results of pressurized SMT data from tests on Alloy 617 at 9500C. A viscoplastic material model was used in an analytic simulation of two-bar tests to compare with EPP strain limits assessments using isochronous stress strain curves that are consistent with the viscoplastic material model. A finite element model of a prior 304H stainless steel Oak Ridge National Laboratory (ORNL) nozzle-to-sphere test was developed and used for an EPP strain limits and creep-fatigue code case damage evaluations. A theoretical treatment of a recurring issue with convergence criteria for plastic shakedown illustrated the role of computer machine precision in EPP calculations.« less

On the effect of model parameters on forecast objects

NASA Astrophysics Data System (ADS)

Marzban, Caren; Jones, Corinne; Li, Ning; Sandgathe, Scott

2018-04-01

Many physics-based numerical models produce a gridded, spatial field of forecasts, e.g., a temperature map. The field for some quantities generally consists of spatially coherent and disconnected objects. Such objects arise in many problems, including precipitation forecasts in atmospheric models, eddy currents in ocean models, and models of forest fires. Certain features of these objects (e.g., location, size, intensity, and shape) are generally of interest. Here, a methodology is developed for assessing the impact of model parameters on the features of forecast objects. The main ingredients of the methodology include the use of (1) Latin hypercube sampling for varying the values of the model parameters, (2) statistical clustering algorithms for identifying objects, (3) multivariate multiple regression for assessing the impact of multiple model parameters on the distribution (across the forecast domain) of object features, and (4) methods for reducing the number of hypothesis tests and controlling the resulting errors. The final output of the methodology is a series of box plots and confidence intervals that visually display the sensitivities. The methodology is demonstrated on precipitation forecasts from a mesoscale numerical weather prediction model.

Application of multimedia models for screening assessment of long-range transport potential and overall persistence.

PubMed

Klasmeier, Jörg; Matthies, Michael; Macleod, Matthew; Fenner, Kathrin; Scheringer, Martin; Stroebe, Maximilian; Le Gall, Anne Christine; Mckone, Thomas; Van De Meent, Dik; Wania, Frank

2006-01-01

We propose a multimedia model-based methodology to evaluate whether a chemical substance qualifies as POP-like based on overall persistence (Pov) and potential for long-range transport (LRTP). It relies upon screening chemicals against the Pov and LRTP characteristics of selected reference chemicals with well-established environmental fates. Results indicate that chemicals of high and low concern in terms of persistence and long-range transport can be consistently identified by eight contemporary multimedia models using the proposed methodology. Model results for three hypothetical chemicals illustrate that the model-based classification of chemicals according to Pov and LRTP is not always consistent with the single-media half-life approach proposed by the UNEP Stockholm Convention and thatthe models provide additional insight into the likely long-term hazards associated with chemicals in the environment. We suggest this model-based classification method be adopted as a complement to screening against defined half-life criteria at the initial stages of tiered assessments designed to identify POP-like chemicals and to prioritize further environmental fate studies for new and existing chemicals.

Model-driven methodology for rapid deployment of smart spaces based on resource-oriented architectures.

PubMed

Corredor, Iván; Bernardos, Ana M; Iglesias, Josué; Casar, José R

2012-01-01

Advances in electronics nowadays facilitate the design of smart spaces based on physical mash-ups of sensor and actuator devices. At the same time, software paradigms such as Internet of Things (IoT) and Web of Things (WoT) are motivating the creation of technology to support the development and deployment of web-enabled embedded sensor and actuator devices with two major objectives: (i) to integrate sensing and actuating functionalities into everyday objects, and (ii) to easily allow a diversity of devices to plug into the Internet. Currently, developers who are applying this Internet-oriented approach need to have solid understanding about specific platforms and web technologies. In order to alleviate this development process, this research proposes a Resource-Oriented and Ontology-Driven Development (ROOD) methodology based on the Model Driven Architecture (MDA). This methodology aims at enabling the development of smart spaces through a set of modeling tools and semantic technologies that support the definition of the smart space and the automatic generation of code at hardware level. ROOD feasibility is demonstrated by building an adaptive health monitoring service for a Smart Gym.

Stochastic output error vibration-based damage detection and assessment in structures under earthquake excitation

NASA Astrophysics Data System (ADS)

Sakellariou, J. S.; Fassois, S. D.

2006-11-01

A stochastic output error (OE) vibration-based methodology for damage detection and assessment (localization and quantification) in structures under earthquake excitation is introduced. The methodology is intended for assessing the state of a structure following potential damage occurrence by exploiting vibration signal measurements produced by low-level earthquake excitations. It is based upon (a) stochastic OE model identification, (b) statistical hypothesis testing procedures for damage detection, and (c) a geometric method (GM) for damage assessment. The methodology's advantages include the effective use of the non-stationary and limited duration earthquake excitation, the handling of stochastic uncertainties, the tackling of the damage localization and quantification subproblems, the use of "small" size, simple and partial (in both the spatial and frequency bandwidth senses) identified OE-type models, and the use of a minimal number of measured vibration signals. Its feasibility and effectiveness are assessed via Monte Carlo experiments employing a simple simulation model of a 6 storey building. It is demonstrated that damage levels of 5% and 20% reduction in a storey's stiffness characteristics may be properly detected and assessed using noise-corrupted vibration signals.

Horizon Mission Methodology - A tool for the study of technology innovation and new paradigms

NASA Technical Reports Server (NTRS)

Anderson, John L.

1993-01-01

The Horizon Mission (HM) methodology was developed to provide a means of identifying and evaluating highly innovative, breakthrough technology concepts (BTCs) and for assessing their potential impact on advanced space missions. The methodology is based on identifying new capabilities needed by hypothetical 'horizon' space missions having performance requirements that cannot be met even by extrapolating known space technologies. Normal human evaluation of new ideas such as BTCs appears to be governed (and limited) by 'inner models of reality' defined as paradigms. Thus, new ideas are evaluated by old models. This paper describes the use of the HM Methodology to define possible future paradigms that would provide alternatives to evaluation by current paradigms. The approach is to represent a future paradigm by a set of new BTC-based capabilities - called a paradigm abstract. The paper describes methods of constructing and using the abstracts for evaluating BTCs for space applications and for exploring the concept of paradigms and paradigm shifts as a representation of technology innovation.

The use of experimental design to find the operating maximum power point of PEM fuel cells

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

Crăciunescu, Aurelian; Pătularu, Laurenţiu; Ciumbulea, Gloria

2015-03-10

Proton Exchange Membrane (PEM) Fuel Cells are difficult to model due to their complex nonlinear nature. In this paper, the development of a PEM Fuel Cells mathematical model based on the Design of Experiment methodology is described. The Design of Experiment provides a very efficient methodology to obtain a mathematical model for the studied multivariable system with only a few experiments. The obtained results can be used for optimization and control of the PEM Fuel Cells systems.

Long-term ensemble forecast of snowmelt inflow into the Cheboksary Reservoir under two different weather scenarios

NASA Astrophysics Data System (ADS)

Gelfan, Alexander; Moreydo, Vsevolod; Motovilov, Yury; Solomatine, Dimitri P.

2018-04-01

A long-term forecasting ensemble methodology, applied to water inflows into the Cheboksary Reservoir (Russia), is presented. The methodology is based on a version of the semi-distributed hydrological model ECOMAG (ECOlogical Model for Applied Geophysics) that allows for the calculation of an ensemble of inflow hydrographs using two different sets of weather ensembles for the lead time period: observed weather data, constructed on the basis of the Ensemble Streamflow Prediction methodology (ESP-based forecast), and synthetic weather data, simulated by a multi-site weather generator (WG-based forecast). We have studied the following: (1) whether there is any advantage of the developed ensemble forecasts in comparison with the currently issued operational forecasts of water inflow into the Cheboksary Reservoir, and (2) whether there is any noticeable improvement in probabilistic forecasts when using the WG-simulated ensemble compared to the ESP-based ensemble. We have found that for a 35-year period beginning from the reservoir filling in 1982, both continuous and binary model-based ensemble forecasts (issued in the deterministic form) outperform the operational forecasts of the April-June inflow volume actually used and, additionally, provide acceptable forecasts of additional water regime characteristics besides the inflow volume. We have also demonstrated that the model performance measures (in the verification period) obtained from the WG-based probabilistic forecasts, which are based on a large number of possible weather scenarios, appeared to be more statistically reliable than the corresponding measures calculated from the ESP-based forecasts based on the observed weather scenarios.

Modelling Ecological Cognitive Rehabilitation Therapies for Building Virtual Environments in Brain Injury.

PubMed

Martínez-Moreno, J M; Sánchez-González, P; Luna, M; Roig, T; Tormos, J M; Gómez, E J

2016-01-01

Brain Injury (BI) has become one of the most common causes of neurological disability in developed countries. Cognitive disorders result in a loss of independence and patients' quality of life. Cognitive rehabilitation aims to promote patients' skills to achieve their highest degree of personal autonomy. New technologies such as virtual reality or interactive video allow developing rehabilitation therapies based on reproducible Activities of Daily Living (ADLs), increasing the ecological validity of the therapy. However, the lack of frameworks to formalize and represent the definition of this kind of therapies can be a barrier for widespread use of interactive virtual environments in clinical routine. To provide neuropsychologists with a methodology and an instrument to design and evaluate cognitive rehabilitation therapeutic interventions strategies based on ADLs performed in interactive virtual environments. The proposed methodology is used to model therapeutic interventions during virtual ADLs considering cognitive deficit, expected abnormal interactions and therapeutic hypotheses. It allows identifying abnormal behavioural patterns and designing interventions strategies in order to achieve errorless-based rehabilitation. An ADL case study ('buying bread') is defined according to the guidelines established by the ADL intervention model. This case study is developed, as a proof of principle, using interactive video technology and is used to assess the feasibility of the proposed methodology in the definition of therapeutic intervention procedures. The proposed methodology provides neuropsychologists with an instrument to design and evaluate ADL-based therapeutic intervention strategies, attending to solve actual limitation of virtual scenarios, to be use for ecological rehabilitation of cognitive deficit in daily clinical practice. The developed case study proves the potential of the methodology to design therapeutic interventions strategies; however our current work is devoted to designing more experiments in order to present more evidence about its values.

Deterministic Multiaxial Creep and Creep Rupture Enhancements for CARES/Creep Integrated Design Code

NASA Technical Reports Server (NTRS)

Jadaan, Osama M.

1998-01-01

High temperature and long duration applications of monolithic ceramics can place their failure mode in the creep rupture regime. A previous model advanced by the authors described a methodology by which the creep rupture life of a loaded component can be predicted. That model was based on the life fraction damage accumulation rule in association with the modified Monkman-Grant creep rupture criterion. However, that model did not take into account the deteriorating state of the material due to creep damage (e.g., cavitation) as time elapsed. In addition, the material creep parameters used in that life prediction methodology, were based on uniaxial creep curves displaying primary and secondary creep behavior, with no tertiary regime. The objective of this paper is to present a creep life prediction methodology based on a modified form of the Kachanov-Rabotnov continuum damage mechanics (CDM) theory. In this theory, the uniaxial creep rate is described in terms of sum, temperature, time, and the current state of material damage. This scalar damage state parameter is basically an abstract measure of the current state of material damage due to creep deformation. The damage rate is assumed to vary with stress, temperature, time, and the current state of damage itself. Multiaxial creep and creep rupture formulations of the CDM approach are presented in this paper. Parameter estimation methodologies based on nonlinear regression analysis are also described for both, isothermal constant stress states and anisothermal variable stress conditions This creep life prediction methodology was preliminarily added to the integrated design code CARES/Creep (Ceramics Analysis and Reliability Evaluation of Structures/Creep), which is a postprocessor program to commercially available finite element analysis (FEA) packages. Two examples, showing comparisons between experimental and predicted creep lives of ceramic specimens, are used to demonstrate the viability of Ns methodology and the CARES/Creep program.

Deterministic and Probabilistic Creep and Creep Rupture Enhancement to CARES/Creep: Multiaxial Creep Life Prediction of Ceramic Structures Using Continuum Damage Mechanics and the Finite Element Method

NASA Technical Reports Server (NTRS)

Jadaan, Osama M.; Powers, Lynn M.; Gyekenyesi, John P.

1998-01-01

High temperature and long duration applications of monolithic ceramics can place their failure mode in the creep rupture regime. A previous model advanced by the authors described a methodology by which the creep rupture life of a loaded component can be predicted. That model was based on the life fraction damage accumulation rule in association with the modified Monkman-Grant creep ripture criterion However, that model did not take into account the deteriorating state of the material due to creep damage (e.g., cavitation) as time elapsed. In addition, the material creep parameters used in that life prediction methodology, were based on uniaxial creep curves displaying primary and secondary creep behavior, with no tertiary regime. The objective of this paper is to present a creep life prediction methodology based on a modified form of the Kachanov-Rabotnov continuum damage mechanics (CDM) theory. In this theory, the uniaxial creep rate is described in terms of stress, temperature, time, and the current state of material damage. This scalar damage state parameter is basically an abstract measure of the current state of material damage due to creep deformation. The damage rate is assumed to vary with stress, temperature, time, and the current state of damage itself. Multiaxial creep and creep rupture formulations of the CDM approach are presented in this paper. Parameter estimation methodologies based on nonlinear regression analysis are also described for both, isothermal constant stress states and anisothermal variable stress conditions This creep life prediction methodology was preliminarily added to the integrated design code CARES/Creep (Ceramics Analysis and Reliability Evaluation of Structures/Creep), which is a postprocessor program to commercially available finite element analysis (FEA) packages. Two examples, showing comparisons between experimental and predicted creep lives of ceramic specimens, are used to demonstrate the viability of this methodology and the CARES/Creep program.

Optical modeling based on mean free path calculations for quantum dot phosphors applied to optoelectronic devices.

PubMed

Shin, Min-Ho; Kim, Hyo-Jun; Kim, Young-Joo

2017-02-20

We proposed an optical simulation model for the quantum dot (QD) nanophosphor based on the mean free path concept to understand precisely the optical performance of optoelectronic devices. A measurement methodology was also developed to get the desired optical characteristics such as the mean free path and absorption spectra for QD nanophosphors which are to be incorporated into the simulation. The simulation results for QD-based white LED and OLED displays show good agreement with the experimental values from the fabricated devices in terms of spectral power distribution, chromaticity coordinate, CCT, and CRI. The proposed simulation model and measurement methodology can be applied easily to the design of lots of optoelectronics devices using QD nanophosphors to obtain high efficiency and the desired color characteristics.

Method and system for dynamic probabilistic risk assessment

NASA Technical Reports Server (NTRS)

Dugan, Joanne Bechta (Inventor); Xu, Hong (Inventor)

2013-01-01

The DEFT methodology, system and computer readable medium extends the applicability of the PRA (Probabilistic Risk Assessment) methodology to computer-based systems, by allowing DFT (Dynamic Fault Tree) nodes as pivot nodes in the Event Tree (ET) model. DEFT includes a mathematical model and solution algorithm, supports all common PRA analysis functions and cutsets. Additional capabilities enabled by the DFT include modularization, phased mission analysis, sequence dependencies, and imperfect coverage.

Methodology for estimating human perception to tremors in high-rise buildings

NASA Astrophysics Data System (ADS)

Du, Wenqi; Goh, Key Seng; Pan, Tso-Chien

2017-07-01

Human perception to tremors during earthquakes in high-rise buildings is usually associated with psychological discomfort such as fear and anxiety. This paper presents a methodology for estimating the level of perception to tremors for occupants living in high-rise buildings subjected to ground motion excitations. Unlike other approaches based on empirical or historical data, the proposed methodology performs a regression analysis using the analytical results of two generic models of 15 and 30 stories. The recorded ground motions in Singapore are collected and modified for structural response analyses. Simple predictive models are then developed to estimate the perception level to tremors based on a proposed ground motion intensity parameter—the average response spectrum intensity in the period range between 0.1 and 2.0 s. These models can be used to predict the percentage of occupants in high-rise buildings who may perceive the tremors at a given ground motion intensity. Furthermore, the models are validated with two recent tremor events reportedly felt in Singapore. It is found that the estimated results match reasonably well with the reports in the local newspapers and from the authorities. The proposed methodology is applicable to urban regions where people living in high-rise buildings might feel tremors during earthquakes.

Simulating large-scale pedestrian movement using CA and event driven model: Methodology and case study

NASA Astrophysics Data System (ADS)

Li, Jun; Fu, Siyao; He, Haibo; Jia, Hongfei; Li, Yanzhong; Guo, Yi

2015-11-01

Large-scale regional evacuation is an important part of national security emergency response plan. Large commercial shopping area, as the typical service system, its emergency evacuation is one of the hot research topics. A systematic methodology based on Cellular Automata with the Dynamic Floor Field and event driven model has been proposed, and the methodology has been examined within context of a case study involving the evacuation within a commercial shopping mall. Pedestrians walking is based on Cellular Automata and event driven model. In this paper, the event driven model is adopted to simulate the pedestrian movement patterns, the simulation process is divided into normal situation and emergency evacuation. The model is composed of four layers: environment layer, customer layer, clerk layer and trajectory layer. For the simulation of movement route of pedestrians, the model takes into account purchase intention of customers and density of pedestrians. Based on evacuation model of Cellular Automata with Dynamic Floor Field and event driven model, we can reflect behavior characteristics of customers and clerks at the situations of normal and emergency evacuation. The distribution of individual evacuation time as a function of initial positions and the dynamics of the evacuation process is studied. Our results indicate that the evacuation model using the combination of Cellular Automata with Dynamic Floor Field and event driven scheduling can be used to simulate the evacuation of pedestrian flows in indoor areas with complicated surroundings and to investigate the layout of shopping mall.

Bayesian outcome-based strategy classification.

PubMed

Lee, Michael D

2016-03-01

Hilbig and Moshagen (Psychonomic Bulletin & Review, 21, 1431-1443, 2014) recently developed a method for making inferences about the decision processes people use in multi-attribute forced choice tasks. Their paper makes a number of worthwhile theoretical and methodological contributions. Theoretically, they provide an insightful psychological motivation for a probabilistic extension of the widely-used "weighted additive" (WADD) model, and show how this model, as well as other important models like "take-the-best" (TTB), can and should be expressed in terms of meaningful priors. Methodologically, they develop an inference approach based on the Minimum Description Length (MDL) principles that balances both the goodness-of-fit and complexity of the decision models they consider. This paper aims to preserve these useful contributions, but provide a complementary Bayesian approach with some theoretical and methodological advantages. We develop a simple graphical model, implemented in JAGS, that allows for fully Bayesian inferences about which models people use to make decisions. To demonstrate the Bayesian approach, we apply it to the models and data considered by Hilbig and Moshagen (Psychonomic Bulletin & Review, 21, 1431-1443, 2014), showing how a prior predictive analysis of the models, and posterior inferences about which models people use and the parameter settings at which they use them, can contribute to our understanding of human decision making.

Methodology based on genetic heuristics for in-vivo characterizing the patient-specific biomechanical behavior of the breast tissues

PubMed Central

Lago, M. A.; Rúperez, M. J.; Martínez-Martínez, F.; Martínez-Sanchis, S.; Bakic, P. R.; Monserrat, C.

2015-01-01

This paper presents a novel methodology to in-vivo estimate the elastic constants of a constitutive model proposed to characterize the mechanical behavior of the breast tissues. An iterative search algorithm based on genetic heuristics was constructed to in-vivo estimate these parameters using only medical images, thus avoiding invasive measurements of the mechanical response of the breast tissues. For the first time, a combination of overlap and distance coefficients were used for the evaluation of the similarity between a deformed MRI of the breast and a simulation of that deformation. The methodology was validated using breast software phantoms for virtual clinical trials, compressed to mimic MRI-guided biopsies. The biomechanical model chosen to characterize the breast tissues was an anisotropic neo-Hookean hyperelastic model. Results from this analysis showed that the algorithm is able to find the elastic constants of the constitutive equations of the proposed model with a mean relative error of about 10%. Furthermore, the overlap between the reference deformation and the simulated deformation was of around 95% showing the good performance of the proposed methodology. This methodology can be easily extended to characterize the real biomechanical behavior of the breast tissues, which means a great novelty in the field of the simulation of the breast behavior for applications such as surgical planing, surgical guidance or cancer diagnosis. This reveals the impact and relevance of the presented work. PMID:27103760

Methodology based on genetic heuristics for in-vivo characterizing the patient-specific biomechanical behavior of the breast tissues.

PubMed

Lago, M A; Rúperez, M J; Martínez-Martínez, F; Martínez-Sanchis, S; Bakic, P R; Monserrat, C

2015-11-30

This paper presents a novel methodology to in-vivo estimate the elastic constants of a constitutive model proposed to characterize the mechanical behavior of the breast tissues. An iterative search algorithm based on genetic heuristics was constructed to in-vivo estimate these parameters using only medical images, thus avoiding invasive measurements of the mechanical response of the breast tissues. For the first time, a combination of overlap and distance coefficients were used for the evaluation of the similarity between a deformed MRI of the breast and a simulation of that deformation. The methodology was validated using breast software phantoms for virtual clinical trials, compressed to mimic MRI-guided biopsies. The biomechanical model chosen to characterize the breast tissues was an anisotropic neo-Hookean hyperelastic model. Results from this analysis showed that the algorithm is able to find the elastic constants of the constitutive equations of the proposed model with a mean relative error of about 10%. Furthermore, the overlap between the reference deformation and the simulated deformation was of around 95% showing the good performance of the proposed methodology. This methodology can be easily extended to characterize the real biomechanical behavior of the breast tissues, which means a great novelty in the field of the simulation of the breast behavior for applications such as surgical planing, surgical guidance or cancer diagnosis. This reveals the impact and relevance of the presented work.

Evaluation of Model-Based Training for Vertical Guidance Logic

NASA Technical Reports Server (NTRS)

Feary, Michael; Palmer, Everett; Sherry, Lance; Polson, Peter; Alkin, Marty; McCrobie, Dan; Kelley, Jerry; Rosekind, Mark (Technical Monitor)

1997-01-01

This paper will summarize the results of a study which introduces a structured, model based approach to learning how the automated vertical guidance system works on a modern commercial air transport. The study proposes a framework to provide accurate and complete information in an attempt to eliminate confusion about 'what the system is doing'. This study will examine a structured methodology for organizing the ideas on which the system was designed, communicating this information through the training material, and displaying it in the airplane. Previous research on model-based, computer aided instructional technology has shown reductions in the amount of time to a specified level of competence. The lessons learned from the development of these technologies are well suited for use with the design methodology which was used to develop the vertical guidance logic for a large commercial air transport. The design methodology presents the model from which to derive the training material, and the content of information to be displayed to the operator. The study consists of a 2 X 2 factorial experiment which will compare a new method of training vertical guidance logic and a new type of display. The format of the material used to derive both the training and the display will be provided by the Operational Procedure Methodology. The training condition will compare current training material to the new structured format. The display condition will involve a change of the content of the information displayed into pieces that agree with the concepts with which the system was designed.

Model Based Verification of Cyber Range Event Environments

DTIC Science & Technology

2015-12-10

Model Based Verification of Cyber Range Event Environments Suresh K. Damodaran MIT Lincoln Laboratory 244 Wood St., Lexington, MA, USA...apply model based verification to cyber range event environment configurations, allowing for the early detection of errors in event environment...Environment Representation (CCER) ontology. We also provide an overview of a methodology to specify verification rules and the corresponding error

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

ERIC Educational Resources Information Center

Shroff, Ronnie H.; Deneen, Christopher

2011-01-01

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

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

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

Paul M. Torrens; Atsushi Nara; Xun Li

2012-01-01

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

A multicriteria decision making model for assessment and selection of an ERP in a logistics context

NASA Astrophysics Data System (ADS)

Pereira, Teresa; Ferreira, Fernanda A.

2017-07-01

The aim of this work is to apply a methodology of decision support based on a multicriteria decision analyses (MCDA) model that allows the assessment and selection of an Enterprise Resource Planning (ERP) in a Portuguese logistics company by Group Decision Maker (GDM). A Decision Support system (DSS) that implements a MCDA - Multicriteria Methodology for the Assessment and Selection of Information Systems / Information Technologies (MMASSI / IT) is used based on its features and facility to change and adapt the model to a given scope. Using this DSS it was obtained the information system that best suited to the decisional context, being this result evaluated through a sensitivity and robustness analysis.

Fault Diagnosis approach based on a model-based reasoner and a functional designer for a wind turbine. An approach towards self-maintenance

NASA Astrophysics Data System (ADS)

Echavarria, E.; Tomiyama, T.; van Bussel, G. J. W.

2007-07-01

The objective of this on-going research is to develop a design methodology to increase the availability for offshore wind farms, by means of an intelligent maintenance system capable of responding to faults by reconfiguring the system or subsystems, without increasing service visits, complexity, or costs. The idea is to make use of the existing functional redundancies within the system and sub-systems to keep the wind turbine operational, even at a reduced capacity if necessary. Re-configuration is intended to be a built-in capability to be used as a repair strategy, based on these existing functionalities provided by the components. The possible solutions can range from using information from adjacent wind turbines, such as wind speed and direction, to setting up different operational modes, for instance re-wiring, re-connecting, changing parameters or control strategy. The methodology described in this paper is based on qualitative physics and consists of a fault diagnosis system based on a model-based reasoner (MBR), and on a functional redundancy designer (FRD). Both design tools make use of a function-behaviour-state (FBS) model. A design methodology based on the re-configuration concept to achieve self-maintained wind turbines is an interesting and promising approach to reduce stoppage rate, failure events, maintenance visits, and to maintain energy output possibly at reduced rate until the next scheduled maintenance.

Advances in Structural Integrity Analysis Methods for Aging Metallic Airframe Structures with Local Damage

NASA Technical Reports Server (NTRS)

Starnes, James H., Jr.; Newman, James C., Jr.; Harris, Charles E.; Piascik, Robert S.; Young, Richard D.; Rose, Cheryl A.

2003-01-01

Analysis methodologies for predicting fatigue-crack growth from rivet holes in panels subjected to cyclic loads and for predicting the residual strength of aluminum fuselage structures with cracks and subjected to combined internal pressure and mechanical loads are described. The fatigue-crack growth analysis methodology is based on small-crack theory and a plasticity induced crack-closure model, and the effect of a corrosive environment on crack-growth rate is included. The residual strength analysis methodology is based on the critical crack-tip-opening-angle fracture criterion that characterizes the fracture behavior of a material of interest, and a geometric and material nonlinear finite element shell analysis code that performs the structural analysis of the fuselage structure of interest. The methodologies have been verified experimentally for structures ranging from laboratory coupons to full-scale structural components. Analytical and experimental results based on these methodologies are described and compared for laboratory coupons and flat panels, small-scale pressurized shells, and full-scale curved stiffened panels. The residual strength analysis methodology is sufficiently general to include the effects of multiple-site damage on structural behavior.

Assessing the impact of modeling limits on intelligent systems

NASA Technical Reports Server (NTRS)

Rouse, William B.; Hammer, John M.

1990-01-01

The knowledge bases underlying intelligent systems are validated. A general conceptual framework is provided for considering the roles in intelligent systems of models of physical, behavioral, and operational phenomena. A methodology is described for identifying limits in particular intelligent systems, and the use of the methodology is illustrated via an experimental evaluation of the pilot-vehicle interface within the Pilot's Associate. The requirements and functionality are outlined for a computer based knowledge engineering environment which would embody the approach advocated and illustrated in earlier discussions. Issues considered include the specific benefits of this functionality, the potential breadth of applicability, and technical feasibility.

A methodology aimed at fostering and sustaining the development processes of an IE-based industry

NASA Astrophysics Data System (ADS)

Corallo, Angelo; Errico, Fabrizio; de Maggio, Marco; Giangreco, Enza

In the current competitive scenario, where business relationships are fundamental in building successful business models and inter/intra organizational business processes are progressively digitalized, an end-to-end methodology is required that is capable of guiding business networks through the Internetworked Enterprise (IE) paradigm: a new and innovative organizational model able to leverage Internet technologies to perform real-time coordination of intra and inter-firm activities, to create value by offering innovative and personalized products/services and reduce transaction costs. This chapter presents the TEKNE project Methodology of change that guides business networks, by means of a modular and flexible approach, towards the IE techno-organizational paradigm, taking into account the competitive environment of the network and how this environment influences its strategic, organizational and technological levels. Contingency, the business model, enterprise architecture and performance metrics are the key concepts that form the cornerstone of this methodological framework.

A methodology to enhance electromagnetic compatibility in joint military operations

NASA Astrophysics Data System (ADS)

Buckellew, William R.

The development and validation of an improved methodology to identify, characterize, and prioritize potential joint EMI (electromagnetic interference) interactions and identify and develop solutions to reduce the effects of the interference are discussed. The methodology identifies potential EMI problems using results from field operations, historical data bases, and analytical modeling. Operational expertise, engineering analysis, and testing are used to characterize and prioritize the potential EMI problems. Results can be used to resolve potential EMI during the development and acquisition of new systems and to develop engineering fixes and operational workarounds for systems already employed. The analytic modeling portion of the methodology is a predictive process that uses progressive refinement of the analysis and the operational electronic environment to eliminate noninterfering equipment pairs, defer further analysis on pairs lacking operational significance, and resolve the remaining EMI problems. Tests are conducted on equipment pairs to ensure that the analytical models provide a realistic description of the predicted interference.

Development of Innovative Business Model of Modern Manager's Qualities

ERIC Educational Resources Information Center

Yashkova, Elena V.; Sineva, Nadezda L.; Shkunova, Angelika A.; Bystrova, Natalia V.; Smirnova, Zhanna V.; Kolosova, Tatyana V.

2016-01-01

The paper defines a complex of manager's qualities based on theoretical and methodological analysis and synthesis methods, available national and world literature, research papers and publications. The complex approach methodology was used, which provides an innovative view of the development of modern manager's qualities. The methodological…

CAMCE: An Environment to Support Multimedia Courseware Projects.

ERIC Educational Resources Information Center

Barrese, R. M.; And Others

1992-01-01

Presents results of CAMCE (Computer-Aided Multimedia Courseware Engineering) project research concerned with definition of a methodology to describe a systematic approach for multimedia courseware development. Discussion covers the CAMCE methodology, requirements of an advanced authoring environment, use of an object-based model in the CAMCE…

Non-linear mixed effects modeling - from methodology and software development to driving implementation in drug development science.

PubMed

Pillai, Goonaseelan Colin; Mentré, France; Steimer, Jean-Louis

2005-04-01

Few scientific contributions have made significant impact unless there was a champion who had the vision to see the potential for its use in seemingly disparate areas-and who then drove active implementation. In this paper, we present a historical summary of the development of non-linear mixed effects (NLME) modeling up to the more recent extensions of this statistical methodology. The paper places strong emphasis on the pivotal role played by Lewis B. Sheiner (1940-2004), who used this statistical methodology to elucidate solutions to real problems identified in clinical practice and in medical research and on how he drove implementation of the proposed solutions. A succinct overview of the evolution of the NLME modeling methodology is presented as well as ideas on how its expansion helped to provide guidance for a more scientific view of (model-based) drug development that reduces empiricism in favor of critical quantitative thinking and decision making.

Methodology for Uncertainty Analysis of Dynamic Computational Toxicology Models

EPA Science Inventory

The task of quantifying the uncertainty in both parameter estimates and model predictions has become more important with the increased use of dynamic computational toxicology models by the EPA. Dynamic toxicological models include physiologically-based pharmacokinetic (PBPK) mode...

Modeling Students' Problem Solving Performance in the Computer-Based Mathematics Learning Environment

ERIC Educational Resources Information Center

Lee, Young-Jin

2017-01-01

Purpose: The purpose of this paper is to develop a quantitative model of problem solving performance of students in the computer-based mathematics learning environment. Design/methodology/approach: Regularized logistic regression was used to create a quantitative model of problem solving performance of students that predicts whether students can…

Bashing Positivism and Reversing a Medical Model under the Guise of Evidence

ERIC Educational Resources Information Center

Wampold, Bruce E.

2003-01-01

In her advocacy of a model to train counseling psychologists as "evidence-based practitioners," Chwalisz (2003) (this issue) criticizes research based on positivism and advocates for methodological pluralism but ironically suggests the adoption of a medical model to influence the discourse on practice. In this comment, the author examines (a)…

Logic-based models in systems biology: a predictive and parameter-free network analysis method†

PubMed Central

Wynn, Michelle L.; Consul, Nikita; Merajver, Sofia D.

2012-01-01

Highly complex molecular networks, which play fundamental roles in almost all cellular processes, are known to be dysregulated in a number of diseases, most notably in cancer. As a consequence, there is a critical need to develop practical methodologies for constructing and analysing molecular networks at a systems level. Mathematical models built with continuous differential equations are an ideal methodology because they can provide a detailed picture of a network’s dynamics. To be predictive, however, differential equation models require that numerous parameters be known a priori and this information is almost never available. An alternative dynamical approach is the use of discrete logic-based models that can provide a good approximation of the qualitative behaviour of a biochemical system without the burden of a large parameter space. Despite their advantages, there remains significant resistance to the use of logic-based models in biology. Here, we address some common concerns and provide a brief tutorial on the use of logic-based models, which we motivate with biological examples. PMID:23072820

A systematic literature review of the key challenges for developing the structure of public health economic models.

PubMed

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

2016-04-01

To identify the key methodological challenges for public health economic modelling and set an agenda for future research. An iterative literature search identified papers describing methodological challenges for developing the structure of public health economic models. Additional multidisciplinary literature searches helped expand upon important ideas raised within the review. Fifteen articles were identified within the formal literature search, highlighting three key challenges: inclusion of non-healthcare costs and outcomes; inclusion of equity; and modelling complex systems and multi-component interventions. Based upon these and multidisciplinary searches about dynamic complexity, the social determinants of health, and models of human behaviour, six areas for future research were specified. Future research should focus on: the use of systems approaches within health economic modelling; approaches to assist the systematic consideration of the social determinants of health; methods for incorporating models of behaviour and social interactions; consideration of equity; and methodology to help modellers develop valid, credible and transparent public health economic model structures.

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.

Case formulation and management using pattern-based formulation (PBF) methodology: clinical case 1.

PubMed

Fernando, Irosh; Cohen, Martin

2014-02-01

A tool for psychiatric case formulation known as pattern-based formulation (PBF) has been recently introduced. This paper presents an application of this methodology in formulating and managing complex clinical cases. The symptomatology of the clinical presentation has been parsed into individual clinical phenomena and interpreted by selecting explanatory models. The clinical presentation demonstrates how PBF has been used as a clinical tool to guide clinicians' thinking, that takes a structured approach to manage multiple issues using a broad range of management strategies. In doing so, the paper also introduces a number of patterns related to the observed clinical phenomena that can be re-used as explanatory models when formulating other clinical cases. It is expected that this paper will assist clinicians, and particularly trainees, to better understand PBF methodology and apply it to improve their formulation skills.

Integrating the human element into the systems engineering process and MBSE methodology

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

Tadros, Michael Samir

In response to the challenges related to the increasing size and complexity of systems, organizations have recognized the need to integrate human considerations in the beginning stages of systems development. Human Systems Integration (HSI) seeks to accomplish this objective by incorporating human factors within systems engineering (SE) processes and methodologies, which is the focus of this paper. A representative set of HSI methods from multiple sources are organized, analyzed, and mapped to the systems engineering Vee-model. These methods are then consolidated and evaluated against the SE process and Models-Based Systems Engineering (MBSE) methodology to determine where and how they couldmore » integrate within systems development activities in the form of specific enhancements. Overall conclusions based on these evaluations are presented and future research areas are proposed.« less

Universal Verification Methodology Based Register Test Automation Flow.

PubMed

Woo, Jae Hun; Cho, Yong Kwan; Park, Sun Kyu

2016-05-01

In today's SoC design, the number of registers has been increased along with complexity of hardware blocks. Register validation is a time-consuming and error-pron task. Therefore, we need an efficient way to perform verification with less effort in shorter time. In this work, we suggest register test automation flow based UVM (Universal Verification Methodology). UVM provides a standard methodology, called a register model, to facilitate stimulus generation and functional checking of registers. However, it is not easy for designers to create register models for their functional blocks or integrate models in test-bench environment because it requires knowledge of SystemVerilog and UVM libraries. For the creation of register models, many commercial tools support a register model generation from register specification described in IP-XACT, but it is time-consuming to describe register specification in IP-XACT format. For easy creation of register model, we propose spreadsheet-based register template which is translated to IP-XACT description, from which register models can be easily generated using commercial tools. On the other hand, we also automate all the steps involved integrating test-bench and generating test-cases, so that designers may use register model without detailed knowledge of UVM or SystemVerilog. This automation flow involves generating and connecting test-bench components (e.g., driver, checker, bus adaptor, etc.) and writing test sequence for each type of register test-case. With the proposed flow, designers can save considerable amount of time to verify functionality of registers.

IFC BIM-Based Methodology for Semi-Automated Building Energy Performance Simulation

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

Bazjanac, Vladimir

2008-07-01

Building energy performance (BEP) simulation is still rarely used in building design, commissioning and operations. The process is too costly and too labor intensive, and it takes too long to deliver results. Its quantitative results are not reproducible due to arbitrary decisions and assumptions made in simulation model definition, and can be trusted only under special circumstances. A methodology to semi-automate BEP simulation preparation and execution makes this process much more effective. It incorporates principles of information science and aims to eliminate inappropriate human intervention that results in subjective and arbitrary decisions. This is achieved by automating every part ofmore » the BEP modeling and simulation process that can be automated, by relying on data from original sources, and by making any necessary data transformation rule-based and automated. This paper describes the new methodology and its relationship to IFC-based BIM and software interoperability. It identifies five steps that are critical to its implementation, and shows what part of the methodology can be applied today. The paper concludes with a discussion of application to simulation with EnergyPlus, and describes data transformation rules embedded in the new Geometry Simplification Tool (GST).« less

Model identification and vision-based H∞ position control of 6-DoF cable-driven parallel robots

NASA Astrophysics Data System (ADS)

Chellal, R.; Cuvillon, L.; Laroche, E.

2017-04-01

This paper presents methodologies for the identification and control of 6-degrees of freedom (6-DoF) cable-driven parallel robots (CDPRs). First a two-step identification methodology is proposed to accurately estimate the kinematic parameters independently and prior to the dynamic parameters of a physics-based model of CDPRs. Second, an original control scheme is developed, including a vision-based position controller tuned with the H∞ methodology and a cable tension distribution algorithm. The position is controlled in the operational space, making use of the end-effector pose measured by a motion-tracking system. A four-block H∞ design scheme with adjusted weighting filters ensures good trajectory tracking and disturbance rejection properties for the CDPR system, which is a nonlinear-coupled MIMO system with constrained states. The tension management algorithm generates control signals that maintain the cables under feasible tensions. The paper makes an extensive review of the available methods and presents an extension of one of them. The presented methodologies are evaluated by simulations and experimentally on a redundant 6-DoF INCA 6D CDPR with eight cables, equipped with a motion-tracking system.

Enhanced methods for determining operational capabilities and support costs of proposed space systems

NASA Technical Reports Server (NTRS)

Ebeling, Charles

1993-01-01

This report documents the work accomplished during the first two years of research to provide support to NASA in predicting operational and support parameters and costs of proposed space systems. The first year's research developed a methodology for deriving reliability and maintainability (R & M) parameters based upon the use of regression analysis to establish empirical relationships between performance and design specifications and corresponding mean times of failure and repair. The second year focused on enhancements to the methodology, increased scope of the model, and software improvements. This follow-on effort expands the prediction of R & M parameters and their effect on the operations and support of space transportation vehicles to include other system components such as booster rockets and external fuel tanks. It also increases the scope of the methodology and the capabilities of the model as implemented by the software. The focus is on the failure and repair of major subsystems and their impact on vehicle reliability, turn times, maintenance manpower, and repairable spares requirements. The report documents the data utilized in this study, outlines the general methodology for estimating and relating R&M parameters, presents the analyses and results of application to the initial data base, and describes the implementation of the methodology through the use of a computer model. The report concludes with a discussion on validation and a summary of the research findings and results.

Research Methods in Healthcare Epidemiology and Antimicrobial Stewardship-Mathematical Modeling.

PubMed

Barnes, Sean L; Kasaie, Parastu; Anderson, Deverick J; Rubin, Michael

2016-11-01

Mathematical modeling is a valuable methodology used to study healthcare epidemiology and antimicrobial stewardship, particularly when more traditional study approaches are infeasible, unethical, costly, or time consuming. We focus on 2 of the most common types of mathematical modeling, namely compartmental modeling and agent-based modeling, which provide important advantages-such as shorter developmental timelines and opportunities for extensive experimentation-over observational and experimental approaches. We summarize these advantages and disadvantages via specific examples and highlight recent advances in the methodology. A checklist is provided to serve as a guideline in the development of mathematical models in healthcare epidemiology and antimicrobial stewardship. Infect Control Hosp Epidemiol 2016;1-7.

mRNA translation and protein synthesis: an analysis of different modelling methodologies and a new PBN based approach

PubMed Central

2014-01-01

Background mRNA translation involves simultaneous movement of multiple ribosomes on the mRNA and is also subject to regulatory mechanisms at different stages. Translation can be described by various codon-based models, including ODE, TASEP, and Petri net models. Although such models have been extensively used, the overlap and differences between these models and the implications of the assumptions of each model has not been systematically elucidated. The selection of the most appropriate modelling framework, and the most appropriate way to develop coarse-grained/fine-grained models in different contexts is not clear. Results We systematically analyze and compare how different modelling methodologies can be used to describe translation. We define various statistically equivalent codon-based simulation algorithms and analyze the importance of the update rule in determining the steady state, an aspect often neglected. Then a novel probabilistic Boolean network (PBN) model is proposed for modelling translation, which enjoys an exact numerical solution. This solution matches those of numerical simulation from other methods and acts as a complementary tool to analytical approximations and simulations. The advantages and limitations of various codon-based models are compared, and illustrated by examples with real biological complexities such as slow codons, premature termination and feedback regulation. Our studies reveal that while different models gives broadly similiar trends in many cases, important differences also arise and can be clearly seen, in the dependence of the translation rate on different parameters. Furthermore, the update rule affects the steady state solution. Conclusions The codon-based models are based on different levels of abstraction. Our analysis suggests that a multiple model approach to understanding translation allows one to ascertain which aspects of the conclusions are robust with respect to the choice of modelling methodology, and when (and why) important differences may arise. This approach also allows for an optimal use of analysis tools, which is especially important when additional complexities or regulatory mechanisms are included. This approach can provide a robust platform for dissecting translation, and results in an improved predictive framework for applications in systems and synthetic biology. PMID:24576337

Calibration Modeling Methodology to Optimize Performance for Low Range Applications

NASA Technical Reports Server (NTRS)

McCollum, Raymond A.; Commo, Sean A.; Parker, Peter A.

2010-01-01

Calibration is a vital process in characterizing the performance of an instrument in an application environment and seeks to obtain acceptable accuracy over the entire design range. Often, project requirements specify a maximum total measurement uncertainty, expressed as a percent of full-scale. However in some applications, we seek to obtain enhanced performance at the low range, therefore expressing the accuracy as a percent of reading should be considered as a modeling strategy. For example, it is common to desire to use a force balance in multiple facilities or regimes, often well below its designed full-scale capacity. This paper presents a general statistical methodology for optimizing calibration mathematical models based on a percent of reading accuracy requirement, which has broad application in all types of transducer applications where low range performance is required. A case study illustrates the proposed methodology for the Mars Entry Atmospheric Data System that employs seven strain-gage based pressure transducers mounted on the heatshield of the Mars Science Laboratory mission.

PLACE-BASED GREEN BUILDING: INTEGRATING LOCAL ENVIRONMENTAL AND PLANNING ANALYSIS INTO GREEN BUILDING GUIDELINES

EPA Science Inventory

This project will develop a model for place-based green building guidelines based on an analysis of local environmental, social, and land use conditions. The ultimate goal of this project is to develop a methodology and model for placing green buildings within their local cont...

Performance-Based Service Quality Model: An Empirical Study on Japanese Universities

ERIC Educational Resources Information Center

Sultan, Parves; Wong, Ho

2010-01-01

Purpose: This paper aims to develop and empirically test the performance-based higher education service quality model. Design/methodology/approach: The study develops 67-item instrument for measuring performance-based service quality with a particular focus on the higher education sector. Scale reliability is confirmed using the Cronbach's alpha.…

A novelty detection diagnostic methodology for gearboxes operating under fluctuating operating conditions using probabilistic techniques

NASA Astrophysics Data System (ADS)

Schmidt, S.; Heyns, P. S.; de Villiers, J. P.

2018-02-01

In this paper, a fault diagnostic methodology is developed which is able to detect, locate and trend gear faults under fluctuating operating conditions when only vibration data from a single transducer, measured on a healthy gearbox are available. A two-phase feature extraction and modelling process is proposed to infer the operating condition and based on the operating condition, to detect changes in the machine condition. Information from optimised machine and operating condition hidden Markov models are statistically combined to generate a discrepancy signal which is post-processed to infer the condition of the gearbox. The discrepancy signal is processed and combined with statistical methods for automatic fault detection and localisation and to perform fault trending over time. The proposed methodology is validated on experimental data and a tacholess order tracking methodology is used to enhance the cost-effectiveness of the diagnostic methodology.

Allometric scaling theory applied to FIA biomass estimation

Treesearch

David C. Chojnacky

2002-01-01

Tree biomass estimates in the Forest Inventory and Analysis (FIA) database are derived from numerous methodologies whose abundance and complexity raise questions about consistent results throughout the U.S. A new model based on allometric scaling theory ("WBE") offers simplified methodology and a theoretically sound basis for improving the reliability and...

Constraint-Driven Software Design: An Escape from the Waterfall Model.

ERIC Educational Resources Information Center

de Hoog, Robert; And Others

1994-01-01

Presents the principles of a development methodology for software design based on a nonlinear, product-driven approach that integrates quality aspects. Two examples are given to show that the flexibility needed for building high quality systems leads to integrated development environments in which methodology, product, and tools are closely…

OPTIMIZATION METHODOLOGY FOR LAND USE PATTERNS-EVALUATION BASED ON MULTISCALE HABITAT PATTERN COMPARISON. (R827169)

EPA Science Inventory

In this paper, the methodological concept of landscape optimization presented by Seppelt and Voinov [Ecol. Model. 151 (2/3) (2002) 125] is analyzed. Two aspects are chosen for detailed study. First, we generalize the performance criterion to assess a vector of ecosystem functi...

Maximum likelihood estimation of signal detection model parameters for the assessment of two-stage diagnostic strategies.

PubMed

Lirio, R B; Dondériz, I C; Pérez Abalo, M C

1992-08-01

The methodology of Receiver Operating Characteristic curves based on the signal detection model is extended to evaluate the accuracy of two-stage diagnostic strategies. A computer program is developed for the maximum likelihood estimation of parameters that characterize the sensitivity and specificity of two-stage classifiers according to this extended methodology. Its use is briefly illustrated with data collected in a two-stage screening for auditory defects.

Preliminary methodology to assess the national and regional impact of U.S. wind energy development on birds and bats

USGS Publications Warehouse

Diffendorfer, James E.; Beston, Julie A.; Merrill, Matthew D.; Stanton, Jessica C.; Corum, Margo D.; Loss, Scott R.; Thogmartin, Wayne E.; Johnson, Douglas H.; Erickson, Richard A.; Heist, Kevin W.

2015-01-01

Components of the methodology are based on simplifying assumptions and require information that, for many species, may be sparse or unreliable. These assumptions are presented in the report and should be carefully considered when using output from the methodology. In addition, this methodology can be used to recommend species for more intensive demographic modeling or highlight those species that may not require any additional protection because effects of wind energy development on their populations are projected to be small.

Computational models for the analysis/design of hypersonic scramjet components. I - Combustor and nozzle models

NASA Technical Reports Server (NTRS)

Dash, S. M.; Sinha, N.; Wolf, D. E.; York, B. J.

1986-01-01

An overview of computational models developed for the complete, design-oriented analysis of a scramjet propulsion system is provided. The modular approach taken involves the use of different PNS models to analyze the individual propulsion system components. The external compression and internal inlet flowfields are analyzed by the SCRAMP and SCRINT components discussed in Part II of this paper. The combustor is analyzed by the SCORCH code which is based upon SPLITP PNS pressure-split methodology formulated by Dash and Sinha. The nozzle is analyzed by the SCHNOZ code which is based upon SCIPVIS PNS shock-capturing methodology formulated by Dash and Wolf. The current status of these models, previous developments leading to this status, and, progress towards future hybrid and 3D versions are discussed in this paper.

A Model-Based Method for Content Validation of Automatically Generated Test Items

ERIC Educational Resources Information Center

Zhang, Xinxin; Gierl, Mark

2016-01-01

The purpose of this study is to describe a methodology to recover the item model used to generate multiple-choice test items with a novel graph theory approach. Beginning with the generated test items and working backward to recover the original item model provides a model-based method for validating the content used to automatically generate test…

Hot emission model for mobile sources: application to the metropolitan region of the city of Santiago, Chile.

PubMed

Corvalán, Roberto M; Osses, Mauricio; Urrutia, Cristian M

2002-02-01

Depending on the final application, several methodologies for traffic emission estimation have been developed. Emission estimation based on total miles traveled or other average factors is a sufficient approach only for extended areas such as national or worldwide areas. For road emission control and strategies design, microscale analysis based on real-world emission estimations is often required. This involves actual driving behavior and emission factors of the local vehicle fleet under study. This paper reports on a microscale model for hot road emissions and its application to the metropolitan region of the city of Santiago, Chile. The methodology considers the street-by-street hot emission estimation with its temporal and spatial distribution. The input data come from experimental emission factors based on local driving patterns and traffic surveys of traffic flows for different vehicle categories. The methodology developed is able to estimate hourly hot road CO, total unburned hydrocarbons (THCs), particulate matter (PM), and NO(x) emissions for predefined day types and vehicle categories.

Sensitivity analysis of Repast computational ecology models with R/Repast.

PubMed

Prestes García, Antonio; Rodríguez-Patón, Alfonso

2016-12-01

Computational ecology is an emerging interdisciplinary discipline founded mainly on modeling and simulation methods for studying ecological systems. Among the existing modeling formalisms, the individual-based modeling is particularly well suited for capturing the complex temporal and spatial dynamics as well as the nonlinearities arising in ecosystems, communities, or populations due to individual variability. In addition, being a bottom-up approach, it is useful for providing new insights on the local mechanisms which are generating some observed global dynamics. Of course, no conclusions about model results could be taken seriously if they are based on a single model execution and they are not analyzed carefully. Therefore, a sound methodology should always be used for underpinning the interpretation of model results. The sensitivity analysis is a methodology for quantitatively assessing the effect of input uncertainty in the simulation output which should be incorporated compulsorily to every work based on in-silico experimental setup. In this article, we present R/Repast a GNU R package for running and analyzing Repast Simphony models accompanied by two worked examples on how to perform global sensitivity analysis and how to interpret the results.

Qualitative model-based diagnosis using possibility theory

NASA Technical Reports Server (NTRS)

Joslyn, Cliff

1994-01-01

The potential for the use of possibility in the qualitative model-based diagnosis of spacecraft systems is described. The first sections of the paper briefly introduce the Model-Based Diagnostic (MBD) approach to spacecraft fault diagnosis; Qualitative Modeling (QM) methodologies; and the concepts of possibilistic modeling in the context of Generalized Information Theory (GIT). Then the necessary conditions for the applicability of possibilistic methods to qualitative MBD, and a number of potential directions for such an application, are described.

A Design Methodology for Medical Processes.

PubMed

Ferrante, Simona; Bonacina, Stefano; Pozzi, Giuseppe; Pinciroli, Francesco; Marceglia, Sara

2016-01-01

Healthcare processes, especially those belonging to the clinical domain, are acknowledged as complex and characterized by the dynamic nature of the diagnosis, the variability of the decisions made by experts driven by their experiences, the local constraints, the patient's needs, the uncertainty of the patient's response, and the indeterminacy of patient's compliance to treatment. Also, the multiple actors involved in patient's care need clear and transparent communication to ensure care coordination. In this paper, we propose a methodology to model healthcare processes in order to break out complexity and provide transparency. The model is grounded on a set of requirements that make the healthcare domain unique with respect to other knowledge domains. The modeling methodology is based on three main phases: the study of the environmental context, the conceptual modeling, and the logical modeling. The proposed methodology was validated by applying it to the case study of the rehabilitation process of stroke patients in the specific setting of a specialized rehabilitation center. The resulting model was used to define the specifications of a software artifact for the digital administration and collection of assessment tests that was also implemented. Despite being only an example, our case study showed the ability of process modeling to answer the actual needs in healthcare practices. Independently from the medical domain in which the modeling effort is done, the proposed methodology is useful to create high-quality models, and to detect and take into account relevant and tricky situations that can occur during process execution.

Nonlinear maneuver autopilot for the F-15 aircraft

NASA Technical Reports Server (NTRS)

Menon, P. K. A.; Badgett, M. E.; Walker, R. A.

1989-01-01

A methodology is described for the development of flight test trajectory control laws based on singular perturbation methodology and nonlinear dynamic modeling. The control design methodology is applied to a detailed nonlinear six degree-of-freedom simulation of the F-15 and results for a level accelerations, pushover/pullup maneuver, zoom and pushover maneuver, excess thrust windup turn, constant thrust windup turn, and a constant dynamic pressure/constant load factor trajectory are presented.

Ethical and Legal Implications of the Methodological Crisis in Neuroimaging.

PubMed

Kellmeyer, Philipp

2017-10-01

Currently, many scientific fields such as psychology or biomedicine face a methodological crisis concerning the reproducibility, replicability, and validity of their research. In neuroimaging, similar methodological concerns have taken hold of the field, and researchers are working frantically toward finding solutions for the methodological problems specific to neuroimaging. This article examines some ethical and legal implications of this methodological crisis in neuroimaging. With respect to ethical challenges, the article discusses the impact of flawed methods in neuroimaging research in cognitive and clinical neuroscience, particularly with respect to faulty brain-based models of human cognition, behavior, and personality. Specifically examined is whether such faulty models, when they are applied to neurological or psychiatric diseases, could put patients at risk, and whether this places special obligations on researchers using neuroimaging. In the legal domain, the actual use of neuroimaging as evidence in United States courtrooms is surveyed, followed by an examination of ways that the methodological problems may create challenges for the criminal justice system. Finally, the article reviews and promotes some promising ideas and initiatives from within the neuroimaging community for addressing the methodological problems.

A Hybrid Coarse-graining Approach for Lipid Bilayers at Large Length and Time Scales

PubMed Central

Ayton, Gary S.; Voth, Gregory A.

2009-01-01

A hybrid analytic-systematic (HAS) coarse-grained (CG) lipid model is developed and employed in a large-scale simulation of a liposome. The methodology is termed hybrid analyticsystematic as one component of the interaction between CG sites is variationally determined from the multiscale coarse-graining (MS-CG) methodology, while the remaining component utilizes an analytic potential. The systematic component models the in-plane center of mass interaction of the lipids as determined from an atomistic-level MD simulation of a bilayer. The analytic component is based on the well known Gay-Berne ellipsoid of revolution liquid crystal model, and is designed to model the highly anisotropic interactions at a highly coarse-grained level. The HAS CG approach is the first step in an “aggressive” CG methodology designed to model multi-component biological membranes at very large length and timescales. PMID:19281167

Updating finite element dynamic models using an element-by-element sensitivity methodology

NASA Technical Reports Server (NTRS)

Farhat, Charbel; Hemez, Francois M.

1993-01-01

A sensitivity-based methodology for improving the finite element model of a given structure using test modal data and a few sensors is presented. The proposed method searches for both the location and sources of the mass and stiffness errors and does not interfere with the theory behind the finite element model while correcting these errors. The updating algorithm is derived from the unconstrained minimization of the squared L sub 2 norms of the modal dynamic residuals via an iterative two-step staggered procedure. At each iteration, the measured mode shapes are first expanded assuming that the model is error free, then the model parameters are corrected assuming that the expanded mode shapes are exact. The numerical algorithm is implemented in an element-by-element fashion and is capable of 'zooming' on the detected error locations. Several simulation examples which demonstate the potential of the proposed methodology are discussed.

Report of the LSPI/NASA Workshop on Lunar Base Methodology Development

NASA Technical Reports Server (NTRS)

Nozette, Stewart; Roberts, Barney

1985-01-01

Groundwork was laid for computer models which will assist in the design of a manned lunar base. The models, herein described, will provide the following functions for the successful conclusion of that task: strategic planning; sensitivity analyses; impact analyses; and documentation. Topics addressed include: upper level model description; interrelationship matrix; user community; model features; model descriptions; system implementation; model management; and plans for future action.

TOWARDS A MULTI-SCALE AGENT-BASED PROGRAMMING LANGUAGE METHODOLOGY

PubMed Central

Somogyi, Endre; Hagar, Amit; Glazier, James A.

2017-01-01

Living tissues are dynamic, heterogeneous compositions of objects, including molecules, cells and extra-cellular materials, which interact via chemical, mechanical and electrical process and reorganize via transformation, birth, death and migration processes. Current programming language have difficulty describing the dynamics of tissues because: 1: Dynamic sets of objects participate simultaneously in multiple processes, 2: Processes may be either continuous or discrete, and their activity may be conditional, 3: Objects and processes form complex, heterogeneous relationships and structures, 4: Objects and processes may be hierarchically composed, 5: Processes may create, destroy and transform objects and processes. Some modeling languages support these concepts, but most cannot translate models into executable simulations. We present a new hybrid executable modeling language paradigm, the Continuous Concurrent Object Process Methodology (CCOPM) which naturally expresses tissue models, enabling users to visually create agent-based models of tissues, and also allows computer simulation of these models. PMID:29282379

TOWARDS A MULTI-SCALE AGENT-BASED PROGRAMMING LANGUAGE METHODOLOGY.

PubMed

Somogyi, Endre; Hagar, Amit; Glazier, James A

2016-12-01

Living tissues are dynamic, heterogeneous compositions of objects , including molecules, cells and extra-cellular materials, which interact via chemical, mechanical and electrical process and reorganize via transformation, birth, death and migration processes . Current programming language have difficulty describing the dynamics of tissues because: 1: Dynamic sets of objects participate simultaneously in multiple processes, 2: Processes may be either continuous or discrete, and their activity may be conditional, 3: Objects and processes form complex, heterogeneous relationships and structures, 4: Objects and processes may be hierarchically composed, 5: Processes may create, destroy and transform objects and processes. Some modeling languages support these concepts, but most cannot translate models into executable simulations. We present a new hybrid executable modeling language paradigm, the Continuous Concurrent Object Process Methodology ( CCOPM ) which naturally expresses tissue models, enabling users to visually create agent-based models of tissues, and also allows computer simulation of these models.

New insights into soil temperature time series modeling: linear or nonlinear?

NASA Astrophysics Data System (ADS)

Bonakdari, Hossein; Moeeni, Hamid; Ebtehaj, Isa; Zeynoddin, Mohammad; Mahoammadian, Abdolmajid; Gharabaghi, Bahram

2018-03-01

Soil temperature (ST) is an important dynamic parameter, whose prediction is a major research topic in various fields including agriculture because ST has a critical role in hydrological processes at the soil surface. In this study, a new linear methodology is proposed based on stochastic methods for modeling daily soil temperature (DST). With this approach, the ST series components are determined to carry out modeling and spectral analysis. The results of this process are compared with two linear methods based on seasonal standardization and seasonal differencing in terms of four DST series. The series used in this study were measured at two stations, Champaign and Springfield, at depths of 10 and 20 cm. The results indicate that in all ST series reviewed, the periodic term is the most robust among all components. According to a comparison of the three methods applied to analyze the various series components, it appears that spectral analysis combined with stochastic methods outperformed the seasonal standardization and seasonal differencing methods. In addition to comparing the proposed methodology with linear methods, the ST modeling results were compared with the two nonlinear methods in two forms: considering hydrological variables (HV) as input variables and DST modeling as a time series. In a previous study at the mentioned sites, Kim and Singh Theor Appl Climatol 118:465-479, (2014) applied the popular Multilayer Perceptron (MLP) neural network and Adaptive Neuro-Fuzzy Inference System (ANFIS) nonlinear methods and considered HV as input variables. The comparison results signify that the relative error projected in estimating DST by the proposed methodology was about 6%, while this value with MLP and ANFIS was over 15%. Moreover, MLP and ANFIS models were employed for DST time series modeling. Due to these models' relatively inferior performance to the proposed methodology, two hybrid models were implemented: the weights and membership function of MLP and ANFIS (respectively) were optimized with the particle swarm optimization (PSO) algorithm in conjunction with the wavelet transform and nonlinear methods (Wavelet-MLP & Wavelet-ANFIS). A comparison of the proposed methodology with individual and hybrid nonlinear models in predicting DST time series indicates the lowest Akaike Information Criterion (AIC) index value, which considers model simplicity and accuracy simultaneously at different depths and stations. The methodology presented in this study can thus serve as an excellent alternative to complex nonlinear methods that are normally employed to examine DST.

Determination of Time Dependent Virus Inactivation Rates

NASA Astrophysics Data System (ADS)

Chrysikopoulos, C. V.; Vogler, E. T.

2003-12-01

A methodology is developed for estimating temporally variable virus inactivation rate coefficients from experimental virus inactivation data. The methodology consists of a technique for slope estimation of normalized virus inactivation data in conjunction with a resampling parameter estimation procedure. The slope estimation technique is based on a relatively flexible geostatistical method known as universal kriging. Drift coefficients are obtained by nonlinear fitting of bootstrap samples and the corresponding confidence intervals are obtained by bootstrap percentiles. The proposed methodology yields more accurate time dependent virus inactivation rate coefficients than those estimated by fitting virus inactivation data to a first-order inactivation model. The methodology is successfully applied to a set of poliovirus batch inactivation data. Furthermore, the importance of accurate inactivation rate coefficient determination on virus transport in water saturated porous media is demonstrated with model simulations.

A novel methodology for non-linear system identification of battery cells used in non-road hybrid electric vehicles

NASA Astrophysics Data System (ADS)

Unger, Johannes; Hametner, Christoph; Jakubek, Stefan; Quasthoff, Marcus

2014-12-01

An accurate state of charge (SoC) estimation of a traction battery in hybrid electric non-road vehicles, which possess higher dynamics and power densities than on-road vehicles, requires a precise battery cell terminal voltage model. This paper presents a novel methodology for non-linear system identification of battery cells to obtain precise battery models. The methodology comprises the architecture of local model networks (LMN) and optimal model based design of experiments (DoE). Three main novelties are proposed: 1) Optimal model based DoE, which aims to high dynamically excite the battery cells at load ranges frequently used in operation. 2) The integration of corresponding inputs in the LMN to regard the non-linearities SoC, relaxation, hysteresis as well as temperature effects. 3) Enhancements to the local linear model tree (LOLIMOT) construction algorithm, to achieve a physical appropriate interpretation of the LMN. The framework is applicable for different battery cell chemistries and different temperatures, and is real time capable, which is shown on an industrial PC. The accuracy of the obtained non-linear battery model is demonstrated on cells with different chemistries and temperatures. The results show significant improvement due to optimal experiment design and integration of the battery non-linearities within the LMN structure.

Algorithm for cellular reprogramming.

PubMed

Ronquist, Scott; Patterson, Geoff; Muir, Lindsey A; Lindsly, Stephen; Chen, Haiming; Brown, Markus; Wicha, Max S; Bloch, Anthony; Brockett, Roger; Rajapakse, Indika

2017-11-07

The day we understand the time evolution of subcellular events at a level of detail comparable to physical systems governed by Newton's laws of motion seems far away. Even so, quantitative approaches to cellular dynamics add to our understanding of cell biology. With data-guided frameworks we can develop better predictions about, and methods for, control over specific biological processes and system-wide cell behavior. Here we describe an approach for optimizing the use of transcription factors (TFs) in cellular reprogramming, based on a device commonly used in optimal control. We construct an approximate model for the natural evolution of a cell-cycle-synchronized population of human fibroblasts, based on data obtained by sampling the expression of 22,083 genes at several time points during the cell cycle. To arrive at a model of moderate complexity, we cluster gene expression based on division of the genome into topologically associating domains (TADs) and then model the dynamics of TAD expression levels. Based on this dynamical model and additional data, such as known TF binding sites and activity, we develop a methodology for identifying the top TF candidates for a specific cellular reprogramming task. Our data-guided methodology identifies a number of TFs previously validated for reprogramming and/or natural differentiation and predicts some potentially useful combinations of TFs. Our findings highlight the immense potential of dynamical models, mathematics, and data-guided methodologies for improving strategies for control over biological processes. Copyright © 2017 the Author(s). Published by PNAS.

Finite Element Method-Based Kinematics and Closed-Loop Control of Soft, Continuum Manipulators.

PubMed

Bieze, Thor Morales; Largilliere, Frederick; Kruszewski, Alexandre; Zhang, Zhongkai; Merzouki, Rochdi; Duriez, Christian

2018-06-01

This article presents a modeling methodology and experimental validation for soft manipulators to obtain forward kinematic model (FKM) and inverse kinematic model (IKM) under quasi-static conditions (in the literature, these manipulators are usually classified as continuum robots. However, their main characteristic of interest in this article is that they create motion by deformation, as opposed to the classical use of articulations). It offers a way to obtain the kinematic characteristics of this type of soft robots that is suitable for offline path planning and position control. The modeling methodology presented relies on continuum mechanics, which does not provide analytic solutions in the general case. Our approach proposes a real-time numerical integration strategy based on finite element method with a numerical optimization based on Lagrange multipliers to obtain FKM and IKM. To reduce the dimension of the problem, at each step, a projection of the model to the constraint space (gathering actuators, sensors, and end-effector) is performed to obtain the smallest number possible of mathematical equations to be solved. This methodology is applied to obtain the kinematics of two different manipulators with complex structural geometry. An experimental comparison is also performed in one of the robots, between two other geometric approaches and the approach that is showcased in this article. A closed-loop controller based on a state estimator is proposed. The controller is experimentally validated and its robustness is evaluated using Lypunov stability method.

Measurement and description of underlying dimensions of comorbid mental disorders using Factor Mixture Models: results of the ESEMeD project.

PubMed

Almansa, Josué; Vermunt, Jeroen K; Forero, Carlos G; Vilagut, Gemma; De Graaf, Ron; De Girolamo, Giovanni; Alonso, Jordi

2011-06-01

Epidemiological studies on mental health and mental comorbidity are usually based on prevalences and correlations between disorders, or some other form of bivariate clustering of disorders. In this paper, we propose a Factor Mixture Model (FMM) methodology based on conceptual models aiming to measure and summarize distinctive disorder information in the internalizing and externalizing dimensions. This methodology includes explicit modelling of subpopulations with and without 12 month disorders ("ill" and "healthy") by means of latent classes, as well as assessment of model invariance and estimation of dimensional scores. We applied this methodology with an internalizing/externalizing two-factor model, to a representative sample gathered in the European Study of the Epidemiology of Mental Disorders (ESEMeD) study -- which includes 8796 individuals from six countries, and used the CIDI 3.0 instrument for disorder assessment. Results revealed that southern European countries have significantly higher mental health levels concerning internalizing/externalizing disorders than central countries; males suffered more externalizing disorders than women did, and conversely, internalizing disorders were more frequent in women. Differences in mental-health level between socio-demographic groups were due to different proportions of healthy and ill individuals and, noticeably, to the ameliorating influence of marital status on severity. An advantage of latent model-based scores is that the inclusion of additional mental-health dimensional information -- other than diagnostic data -- allows for greater precision within a target range of scores. Copyright © 2011 John Wiley & Sons, Ltd.

Two solar proton fluence models based on ground level enhancement observations

NASA Astrophysics Data System (ADS)

Raukunen, Osku; Vainio, Rami; Tylka, Allan J.; Dietrich, William F.; Jiggens, Piers; Heynderickx, Daniel; Dierckxsens, Mark; Crosby, Norma; Ganse, Urs; Siipola, Robert

2018-01-01

Solar energetic particles (SEPs) constitute an important component of the radiation environment in interplanetary space. Accurate modeling of SEP events is crucial for the mitigation of radiation hazards in spacecraft design. In this study we present two new statistical models of high energy solar proton fluences based on ground level enhancement (GLE) observations during solar cycles 19-24. As the basis of our modeling, we utilize a four parameter double power law function (known as the Band function) fits to integral GLE fluence spectra in rigidity. In the first model, the integral and differential fluences for protons with energies between 10 MeV and 1 GeV are calculated using the fits, and the distributions of the fluences at certain energies are modeled with an exponentially cut-off power law function. In the second model, we use a more advanced methodology: by investigating the distributions and relationships of the spectral fit parameters we find that they can be modeled as two independent and two dependent variables. Therefore, instead of modeling the fluences separately at different energies, we can model the shape of the fluence spectrum. We present examples of modeling results and show that the two methodologies agree well except for a short mission duration (1 year) at low confidence level. We also show that there is a reasonable agreement between our models and three well-known solar proton models (JPL, ESP and SEPEM), despite the differences in both the modeling methodologies and the data used to construct the models.

A methodology for model-based development and automated verification of software for aerospace systems

NASA Astrophysics Data System (ADS)

Martin, L.; Schatalov, M.; Hagner, M.; Goltz, U.; Maibaum, O.

Today's software for aerospace systems typically is very complex. This is due to the increasing number of features as well as the high demand for safety, reliability, and quality. This complexity also leads to significant higher software development costs. To handle the software complexity, a structured development process is necessary. Additionally, compliance with relevant standards for quality assurance is a mandatory concern. To assure high software quality, techniques for verification are necessary. Besides traditional techniques like testing, automated verification techniques like model checking become more popular. The latter examine the whole state space and, consequently, result in a full test coverage. Nevertheless, despite the obvious advantages, this technique is rarely yet used for the development of aerospace systems. In this paper, we propose a tool-supported methodology for the development and formal verification of safety-critical software in the aerospace domain. The methodology relies on the V-Model and defines a comprehensive work flow for model-based software development as well as automated verification in compliance to the European standard series ECSS-E-ST-40C. Furthermore, our methodology supports the generation and deployment of code. For tool support we use the tool SCADE Suite (Esterel Technology), an integrated design environment that covers all the requirements for our methodology. The SCADE Suite is well established in avionics and defense, rail transportation, energy and heavy equipment industries. For evaluation purposes, we apply our approach to an up-to-date case study of the TET-1 satellite bus. In particular, the attitude and orbit control software is considered. The behavioral models for the subsystem are developed, formally verified, and optimized.

Whole-Volume Clustering of Time Series Data from Zebrafish Brain Calcium Images via Mixture Modeling.

PubMed

Nguyen, Hien D; Ullmann, Jeremy F P; McLachlan, Geoffrey J; Voleti, Venkatakaushik; Li, Wenze; Hillman, Elizabeth M C; Reutens, David C; Janke, Andrew L

2018-02-01

Calcium is a ubiquitous messenger in neural signaling events. An increasing number of techniques are enabling visualization of neurological activity in animal models via luminescent proteins that bind to calcium ions. These techniques generate large volumes of spatially correlated time series. A model-based functional data analysis methodology via Gaussian mixtures is suggested for the clustering of data from such visualizations is proposed. The methodology is theoretically justified and a computationally efficient approach to estimation is suggested. An example analysis of a zebrafish imaging experiment is presented.

A Co-modeling Method Based on Component Features for Mechatronic Devices in Aero-engines

NASA Astrophysics Data System (ADS)

Wang, Bin; Zhao, Haocen; Ye, Zhifeng

2017-08-01

Data-fused and user-friendly design of aero-engine accessories is required because of their structural complexity and stringent reliability. This paper gives an overview of a typical aero-engine control system and the development process of key mechatronic devices used. Several essential aspects of modeling and simulation in the process are investigated. Considering the limitations of a single theoretic model, feature-based co-modeling methodology is suggested to satisfy the design requirements and compensate for diversity of component sub-models for these devices. As an example, a stepper motor controlled Fuel Metering Unit (FMU) is modeled in view of the component physical features using two different software tools. An interface is suggested to integrate the single discipline models into the synthesized one. Performance simulation of this device using the co-model and parameter optimization for its key components are discussed. Comparison between delivery testing and the simulation shows that the co-model for the FMU has a high accuracy and the absolute superiority over a single model. Together with its compatible interface with the engine mathematical model, the feature-based co-modeling methodology is proven to be an effective technical measure in the development process of the device.

MUSIC-Expected maximization gaussian mixture methodology for clustering and detection of task-related neuronal firing rates.

PubMed

Ortiz-Rosario, Alexis; Adeli, Hojjat; Buford, John A

2017-01-15

Researchers often rely on simple methods to identify involvement of neurons in a particular motor task. The historical approach has been to inspect large groups of neurons and subjectively separate neurons into groups based on the expertise of the investigator. In cases where neuron populations are small it is reasonable to inspect these neuronal recordings and their firing rates carefully to avoid data omissions. In this paper, a new methodology is presented for automatic objective classification of neurons recorded in association with behavioral tasks into groups. By identifying characteristics of neurons in a particular group, the investigator can then identify functional classes of neurons based on their relationship to the task. The methodology is based on integration of a multiple signal classification (MUSIC) algorithm to extract relevant features from the firing rate and an expectation-maximization Gaussian mixture algorithm (EM-GMM) to cluster the extracted features. The methodology is capable of identifying and clustering similar firing rate profiles automatically based on specific signal features. An empirical wavelet transform (EWT) was used to validate the features found in the MUSIC pseudospectrum and the resulting signal features captured by the methodology. Additionally, this methodology was used to inspect behavioral elements of neurons to physiologically validate the model. This methodology was tested using a set of data collected from awake behaving non-human primates. Copyright © 2016 Elsevier B.V. All rights reserved.

Knowledge representation to support reasoning based on multiple models

NASA Technical Reports Server (NTRS)

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

1990-01-01

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

A hierarchical clustering methodology for the estimation of toxicity.

PubMed

Martin, Todd M; Harten, Paul; Venkatapathy, Raghuraman; Das, Shashikala; Young, Douglas M

2008-01-01

ABSTRACT A quantitative structure-activity relationship (QSAR) methodology based on hierarchical clustering was developed to predict toxicological endpoints. This methodology utilizes Ward's method to divide a training set into a series of structurally similar clusters. The structural similarity is defined in terms of 2-D physicochemical descriptors (such as connectivity and E-state indices). A genetic algorithm-based technique is used to generate statistically valid QSAR models for each cluster (using the pool of descriptors described above). The toxicity for a given query compound is estimated using the weighted average of the predictions from the closest cluster from each step in the hierarchical clustering assuming that the compound is within the domain of applicability of the cluster. The hierarchical clustering methodology was tested using a Tetrahymena pyriformis acute toxicity data set containing 644 chemicals in the training set and with two prediction sets containing 339 and 110 chemicals. The results from the hierarchical clustering methodology were compared to the results from several different QSAR methodologies.

Data Sufficiency Assessment and Pumping Test Design for Groundwater Prediction Using Decision Theory and Genetic Algorithms

NASA Astrophysics Data System (ADS)

McPhee, J.; William, Y. W.

2005-12-01

This work presents a methodology for pumping test design based on the reliability requirements of a groundwater model. Reliability requirements take into consideration the application of the model results in groundwater management, expressed in this case as a multiobjective management model. The pumping test design is formulated as a mixed-integer nonlinear programming (MINLP) problem and solved using a combination of genetic algorithm (GA) and gradient-based optimization. Bayesian decision theory provides a formal framework for assessing the influence of parameter uncertainty over the reliability of the proposed pumping test. The proposed methodology is useful for selecting a robust design that will outperform all other candidate designs under most potential 'true' states of the system

More than Anecdotes: Fishers’ Ecological Knowledge Can Fill Gaps for Ecosystem Modeling

PubMed Central

Bevilacqua, Ana Helena V.; Carvalho, Adriana R.; Angelini, Ronaldo; Christensen, Villy

2016-01-01

Background Ecosystem modeling applied to fisheries remains hampered by a lack of local information. Fishers’ knowledge could fill this gap, improving participation in and the management of fisheries. Methodology The same fishing area was modeled using two approaches: based on fishers’ knowledge and based on scientific information. For the former, the data was collected by interviews through the Delphi methodology, and for the latter, the data was gathered from the literature. Agreement between the attributes generated by the fishers’ knowledge model and scientific model is discussed and explored, aiming to improve data availability, the ecosystem model, and fisheries management. Principal Findings The ecosystem attributes produced from the fishers’ knowledge model were consistent with the ecosystem attributes produced by the scientific model, and elaborated using only the scientific data from literature. Conclusions/Significance This study provides evidence that fishers’ knowledge may suitably complement scientific data, and may improve the modeling tools for the research and management of fisheries. PMID:27196131

Taxonomy-Based Approaches to Quality Assurance of Ontologies

PubMed Central

Perl, Yehoshua; Ochs, Christopher

2017-01-01

Ontologies are important components of health information management systems. As such, the quality of their content is of paramount importance. It has been proven to be practical to develop quality assurance (QA) methodologies based on automated identification of sets of concepts expected to have higher likelihood of errors. Four kinds of such sets (called QA-sets) organized around the themes of complex and uncommonly modeled concepts are introduced. A survey of different methodologies based on these QA-sets and the results of applying them to various ontologies are presented. Overall, following these approaches leads to higher QA yields and better utilization of QA personnel. The formulation of additional QA-set methodologies will further enhance the suite of available ontology QA tools. PMID:29158885

New geometric design consistency model based on operating speed profiles for road safety evaluation.

PubMed

Camacho-Torregrosa, Francisco J; Pérez-Zuriaga, Ana M; Campoy-Ungría, J Manuel; García-García, Alfredo

2013-12-01

To assist in the on-going effort to reduce road fatalities as much as possible, this paper presents a new methodology to evaluate road safety in both the design and redesign stages of two-lane rural highways. This methodology is based on the analysis of road geometric design consistency, a value which will be a surrogate measure of the safety level of the two-lane rural road segment. The consistency model presented in this paper is based on the consideration of continuous operating speed profiles. The models used for their construction were obtained by using an innovative GPS-data collection method that is based on continuous operating speed profiles recorded from individual drivers. This new methodology allowed the researchers to observe the actual behavior of drivers and to develop more accurate operating speed models than was previously possible with spot-speed data collection, thereby enabling a more accurate approximation to the real phenomenon and thus a better consistency measurement. Operating speed profiles were built for 33 Spanish two-lane rural road segments, and several consistency measurements based on the global and local operating speed were checked. The final consistency model takes into account not only the global dispersion of the operating speed, but also some indexes that consider both local speed decelerations and speeds over posted speeds as well. For the development of the consistency model, the crash frequency for each study site was considered, which allowed estimating the number of crashes on a road segment by means of the calculation of its geometric design consistency. Consequently, the presented consistency evaluation method is a promising innovative tool that can be used as a surrogate measure to estimate the safety of a road segment. Copyright © 2012 Elsevier Ltd. All rights reserved.

Real-time plasma control in a dual-frequency, confined plasma etcher

NASA Astrophysics Data System (ADS)

Milosavljević, V.; Ellingboe, A. R.; Gaman, C.; Ringwood, J. V.

2008-04-01

The physics issues of developing model-based control of plasma etching are presented. A novel methodology for incorporating real-time model-based control of plasma processing systems is developed. The methodology is developed for control of two dependent variables (ion flux and chemical densities) by two independent controls (27 MHz power and O2 flow). A phenomenological physics model of the nonlinear coupling between the independent controls and the dependent variables of the plasma is presented. By using a design of experiment, the functional dependencies of the response surface are determined. In conjunction with the physical model, the dependencies are used to deconvolve the sensor signals onto the control inputs, allowing compensation of the interaction between control paths. The compensated sensor signals and compensated set-points are then used as inputs to proportional-integral-derivative controllers to adjust radio frequency power and oxygen flow to yield the desired ion flux and chemical density. To illustrate the methodology, model-based real-time control is realized in a commercial semiconductor dielectric etch chamber. The two radio frequency symmetric diode operates with typical commercial fluorocarbon feed-gas mixtures (Ar/O2/C4F8). Key parameters for dielectric etching are known to include ion flux to the surface and surface flux of oxygen containing species. Control is demonstrated using diagnostics of electrode-surface ion current, and chemical densities of O, O2, and CO measured by optical emission spectrometry and/or mass spectrometry. Using our model-based real-time control, the set-point tracking accuracy to changes in chemical species density and ion flux is enhanced.

Implementation of a Project-Based Engineering School: Increasing Student Motivation and Relevant Learning

ERIC Educational Resources Information Center

Terrón-López, María-José; García-García, María-José; Velasco-Quintana, Paloma-Julia; Ocampo, Jared; Vigil Montaño, María-Reyes; Gaya-López, María-Cruz

2017-01-01

The School of Engineering at Universidad Europea de Madrid (UEM) implemented, starting in the 2012-2013 period, a unified academic model based on project-based learning as the methodology used throughout the entire School. This model expects that every year, in each grade, all the students should participate in a capstone project integrating the…

Estimating the ROI on Implementation of RFID at the Ammunition Storage Warehouse and the 40th Supply Depot: KVA as a Methodology

DTIC Science & Technology

2009-12-01

Balanced Scorecard CAPM Capital Asset Pricing Model DIS Defense Information System DoD Department of...Measurement Tool (PMT) is the Balanced Scorecard (BSC) based on critical success factors and key performance indicators. The MND has referred to Jung’s...authors can replicate the methodology for multiple projects to generate a portfolio of projects. Similar to the Capital Asset Pricing Model ( CAPM ) or

Wavelet and Multiresolution Analysis for Finite Element Networking Paradigms

NASA Technical Reports Server (NTRS)

Kurdila, Andrew J.; Sharpley, Robert C.

1999-01-01

This paper presents a final report on Wavelet and Multiresolution Analysis for Finite Element Networking Paradigms. The focus of this research is to derive and implement: 1) Wavelet based methodologies for the compression, transmission, decoding, and visualization of three dimensional finite element geometry and simulation data in a network environment; 2) methodologies for interactive algorithm monitoring and tracking in computational mechanics; and 3) Methodologies for interactive algorithm steering for the acceleration of large scale finite element simulations. Also included in this report are appendices describing the derivation of wavelet based Particle Image Velocity algorithms and reduced order input-output models for nonlinear systems by utilizing wavelet approximations.

Strategy for design NIR calibration sets based on process spectrum and model space: An innovative approach for process analytical technology.

PubMed

Cárdenas, V; Cordobés, M; Blanco, M; Alcalà, M

2015-10-10

The pharmaceutical industry is under stringent regulations on quality control of their products because is critical for both, productive process and consumer safety. According to the framework of "process analytical technology" (PAT), a complete understanding of the process and a stepwise monitoring of manufacturing are required. Near infrared spectroscopy (NIRS) combined with chemometrics have lately performed efficient, useful and robust for pharmaceutical analysis. One crucial step in developing effective NIRS-based methodologies is selecting an appropriate calibration set to construct models affording accurate predictions. In this work, we developed calibration models for a pharmaceutical formulation during its three manufacturing stages: blending, compaction and coating. A novel methodology is proposed for selecting the calibration set -"process spectrum"-, into which physical changes in the samples at each stage are algebraically incorporated. Also, we established a "model space" defined by Hotelling's T(2) and Q-residuals statistics for outlier identification - inside/outside the defined space - in order to select objectively the factors to be used in calibration set construction. The results obtained confirm the efficacy of the proposed methodology for stepwise pharmaceutical quality control, and the relevance of the study as a guideline for the implementation of this easy and fast methodology in the pharma industry. Copyright © 2015 Elsevier B.V. All rights reserved.

A simple methodology to produce flood risk maps consistent with FEMA's base flood elevation maps: Implementation and validation over the entire contiguous United States

NASA Astrophysics Data System (ADS)

Goteti, G.; Kaheil, Y. H.; Katz, B. G.; Li, S.; Lohmann, D.

2011-12-01

In the United States, government agencies as well as the National Flood Insurance Program (NFIP) use flood inundation maps associated with the 100-year return period (base flood elevation, BFE), produced by the Federal Emergency Management Agency (FEMA), as the basis for flood insurance. A credibility check of the flood risk hydraulic models, often employed by insurance companies, is their ability to reasonably reproduce FEMA's BFE maps. We present results from the implementation of a flood modeling methodology aimed towards reproducing FEMA's BFE maps at a very fine spatial resolution using a computationally parsimonious, yet robust, hydraulic model. The hydraulic model used in this study has two components: one for simulating flooding of the river channel and adjacent floodplain, and the other for simulating flooding in the remainder of the catchment. The first component is based on a 1-D wave propagation model, while the second component is based on a 2-D diffusive wave model. The 1-D component captures the flooding from large-scale river transport (including upstream effects), while the 2-D component captures the flooding from local rainfall. The study domain consists of the contiguous United States, hydrologically subdivided into catchments averaging about 500 km2 in area, at a spatial resolution of 30 meters. Using historical daily precipitation data from the Climate Prediction Center (CPC), the precipitation associated with the 100-year return period event was computed for each catchment and was input to the hydraulic model. Flood extent from the FEMA BFE maps is reasonably replicated by the 1-D component of the model (riverine flooding). FEMA's BFE maps only represent the riverine flooding component and are unavailable for many regions of the USA. However, this modeling methodology (1-D and 2-D components together) covers the entire contiguous USA. This study is part of a larger modeling effort from Risk Management Solutions° (RMS) to estimate flood risk associated with extreme precipitation events in the USA. Towards this greater objective, state-of-the-art models of flood hazard and stochastic precipitation are being implemented over the contiguous United States. Results from the successful implementation of the modeling methodology will be presented.

Coal conversion processes and analysis methodologies for synthetic fuels production. [technology assessment and economic analysis of reactor design for coal gasification

NASA Technical Reports Server (NTRS)

1979-01-01

Information to identify viable coal gasification and utilization technologies is presented. Analysis capabilities required to support design and implementation of coal based synthetic fuels complexes are identified. The potential market in the Southeast United States for coal based synthetic fuels is investigated. A requirements analysis to identify the types of modeling and analysis capabilities required to conduct and monitor coal gasification project designs is discussed. Models and methodologies to satisfy these requirements are identified and evaluated, and recommendations are developed. Requirements for development of technology and data needed to improve gasification feasibility and economies are examined.

Teaching research methodology to student midwives through a socio-constructivist educational model: The experience of the high school for science and health techniques of Tunis.

PubMed

Gherissi, Atf; Tinsa, Francine; Soussi, Sonia; Benzarti, Anis

2016-02-01

Since its independence in 1956, Tunisia's maternal health indicators have steadily improved as the result of the implementation of a national holistic strategy that emancipated women and developed midwifery education and maternal health services provision. The last review of the midwifery education programme, occurred in 2008, and was based on evidence based core competencies. This paper describes the implementation process of the socio-constructivist educational model used by to teach research methodology to student midwives, the changes observed among them, the challenges and the lessons learned. Copyright © 2015 Elsevier Ltd. All rights reserved.

Model-Driven Methodology for Rapid Deployment of Smart Spaces Based on Resource-Oriented Architectures

PubMed Central

Corredor, Iván; Bernardos, Ana M.; Iglesias, Josué; Casar, José R.

2012-01-01

Advances in electronics nowadays facilitate the design of smart spaces based on physical mash-ups of sensor and actuator devices. At the same time, software paradigms such as Internet of Things (IoT) and Web of Things (WoT) are motivating the creation of technology to support the development and deployment of web-enabled embedded sensor and actuator devices with two major objectives: (i) to integrate sensing and actuating functionalities into everyday objects, and (ii) to easily allow a diversity of devices to plug into the Internet. Currently, developers who are applying this Internet-oriented approach need to have solid understanding about specific platforms and web technologies. In order to alleviate this development process, this research proposes a Resource-Oriented and Ontology-Driven Development (ROOD) methodology based on the Model Driven Architecture (MDA). This methodology aims at enabling the development of smart spaces through a set of modeling tools and semantic technologies that support the definition of the smart space and the automatic generation of code at hardware level. ROOD feasibility is demonstrated by building an adaptive health monitoring service for a Smart Gym. PMID:23012544

Detecting and correcting for publication bias in meta-analysis - A truncated normal distribution approach.

PubMed

Zhu, Qiaohao; Carriere, K C

2016-01-01

Publication bias can significantly limit the validity of meta-analysis when trying to draw conclusion about a research question from independent studies. Most research on detection and correction for publication bias in meta-analysis focus mainly on funnel plot-based methodologies or selection models. In this paper, we formulate publication bias as a truncated distribution problem, and propose new parametric solutions. We develop methodologies of estimating the underlying overall effect size and the severity of publication bias. We distinguish the two major situations, in which publication bias may be induced by: (1) small effect size or (2) large p-value. We consider both fixed and random effects models, and derive estimators for the overall mean and the truncation proportion. These estimators will be obtained using maximum likelihood estimation and method of moments under fixed- and random-effects models, respectively. We carried out extensive simulation studies to evaluate the performance of our methodology, and to compare with the non-parametric Trim and Fill method based on funnel plot. We find that our methods based on truncated normal distribution perform consistently well, both in detecting and correcting publication bias under various situations.

A methodology for selecting optimum organizations for space communities

NASA Technical Reports Server (NTRS)

Ragusa, J. M.

1978-01-01

This paper suggests that a methodology exists for selecting optimum organizations for future space communities of various sizes and purposes. Results of an exploratory study to identify an optimum hypothetical organizational structure for a large earth-orbiting multidisciplinary research and applications (R&A) Space Base manned by a mixed crew of technologists are presented. Since such a facility does not presently exist, in situ empirical testing was not possible. Study activity was, therefore, concerned with the identification of a desired organizational structural model rather than the empirical testing of it. The principal finding of this research was that a four-level project type 'total matrix' model will optimize the effectiveness of Space Base technologists. An overall conclusion which can be reached from the research is that application of this methodology, or portions of it, may provide planning insights for the formal organizations which will be needed during the Space Industrialization Age.

The Scenario-Based Engineering Process (SEP): a user-centered approach for the development of health care systems.

PubMed

Harbison, K; Kelly, J; Burnell, L; Silva, J

1995-01-01

The Scenario-based Engineering Process (SEP) is a user-focused methodology for large and complex system design. This process supports new application development from requirements analysis with domain models to component selection, design and modification, implementation, integration, and archival placement. It is built upon object-oriented methodologies, domain modeling strategies, and scenario-based techniques to provide an analysis process for mapping application requirements to available components. We are using SEP in the health care applications that we are developing. The process has already achieved success in the manufacturing and military domains and is being adopted by many organizations. SEP should prove viable in any domain containing scenarios that can be decomposed into tasks.

Methodological Innovation in Practice-Based Design Doctorates

ERIC Educational Resources Information Center

Yee, Joyce S. R.

2010-01-01

This article presents a selective review of recent design PhDs that identify and analyse the methodological innovation that is occurring in the field, in order to inform future provision of research training. Six recently completed design PhDs are used to highlight possible philosophical and practical models that can be adopted by future PhD…

Application of Resource Description Framework to Personalise Learning: Systematic Review and Methodology

ERIC Educational Resources Information Center

Jevsikova, Tatjana; Berniukevicius, Andrius; Kurilovas, Eugenijus

2017-01-01

The paper is aimed to present a methodology of learning personalisation based on applying Resource Description Framework (RDF) standard model. Research results are two-fold: first, the results of systematic literature review on Linked Data, RDF "subject-predicate-object" triples, and Web Ontology Language (OWL) application in education…

An E-Assessment Approach for Evaluation in Engineering Overcrowded Groups

ERIC Educational Resources Information Center

Mora, M. C.; Sancho-Bru, J. L.; Iserte, J. L.; Sanchez, F. T.

2012-01-01

The construction of the European Higher Education Area has been an adaptation challenge for Spanish universities. New methodologies require a more active role on the students' part and come into conflict with the previous educational model characterised by a high student/professor ratio, a lecture-based teaching methodology and a summative…

A Methodology for Using Workforce Data to Decide Which Specialties and States to Target for Graduate Medical Education Expansion.

PubMed

Fraher, Erin P; Knapton, Andy; Holmes, George M

2017-02-01

To outline a methodology for allocating graduate medical education (GME) training positions based on data from a workforce projection model. Demand for visits is derived from the Medical Expenditure Panel Survey and Census data. Physician supply, retirements, and geographic mobility are estimated using concatenated AMA Masterfiles and ABMS certification data. The number and specialization behaviors of residents are derived from the AAMC's GMETrack survey. We show how the methodology could be used to allocate 3,000 new GME slots over 5 years-15,000 total positions-by state and specialty to address workforce shortages in 2026. We use the model to identify shortages for 19 types of health care services provided by 35 specialties in 50 states. The new GME slots are allocated to nearly all specialties, but nine states and the District of Columbia do not receive any new positions. This analysis illustrates an objective, evidence-based methodology for allocating GME positions that could be used as the starting point for discussions about GME expansion or redistribution. © Health Research and Educational Trust.

Qualitative Assessment of Inquiry-Based Teaching Methods

ERIC Educational Resources Information Center

Briggs, Michael; Long, George; Owens, Katrina

2011-01-01

A new approach to teaching method assessment using student focused qualitative studies and the theoretical framework of mental models is proposed. The methodology is considered specifically for the advantages it offers when applied to the assessment of inquiry-based teaching methods. The theoretical foundation of mental models is discussed, and…

A network-base analysis of CMIP5 "historical" experiments

NASA Astrophysics Data System (ADS)

Bracco, A.; Foudalis, I.; Dovrolis, C.

2012-12-01

In computer science, "complex network analysis" refers to a set of metrics, modeling tools and algorithms commonly used in the study of complex nonlinear dynamical systems. Its main premise is that the underlying topology or network structure of a system has a strong impact on its dynamics and evolution. By allowing to investigate local and non-local statistical interaction, network analysis provides a powerful, but only marginally explored, framework to validate climate models and investigate teleconnections, assessing their strength, range, and impacts on the climate system. In this work we propose a new, fast, robust and scalable methodology to examine, quantify, and visualize climate sensitivity, while constraining general circulation models (GCMs) outputs with observations. The goal of our novel approach is to uncover relations in the climate system that are not (or not fully) captured by more traditional methodologies used in climate science and often adopted from nonlinear dynamical systems analysis, and to explain known climate phenomena in terms of the network structure or its metrics. Our methodology is based on a solid theoretical framework and employs mathematical and statistical tools, exploited only tentatively in climate research so far. Suitably adapted to the climate problem, these tools can assist in visualizing the trade-offs in representing global links and teleconnections among different data sets. Here we present the methodology, and compare network properties for different reanalysis data sets and a suite of CMIP5 coupled GCM outputs. With an extensive model intercomparison in terms of the climate network that each model leads to, we quantify how each model reproduces major teleconnections, rank model performances, and identify common or specific errors in comparing model outputs and observations.

The Influence of Accreditation on the Sustainability of Organizations with the Brazilian Accreditation Methodology

PubMed Central

de Paiva, Anderson Paulo

2018-01-01

This research evaluates the influence of the Brazilian accreditation methodology on the sustainability of the organizations. Critical factors for implementing accreditation were also examined, including measuring the relationships established between these factors in the organization sustainability. The present study was developed based on the survey methodology applied in the organizations accredited by ONA (National Accreditation Organization); 288 responses were received from the top level managers. The analysis of quantitative data of the measurement models was made with factorial analysis from principal components. The final model was evaluated from the confirmatory factorial analysis and structural equation modeling techniques. The results from the research are vital for the definition of factors that interfere in the accreditation processes, providing a better understanding for accredited organizations and for Brazilian accreditation. PMID:29599939

Mathematical modeling of malaria infection with innate and adaptive immunity in individuals and agent-based communities.

PubMed

Gurarie, David; Karl, Stephan; Zimmerman, Peter A; King, Charles H; St Pierre, Timothy G; Davis, Timothy M E

2012-01-01

Agent-based modeling of Plasmodium falciparum infection offers an attractive alternative to the conventional Ross-Macdonald methodology, as it allows simulation of heterogeneous communities subjected to realistic transmission (inoculation patterns). We developed a new, agent based model that accounts for the essential in-host processes: parasite replication and its regulation by innate and adaptive immunity. The model also incorporates a simplified version of antigenic variation by Plasmodium falciparum. We calibrated the model using data from malaria-therapy (MT) studies, and developed a novel calibration procedure that accounts for a deterministic and a pseudo-random component in the observed parasite density patterns. Using the parasite density patterns of 122 MT patients, we generated a large number of calibrated parameters. The resulting data set served as a basis for constructing and simulating heterogeneous agent-based (AB) communities of MT-like hosts. We conducted several numerical experiments subjecting AB communities to realistic inoculation patterns reported from previous field studies, and compared the model output to the observed malaria prevalence in the field. There was overall consistency, supporting the potential of this agent-based methodology to represent transmission in realistic communities. Our approach represents a novel, convenient and versatile method to model Plasmodium falciparum infection.

FAME, a microprocessor based front-end analysis and modeling environment

NASA Technical Reports Server (NTRS)

Rosenbaum, J. D.; Kutin, E. B.

1980-01-01

Higher order software (HOS) is a methodology for the specification and verification of large scale, complex, real time systems. The HOS methodology was implemented as FAME (front end analysis and modeling environment), a microprocessor based system for interactively developing, analyzing, and displaying system models in a low cost user-friendly environment. The nature of the model is such that when completed it can be the basis for projection to a variety of forms such as structured design diagrams, Petri-nets, data flow diagrams, and PSL/PSA source code. The user's interface with the analyzer is easily recognized by any current user of a structured modeling approach; therefore extensive training is unnecessary. Furthermore, when all the system capabilities are used one can check on proper usage of data types, functions, and control structures thereby adding a new dimension to the design process that will lead to better and more easily verified software designs.

Spatio-temporal modelling of electrical supply systems to optimize the site planning process for the "power to mobility" technology

NASA Astrophysics Data System (ADS)

Karl, Florian; Zink, Roland

2016-04-01

The transformation of the energy sector towards decentralized renewable energies (RE) requires also storage systems to ensure security of supply. The new "Power to Mobility" (PtM) technology is one potential solution to use electrical overproduction to produce methane for i.e. gas vehicles. Motivated by these fact, the paper presents a methodology for a GIS-based temporal modelling of the power grid, to optimize the site planning process for the new PtM-technology. The modelling approach is based on a combination of the software QuantumGIS for the geographical and topological energy supply structure and OpenDSS for the net modelling. For a case study (work in progress) of the city of Straubing (Lower Bavaria) the parameters of the model are quantified. The presentation will discuss the methodology as well as the first results with a view to the application on a regional scale.

A Framework for Preliminary Design of Aircraft Structures Based on Process Information. Part 1

NASA Technical Reports Server (NTRS)

Rais-Rohani, Masoud

1998-01-01

This report discusses the general framework and development of a computational tool for preliminary design of aircraft structures based on process information. The described methodology is suitable for multidisciplinary design optimization (MDO) activities associated with integrated product and process development (IPPD). The framework consists of three parts: (1) product and process definitions; (2) engineering synthesis, and (3) optimization. The product and process definitions are part of input information provided by the design team. The backbone of the system is its ability to analyze a given structural design for performance as well as manufacturability and cost assessment. The system uses a database on material systems and manufacturing processes. Based on the identified set of design variables and an objective function, the system is capable of performing optimization subject to manufacturability, cost, and performance constraints. The accuracy of the manufacturability measures and cost models discussed here depend largely on the available data on specific methods of manufacture and assembly and associated labor requirements. As such, our focus in this research has been on the methodology itself and not so much on its accurate implementation in an industrial setting. A three-tier approach is presented for an IPPD-MDO based design of aircraft structures. The variable-complexity cost estimation methodology and an approach for integrating manufacturing cost assessment into design process are also discussed. This report is presented in two parts. In the first part, the design methodology is presented, and the computational design tool is described. In the second part, a prototype model of the preliminary design Tool for Aircraft Structures based on Process Information (TASPI) is described. Part two also contains an example problem that applies the methodology described here for evaluation of six different design concepts for a wing spar.

Utilizing a structural meta-ontology for family-based quality assurance of the BioPortal ontologies.

PubMed

Ochs, Christopher; He, Zhe; Zheng, Ling; Geller, James; Perl, Yehoshua; Hripcsak, George; Musen, Mark A

2016-06-01

An Abstraction Network is a compact summary of an ontology's structure and content. In previous research, we showed that Abstraction Networks support quality assurance (QA) of biomedical ontologies. The development of an Abstraction Network and its associated QA methodologies, however, is a labor-intensive process that previously was applicable only to one ontology at a time. To improve the efficiency of the Abstraction-Network-based QA methodology, we introduced a QA framework that uses uniform Abstraction Network derivation techniques and QA methodologies that are applicable to whole families of structurally similar ontologies. For the family-based framework to be successful, it is necessary to develop a method for classifying ontologies into structurally similar families. We now describe a structural meta-ontology that classifies ontologies according to certain structural features that are commonly used in the modeling of ontologies (e.g., object properties) and that are important for Abstraction Network derivation. Each class of the structural meta-ontology represents a family of ontologies with identical structural features, indicating which types of Abstraction Networks and QA methodologies are potentially applicable to all of the ontologies in the family. We derive a collection of 81 families, corresponding to classes of the structural meta-ontology, that enable a flexible, streamlined family-based QA methodology, offering multiple choices for classifying an ontology. The structure of 373 ontologies from the NCBO BioPortal is analyzed and each ontology is classified into multiple families modeled by the structural meta-ontology. Copyright © 2016 Elsevier Inc. All rights reserved.

Participatory Development and Analysis of a Fuzzy Cognitive Map of the Establishment of a Bio-Based Economy in the Humber Region

PubMed Central

Penn, Alexandra S.; Knight, Christopher J. K.; Lloyd, David J. B.; Avitabile, Daniele; Kok, Kasper; Schiller, Frank; Woodward, Amy; Druckman, Angela; Basson, Lauren

2013-01-01

Fuzzy Cognitive Mapping (FCM) is a widely used participatory modelling methodology in which stakeholders collaboratively develop a ‘cognitive map’ (a weighted, directed graph), representing the perceived causal structure of their system. This can be directly transformed by a workshop facilitator into simple mathematical models to be interrogated by participants by the end of the session. Such simple models provide thinking tools which can be used for discussion and exploration of complex issues, as well as sense checking the implications of suggested causal links. They increase stakeholder motivation and understanding of whole systems approaches, but cannot be separated from an intersubjective participatory context. Standard FCM methodologies make simplifying assumptions, which may strongly influence results, presenting particular challenges and opportunities. We report on a participatory process, involving local companies and organisations, focussing on the development of a bio-based economy in the Humber region. The initial cognitive map generated consisted of factors considered key for the development of the regional bio-based economy and their directional, weighted, causal interconnections. A verification and scenario generation procedure, to check the structure of the map and suggest modifications, was carried out with a second session. Participants agreed on updates to the original map and described two alternate potential causal structures. In a novel analysis all map structures were tested using two standard methodologies usually used independently: linear and sigmoidal FCMs, demonstrating some significantly different results alongside some broad similarities. We suggest a development of FCM methodology involving a sensitivity analysis with different mappings and discuss the use of this technique in the context of our case study. Using the results and analysis of our process, we discuss the limitations and benefits of the FCM methodology in this case and in general. We conclude by proposing an extended FCM methodology, including multiple functional mappings within one participant-constructed graph. PMID:24244303

Automatic food intake detection based on swallowing sounds.

PubMed

Makeyev, Oleksandr; Lopez-Meyer, Paulo; Schuckers, Stephanie; Besio, Walter; Sazonov, Edward

2012-11-01

This paper presents a novel fully automatic food intake detection methodology, an important step toward objective monitoring of ingestive behavior. The aim of such monitoring is to improve our understanding of eating behaviors associated with obesity and eating disorders. The proposed methodology consists of two stages. First, acoustic detection of swallowing instances based on mel-scale Fourier spectrum features and classification using support vector machines is performed. Principal component analysis and a smoothing algorithm are used to improve swallowing detection accuracy. Second, the frequency of swallowing is used as a predictor for detection of food intake episodes. The proposed methodology was tested on data collected from 12 subjects with various degrees of adiposity. Average accuracies of >80% and >75% were obtained for intra-subject and inter-subject models correspondingly with a temporal resolution of 30s. Results obtained on 44.1 hours of data with a total of 7305 swallows show that detection accuracies are comparable for obese and lean subjects. They also suggest feasibility of food intake detection based on swallowing sounds and potential of the proposed methodology for automatic monitoring of ingestive behavior. Based on a wearable non-invasive acoustic sensor the proposed methodology may potentially be used in free-living conditions.

Automatic food intake detection based on swallowing sounds

PubMed Central

Makeyev, Oleksandr; Lopez-Meyer, Paulo; Schuckers, Stephanie; Besio, Walter; Sazonov, Edward

2012-01-01

This paper presents a novel fully automatic food intake detection methodology, an important step toward objective monitoring of ingestive behavior. The aim of such monitoring is to improve our understanding of eating behaviors associated with obesity and eating disorders. The proposed methodology consists of two stages. First, acoustic detection of swallowing instances based on mel-scale Fourier spectrum features and classification using support vector machines is performed. Principal component analysis and a smoothing algorithm are used to improve swallowing detection accuracy. Second, the frequency of swallowing is used as a predictor for detection of food intake episodes. The proposed methodology was tested on data collected from 12 subjects with various degrees of adiposity. Average accuracies of >80% and >75% were obtained for intra-subject and inter-subject models correspondingly with a temporal resolution of 30s. Results obtained on 44.1 hours of data with a total of 7305 swallows show that detection accuracies are comparable for obese and lean subjects. They also suggest feasibility of food intake detection based on swallowing sounds and potential of the proposed methodology for automatic monitoring of ingestive behavior. Based on a wearable non-invasive acoustic sensor the proposed methodology may potentially be used in free-living conditions. PMID:23125873

Performer-centric Interface Design.

ERIC Educational Resources Information Center

McGraw, Karen L.

1995-01-01

Describes performer-centric interface design and explains a model-based approach for conducting performer-centric analysis and design. Highlights include design methodology, including cognitive task analysis; creating task scenarios; creating the presentation model; creating storyboards; proof of concept screens; object models and icons;…

Reliability modelling and analysis of thermal MEMS

NASA Astrophysics Data System (ADS)

Muratet, Sylvaine; Lavu, Srikanth; Fourniols, Jean-Yves; Bell, George; Desmulliez, Marc P. Y.

2006-04-01

This paper presents a MEMS reliability study methodology based on the novel concept of 'virtual prototyping'. This methodology can be used for the development of reliable sensors or actuators and also to characterize their behaviour in specific use conditions and applications. The methodology is demonstrated on the U-shaped micro electro thermal actuator used as test vehicle. To demonstrate this approach, a 'virtual prototype' has been developed with the modeling tools MatLab and VHDL-AMS. A best practice FMEA (Failure Mode and Effect Analysis) is applied on the thermal MEMS to investigate and assess the failure mechanisms. Reliability study is performed by injecting the identified defaults into the 'virtual prototype'. The reliability characterization methodology predicts the evolution of the behavior of these MEMS as a function of the number of cycles of operation and specific operational conditions.

1996-2016: Two decades of econophysics: Between methodological diversification and conceptual coherence

NASA Astrophysics Data System (ADS)

Schinckus, C.

2016-12-01

This article aimed at presenting the scattered econophysics literature as a unified and coherent field through a specific lens imported from philosophy science. More precisely, I used the methodology developed by Imre Lakatos to cover the methodological evolution of econophysics over these last two decades. In this perspective, three co-existing approaches have been identified: statistical econophysics, bottom-up agent based econophysics and top-down agent based econophysics. Although the last is presented here as the last step of the methodological evolution of econophysics, it is worth mentioning that this tradition is still very new. A quick look on the econophysics literature shows that the vast majority of works in this field deal with a strictly statistical approach or a classical bottom-up agent-based modelling. In this context of diversification, the objective (and contribution) of this article is to emphasize the conceptual coherence of econophysics as a unique field of research. With this purpose, I used a theoretical framework coming from philosophy of science to characterize how econophysics evolved by combining a methodological enrichment with the preservation of its core conceptual statements.

A goal programming approach for a joint design of macroeconomic and environmental policies: a methodological proposal and an application to the Spanish economy.

PubMed

André, Francisco J; Cardenete, M Alejandro; Romero, Carlos

2009-05-01

The economic policy needs to pay increasingly more attention to the environmental issues, which requires the development of methodologies able to incorporate environmental, as well as macroeconomic, goals in the design of public policies. Starting from this observation, this article proposes a methodology based upon a Simonian satisficing logic made operational with the help of goal programming (GP) models, to address the joint design of macroeconomic and environmental policies. The methodology is applied to the Spanish economy, where a joint policy is elicited, taking into consideration macroeconomic goals (economic growth, inflation, unemployment, public deficit) and environmental goals (CO(2), NO( x ) and SO( x ) emissions) within the context of a computable general equilibrium model. The results show how the government can "fine-tune" its policy according to different criteria using GP models. The resulting policies aggregate the environmental and the economic goals in different ways: maximum aggregate performance, maximum balance and a lexicographic hierarchy of the goals.

A Model for Oil-Gas Pipelines Cost Prediction Based on a Data Mining Process

NASA Astrophysics Data System (ADS)

Batzias, Fragiskos A.; Spanidis, Phillip-Mark P.

2009-08-01

This paper addresses the problems associated with the cost estimation of oil/gas pipelines during the elaboration of feasibility assessments. Techno-economic parameters, i.e., cost, length and diameter, are critical for such studies at the preliminary design stage. A methodology for the development of a cost prediction model based on Data Mining (DM) process is proposed. The design and implementation of a Knowledge Base (KB), maintaining data collected from various disciplines of the pipeline industry, are presented. The formulation of a cost prediction equation is demonstrated by applying multiple regression analysis using data sets extracted from the KB. Following the methodology proposed, a learning context is inductively developed as background pipeline data are acquired, grouped and stored in the KB, and through a linear regression model provide statistically substantial results, useful for project managers or decision makers.

Strategies for efficient numerical implementation of hybrid multi-scale agent-based models to describe biological systems

PubMed Central

Cilfone, Nicholas A.; Kirschner, Denise E.; Linderman, Jennifer J.

2015-01-01

Biologically related processes operate across multiple spatiotemporal scales. For computational modeling methodologies to mimic this biological complexity, individual scale models must be linked in ways that allow for dynamic exchange of information across scales. A powerful methodology is to combine a discrete modeling approach, agent-based models (ABMs), with continuum models to form hybrid models. Hybrid multi-scale ABMs have been used to simulate emergent responses of biological systems. Here, we review two aspects of hybrid multi-scale ABMs: linking individual scale models and efficiently solving the resulting model. We discuss the computational choices associated with aspects of linking individual scale models while simultaneously maintaining model tractability. We demonstrate implementations of existing numerical methods in the context of hybrid multi-scale ABMs. Using an example model describing Mycobacterium tuberculosis infection, we show relative computational speeds of various combinations of numerical methods. Efficient linking and solution of hybrid multi-scale ABMs is key to model portability, modularity, and their use in understanding biological phenomena at a systems level. PMID:26366228

A Design Methodology for Medical Processes

PubMed Central

Bonacina, Stefano; Pozzi, Giuseppe; Pinciroli, Francesco; Marceglia, Sara

2016-01-01

Summary Background Healthcare processes, especially those belonging to the clinical domain, are acknowledged as complex and characterized by the dynamic nature of the diagnosis, the variability of the decisions made by experts driven by their experiences, the local constraints, the patient’s needs, the uncertainty of the patient’s response, and the indeterminacy of patient’s compliance to treatment. Also, the multiple actors involved in patient’s care need clear and transparent communication to ensure care coordination. Objectives In this paper, we propose a methodology to model healthcare processes in order to break out complexity and provide transparency. Methods The model is grounded on a set of requirements that make the healthcare domain unique with respect to other knowledge domains. The modeling methodology is based on three main phases: the study of the environmental context, the conceptual modeling, and the logical modeling. Results The proposed methodology was validated by applying it to the case study of the rehabilitation process of stroke patients in the specific setting of a specialized rehabilitation center. The resulting model was used to define the specifications of a software artifact for the digital administration and collection of assessment tests that was also implemented. Conclusions Despite being only an example, our case study showed the ability of process modeling to answer the actual needs in healthcare practices. Independently from the medical domain in which the modeling effort is done, the proposed methodology is useful to create high-quality models, and to detect and take into account relevant and tricky situations that can occur during process execution. PMID:27081415

Semantic modeling for theory clarification: The realist vs liberal international relations perspective

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

Bray, O.H.

This paper describes a natural language based, semantic information modeling methodology and explores its use and value in clarifying and comparing political science theories and frameworks. As an example, the paper uses this methodology to clarify and compare some of the basic concepts and relationships in the realist (e.g. Waltz) and the liberal (e.g. Rosenau) paradigms for international relations. The methodology can provide three types of benefits: (1) it can clarify and make explicit exactly what is meant by a concept; (2) it can often identify unanticipated implications and consequence of concepts and relationships; and (3) it can help inmore » identifying and operationalizing testable hypotheses.« less

Constraint Force Equation Methodology for Modeling Multi-Body Stage Separation Dynamics

NASA Technical Reports Server (NTRS)

Toniolo, Matthew D.; Tartabini, Paul V.; Pamadi, Bandu N.; Hotchko, Nathaniel

2008-01-01

This paper discusses a generalized approach to the multi-body separation problems in a launch vehicle staging environment based on constraint force methodology and its implementation into the Program to Optimize Simulated Trajectories II (POST2), a widely used trajectory design and optimization tool. This development facilitates the inclusion of stage separation analysis into POST2 for seamless end-to-end simulations of launch vehicle trajectories, thus simplifying the overall implementation and providing a range of modeling and optimization capabilities that are standard features in POST2. Analysis and results are presented for two test cases that validate the constraint force equation methodology in a stand-alone mode and its implementation in POST2.

Privacy-Aware Relevant Data Access with Semantically Enriched Search Queries for Untrusted Cloud Storage Services.

PubMed

Pervez, Zeeshan; Ahmad, Mahmood; Khattak, Asad Masood; Lee, Sungyoung; Chung, Tae Choong

2016-01-01

Privacy-aware search of outsourced data ensures relevant data access in the untrusted domain of a public cloud service provider. Subscriber of a public cloud storage service can determine the presence or absence of a particular keyword by submitting search query in the form of a trapdoor. However, these trapdoor-based search queries are limited in functionality and cannot be used to identify secure outsourced data which contains semantically equivalent information. In addition, trapdoor-based methodologies are confined to pre-defined trapdoors and prevent subscribers from searching outsourced data with arbitrarily defined search criteria. To solve the problem of relevant data access, we have proposed an index-based privacy-aware search methodology that ensures semantic retrieval of data from an untrusted domain. This method ensures oblivious execution of a search query and leverages authorized subscribers to model conjunctive search queries without relying on predefined trapdoors. A security analysis of our proposed methodology shows that, in a conspired attack, unauthorized subscribers and untrusted cloud service providers cannot deduce any information that can lead to the potential loss of data privacy. A computational time analysis on commodity hardware demonstrates that our proposed methodology requires moderate computational resources to model a privacy-aware search query and for its oblivious evaluation on a cloud service provider.

Formulation of a correlated variables methodology for assessment of continuous gas resources with an application to the Woodford play, Arkoma Basin, eastern Oklahoma

USGS Publications Warehouse

Olea, R.A.; Houseknecht, D.W.; Garrity, C.P.; Cook, T.A.

2011-01-01

Shale gas is a form of continuous unconventional hydrocarbon accumulation whose resource estimation is unfeasible through the inference of pore volume. Under these circumstances, the usual approach is to base the assessment on well productivity through estimated ultimate recovery (EUR). Unconventional resource assessments that consider uncertainty are typically done by applying analytical procedures based on classical statistics theory that ignores geographical location, does not take into account spatial correlation, and assumes independence of EUR from other variables that may enter into the modeling. We formulate a new, more comprehensive approach based on sequential simulation to test methodologies known to be capable of more fully utilizing the data and overcoming unrealistic simplifications. Theoretical requirements demand modeling of EUR as areal density instead of well EUR. The new experimental methodology is illustrated by evaluating a gas play in the Woodford Shale in the Arkoma Basin of Oklahoma. Differently from previous assessments, we used net thickness and vitrinite reflectance as secondary variables correlated to cell EUR. In addition to the traditional probability distribution for undiscovered resources, the new methodology provides maps of EUR density and maps with probabilities to reach any given cell EUR, which are useful to visualize geographical variations in prospectivity.

Privacy-Aware Relevant Data Access with Semantically Enriched Search Queries for Untrusted Cloud Storage Services

PubMed Central

Pervez, Zeeshan; Ahmad, Mahmood; Khattak, Asad Masood; Lee, Sungyoung; Chung, Tae Choong

2016-01-01

Privacy-aware search of outsourced data ensures relevant data access in the untrusted domain of a public cloud service provider. Subscriber of a public cloud storage service can determine the presence or absence of a particular keyword by submitting search query in the form of a trapdoor. However, these trapdoor-based search queries are limited in functionality and cannot be used to identify secure outsourced data which contains semantically equivalent information. In addition, trapdoor-based methodologies are confined to pre-defined trapdoors and prevent subscribers from searching outsourced data with arbitrarily defined search criteria. To solve the problem of relevant data access, we have proposed an index-based privacy-aware search methodology that ensures semantic retrieval of data from an untrusted domain. This method ensures oblivious execution of a search query and leverages authorized subscribers to model conjunctive search queries without relying on predefined trapdoors. A security analysis of our proposed methodology shows that, in a conspired attack, unauthorized subscribers and untrusted cloud service providers cannot deduce any information that can lead to the potential loss of data privacy. A computational time analysis on commodity hardware demonstrates that our proposed methodology requires moderate computational resources to model a privacy-aware search query and for its oblivious evaluation on a cloud service provider. PMID:27571421

Multi-scale landslide hazard assessment: Advances in global and regional methodologies

NASA Astrophysics Data System (ADS)

Kirschbaum, Dalia; Peters-Lidard, Christa; Adler, Robert; Hong, Yang

2010-05-01

The increasing availability of remotely sensed surface data and precipitation provides a unique opportunity to explore how smaller-scale landslide susceptibility and hazard assessment methodologies may be applicable at larger spatial scales. This research first considers an emerging satellite-based global algorithm framework, which evaluates how the landslide susceptibility and satellite derived rainfall estimates can forecast potential landslide conditions. An analysis of this algorithm using a newly developed global landslide inventory catalog suggests that forecasting errors are geographically variable due to improper weighting of surface observables, resolution of the current susceptibility map, and limitations in the availability of landslide inventory data. These methodological and data limitation issues can be more thoroughly assessed at the regional level, where available higher resolution landslide inventories can be applied to empirically derive relationships between surface variables and landslide occurrence. The regional empirical model shows improvement over the global framework in advancing near real-time landslide forecasting efforts; however, there are many uncertainties and assumptions surrounding such a methodology that decreases the functionality and utility of this system. This research seeks to improve upon this initial concept by exploring the potential opportunities and methodological structure needed to advance larger-scale landslide hazard forecasting and make it more of an operational reality. Sensitivity analysis of the surface and rainfall parameters in the preliminary algorithm indicates that surface data resolution and the interdependency of variables must be more appropriately quantified at local and regional scales. Additionally, integrating available surface parameters must be approached in a more theoretical, physically-based manner to better represent the physical processes underlying slope instability and landslide initiation. Several rainfall infiltration and hydrological flow models have been developed to model slope instability at small spatial scales. This research investigates the potential of applying a more quantitative hydrological model to larger spatial scales, utilizing satellite and surface data inputs that are obtainable over different geographic regions. Due to the significant role that data and methodological uncertainties play in the effectiveness of landslide hazard assessment outputs, the methodology and data inputs are considered within an ensemble uncertainty framework in order to better resolve the contribution and limitations of model inputs and to more effectively communicate the model skill for improved landslide hazard assessment.

[Strategic health planning based on determinants: case of the municipality of Campo Bom, Rio Grande do Sul State. A methodological proposal for the decentralized management].

PubMed

González, Martín Maximino León

2009-10-01

With the purpose to analyze the health strategic planning model based on determinants experienced in the municipality of Campo Bom, Rio Grande do Sul State, it was conducted an observational, qualitative study, of documental analysis as well as an evaluation of new process technologies in local health administration. This study contains an analysis of the methodological coherency and applicability of this model, based on the revision of the elaborated plans. The plans presented at Campo Bom case shows the possibility of integration and applicability at local level, of a health strategic planning model oriented to the new health concepts considering elements of different theoretical developments that enables the response to the most common local needs and situations. It was identified evolutional stages of health planning and analyzed integrative elements of the model and limitations of its application, pointing to the need of support the deepening on the study and the development of the field.

Evolving RBF neural networks for adaptive soft-sensor design.

PubMed

Alexandridis, Alex

2013-12-01

This work presents an adaptive framework for building soft-sensors based on radial basis function (RBF) neural network models. The adaptive fuzzy means algorithm is utilized in order to evolve an RBF network, which approximates the unknown system based on input-output data from it. The methodology gradually builds the RBF network model, based on two separate levels of adaptation: On the first level, the structure of the hidden layer is modified by adding or deleting RBF centers, while on the second level, the synaptic weights are adjusted with the recursive least squares with exponential forgetting algorithm. The proposed approach is tested on two different systems, namely a simulated nonlinear DC Motor and a real industrial reactor. The results show that the produced soft-sensors can be successfully applied to model the two nonlinear systems. A comparison with two different adaptive modeling techniques, namely a dynamic evolving neural-fuzzy inference system (DENFIS) and neural networks trained with online backpropagation, highlights the advantages of the proposed methodology.

Environmental Risk Assessment of dredging processes - application to Marin harbour (NW Spain)

NASA Astrophysics Data System (ADS)

Gómez, A. G.; García Alba, J.; Puente, A.; Juanes, J. A.

2014-04-01

A methodological procedure to estimate the environmental risk of dredging operations in aquatic systems has been developed. Environmental risk estimations are based on numerical models results, which provide an appropriated spatio-temporal framework analysis to guarantee an effective decision-making process. The methodological procedure has been applied on a real dredging operation in the port of Marin (NW Spain). Results from Marin harbour confirmed the suitability of the developed methodology and the conceptual approaches as a comprehensive and practical management tool.

Haptic Technologies for MEMS Design

NASA Astrophysics Data System (ADS)

Calis, Mustafa; Desmulliez, Marc P. Y.

2006-04-01

This paper presents for the first time a design methodology for MEMS/NEMS based on haptic sensing technologies. The software tool created as a result of this methodology will enable designers to model and interact in real time with their virtual prototype. One of the main advantages of haptic sensing is the ability to bring unusual microscopic forces back to the designer's world. Other significant benefits for developing such a methodology include gain productivity and the capability to include manufacturing costs within the design cycle.

Data Mining for Financial Applications

NASA Astrophysics Data System (ADS)

Kovalerchuk, Boris; Vityaev, Evgenii

This chapter describes Data Mining in finance by discussing financial tasks, specifics of methodologies and techniques in this Data Mining area. It includes time dependence, data selection, forecast horizon, measures of success, quality of patterns, hypothesis evaluation, problem ID, method profile, attribute-based and relational methodologies. The second part of the chapter discusses Data Mining models and practice in finance. It covers use of neural networks in portfolio management, design of interpretable trading rules and discovering money laundering schemes using decision rules and relational Data Mining methodology.

Requirements analysis notebook for the flight data systems definition in the Real-Time Systems Engineering Laboratory (RSEL)

NASA Astrophysics Data System (ADS)

Wray, Richard B.

1991-12-01

A hybrid requirements analysis methodology was developed, based on the practices actually used in developing a Space Generic Open Avionics Architecture. During the development of this avionics architecture, a method of analysis able to effectively define the requirements for this space avionics architecture was developed. In this methodology, external interfaces and relationships are defined, a static analysis resulting in a static avionics model was developed, operating concepts for simulating the requirements were put together, and a dynamic analysis of the execution needs for the dynamic model operation was planned. The systems engineering approach was used to perform a top down modified structured analysis of a generic space avionics system and to convert actual program results into generic requirements. CASE tools were used to model the analyzed system and automatically generate specifications describing the model's requirements. Lessons learned in the use of CASE tools, the architecture, and the design of the Space Generic Avionics model were established, and a methodology notebook was prepared for NASA. The weaknesses of standard real-time methodologies for practicing systems engineering, such as Structured Analysis and Object Oriented Analysis, were identified.

Requirements analysis notebook for the flight data systems definition in the Real-Time Systems Engineering Laboratory (RSEL)

NASA Technical Reports Server (NTRS)

Wray, Richard B.

1991-01-01

A hybrid requirements analysis methodology was developed, based on the practices actually used in developing a Space Generic Open Avionics Architecture. During the development of this avionics architecture, a method of analysis able to effectively define the requirements for this space avionics architecture was developed. In this methodology, external interfaces and relationships are defined, a static analysis resulting in a static avionics model was developed, operating concepts for simulating the requirements were put together, and a dynamic analysis of the execution needs for the dynamic model operation was planned. The systems engineering approach was used to perform a top down modified structured analysis of a generic space avionics system and to convert actual program results into generic requirements. CASE tools were used to model the analyzed system and automatically generate specifications describing the model's requirements. Lessons learned in the use of CASE tools, the architecture, and the design of the Space Generic Avionics model were established, and a methodology notebook was prepared for NASA. The weaknesses of standard real-time methodologies for practicing systems engineering, such as Structured Analysis and Object Oriented Analysis, were identified.

Uncertainty propagation by using spectral methods: A practical application to a two-dimensional turbulence fluid model

NASA Astrophysics Data System (ADS)

Riva, Fabio; Milanese, Lucio; Ricci, Paolo

2017-10-01

To reduce the computational cost of the uncertainty propagation analysis, which is used to study the impact of input parameter variations on the results of a simulation, a general and simple to apply methodology based on decomposing the solution to the model equations in terms of Chebyshev polynomials is discussed. This methodology, based on the work by Scheffel [Am. J. Comput. Math. 2, 173-193 (2012)], approximates the model equation solution with a semi-analytic expression that depends explicitly on time, spatial coordinates, and input parameters. By employing a weighted residual method, a set of nonlinear algebraic equations for the coefficients appearing in the Chebyshev decomposition is then obtained. The methodology is applied to a two-dimensional Braginskii model used to simulate plasma turbulence in basic plasma physics experiments and in the scrape-off layer of tokamaks, in order to study the impact on the simulation results of the input parameter that describes the parallel losses. The uncertainty that characterizes the time-averaged density gradient lengths, time-averaged densities, and fluctuation density level are evaluated. A reasonable estimate of the uncertainty of these distributions can be obtained with a single reduced-cost simulation.

Abstracting event-based control models for high autonomy systems

NASA Technical Reports Server (NTRS)

Luh, Cheng-Jye; Zeigler, Bernard P.

1993-01-01

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

Time-lapse ERT interpretation methodology for leachate injection monitoring based on multiple inversions and a clustering strategy (MICS)

NASA Astrophysics Data System (ADS)

Audebert, M.; Clément, R.; Touze-Foltz, N.; Günther, T.; Moreau, S.; Duquennoi, C.

2014-12-01

Leachate recirculation is a key process in municipal waste landfills functioning as bioreactors. To quantify the water content and to assess the leachate injection system, in-situ methods are required to obtain spatially distributed information, usually electrical resistivity tomography (ERT). This geophysical method is based on the inversion process, which presents two major problems in terms of delimiting the infiltration area. First, it is difficult for ERT users to choose an appropriate inversion parameter set. Indeed, it might not be sufficient to interpret only the optimum model (i.e. the model with the chosen regularisation strength) because it is not necessarily the model which best represents the physical process studied. Second, it is difficult to delineate the infiltration front based on resistivity models because of the smoothness of the inversion results. This paper proposes a new methodology called MICS (multiple inversions and clustering strategy), which allows ERT users to improve the delimitation of the infiltration area in leachate injection monitoring. The MICS methodology is based on (i) a multiple inversion step by varying the inversion parameter values to take a wide range of resistivity models into account and (ii) a clustering strategy to improve the delineation of the infiltration front. In this paper, MICS was assessed on two types of data. First, a numerical assessment allows us to optimise and test MICS for different infiltration area sizes, contrasts and shapes. Second, MICS was applied to a field data set gathered during leachate recirculation on a bioreactor.

Recent activities within the Aeroservoelasticity Branch at the NASA Langley Research Center

NASA Technical Reports Server (NTRS)

Noll, Thomas E.; Perry, Boyd, III; Gilbert, Michael G.

1989-01-01

The objective of research in aeroservoelasticity at the NASA Langley Research Center is to enhance the modeling, analysis, and multidisciplinary design methodologies for obtaining multifunction digital control systems for application to flexible flight vehicles. Recent accomplishments are discussed, and a status report on current activities within the Aeroservoelasticity Branch is presented. In the area of modeling, improvements to the Minimum-State Method of approximating unsteady aerodynamics are shown to provide precise, low-order aeroservoelastic models for design and simulation activities. Analytical methods based on Matched Filter Theory and Random Process Theory to provide efficient and direct predictions of the critical gust profile and the time-correlated gust loads for linear structural design considerations are also discussed. Two research projects leading towards improved design methodology are summarized. The first program is developing an integrated structure/control design capability based on hierarchical problem decomposition, multilevel optimization and analytical sensitivities. The second program provides procedures for obtaining low-order, robust digital control laws for aeroelastic applications. In terms of methodology validation and application the current activities associated with the Active Flexible Wing project are reviewed.

Modeling and optimization of anaerobic codigestion of potato waste and aquatic weed by response surface methodology and artificial neural network coupled genetic algorithm.

PubMed

Jacob, Samuel; Banerjee, Rintu

2016-08-01

A novel approach to overcome the acidification problem has been attempted in the present study by codigesting industrial potato waste (PW) with Pistia stratiotes (PS, an aquatic weed). The effectiveness of codigestion of the weed and PW was tested in an equal (1:1) proportion by weight with substrate concentration of 5g total solid (TS)/L (2.5gPW+2.5gPS) which resulted in enhancement of methane yield by 76.45% as compared to monodigestion of PW with a positive synergistic effect. Optimization of process parameters was conducted using central composite design (CCD) based response surface methodology (RSM) and artificial neural network (ANN) coupled genetic algorithm (GA) model. Upon comparison of these two optimization techniques, ANN-GA model obtained through feed forward back propagation methodology was found to be efficient and yielded 447.4±21.43LCH4/kgVSfed (0.279gCH4/kgCODvs) which is 6% higher as compared to the CCD-RSM based approach. Copyright © 2016 Elsevier Ltd. All rights reserved.

Estimation of the Reactive Flow Model Parameters for an Ammonium Nitrate-Based Emulsion Explosive Using Genetic Algorithms

NASA Astrophysics Data System (ADS)

Ribeiro, J. B.; Silva, C.; Mendes, R.

2010-10-01

A real coded genetic algorithm methodology that has been developed for the estimation of the parameters of the reaction rate equation of the Lee-Tarver reactive flow model is described in detail. This methodology allows, in a single optimization procedure, using only one experimental result and, without the need of any starting solution, to seek the 15 parameters of the reaction rate equation that fit the numerical to the experimental results. Mass averaging and the plate-gap model have been used for the determination of the shock data used in the unreacted explosive JWL equation of state (EOS) assessment and the thermochemical code THOR retrieved the data used in the detonation products' JWL EOS assessments. The developed methodology was applied for the estimation of the referred parameters for an ammonium nitrate-based emulsion explosive using poly(methyl methacrylate) (PMMA)-embedded manganin gauge pressure-time data. The obtained parameters allow a reasonably good description of the experimental data and show some peculiarities arising from the intrinsic nature of this kind of composite explosive.

[Methodological approach to the use of artificial neural networks for predicting results in medicine].

PubMed

Trujillano, Javier; March, Jaume; Sorribas, Albert

2004-01-01

In clinical practice, there is an increasing interest in obtaining adequate models of prediction. Within the possible available alternatives, the artificial neural networks (ANN) are progressively more used. In this review we first introduce the ANN methodology, describing the most common type of ANN, the Multilayer Perceptron trained with backpropagation algorithm (MLP). Then we compare the MLP with the Logistic Regression (LR). Finally, we show a practical scheme to make an application based on ANN by means of an example with actual data. The main advantage of the RN is its capacity to incorporate nonlinear effects and interactions between the variables of the model without need to include them a priori. As greater disadvantages, they show a difficult interpretation of their parameters and large empiricism in their process of construction and training. ANN are useful for the computation of probabilities of a given outcome based on a set of predicting variables. Furthermore, in some cases, they obtain better results than LR. Both methodologies, ANN and LR, are complementary and they help us to obtain more valid models.

A Methodology for Data Structure Assessment in Higher Education Administration. AIR Forum Paper 1978.

ERIC Educational Resources Information Center

Baltes, Kenneth G.; Hendrix, Vernon L.

Two recent developments in management information system technology and higher education administration have brought about the need for this study, designed to develop a methodology for revealing a relational model of the data base that administrators are operating from currently or would like to be able to operate from in the future.…

Dynamic determination of kinetic parameters and computer simulation of growth of Clostridium perfringens in cooked beef

USDA-ARS?s Scientific Manuscript database

The objective of this research was to develop a new one-step methodology that uses a dynamic approach to directly construct a tertiary model for prediction of the growth of C. perfringens in cooked beef. This methodology was based on numerical analysis and optimization of both primary and secondary...

International Harmonization of Training and Qualification in the Manufacturing Industry

ERIC Educational Resources Information Center

Quintino, L.; Fernandes, I.; Miranda, R. M.

2011-01-01

Purpose: The aim of this paper is to propose a model for international harmonization of the training and qualification of human resources for industrial professions. The outcome is a system based on training guidelines and a quality assurance methodology that is now in use in 42 countries around the world. Design/methodology/approach: The paper…

A Methodology for Developing Learning Objects for Web Course Delivery

ERIC Educational Resources Information Center

Stauffer, Karen; Lin, Fuhua; Koole, Marguerite

2008-01-01

This article presents a methodology for developing learning objects for web-based courses using the IMS Learning Design (IMS LD) specification. We first investigated the IMS LD specification, determining how to use it with online courses and the student delivery model, and then applied this to a Unit of Learning (UOL) for online computer science…

The Perceptions of U.S.-Based IT Security Professionals about the Effectiveness of IT Security Frameworks: A Quantitative Study

ERIC Educational Resources Information Center

Warfield, Douglas L.

2011-01-01

The evolution of information technology has included new methodologies that use information technology to control and manage various industries and government activities. Information Technology has also evolved as its own industry with global networks of interconnectivity, such as the Internet, and frameworks, models, and methodologies to control…

The Decisions of Elementary School Principals: A Test of Ideal Type Methodology.

ERIC Educational Resources Information Center

Greer, John T.

Interviews with 25 Georgia elementary school principals provided data that could be used to test an application of Max Weber's ideal type methodology to decision-making. Alfred Schuetz's model of the rational act, based on one of Weber's ideal types, was analyzed and translated into describable acts and behaviors. Interview procedures were…

Assessment methodology for computer-based instructional simulations.

PubMed

Koenig, Alan; Iseli, Markus; Wainess, Richard; Lee, John J

2013-10-01

Computer-based instructional simulations are becoming more and more ubiquitous, particularly in military and medical domains. As the technology that drives these simulations grows ever more sophisticated, the underlying pedagogical models for how instruction, assessment, and feedback are implemented within these systems must evolve accordingly. In this article, we review some of the existing educational approaches to medical simulations, and present pedagogical methodologies that have been used in the design and development of games and simulations at the University of California, Los Angeles, Center for Research on Evaluation, Standards, and Student Testing. In particular, we present a methodology for how automated assessments of computer-based simulations can be implemented using ontologies and Bayesian networks, and discuss their advantages and design considerations for pedagogical use. Reprint & Copyright © 2013 Association of Military Surgeons of the U.S.

A methodology for long range prediction of air transportation

NASA Technical Reports Server (NTRS)

Ayati, M. B.; English, J. M.

1980-01-01

The paper describes the methodology for long-time projection of aircraft fuel requirements. A new concept of social and economic factors for future aviation industry which provides an estimate of predicted fuel usage is presented; it includes air traffic forecasts and lead times for producing new engines and aircraft types. An air transportation model is then developed in terms of an abstracted set of variables which represent the entire aircraft industry on a macroscale. This model was evaluated by testing the required output variables from a model based on historical data over the past decades.

Predictive Inference Using Latent Variables with Covariates*

PubMed Central

Schofield, Lynne Steuerle; Junker, Brian; Taylor, Lowell J.; Black, Dan A.

2014-01-01

Plausible Values (PVs) are a standard multiple imputation tool for analysis of large education survey data that measures latent proficiency variables. When latent proficiency is the dependent variable, we reconsider the standard institutionally-generated PV methodology and find it applies with greater generality than shown previously. When latent proficiency is an independent variable, we show that the standard institutional PV methodology produces biased inference because the institutional conditioning model places restrictions on the form of the secondary analysts’ model. We offer an alternative approach that avoids these biases based on the mixed effects structural equations (MESE) model of Schofield (2008). PMID:25231627

Parallelization of fine-scale computation in Agile Multiscale Modelling Methodology

NASA Astrophysics Data System (ADS)

Macioł, Piotr; Michalik, Kazimierz

2016-10-01

Nowadays, multiscale modelling of material behavior is an extensively developed area. An important obstacle against its wide application is high computational demands. Among others, the parallelization of multiscale computations is a promising solution. Heterogeneous multiscale models are good candidates for parallelization, since communication between sub-models is limited. In this paper, the possibility of parallelization of multiscale models based on Agile Multiscale Methodology framework is discussed. A sequential, FEM based macroscopic model has been combined with concurrently computed fine-scale models, employing a MatCalc thermodynamic simulator. The main issues, being investigated in this work are: (i) the speed-up of multiscale models with special focus on fine-scale computations and (ii) on decreasing the quality of computations enforced by parallel execution. Speed-up has been evaluated on the basis of Amdahl's law equations. The problem of `delay error', rising from the parallel execution of fine scale sub-models, controlled by the sequential macroscopic sub-model is discussed. Some technical aspects of combining third-party commercial modelling software with an in-house multiscale framework and a MPI library are also discussed.

A response surface methodology based damage identification technique

NASA Astrophysics Data System (ADS)

Fang, S. E.; Perera, R.

2009-06-01

Response surface methodology (RSM) is a combination of statistical and mathematical techniques to represent the relationship between the inputs and outputs of a physical system by explicit functions. This methodology has been widely employed in many applications such as design optimization, response prediction and model validation. But so far the literature related to its application in structural damage identification (SDI) is scarce. Therefore this study attempts to present a systematic SDI procedure comprising four sequential steps of feature selection, parameter screening, primary response surface (RS) modeling and updating, and reference-state RS modeling with SDI realization using the factorial design (FD) and the central composite design (CCD). The last two steps imply the implementation of inverse problems by model updating in which the RS models substitute the FE models. The proposed method was verified against a numerical beam, a tested reinforced concrete (RC) frame and an experimental full-scale bridge with the modal frequency being the output responses. It was found that the proposed RSM-based method performs well in predicting the damage of both numerical and experimental structures having single and multiple damage scenarios. The screening capacity of the FD can provide quantitative estimation of the significance levels of updating parameters. Meanwhile, the second-order polynomial model established by the CCD provides adequate accuracy in expressing the dynamic behavior of a physical system.

Methodology for the Model-based Small Area Estimates of Cancer Risk Factors and Screening Behaviors - Small Area Estimates

Cancer.gov

This model-based approach uses data from both the Behavioral Risk Factor Surveillance System (BRFSS) and the National Health Interview Survey (NHIS) to produce estimates of the prevalence rates of cancer risk factors and screening behaviors at the state, health service area, and county levels.

A user-centred methodology for designing an online social network to motivate health behaviour change.

PubMed

Kamal, Noreen; Fels, Sidney

2013-01-01

Positive health behaviour is critical to preventing illness and managing chronic conditions. A user-centred methodology was employed to design an online social network to motivate health behaviour change. The methodology was augmented by utilizing the Appeal, Belonging, Commitment (ABC) Framework, which is based on theoretical models for health behaviour change and use of online social networks. The user-centred methodology included four phases: 1) initial user inquiry on health behaviour and use of online social networks; 2) interview feedback on paper prototypes; 2) laboratory study on medium fidelity prototype; and 4) a field study on the high fidelity prototype. The points of inquiry through these phases were based on the ABC Framework. This yielded an online social network system that linked to external third party databases to deploy to users via an interactive website.

Design and analysis of sustainable computer mouse using design for disassembly methodology

NASA Astrophysics Data System (ADS)

Roni Sahroni, Taufik; Fitri Sukarman, Ahmad; Agung Mahardini, Karunia

2017-12-01

This paper presents the design and analysis of computer mouse using Design for Disassembly methodology. Basically, the existing computer mouse model consist a number of unnecessary part that cause the assembly and disassembly time in production. The objective of this project is to design a new computer mouse based on Design for Disassembly (DFD) methodology. The main methodology of this paper was proposed from sketch generation, concept selection, and concept scoring. Based on the design screening, design concept B was selected for further analysis. New design of computer mouse is proposed using fastening system. Furthermore, three materials of ABS, Polycarbonate, and PE high density were prepared to determine the environmental impact category. Sustainable analysis was conducted using software SolidWorks. As a result, PE High Density gives the lowers amount in the environmental category with great maximum stress value.

A Methodology and Software Environment for Testing Process Model’s Sequential Predictions with Protocols

DTIC Science & Technology

1992-12-21

in preparation). Foundations of artificial intelligence. Cambridge, MA: MIT Press. O’Reilly, R. C. (1991). X3DNet: An X- Based Neural Network ...2.2.3 Trace based protocol analysis 19 2.2A Summary of important data features 21 2.3 Tools related to process model testing 23 2.3.1 Tools for building...algorithm 57 3. Requirements for testing process models using trace based protocol 59 analysis 3.1 Definition of trace based protocol analysis (TBPA) 59

Accelerated Aging in Electrolytic Capacitors for Prognostics

NASA Technical Reports Server (NTRS)

Celaya, Jose R.; Kulkarni, Chetan; Saha, Sankalita; Biswas, Gautam; Goebel, Kai Frank

2012-01-01

The focus of this work is the analysis of different degradation phenomena based on thermal overstress and electrical overstress accelerated aging systems and the use of accelerated aging techniques for prognostics algorithm development. Results on thermal overstress and electrical overstress experiments are presented. In addition, preliminary results toward the development of physics-based degradation models are presented focusing on the electrolyte evaporation failure mechanism. An empirical degradation model based on percentage capacitance loss under electrical overstress is presented and used in: (i) a Bayesian-based implementation of model-based prognostics using a discrete Kalman filter for health state estimation, and (ii) a dynamic system representation of the degradation model for forecasting and remaining useful life (RUL) estimation. A leave-one-out validation methodology is used to assess the validity of the methodology under the small sample size constrain. The results observed on the RUL estimation are consistent through the validation tests comparing relative accuracy and prediction error. It has been observed that the inaccuracy of the model to represent the change in degradation behavior observed at the end of the test data is consistent throughout the validation tests, indicating the need of a more detailed degradation model or the use of an algorithm that could estimate model parameters on-line. Based on the observed degradation process under different stress intensity with rest periods, the need for more sophisticated degradation models is further supported. The current degradation model does not represent the capacitance recovery over rest periods following an accelerated aging stress period.

Multiphysics Analysis of a Solid-Core Nuclear Thermal Engine Thrust Chamber

NASA Technical Reports Server (NTRS)

Wang, Ten-See; Canabal, Francisco; Cheng, Gary; Chen, Yen-Sen

2006-01-01

The objective of this effort is to develop an efficient and accurate thermo-fluid computational methodology to predict environments for a hypothetical solid-core, nuclear thermal engine thrust chamber. The computational methodology is based on an unstructured-grid, pressure-based computational fluid dynamics methodology. Formulations for heat transfer in solids and porous media were implemented and anchored. A two-pronged approach was employed in this effort: A detailed thermo-fluid analysis on a multi-channel flow element for mid-section corrosion investigation; and a global modeling of the thrust chamber to understand the effect of hydrogen dissociation and recombination on heat transfer and thrust performance. The formulations and preliminary results on both aspects are presented.

A Design Methodology for Complex (E)-Learning. Innovative Session.

ERIC Educational Resources Information Center

Bastiaens, Theo; van Merrienboer, Jeroen; Hoogveld, Bert

Human resource development (HRD) specialists are searching for instructional design models that accommodate e-learning platforms. Van Merrienboer proposed the four-component instructional design model (4C/ID model) for competency-based education. The model's basic message is that well-designed learning environments can always be described in terms…

On the equivalence between traction- and stress-based approaches for the modeling of localized failure in solids

NASA Astrophysics Data System (ADS)

Wu, Jian-Ying; Cervera, Miguel

2015-09-01

This work investigates systematically traction- and stress-based approaches for the modeling of strong and regularized discontinuities induced by localized failure in solids. Two complementary methodologies, i.e., discontinuities localized in an elastic solid and strain localization of an inelastic softening solid, are addressed. In the former it is assumed a priori that the discontinuity forms with a continuous stress field and along the known orientation. A traction-based failure criterion is introduced to characterize the discontinuity and the orientation is determined from Mohr's maximization postulate. If the displacement jumps are retained as independent variables, the strong/regularized discontinuity approaches follow, requiring constitutive models for both the bulk and discontinuity. Elimination of the displacement jumps at the material point level results in the embedded/smeared discontinuity approaches in which an overall inelastic constitutive model fulfilling the static constraint suffices. The second methodology is then adopted to check whether the assumed strain localization can occur and identify its consequences on the resulting approaches. The kinematic constraint guaranteeing stress boundedness and continuity upon strain localization is established for general inelastic softening solids. Application to a unified stress-based elastoplastic damage model naturally yields all the ingredients of a localized model for the discontinuity (band), justifying the first methodology. Two dual but not necessarily equivalent approaches, i.e., the traction-based elastoplastic damage model and the stress-based projected discontinuity model, are identified. The former is equivalent to the embedded and smeared discontinuity approaches, whereas in the later the discontinuity orientation and associated failure criterion are determined consistently from the kinematic constraint rather than given a priori. The bi-directional connections and equivalence conditions between the traction- and stress-based approaches are classified. Closed-form results under plane stress condition are also given. A generic failure criterion of either elliptic, parabolic or hyperbolic type is analyzed in a unified manner, with the classical von Mises (J2), Drucker-Prager, Mohr-Coulomb and many other frequently employed criteria recovered as its particular cases.

A new hybrid transfinite element computational methodology for applicability to conduction/convection/radiation heat transfer

NASA Technical Reports Server (NTRS)

Tamma, Kumar K.; Railkar, Sudhir B.

1988-01-01

This paper describes new and recent advances in the development of a hybrid transfinite element computational methodology for applicability to conduction/convection/radiation heat transfer problems. The transfinite element methodology, while retaining the modeling versatility of contemporary finite element formulations, is based on application of transform techniques in conjunction with classical Galerkin schemes and is a hybrid approach. The purpose of this paper is to provide a viable hybrid computational methodology for applicability to general transient thermal analysis. Highlights and features of the methodology are described and developed via generalized formulations and applications to several test problems. The proposed transfinite element methodology successfully provides a viable computational approach and numerical test problems validate the proposed developments for conduction/convection/radiation thermal analysis.

Use of raster-based data layers to model spatial variation of seismotectonic data in probabilistic seismic hazard assessment

NASA Astrophysics Data System (ADS)

Zolfaghari, Mohammad R.

2009-07-01

Recent achievements in computer and information technology have provided the necessary tools to extend the application of probabilistic seismic hazard mapping from its traditional engineering use to many other applications. Examples for such applications are risk mitigation, disaster management, post disaster recovery planning and catastrophe loss estimation and risk management. Due to the lack of proper knowledge with regard to factors controlling seismic hazards, there are always uncertainties associated with all steps involved in developing and using seismic hazard models. While some of these uncertainties can be controlled by more accurate and reliable input data, the majority of the data and assumptions used in seismic hazard studies remain with high uncertainties that contribute to the uncertainty of the final results. In this paper a new methodology for the assessment of seismic hazard is described. The proposed approach provides practical facility for better capture of spatial variations of seismological and tectonic characteristics, which allows better treatment of their uncertainties. In the proposed approach, GIS raster-based data models are used in order to model geographical features in a cell-based system. The cell-based source model proposed in this paper provides a framework for implementing many geographically referenced seismotectonic factors into seismic hazard modelling. Examples for such components are seismic source boundaries, rupture geometry, seismic activity rate, focal depth and the choice of attenuation functions. The proposed methodology provides improvements in several aspects of the standard analytical tools currently being used for assessment and mapping of regional seismic hazard. The proposed methodology makes the best use of the recent advancements in computer technology in both software and hardware. The proposed approach is well structured to be implemented using conventional GIS tools.

Personalized Clinical Diagnosis in Data Bases for Treatment Support in Phthisiology.

PubMed

Lugovkina, T K; Skornyakov, S N; Golubev, D N; Egorov, E A; Medvinsky, I D

2016-01-01

The decision-making is a key event in the clinical practice. The program products with clinical decision support models in electronic data-base as well as with fixed decision moments of the real clinical practice and treatment results are very actual instruments for improving phthisiological practice and may be useful in the severe cases caused by the resistant strains of Mycobacterium tuberculosis. The methodology for gathering and structuring of useful information (critical clinical signals for decisions) is described. Additional coding of clinical diagnosis characteristics was implemented for numeric reflection of the personal situations. The created methodology for systematization and coding Clinical Events allowed to improve the clinical decision models for better clinical results.

Validation of a SysML based design for wireless sensor networks

NASA Astrophysics Data System (ADS)

Berrachedi, Amel; Rahim, Messaoud; Ioualalen, Malika; Hammad, Ahmed

2017-07-01

When developing complex systems, the requirement for the verification of the systems' design is one of the main challenges. Wireless Sensor Networks (WSNs) are examples of such systems. We address the problem of how WSNs must be designed to fulfil the system requirements. Using the SysML Language, we propose a Model Based System Engineering (MBSE) specification and verification methodology for designing WSNs. This methodology uses SysML to describe the WSNs requirements, structure and behaviour. Then, it translates the SysML elements to an analytic model, specifically, to a Deterministic Stochastic Petri Net. The proposed approach allows to design WSNs and study their behaviors and their energy performances.

Advanced Machine Learning Emulators of Radiative Transfer Models

NASA Astrophysics Data System (ADS)

Camps-Valls, G.; Verrelst, J.; Martino, L.; Vicent, J.

2017-12-01

Physically-based model inversion methodologies are based on physical laws and established cause-effect relationships. A plethora of remote sensing applications rely on the physical inversion of a Radiative Transfer Model (RTM), which lead to physically meaningful bio-geo-physical parameter estimates. The process is however computationally expensive, needs expert knowledge for both the selection of the RTM, its parametrization and the the look-up table generation, as well as its inversion. Mimicking complex codes with statistical nonlinear machine learning algorithms has become the natural alternative very recently. Emulators are statistical constructs able to approximate the RTM, although at a fraction of the computational cost, providing an estimation of uncertainty, and estimations of the gradient or finite integral forms. We review the field and recent advances of emulation of RTMs with machine learning models. We posit Gaussian processes (GPs) as the proper framework to tackle the problem. Furthermore, we introduce an automatic methodology to construct emulators for costly RTMs. The Automatic Gaussian Process Emulator (AGAPE) methodology combines the interpolation capabilities of GPs with the accurate design of an acquisition function that favours sampling in low density regions and flatness of the interpolation function. We illustrate the good capabilities of our emulators in toy examples, leaf and canopy levels PROSPECT and PROSAIL RTMs, and for the construction of an optimal look-up-table for atmospheric correction based on MODTRAN5.

Evaluating perceptual integration: uniting response-time- and accuracy-based methodologies.

PubMed

Eidels, Ami; Townsend, James T; Hughes, Howard C; Perry, Lacey A

2015-02-01

This investigation brings together a response-time system identification methodology (e.g., Townsend & Wenger Psychonomic Bulletin & Review 11, 391-418, 2004a) and an accuracy methodology, intended to assess models of integration across stimulus dimensions (features, modalities, etc.) that were proposed by Shaw and colleagues (e.g., Mulligan & Shaw Perception & Psychophysics 28, 471-478, 1980). The goal was to theoretically examine these separate strategies and to apply them conjointly to the same set of participants. The empirical phases were carried out within an extension of an established experimental design called the double factorial paradigm (e.g., Townsend & Nozawa Journal of Mathematical Psychology 39, 321-359, 1995). That paradigm, based on response times, permits assessments of architecture (parallel vs. serial processing), stopping rule (exhaustive vs. minimum time), and workload capacity, all within the same blocks of trials. The paradigm introduced by Shaw and colleagues uses a statistic formally analogous to that of the double factorial paradigm, but based on accuracy rather than response times. We demonstrate that the accuracy measure cannot discriminate between parallel and serial processing. Nonetheless, the class of models supported by the accuracy data possesses a suitable interpretation within the same set of models supported by the response-time data. The supported model, consistent across individuals, is parallel and has limited capacity, with the participants employing the appropriate stopping rule for the experimental setting.

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

Tom Elicson; Bentley Harwood; Jim Bouchard

Over a 12 month period, a fire PRA was developed for a DOE facility using the NUREG/CR-6850 EPRI/NRC fire PRA methodology. The fire PRA modeling included calculation of fire severity factors (SFs) and fire non-suppression probabilities (PNS) for each safe shutdown (SSD) component considered in the fire PRA model. The SFs were developed by performing detailed fire modeling through a combination of CFAST fire zone model calculations and Latin Hypercube Sampling (LHS). Component damage times and automatic fire suppression system actuation times calculated in the CFAST LHS analyses were then input to a time-dependent model of fire non-suppression probability. Themore » fire non-suppression probability model is based on the modeling approach outlined in NUREG/CR-6850 and is supplemented with plant specific data. This paper presents the methodology used in the DOE facility fire PRA for modeling fire-induced SSD component failures and includes discussions of modeling techniques for: • Development of time-dependent fire heat release rate profiles (required as input to CFAST), • Calculation of fire severity factors based on CFAST detailed fire modeling, and • Calculation of fire non-suppression probabilities.« less

Method for experimental investigation of transient operation on Laval test stand for model size turbines

NASA Astrophysics Data System (ADS)

Fraser, R.; Coulaud, M.; Aeschlimann, V.; Lemay, J.; Deschenes, C.

2016-11-01

With the growing proportion of inconstant energy source as wind and solar, hydroelectricity becomes a first class source of peak energy in order to regularize the grid. The important increase of start - stop cycles may then cause a premature ageing of runners by both a higher number of cycles in stress fluctuations and by reaching a higher stress level in absolute. Aiming to sustain good quality development on fully homologous scale model turbines, the Hydraulic Machines Laboratory (LAMH) of Laval University has developed a methodology to operate model size turbines on transient regimes such as start-up, stop or load rejection on its test stand. This methodology allows maintaining a constant head while the wicket gates are opening or closing in a representative speed on the model scale of what is made on the prototype. This paper first presents the opening speed on model based on dimensionless numbers, the methodology itself and its application. Then both its limitation and the first results using a bulb turbine are detailed.

Modeling Common-Sense Decisions in Artificial Intelligence

NASA Technical Reports Server (NTRS)

Zak, Michail

2010-01-01

A methodology has been conceived for efficient synthesis of dynamical models that simulate common-sense decision- making processes. This methodology is intended to contribute to the design of artificial-intelligence systems that could imitate human common-sense decision making or assist humans in making correct decisions in unanticipated circumstances. This methodology is a product of continuing research on mathematical models of the behaviors of single- and multi-agent systems known in biology, economics, and sociology, ranging from a single-cell organism at one extreme to the whole of human society at the other extreme. Earlier results of this research were reported in several prior NASA Tech Briefs articles, the three most recent and relevant being Characteristics of Dynamics of Intelligent Systems (NPO -21037), NASA Tech Briefs, Vol. 26, No. 12 (December 2002), page 48; Self-Supervised Dynamical Systems (NPO-30634), NASA Tech Briefs, Vol. 27, No. 3 (March 2003), page 72; and Complexity for Survival of Living Systems (NPO- 43302), NASA Tech Briefs, Vol. 33, No. 7 (July 2009), page 62. The methodology involves the concepts reported previously, albeit viewed from a different perspective. One of the main underlying ideas is to extend the application of physical first principles to the behaviors of living systems. Models of motor dynamics are used to simulate the observable behaviors of systems or objects of interest, and models of mental dynamics are used to represent the evolution of the corresponding knowledge bases. For a given system, the knowledge base is modeled in the form of probability distributions and the mental dynamics is represented by models of the evolution of the probability densities or, equivalently, models of flows of information. Autonomy is imparted to the decisionmaking process by feedback from mental to motor dynamics. This feedback replaces unavailable external information by information stored in the internal knowledge base. Representation of the dynamical models in a parameterized form reduces the task of common-sense-based decision making to a solution of the following hetero-associated-memory problem: store a set of m predetermined stochastic processes given by their probability distributions in such a way that when presented with an unexpected change in the form of an input out of the set of M inputs, the coupled motormental dynamics converges to the corresponding one of the m pre-assigned stochastic process, and a sample of this process represents the decision.

Variability-aware compact modeling and statistical circuit validation on SRAM test array

NASA Astrophysics Data System (ADS)

Qiao, Ying; Spanos, Costas J.

2016-03-01

Variability modeling at the compact transistor model level can enable statistically optimized designs in view of limitations imposed by the fabrication technology. In this work we propose a variability-aware compact model characterization methodology based on stepwise parameter selection. Transistor I-V measurements are obtained from bit transistor accessible SRAM test array fabricated using a collaborating foundry's 28nm FDSOI technology. Our in-house customized Monte Carlo simulation bench can incorporate these statistical compact models; and simulation results on SRAM writability performance are very close to measurements in distribution estimation. Our proposed statistical compact model parameter extraction methodology also has the potential of predicting non-Gaussian behavior in statistical circuit performances through mixtures of Gaussian distributions.

A data storage and retrieval model for Louisiana traffic operations data : technical summary.

DOT National Transportation Integrated Search

1996-08-01

The overall goal of this research study was to develop a prototype computer-based indexing model for traffic operation data in DOTD. The methodology included: 1) extraction of state road network, 2) development of geographic reference model, 3) engin...

USEPA SHEDS MODEL: METHODOLOGY FOR EXPOSURE ASSESSMENT FOR WOOD PRESERVATIVES

EPA Science Inventory

A physically-based, Monte Carlo probabilistic model (SHEDS-Wood: Stochastic Human Exposure and Dose Simulation model for wood preservatives) has been applied to assess the exposure and dose of children to arsenic (As) and chromium (Cr) from contact with chromated copper arsenat...

Commercial Demand Module - NEMS Documentation

EIA Publications

2017-01-01

Documents the objectives, analytical approach and development of the National Energy Modeling System (NEMS) Commercial Sector Demand Module. The report catalogues and describes the model assumptions, computational methodology, parameter estimation techniques, model source code, and forecast results generated through the synthesis and scenario development based on these components.

Clinical, information and business process modeling to promote development of safe and flexible software.

PubMed

Liaw, Siaw-Teng; Deveny, Elizabeth; Morrison, Iain; Lewis, Bryn

2006-09-01

Using a factorial vignette survey and modeling methodology, we developed clinical and information models - incorporating evidence base, key concepts, relevant terms, decision-making and workflow needed to practice safely and effectively - to guide the development of an integrated rule-based knowledge module to support prescribing decisions in asthma. We identified workflows, decision-making factors, factor use, and clinician information requirements. The Unified Modeling Language (UML) and public domain software and knowledge engineering tools (e.g. Protégé) were used, with the Australian GP Data Model as the starting point for expressing information needs. A Web Services service-oriented architecture approach was adopted within which to express functional needs, and clinical processes and workflows were expressed in the Business Process Execution Language (BPEL). This formal analysis and modeling methodology to define and capture the process and logic of prescribing best practice in a reference implementation is fundamental to tackling deficiencies in prescribing decision support software.

Application of enhanced modern structured analysis techniques to Space Station Freedom electric power system requirements

NASA Technical Reports Server (NTRS)

Biernacki, John; Juhasz, John; Sadler, Gerald

1991-01-01

A team of Space Station Freedom (SSF) system engineers are in the process of extensive analysis of the SSF requirements, particularly those pertaining to the electrical power system (EPS). The objective of this analysis is the development of a comprehensive, computer-based requirements model, using an enhanced modern structured analysis methodology (EMSA). Such a model provides a detailed and consistent representation of the system's requirements. The process outlined in the EMSA methodology is unique in that it allows the graphical modeling of real-time system state transitions, as well as functional requirements and data relationships, to be implemented using modern computer-based tools. These tools permit flexible updating and continuous maintenance of the models. Initial findings resulting from the application of EMSA to the EPS have benefited the space station program by linking requirements to design, providing traceability of requirements, identifying discrepancies, and fostering an understanding of the EPS.

Surrogate Modeling of High-Fidelity Fracture Simulations for Real-Time Residual Strength Predictions

NASA Technical Reports Server (NTRS)

Spear, Ashley D.; Priest, Amanda R.; Veilleux, Michael G.; Ingraffea, Anthony R.; Hochhalter, Jacob D.

2011-01-01

A surrogate model methodology is described for predicting in real time the residual strength of flight structures with discrete-source damage. Starting with design of experiment, an artificial neural network is developed that takes as input discrete-source damage parameters and outputs a prediction of the structural residual strength. Target residual strength values used to train the artificial neural network are derived from 3D finite element-based fracture simulations. A residual strength test of a metallic, integrally-stiffened panel is simulated to show that crack growth and residual strength are determined more accurately in discrete-source damage cases by using an elastic-plastic fracture framework rather than a linear-elastic fracture mechanics-based method. Improving accuracy of the residual strength training data would, in turn, improve accuracy of the surrogate model. When combined, the surrogate model methodology and high-fidelity fracture simulation framework provide useful tools for adaptive flight technology.

Surrogate Modeling of High-Fidelity Fracture Simulations for Real-Time Residual Strength Predictions

NASA Technical Reports Server (NTRS)

Spear, Ashley D.; Priest, Amanda R.; Veilleux, Michael G.; Ingraffea, Anthony R.; Hochhalter, Jacob D.

2011-01-01

A surrogate model methodology is described for predicting, during flight, the residual strength of aircraft structures that sustain discrete-source damage. Starting with design of experiment, an artificial neural network is developed that takes as input discrete-source damage parameters and outputs a prediction of the structural residual strength. Target residual strength values used to train the artificial neural network are derived from 3D finite element-based fracture simulations. Two ductile fracture simulations are presented to show that crack growth and residual strength are determined more accurately in discrete-source damage cases by using an elastic-plastic fracture framework rather than a linear-elastic fracture mechanics-based method. Improving accuracy of the residual strength training data does, in turn, improve accuracy of the surrogate model. When combined, the surrogate model methodology and high fidelity fracture simulation framework provide useful tools for adaptive flight technology.

A hybrid system identification methodology for wireless structural health monitoring systems based on dynamic substructuring

NASA Astrophysics Data System (ADS)

Dragos, Kosmas; Smarsly, Kay

2016-04-01

System identification has been employed in numerous structural health monitoring (SHM) applications. Traditional system identification methods usually rely on centralized processing of structural response data to extract information on structural parameters. However, in wireless SHM systems the centralized processing of structural response data introduces a significant communication bottleneck. Exploiting the merits of decentralization and on-board processing power of wireless SHM systems, many system identification methods have been successfully implemented in wireless sensor networks. While several system identification approaches for wireless SHM systems have been proposed, little attention has been paid to obtaining information on the physical parameters (e.g. stiffness, damping) of the monitored structure. This paper presents a hybrid system identification methodology suitable for wireless sensor networks based on the principles of component mode synthesis (dynamic substructuring). A numerical model of the monitored structure is embedded into the wireless sensor nodes in a distributed manner, i.e. the entire model is segmented into sub-models, each embedded into one sensor node corresponding to the substructure the sensor node is assigned to. The parameters of each sub-model are estimated by extracting local mode shapes and by applying the equations of the Craig-Bampton method on dynamic substructuring. The proposed methodology is validated in a laboratory test conducted on a four-story frame structure to demonstrate the ability of the methodology to yield accurate estimates of stiffness parameters. Finally, the test results are discussed and an outlook on future research directions is provided.

Watermark: An Application and Methodology and Application for Interactive and intelligent Decision Support for Groundwater Systems

NASA Astrophysics Data System (ADS)

Pierce, S. A.; Wagner, K.; Schwartz, S.; Gentle, J. N., Jr.

2016-12-01

Critical water resources face the effects of historic drought, increased demand, and potential contamination, the need has never been greater to develop resources to effectively communicate conservation and protection across a broad audience and geographical area. The Watermark application and macro-analysis methodology merges topical analysis of context rich corpus from policy texts with multi-attributed solution sets from integrated models of water resource and other subsystems, such as mineral, food, energy, or environmental systems to construct a scalable, robust, and reproducible approach for identifying links between policy and science knowledge bases. The Watermark application is an open-source, interactive workspace to support science-based visualization and decision making. Designed with generalization in mind, Watermark is a flexible platform that allows for data analysis and inclusion of large datasets with an interactive front-end capable of connecting with other applications as well as advanced computing resources. In addition, the Watermark analysis methodology offers functionality that streamlines communication with non-technical users for policy, education, or engagement with groups around scientific topics of societal relevance. The technology stack for Watermark was selected with the goal of creating a robust and dynamic modular codebase that can be adjusted to fit many use cases and scale to support usage loads that range between simple data display to complex scientific simulation-based modelling and analytics. The methodology uses to topical analysis and simulation-optimization to systematically analyze the policy and management realities of resource systems and explicitly connect the social and problem contexts with science-based and engineering knowledge from models. A case example demonstrates use in a complex groundwater resources management study highlighting multi-criteria spatial decision making and uncertainty comparisons.

Choice-Based Segmentation as an Enrollment Management Tool

ERIC Educational Resources Information Center

Young, Mark R.

2002-01-01

This article presents an approach to enrollment management based on target marketing strategies developed from a choice-based segmentation methodology. Students are classified into "switchable" or "non-switchable" segments based on their probability of selecting specific majors. A modified multinomial logit choice model is used to identify…

Nonlinear data assimilation: towards a prediction of the solar cycle

NASA Astrophysics Data System (ADS)

Svedin, Andreas

The solar cycle is the cyclic variation of solar activity, with a span of 9-14 years. The prediction of the solar cycle is an important and unsolved problem with implications for communications, aviation and other aspects of our high-tech society. Our interest is model-based prediction, and we present a self-consistent procedure for parameter estimation and model state estimation, even when only one of several model variables can be observed. Data assimilation is the art of comparing, combining and transferring observed data into a mathematical model or computer simulation. We use the 3DVAR methodology, based on the notion of least squares, to present an implementation of a traditional data assimilation. Using the Shadowing Filter — a recently developed method for nonlinear data assimilation — we outline a path towards model based prediction of the solar cycle. To achieve this end we solve a number of methodological challenges related to unobserved variables. We also provide a new framework for interpretation that can guide future predictions of the Sun and other astrophysical objects.

Application of new methodologies based on design of experiments, independent component analysis and design space for robust optimization in liquid chromatography.

PubMed

Debrus, Benjamin; Lebrun, Pierre; Ceccato, Attilio; Caliaro, Gabriel; Rozet, Eric; Nistor, Iolanda; Oprean, Radu; Rupérez, Francisco J; Barbas, Coral; Boulanger, Bruno; Hubert, Philippe

2011-04-08

HPLC separations of an unknown sample mixture and a pharmaceutical formulation have been optimized using a recently developed chemometric methodology proposed by W. Dewé et al. in 2004 and improved by P. Lebrun et al. in 2008. This methodology is based on experimental designs which are used to model retention times of compounds of interest. Then, the prediction accuracy and the optimal separation robustness, including the uncertainty study, were evaluated. Finally, the design space (ICH Q8(R1) guideline) was computed as the probability for a criterion to lie in a selected range of acceptance. Furthermore, the chromatograms were automatically read. Peak detection and peak matching were carried out with a previously developed methodology using independent component analysis published by B. Debrus et al. in 2009. The present successful applications strengthen the high potential of these methodologies for the automated development of chromatographic methods. Copyright © 2011 Elsevier B.V. All rights reserved.

Computational studies of horizontal axis wind turbines

NASA Astrophysics Data System (ADS)

Xu, Guanpeng

A numerical technique has been developed for efficiently simulating fully three-dimensional viscous fluid flow around horizontal axis wind turbines (HAWT) using a zonal approach. The flow field is viewed as a combination of viscous regions, inviscid regions and vortices. The method solves the costly unsteady Reynolds averaged Navier-Stokes (RANS) equations only in the viscous region around the turbine blades. It solves the full potential equation in the inviscid region where flow is irrotational and isentropic. The tip vortices are simulated using a Lagrangean approach, thus removing the need to accurately resolve them on a fine grid. The hybrid method is shown to provide good results with modest CPU resources. A full Navier-Stokes based methodology has also been developed for modeling wind turbines at high wind conditions where extensive stall may occur. An overset grid based version that can model rotor-tower interactions has been developed. Finally, a blade element theory based methodology has been developed for the purpose of developing improved tip loss models and stall delay models. The effects of turbulence are simulated using a zero equation eddy viscosity model, or a one equation Spalart-Allmaras model. Two transition models, one based on the Eppler's criterion, and the other based on Michel's criterion, have been developed and tested. The hybrid method has been extensively validated for axial wind conditions for three rotors---NREL Phase II, Phase III, and Phase VI configurations. A limited set of calculations has been done for rotors operating under yaw conditions. Preliminary simulations have also been carried out to assess the effects of the tower wake on the rotor. In most of these cases, satisfactory agreement has been obtained with measurements. Using the numerical results from present methodologies as a guide, Prandtl's tip loss model and Corrigan's stall delay model were correlated with present calculations. An improved tip loss model has been obtained. A correction to the Corrigan's stall delay model has also been developed. Incorporation of these corrections is shown to considerably improve power predictions, even when a very simple aerodynamic theory---blade element method with annular inflow---is used.

TH-CD-202-07: A Methodology for Generating Numerical Phantoms for Radiation Therapy Using Geometric Attribute Distribution Models

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

Dolly, S; Chen, H; Mutic, S

Purpose: A persistent challenge for the quality assessment of radiation therapy treatments (e.g. contouring accuracy) is the absence of the known, ground truth for patient data. Moreover, assessment results are often patient-dependent. Computer simulation studies utilizing numerical phantoms can be performed for quality assessment with a known ground truth. However, previously reported numerical phantoms do not include the statistical properties of inter-patient variations, as their models are based on only one patient. In addition, these models do not incorporate tumor data. In this study, a methodology was developed for generating numerical phantoms which encapsulate the statistical variations of patients withinmore » radiation therapy, including tumors. Methods: Based on previous work in contouring assessment, geometric attribute distribution (GAD) models were employed to model both the deterministic and stochastic properties of individual organs via principle component analysis. Using pre-existing radiation therapy contour data, the GAD models are trained to model the shape and centroid distributions of each organ. Then, organs with different shapes and positions can be generated by assigning statistically sound weights to the GAD model parameters. Organ contour data from 20 retrospective prostate patient cases were manually extracted and utilized to train the GAD models. As a demonstration, computer-simulated CT images of generated numerical phantoms were calculated and assessed subjectively and objectively for realism. Results: A cohort of numerical phantoms of the male human pelvis was generated. CT images were deemed realistic both subjectively and objectively in terms of image noise power spectrum. Conclusion: A methodology has been developed to generate realistic numerical anthropomorphic phantoms using pre-existing radiation therapy data. The GAD models guarantee that generated organs span the statistical distribution of observed radiation therapy patients, according to the training dataset. The methodology enables radiation therapy treatment assessment with multi-modality imaging and a known ground truth, and without patient-dependent bias.« less

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

NASA Technical Reports Server (NTRS)

2005-01-01

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

Use of a land-use-based emissions inventory in delineating clean-air zones

Treesearch

Victor S. Fahrer; Howard A. Peters

1977-01-01

Use of a land-use-based emissions inventory from which air-pollution estimates can be projected was studied. First the methodology used to establish a land-use-based emission inventory is described. Then this inventory is used as input in a simple model that delineates clean air and buffer zones. The model is applied to the town of Burlington, Massachusetts....

Analysing the Correlation between Social Network Analysis Measures and Performance of Students in Social Network-Based Engineering Education

ERIC Educational Resources Information Center

Putnik, Goran; Costa, Eric; Alves, Cátia; Castro, Hélio; Varela, Leonilde; Shah, Vaibhav

2016-01-01

Social network-based engineering education (SNEE) is designed and implemented as a model of Education 3.0 paradigm. SNEE represents a new learning methodology, which is based on the concept of social networks and represents an extended model of project-led education. The concept of social networks was applied in the real-life experiment,…

Ab-Initio Molecular Dynamics Simulations of Molten Ni-Based Superalloys (Preprint)

DTIC Science & Technology

2011-10-01

in liquid–metal density with composition and temperature across the solidification zone. Here, fundamental properties of molten Ni -based alloys ...temperature across the solidification zone. Here, fundamental properties of molten Ni -based alloys , required for modeling these instabilities, are...temperature is assessed in model Ni -Al-W and RENE-N4 alloys . Calculations are performed using a recently implemented constant pressure methodology (NPT) which

[New calculation algorithms in brachytherapy for iridium 192 treatments].

PubMed

Robert, C; Dumas, I; Martinetti, F; Chargari, C; Haie-Meder, C; Lefkopoulos, D

2018-05-18

Since 1995, the brachytherapy dosimetry protocols follow the methodology recommended by the Task Group 43. This methodology, which has the advantage of being fast, is based on several approximations that are not always valid in clinical conditions. Model-based dose calculation algorithms have recently emerged in treatment planning stations and are considered as a major evolution by allowing for consideration of the patient's finite dimensions, tissue heterogeneities and the presence of high atomic number materials in applicators. In 2012, a report from the American Association of Physicists in Medicine Radiation Therapy Task Group 186 reviews these models and makes recommendations for their clinical implementation. This review focuses on the use of model-based dose calculation algorithms in the context of iridium 192 treatments. After a description of these algorithms and their clinical implementation, a summary of the main questions raised by these new methods is performed. Considerations regarding the choice of the medium used for the dose specification and the recommended methodology for assigning materials characteristics are especially described. In the last part, recent concrete examples from the literature illustrate the capabilities of these new algorithms on clinical cases. Copyright © 2018 Société française de radiothérapie oncologique (SFRO). Published by Elsevier SAS. All rights reserved.

Computing elastic‐rebound‐motivated rarthquake probabilities in unsegmented fault models: a new methodology supported by physics‐based simulators

USGS Publications Warehouse

Field, Edward H.

2015-01-01

A methodology is presented for computing elastic‐rebound‐based probabilities in an unsegmented fault or fault system, which involves computing along‐fault averages of renewal‐model parameters. The approach is less biased and more self‐consistent than a logical extension of that applied most recently for multisegment ruptures in California. It also enables the application of magnitude‐dependent aperiodicity values, which the previous approach does not. Monte Carlo simulations are used to analyze long‐term system behavior, which is generally found to be consistent with that of physics‐based earthquake simulators. Results cast doubt that recurrence‐interval distributions at points on faults look anything like traditionally applied renewal models, a fact that should be considered when interpreting paleoseismic data. We avoid such assumptions by changing the "probability of what" question (from offset at a point to the occurrence of a rupture, assuming it is the next event to occur). The new methodology is simple, although not perfect in terms of recovering long‐term rates in Monte Carlo simulations. It represents a reasonable, improved way to represent first‐order elastic‐rebound predictability, assuming it is there in the first place, and for a system that clearly exhibits other unmodeled complexities, such as aftershock triggering.

Satellite-based terrestrial production efficiency modeling

PubMed Central

McCallum, Ian; Wagner, Wolfgang; Schmullius, Christiane; Shvidenko, Anatoly; Obersteiner, Michael; Fritz, Steffen; Nilsson, Sten

2009-01-01

Production efficiency models (PEMs) are based on the theory of light use efficiency (LUE) which states that a relatively constant relationship exists between photosynthetic carbon uptake and radiation receipt at the canopy level. Challenges remain however in the application of the PEM methodology to global net primary productivity (NPP) monitoring. The objectives of this review are as follows: 1) to describe the general functioning of six PEMs (CASA; GLO-PEM; TURC; C-Fix; MOD17; and BEAMS) identified in the literature; 2) to review each model to determine potential improvements to the general PEM methodology; 3) to review the related literature on satellite-based gross primary productivity (GPP) and NPP modeling for additional possibilities for improvement; and 4) based on this review, propose items for coordinated research. This review noted a number of possibilities for improvement to the general PEM architecture - ranging from LUE to meteorological and satellite-based inputs. Current PEMs tend to treat the globe similarly in terms of physiological and meteorological factors, often ignoring unique regional aspects. Each of the existing PEMs has developed unique methods to estimate NPP and the combination of the most successful of these could lead to improvements. It may be beneficial to develop regional PEMs that can be combined under a global framework. The results of this review suggest the creation of a hybrid PEM could bring about a significant enhancement to the PEM methodology and thus terrestrial carbon flux modeling. Key items topping the PEM research agenda identified in this review include the following: LUE should not be assumed constant, but should vary by plant functional type (PFT) or photosynthetic pathway; evidence is mounting that PEMs should consider incorporating diffuse radiation; continue to pursue relationships between satellite-derived variables and LUE, GPP and autotrophic respiration (Ra); there is an urgent need for satellite-based biomass measurements to improve Ra estimation; and satellite-based soil moisture data could improve determination of soil water stress. PMID:19765285

Capturing security requirements for software systems.

PubMed

El-Hadary, Hassan; El-Kassas, Sherif

2014-07-01

Security is often an afterthought during software development. Realizing security early, especially in the requirement phase, is important so that security problems can be tackled early enough before going further in the process and avoid rework. A more effective approach for security requirement engineering is needed to provide a more systematic way for eliciting adequate security requirements. This paper proposes a methodology for security requirement elicitation based on problem frames. The methodology aims at early integration of security with software development. The main goal of the methodology is to assist developers elicit adequate security requirements in a more systematic way during the requirement engineering process. A security catalog, based on the problem frames, is constructed in order to help identifying security requirements with the aid of previous security knowledge. Abuse frames are used to model threats while security problem frames are used to model security requirements. We have made use of evaluation criteria to evaluate the resulting security requirements concentrating on conflicts identification among requirements. We have shown that more complete security requirements can be elicited by such methodology in addition to the assistance offered to developers to elicit security requirements in a more systematic way.

Capturing security requirements for software systems

PubMed Central

El-Hadary, Hassan; El-Kassas, Sherif

2014-01-01

Security is often an afterthought during software development. Realizing security early, especially in the requirement phase, is important so that security problems can be tackled early enough before going further in the process and avoid rework. A more effective approach for security requirement engineering is needed to provide a more systematic way for eliciting adequate security requirements. This paper proposes a methodology for security requirement elicitation based on problem frames. The methodology aims at early integration of security with software development. The main goal of the methodology is to assist developers elicit adequate security requirements in a more systematic way during the requirement engineering process. A security catalog, based on the problem frames, is constructed in order to help identifying security requirements with the aid of previous security knowledge. Abuse frames are used to model threats while security problem frames are used to model security requirements. We have made use of evaluation criteria to evaluate the resulting security requirements concentrating on conflicts identification among requirements. We have shown that more complete security requirements can be elicited by such methodology in addition to the assistance offered to developers to elicit security requirements in a more systematic way. PMID:25685514

Methodology Developed for Modeling the Fatigue Crack Growth Behavior of Single-Crystal, Nickel-Base Superalloys

NASA Technical Reports Server (NTRS)

1996-01-01

Because of their superior high-temperature properties, gas generator turbine airfoils made of single-crystal, nickel-base superalloys are fast becoming the standard equipment on today's advanced, high-performance aerospace engines. The increased temperature capabilities of these airfoils has allowed for a significant increase in the operating temperatures in turbine sections, resulting in superior propulsion performance and greater efficiencies. However, the previously developed methodologies for life-prediction models are based on experience with polycrystalline alloys and may not be applicable to single-crystal alloys under certain operating conditions. One of the main areas where behavior differences between single-crystal and polycrystalline alloys are readily apparent is subcritical fatigue crack growth (FCG). The NASA Lewis Research Center's work in this area enables accurate prediction of the subcritical fatigue crack growth behavior in single-crystal, nickel-based superalloys at elevated temperatures.

Application of process mining to assess the data quality of routinely collected time-based performance data sourced from electronic health records by validating process conformance.

PubMed

Perimal-Lewis, Lua; Teubner, David; Hakendorf, Paul; Horwood, Chris

2016-12-01

Effective and accurate use of routinely collected health data to produce Key Performance Indicator reporting is dependent on the underlying data quality. In this research, Process Mining methodology and tools were leveraged to assess the data quality of time-based Emergency Department data sourced from electronic health records. This research was done working closely with the domain experts to validate the process models. The hospital patient journey model was used to assess flow abnormalities which resulted from incorrect timestamp data used in time-based performance metrics. The research demonstrated process mining as a feasible methodology to assess data quality of time-based hospital performance metrics. The insight gained from this research enabled appropriate corrective actions to be put in place to address the data quality issues. © The Author(s) 2015.

Regression Tree-Based Methodology for Customizing Building Energy Benchmarks to Individual Commercial Buildings

NASA Astrophysics Data System (ADS)

Kaskhedikar, Apoorva Prakash

According to the U.S. Energy Information Administration, commercial buildings represent about 40% of the United State's energy consumption of which office buildings consume a major portion. Gauging the extent to which an individual building consumes energy in excess of its peers is the first step in initiating energy efficiency improvement. Energy Benchmarking offers initial building energy performance assessment without rigorous evaluation. Energy benchmarking tools based on the Commercial Buildings Energy Consumption Survey (CBECS) database are investigated in this thesis. This study proposes a new benchmarking methodology based on decision trees, where a relationship between the energy use intensities (EUI) and building parameters (continuous and categorical) is developed for different building types. This methodology was applied to medium office and school building types contained in the CBECS database. The Random Forest technique was used to find the most influential parameters that impact building energy use intensities. Subsequently, correlations which were significant were identified between EUIs and CBECS variables. Other than floor area, some of the important variables were number of workers, location, number of PCs and main cooling equipment. The coefficient of variation was used to evaluate the effectiveness of the new model. The customization technique proposed in this thesis was compared with another benchmarking model that is widely used by building owners and designers namely, the ENERGY STAR's Portfolio Manager. This tool relies on the standard Linear Regression methods which is only able to handle continuous variables. The model proposed uses data mining technique and was found to perform slightly better than the Portfolio Manager. The broader impacts of the new benchmarking methodology proposed is that it allows for identifying important categorical variables, and then incorporating them in a local, as against a global, model framework for EUI pertinent to the building type. The ability to identify and rank the important variables is of great importance in practical implementation of the benchmarking tools which rely on query-based building and HVAC variable filters specified by the user.

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

Mou, J.I.; King, C.

The focus of this study is to develop a sensor fused process modeling and control methodology to model, assess, and then enhance the performance of a hexapod machine for precision product realization. Deterministic modeling technique was used to derive models for machine performance assessment and enhancement. Sensor fusion methodology was adopted to identify the parameters of the derived models. Empirical models and computational algorithms were also derived and implemented to model, assess, and then enhance the machine performance. The developed sensor fusion algorithms can be implemented on a PC-based open architecture controller to receive information from various sensors, assess themore » status of the process, determine the proper action, and deliver the command to actuators for task execution. This will enhance a hexapod machine`s capability to produce workpieces within the imposed dimensional tolerances.« less

Coarse-grained molecular dynamics simulations for giant protein-DNA complexes

NASA Astrophysics Data System (ADS)

Takada, Shoji

Biomolecules are highly hierarchic and intrinsically flexible. Thus, computational modeling calls for multi-scale methodologies. We have been developing a coarse-grained biomolecular model where on-average 10-20 atoms are grouped into one coarse-grained (CG) particle. Interactions among CG particles are tuned based on atomistic interactions and the fluctuation matching algorithm. CG molecular dynamics methods enable us to simulate much longer time scale motions of much larger molecular systems than fully atomistic models. After broad sampling of structures with CG models, we can easily reconstruct atomistic models, from which one can continue conventional molecular dynamics simulations if desired. Here, we describe our CG modeling methodology for protein-DNA complexes, together with various biological applications, such as the DNA duplication initiation complex, model chromatins, and transcription factor dynamics on chromatin-like environment.

A Model-Free Diagnostic for Single-Peakedness of Item Responses Using Ordered Conditional Means

ERIC Educational Resources Information Center

Polak, Marike; De Rooij, Mark; Heiser, Willem J.

2012-01-01

In this article we propose a model-free diagnostic for single-peakedness (unimodality) of item responses. Presuming a unidimensional unfolding scale and a given item ordering, we approximate item response functions of all items based on ordered conditional means (OCM). The proposed OCM methodology is based on Thurstone & Chave's (1929) "criterion…

An e-Portfolio-Based Model for the Application and Sharing of College English ESP MOOCs

ERIC Educational Resources Information Center

Chen, Jinshi

2017-01-01

The informationalized knowledge sharing of MOOCs not only promotes the change of teaching concept and the reform of teaching methodology, but also provides a new opportunity for the teaching resource integration and sharing between different universities. The present study has constructed an e-Portfolio-based model for the application and sharing…

Identification of walking human model using agent-based modelling

NASA Astrophysics Data System (ADS)

Shahabpoor, Erfan; Pavic, Aleksandar; Racic, Vitomir

2018-03-01

The interaction of walking people with large vibrating structures, such as footbridges and floors, in the vertical direction is an important yet challenging phenomenon to describe mathematically. Several different models have been proposed in the literature to simulate interaction of stationary people with vibrating structures. However, the research on moving (walking) human models, explicitly identified for vibration serviceability assessment of civil structures, is still sparse. In this study, the results of a comprehensive set of FRF-based modal tests were used, in which, over a hundred test subjects walked in different group sizes and walking patterns on a test structure. An agent-based model was used to simulate discrete traffic-structure interactions. The occupied structure modal parameters found in tests were used to identify the parameters of the walking individual's single-degree-of-freedom (SDOF) mass-spring-damper model using 'reverse engineering' methodology. The analysis of the results suggested that the normal distribution with the average of μ = 2.85Hz and standard deviation of σ = 0.34Hz can describe human SDOF model natural frequency. Similarly, the normal distribution with μ = 0.295 and σ = 0.047 can describe the human model damping ratio. Compared to the previous studies, the agent-based modelling methodology proposed in this paper offers significant flexibility in simulating multi-pedestrian walking traffics, external forces and simulating different mechanisms of human-structure and human-environment interaction at the same time.

A proposal on teaching methodology: cooperative learning by peer tutoring based on the case method

NASA Astrophysics Data System (ADS)

Pozo, Antonio M.; Durbán, Juan J.; Salas, Carlos; del Mar Lázaro, M.

2014-07-01

The European Higher Education Area (EHEA) proposes substantial changes in the teaching-learning model, moving from a model based mainly on the activity of teachers to a model in which the true protagonist is the student. This new framework requires that students develop new abilities and acquire specific skills. This also implies that the teacher should incorporate new methodologies in class. In this work, we present a proposal on teaching methodology based on cooperative learning and peer tutoring by case study. A noteworthy aspect of the case-study method is that it presents situations that can occur in real life. Therefore, students can acquire certain skills that will be useful in their future professional practice. An innovative aspect in the teaching methodology that we propose is to form work groups consisting of students from different levels in the same major. In our case, the teaching of four subjects would be involved: one subject of the 4th year, one subject of the 3rd year, and two subjects of the 2nd year of the Degree in Optics and Optometry of the University of Granada, Spain. Each work group would consist of a professor and a student of the 4th year, a professor and a student of the 3rd year, and two professors and two students of the 2nd year. Each work group would have a tutoring process from each professor for the corresponding student, and a 4th-year student providing peer tutoring for the students of the 2nd and 3rd year.

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

DTIC Science & Technology

2008-05-20

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

Applications of Quantum Cascade Laser Spectroscopy in the Analysis of Pharmaceutical Formulations.

PubMed

Galán-Freyle, Nataly J; Pacheco-Londoño, Leonardo C; Román-Ospino, Andrés D; Hernandez-Rivera, Samuel P

2016-09-01

Quantum cascade laser spectroscopy was used to quantify active pharmaceutical ingredient content in a model formulation. The analyses were conducted in non-contact mode by mid-infrared diffuse reflectance. Measurements were carried out at a distance of 15 cm, covering the spectral range 1000-1600 cm(-1) Calibrations were generated by applying multivariate analysis using partial least squares models. Among the figures of merit of the proposed methodology are the high analytical sensitivity equivalent to 0.05% active pharmaceutical ingredient in the formulation, high repeatability (2.7%), high reproducibility (5.4%), and low limit of detection (1%). The relatively high power of the quantum-cascade-laser-based spectroscopic system resulted in the design of detection and quantification methodologies for pharmaceutical applications with high accuracy and precision that are comparable to those of methodologies based on near-infrared spectroscopy, attenuated total reflection mid-infrared Fourier transform infrared spectroscopy, and Raman spectroscopy. © The Author(s) 2016.

H-infinity based integrated flight-propulsion control design for a STOVL aircraft in transition flight

NASA Technical Reports Server (NTRS)

Garg, Sanjay; Mattern, Duane L.; Bright, Michelle M.; Ouzts, Peter J.

1990-01-01

Results are presented from an application of H-infinity control design methodology to a centralized integrated flight/propulsion control (IFPC) system design for a supersonic Short Take-Off and Vertical Landing (STOVL) fighter aircraft in transition flight. The overall design methodology consists of a centralized IFPC controller design with controller partitioning. Only the feedback controller design portion of the methodology is addressed. Design and evaluation vehicle models are summarized, and insight is provided into formulating the H-infinity control problem such that it reflects the IFPC design objectives. The H-infinity controller is shown to provide decoupled command tracking for the design model. The controller order could be significantly reduced by modal residualization of the fast controller modes without any deterioration in performance. A discussion is presented of the areas in which the controller performance needs to be improved, and ways in which these improvements can be achieved within the framework of an H-infinity based linear control design.

Statistical optimization of process parameters for lipase-catalyzed synthesis of triethanolamine-based esterquats using response surface methodology in 2-liter bioreactor.

PubMed

Masoumi, Hamid Reza Fard; Basri, Mahiran; Kassim, Anuar; Abdullah, Dzulkefly Kuang; Abdollahi, Yadollah; Abd Gani, Siti Salwa; Rezaee, Malahat

2013-01-01

Lipase-catalyzed production of triethanolamine-based esterquat by esterification of oleic acid (OA) with triethanolamine (TEA) in n-hexane was performed in 2 L stirred-tank reactor. A set of experiments was designed by central composite design to process modeling and statistically evaluate the findings. Five independent process variables, including enzyme amount, reaction time, reaction temperature, substrates molar ratio of OA to TEA, and agitation speed, were studied under the given conditions designed by Design Expert software. Experimental data were examined for normality test before data processing stage and skewness and kurtosis indices were determined. The mathematical model developed was found to be adequate and statistically accurate to predict the optimum conversion of product. Response surface methodology with central composite design gave the best performance in this study, and the methodology as a whole has been proven to be adequate for the design and optimization of the enzymatic process.

Coupled socioeconomic-crop modelling for the participatory local analysis of climate change impacts on smallholder farmers in Guatemala

NASA Astrophysics Data System (ADS)

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

2015-12-01

The modelling of the impacts of climate change on agriculture requires the inclusion of socio-economic factors. However, while cropping models and economic models of agricultural systems are common, dynamically coupled socio-economic-biophysical models have not received as much success. A promising methodology for modelling the socioeconomic aspects of coupled natural-human systems is participatory system dynamics modelling, in which stakeholders develop mental maps of the socio-economic system that are then turned into quantified simulation models. This methodology has been successful in the water resources management field. However, while the stocks and flows of water resources have also been represented within the system dynamics modelling framework and thus coupled to the socioeconomic portion of the model, cropping models are ill-suited for such reformulation. In addition, most of these system dynamics models were developed without stakeholder input, limiting the scope for the adoption and implementation of their results. We therefore propose a new methodology for the analysis of climate change variability on agroecosystems which uses dynamically coupled system dynamics (socio-economic) and biophysical (cropping) models to represent both physical and socioeconomic aspects of the agricultural system, using two case studies (intensive market-based agricultural development versus subsistence crop-based development) from rural Guatemala. The system dynamics model component is developed with relevant governmental and NGO stakeholders from rural and agricultural development in the case study regions and includes such processes as education, poverty and food security. Common variables with the cropping models (yield and agricultural management choices) are then used to dynamically couple the two models together, allowing for the analysis of the agroeconomic system's response to and resilience against various climatic and socioeconomic shocks.

A methodology for modeling barrier island storm-impact scenarios

USGS Publications Warehouse

Mickey, Rangley C.; Long, Joseph W.; Plant, Nathaniel G.; Thompson, David M.; Dalyander, P. Soupy

2017-02-16

A methodology for developing a representative set of storm scenarios based on historical wave buoy and tide gauge data for a region at the Chandeleur Islands, Louisiana, was developed by the U.S. Geological Survey. The total water level was calculated for a 10-year period and analyzed against existing topographic data to identify when storm-induced wave action would affect island morphology. These events were categorized on the basis of the threshold of total water level and duration to create a set of storm scenarios that were simulated, using a high-fidelity, process-based, morphologic evolution model, on an idealized digital elevation model of the Chandeleur Islands. The simulated morphological changes resulting from these scenarios provide a range of impacts that can help coastal managers determine resiliency of proposed or existing coastal structures and identify vulnerable areas within those structures.

A methodology to design heuristics for model selection based on the characteristics of data: Application to investigate when the Negative Binomial Lindley (NB-L) is preferred over the Negative Binomial (NB).

PubMed

Shirazi, Mohammadali; Dhavala, Soma Sekhar; Lord, Dominique; Geedipally, Srinivas Reddy

2017-10-01

Safety analysts usually use post-modeling methods, such as the Goodness-of-Fit statistics or the Likelihood Ratio Test, to decide between two or more competitive distributions or models. Such metrics require all competitive distributions to be fitted to the data before any comparisons can be accomplished. Given the continuous growth in introducing new statistical distributions, choosing the best one using such post-modeling methods is not a trivial task, in addition to all theoretical or numerical issues the analyst may face during the analysis. Furthermore, and most importantly, these measures or tests do not provide any intuitions into why a specific distribution (or model) is preferred over another (Goodness-of-Logic). This paper ponders into these issues by proposing a methodology to design heuristics for Model Selection based on the characteristics of data, in terms of descriptive summary statistics, before fitting the models. The proposed methodology employs two analytic tools: (1) Monte-Carlo Simulations and (2) Machine Learning Classifiers, to design easy heuristics to predict the label of the 'most-likely-true' distribution for analyzing data. The proposed methodology was applied to investigate when the recently introduced Negative Binomial Lindley (NB-L) distribution is preferred over the Negative Binomial (NB) distribution. Heuristics were designed to select the 'most-likely-true' distribution between these two distributions, given a set of prescribed summary statistics of data. The proposed heuristics were successfully compared against classical tests for several real or observed datasets. Not only they are easy to use and do not need any post-modeling inputs, but also, using these heuristics, the analyst can attain useful information about why the NB-L is preferred over the NB - or vice versa- when modeling data. Copyright © 2017 Elsevier Ltd. All rights reserved.

Fuzzy logic modeling of high performance rechargeable batteries

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

Singh, P.; Fennie, C. Jr.; Reisner, D.E.

1998-07-01

Accurate battery state-of-charge (SOC) measurements are critical in many portable electronic device applications. Yet conventional techniques for battery SOC estimation are limited in their accuracy, reliability, and flexibility. In this paper the authors present a powerful new approach to estimate battery SOC using a fuzzy logic-based methodology. This approach provides a universally applicable, accurate method for battery SOC estimation either integrated within, or as an external monitor to, an electronic device. The methodology is demonstrated in modeling impedance measurements on Ni-MH cells and discharge voltage curves of Li-ion cells.

Models, Definitions, and Outcome Variables of Action Learning: A Synthesis with Implications for HRD

ERIC Educational Resources Information Center

Chenhall, Everon C.; Chermack, Thomas J.

2010-01-01

Purpose: The purpose of this paper is to propose an integrated model of action learning based on an examination of four reviewed action learning models, definitions, and espoused outcomes. Design/methodology/approach: A clear articulation of the strengths and limitations of each model was essential to developing an integrated model, which could be…

FDTD-based optical simulations methodology for CMOS image sensors pixels architecture and process optimization

NASA Astrophysics Data System (ADS)

Hirigoyen, Flavien; Crocherie, Axel; Vaillant, Jérôme M.; Cazaux, Yvon

2008-02-01

This paper presents a new FDTD-based optical simulation model dedicated to describe the optical performances of CMOS image sensors taking into account diffraction effects. Following market trend and industrialization constraints, CMOS image sensors must be easily embedded into even smaller packages, which are now equipped with auto-focus and short-term coming zoom system. Due to miniaturization, the ray-tracing models used to evaluate pixels optical performances are not accurate anymore to describe the light propagation inside the sensor, because of diffraction effects. Thus we adopt a more fundamental description to take into account these diffraction effects: we chose to use Maxwell-Boltzmann based modeling to compute the propagation of light, and to use a software with an FDTD-based (Finite Difference Time Domain) engine to solve this propagation. We present in this article the complete methodology of this modeling: on one hand incoherent plane waves are propagated to approximate a product-use diffuse-like source, on the other hand we use periodic conditions to limit the size of the simulated model and both memory and computation time. After having presented the correlation of the model with measurements we will illustrate its use in the case of the optimization of a 1.75μm pixel.

Methodology for cost analysis of film-based and filmless portable chest systems

NASA Astrophysics Data System (ADS)

Melson, David L.; Gauvain, Karen M.; Beardslee, Brian M.; Kraitsik, Michael J.; Burton, Larry; Blaine, G. James; Brink, Gary S.

1996-05-01

Many studies analyzing the costs of film-based and filmless radiology have focused on multi- modality, hospital-wide solutions. Yet due to the enormous cost of converting an entire large radiology department or hospital to a filmless environment all at once, institutions often choose to eliminate film one area at a time. Narrowing the focus of cost-analysis may be useful in making such decisions. This presentation will outline a methodology for analyzing the cost per exam of film-based and filmless solutions for providing portable chest exams to Intensive Care Units (ICUs). The methodology, unlike most in the literature, is based on parallel data collection from existing filmless and film-based ICUs, and is currently being utilized at our institution. Direct costs, taken from the perspective of the hospital, for portable computed radiography chest exams in one filmless and two film-based ICUs are identified. The major cost components are labor, equipment, materials, and storage. Methods for gathering and analyzing each of the cost components are discussed, including FTE-based and time-based labor analysis, incorporation of equipment depreciation, lease, and maintenance costs, and estimation of materials costs. Extrapolation of data from three ICUs to model hypothetical, hospital-wide film-based and filmless ICU imaging systems is described. Performance of sensitivity analysis on the filmless model to assess the impact of anticipated reductions in specific labor, equipment, and archiving costs is detailed. A number of indirect costs, which are not explicitly included in the analysis, are identified and discussed.

Day-Ahead Crude Oil Price Forecasting Using a Novel Morphological Component Analysis Based Model

PubMed Central

Zhu, Qing; Zou, Yingchao; Lai, Kin Keung

2014-01-01

As a typical nonlinear and dynamic system, the crude oil price movement is difficult to predict and its accurate forecasting remains the subject of intense research activity. Recent empirical evidence suggests that the multiscale data characteristics in the price movement are another important stylized fact. The incorporation of mixture of data characteristics in the time scale domain during the modelling process can lead to significant performance improvement. This paper proposes a novel morphological component analysis based hybrid methodology for modeling the multiscale heterogeneous characteristics of the price movement in the crude oil markets. Empirical studies in two representative benchmark crude oil markets reveal the existence of multiscale heterogeneous microdata structure. The significant performance improvement of the proposed algorithm incorporating the heterogeneous data characteristics, against benchmark random walk, ARMA, and SVR models, is also attributed to the innovative methodology proposed to incorporate this important stylized fact during the modelling process. Meanwhile, work in this paper offers additional insights into the heterogeneous market microstructure with economic viable interpretations. PMID:25061614

Day-ahead crude oil price forecasting using a novel morphological component analysis based model.

PubMed

Zhu, Qing; He, Kaijian; Zou, Yingchao; Lai, Kin Keung

2014-01-01

As a typical nonlinear and dynamic system, the crude oil price movement is difficult to predict and its accurate forecasting remains the subject of intense research activity. Recent empirical evidence suggests that the multiscale data characteristics in the price movement are another important stylized fact. The incorporation of mixture of data characteristics in the time scale domain during the modelling process can lead to significant performance improvement. This paper proposes a novel morphological component analysis based hybrid methodology for modeling the multiscale heterogeneous characteristics of the price movement in the crude oil markets. Empirical studies in two representative benchmark crude oil markets reveal the existence of multiscale heterogeneous microdata structure. The significant performance improvement of the proposed algorithm incorporating the heterogeneous data characteristics, against benchmark random walk, ARMA, and SVR models, is also attributed to the innovative methodology proposed to incorporate this important stylized fact during the modelling process. Meanwhile, work in this paper offers additional insights into the heterogeneous market microstructure with economic viable interpretations.

An autonomous satellite architecture integrating deliberative reasoning and behavioural intelligence

NASA Technical Reports Server (NTRS)

Lindley, Craig A.

1993-01-01

This paper describes a method for the design of autonomous spacecraft, based upon behavioral approaches to intelligent robotics. First, a number of previous spacecraft automation projects are reviewed. A methodology for the design of autonomous spacecraft is then presented, drawing upon both the European Space Agency technological center (ESTEC) automation and robotics methodology and the subsumption architecture for autonomous robots. A layered competency model for autonomous orbital spacecraft is proposed. A simple example of low level competencies and their interaction is presented in order to illustrate the methodology. Finally, the general principles adopted for the control hardware design of the AUSTRALIS-1 spacecraft are described. This system will provide an orbital experimental platform for spacecraft autonomy studies, supporting the exploration of different logical control models, different computational metaphors within the behavioral control framework, and different mappings from the logical control model to its physical implementation.

Soft tissue modelling through autowaves for surgery simulation.

PubMed

Zhong, Yongmin; Shirinzadeh, Bijan; Alici, Gursel; Smith, Julian

2006-09-01

Modelling of soft tissue deformation is of great importance to virtual reality based surgery simulation. This paper presents a new methodology for simulation of soft tissue deformation by drawing an analogy between autowaves and soft tissue deformation. The potential energy stored in a soft tissue as a result of a deformation caused by an external force is propagated among mass points of the soft tissue by non-linear autowaves. The novelty of the methodology is that (i) autowave techniques are established to describe the potential energy distribution of a deformation for extrapolating internal forces, and (ii) non-linear materials are modelled with non-linear autowaves other than geometric non-linearity. Integration with a haptic device has been achieved to simulate soft tissue deformation with force feedback. The proposed methodology not only deals with large-range deformations, but also accommodates isotropic, anisotropic and inhomogeneous materials by simply changing diffusion coefficients.

Display/control requirements for automated VTOL aircraft

NASA Technical Reports Server (NTRS)

Hoffman, W. C.; Kleinman, D. L.; Young, L. R.

1976-01-01

A systematic design methodology for pilot displays in advanced commercial VTOL aircraft was developed and refined. The analyst is provided with a step-by-step procedure for conducting conceptual display/control configurations evaluations for simultaneous monitoring and control pilot tasks. The approach consists of three phases: formulation of information requirements, configuration evaluation, and system selection. Both the monitoring and control performance models are based upon the optimal control model of the human operator. Extensions to the conventional optimal control model required in the display design methodology include explicit optimization of control/monitoring attention; simultaneous monitoring and control performance predictions; and indifference threshold effects. The methodology was applied to NASA's experimental CH-47 helicopter in support of the VALT program. The CH-47 application examined the system performance of six flight conditions. Four candidate configurations are suggested for evaluation in pilot-in-the-loop simulations and eventual flight tests.

Inference regarding multiple structural changes in linear models with endogenous regressors☆

PubMed Central

Hall, Alastair R.; Han, Sanggohn; Boldea, Otilia

2012-01-01

This paper considers the linear model with endogenous regressors and multiple changes in the parameters at unknown times. It is shown that minimization of a Generalized Method of Moments criterion yields inconsistent estimators of the break fractions, but minimization of the Two Stage Least Squares (2SLS) criterion yields consistent estimators of these parameters. We develop a methodology for estimation and inference of the parameters of the model based on 2SLS. The analysis covers the cases where the reduced form is either stable or unstable. The methodology is illustrated via an application to the New Keynesian Phillips Curve for the US. PMID:23805021

The prospect of modern thermomechanics in structural integrity calculations of large-scale pressure vessels

NASA Astrophysics Data System (ADS)

Fekete, Tamás

2018-05-01

Structural integrity calculations play a crucial role in designing large-scale pressure vessels. Used in the electric power generation industry, these kinds of vessels undergo extensive safety analyses and certification procedures before deemed feasible for future long-term operation. The calculations are nowadays directed and supported by international standards and guides based on state-of-the-art results of applied research and technical development. However, their ability to predict a vessel's behavior under accidental circumstances after long-term operation is largely limited by the strong dependence of the analysis methodology on empirical models that are correlated to the behavior of structural materials and their changes during material aging. Recently a new scientific engineering paradigm, structural integrity has been developing that is essentially a synergistic collaboration between a number of scientific and engineering disciplines, modeling, experiments and numerics. Although the application of the structural integrity paradigm highly contributed to improving the accuracy of safety evaluations of large-scale pressure vessels, the predictive power of the analysis methodology has not yet improved significantly. This is due to the fact that already existing structural integrity calculation methodologies are based on the widespread and commonly accepted 'traditional' engineering thermal stress approach, which is essentially based on the weakly coupled model of thermomechanics and fracture mechanics. Recently, a research has been initiated in MTA EK with the aim to review and evaluate current methodologies and models applied in structural integrity calculations, including their scope of validity. The research intends to come to a better understanding of the physical problems that are inherently present in the pool of structural integrity problems of reactor pressure vessels, and to ultimately find a theoretical framework that could serve as a well-grounded theoretical foundation for a new modeling framework of structural integrity. This paper presents the first findings of the research project.

Ambient Vibration Testing for Story Stiffness Estimation of a Heritage Timber Building

PubMed Central

Min, Kyung-Won; Kim, Junhee; Park, Sung-Ah; Park, Chan-Soo

2013-01-01

This paper investigates dynamic characteristics of a historic wooden structure by ambient vibration testing, presenting a novel estimation methodology of story stiffness for the purpose of vibration-based structural health monitoring. As for the ambient vibration testing, measured structural responses are analyzed by two output-only system identification methods (i.e., frequency domain decomposition and stochastic subspace identification) to estimate modal parameters. The proposed methodology of story stiffness is estimation based on an eigenvalue problem derived from a vibratory rigid body model. Using the identified natural frequencies, the eigenvalue problem is efficiently solved and uniquely yields story stiffness. It is noteworthy that application of the proposed methodology is not necessarily confined to the wooden structure exampled in the paper. PMID:24227999

Flood damage modeling based on expert knowledge: Insights from French damage model for agricultural sector

NASA Astrophysics Data System (ADS)

Grelot, Frédéric; Agenais, Anne-Laurence; Brémond, Pauline

2015-04-01

In France, since 2011, it is mandatory for local communities to conduct cost-benefit analysis (CBA) of their flood management projects, to make them eligible for financial support from the State. Meanwhile, as a support, the French Ministry in charge of Environment proposed a methodology to fulfill CBA. Like for many other countries, this methodology is based on the estimation of flood damage. However, existing models to estimate flood damage were judged not convenient for a national-wide use. As a consequence, the French Ministry in charge of Environment launched studies to develop damage models for different sectors, such as: residential sector, public infrastructures, agricultural sector, and commercial and industrial sector. In this presentation, we aim at presenting and discussing methodological choices of those damage models. They all share the same principle: no sufficient data from past events were available to build damage models on a statistical analysis, so modeling was based on expert knowledge. We will focus on the model built for agricultural activities and more precisely for agricultural lands. This model was based on feedback from 30 agricultural experts who experienced floods in their geographical areas. They were selected to have a representative experience of crops and flood conditions in France. The model is composed of: (i) damaging functions, which reveal physiological vulnerability of crops, (ii) action functions, which correspond to farmers' decision rules for carrying on crops after a flood, and (iii) economic agricultural data, which correspond to featured characteristics of crops in the geographical area where the flood management project studied takes place. The two first components are generic and the third one is specific to the area studied. It is, thus, possible to produce flood damage functions adapted to different agronomic and geographical contexts. In the end, the model was applied to obtain a pool of damage functions giving damage in euros by hectare for 14 agricultural lands categories. As a conclusion, we will discuss the validation step of the model. Although the model was validated by experts, we analyse how it could gain insight from comparison with past events.

Flood damage modeling based on expert knowledge: Insights from French damage model for agricultural sector

NASA Astrophysics Data System (ADS)

Grelot, Frédéric; Agenais, Anne-Laurence; Brémond, Pauline

2014-05-01

In France, since 2011, it is mandatory for local communities to conduct cost-benefit analysis (CBA) of their flood management projects, to make them eligible for financial support from the State. Meanwhile, as a support, the French Ministry in charge of Environment proposed a methodology to fulfill CBA. Like for many other countries, this methodology is based on the estimation of flood damage. Howerver, existing models to estimate flood damage were judged not convenient for a national-wide use. As a consequence, the French Ministry in charge of Environment launched studies to develop damage models for different sectors, such as: residential sector, public infrastructures, agricultural sector, and commercial and industrial sector. In this presentation, we aim at presenting and discussing methodological choices of those damage models. They all share the same principle: no sufficient data from past events were available to build damage models on a statistical analysis, so modeling was based on expert knowledge. We will focus on the model built for agricultural activities and more precisely for agricultural lands. This model was based on feedback from 30 agricultural experts who experienced floods in their geographical areas. They were selected to have a representative experience of crops and flood conditions in France. The model is composed of: (i) damaging functions, which reveal physiological vulnerability of crops, (ii) action functions, which correspond to farmers' decision rules for carrying on crops after a flood, and (iii) economic agricultural data, which correspond to featured characteristics of crops in the geographical area where the flood management project studied takes place. The two first components are generic and the third one is specific to the area studied. It is, thus, possible to produce flood damage functions adapted to different agronomic and geographical contexts. In the end, the model was applied to obtain a pool of damage functions giving damage in euros by hectare for 14 agricultural lands categories. As a conclusion, we will discuss the validation step of the model. Although the model was validated by experts, we analyse how it could gain insight from comparison with past events.

Regression to fuzziness method for estimation of remaining useful life in power plant components

NASA Astrophysics Data System (ADS)

Alamaniotis, Miltiadis; Grelle, Austin; Tsoukalas, Lefteri H.

2014-10-01

Mitigation of severe accidents in power plants requires the reliable operation of all systems and the on-time replacement of mechanical components. Therefore, the continuous surveillance of power systems is a crucial concern for the overall safety, cost control, and on-time maintenance of a power plant. In this paper a methodology called regression to fuzziness is presented that estimates the remaining useful life (RUL) of power plant components. The RUL is defined as the difference between the time that a measurement was taken and the estimated failure time of that component. The methodology aims to compensate for a potential lack of historical data by modeling an expert's operational experience and expertise applied to the system. It initially identifies critical degradation parameters and their associated value range. Once completed, the operator's experience is modeled through fuzzy sets which span the entire parameter range. This model is then synergistically used with linear regression and a component's failure point to estimate the RUL. The proposed methodology is tested on estimating the RUL of a turbine (the basic electrical generating component of a power plant) in three different cases. Results demonstrate the benefits of the methodology for components for which operational data is not readily available and emphasize the significance of the selection of fuzzy sets and the effect of knowledge representation on the predicted output. To verify the effectiveness of the methodology, it was benchmarked against the data-based simple linear regression model used for predictions which was shown to perform equal or worse than the presented methodology. Furthermore, methodology comparison highlighted the improvement in estimation offered by the adoption of appropriate of fuzzy sets for parameter representation.

Model of Emotional Expressions in Movements

ERIC Educational Resources Information Center

Rozaliev, Vladimir L.; Orlova, Yulia A.

2013-01-01

This paper presents a new approach to automated identification of human emotions based on analysis of body movements, a recognition of gestures and poses. Methodology, models and automated system for emotion identification are considered. To characterize the person emotions in the model, body movements are described with linguistic variables and a…

Statistical power calculations for mixed pharmacokinetic study designs using a population approach.

PubMed

Kloprogge, Frank; Simpson, Julie A; Day, Nicholas P J; White, Nicholas J; Tarning, Joel

2014-09-01

Simultaneous modelling of dense and sparse pharmacokinetic data is possible with a population approach. To determine the number of individuals required to detect the effect of a covariate, simulation-based power calculation methodologies can be employed. The Monte Carlo Mapped Power method (a simulation-based power calculation methodology using the likelihood ratio test) was extended in the current study to perform sample size calculations for mixed pharmacokinetic studies (i.e. both sparse and dense data collection). A workflow guiding an easy and straightforward pharmacokinetic study design, considering also the cost-effectiveness of alternative study designs, was used in this analysis. Initially, data were simulated for a hypothetical drug and then for the anti-malarial drug, dihydroartemisinin. Two datasets (sampling design A: dense; sampling design B: sparse) were simulated using a pharmacokinetic model that included a binary covariate effect and subsequently re-estimated using (1) the same model and (2) a model not including the covariate effect in NONMEM 7.2. Power calculations were performed for varying numbers of patients with sampling designs A and B. Study designs with statistical power >80% were selected and further evaluated for cost-effectiveness. The simulation studies of the hypothetical drug and the anti-malarial drug dihydroartemisinin demonstrated that the simulation-based power calculation methodology, based on the Monte Carlo Mapped Power method, can be utilised to evaluate and determine the sample size of mixed (part sparsely and part densely sampled) study designs. The developed method can contribute to the design of robust and efficient pharmacokinetic studies.

Relative Panoramic Camera Position Estimation for Image-Based Virtual Reality Networks in Indoor Environments

NASA Astrophysics Data System (ADS)

Nakagawa, M.; Akano, K.; Kobayashi, T.; Sekiguchi, Y.

2017-09-01

Image-based virtual reality (VR) is a virtual space generated with panoramic images projected onto a primitive model. In imagebased VR, realistic VR scenes can be generated with lower rendering cost, and network data can be described as relationships among VR scenes. The camera network data are generated manually or by an automated procedure using camera position and rotation data. When panoramic images are acquired in indoor environments, network data should be generated without Global Navigation Satellite Systems (GNSS) positioning data. Thus, we focused on image-based VR generation using a panoramic camera in indoor environments. We propose a methodology to automate network data generation using panoramic images for an image-based VR space. We verified and evaluated our methodology through five experiments in indoor environments, including a corridor, elevator hall, room, and stairs. We confirmed that our methodology can automatically reconstruct network data using panoramic images for image-based VR in indoor environments without GNSS position data.

Security issues of Internet-based biometric authentication systems: risks of Man-in-the-Middle and BioPhishing on the example of BioWebAuth

NASA Astrophysics Data System (ADS)

Zeitz, Christian; Scheidat, Tobias; Dittmann, Jana; Vielhauer, Claus; González Agulla, Elisardo; Otero Muras, Enrique; García Mateo, Carmen; Alba Castro, José L.

2008-02-01

Beside the optimization of biometric error rates the overall security system performance in respect to intentional security attacks plays an important role for biometric enabled authentication schemes. As traditionally most user authentication schemes are knowledge and/or possession based, firstly in this paper we present a methodology for a security analysis of Internet-based biometric authentication systems by enhancing known methodologies such as the CERT attack-taxonomy with a more detailed view on the OSI-Model. Secondly as proof of concept, the guidelines extracted from this methodology are strictly applied to an open source Internet-based biometric authentication system (BioWebAuth). As case studies, two exemplary attacks, based on the found security leaks, are investigated and the attack performance is presented to show that during the biometric authentication schemes beside biometric error performance tuning also security issues need to be addressed. Finally, some design recommendations are given in order to ensure a minimum security level.

GREENSCOPE: A Method for Modeling Chemical Process Sustainability

EPA Science Inventory

Current work within the U.S. Environmental Protection Agency’s National Risk Management Research Laboratory is focused on the development of a method for modeling chemical process sustainability. The GREENSCOPE methodology, defined for the four bases of Environment, Economics, Ef...

COMPILATION OF GROUND-WATER MODELS

EPA Science Inventory

Ground-water modeling is a computer-based methodology for mathematical analysis of the mechanisms and controls of ground-water systems for the evaluation of policies, action, and designs that may affect such systems. n addition to satisfying scientific interest in the workings of...

Uncertainties in Emissions In Emissions Inputs for Near-Road Assessments

EPA Science Inventory

Emissions, travel demand, and dispersion models are all needed to obtain temporally and spatially resolved pollutant concentrations. Current methodology combines these three models in a bottom-up approach based on hourly traffic and emissions estimates, and hourly dispersion conc...

Multi-hazard risk analysis related to hurricanes

NASA Astrophysics Data System (ADS)

Lin, Ning

Hurricanes present major hazards to the United States. Associated with extreme winds, heavy rainfall, and storm surge, landfalling hurricanes often cause enormous structural damage to coastal regions. Hurricane damage risk assessment provides the basis for loss mitigation and related policy-making. Current hurricane risk models, however, often oversimplify the complex processes of hurricane damage. This dissertation aims to improve existing hurricane risk assessment methodology by coherently modeling the spatial-temporal processes of storm landfall, hazards, and damage. Numerical modeling technologies are used to investigate the multiplicity of hazards associated with landfalling hurricanes. The application and effectiveness of current weather forecasting technologies to predict hurricane hazards is investigated. In particular, the Weather Research and Forecasting model (WRF), with Geophysical Fluid Dynamics Laboratory (GFDL)'s hurricane initialization scheme, is applied to the simulation of the wind and rainfall environment during hurricane landfall. The WRF model is further coupled with the Advanced Circulation (AD-CIRC) model to simulate storm surge in coastal regions. A case study examines the multiple hazards associated with Hurricane Isabel (2003). Also, a risk assessment methodology is developed to estimate the probability distribution of hurricane storm surge heights along the coast, particularly for data-scarce regions, such as New York City. This methodology makes use of relatively simple models, specifically a statistical/deterministic hurricane model and the Sea, Lake and Overland Surges from Hurricanes (SLOSH) model, to simulate large numbers of synthetic surge events, and conducts statistical analysis. The estimation of hurricane landfall probability and hazards are combined with structural vulnerability models to estimate hurricane damage risk. Wind-induced damage mechanisms are extensively studied. An innovative windborne debris risk model is developed based on the theory of Poisson random measure, substantiated by a large amount of empirical data. An advanced vulnerability assessment methodology is then developed, by integrating this debris risk model and a component-based pressure damage model, to predict storm-specific or annual damage to coastal residential neighborhoods. The uniqueness of this vulnerability model lies in its detailed description of the interaction between wind pressure and windborne debris effects over periods of strong winds, which is a major mechanism leading to structural failures during hurricanes.

A methodology to model causal relationships on offshore safety assessment focusing on human and organizational factors.

PubMed

Ren, J; Jenkinson, I; Wang, J; Xu, D L; Yang, J B

2008-01-01

Focusing on people and organizations, this paper aims to contribute to offshore safety assessment by proposing a methodology to model causal relationships. The methodology is proposed in a general sense that it will be capable of accommodating modeling of multiple risk factors considered in offshore operations and will have the ability to deal with different types of data that may come from different resources. Reason's "Swiss cheese" model is used to form a generic offshore safety assessment framework, and Bayesian Network (BN) is tailored to fit into the framework to construct a causal relationship model. The proposed framework uses a five-level-structure model to address latent failures within the causal sequence of events. The five levels include Root causes level, Trigger events level, Incidents level, Accidents level, and Consequences level. To analyze and model a specified offshore installation safety, a BN model was established following the guideline of the proposed five-level framework. A range of events was specified, and the related prior and conditional probabilities regarding the BN model were assigned based on the inherent characteristics of each event. This paper shows that Reason's "Swiss cheese" model and BN can be jointly used in offshore safety assessment. On the one hand, the five-level conceptual model is enhanced by BNs that are capable of providing graphical demonstration of inter-relationships as well as calculating numerical values of occurrence likelihood for each failure event. Bayesian inference mechanism also makes it possible to monitor how a safety situation changes when information flow travel forwards and backwards within the networks. On the other hand, BN modeling relies heavily on experts' personal experiences and is therefore highly domain specific. "Swiss cheese" model is such a theoretic framework that it is based on solid behavioral theory and therefore can be used to provide industry with a roadmap for BN modeling and implications. A case study of the collision risk between a Floating Production, Storage and Offloading (FPSO) unit and authorized vessels caused by human and organizational factors (HOFs) during operations is used to illustrate an industrial application of the proposed methodology.

Copula based prediction models: an application to an aortic regurgitation study

PubMed Central

Kumar, Pranesh; Shoukri, Mohamed M

2007-01-01

Background: An important issue in prediction modeling of multivariate data is the measure of dependence structure. The use of Pearson's correlation as a dependence measure has several pitfalls and hence application of regression prediction models based on this correlation may not be an appropriate methodology. As an alternative, a copula based methodology for prediction modeling and an algorithm to simulate data are proposed. Methods: The method consists of introducing copulas as an alternative to the correlation coefficient commonly used as a measure of dependence. An algorithm based on the marginal distributions of random variables is applied to construct the Archimedean copulas. Monte Carlo simulations are carried out to replicate datasets, estimate prediction model parameters and validate them using Lin's concordance measure. Results: We have carried out a correlation-based regression analysis on data from 20 patients aged 17–82 years on pre-operative and post-operative ejection fractions after surgery and estimated the prediction model: Post-operative ejection fraction = - 0.0658 + 0.8403 (Pre-operative ejection fraction); p = 0.0008; 95% confidence interval of the slope coefficient (0.3998, 1.2808). From the exploratory data analysis, it is noted that both the pre-operative and post-operative ejection fractions measurements have slight departures from symmetry and are skewed to the left. It is also noted that the measurements tend to be widely spread and have shorter tails compared to normal distribution. Therefore predictions made from the correlation-based model corresponding to the pre-operative ejection fraction measurements in the lower range may not be accurate. Further it is found that the best approximated marginal distributions of pre-operative and post-operative ejection fractions (using q-q plots) are gamma distributions. The copula based prediction model is estimated as: Post -operative ejection fraction = - 0.0933 + 0.8907 × (Pre-operative ejection fraction); p = 0.00008 ; 95% confidence interval for slope coefficient (0.4810, 1.3003). For both models differences in the predicted post-operative ejection fractions in the lower range of pre-operative ejection measurements are considerably different and prediction errors due to copula model are smaller. To validate the copula methodology we have re-sampled with replacement fifty independent bootstrap samples and have estimated concordance statistics 0.7722 (p = 0.0224) for the copula model and 0.7237 (p = 0.0604) for the correlation model. The predicted and observed measurements are concordant for both models. The estimates of accuracy components are 0.9233 and 0.8654 for copula and correlation models respectively. Conclusion: Copula-based prediction modeling is demonstrated to be an appropriate alternative to the conventional correlation-based prediction modeling since the correlation-based prediction models are not appropriate to model the dependence in populations with asymmetrical tails. Proposed copula-based prediction model has been validated using the independent bootstrap samples. PMID:17573974

LEARNING STYLE OF MEDICAL STUDENTS AND ITS CORRELATION WITH PREFERRED TEACHING METHODOLOGIES AND ACADEMIC ACHIEVEMENT.

PubMed

Bhalli, Muhammad Asif; Khan, Ishtiaq Ali; Sattar, Abdul

2015-01-01

Researchers have categorized the learning styles in many ways. Kolb proposed a classification of learner's styles as convergers, divergers, assimilators and accommodators. Honey and Mumford simplified learning styles as activists, reflectors, theorists and pragmatists. Neil Fleming's VARK model (Visual, Auditory, Read/write and Kinesthetic) is also popular. This study was carried out to determine the frequency of learning styles (Honey and Mumford) of medical students and its correlation with preferred teaching methodologies and academic achievements. A total of 77 medical students of 4th year MBBS were selected through non-probability convenient sampling for this study. Honey and Mumford's learning style questionnaire, and a 2nd questionnaire to know their preference for different teaching methodologies were distributed to the students. Learning styles were identified and correlated with preferred teaching methodologies and academic achievements by Chi-square test. Mean age of the medical students was 22.75 ± 1.05 years. Twenty one (27.3%) participants were males and 56 (72.7%) females. By learning styles, 7 (9.1%) medical students were activists, 36 (46.8%) reflectors, 13 (16.9%) theorists and 21 (27.3%) were pragmatists. Out of 77 students, 22 preferred interactive lectures; 16, small group discussion; 20 problem based learning, 10 preferred demonstration on models. Only 01 students preferred one-way lecture as the best teaching methodology. No significant correlation was found between learning styles and preferred teaching methodologies and learning styles and academic scores. Most of the medical students had reflector (46.8%) and pragmatist (27.3%) learning styles. Majority preferred interactive lectures (28.57%) and problem based learning (25.98%) as teaching methodologies. Aligning our instructional strategies with learning styles of the medical students will improve learning and academic performance.

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

NASA Astrophysics Data System (ADS)

Knox, Lenora A.

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

Optimum extrusion-cooking conditions for improving physical properties of fish-cereal based snacks by response surface methodology.

PubMed

Singh, R K Ratankumar; Majumdar, Ranendra K; Venkateshwarlu, G

2014-09-01

To establish the effect of barrel temperature, screw speed, total moisture and fish flour content on the expansion ratio and bulk density of the fish based extrudates, response surface methodology was adopted in this study. The experiments were optimized using five-levels, four factors central composite design. Analysis of Variance was carried to study the effects of main factors and interaction effects of various factors and regression analysis was carried out to explain the variability. The fitting was done to a second order model with the coded variables for each response. The response surface plots were developed as a function of two independent variables while keeping the other two independent variables at optimal values. Based on the ANOVA, the fitted model confirmed the model fitness for both the dependent variables. Organoleptically highest score was obtained with the combination of temperature-110(0) C, screw speed-480 rpm, moisture-18 % and fish flour-20 %.

The FoReVer Methodology: A MBSE Framework for Formal Verification

NASA Astrophysics Data System (ADS)

Baracchi, Laura; Mazzini, Silvia; Cimatti, Alessandro; Tonetta, Stefano; Garcia, Gerald

2013-08-01

The need for high level of confidence and operational integrity in critical space (software) systems is well recognized in the Space industry and has been addressed so far through rigorous System and Software Development Processes and stringent Verification and Validation regimes. The Model Based Space System Engineering process (MBSSE) derived in the System and Software Functional Requirement Techniques study (SSFRT) focused on the application of model based engineering technologies to support the space system and software development processes, from mission level requirements to software implementation through model refinements and translations. In this paper we report on our work in the ESA-funded FoReVer project where we aim at developing methodological, theoretical and technological support for a systematic approach to the space avionics system development, in phases 0/A/B/C. FoReVer enriches the MBSSE process with contract-based formal verification of properties, at different stages from system to software, through a step-wise refinement approach, with the support for a Software Reference Architecture.

Model-Based Control of a Nonlinear Aircraft Engine Simulation using an Optimal Tuner Kalman Filter Approach

NASA Technical Reports Server (NTRS)

Connolly, Joseph W.; Csank, Jeffrey Thomas; Chicatelli, Amy; Kilver, Jacob

2013-01-01

This paper covers the development of a model-based engine control (MBEC) methodology featuring a self tuning on-board model applied to an aircraft turbofan engine simulation. Here, the Commercial Modular Aero-Propulsion System Simulation 40,000 (CMAPSS40k) serves as the MBEC application engine. CMAPSS40k is capable of modeling realistic engine performance, allowing for a verification of the MBEC over a wide range of operating points. The on-board model is a piece-wise linear model derived from CMAPSS40k and updated using an optimal tuner Kalman Filter (OTKF) estimation routine, which enables the on-board model to self-tune to account for engine performance variations. The focus here is on developing a methodology for MBEC with direct control of estimated parameters of interest such as thrust and stall margins. Investigations using the MBEC to provide a stall margin limit for the controller protection logic are presented that could provide benefits over a simple acceleration schedule that is currently used in traditional engine control architectures.

Mechanistic modelling of the inhibitory effect of pH on microbial growth.

PubMed

Akkermans, Simen; Van Impe, Jan F

2018-06-01

Modelling and simulation of microbial dynamics as a function of processing, transportation and storage conditions is a useful tool to improve microbial food safety and quality. The goal of this research is to improve an existing methodology for building mechanistic predictive models based on the environmental conditions. The effect of environmental conditions on microbial dynamics is often described by combining the separate effects in a multiplicative way (gamma concept). This idea was extended further in this work by including the effects of the lag and stationary growth phases on microbial growth rate as independent gamma factors. A mechanistic description of the stationary phase as a function of pH was included, based on a novel class of models that consider product inhibition. Experimental results on Escherichia coli growth dynamics indicated that also the parameters of the product inhibition equations can be modelled with the gamma approach. This work has extended a modelling methodology, resulting in predictive models that are (i) mechanistically inspired, (ii) easily identifiable with a limited work load and (iii) easily extended to additional environmental conditions. Copyright © 2017. Published by Elsevier Ltd.

A Novel Methodology for Improving Plant Pest Surveillance in Vineyards and Crops Using UAV-Based Hyperspectral and Spatial Data.

PubMed

Vanegas, Fernando; Bratanov, Dmitry; Powell, Kevin; Weiss, John; Gonzalez, Felipe

2018-01-17

Recent advances in remote sensed imagery and geospatial image processing using unmanned aerial vehicles (UAVs) have enabled the rapid and ongoing development of monitoring tools for crop management and the detection/surveillance of insect pests. This paper describes a (UAV) remote sensing-based methodology to increase the efficiency of existing surveillance practices (human inspectors and insect traps) for detecting pest infestations (e.g., grape phylloxera in vineyards). The methodology uses a UAV integrated with advanced digital hyperspectral, multispectral, and RGB sensors. We implemented the methodology for the development of a predictive model for phylloxera detection. In this method, we explore the combination of airborne RGB, multispectral, and hyperspectral imagery with ground-based data at two separate time periods and under different levels of phylloxera infestation. We describe the technology used-the sensors, the UAV, and the flight operations-the processing workflow of the datasets from each imagery type, and the methods for combining multiple airborne with ground-based datasets. Finally, we present relevant results of correlation between the different processed datasets. The objective of this research is to develop a novel methodology for collecting, processing, analising and integrating multispectral, hyperspectral, ground and spatial data to remote sense different variables in different applications, such as, in this case, plant pest surveillance. The development of such methodology would provide researchers, agronomists, and UAV practitioners reliable data collection protocols and methods to achieve faster processing techniques and integrate multiple sources of data in diverse remote sensing applications.

Some requirements and suggestions for a methodology to develop knowledge based systems.

PubMed

Green, D W; Colbert, M; Long, J

1989-11-01

This paper describes an approach to the creation of a methodology for the development of knowledge based systems. It specifies some requirements and suggests how these requirements might be met. General requirements can be satisfied using a systems approach. More specific ones can be met by viewing an organization as a network of consultations for coordinating expertise. The nature of consultations is described and the form of a possible cognitive model using a blackboard architecture is outlined. The value of the approach is illustrated in terms of certain knowledge elicitation methods.

Case based reasoning in criminal intelligence using forensic case data.

PubMed

Ribaux, O; Margot, P

2003-01-01

A model that is based on the knowledge of experienced investigators in the analysis of serial crime is suggested to bridge a gap between technology and methodology. Its purpose is to provide a solid methodology for the analysis of serial crimes that supports decision making in the deployment of resources, either by guiding proactive policing operations or helping the investigative process. Formalisation has helped to derive a computerised system that efficiently supports the reasoning processes in the analysis of serial crime. This novel approach fully integrates forensic science data.

ChargeOut! : determining machine and capital equipment charge-out rates using discounted cash-flow analysis

Treesearch

E.M. (Ted) Bilek

2007-01-01

The model ChargeOut! was developed to determine charge-out rates or rates of return for machines and capital equipment. This paper introduces a costing methodology and applies it to a piece of capital equipment. Although designed for the forest industry, the methodology is readily transferable to other sectors. Based on discounted cash-flow analysis, ChargeOut!...

AMOVA ["Accumulative Manifold Validation Analysis"]: An Advanced Statistical Methodology Designed to Measure and Test the Validity, Reliability, and Overall Efficacy of Inquiry-Based Psychometric Instruments

ERIC Educational Resources Information Center

Osler, James Edward, II

2015-01-01

This monograph provides an epistemological rational for the Accumulative Manifold Validation Analysis [also referred by the acronym "AMOVA"] statistical methodology designed to test psychometric instruments. This form of inquiry is a form of mathematical optimization in the discipline of linear stochastic modelling. AMOVA is an in-depth…

Adaptation of Mesoscale Weather Models to Local Forecasting

NASA Technical Reports Server (NTRS)

Manobianco, John T.; Taylor, Gregory E.; Case, Jonathan L.; Dianic, Allan V.; Wheeler, Mark W.; Zack, John W.; Nutter, Paul A.

2003-01-01

Methodologies have been developed for (1) configuring mesoscale numerical weather-prediction models for execution on high-performance computer workstations to make short-range weather forecasts for the vicinity of the Kennedy Space Center (KSC) and the Cape Canaveral Air Force Station (CCAFS) and (2) evaluating the performances of the models as configured. These methodologies have been implemented as part of a continuing effort to improve weather forecasting in support of operations of the U.S. space program. The models, methodologies, and results of the evaluations also have potential value for commercial users who could benefit from tailoring their operations and/or marketing strategies based on accurate predictions of local weather. More specifically, the purpose of developing the methodologies for configuring the models to run on computers at KSC and CCAFS is to provide accurate forecasts of winds, temperature, and such specific thunderstorm-related phenomena as lightning and precipitation. The purpose of developing the evaluation methodologies is to maximize the utility of the models by providing users with assessments of the capabilities and limitations of the models. The models used in this effort thus far include the Mesoscale Atmospheric Simulation System (MASS), the Regional Atmospheric Modeling System (RAMS), and the National Centers for Environmental Prediction Eta Model ( Eta for short). The configuration of the MASS and RAMS is designed to run the models at very high spatial resolution and incorporate local data to resolve fine-scale weather features. Model preprocessors were modified to incorporate surface, ship, buoy, and rawinsonde data as well as data from local wind towers, wind profilers, and conventional or Doppler radars. The overall evaluation of the MASS, Eta, and RAMS was designed to assess the utility of these mesoscale models for satisfying the weather-forecasting needs of the U.S. space program. The evaluation methodology includes objective and subjective verification methodologies. Objective (e.g., statistical) verification of point forecasts is a stringent measure of model performance, but when used alone, it is not usually sufficient for quantifying the value of the overall contribution of the model to the weather-forecasting process. This is especially true for mesoscale models with enhanced spatial and temporal resolution that may be capable of predicting meteorologically consistent, though not necessarily accurate, fine-scale weather phenomena. Therefore, subjective (phenomenological) evaluation, focusing on selected case studies and specific weather features, such as sea breezes and precipitation, has been performed to help quantify the added value that cannot be inferred solely from objective evaluation.

Modeling of plug-in electric vehicle travel patterns and charging load based on trip chain generation

NASA Astrophysics Data System (ADS)

Wang, Dai; Gao, Junyu; Li, Pan; Wang, Bin; Zhang, Cong; Saxena, Samveg

2017-08-01

Modeling PEV travel and charging behavior is the key to estimate the charging demand and further explore the potential of providing grid services. This paper presents a stochastic simulation methodology to generate itineraries and charging load profiles for a population of PEVs based on real-world vehicle driving data. In order to describe the sequence of daily travel activities, we use the trip chain model which contains the detailed information of each trip, namely start time, end time, trip distance, start location and end location. A trip chain generation method is developed based on the Naive Bayes model to generate a large number of trips which are temporally and spatially coupled. We apply the proposed methodology to investigate the multi-location charging loads in three different scenarios. Simulation results show that home charging can meet the energy demand of the majority of PEVs in an average condition. In addition, we calculate the lower bound of charging load peak on the premise of lowest charging cost. The results are instructive for the design and construction of charging facilities to avoid excessive infrastructure.

Development and exploration of a new methodology for the fitting and analysis of XAS data.

PubMed

Delgado-Jaime, Mario Ulises; Kennepohl, Pierre

2010-01-01

A new data analysis methodology for X-ray absorption near-edge spectroscopy (XANES) is introduced and tested using several examples. The methodology has been implemented within the context of a new Matlab-based program discussed in a companion related article [Delgado-Jaime et al. (2010), J. Synchrotron Rad. 17, 132-137]. The approach makes use of a Monte Carlo search method to seek appropriate starting points for a fit model, allowing for the generation of a large number of independent fits with minimal user-induced bias. The applicability of this methodology is tested using various data sets on the Cl K-edge XAS data for tetragonal CuCl(4)(2-), a common reference compound used for calibration and covalency estimation in M-Cl bonds. A new background model function that effectively blends together background profiles with spectral features is an important component of the discussed methodology. The development of a robust evaluation function to fit multiple-edge data is discussed and the implications regarding standard approaches to data analysis are discussed and explored within these examples.

Development and exploration of a new methodology for the fitting and analysis of XAS data

PubMed Central

Delgado-Jaime, Mario Ulises; Kennepohl, Pierre

2010-01-01

A new data analysis methodology for X-ray absorption near-edge spectroscopy (XANES) is introduced and tested using several examples. The methodology has been implemented within the context of a new Matlab-based program discussed in a companion related article [Delgado-Jaime et al. (2010 ▶), J. Synchrotron Rad. 17, 132–137]. The approach makes use of a Monte Carlo search method to seek appropriate starting points for a fit model, allowing for the generation of a large number of independent fits with minimal user-induced bias. The applicability of this methodology is tested using various data sets on the Cl K-edge XAS data for tetragonal CuCl4 2−, a common reference compound used for calibration and covalency estimation in M—Cl bonds. A new background model function that effectively blends together background profiles with spectral features is an important component of the discussed methodology. The development of a robust evaluation function to fit multiple-edge data is discussed and the implications regarding standard approaches to data analysis are discussed and explored within these examples. PMID:20029120

Capturing complexity in work disability research: application of system dynamics modeling methodology.

PubMed

Jetha, Arif; Pransky, Glenn; Hettinger, Lawrence J

2016-01-01

Work disability (WD) is characterized by variable and occasionally undesirable outcomes. The underlying determinants of WD outcomes include patterns of dynamic relationships among health, personal, organizational and regulatory factors that have been challenging to characterize, and inadequately represented by contemporary WD models. System dynamics modeling (SDM) methodology applies a sociotechnical systems thinking lens to view WD systems as comprising a range of influential factors linked by feedback relationships. SDM can potentially overcome limitations in contemporary WD models by uncovering causal feedback relationships, and conceptualizing dynamic system behaviors. It employs a collaborative and stakeholder-based model building methodology to create a visual depiction of the system as a whole. SDM can also enable researchers to run dynamic simulations to provide evidence of anticipated or unanticipated outcomes that could result from policy and programmatic intervention. SDM may advance rehabilitation research by providing greater insights into the structure and dynamics of WD systems while helping to understand inherent complexity. Challenges related to data availability, determining validity, and the extensive time and technical skill requirements for model building may limit SDM's use in the field and should be considered. Contemporary work disability (WD) models provide limited insight into complexity associated with WD processes. System dynamics modeling (SDM) has the potential to capture complexity through a stakeholder-based approach that generates a simulation model consisting of multiple feedback loops. SDM may enable WD researchers and practitioners to understand the structure and behavior of the WD system as a whole, and inform development of improved strategies to manage straightforward and complex WD cases.

Evaluation of Structural Robustness against Column Loss: Methodology and Application to RC Frame Buildings.

PubMed

Bao, Yihai; Main, Joseph A; Noh, Sam-Young

2017-08-01

A computational methodology is presented for evaluating structural robustness against column loss. The methodology is illustrated through application to reinforced concrete (RC) frame buildings, using a reduced-order modeling approach for three-dimensional RC framing systems that includes the floor slabs. Comparisons with high-fidelity finite-element model results are presented to verify the approach. Pushdown analyses of prototype buildings under column loss scenarios are performed using the reduced-order modeling approach, and an energy-based procedure is employed to account for the dynamic effects associated with sudden column loss. Results obtained using the energy-based approach are found to be in good agreement with results from direct dynamic analysis of sudden column loss. A metric for structural robustness is proposed, calculated by normalizing the ultimate capacities of the structural system under sudden column loss by the applicable service-level gravity loading and by evaluating the minimum value of this normalized ultimate capacity over all column removal scenarios. The procedure is applied to two prototype 10-story RC buildings, one employing intermediate moment frames (IMFs) and the other employing special moment frames (SMFs). The SMF building, with its more stringent seismic design and detailing, is found to have greater robustness.

Cellular neural network-based hybrid approach toward automatic image registration

NASA Astrophysics Data System (ADS)

Arun, Pattathal VijayaKumar; Katiyar, Sunil Kumar

2013-01-01

Image registration is a key component of various image processing operations that involve the analysis of different image data sets. Automatic image registration domains have witnessed the application of many intelligent methodologies over the past decade; however, inability to properly model object shape as well as contextual information has limited the attainable accuracy. A framework for accurate feature shape modeling and adaptive resampling using advanced techniques such as vector machines, cellular neural network (CNN), scale invariant feature transform (SIFT), coreset, and cellular automata is proposed. CNN has been found to be effective in improving feature matching as well as resampling stages of registration and complexity of the approach has been considerably reduced using coreset optimization. The salient features of this work are cellular neural network approach-based SIFT feature point optimization, adaptive resampling, and intelligent object modelling. Developed methodology has been compared with contemporary methods using different statistical measures. Investigations over various satellite images revealed that considerable success was achieved with the approach. This system has dynamically used spectral and spatial information for representing contextual knowledge using CNN-prolog approach. This methodology is also illustrated to be effective in providing intelligent interpretation and adaptive resampling.

Speciation of adsorbates on surface of solids by infrared spectroscopy and chemometrics.

PubMed

Vilmin, Franck; Bazin, Philippe; Thibault-Starzyk, Frédéric; Travert, Arnaud

2015-09-03

Speciation, i.e. identification and quantification, of surface species on heterogeneous surfaces by infrared spectroscopy is important in many fields but remains a challenging task when facing strongly overlapped spectra of multiple adspecies. Here, we propose a new methodology, combining state of the art instrumental developments for quantitative infrared spectroscopy of adspecies and chemometrics tools, mainly a novel data processing algorithm, called SORB-MCR (SOft modeling by Recursive Based-Multivariate Curve Resolution) and multivariate calibration. After formal transposition of the general linear mixture model to adsorption spectral data, the main issues, i.e. validity of Beer-Lambert law and rank deficiency problems, are theoretically discussed. Then, the methodology is exposed through application to two case studies, each of them characterized by a specific type of rank deficiency: (i) speciation of physisorbed water species over a hydrated silica surface, and (ii) speciation (chemisorption and physisorption) of a silane probe molecule over a dehydrated silica surface. In both cases, we demonstrate the relevance of this approach which leads to a thorough surface speciation based on comprehensive and fully interpretable multivariate quantitative models. Limitations and drawbacks of the methodology are also underlined. Copyright © 2015 Elsevier B.V. All rights reserved.

Hybrid CMS methods with model reduction for assembly of structures

NASA Technical Reports Server (NTRS)

Farhat, Charbel

1991-01-01

Future on-orbit structures will be designed and built in several stages, each with specific control requirements. Therefore there must be a methodology which can predict the dynamic characteristics of the assembled structure, based on the dynamic characteristics of the subassemblies and their interfaces. The methodology developed by CSC to address this issue is Hybrid Component Mode Synthesis (HCMS). HCMS distinguishes itself from standard component mode synthesis algorithms in the following features: (1) it does not require the subcomponents to have displacement compatible models, which makes it ideal for analyzing the deployment of heterogeneous flexible multibody systems, (2) it incorporates a second-level model reduction scheme at the interface, which makes it much faster than other algorithms and therefore suitable for control purposes, and (3) it does answer specific questions such as 'how does the global fundamental frequency vary if I change the physical parameters of substructure k by a specified amount?'. Because it is based on an energy principle rather than displacement compatibility, this methodology can also help the designer to define an assembly process. Current and future efforts are devoted to applying the HCMS method to design and analyze docking and berthing procedures in orbital construction.

Creep force modelling for rail traction vehicles based on the Fastsim algorithm

NASA Astrophysics Data System (ADS)

Spiryagin, Maksym; Polach, Oldrich; Cole, Colin

2013-11-01

The evaluation of creep forces is a complex task and their calculation is a time-consuming process for multibody simulation (MBS). A methodology of creep forces modelling at large traction creepages has been proposed by Polach [Creep forces in simulations of traction vehicles running on adhesion limit. Wear. 2005;258:992-1000; Influence of locomotive tractive effort on the forces between wheel and rail. Veh Syst Dyn. 2001(Suppl);35:7-22] adapting his previously published algorithm [Polach O. A fast wheel-rail forces calculation computer code. Veh Syst Dyn. 1999(Suppl);33:728-739]. The most common method for creep force modelling used by software packages for MBS of running dynamics is the Fastsim algorithm by Kalker [A fast algorithm for the simplified theory of rolling contact. Veh Syst Dyn. 1982;11:1-13]. However, the Fastsim code has some limitations which do not allow modelling the creep force - creep characteristic in agreement with measurements for locomotives and other high-power traction vehicles, mainly for large traction creep at low-adhesion conditions. This paper describes a newly developed methodology based on a variable contact flexibility increasing with the ratio of the slip area to the area of adhesion. This variable contact flexibility is introduced in a modification of Kalker's code Fastsim by replacing the constant Kalker's reduction factor, widely used in MBS, by a variable reduction factor together with a slip-velocity-dependent friction coefficient decreasing with increasing global creepage. The proposed methodology is presented in this work and compared with measurements for different locomotives. The modification allows use of the well recognised Fastsim code for simulation of creep forces at large creepages in agreement with measurements without modifying the proven modelling methodology at small creepages.

Software reliability studies

NASA Technical Reports Server (NTRS)

Hoppa, Mary Ann; Wilson, Larry W.

1994-01-01

There are many software reliability models which try to predict future performance of software based on data generated by the debugging process. Our research has shown that by improving the quality of the data one can greatly improve the predictions. We are working on methodologies which control some of the randomness inherent in the standard data generation processes in order to improve the accuracy of predictions. Our contribution is twofold in that we describe an experimental methodology using a data structure called the debugging graph and apply this methodology to assess the robustness of existing models. The debugging graph is used to analyze the effects of various fault recovery orders on the predictive accuracy of several well-known software reliability algorithms. We found that, along a particular debugging path in the graph, the predictive performance of different models can vary greatly. Similarly, just because a model 'fits' a given path's data well does not guarantee that the model would perform well on a different path. Further we observed bug interactions and noted their potential effects on the predictive process. We saw that not only do different faults fail at different rates, but that those rates can be affected by the particular debugging stage at which the rates are evaluated. Based on our experiment, we conjecture that the accuracy of a reliability prediction is affected by the fault recovery order as well as by fault interaction.

Dynamic Educational e-Content Selection Using Multiple Criteria in Web-Based Personalized Learning Environments.

ERIC Educational Resources Information Center

Manouselis, Nikos; Sampson, Demetrios

This paper focuses on the way a multi-criteria decision making methodology is applied in the case of agent-based selection of offered learning objects. The problem of selection is modeled as a decision making one, with the decision variables being the learner model and the learning objects' educational description. In this way, selection of…

Development of an Adolescent Alcohol Misuse Intervention Based on the Prototype Willingness Model: A Delphi Study

ERIC Educational Resources Information Center

Davies, Emma; Martin, Jilly; Foxcroft, David

2016-01-01

Purpose: The purpose of this paper is to report on the use of the Delphi method to gain expert feedback on the identification of behaviour change techniques (BCTs) and development of a novel intervention to reduce adolescent alcohol misuse, based on the Prototype Willingness Model (PWM) of health risk behaviour. Design/methodology/approach: Four…

Learning-based stochastic object models for characterizing anatomical variations

NASA Astrophysics Data System (ADS)

Dolly, Steven R.; Lou, Yang; Anastasio, Mark A.; Li, Hua

2018-03-01

It is widely known that the optimization of imaging systems based on objective, task-based measures of image quality via computer-simulation requires the use of a stochastic object model (SOM). However, the development of computationally tractable SOMs that can accurately model the statistical variations in human anatomy within a specified ensemble of patients remains a challenging task. Previously reported numerical anatomic models lack the ability to accurately model inter-patient and inter-organ variations in human anatomy among a broad patient population, mainly because they are established on image data corresponding to a few of patients and individual anatomic organs. This may introduce phantom-specific bias into computer-simulation studies, where the study result is heavily dependent on which phantom is used. In certain applications, however, databases of high-quality volumetric images and organ contours are available that can facilitate this SOM development. In this work, a novel and tractable methodology for learning a SOM and generating numerical phantoms from a set of volumetric training images is developed. The proposed methodology learns geometric attribute distributions (GAD) of human anatomic organs from a broad patient population, which characterize both centroid relationships between neighboring organs and anatomic shape similarity of individual organs among patients. By randomly sampling the learned centroid and shape GADs with the constraints of the respective principal attribute variations learned from the training data, an ensemble of stochastic objects can be created. The randomness in organ shape and position reflects the learned variability of human anatomy. To demonstrate the methodology, a SOM of an adult male pelvis is computed and examples of corresponding numerical phantoms are created.

Small car exposure data project. Phase 1 : methodology

DOT National Transportation Integrated Search

1985-10-01

The Small Car Exposure Data Project represents the first phase of an effort to build a data : base of exposure variables for crash-avoidance studies. Among these are: (1) vehicle make, : model, year, body style, wheel base, weight, and horsepower; (2...

Analysis of the possibility of SysML and BPMN application in formal data acquisition system description

NASA Astrophysics Data System (ADS)

Ćwikła, G.; Gwiazda, A.; Banaś, W.; Monica, Z.; Foit, K.

2017-08-01

The article presents the study of possible application of selected methods of complex description, that can be used as a support of the Manufacturing Information Acquisition System (MIAS) methodology, describing how to design a data acquisition system, allowing for collecting and processing real-time data on the functioning of a production system, necessary for management of a company. MIAS can allow conversion into Cyber-Physical Production System. MIAS is gathering and pre-processing data on the state of production system, including e.g. realisation of production orders, state of machines, materials and human resources. Systematised approach and model-based development is proposed for improving the quality of the design of MIAS methodology-based complex systems supporting data acquisition in various types of companies. Graphical specification can be the baseline for any model-based development in specified areas. The possibility of application of SysML and BPMN, both being UML-based languages, representing different approaches to modelling of requirements, architecture and implementation of the data acquisition system, as a tools supporting description of required features of MIAS, were considered.

Catchment area-based evaluation of the AMC-dependent SCS-CN-based rainfall-runoff models

NASA Astrophysics Data System (ADS)

Mishra, S. K.; Jain, M. K.; Pandey, R. P.; Singh, V. P.

2005-09-01

Using a large set of rainfall-runoff data from 234 watersheds in the USA, a catchment area-based evaluation of the modified version of the Mishra and Singh (2002a) model was performed. The model is based on the Soil Conservation Service Curve Number (SCS-CN) methodology and incorporates the antecedent moisture in computation of direct surface runoff. Comparison with the existing SCS-CN method showed that the modified version performed better than did the existing one on the data of all seven area-based groups of watersheds ranging from 0.01 to 310.3 km2.

Equivalent Viscous Damping Methodologies Applied on VEGA Launch Vehicle Numerical Model

NASA Astrophysics Data System (ADS)

Bartoccini, D.; Di Trapani, C.; Fransen, S.

2014-06-01

Part of the mission analysis of a spacecraft is the so- called launcher-satellite coupled loads analysis which aims at computing the dynamic environment of the satellite and of the launch vehicle for the most severe load cases in flight. Evidently the damping of the coupled system shall be defined with care as to not overestimate or underestimate the loads derived for the spacecraft. In this paper the application of several EqVD (Equivalent Viscous Damping) for Craig an Bampton (CB)-systems are investigated. Based on the structural damping defined for the various materials in the parent FE-models of the CB-components, EqVD matrices can be computed according to different methodologies. The effect of these methodologies on the numerical reconstruction of the VEGA launch vehicle dynamic environment will be presented.

Risk assessment of groundwater level variability using variable Kriging methods

NASA Astrophysics Data System (ADS)

Spanoudaki, Katerina; Kampanis, Nikolaos A.

2015-04-01

Assessment of the water table level spatial variability in aquifers provides useful information regarding optimal groundwater management. This information becomes more important in basins where the water table level has fallen significantly. The spatial variability of the water table level in this work is estimated based on hydraulic head measured during the wet period of the hydrological year 2007-2008, in a sparsely monitored basin in Crete, Greece, which is of high socioeconomic and agricultural interest. Three Kriging-based methodologies are elaborated in Matlab environment to estimate the spatial variability of the water table level in the basin. The first methodology is based on the Ordinary Kriging approach, the second involves auxiliary information from a Digital Elevation Model in terms of Residual Kriging and the third methodology calculates the probability of the groundwater level to fall below a predefined minimum value that could cause significant problems in groundwater resources availability, by means of Indicator Kriging. The Box-Cox methodology is applied to normalize both the data and the residuals for improved prediction results. In addition, various classical variogram models are applied to determine the spatial dependence of the measurements. The Matérn model proves to be the optimal, which in combination with Kriging methodologies provides the most accurate cross validation estimations. Groundwater level and probability maps are constructed to examine the spatial variability of the groundwater level in the basin and the associated risk that certain locations exhibit regarding a predefined minimum value that has been set for the sustainability of the basin's groundwater resources. Acknowledgement The work presented in this paper has been funded by the Greek State Scholarships Foundation (IKY), Fellowships of Excellence for Postdoctoral Studies (Siemens Program), 'A simulation-optimization model for assessing the best practices for the protection of surface water and groundwater in the coastal zone', (2013 - 2015). Varouchakis, E. A. and D. T. Hristopulos (2013). "Improvement of groundwater level prediction in sparsely gauged basins using physical laws and local geographic features as auxiliary variables." Advances in Water Resources 52: 34-49. Kitanidis, P. K. (1997). Introduction to geostatistics, Cambridge: University Press.

Scales and erosion

USDA-ARS?s Scientific Manuscript database

There is a need to develop scale explicit understanding of erosion to overcome existing conceptual and methodological flaws in our modelling methods currently applied to understand the process of erosion, transport and deposition at the catchment scale. These models need to be based on a sound under...

Examining the Utility of Topic Models for Linguistic Analysis of Couple Therapy

ERIC Educational Resources Information Center

Doeden, Michelle A.

2012-01-01

This study examined the basic utility of topic models, a computational linguistics model for text-based data, to the investigation of the process of couple therapy. Linguistic analysis offers an additional lens through which to examine clinical data, and the topic model is presented as a novel methodology within couple and family psychology that…

An Overview of Markov Chain Methods for the Study of Stage-Sequential Developmental Processes

ERIC Educational Resources Information Center

Kapland, David

2008-01-01

This article presents an overview of quantitative methodologies for the study of stage-sequential development based on extensions of Markov chain modeling. Four methods are presented that exemplify the flexibility of this approach: the manifest Markov model, the latent Markov model, latent transition analysis, and the mixture latent Markov model.…

Model documentation: Electricity Market Module, Electricity Fuel Dispatch Submodule

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

Not Available

This report documents the objectives, analytical approach and development of the National Energy Modeling System Electricity Fuel Dispatch Submodule (EFD), a submodule of the Electricity Market Module (EMM). The report catalogues and describes the model assumptions, computational methodology, parameter estimation techniques, model source code, and forecast results generated through the synthesis and scenario development based on these components.

A neural network based methodology to predict site-specific spectral acceleration values

NASA Astrophysics Data System (ADS)

Kamatchi, P.; Rajasankar, J.; Ramana, G. V.; Nagpal, A. K.

2010-12-01

A general neural network based methodology that has the potential to replace the computationally-intensive site-specific seismic analysis of structures is proposed in this paper. The basic framework of the methodology consists of a feed forward back propagation neural network algorithm with one hidden layer to represent the seismic potential of a region and soil amplification effects. The methodology is implemented and verified with parameters corresponding to Delhi city in India. For this purpose, strong ground motions are generated at bedrock level for a chosen site in Delhi due to earthquakes considered to originate from the central seismic gap of the Himalayan belt using necessary geological as well as geotechnical data. Surface level ground motions and corresponding site-specific response spectra are obtained by using a one-dimensional equivalent linear wave propagation model. Spectral acceleration values are considered as a target parameter to verify the performance of the methodology. Numerical studies carried out to validate the proposed methodology show that the errors in predicted spectral acceleration values are within acceptable limits for design purposes. The methodology is general in the sense that it can be applied to other seismically vulnerable regions and also can be updated by including more parameters depending on the state-of-the-art in the subject.

Performance analysis of complex repairable industrial systems using PSO and fuzzy confidence interval based methodology.

PubMed

Garg, Harish

2013-03-01

The main objective of the present paper is to propose a methodology for analyzing the behavior of the complex repairable industrial systems. In real-life situations, it is difficult to find the most optimal design policies for MTBF (mean time between failures), MTTR (mean time to repair) and related costs by utilizing available resources and uncertain data. For this, the availability-cost optimization model has been constructed for determining the optimal design parameters for improving the system design efficiency. The uncertainties in the data related to each component of the system are estimated with the help of fuzzy and statistical methodology in the form of the triangular fuzzy numbers. Using these data, the various reliability parameters, which affects the system performance, are obtained in the form of the fuzzy membership function by the proposed confidence interval based fuzzy Lambda-Tau (CIBFLT) methodology. The computed results by CIBFLT are compared with the existing fuzzy Lambda-Tau methodology. Sensitivity analysis on the system MTBF has also been addressed. The methodology has been illustrated through a case study of washing unit, the main part of the paper industry. Copyright © 2012 ISA. Published by Elsevier Ltd. All rights reserved.

Maximizing the Impact of Program Evaluation: A Discrepancy-Based Process for Educational Program Evaluation.

ERIC Educational Resources Information Center

Cantor, Jeffrey A.

This paper describes a formative/summative process for educational program evaluation, which is appropriate for higher education programs and is based on M. Provus' Discrepancy Evaluation Model and the principles of instructional design. The Discrepancy Based Methodology for Educational Program Evaluation facilitates systematic and detailed…

On 4-degree-of-freedom biodynamic models of seated occupants: Lumped-parameter modeling

NASA Astrophysics Data System (ADS)

Bai, Xian-Xu; Xu, Shi-Xu; Cheng, Wei; Qian, Li-Jun

2017-08-01

It is useful to develop an effective biodynamic model of seated human occupants to help understand the human vibration exposure to transportation vehicle vibrations and to help design and improve the anti-vibration devices and/or test dummies. This study proposed and demonstrated a methodology for systematically identifying the best configuration or structure of a 4-degree-of-freedom (4DOF) human vibration model and for its parameter identification. First, an equivalent simplification expression for the models was made. Second, all of the possible 23 structural configurations of the models were identified. Third, each of them was calibrated using the frequency response functions recommended in a biodynamic standard. An improved version of non-dominated sorting genetic algorithm (NSGA-II) based on Pareto optimization principle was used to determine the model parameters. Finally, a model evaluation criterion proposed in this study was used to assess the models and to identify the best one, which was based on both the goodness of curve fits and comprehensive goodness of the fits. The identified top configurations were better than those reported in the literature. This methodology may also be extended and used to develop the models with other DOFs.

Use of a GIS-based hybrid artificial neural network to prioritize the order of pipe replacement in a water distribution network.

PubMed

Ho, Cheng-I; Lin, Min-Der; Lo, Shang-Lien

2010-07-01

A methodology based on the integration of a seismic-based artificial neural network (ANN) model and a geographic information system (GIS) to assess water leakage and to prioritize pipeline replacement is developed in this work. Qualified pipeline break-event data derived from the Taiwan Water Corporation Pipeline Leakage Repair Management System were analyzed. "Pipe diameter," "pipe material," and "the number of magnitude-3( + ) earthquakes" were employed as the input factors of ANN, while "the number of monthly breaks" was used for the prediction output. This study is the first attempt to manipulate earthquake data in the break-event ANN prediction model. Spatial distribution of the pipeline break-event data was analyzed and visualized by GIS. Through this, the users can swiftly figure out the hotspots of the leakage areas. A northeastern township in Taiwan, frequently affected by earthquakes, is chosen as the case study. Compared to the traditional processes for determining the priorities of pipeline replacement, the methodology developed is more effective and efficient. Likewise, the methodology can overcome the difficulty of prioritizing pipeline replacement even in situations where the break-event records are unavailable.

A multichannel model-based methodology for extubation readiness decision of patients on weaning trials.

PubMed

Casaseca-de-la-Higuera, Pablo; Simmross-Wattenberg, Federico; Martín-Fernández, Marcos; Alberola-López, Carlos

2009-07-01

Discontinuation of mechanical ventilation is a challenging task that involves a number of subtle clinical issues. The gradual removal of the respiratory support (referred to as weaning) should be performed as soon as autonomous respiration can be sustained. However, the prediction rate of successful extubation is still below 25% based on previous studies. Construction of an automatic system that provides information on extubation readiness is thus desirable. Recent works have demonstrated that the breathing pattern variability is a useful extubation readiness indicator, with improving performance when multiple respiratory signals are jointly processed. However, the existing methods for predictor extraction present several drawbacks when length-limited time series are to be processed in heterogeneous groups of patients. In this paper, we propose a model-based methodology for automatic readiness prediction. It is intended to deal with multichannel, nonstationary, short records of the breathing pattern. Results on experimental data yield an 87.27% of successful readiness prediction, which is in line with the best figures reported in the literature. A comparative analysis shows that our methodology overcomes the shortcomings of so far proposed methods when applied to length-limited records on heterogeneous groups of patients.

Non-Fourier based thermal-mechanical tissue damage prediction for thermal ablation.

PubMed

Li, Xin; Zhong, Yongmin; Smith, Julian; Gu, Chengfan

2017-01-02

Prediction of tissue damage under thermal loads plays important role for thermal ablation planning. A new methodology is presented in this paper by combing non-Fourier bio-heat transfer, constitutive elastic mechanics as well as non-rigid motion of dynamics to predict and analyze thermal distribution, thermal-induced mechanical deformation and thermal-mechanical damage of soft tissues under thermal loads. Simulations and comparison analysis demonstrate that the proposed methodology based on the non-Fourier bio-heat transfer can account for the thermal-induced mechanical behaviors of soft tissues and predict tissue thermal damage more accurately than classical Fourier bio-heat transfer based model.

Non-Fourier based thermal-mechanical tissue damage prediction for thermal ablation

PubMed Central

Li, Xin; Zhong, Yongmin; Smith, Julian; Gu, Chengfan

2017-01-01

ABSTRACT Prediction of tissue damage under thermal loads plays important role for thermal ablation planning. A new methodology is presented in this paper by combing non-Fourier bio-heat transfer, constitutive elastic mechanics as well as non-rigid motion of dynamics to predict and analyze thermal distribution, thermal-induced mechanical deformation and thermal-mechanical damage of soft tissues under thermal loads. Simulations and comparison analysis demonstrate that the proposed methodology based on the non-Fourier bio-heat transfer can account for the thermal-induced mechanical behaviors of soft tissues and predict tissue thermal damage more accurately than classical Fourier bio-heat transfer based model. PMID:27690290

VARIABLE SELECTION FOR REGRESSION MODELS WITH MISSING DATA

PubMed Central

Garcia, Ramon I.; Ibrahim, Joseph G.; Zhu, Hongtu

2009-01-01

We consider the variable selection problem for a class of statistical models with missing data, including missing covariate and/or response data. We investigate the smoothly clipped absolute deviation penalty (SCAD) and adaptive LASSO and propose a unified model selection and estimation procedure for use in the presence of missing data. We develop a computationally attractive algorithm for simultaneously optimizing the penalized likelihood function and estimating the penalty parameters. Particularly, we propose to use a model selection criterion, called the ICQ statistic, for selecting the penalty parameters. We show that the variable selection procedure based on ICQ automatically and consistently selects the important covariates and leads to efficient estimates with oracle properties. The methodology is very general and can be applied to numerous situations involving missing data, from covariates missing at random in arbitrary regression models to nonignorably missing longitudinal responses and/or covariates. Simulations are given to demonstrate the methodology and examine the finite sample performance of the variable selection procedures. Melanoma data from a cancer clinical trial is presented to illustrate the proposed methodology. PMID:20336190

A Perspective on Computational Human Performance Models as Design Tools

NASA Technical Reports Server (NTRS)

Jones, Patricia M.

2010-01-01

The design of interactive systems, including levels of automation, displays, and controls, is usually based on design guidelines and iterative empirical prototyping. A complementary approach is to use computational human performance models to evaluate designs. An integrated strategy of model-based and empirical test and evaluation activities is particularly attractive as a methodology for verification and validation of human-rated systems for commercial space. This talk will review several computational human performance modeling approaches and their applicability to design of display and control requirements.

Generalized Predictive and Neural Generalized Predictive Control of Aerospace Systems

NASA Technical Reports Server (NTRS)

Kelkar, Atul G.

2000-01-01

The research work presented in this thesis addresses the problem of robust control of uncertain linear and nonlinear systems using Neural network-based Generalized Predictive Control (NGPC) methodology. A brief overview of predictive control and its comparison with Linear Quadratic (LQ) control is given to emphasize advantages and drawbacks of predictive control methods. It is shown that the Generalized Predictive Control (GPC) methodology overcomes the drawbacks associated with traditional LQ control as well as conventional predictive control methods. It is shown that in spite of the model-based nature of GPC it has good robustness properties being special case of receding horizon control. The conditions for choosing tuning parameters for GPC to ensure closed-loop stability are derived. A neural network-based GPC architecture is proposed for the control of linear and nonlinear uncertain systems. A methodology to account for parametric uncertainty in the system is proposed using on-line training capability of multi-layer neural network. Several simulation examples and results from real-time experiments are given to demonstrate the effectiveness of the proposed methodology.

Expanding the Parameters for Excellence in Patient Assignments: Is Leveraging an Evidence-Data-Based Acuity Methodology Realistic?

PubMed

Gray, Joel; Kerfoot, Karlene

2016-01-01

Finding the balance of equitable assignments continues to be a challenge for health care organizations seeking to leverage evidence-based leadership practices. Ratios and subjective acuity strategies for nurse-patient staffing continue to be the dominant approach in health care organizations. In addition to ratio-based assignments and acuity-based assignment models driven by financial targets, more emphasis on using evidence-based leadership strategies to manage and create science for effective staffing is needed. In particular, nurse leaders are challenged to increase the sophistication of management of patient turnover (admissions, discharges, and transfers) and integrate tools from Lean methodologies and quality management strategies to determine the effectiveness of nurse-patient staffing.

Grain-Boundary Resistance in Copper Interconnects: From an Atomistic Model to a Neural Network

NASA Astrophysics Data System (ADS)

Valencia, Daniel; Wilson, Evan; Jiang, Zhengping; Valencia-Zapata, Gustavo A.; Wang, Kuang-Chung; Klimeck, Gerhard; Povolotskyi, Michael

2018-04-01

Orientation effects on the specific resistance of copper grain boundaries are studied systematically with two different atomistic tight-binding methods. A methodology is developed to model the specific resistance of grain boundaries in the ballistic limit using the embedded atom model, tight- binding methods, and nonequilibrium Green's functions. The methodology is validated against first-principles calculations for thin films with a single coincident grain boundary, with 6.4% deviation in the specific resistance. A statistical ensemble of 600 large, random structures with grains is studied. For structures with three grains, it is found that the distribution of specific resistances is close to normal. Finally, a compact model for grain-boundary-specific resistance is constructed based on a neural network.

A Methodology for Phased Array Radar Threshold Modeling Using the Advanced Propagation Model (APM)

DTIC Science & Technology

2017-10-01

TECHNICAL REPORT 3079 October 2017 A Methodology for Phased Array Radar Threshold Modeling Using the Advanced Propagation Model (APM...Head 55190 Networks Division iii EXECUTIVE SUMMARY This report summarizes the methodology developed to improve the radar threshold modeling...PHASED ARRAY RADAR CONFIGURATION ..................................................................... 1 3. METHODOLOGY

Simulation-based cutaneous surgical-skill training on a chicken-skin bench model in a medical undergraduate program.

PubMed

Denadai, Rafael; Saad-Hossne, Rogério; Martinhão Souto, Luís Ricardo

2013-05-01

Because of ethical and medico-legal aspects involved in the training of cutaneous surgical skills on living patients, human cadavers and living animals, it is necessary the search for alternative and effective forms of training simulation. To propose and describe an alternative methodology for teaching and learning the principles of cutaneous surgery in a medical undergraduate program by using a chicken-skin bench model. One instructor for every four students, teaching materials on cutaneous surgical skills, chicken trunks, wings, or thighs, a rigid platform support, needled threads, needle holders, surgical blades with scalpel handles, rat-tooth tweezers, scissors, and marking pens were necessary for training simulation. A proposal for simulation-based training on incision, suture, biopsy, and on reconstruction techniques using a chicken-skin bench model distributed in several sessions and with increasing levels of difficultywas structured. Both feedback and objective evaluations always directed to individual students were also outlined. The teaching of a methodology for the principles of cutaneous surgery using a chicken-skin bench model versatile, portable, easy to assemble, and inexpensive is an alternative and complementary option to the armamentarium of methods based on other bench models described.

Prediction of dosage-based parameters from the puff dispersion of airborne materials in urban environments using the CFD-RANS methodology

NASA Astrophysics Data System (ADS)

Efthimiou, G. C.; Andronopoulos, S.; Bartzis, J. G.

2018-02-01

One of the key issues of recent research on the dispersion inside complex urban environments is the ability to predict dosage-based parameters from the puff release of an airborne material from a point source in the atmospheric boundary layer inside the built-up area. The present work addresses the question of whether the computational fluid dynamics (CFD)-Reynolds-averaged Navier-Stokes (RANS) methodology can be used to predict ensemble-average dosage-based parameters that are related with the puff dispersion. RANS simulations with the ADREA-HF code were, therefore, performed, where a single puff was released in each case. The present method is validated against the data sets from two wind-tunnel experiments. In each experiment, more than 200 puffs were released from which ensemble-averaged dosage-based parameters were calculated and compared to the model's predictions. The performance of the model was evaluated using scatter plots and three validation metrics: fractional bias, normalized mean square error, and factor of two. The model presented a better performance for the temporal parameters (i.e., ensemble-average times of puff arrival, peak, leaving, duration, ascent, and descent) than for the ensemble-average dosage and peak concentration. The majority of the obtained values of validation metrics were inside established acceptance limits. Based on the obtained model performance indices, the CFD-RANS methodology as implemented in the code ADREA-HF is able to predict the ensemble-average temporal quantities related to transient emissions of airborne material in urban areas within the range of the model performance acceptance criteria established in the literature. The CFD-RANS methodology as implemented in the code ADREA-HF is also able to predict the ensemble-average dosage, but the dosage results should be treated with some caution; as in one case, the observed ensemble-average dosage was under-estimated slightly more than the acceptance criteria. Ensemble-average peak concentration was systematically underpredicted by the model to a degree higher than the allowable by the acceptance criteria, in 1 of the 2 wind-tunnel experiments. The model performance depended on the positions of the examined sensors in relation to the emission source and the buildings configuration. The work presented in this paper was carried out (partly) within the scope of COST Action ES1006 "Evaluation, improvement, and guidance for the use of local-scale emergency prediction and response tools for airborne hazards in built environments".

[Qualitative research methodology in health care].

PubMed

Bedregal, Paula; Besoain, Carolina; Reinoso, Alejandro; Zubarew, Tamara

2017-03-01

Health care research requires different methodological approaches such as qualitative and quantitative analyzes to understand the phenomena under study. Qualitative research is usually the least considered. Central elements of the qualitative method are that the object of study is constituted by perceptions, emotions and beliefs, non-random sampling by purpose, circular process of knowledge construction, and methodological rigor throughout the research process, from quality design to the consistency of results. The objective of this work is to contribute to the methodological knowledge about qualitative research in health services, based on the implementation of the study, “The transition process from pediatric to adult services: perspectives from adolescents with chronic diseases, caregivers and health professionals”. The information gathered through the qualitative methodology facilitated the understanding of critical points, barriers and facilitators of the transition process of adolescents with chronic diseases, considering the perspective of users and the health team. This study allowed the design of a transition services model from pediatric to adult health services based on the needs of adolescents with chronic diseases, their caregivers and the health team.

Development of an Optimization Methodology for the Aluminum Alloy Wheel Casting Process

NASA Astrophysics Data System (ADS)

Duan, Jianglan; Reilly, Carl; Maijer, Daan M.; Cockcroft, Steve L.; Phillion, Andre B.

2015-08-01

An optimization methodology has been developed for the aluminum alloy wheel casting process. The methodology is focused on improving the timing of cooling processes in a die to achieve improved casting quality. This methodology utilizes (1) a casting process model, which was developed within the commercial finite element package, ABAQUS™—ABAQUS is a trademark of Dassault Systèms; (2) a Python-based results extraction procedure; and (3) a numerical optimization module from the open-source Python library, Scipy. To achieve optimal casting quality, a set of constraints have been defined to ensure directional solidification, and an objective function, based on the solidification cooling rates, has been defined to either maximize, or target a specific, cooling rate. The methodology has been applied to a series of casting and die geometries with different cooling system configurations, including a 2-D axisymmetric wheel and die assembly generated from a full-scale prototype wheel. The results show that, with properly defined constraint and objective functions, solidification conditions can be improved and optimal cooling conditions can be achieved leading to process productivity and product quality improvements.

Epistemological Beliefs and Knowledge Sharing in Work Teams: A New Model and Research Questions

ERIC Educational Resources Information Center

Weinberg, Frankie J.

2015-01-01

Purpose: The purpose of this paper is to present a knowledge-sharing model that explains individual members' motivation to share knowledge (knowledge donation and knowledge collection). Design/methodology/approach: The model is based on social-constructivist theories of epistemological beliefs, learning and distributed cognition, and is organized…

A Career Success Model for Academics at Malaysian Research Universities

ERIC Educational Resources Information Center

Abu Said, Al-Mansor; Mohd Rasdi, Roziah; Abu Samah, Bahaman; Silong, Abu Daud; Sulaiman, Suzaimah

2015-01-01

Purpose: The purpose of this paper is to develop a career success model for academics at the Malaysian research universities. Design/methodology/approach: Self-administered and online surveys were used for data collection among 325 academics from Malaysian research universities. Findings: Based on the analysis of structural equation modeling, the…

A general gridding, discretization, and coarsening methodology for modeling flow in porous formations with discrete geological features

NASA Astrophysics Data System (ADS)

Karimi-Fard, M.; Durlofsky, L. J.

2016-10-01

A comprehensive framework for modeling flow in porous media containing thin, discrete features, which could be high-permeability fractures or low-permeability deformation bands, is presented. The key steps of the methodology are mesh generation, fine-grid discretization, upscaling, and coarse-grid discretization. Our specialized gridding technique combines a set of intersecting triangulated surfaces by constructing approximate intersections using existing edges. This procedure creates a conforming mesh of all surfaces, which defines the internal boundaries for the volumetric mesh. The flow equations are discretized on this conforming fine mesh using an optimized two-point flux finite-volume approximation. The resulting discrete model is represented by a list of control-volumes with associated positions and pore-volumes, and a list of cell-to-cell connections with associated transmissibilities. Coarse models are then constructed by the aggregation of fine-grid cells, and the transmissibilities between adjacent coarse cells are obtained using flow-based upscaling procedures. Through appropriate computation of fracture-matrix transmissibilities, a dual-continuum representation is obtained on the coarse scale in regions with connected fracture networks. The fine and coarse discrete models generated within the framework are compatible with any connectivity-based simulator. The applicability of the methodology is illustrated for several two- and three-dimensional examples. In particular, we consider gas production from naturally fractured low-permeability formations, and transport through complex fracture networks. In all cases, highly accurate solutions are obtained with significant model reduction.

The use of geospatial web services for exchanging utilities data

NASA Astrophysics Data System (ADS)

Kuczyńska, Joanna

2013-04-01

Geographic information technologies and related geo-information systems currently play an important role in the management of public administration in Poland. One of these tasks is to maintain and update Geodetic Evidence of Public Utilities (GESUT), part of the National Geodetic and Cartographic Resource, which contains an important for many institutions information of technical infrastructure. It requires an active exchange of data between the Geodesy and Cartography Documentation Centers and institutions, which administrate transmission lines. The administrator of public utilities, is legally obliged to provide information about utilities to GESUT. The aim of the research work was to develop a universal data exchange methodology, which can be implemented on a variety of hardware and software platforms. This methodology use Unified Modeling Language (UML), eXtensible Markup Language (XML), and Geography Markup Language (GML). The proposed methodology is based on the two different strategies: Model Driven Architecture (MDA) and Service Oriented Architecture (SOA). Used solutions are consistent with the INSPIRE Directive and ISO 19100 series standards for geographic information. On the basis of analysis of the input data structures, conceptual models were built for both databases. Models were written in the universal modeling language: UML. Combined model that defines a common data structure was also built. This model was transformed into developed for the exchange of geographic information GML standard. The structure of the document describing the data that may be exchanged is defined in the .xsd file. Network services were selected and implemented in the system designed for data exchange based on open source tools. Methodology was implemented and tested. Data in the agreed data structure and metadata were set up on the server. Data access was provided by geospatial network services: data searching possibilities by Catalog Service for the Web (CSW), data collection by Web Feature Service (WFS). WFS provides also operation for modification data, for example to update them by utility administrator. The proposed solution significantly increases the efficiency of data exchange and facilitates maintenance the National Geodetic and Cartographic Resource.

Adapting Rational Unified Process (RUP) approach in designing a secure e-Tendering model

NASA Astrophysics Data System (ADS)

Mohd, Haslina; Robie, Muhammad Afdhal Muhammad; Baharom, Fauziah; Darus, Norida Muhd; Saip, Mohamed Ali; Yasin, Azman

2016-08-01

e-Tendering is an electronic processing of the tender document via internet and allow tenderer to publish, communicate, access, receive and submit all tender related information and documentation via internet. This study aims to design the e-Tendering system using Rational Unified Process approach. RUP provides a disciplined approach on how to assign tasks and responsibilities within the software development process. RUP has four phases that can assist researchers to adjust the requirements of various projects with different scope, problem and the size of projects. RUP is characterized as a use case driven, architecture centered, iterative and incremental process model. However the scope of this study only focusing on Inception and Elaboration phases as step to develop the model and perform only three of nine workflows (business modeling, requirements, analysis and design). RUP has a strong focus on documents and the activities in the inception and elaboration phases mainly concern the creation of diagrams and writing of textual descriptions. The UML notation and the software program, Star UML are used to support the design of e-Tendering. The e-Tendering design based on the RUP approach can contribute to e-Tendering developers and researchers in e-Tendering domain. In addition, this study also shows that the RUP is one of the best system development methodology that can be used as one of the research methodology in Software Engineering domain related to secured design of any observed application. This methodology has been tested in various studies in certain domains, such as in Simulation-based Decision Support, Security Requirement Engineering, Business Modeling and Secure System Requirement, and so forth. As a conclusion, these studies showed that the RUP one of a good research methodology that can be adapted in any Software Engineering (SE) research domain that required a few artifacts to be generated such as use case modeling, misuse case modeling, activity diagram, and initial class diagram from a list of requirements as identified earlier by the SE researchers

Model-based approach for design verification and co-optimization of catastrophic and parametric-related defects due to systematic manufacturing variations

NASA Astrophysics Data System (ADS)

Perry, Dan; Nakamoto, Mark; Verghese, Nishath; Hurat, Philippe; Rouse, Rich

2007-03-01

Model-based hotspot detection and silicon-aware parametric analysis help designers optimize their chips for yield, area and performance without the high cost of applying foundries' recommended design rules. This set of DFM/ recommended rules is primarily litho-driven, but cannot guarantee a manufacturable design without imposing overly restrictive design requirements. This rule-based methodology of making design decisions based on idealized polygons that no longer represent what is on silicon needs to be replaced. Using model-based simulation of the lithography, OPC, RET and etch effects, followed by electrical evaluation of the resulting shapes, leads to a more realistic and accurate analysis. This analysis can be used to evaluate intelligent design trade-offs and identify potential failures due to systematic manufacturing defects during the design phase. The successful DFM design methodology consists of three parts: 1. Achieve a more aggressive layout through limited usage of litho-related recommended design rules. A 10% to 15% area reduction is achieved by using more aggressive design rules. DFM/recommended design rules are used only if there is no impact on cell size. 2. Identify and fix hotspots using a model-based layout printability checker. Model-based litho and etch simulation are done at the cell level to identify hotspots. Violations of recommended rules may cause additional hotspots, which are then fixed. The resulting design is ready for step 3. 3. Improve timing accuracy with a process-aware parametric analysis tool for transistors and interconnect. Contours of diffusion, poly and metal layers are used for parametric analysis. In this paper, we show the results of this physical and electrical DFM methodology at Qualcomm. We describe how Qualcomm was able to develop more aggressive cell designs that yielded a 10% to 15% area reduction using this methodology. Model-based shape simulation was employed during library development to validate architecture choices and to optimize cell layout. At the physical verification stage, the shape simulator was run at full-chip level to identify and fix residual hotspots on interconnect layers, on poly or metal 1 due to interaction between adjacent cells, or on metal 1 due to interaction between routing (via and via cover) and cell geometry. To determine an appropriate electrical DFM solution, Qualcomm developed an experiment to examine various electrical effects. After reporting the silicon results of this experiment, which showed sizeable delay variations due to lithography-related systematic effects, we also explain how contours of diffusion, poly and metal can be used for silicon-aware parametric analysis of transistors and interconnect at the cell-, block- and chip-level.

In Vivo Patellofemoral Contact Mechanics During Active Extension Using a Novel Dynamic MRI-based Methodology

PubMed Central

Borotikar, Bhushan S.; Sheehan, Frances T.

2017-01-01

Objectives To establish an in vivo, normative patellofemoral cartilage contact mechanics database acquired during voluntary muscle control using a novel dynamic magnetic resonance (MR) imaging-based computational methodology and validate the contact mechanics sensitivity to the known sub-millimeter methodological inaccuracies. Design Dynamic cine phase-contrast and multi-plane cine images were acquired while female subjects (n=20, sample of convenience) performed an open kinetic chain (knee flexion-extension) exercise inside a 3-Tesla MR scanner. Static cartilage models were created from high resolution three-dimensional static MR data and accurately placed in their dynamic pose at each time frame based on the cine-PC data. Cartilage contact parameters were calculated based on the surface overlap. Statistical analysis was performed using paired t-test and a one-sample repeated measures ANOVA. The sensitivity of the contact parameters to the known errors in the patellofemoral kinematics was determined. Results Peak mean patellofemoral contact area was 228.7±173.6mm2 at 40° knee angle. During extension, contact centroid and peak strain locations tracked medially on the femoral and patellar cartilage and were not significantly different from each other. At 30°, 35°, and 40° of knee extension, contact area was significantly different. Contact area and centroid locations were insensitive to rotational and translational perturbations. Conclusion This study is a first step towards unfolding the biomechanical pathways to anterior patellofemoral pain and OA using dynamic, in vivo, and accurate methodologies. The database provides crucial data for future studies and for validation of, or as an input to, computational models. PMID:24012620

Research Advances on Radiation Transfer Modeling and Inversion for Multi-scale Land Surface Remote Sensing

NASA Astrophysics Data System (ADS)

Liu, Q.; Li, J.; Du, Y.; Wen, J.; Zhong, B.; Wang, K.

2011-12-01

As the remote sensing data accumulating, it is a challenge and significant issue how to generate high accurate and consistent land surface parameter product from the multi source remote observation and the radiation transfer modeling and inversion methodology are the theoretical bases. In this paper, recent research advances and unresolved issues are presented. At first, after a general overview, recent research advances on multi-scale remote sensing radiation transfer modeling are presented, including leaf spectrum model, vegetation canopy BRDF models, directional thermal infrared emission models, rugged mountains area radiation models, and kernel driven models etc. Then, new methodologies on land surface parameters inversion based on multi-source remote sensing data are proposed, taking the land surface Albedo, leaf area index, temperature/emissivity, and surface net radiation as examples. A new synthetic land surface parameter quantitative remote sensing product generation system is suggested and the software system prototype will be demonstrated. At last, multi-scale field experiment campaigns, such as the field campaigns in Gansu and Beijing, China are introduced briefly. The ground based, tower based, and airborne multi-angular measurement system have been built to measure the directional reflectance, emission and scattering characteristics from visible, near infrared, thermal infrared and microwave bands for model validation and calibration. The remote sensing pixel scale "true value" measurement strategy have been designed to gain the ground "true value" of LST, ALBEDO, LAI, soil moisture and ET etc. at 1-km2 for remote sensing product validation.

Risk Based Inspection Methodology and Software Applied to Atmospheric Storage Tanks

NASA Astrophysics Data System (ADS)

Topalis, P.; Korneliussen, G.; Hermanrud, J.; Steo, Y.

2012-05-01

A new risk-based inspection (RBI) methodology and software is presented in this paper. The objective of this work is to allow management of the inspections of atmospheric storage tanks in the most efficient way, while, at the same time, accident risks are minimized. The software has been built on the new risk framework architecture, a generic platform facilitating efficient and integrated development of software applications using risk models. The framework includes a library of risk models and the user interface is automatically produced on the basis of editable schemas. This risk-framework-based RBI tool has been applied in the context of RBI for above-ground atmospheric storage tanks (AST) but it has been designed with the objective of being generic enough to allow extension to the process plants in general. This RBI methodology is an evolution of an approach and mathematical models developed for Det Norske Veritas (DNV) and the American Petroleum Institute (API). The methodology assesses damage mechanism potential, degradation rates, probability of failure (PoF), consequence of failure (CoF) in terms of environmental damage and financial loss, risk and inspection intervals and techniques. The scope includes assessment of the tank floor for soil-side external corrosion and product-side internal corrosion and the tank shell courses for atmospheric corrosion and internal thinning. It also includes preliminary assessment for brittle fracture and cracking. The data are structured according to an asset hierarchy including Plant, Production Unit, Process Unit, Tag, Part and Inspection levels and the data are inherited / defaulted seamlessly from a higher hierarchy level to a lower level. The user interface includes synchronized hierarchy tree browsing, dynamic editor and grid-view editing and active reports with drill-in capability.

SMOS+RAINFALL: Evaluating the ability of different methodologies to improve rainfall estimations using soil moisture data from SMOS

NASA Astrophysics Data System (ADS)

Pellarin, Thierry; Brocca, Luca; Crow, Wade; Kerr, Yann; Massari, Christian; Román-Cascón, Carlos; Fernández, Diego

2017-04-01

Recent studies have demonstrated the usefulness of soil moisture retrieved from satellite for improving rainfall estimations of satellite based precipitation products (SBPP). The real-time version of these products are known to be biased from the real precipitation observed at the ground. Therefore, the information contained in soil moisture can be used to correct the inaccuracy and uncertainty of these products, since the value and behavior of this soil variable preserve the information of a rain event even for several days. In this work, we take advantage of the soil moisture data from the Soil Moisture and Ocean Salinity (SMOS) satellite, which provides information with a quite appropriate temporal and spatial resolution for correcting rainfall events. Specifically, we test and compare the ability of three different methodologies for this aim: 1) SM2RAIN, which directly relate changes in soil moisture to rainfall quantities; 2) The LMAA methodology, which is based on the assimilation of soil moisture in two models of different complexity (see EGU2017-5324 in this same session); 3) The SMART method, based on the assimilation of soil moisture in a simple hydrological model with a different assimilation/modelling technique. The results are tested for 6 years over 10 sites around the world with different features (land surface, rainfall climatology, orography complexity, etc.). These preliminary and promising results are shown here for the first time to the scientific community, as also the observed limitations of the different methodologies. Specific remarks on the technical configurations, filtering/smoothing of SMOS soil moisture or re-scaling techniques are also provided from the results of different sensitivity experiments.

An implementation framework for wastewater treatment models requiring a minimum programming expertise.

PubMed

Rodríguez, J; Premier, G C; Dinsdale, R; Guwy, A J

2009-01-01

Mathematical modelling in environmental biotechnology has been a traditionally difficult resource to access for researchers and students without programming expertise. The great degree of flexibility required from model implementation platforms to be suitable for research applications restricts their use to programming expert users. More user friendly software packages however do not normally incorporate the necessary flexibility for most research applications. This work presents a methodology based on Excel and Matlab-Simulink for both flexible and accessible implementation of mathematical models by researchers with and without programming expertise. The models are almost fully defined in an Excel file in which the names and values of the state variables and parameters are easily created. This information is automatically processed in Matlab to create the model structure and almost immediate model simulation, after only a minimum Matlab code definition, is possible. The framework proposed also provides programming expert researchers with a highly flexible and modifiable platform on which to base more complex model implementations. The method takes advantage of structural generalities in most mathematical models of environmental bioprocesses while enabling the integration of advanced elements (e.g. heuristic functions, correlations). The methodology has already been successfully used in a number of research studies.

Students' and teachers' perceptions: initial achievements of a Project-Based Engineering School

NASA Astrophysics Data System (ADS)

Terrón-López, María-José; Velasco-Quintana, Paloma-Julia; García-García, María-José; Ocampo, Jared R.

2017-11-01

A unified academic model based on the project-based learning (PBL) methodology was implemented, in the 2012-2013 period, in the School of Engineering at Universidad Europea de Madrid. The purpose of this paper is to explore whether teachers and students participating in the capstone projects feel that the objectives for which this methodology was designed for are being achieved. The data were collected through interviews to participants at the end of the PBL experience. The results are encouraging, as students seem to be more motivated, and they say that they are experiencing deeper learning, and have developed key competitive skills required for their professional lives. Findings also suggest that teachers face positively the PBL as a learning approach since they perceive that students obtain a deeper learning, develop transversal skills with the projects and are more engaged with their studies. Implications and recommendations for the future of the model are also discussed.

Teaching and assessing procedural skills using simulation: metrics and methodology.

PubMed

Lammers, Richard L; Davenport, Moira; Korley, Frederick; Griswold-Theodorson, Sharon; Fitch, Michael T; Narang, Aneesh T; Evans, Leigh V; Gross, Amy; Rodriguez, Elliot; Dodge, Kelly L; Hamann, Cara J; Robey, Walter C

2008-11-01

Simulation allows educators to develop learner-focused training and outcomes-based assessments. However, the effectiveness and validity of simulation-based training in emergency medicine (EM) requires further investigation. Teaching and testing technical skills require methods and assessment instruments that are somewhat different than those used for cognitive or team skills. Drawing from work published by other medical disciplines as well as educational, behavioral, and human factors research, the authors developed six research themes: measurement of procedural skills; development of performance standards; assessment and validation of training methods, simulator models, and assessment tools; optimization of training methods; transfer of skills learned on simulator models to patients; and prevention of skill decay over time. The article reviews relevant and established educational research methodologies and identifies gaps in our knowledge of how physicians learn procedures. The authors present questions requiring further research that, once answered, will advance understanding of simulation-based procedural training and assessment in EM.

CNN based approach for activity recognition using a wrist-worn accelerometer.

PubMed

Panwar, Madhuri; Dyuthi, S Ram; Chandra Prakash, K; Biswas, Dwaipayan; Acharyya, Amit; Maharatna, Koushik; Gautam, Arvind; Naik, Ganesh R

2017-07-01

In recent years, significant advancements have taken place in human activity recognition using various machine learning approaches. However, feature engineering have dominated conventional methods involving the difficult process of optimal feature selection. This problem has been mitigated by using a novel methodology based on deep learning framework which automatically extracts the useful features and reduces the computational cost. As a proof of concept, we have attempted to design a generalized model for recognition of three fundamental movements of the human forearm performed in daily life where data is collected from four different subjects using a single wrist worn accelerometer sensor. The validation of the proposed model is done with different pre-processing and noisy data condition which is evaluated using three possible methods. The results show that our proposed methodology achieves an average recognition rate of 99.8% as opposed to conventional methods based on K-means clustering, linear discriminant analysis and support vector machine.

Improving the spatial and temporal resolution with quantification of uncertainty and errors in earth observation data sets using Data Interpolating Empirical Orthogonal Functions methodology

NASA Astrophysics Data System (ADS)

El Serafy, Ghada; Gaytan Aguilar, Sandra; Ziemba, Alexander

2016-04-01

There is an increasing use of process-based models in the investigation of ecological systems and scenario predictions. The accuracy and quality of these models are improved when run with high spatial and temporal resolution data sets. However, ecological data can often be difficult to collect which manifests itself through irregularities in the spatial and temporal domain of these data sets. Through the use of Data INterpolating Empirical Orthogonal Functions(DINEOF) methodology, earth observation products can be improved to have full spatial coverage within the desired domain as well as increased temporal resolution to daily and weekly time step, those frequently required by process-based models[1]. The DINEOF methodology results in a degree of error being affixed to the refined data product. In order to determine the degree of error introduced through this process, the suspended particulate matter and chlorophyll-a data from MERIS is used with DINEOF to produce high resolution products for the Wadden Sea. These new data sets are then compared with in-situ and other data sources to determine the error. Also, artificial cloud cover scenarios are conducted in order to substantiate the findings from MERIS data experiments. Secondly, the accuracy of DINEOF is explored to evaluate the variance of the methodology. The degree of accuracy is combined with the overall error produced by the methodology and reported in an assessment of the quality of DINEOF when applied to resolution refinement of chlorophyll-a and suspended particulate matter in the Wadden Sea. References [1] Sirjacobs, D.; Alvera-Azcárate, A.; Barth, A.; Lacroix, G.; Park, Y.; Nechad, B.; Ruddick, K.G.; Beckers, J.-M. (2011). Cloud filling of ocean colour and sea surface temperature remote sensing products over the Southern North Sea by the Data Interpolating Empirical Orthogonal Functions methodology. J. Sea Res. 65(1): 114-130. Dx.doi.org/10.1016/j.seares.2010.08.002

Development of an Aeroelastic Modeling Capability for Transient Nozzle Side Load Analysis

NASA Technical Reports Server (NTRS)

Wang, Ten-See; Zhao, Xiang; Zhang, Sijun; Chen, Yen-Sen

2013-01-01

Lateral nozzle forces are known to cause severe structural damage to any new rocket engine in development during test. While three-dimensional, transient, turbulent, chemically reacting computational fluid dynamics methodology has been demonstrated to capture major side load physics with rigid nozzles, hot-fire tests often show nozzle structure deformation during major side load events, leading to structural damages if structural strengthening measures were not taken. The modeling picture is incomplete without the capability to address the two-way responses between the structure and fluid. The objective of this study is to develop a coupled aeroelastic modeling capability by implementing the necessary structural dynamics component into an anchored computational fluid dynamics methodology. The computational fluid dynamics component is based on an unstructured-grid, pressure-based computational fluid dynamics formulation, while the computational structural dynamics component is developed in the framework of modal analysis. Transient aeroelastic nozzle startup analyses of the Block I Space Shuttle Main Engine at sea level were performed. The computed results from the aeroelastic nozzle modeling are presented.

Validation of the thermal challenge problem using Bayesian Belief Networks.

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

McFarland, John; Swiler, Laura Painton

The thermal challenge problem has been developed at Sandia National Laboratories as a testbed for demonstrating various types of validation approaches and prediction methods. This report discusses one particular methodology to assess the validity of a computational model given experimental data. This methodology is based on Bayesian Belief Networks (BBNs) and can incorporate uncertainty in experimental measurements, in physical quantities, and model uncertainties. The approach uses the prior and posterior distributions of model output to compute a validation metric based on Bayesian hypothesis testing (a Bayes' factor). This report discusses various aspects of the BBN, specifically in the context ofmore » the thermal challenge problem. A BBN is developed for a given set of experimental data in a particular experimental configuration. The development of the BBN and the method for ''solving'' the BBN to develop the posterior distribution of model output through Monte Carlo Markov Chain sampling is discussed in detail. The use of the BBN to compute a Bayes' factor is demonstrated.« less

Appraising Healthcare Delivery Provision: A Framework to Model Business Processes.

PubMed

Luzi, Daniela; Pecoraro, Fabrizio; Tamburis, Oscar

2017-01-01

Children are dependent on a reliable healthcare system, especially for the delivery of care which crosses the primary/secondary care boundary. A methodology based on UML has been developed to capture and single out meaningful parts of the child healthcare pathways in order to facilitate comparison among 30 EU countries within the MOCHA project. A first application of this methodology has been reported considering asthma management as an example.

GPR image analysis to locate water leaks from buried pipes by applying variance filters

NASA Astrophysics Data System (ADS)

Ocaña-Levario, Silvia J.; Carreño-Alvarado, Elizabeth P.; Ayala-Cabrera, David; Izquierdo, Joaquín

2018-05-01

Nowadays, there is growing interest in controlling and reducing the amount of water lost through leakage in water supply systems (WSSs). Leakage is, in fact, one of the biggest problems faced by the managers of these utilities. This work addresses the problem of leakage in WSSs by using GPR (Ground Penetrating Radar) as a non-destructive method. The main objective is to identify and extract features from GPR images such as leaks and components in a controlled laboratory condition by a methodology based on second order statistical parameters and, using the obtained features, to create 3D models that allows quick visualization of components and leaks in WSSs from GPR image analysis and subsequent interpretation. This methodology has been used before in other fields and provided promising results. The results obtained with the proposed methodology are presented, analyzed, interpreted and compared with the results obtained by using a well-established multi-agent based methodology. These results show that the variance filter is capable of highlighting the characteristics of components and anomalies, in an intuitive manner, which can be identified by non-highly qualified personnel, using the 3D models we develop. This research intends to pave the way towards future intelligent detection systems that enable the automatic detection of leaks in WSSs.

Closed-loop, pilot/vehicle analysis of the approach and landing task

NASA Technical Reports Server (NTRS)

Schmidt, D. K.; Anderson, M. R.

1985-01-01

Optimal-control-theoretic modeling and frequency-domain analysis is the methodology proposed to evaluate analytically the handling qualities of higher-order manually controlled dynamic systems. Fundamental to the methodology is evaluating the interplay between pilot workload and closed-loop pilot/vehicle performance and stability robustness. The model-based metric for pilot workload is the required pilot phase compensation. Pilot/vehicle performance and loop stability is then evaluated using frequency-domain techniques. When these techniques were applied to the flight-test data for thirty-two highly-augmented fighter configurations, strong correlation was obtained between the analytical and experimental results.

Predicting operator workload during system design

NASA Technical Reports Server (NTRS)

Aldrich, Theodore B.; Szabo, Sandra M.

1988-01-01

A workload prediction methodology was developed in response to the need to measure workloads associated with operation of advanced aircraft. The application of the methodology will involve: (1) conducting mission/task analyses of critical mission segments and assigning estimates of workload for the sensory, cognitive, and psychomotor workload components of each task identified; (2) developing computer-based workload prediction models using the task analysis data; and (3) exercising the computer models to produce predictions of crew workload under varying automation and/or crew configurations. Critical issues include reliability and validity of workload predictors and selection of appropriate criterion measures.

MoPCoM Methodology: Focus on Models of Computation

NASA Astrophysics Data System (ADS)

Koudri, Ali; Champeau, Joël; Le Lann, Jean-Christophe; Leilde, Vincent

Today, developments of Real Time Embedded Systems have to face new challenges. On the one hand, Time-To-Market constraints require a reliable development process allowing quick design space exploration. On the other hand, rapidly developing technology, as stated by Moore's law, requires techniques to handle the resulting productivity gap. In a previous paper, we have presented our Model Based Engineering methodology addressing those issues. In this paper, we make a focus on Models of Computation design and analysis. We illustrate our approach on a Cognitive Radio System development implemented on an FPGA. This work is part of the MoPCoM research project gathering academic and industrial organizations (http://www.mopcom.fr).

Model-Based Experimental Development of Passive Compliant Robot Legs from Fiberglass Composites

PubMed Central

Lin, Shang-Chang; Hu, Chia-Jui; Lin, Pei-Chun

2015-01-01

We report on the methodology of developing compliant, half-circular, and composite robot legs with designable stiffness. First, force-displacement experiments on flat cantilever composites made by one or multifiberglass cloths are executed. By mapping the cantilever mechanics to the virtual spring model, the equivalent elastic moduli of the composites can be derived. Next, by using the model that links the curved beam mechanics back to the virtual spring, the resultant stiffness of the composite in a half-circular shape can be estimated without going through intensive experimental tryouts. The overall methodology has been experimentally validated, and the fabricated composites were used on a hexapod robot to perform walking and leaping behaviors. PMID:27065748

Aeroservoelastic wind-tunnel investigations using the Active Flexible Wing Model: Status and recent accomplishments

NASA Technical Reports Server (NTRS)

Noll, Thomas E.; Perry, Boyd, III; Tiffany, Sherwood H.; Cole, Stanley R.; Buttrill, Carey S.; Adams, William M., Jr.; Houck, Jacob A.; Srinathkumar, S.; Mukhopadhyay, Vivek; Pototzky, Anthony S.

1989-01-01

The status of the joint NASA/Rockwell Active Flexible Wing Wind-Tunnel Test Program is described. The objectives are to develop and validate the analysis, design, and test methodologies required to apply multifunction active control technology for improving aircraft performance and stability. Major tasks include designing digital multi-input/multi-output flutter-suppression and rolling-maneuver-load alleviation concepts for a flexible full-span wind-tunnel model, obtaining an experimental data base for the basic model and each control concept and providing comparisons between experimental and analytical results to validate the methodologies. The opportunity is provided to improve real-time simulation techniques and to gain practical experience with digital control law implementation procedures.

Health economic assessment: a methodological primer.

PubMed

Simoens, Steven

2009-12-01

This review article aims to provide an introduction to the methodology of health economic assessment of a health technology. Attention is paid to defining the fundamental concepts and terms that are relevant to health economic assessments. The article describes the methodology underlying a cost study (identification, measurement and valuation of resource use, calculation of costs), an economic evaluation (type of economic evaluation, the cost-effectiveness plane, trial- and model-based economic evaluation, discounting, sensitivity analysis, incremental analysis), and a budget impact analysis. Key references are provided for those readers who wish a more advanced understanding of health economic assessments.

Health Economic Assessment: A Methodological Primer

PubMed Central

Simoens, Steven

2009-01-01

This review article aims to provide an introduction to the methodology of health economic assessment of a health technology. Attention is paid to defining the fundamental concepts and terms that are relevant to health economic assessments. The article describes the methodology underlying a cost study (identification, measurement and valuation of resource use, calculation of costs), an economic evaluation (type of economic evaluation, the cost-effectiveness plane, trial- and model-based economic evaluation, discounting, sensitivity analysis, incremental analysis), and a budget impact analysis. Key references are provided for those readers who wish a more advanced understanding of health economic assessments. PMID:20049237

[Definition of "Safety and Hygiene Packages" as a management model for the Hospital Hygiene Service (HHS)].

PubMed

Raponi, Matteo; Damiani, Gianfranco; Vincenti, Sara; Wachocka, Malgorzata; Boninti, Federica; Bruno, Stefania; Quaranta, Gianluigi; Moscato, Umberto; Boccia, Stefania; Ficarra, Maria Giovanna; Specchia, Maria Lucia; Posteraro, Brunella; Berloco, Filippo; Celani, Fabrizio; Ricciardi, Walter; Laurenti, Patrizia

2014-01-01

The purpose of this research is to identify and formalize the Hospital Hygiene Service activities and products, evaluating them in a cost accounting management view. The ultimate aim, is to evaluate the financial adverse events prevention impact, in an Hospital Hygiene Service management. A three step methodology based on affinity grouping activities, was employed. This methodology led us to identify 4 action areas, with 23 related productive processes, and 86 available safety packages. Owing to this new methodology, we was able to implement a systematic evaluation of the furnished services.

Self-optimisation and model-based design of experiments for developing a C-H activation flow process.

PubMed

Echtermeyer, Alexander; Amar, Yehia; Zakrzewski, Jacek; Lapkin, Alexei

2017-01-01

A recently described C(sp 3 )-H activation reaction to synthesise aziridines was used as a model reaction to demonstrate the methodology of developing a process model using model-based design of experiments (MBDoE) and self-optimisation approaches in flow. The two approaches are compared in terms of experimental efficiency. The self-optimisation approach required the least number of experiments to reach the specified objectives of cost and product yield, whereas the MBDoE approach enabled a rapid generation of a process model.

Analysis of decision fusion algorithms in handling uncertainties for integrated health monitoring systems

NASA Astrophysics Data System (ADS)

Zein-Sabatto, Saleh; Mikhail, Maged; Bodruzzaman, Mohammad; DeSimio, Martin; Derriso, Mark; Behbahani, Alireza

2012-06-01

It has been widely accepted that data fusion and information fusion methods can improve the accuracy and robustness of decision-making in structural health monitoring systems. It is arguably true nonetheless, that decision-level is equally beneficial when applied to integrated health monitoring systems. Several decisions at low-levels of abstraction may be produced by different decision-makers; however, decision-level fusion is required at the final stage of the process to provide accurate assessment about the health of the monitored system as a whole. An example of such integrated systems with complex decision-making scenarios is the integrated health monitoring of aircraft. Thorough understanding of the characteristics of the decision-fusion methodologies is a crucial step for successful implementation of such decision-fusion systems. In this paper, we have presented the major information fusion methodologies reported in the literature, i.e., probabilistic, evidential, and artificial intelligent based methods. The theoretical basis and characteristics of these methodologies are explained and their performances are analyzed. Second, candidate methods from the above fusion methodologies, i.e., Bayesian, Dempster-Shafer, and fuzzy logic algorithms are selected and their applications are extended to decisions fusion. Finally, fusion algorithms are developed based on the selected fusion methods and their performance are tested on decisions generated from synthetic data and from experimental data. Also in this paper, a modeling methodology, i.e. cloud model, for generating synthetic decisions is presented and used. Using the cloud model, both types of uncertainties; randomness and fuzziness, involved in real decision-making are modeled. Synthetic decisions are generated with an unbiased process and varying interaction complexities among decisions to provide for fair performance comparison of the selected decision-fusion algorithms. For verification purposes, implementation results of the developed fusion algorithms on structural health monitoring data collected from experimental tests are reported in this paper.

A Novel Multiscale Physics Based Progressive Failure Methodology for Laminated Composite Structures

NASA Technical Reports Server (NTRS)

Pineda, Evan J.; Waas, Anthony M.; Bednarcyk, Brett A.; Collier, Craig S.; Yarrington, Phillip W.

2008-01-01

A variable fidelity, multiscale, physics based finite element procedure for predicting progressive damage and failure of laminated continuous fiber reinforced composites is introduced. At every integration point in a finite element model, progressive damage is accounted for at the lamina-level using thermodynamically based Schapery Theory. Separate failure criteria are applied at either the global-scale or the microscale in two different FEM models. A micromechanics model, the Generalized Method of Cells, is used to evaluate failure criteria at the micro-level. The stress-strain behavior and observed failure mechanisms are compared with experimental results for both models.

Assessment of Professional Development for Teachers in the Vocational Education and Training Sector: An Examination of the Concerns Based Adoption Model

ERIC Educational Resources Information Center

Saunders, Rebecca

2012-01-01

The purpose of this article is to describe the use of the Concerns Based Adoption Model (Hall & Hord, 2006) as a conceptual lens and practical methodology for professional development program assessment in the vocational education and training (VET) sector. In this sequential mixed-methods study, findings from the first two phases (two of…

Risk assessment methodology applied to counter IED research & development portfolio prioritization

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

Shevitz, Daniel W; O' Brien, David A; Zerkle, David K

2009-01-01

In an effort to protect the United States from the ever increasing threat of domestic terrorism, the Department of Homeland Security, Science and Technology Directorate (DHS S&T), has significantly increased research activities to counter the terrorist use of explosives. More over, DHS S&T has established a robust Counter-Improvised Explosive Device (C-IED) Program to Deter, Predict, Detect, Defeat, and Mitigate this imminent threat to the Homeland. The DHS S&T portfolio is complicated and changing. In order to provide the ''best answer'' for the available resources, DHS S&T would like some ''risk based'' process for making funding decisions. There is a definitemore » need for a methodology to compare very different types of technologies on a common basis. A methodology was developed that allows users to evaluate a new ''quad chart'' and rank it, compared to all other quad charts across S&T divisions. It couples a logic model with an evidential reasoning model using an Excel spreadsheet containing weights of the subjective merits of different technologies. The methodology produces an Excel spreadsheet containing the aggregate rankings of the different technologies. It uses Extensible Logic Modeling (ELM) for logic models combined with LANL software called INFTree for evidential reasoning.« less

Agent-Based Simulation of Learning Dissemination in a Project-Based Learning Context Considering the Human Aspects

ERIC Educational Resources Information Center

Seman, Laio Oriel; Hausmann, Romeu; Bezerra, Eduardo Augusto

2018-01-01

Contribution: This paper presents the "PBL classroom model," an agent-based simulation (ABS) that allows testing of several scenarios of a project-based learning (PBL) application by considering different levels of soft-skills, and students' perception of the methodology. Background: While the community has made great advances in…

Evidence-Based Administration for Decision Making in the Framework of Knowledge Strategic Management

ERIC Educational Resources Information Center

Del Junco, Julio Garcia; Zaballa, Rafael De Reyna; de Perea, Juan Garcia Alvarez

2010-01-01

Purpose: This paper seeks to present a model based on evidence-based administration (EBA), which aims to facilitate the creation, transformation and diffusion of knowledge in learning organizations. Design/methodology/approach: A theoretical framework is proposed based on EBA and the case method. Accordingly, an empirical study was carried out in…

Measurement-based reliability prediction methodology. M.S. Thesis

NASA Technical Reports Server (NTRS)

Linn, Linda Shen

1991-01-01

In the past, analytical and measurement based models were developed to characterize computer system behavior. An open issue is how these models can be used, if at all, for system design improvement. The issue is addressed here. A combined statistical/analytical approach to use measurements from one environment to model the system failure behavior in a new environment is proposed. A comparison of the predicted results with the actual data from the new environment shows a close correspondence.

Using artificial neural networks to model aluminium based sheet forming processes and tools details

NASA Astrophysics Data System (ADS)

Mekras, N.

2017-09-01

In this paper, a methodology and a software system will be presented concerning the use of Artificial Neural Networks (ANNs) for modeling aluminium based sheet forming processes. ANNs models’ creation is based on the training of the ANNs using experimental, trial and historical data records of processes’ inputs and outputs. ANNs models are useful in cases that processes’ mathematical models are not accurate enough, are not well defined or are missing e.g. in cases of complex product shapes, new material alloys, new process requirements, micro-scale products, etc. Usually, after the design and modeling of the forming tools (die, punch, etc.) and before mass production, a set of trials takes place at the shop floor for finalizing processes and tools details concerning e.g. tools’ minimum radii, die/punch clearance, press speed, process temperature, etc. and in relation with the material type, the sheet thickness and the quality achieved from the trials. Using data from the shop floor trials and forming theory data, ANNs models can be trained and created, and can be used to estimate processes and tools final details, hence supporting efficient set-up of processes and tools before mass production starts. The proposed ANNs methodology and the respective software system are implemented within the EU H2020 project LoCoMaTech for the aluminium-based sheet forming process HFQ (solution Heat treatment, cold die Forming and Quenching).

Uncertainty Representation and Interpretation in Model-Based Prognostics Algorithms Based on Kalman Filter Estimation

NASA Technical Reports Server (NTRS)

Galvan, Jose Ramon; Saxena, Abhinav; Goebel, Kai Frank

2012-01-01

This article discusses several aspects of uncertainty representation and management for model-based prognostics methodologies based on our experience with Kalman Filters when applied to prognostics for electronics components. In particular, it explores the implications of modeling remaining useful life prediction as a stochastic process, and how it relates to uncertainty representation, management and the role of prognostics in decision-making. A distinction between the interpretations of estimated remaining useful life probability density function is explained and a cautionary argument is provided against mixing interpretations for two while considering prognostics in making critical decisions.

What's in a Model? Issues in the Use of Simulation Models to Analyze Student Understanding: A Reaction to Ohlsson, Ernst, and Rees.

ERIC Educational Resources Information Center

Schoenfeld, Alan H.

1992-01-01

Reacts to Ohlsson, Ernst, and Rees' paper by initially discussing the costs of methodology that utilizes artificial intelligence (AI) to model cognitive processes. Raises three concerns with the paper: insufficient clarification of the meaning of conceptual versus procedural understanding of base-10 subtraction; realism of the learning model; and…

Housing Value Projection Model Related to Educational Planning: The Feasibility of a New Methodology. Final Report.

ERIC Educational Resources Information Center

Helbock, Richard W.; Marker, Gordon

This study concerns the feasibility of a Markov chain model for projecting housing values and racial mixes. Such projections could be used in planning the layout of school districts to achieve desired levels of socioeconomic heterogeneity. Based upon the concepts and assumptions underlying a Markov chain model, it is concluded that such a model is…

A Methodology for Cybercraft Requirement Definition and Initial System Design

DTIC Science & Technology

2008-06-01

the software development concepts of the SDLC , requirements, use cases and domain modeling . It ...collectively as Software Development 5 Life Cycle ( SDLC ) models . While there are numerous models that fit under the SDLC definition, all are based on... developed that provided expanded understanding of the domain, it is necessary to either update an existing domain model or create another domain

Using experimental data to reduce the single-building sigma of fragility curves: case study of the BRD tower in Bucharest, Romania

NASA Astrophysics Data System (ADS)

Perrault, Matthieu; Gueguen, Philippe; Aldea, Alexandru; Demetriu, Sorin

2013-12-01

The lack of knowledge concerning modelling existing buildings leads to signifiant variability in fragility curves for single or grouped existing buildings. This study aims to investigate the uncertainties of fragility curves, with special consideration of the single-building sigma. Experimental data and simplified models are applied to the BRD tower in Bucharest, Romania, a RC building with permanent instrumentation. A three-step methodology is applied: (1) adjustment of a linear MDOF model for experimental modal analysis using a Timoshenko beam model and based on Anderson's criteria, (2) computation of the structure's response to a large set of accelerograms simulated by SIMQKE software, considering twelve ground motion parameters as intensity measurements (IM), and (3) construction of the fragility curves by comparing numerical interstory drift with the threshold criteria provided by the Hazus methodology for the slight damage state. By introducing experimental data into the model, uncertainty is reduced to 0.02 considering S d ( f 1) as seismic intensity IM and uncertainty related to the model is assessed at 0.03. These values must be compared with the total uncertainty value of around 0.7 provided by the Hazus methodology.

Scalable tuning of building models to hourly data

DOE PAGES

Garrett, Aaron; New, Joshua Ryan

2015-03-31

Energy models of existing buildings are unreliable unless calibrated so they correlate well with actual energy usage. Manual tuning requires a skilled professional, is prohibitively expensive for small projects, imperfect, non-repeatable, non-transferable, and not scalable to the dozens of sensor channels that smart meters, smart appliances, and cheap/ubiquitous sensors are beginning to make available today. A scalable, automated methodology is needed to quickly and intelligently calibrate building energy models to all available data, increase the usefulness of those models, and facilitate speed-and-scale penetration of simulation-based capabilities into the marketplace for actualized energy savings. The "Autotune'' project is a novel, model-agnosticmore » methodology which leverages supercomputing, large simulation ensembles, and big data mining with multiple machine learning algorithms to allow automatic calibration of simulations that match measured experimental data in a way that is deployable on commodity hardware. This paper shares several methodologies employed to reduce the combinatorial complexity to a computationally tractable search problem for hundreds of input parameters. Furthermore, accuracy metrics are provided which quantify model error to measured data for either monthly or hourly electrical usage from a highly-instrumented, emulated-occupancy research home.« less

A Novel Methodology for Improving Plant Pest Surveillance in Vineyards and Crops Using UAV-Based Hyperspectral and Spatial Data

PubMed Central

Vanegas, Fernando; Weiss, John; Gonzalez, Felipe

2018-01-01

Recent advances in remote sensed imagery and geospatial image processing using unmanned aerial vehicles (UAVs) have enabled the rapid and ongoing development of monitoring tools for crop management and the detection/surveillance of insect pests. This paper describes a (UAV) remote sensing-based methodology to increase the efficiency of existing surveillance practices (human inspectors and insect traps) for detecting pest infestations (e.g., grape phylloxera in vineyards). The methodology uses a UAV integrated with advanced digital hyperspectral, multispectral, and RGB sensors. We implemented the methodology for the development of a predictive model for phylloxera detection. In this method, we explore the combination of airborne RGB, multispectral, and hyperspectral imagery with ground-based data at two separate time periods and under different levels of phylloxera infestation. We describe the technology used—the sensors, the UAV, and the flight operations—the processing workflow of the datasets from each imagery type, and the methods for combining multiple airborne with ground-based datasets. Finally, we present relevant results of correlation between the different processed datasets. The objective of this research is to develop a novel methodology for collecting, processing, analysing and integrating multispectral, hyperspectral, ground and spatial data to remote sense different variables in different applications, such as, in this case, plant pest surveillance. The development of such methodology would provide researchers, agronomists, and UAV practitioners reliable data collection protocols and methods to achieve faster processing techniques and integrate multiple sources of data in diverse remote sensing applications. PMID:29342101

Designing an activity-based costing model for a non-admitted prisoner healthcare setting.

PubMed

Cai, Xiao; Moore, Elizabeth; McNamara, Martin

2013-09-01

To design and deliver an activity-based costing model within a non-admitted prisoner healthcare setting. Key phases from the NSW Health clinical redesign methodology were utilised: diagnostic, solution design and implementation. The diagnostic phase utilised a range of strategies to identify issues requiring attention in the development of the costing model. The solution design phase conceptualised distinct 'building blocks' of activity and cost based on the speciality of clinicians providing care. These building blocks enabled the classification of activity and comparisons of costs between similar facilities. The implementation phase validated the model. The project generated an activity-based costing model based on actual activity performed, gained acceptability among clinicians and managers, and provided the basis for ongoing efficiency and benchmarking efforts.

Parametric Optimization of Thermoelectric Generators for Waste Heat Recovery

NASA Astrophysics Data System (ADS)

Huang, Shouyuan; Xu, Xianfan

2016-10-01

This paper presents a methodology for design optimization of thermoelectric-based waste heat recovery systems called thermoelectric generators (TEGs). The aim is to maximize the power output from thermoelectrics which are used as add-on modules to an existing gas-phase heat exchanger, without negative impacts, e.g., maintaining a minimum heat dissipation rate from the hot side. A numerical model is proposed for TEG coupled heat transfer and electrical power output. This finite-volume-based model simulates different types of heat exchangers, i.e., counter-flow and cross-flow, for TEGs. Multiple-filled skutterudites and bismuth-telluride-based thermoelectric modules (TEMs) are applied, respectively, in higher and lower temperature regions. The response surface methodology is implemented to determine the optimized TEG size along and across the flow direction and the height of thermoelectric couple legs, and to analyze their covariance and relative sensitivity. A genetic algorithm is employed to verify the globality of the optimum. The presented method will be generally useful for optimizing heat-exchanger-based TEG performance.

An Agent-Based Modeling Framework and Application for the Generic Nuclear Fuel Cycle

NASA Astrophysics Data System (ADS)

Gidden, Matthew J.

Key components of a novel methodology and implementation of an agent-based, dynamic nuclear fuel cycle simulator, Cyclus , are presented. The nuclear fuel cycle is a complex, physics-dependent supply chain. To date, existing dynamic simulators have not treated constrained fuel supply, time-dependent, isotopic-quality based demand, or fuel fungibility particularly well. Utilizing an agent-based methodology that incorporates sophisticated graph theory and operations research techniques can overcome these deficiencies. This work describes a simulation kernel and agents that interact with it, highlighting the Dynamic Resource Exchange (DRE), the supply-demand framework at the heart of the kernel. The key agent-DRE interaction mechanisms are described, which enable complex entity interaction through the use of physics and socio-economic models. The translation of an exchange instance to a variant of the Multicommodity Transportation Problem, which can be solved feasibly or optimally, follows. An extensive investigation of solution performance and fidelity is then presented. Finally, recommendations for future users of Cyclus and the DRE are provided.

Rain/No-Rain Identification from Bispectral Satellite Information using Deep Neural Networks

NASA Astrophysics Data System (ADS)

Tao, Y.

2016-12-01

Satellite-based precipitation estimation products have the advantage of high resolution and global coverage. However, they still suffer from insufficient accuracy. To accurately estimate precipitation from satellite data, there are two most important aspects: sufficient precipitation information in the satellite information and proper methodologies to extract such information effectively. This study applies the state-of-the-art machine learning methodologies to bispectral satellite information for Rain/No-Rain detection. Specifically, we use deep neural networks to extract features from infrared and water vapor channels and connect it to precipitation identification. To evaluate the effectiveness of the methodology, we first applies it to the infrared data only (Model DL-IR only), the most commonly used inputs for satellite-based precipitation estimation. Then we incorporates water vapor data (Model DL-IR + WV) to further improve the prediction performance. Radar stage IV dataset is used as ground measurement for parameter calibration. The operational product, Precipitation Estimation from Remotely Sensed Information Using Artificial Neural Networks Cloud Classification System (PERSIANN-CCS), is used as a reference to compare the performance of both models in both winter and summer seasons.The experiments show significant improvement for both models in precipitation identification. The overall performance gains in the Critical Success Index (CSI) are 21.60% and 43.66% over the verification periods for Model DL-IR only and Model DL-IR+WV model compared to PERSIANN-CCS, respectively. Moreover, specific case studies show that the water vapor channel information and the deep neural networks effectively help recover a large number of missing precipitation pixels under warm clouds while reducing false alarms under cold clouds.

Simulation of nitrate reduction in groundwater - An upscaling approach from small catchments to the Baltic Sea basin

NASA Astrophysics Data System (ADS)

Hansen, A. L.; Donnelly, C.; Refsgaard, J. C.; Karlsson, I. B.

2018-01-01

This paper describes a modeling approach proposed to simulate the impact of local-scale, spatially targeted N-mitigation measures for the Baltic Sea Basin. Spatially targeted N-regulations aim at exploiting the considerable spatial differences in the natural N-reduction taking place in groundwater and surface water. While such measures can be simulated using local-scale physically-based catchment models, use of such detailed models for the 1.8 million km2 Baltic Sea basin is not feasible due to constraints on input data and computing power. Large-scale models that are able to simulate the Baltic Sea basin, on the other hand, do not have adequate spatial resolution to simulate some of the field-scale measures. Our methodology combines knowledge and results from two local-scale physically-based MIKE SHE catchment models, the large-scale and more conceptual E-HYPE model, and auxiliary data in order to enable E-HYPE to simulate how spatially targeted regulation of agricultural practices may affect N-loads to the Baltic Sea. We conclude that the use of E-HYPE with this upscaling methodology enables the simulation of the impact on N-loads of applying a spatially targeted regulation at the Baltic Sea basin scale to the correct order-of-magnitude. The E-HYPE model together with the upscaling methodology therefore provides a sound basis for large-scale policy analysis; however, we do not expect it to be sufficiently accurate to be useful for the detailed design of local-scale measures.

Predicting the graft survival for heart-lung transplantation patients: an integrated data mining methodology.

PubMed

Oztekin, Asil; Delen, Dursun; Kong, Zhenyu James

2009-12-01

Predicting the survival of heart-lung transplant patients has the potential to play a critical role in understanding and improving the matching procedure between the recipient and graft. Although voluminous data related to the transplantation procedures is being collected and stored, only a small subset of the predictive factors has been used in modeling heart-lung transplantation outcomes. The previous studies have mainly focused on applying statistical techniques to a small set of factors selected by the domain-experts in order to reveal the simple linear relationships between the factors and survival. The collection of methods known as 'data mining' offers significant advantages over conventional statistical techniques in dealing with the latter's limitations such as normality assumption of observations, independence of observations from each other, and linearity of the relationship between the observations and the output measure(s). There are statistical methods that overcome these limitations. Yet, they are computationally more expensive and do not provide fast and flexible solutions as do data mining techniques in large datasets. The main objective of this study is to improve the prediction of outcomes following combined heart-lung transplantation by proposing an integrated data-mining methodology. A large and feature-rich dataset (16,604 cases with 283 variables) is used to (1) develop machine learning based predictive models and (2) extract the most important predictive factors. Then, using three different variable selection methods, namely, (i) machine learning methods driven variables-using decision trees, neural networks, logistic regression, (ii) the literature review-based expert-defined variables, and (iii) common sense-based interaction variables, a consolidated set of factors is generated and used to develop Cox regression models for heart-lung graft survival. The predictive models' performance in terms of 10-fold cross-validation accuracy rates for two multi-imputed datasets ranged from 79% to 86% for neural networks, from 78% to 86% for logistic regression, and from 71% to 79% for decision trees. The results indicate that the proposed integrated data mining methodology using Cox hazard models better predicted the graft survival with different variables than the conventional approaches commonly used in the literature. This result is validated by the comparison of the corresponding Gains charts for our proposed methodology and the literature review based Cox results, and by the comparison of Akaike information criteria (AIC) values received from each. Data mining-based methodology proposed in this study reveals that there are undiscovered relationships (i.e. interactions of the existing variables) among the survival-related variables, which helps better predict the survival of the heart-lung transplants. It also brings a different set of variables into the scene to be evaluated by the domain-experts and be considered prior to the organ transplantation.

Moving from Pathology to Possibility: Integrating Strengths-Based Interventions in Child Welfare Provision

ERIC Educational Resources Information Center

Sabalauskas, Kara L.; Ortolani, Charles L.; McCall, Matthew J.

2014-01-01

Child welfare providers are increasingly required to demonstrate that strengths-based, evidence-informed practices are central to their intervention methodology. This case study describes how a large child welfare agency instituted cognitive behavioural therapy (CBT) as the core component of a strength-based practice model with the goal of…

An information-theoretic approach to surrogate-marker evaluation with failure time endpoints.

PubMed

Pryseley, Assam; Tilahun, Abel; Alonso, Ariel; Molenberghs, Geert

2011-04-01

Over the last decades, the evaluation of potential surrogate endpoints in clinical trials has steadily been growing in importance, not only thanks to the availability of ever more potential markers and surrogate endpoints, also because more methodological development has become available. While early work has been devoted, to a large extent, to Gaussian, binary, and longitudinal endpoints, the case of time-to-event endpoints is in need of careful scrutiny as well, owing to the strong presence of such endpoints in oncology and beyond. While work had been done in the past, it was often cumbersome to use such tools in practice, because of the need for fitting copula or frailty models that were further embedded in a hierarchical or two-stage modeling approach. In this paper, we present a methodologically elegant and easy-to-use approach based on information theory. We resolve essential issues, including the quantification of "surrogacy" based on such an approach. Our results are put to the test in a simulation study and are applied to data from clinical trials in oncology. The methodology has been implemented in R.

Modelling soil water retention using support vector machines with genetic algorithm optimisation.

PubMed

Lamorski, Krzysztof; Sławiński, Cezary; Moreno, Felix; Barna, Gyöngyi; Skierucha, Wojciech; Arrue, José L

2014-01-01

This work presents point pedotransfer function (PTF) models of the soil water retention curve. The developed models allowed for estimation of the soil water content for the specified soil water potentials: -0.98, -3.10, -9.81, -31.02, -491.66, and -1554.78 kPa, based on the following soil characteristics: soil granulometric composition, total porosity, and bulk density. Support Vector Machines (SVM) methodology was used for model development. A new methodology for elaboration of retention function models is proposed. Alternative to previous attempts known from literature, the ν-SVM method was used for model development and the results were compared with the formerly used the C-SVM method. For the purpose of models' parameters search, genetic algorithms were used as an optimisation framework. A new form of the aim function used for models parameters search is proposed which allowed for development of models with better prediction capabilities. This new aim function avoids overestimation of models which is typically encountered when root mean squared error is used as an aim function. Elaborated models showed good agreement with measured soil water retention data. Achieved coefficients of determination values were in the range 0.67-0.92. Studies demonstrated usability of ν-SVM methodology together with genetic algorithm optimisation for retention modelling which gave better performing models than other tested approaches.

Virtual Patients and Sensitivity Analysis of the Guyton Model of Blood Pressure Regulation: Towards Individualized Models of Whole-Body Physiology

PubMed Central

Moss, Robert; Grosse, Thibault; Marchant, Ivanny; Lassau, Nathalie; Gueyffier, François; Thomas, S. Randall

2012-01-01

Mathematical models that integrate multi-scale physiological data can offer insight into physiological and pathophysiological function, and may eventually assist in individualized predictive medicine. We present a methodology for performing systematic analyses of multi-parameter interactions in such complex, multi-scale models. Human physiology models are often based on or inspired by Arthur Guyton's whole-body circulatory regulation model. Despite the significance of this model, it has not been the subject of a systematic and comprehensive sensitivity study. Therefore, we use this model as a case study for our methodology. Our analysis of the Guyton model reveals how the multitude of model parameters combine to affect the model dynamics, and how interesting combinations of parameters may be identified. It also includes a “virtual population” from which “virtual individuals” can be chosen, on the basis of exhibiting conditions similar to those of a real-world patient. This lays the groundwork for using the Guyton model for in silico exploration of pathophysiological states and treatment strategies. The results presented here illustrate several potential uses for the entire dataset of sensitivity results and the “virtual individuals” that we have generated, which are included in the supplementary material. More generally, the presented methodology is applicable to modern, more complex multi-scale physiological models. PMID:22761561