Critical Applied Linguistics: An Evaluative Interdisciplinary Approach in Criticism and Evaluation of Applied Linguistics’ Disciplines

OpenAIRE

H. Davari

2015-01-01

The emergence of some significant critical approaches and directions in the field of applied linguistics from the mid-1980s onwards has met with various positive and opposite reactions. On the basis of their strength and significance, such approaches and directions have challenged some of the mainstream approaches’ claims, principles and assumptions. Among them, critical applied linguistics can be highlighted as a new approach, developed by the Australian applied linguist, Alastair Pennycook....

Patient perception of nursing service quality; an applied model of Donabedian's structure-process-outcome approach theory.

Science.gov (United States)

Kobayashi, Hideyuki; Takemura, Yukie; Kanda, Katsuya

2011-09-01

Nursing is a labour-intensive field, and an extensive amount of latent information exists to aid in evaluating the quality of nursing service, with patients' experiences, the primary focus of such evaluations. To effect further improvement in nursing as well as medical care, Donabedian's structure-process-outcome approach has been applied. To classify and confirm patients' specific experiences with regard to nursing service based on Donabedian's structure-process-outcomes model for improving the quality of nursing care. Items were compiled from existing scales and assigned to structure, process or outcomes in Donabedian's model through discussion among expert nurses and pilot data collection. With regard to comfort, surroundings were classified as structure (e.g. accessibility to nurses, disturbance); with regard to patient-practitioner interaction, patient participation was classified as a process (e.g. expertise and skill, patient decision-making); and with regard to changes in patients, satisfaction was classified as an outcome (e.g. information support, overall satisfaction). Patient inquiry was carried out using the finalized questionnaire at general wards in Japanese hospitals in 2005-2006. Reliability and validity were tested using psychometric methods. Data from 1,810 patients (mean age: 59.7 years; mean length of stay: 23.7 days) were analysed. Internal consistency reliability was supported (α = 0.69-0.96), with factor analysis items of structure aggregated to one factor and overall satisfaction under outcome aggregated to one. The remaining items of outcome and process were distributed together in two factors. Inter-scale correlation (r = 0.442-0.807) supported the construct validity of each structure-process-outcome approach. All structure items were represented as negative-worded examples, as they dealt with basic conditions under Japanese universal health care system, and were regarded as representative related to concepts of dissatisfaction and no

Fuzzy uncertainty modeling applied to AP1000 nuclear power plant LOCA

International Nuclear Information System (INIS)

Ferreira Guimaraes, Antonio Cesar; Franklin Lapa, Celso Marcelo; Lamego Simoes Filho, Francisco Fernando; Cabral, Denise Cunha

2011-01-01

Research highlights: → This article presents an uncertainty modelling study using a fuzzy approach. → The AP1000 Westinghouse NPP was used and it is provided of passive safety systems. → The use of advanced passive safety systems in NPP has limited operational experience. → Failure rates and basic events probabilities used on the fault tree analysis. → Fuzzy uncertainty approach was employed to reliability of the AP1000 large LOCA. - Abstract: This article presents an uncertainty modeling study using a fuzzy approach applied to the Westinghouse advanced nuclear reactor. The AP1000 Westinghouse Nuclear Power Plant (NPP) is provided of passive safety systems, based on thermo physics phenomenon, that require no operating actions, soon after an incident has been detected. The use of advanced passive safety systems in NPP has limited operational experience. As it occurs in any reliability study, statistically non-significant events report introduces a significant uncertainty level about the failure rates and basic events probabilities used on the fault tree analysis (FTA). In order to model this uncertainty, a fuzzy approach was employed to reliability analysis of the AP1000 large break Loss of Coolant Accident (LOCA). The final results have revealed that the proposed approach may be successfully applied to modeling of uncertainties in safety studies.

Molecular modeling: An open invitation for applied mathematics

Science.gov (United States)

Mezey, Paul G.

2013-10-01

Molecular modeling methods provide a very wide range of challenges for innovative mathematical and computational techniques, where often high dimensionality, large sets of data, and complicated interrelations imply a multitude of iterative approximations. The physical and chemical basis of these methodologies involves quantum mechanics with several non-intuitive aspects, where classical interpretation and classical analogies are often misleading or outright wrong. Hence, instead of the everyday, common sense approaches which work so well in engineering, in molecular modeling one often needs to rely on rather abstract mathematical constraints and conditions, again emphasizing the high level of reliance on applied mathematics. Yet, the interdisciplinary aspects of the field of molecular modeling also generates some inertia and perhaps too conservative reliance on tried and tested methodologies, that is at least partially caused by the less than up-to-date involvement in the newest developments in applied mathematics. It is expected that as more applied mathematicians take up the challenge of employing the latest advances of their field in molecular modeling, important breakthroughs may follow. In this presentation some of the current challenges of molecular modeling are discussed.

Methods for model selection in applied science and engineering.

Energy Technology Data Exchange (ETDEWEB)

Field, Richard V., Jr.

2004-10-01

Mathematical models are developed and used to study the properties of complex systems and/or modify these systems to satisfy some performance requirements in just about every area of applied science and engineering. A particular reason for developing a model, e.g., performance assessment or design, is referred to as the model use. Our objective is the development of a methodology for selecting a model that is sufficiently accurate for an intended use. Information on the system being modeled is, in general, incomplete, so that there may be two or more models consistent with the available information. The collection of these models is called the class of candidate models. Methods are developed for selecting the optimal member from a class of candidate models for the system. The optimal model depends on the available information, the selected class of candidate models, and the model use. Classical methods for model selection, including the method of maximum likelihood and Bayesian methods, as well as a method employing a decision-theoretic approach, are formulated to select the optimal model for numerous applications. There is no requirement that the candidate models be random. Classical methods for model selection ignore model use and require data to be available. Examples are used to show that these methods can be unreliable when data is limited. The decision-theoretic approach to model selection does not have these limitations, and model use is included through an appropriate utility function. This is especially important when modeling high risk systems, where the consequences of using an inappropriate model for the system can be disastrous. The decision-theoretic method for model selection is developed and applied for a series of complex and diverse applications. These include the selection of the: (1) optimal order of the polynomial chaos approximation for non-Gaussian random variables and stationary stochastic processes, (2) optimal pressure load model to be

A suggested approach toward measuring sorption and applying sorption data to repository performance assessment

International Nuclear Information System (INIS)

Rundberg, R.S.

1992-01-01

The prediction of radionuclide migration for the purpose of assessing the safety of a nuclear waste repository will be based on a collective knowledge of hydrologic and geochemical properties of the surrounding rock and groundwater. This knowledge along with assumption about the interactions of radionuclides with groundwater and minerals form the scientific basis for a model capable of accurately predicting the repository's performance. Because the interaction of radionuclides in geochemical systems is known to be complicated, several fundamental and empirical approaches to measuring the interaction between radionuclides and the geologic barrier have been developed. The approaches applied to the measurement of sorption involve the use of pure minerals, intact, or crushed rock in dynamic and static experiments. Each approach has its advantages and disadvantages. There is no single best method for providing sorption data for performance assessment models which can be applied without invoking information derived from multiple experiments. 53 refs., 12 figs

Online traffic flow model applying dynamic flow-density relation

International Nuclear Information System (INIS)

Kim, Y.

2002-01-01

This dissertation describes a new approach of the online traffic flow modelling based on the hydrodynamic traffic flow model and an online process to adapt the flow-density relation dynamically. The new modelling approach was tested based on the real traffic situations in various homogeneous motorway sections and a motorway section with ramps and gave encouraging simulation results. This work is composed of two parts: first the analysis of traffic flow characteristics and second the development of a new online traffic flow model applying these characteristics. For homogeneous motorway sections traffic flow is classified into six different traffic states with different characteristics. Delimitation criteria were developed to separate these states. The hysteresis phenomena were analysed during the transitions between these traffic states. The traffic states and the transitions are represented on a states diagram with the flow axis and the density axis. For motorway sections with ramps the complicated traffic flow is simplified and classified into three traffic states depending on the propagation of congestion. The traffic states are represented on a phase diagram with the upstream demand axis and the interaction strength axis which was defined in this research. The states diagram and the phase diagram provide a basis for the development of the dynamic flow-density relation. The first-order hydrodynamic traffic flow model was programmed according to the cell-transmission scheme extended by the modification of flow dependent sending/receiving functions, the classification of cells and the determination strategy for the flow-density relation in the cells. The unreasonable results of macroscopic traffic flow models, which may occur in the first and last cells in certain conditions are alleviated by applying buffer cells between the traffic data and the model. The sending/receiving functions of the cells are determined dynamically based on the classification of the

A new approach for developing adjoint models

Science.gov (United States)

Farrell, P. E.; Funke, S. W.

2011-12-01

Many data assimilation algorithms rely on the availability of gradients of misfit functionals, which can be efficiently computed with adjoint models. However, the development of an adjoint model for a complex geophysical code is generally very difficult. Algorithmic differentiation (AD, also called automatic differentiation) offers one strategy for simplifying this task: it takes the abstraction that a model is a sequence of primitive instructions, each of which may be differentiated in turn. While extremely successful, this low-level abstraction runs into time-consuming difficulties when applied to the whole codebase of a model, such as differentiating through linear solves, model I/O, calls to external libraries, language features that are unsupported by the AD tool, and the use of multiple programming languages. While these difficulties can be overcome, it requires a large amount of technical expertise and an intimate familiarity with both the AD tool and the model. An alternative to applying the AD tool to the whole codebase is to assemble the discrete adjoint equations and use these to compute the necessary gradients. With this approach, the AD tool must be applied to the nonlinear assembly operators, which are typically small, self-contained units of the codebase. The disadvantage of this approach is that the assembly of the discrete adjoint equations is still very difficult to perform correctly, especially for complex multiphysics models that perform temporal integration; as it stands, this approach is as difficult and time-consuming as applying AD to the whole model. In this work, we have developed a library which greatly simplifies and automates the alternate approach of assembling the discrete adjoint equations. We propose a complementary, higher-level abstraction to that of AD: that a model is a sequence of linear solves. The developer annotates model source code with library calls that build a 'tape' of the operators involved and their dependencies, and

Fuzzy model predictive control algorithm applied in nuclear power plant

International Nuclear Information System (INIS)

Zuheir, Ahmad

2006-01-01

The aim of this paper is to design a predictive controller based on a fuzzy model. The Takagi-Sugeno fuzzy model with an Adaptive B-splines neuro-fuzzy implementation is used and incorporated as a predictor in a predictive controller. An optimization approach with a simplified gradient technique is used to calculate predictions of the future control actions. In this approach, adaptation of the fuzzy model using dynamic process information is carried out to build the predictive controller. The easy description of the fuzzy model and the easy computation of the gradient sector during the optimization procedure are the main advantages of the computation algorithm. The algorithm is applied to the control of a U-tube steam generation unit (UTSG) used for electricity generation. (author)

A Log Logistic Survival Model Applied to Hypobaric Decompression Sickness

Science.gov (United States)

Conkin, Johnny

2001-01-01

Decompression sickness (DCS) is a complex, multivariable problem. A mathematical description or model of the likelihood of DCS requires a large amount of quality research data, ideas on how to define a decompression dose using physical and physiological variables, and an appropriate analytical approach. It also requires a high-performance computer with specialized software. I have used published DCS data to develop my decompression doses, which are variants of equilibrium expressions for evolved gas plus other explanatory variables. My analytical approach is survival analysis, where the time of DCS occurrence is modeled. My conclusions can be applied to simple hypobaric decompressions - ascents lasting from 5 to 30 minutes - and, after minutes to hours, to denitrogenation (prebreathing). They are also applicable to long or short exposures, and can be used whether the sufferer of DCS is at rest or exercising at altitude. Ultimately I would like my models to be applied to astronauts to reduce the risk of DCS during spacewalks, as well as to future spaceflight crews on the Moon and Mars.

Applying different quality and safety models in healthcare improvement work: Boundary objects and system thinking

International Nuclear Information System (INIS)

Wiig, Siri; Robert, Glenn; Anderson, Janet E.; Pietikainen, Elina; Reiman, Teemu; Macchi, Luigi; Aase, Karina

2014-01-01

A number of theoretical models can be applied to help guide quality improvement and patient safety interventions in hospitals. However there are often significant differences between such models and, therefore, their potential contribution when applied in diverse contexts. The aim of this paper is to explore how two such models have been applied by hospitals to improve quality and safety. We describe and compare the models: (1) The Organizing for Quality (OQ) model, and (2) the Design for Integrated Safety Culture (DISC) model. We analyze the theoretical foundations of the models, and show, by using a retrospective comparative case study approach from two European hospitals, how these models have been applied to improve quality and safety. The analysis shows that differences appear in the theoretical foundations, practical approaches and applications of the models. Nevertheless, the case studies indicate that the choice between the OQ and DISC models is of less importance for guiding the practice of quality and safety improvement work, as they are both systemic and share some important characteristics. The main contribution of the models lay in their role as boundary objects directing attention towards organizational and systems thinking, culture, and collaboration

A Numerical Procedure for Model Identifiability Analysis Applied to Enzyme Kinetics

DEFF Research Database (Denmark)

Daele, Timothy, Van; Van Hoey, Stijn; Gernaey, Krist

2015-01-01

The proper calibration of models describing enzyme kinetics can be quite challenging. In the literature, different procedures are available to calibrate these enzymatic models in an efficient way. However, in most cases the model structure is already decided on prior to the actual calibration...... and Pronzato (1997) and which can be easily set up for any type of model. In this paper the proposed approach is applied to the forward reaction rate of the enzyme kinetics proposed by Shin and Kim(1998). Structural identifiability analysis showed that no local structural model problems were occurring......) identifiability problems. By using the presented approach it is possible to detect potential identifiability problems and avoid pointless calibration (and experimental!) effort....

Applied data analysis and modeling for energy engineers and scientists

CERN Document Server

Reddy, T Agami

2011-01-01

""Applied Data Analysis and Modeling for Energy Engineers and Scientists"" discusses mathematical models, data analysis, and decision analysis in modeling. The approach taken in this volume focuses on the modeling and analysis of thermal systems in an engineering environment, while also covering a number of other critical areas. Other material covered includes the tools that researchers and engineering professionals will need in order to explore different analysis methods, use critical assessment skills and reach sound engineering conclusions. The book also covers process and system design and

Eliciting expert opinion for economic models: an applied example.

Science.gov (United States)

Leal, José; Wordsworth, Sarah; Legood, Rosa; Blair, Edward

2007-01-01

Expert opinion is considered as a legitimate source of information for decision-analytic modeling where required data are unavailable. Our objective was to develop a practical computer-based tool for eliciting expert opinion about the shape of the uncertainty distribution around individual model parameters. We first developed a prepilot survey with departmental colleagues to test a number of alternative approaches to eliciting opinions on the shape of the uncertainty distribution around individual parameters. This information was used to develop a survey instrument for an applied clinical example. This involved eliciting opinions from experts to inform a number of parameters involving Bernoulli processes in an economic model evaluating DNA testing for families with a genetic disease, hypertrophic cardiomyopathy. The experts were cardiologists, clinical geneticists, and laboratory scientists working with cardiomyopathy patient populations and DNA testing. Our initial prepilot work suggested that the more complex elicitation techniques advocated in the literature were difficult to use in practice. In contrast, our approach achieved a reasonable response rate (50%), provided logical answers, and was generally rated as easy to use by respondents. The computer software user interface permitted graphical feedback throughout the elicitation process. The distributions obtained were incorporated into the model, enabling the use of probabilistic sensitivity analysis. There is clearly a gap in the literature between theoretical elicitation techniques and tools that can be used in applied decision-analytic models. The results of this methodological study are potentially valuable for other decision analysts deriving expert opinion.

Applying Mathematical Optimization Methods to an ACT-R Instance-Based Learning Model.

Science.gov (United States)

Said, Nadia; Engelhart, Michael; Kirches, Christian; Körkel, Stefan; Holt, Daniel V

2016-01-01

Computational models of cognition provide an interface to connect advanced mathematical tools and methods to empirically supported theories of behavior in psychology, cognitive science, and neuroscience. In this article, we consider a computational model of instance-based learning, implemented in the ACT-R cognitive architecture. We propose an approach for obtaining mathematical reformulations of such cognitive models that improve their computational tractability. For the well-established Sugar Factory dynamic decision making task, we conduct a simulation study to analyze central model parameters. We show how mathematical optimization techniques can be applied to efficiently identify optimal parameter values with respect to different optimization goals. Beyond these methodological contributions, our analysis reveals the sensitivity of this particular task with respect to initial settings and yields new insights into how average human performance deviates from potential optimal performance. We conclude by discussing possible extensions of our approach as well as future steps towards applying more powerful derivative-based optimization methods.

Applying Mathematical Optimization Methods to an ACT-R Instance-Based Learning Model.

Directory of Open Access Journals (Sweden)

Nadia Said

Full Text Available Computational models of cognition provide an interface to connect advanced mathematical tools and methods to empirically supported theories of behavior in psychology, cognitive science, and neuroscience. In this article, we consider a computational model of instance-based learning, implemented in the ACT-R cognitive architecture. We propose an approach for obtaining mathematical reformulations of such cognitive models that improve their computational tractability. For the well-established Sugar Factory dynamic decision making task, we conduct a simulation study to analyze central model parameters. We show how mathematical optimization techniques can be applied to efficiently identify optimal parameter values with respect to different optimization goals. Beyond these methodological contributions, our analysis reveals the sensitivity of this particular task with respect to initial settings and yields new insights into how average human performance deviates from potential optimal performance. We conclude by discussing possible extensions of our approach as well as future steps towards applying more powerful derivative-based optimization methods.

A single grain approach applied to modelling recrystallization kinetics in a single-phase metal

NARCIS (Netherlands)

Chen, S.P.; Zwaag, van der S.

2004-01-01

A comprehensive model for the recrystallization kinetics is proposed which incorporates both microstructure and the textural components in the deformed state. The model is based on the single-grain approach proposed previously. The influence of the as-deformed grain orientation, which affects the

Nonlinear Modeling of the PEMFC Based On NNARX Approach

OpenAIRE

Shan-Jen Cheng; Te-Jen Chang; Kuang-Hsiung Tan; Shou-Ling Kuo

2015-01-01

Polymer Electrolyte Membrane Fuel Cell (PEMFC) is such a time-vary nonlinear dynamic system. The traditional linear modeling approach is hard to estimate structure correctly of PEMFC system. From this reason, this paper presents a nonlinear modeling of the PEMFC using Neural Network Auto-regressive model with eXogenous inputs (NNARX) approach. The multilayer perception (MLP) network is applied to evaluate the structure of the NNARX model of PEMFC. The validity and accurac...

Applying a new ensemble approach to estimating stock status of marine fisheries around the world

DEFF Research Database (Denmark)

Rosenberg, Andrew A.; Kleisner, Kristin M.; Afflerbach, Jamie

2018-01-01

The exploitation status of marine fisheries stocks worldwide is of critical importance for food security, ecosystem conservation, and fishery sustainability. Applying a suite of data-limited methods to global catch data, combined through an ensemble modeling approach, we provide quantitative esti...

Applied systems ecology: models, data, and statistical methods

Energy Technology Data Exchange (ETDEWEB)

Eberhardt, L L

1976-01-01

In this report, systems ecology is largely equated to mathematical or computer simulation modelling. The need for models in ecology stems from the necessity to have an integrative device for the diversity of ecological data, much of which is observational, rather than experimental, as well as from the present lack of a theoretical structure for ecology. Different objectives in applied studies require specialized methods. The best predictive devices may be regression equations, often non-linear in form, extracted from much more detailed models. A variety of statistical aspects of modelling, including sampling, are discussed. Several aspects of population dynamics and food-chain kinetics are described, and it is suggested that the two presently separated approaches should be combined into a single theoretical framework. It is concluded that future efforts in systems ecology should emphasize actual data and statistical methods, as well as modelling.

The asymmetric rotator model applied to odd-mass iridium isotopes

International Nuclear Information System (INIS)

Piepenbring, R.

1980-04-01

The method of inversion of the eigenvalue problem previously developed for nuclei with axial symmetry is extended to asymmetric equilibrium shapes. This new approach of the asymmetric rotator model is applied to the odd-mass iridium isotopes. A satisfactory and coherent description of the observed energy spectra is obtained, especially for the lighter isotopes

The hybrid thermography approach applied to architectural structures

Science.gov (United States)

Sfarra, S.; Ambrosini, D.; Paoletti, D.; Nardi, I.; Pasqualoni, G.

2017-07-01

This work contains an overview of infrared thermography (IRT) method and its applications relating to the investigation of architectural structures. In this method, the passive approach is usually used in civil engineering, since it provides a panoramic view of the thermal anomalies to be interpreted also thanks to the use of photographs focused on the region of interest (ROI). The active approach, is more suitable for laboratory or indoor inspections, as well as for objects having a small size. The external stress to be applied is thermal, coming from non-natural apparatus such as lamps or hot / cold air jets. In addition, the latter permits to obtain quantitative information related to defects not detectable to the naked eyes. Very recently, the hybrid thermography (HIRT) approach has been introduced to the attention of the scientific panorama. It can be applied when the radiation coming from the sun, directly arrives (i.e., possibly without the shadow cast effect) on a surface exposed to the air. A large number of thermograms must be collected and a post-processing analysis is subsequently applied via advanced algorithms. Therefore, an appraisal of the defect depth can be obtained passing through the calculation of the combined thermal diffusivity of the materials above the defect. The approach is validated herein by working, in a first stage, on a mosaic sample having known defects while, in a second stage, on a Church built in L'Aquila (Italy) and covered with a particular masonry structure called apparecchio aquilano. The results obtained appear promising.

Benefits of Applying Hierarchical Models to the Empirical Green's Function Approach

Science.gov (United States)

Denolle, M.; Van Houtte, C.

2017-12-01

Stress drops calculated from source spectral studies currently show larger variability than what is implied by empirical ground motion models. One of the potential origins of the inflated variability is the simplified model-fitting techniques used in most source spectral studies. This study improves upon these existing methods, and shows that the fitting method may explain some of the discrepancy. In particular, Bayesian hierarchical modelling is shown to be a method that can reduce bias, better quantify uncertainties and allow additional effects to be resolved. The method is applied to the Mw7.1 Kumamoto, Japan earthquake, and other global, moderate-magnitude, strike-slip earthquakes between Mw5 and Mw7.5. It is shown that the variation of the corner frequency, fc, and the falloff rate, n, across the focal sphere can be reliably retrieved without overfitting the data. Additionally, it is shown that methods commonly used to calculate corner frequencies can give substantial biases. In particular, if fc were calculated for the Kumamoto earthquake using a model with a falloff rate fixed at 2 instead of the best fit 1.6, the obtained fc would be as large as twice its realistic value. The reliable retrieval of the falloff rate allows deeper examination of this parameter for a suite of global, strike-slip earthquakes, and its scaling with magnitude. The earthquake sequences considered in this study are from Japan, New Zealand, Haiti and California.

Commercial Consolidation Model Applied to Transport Infrastructure

Energy Technology Data Exchange (ETDEWEB)

Guilherme de Aragão, J.J.; Santos Fontes Pereira, L. dos; Yamashita, Y.

2016-07-01

Since the 1990s, transport concessions, including public-private partnerships (PPPs), have been increasingly adopted by governments as an alternative for financing and operations in public investments, especially in transport infrastructure. The advantage pointed out by proponents of these models lies in merging the expertise and capital of the private sector to the public interest. Several arrangements are possible and have been employed in different cases. After the duration of the first PPP contracts in transportation, many authors have analyzed the success and failure factors of partnerships. The occurrence of failures in some stages of the process can greatly encumber the public administration, incurring losses to the fiscal responsibility of the competent bodies. This article aims to propose a new commercial consolidation model applied to transport infrastructure to ensure fiscal sustainability and overcome the weaknesses of current models. Initially, a systematic review of the literature covering studies on transport concessions between 1990 and 2015 is offered, where the different approaches between various countries are compared and the critical success factors indicated in the studies are identified. In the subsequent part of the paper, an approach for the commercial consolidation of the infrastructure concessions is presented, where the concessionary is paid following a finalistic performance model, which includes the overall fiscal balance of regional growth. Finally, the papers analyses the usefulness of the model in coping with the critical success factors explained before. (Author)

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

Science.gov (United States)

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

2013-01-01

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

Variational approach to chiral quark models

Energy Technology Data Exchange (ETDEWEB)

Futami, Yasuhiko; Odajima, Yasuhiko; Suzuki, Akira

1987-03-01

A variational approach is applied to a chiral quark model to test the validity of the perturbative treatment of the pion-quark interaction based on the chiral symmetry principle. It is indispensably related to the chiral symmetry breaking radius if the pion-quark interaction can be regarded as a perturbation.

A Constructive Neural-Network Approach to Modeling Psychological Development

Science.gov (United States)

Shultz, Thomas R.

2012-01-01

This article reviews a particular computational modeling approach to the study of psychological development--that of constructive neural networks. This approach is applied to a variety of developmental domains and issues, including Piagetian tasks, shift learning, language acquisition, number comparison, habituation of visual attention, concept…

From basic physics to mechanisms of toxicity: the ``liquid drop'' approach applied to develop predictive classification models for toxicity of metal oxide nanoparticles

Science.gov (United States)

Sizochenko, Natalia; Rasulev, Bakhtiyor; Gajewicz, Agnieszka; Kuz'min, Victor; Puzyn, Tomasz; Leszczynski, Jerzy

2014-10-01

Many metal oxide nanoparticles are able to cause persistent stress to live organisms, including humans, when discharged to the environment. To understand the mechanism of metal oxide nanoparticles' toxicity and reduce the number of experiments, the development of predictive toxicity models is important. In this study, performed on a series of nanoparticles, the comparative quantitative-structure activity relationship (nano-QSAR) analyses of their toxicity towards E. coli and HaCaT cells were established. A new approach for representation of nanoparticles' structure is presented. For description of the supramolecular structure of nanoparticles the ``liquid drop'' model was applied. It is expected that a novel, proposed approach could be of general use for predictions related to nanomaterials. In addition, in our study fragmental simplex descriptors and several ligand-metal binding characteristics were calculated. The developed nano-QSAR models were validated and reliably predict the toxicity of all studied metal oxide nanoparticles. Based on the comparative analysis of contributed properties in both models the LDM-based descriptors were revealed to have an almost similar level of contribution to toxicity in both cases, while other parameters (van der Waals interactions, electronegativity and metal-ligand binding characteristics) have unequal contribution levels. In addition, the models developed here suggest different mechanisms of nanotoxicity for these two types of cells.Many metal oxide nanoparticles are able to cause persistent stress to live organisms, including humans, when discharged to the environment. To understand the mechanism of metal oxide nanoparticles' toxicity and reduce the number of experiments, the development of predictive toxicity models is important. In this study, performed on a series of nanoparticles, the comparative quantitative-structure activity relationship (nano-QSAR) analyses of their toxicity towards E. coli and HaCaT cells were

Does the interpersonal model apply across eating disorder diagnostic groups? A structural equation modeling approach.

Science.gov (United States)

Ivanova, Iryna V; Tasca, Giorgio A; Proulx, Geneviève; Bissada, Hany

2015-11-01

Interpersonal model has been validated with binge-eating disorder (BED), but it is not yet known if the model applies across a range of eating disorders (ED). The goal of this study was to investigate the validity of the interpersonal model in anorexia nervosa (restricting type; ANR and binge-eating/purge type; ANBP), bulimia nervosa (BN), BED, and eating disorder not otherwise specified (EDNOS). Data from a cross-sectional sample of 1459 treatment-seeking women diagnosed with ANR, ANBP, BN, BED and EDNOS were examined for indirect effects of interpersonal problems on ED psychopathology mediated through negative affect. Findings from structural equation modeling demonstrated the mediating role of negative affect in four of the five diagnostic groups. There were significant, medium to large (.239, .558), indirect effects in the ANR, BN, BED and EDNOS groups but not in the ANBP group. The results of the first reverse model of interpersonal problems as a mediator between negative affect and ED psychopathology were nonsignificant, suggesting the specificity of these hypothesized paths. However, in the second reverse model ED psychopathology was related to interpersonal problems indirectly through negative affect. This is the first study to find support for the interpersonal model of ED in a clinical sample of women with diverse ED diagnoses, though there may be a reciprocal relationship between ED psychopathology and relationship problems through negative affect. Negative affect partially explains the relationship between interpersonal problems and ED psychopathology in women diagnosed with ANR, BN, BED and EDNOS. Interpersonal psychotherapies for ED may be addressing the underlying interpersonal-affective difficulties, thereby reducing ED psychopathology. Copyright © 2015 Elsevier Inc. All rights reserved.

Applied stochastic modelling

CERN Document Server

Morgan, Byron JT; Tanner, Martin Abba; Carlin, Bradley P

2008-01-01

Introduction and Examples Introduction Examples of data sets Basic Model Fitting Introduction Maximum-likelihood estimation for a geometric model Maximum-likelihood for the beta-geometric model Modelling polyspermy Which model? What is a model for? Mechanistic models Function Optimisation Introduction MATLAB: graphs and finite differences Deterministic search methods Stochastic search methods Accuracy and a hybrid approach Basic Likelihood ToolsIntroduction Estimating standard errors and correlations Looking at surfaces: profile log-likelihoods Confidence regions from profiles Hypothesis testing in model selectionScore and Wald tests Classical goodness of fit Model selection biasGeneral Principles Introduction Parameterisation Parameter redundancy Boundary estimates Regression and influence The EM algorithm Alternative methods of model fitting Non-regular problemsSimulation Techniques Introduction Simulating random variables Integral estimation Verification Monte Carlo inference Estimating sampling distributi...

An effective model for ergonomic optimization applied to a new automotive assembly line

Energy Technology Data Exchange (ETDEWEB)

Duraccio, Vincenzo [University Niccolò Cusano, Rome Via Don Gnocchi,00166, Roma Italy (Italy); Elia, Valerio [Dept. of Innovation Engineering - University of Salento Via Monteroni, 73100, Lecce (Italy); Forcina, Antonio [University Parthenope, Dep. of Engineering Centro Direzionale - Isola C4 80143 - Naples - Italy (Italy)

2016-06-08

An efficient ergonomic optimization can lead to a significant improvement in production performance and a considerable reduction of costs. In the present paper new model for ergonomic optimization is proposed. The new approach is based on the criteria defined by National Institute of Occupational Safety and Health and, adapted to Italian legislation. The proposed model provides an ergonomic optimization, by analyzing ergonomic relations between manual work in correct conditions. The model includes a schematic and systematic analysis method of the operations, and identifies all possible ergonomic aspects to be evaluated. The proposed approach has been applied to an automotive assembly line, where the operation repeatability makes the optimization fundamental. The proposed application clearly demonstrates the effectiveness of the new approach.

An effective model for ergonomic optimization applied to a new automotive assembly line

International Nuclear Information System (INIS)

Duraccio, Vincenzo; Elia, Valerio; Forcina, Antonio

2016-01-01

An efficient ergonomic optimization can lead to a significant improvement in production performance and a considerable reduction of costs. In the present paper new model for ergonomic optimization is proposed. The new approach is based on the criteria defined by National Institute of Occupational Safety and Health and, adapted to Italian legislation. The proposed model provides an ergonomic optimization, by analyzing ergonomic relations between manual work in correct conditions. The model includes a schematic and systematic analysis method of the operations, and identifies all possible ergonomic aspects to be evaluated. The proposed approach has been applied to an automotive assembly line, where the operation repeatability makes the optimization fundamental. The proposed application clearly demonstrates the effectiveness of the new approach.

An effective model for ergonomic optimization applied to a new automotive assembly line

Science.gov (United States)

Duraccio, Vincenzo; Elia, Valerio; Forcina, Antonio

2016-06-01

An efficient ergonomic optimization can lead to a significant improvement in production performance and a considerable reduction of costs. In the present paper new model for ergonomic optimization is proposed. The new approach is based on the criteria defined by National Institute of Occupational Safety and Health and, adapted to Italian legislation. The proposed model provides an ergonomic optimization, by analyzing ergonomic relations between manual work in correct conditions. The model includes a schematic and systematic analysis method of the operations, and identifies all possible ergonomic aspects to be evaluated. The proposed approach has been applied to an automotive assembly line, where the operation repeatability makes the optimization fundamental. The proposed application clearly demonstrates the effectiveness of the new approach.

An Inverse Kinematic Approach Using Groebner Basis Theory Applied to Gait Cycle Analysis

Science.gov (United States)

2013-03-01

AN INVERSE KINEMATIC APPROACH USING GROEBNER BASIS THEORY APPLIED TO GAIT CYCLE ANALYSIS THESIS Anum Barki AFIT-ENP-13-M-02 DEPARTMENT OF THE AIR...copyright protection in the United States. AFIT-ENP-13-M-02 AN INVERSE KINEMATIC APPROACH USING GROEBNER BASIS THEORY APPLIED TO GAIT CYCLE ANALYSIS THESIS...APPROACH USING GROEBNER BASIS THEORY APPLIED TO GAIT CYCLE ANALYSIS Anum Barki, BS Approved: Dr. Ronald F. Tuttle (Chairman) Date Dr. Kimberly Kendricks

A Composite Modelling Approach to Decision Support by the Use of the CBA-DK Model

DEFF Research Database (Denmark)

Barfod, Michael Bruhn; Salling, Kim Bang; Leleur, Steen

2007-01-01

This paper presents a decision support system for assessment of transport infrastructure projects. The composite modelling approach, COSIMA, combines a cost-benefit analysis by use of the CBA-DK model with multi-criteria analysis applying the AHP and SMARTER techniques. The modelling uncertaintie...

Merging Digital Surface Models Implementing Bayesian Approaches

Science.gov (United States)

Sadeq, H.; Drummond, J.; Li, Z.

2016-06-01

In this research different DSMs from different sources have been merged. The merging is based on a probabilistic model using a Bayesian Approach. The implemented data have been sourced from very high resolution satellite imagery sensors (e.g. WorldView-1 and Pleiades). It is deemed preferable to use a Bayesian Approach when the data obtained from the sensors are limited and it is difficult to obtain many measurements or it would be very costly, thus the problem of the lack of data can be solved by introducing a priori estimations of data. To infer the prior data, it is assumed that the roofs of the buildings are specified as smooth, and for that purpose local entropy has been implemented. In addition to the a priori estimations, GNSS RTK measurements have been collected in the field which are used as check points to assess the quality of the DSMs and to validate the merging result. The model has been applied in the West-End of Glasgow containing different kinds of buildings, such as flat roofed and hipped roofed buildings. Both quantitative and qualitative methods have been employed to validate the merged DSM. The validation results have shown that the model was successfully able to improve the quality of the DSMs and improving some characteristics such as the roof surfaces, which consequently led to better representations. In addition to that, the developed model has been compared with the well established Maximum Likelihood model and showed similar quantitative statistical results and better qualitative results. Although the proposed model has been applied on DSMs that were derived from satellite imagery, it can be applied to any other sourced DSMs.

MERGING DIGITAL SURFACE MODELS IMPLEMENTING BAYESIAN APPROACHES

Directory of Open Access Journals (Sweden)

H. Sadeq

2016-06-01

Full Text Available In this research different DSMs from different sources have been merged. The merging is based on a probabilistic model using a Bayesian Approach. The implemented data have been sourced from very high resolution satellite imagery sensors (e.g. WorldView-1 and Pleiades. It is deemed preferable to use a Bayesian Approach when the data obtained from the sensors are limited and it is difficult to obtain many measurements or it would be very costly, thus the problem of the lack of data can be solved by introducing a priori estimations of data. To infer the prior data, it is assumed that the roofs of the buildings are specified as smooth, and for that purpose local entropy has been implemented. In addition to the a priori estimations, GNSS RTK measurements have been collected in the field which are used as check points to assess the quality of the DSMs and to validate the merging result. The model has been applied in the West-End of Glasgow containing different kinds of buildings, such as flat roofed and hipped roofed buildings. Both quantitative and qualitative methods have been employed to validate the merged DSM. The validation results have shown that the model was successfully able to improve the quality of the DSMs and improving some characteristics such as the roof surfaces, which consequently led to better representations. In addition to that, the developed model has been compared with the well established Maximum Likelihood model and showed similar quantitative statistical results and better qualitative results. Although the proposed model has been applied on DSMs that were derived from satellite imagery, it can be applied to any other sourced DSMs.

The possibilities of applying a risk-oriented approach to the NPP reliability and safety enhancement problem

Science.gov (United States)

Komarov, Yu. A.

2014-10-01

An analysis and some generalizations of approaches to risk assessments are presented. Interconnection between different interpretations of the "risk" notion is shown, and the possibility of applying the fuzzy set theory to risk assessments is demonstrated. A generalized formulation of the risk assessment notion is proposed in applying risk-oriented approaches to the problem of enhancing reliability and safety in nuclear power engineering. The solution of problems using the developed risk-oriented approaches aimed at achieving more reliable and safe operation of NPPs is described. The results of studies aimed at determining the need (advisability) to modernize/replace NPP elements and systems are presented together with the results obtained from elaborating the methodical principles of introducing the repair concept based on the equipment technical state. The possibility of reducing the scope of tests and altering the NPP systems maintenance strategy is substantiated using the risk-oriented approach. A probabilistic model for estimating the validity of boric acid concentration measurements is developed.

Didactical suggestion for a Dynamic Hybrid Intelligent e-Learning Environment (DHILE) applying the PENTHA ID Model

Science.gov (United States)

dall'Acqua, Luisa

2011-08-01

The teleology of our research is to propose a solution to the request of "innovative, creative teaching", proposing a methodology to educate creative Students in a society characterized by multiple reference points and hyper dynamic knowledge, continuously subject to reviews and discussions. We apply a multi-prospective Instructional Design Model (PENTHA ID Model), defined and developed by our research group, which adopts a hybrid pedagogical approach, consisting of elements of didactical connectivism intertwined with aspects of social constructivism and enactivism. The contribution proposes an e-course structure and approach, applying the theoretical design principles of the above mentioned ID Model, describing methods, techniques, technologies and assessment criteria for the definition of lesson modes in an e-course.

Models, validation, and applied geochemistry: Issues in science, communication, and philosophy

International Nuclear Information System (INIS)

Kirk Nordstrom, D.

2012-01-01

Models have become so fashionable that many scientists and engineers cannot imagine working without them. The predominant use of computer codes to execute model calculations has blurred the distinction between code and model. The recent controversy regarding model validation has brought into question what we mean by a ‘model’ and by ‘validation.’ It has become apparent that the usual meaning of validation may be common in engineering practice and seems useful in legal practice but it is contrary to scientific practice and brings into question our understanding of science and how it can best be applied to such problems as hazardous waste characterization, remediation, and aqueous geochemistry in general. This review summarizes arguments against using the phrase model validation and examines efforts to validate models for high-level radioactive waste management and for permitting and monitoring open-pit mines. Part of the controversy comes from a misunderstanding of ‘prediction’ and the need to distinguish logical from temporal prediction. Another problem stems from the difference in the engineering approach contrasted with the scientific approach. The reductionist influence on the way we approach environmental investigations also limits our ability to model the interconnected nature of reality. Guidelines are proposed to improve our perceptions and proper utilization of models. Use of the word ‘validation’ is strongly discouraged when discussing model reliability.

A Set Theoretical Approach to Maturity Models

DEFF Research Database (Denmark)

Lasrado, Lester; Vatrapu, Ravi; Andersen, Kim Normann

2016-01-01

characterized by equifinality, multiple conjunctural causation, and case diversity. We prescribe methodological guidelines consisting of a six-step procedure to systematically apply set theoretic methods to conceptualize, develop, and empirically derive maturity models and provide a demonstration......Maturity Model research in IS has been criticized for the lack of theoretical grounding, methodological rigor, empirical validations, and ignorance of multiple and non-linear paths to maturity. To address these criticisms, this paper proposes a novel set-theoretical approach to maturity models...

A Bayesian approach for quantification of model uncertainty

International Nuclear Information System (INIS)

Park, Inseok; Amarchinta, Hemanth K.; Grandhi, Ramana V.

2010-01-01

In most engineering problems, more than one model can be created to represent an engineering system's behavior. Uncertainty is inevitably involved in selecting the best model from among the models that are possible. Uncertainty in model selection cannot be ignored, especially when the differences between the predictions of competing models are significant. In this research, a methodology is proposed to quantify model uncertainty using measured differences between experimental data and model outcomes under a Bayesian statistical framework. The adjustment factor approach is used to propagate model uncertainty into prediction of a system response. A nonlinear vibration system is used to demonstrate the processes for implementing the adjustment factor approach. Finally, the methodology is applied on the engineering benefits of a laser peening process, and a confidence band for residual stresses is established to indicate the reliability of model prediction.

A variational approach to chiral quark models

International Nuclear Information System (INIS)

Futami, Yasuhiko; Odajima, Yasuhiko; Suzuki, Akira.

1987-01-01

A variational approach is applied to a chiral quark model to test the validity of the perturbative treatment of the pion-quark interaction based on the chiral symmetry principle. It is indispensably related to the chiral symmetry breaking radius if the pion-quark interaction can be regarded as a perturbation. (author)

Alternative Approaches to Technical Efficiency Estimation in the Stochastic Frontier Model

OpenAIRE

Acquah, H. de-Graft; Onumah, E. E.

2014-01-01

Estimating the stochastic frontier model and calculating technical efficiency of decision making units are of great importance in applied production economic works. This paper estimates technical efficiency from the stochastic frontier model using Jondrow, and Battese and Coelli approaches. In order to compare alternative methods, simulated data with sample sizes of 60 and 200 are generated from stochastic frontier model commonly applied to agricultural firms. Simulated data is employed to co...

Applying Probabilistic Decision Models to Clinical Trial Design

Science.gov (United States)

Smith, Wade P; Phillips, Mark H

2018-01-01

Clinical trial design most often focuses on a single or several related outcomes with corresponding calculations of statistical power. We consider a clinical trial to be a decision problem, often with competing outcomes. Using a current controversy in the treatment of HPV-positive head and neck cancer, we apply several different probabilistic methods to help define the range of outcomes given different possible trial designs. Our model incorporates the uncertainties in the disease process and treatment response and the inhomogeneities in the patient population. Instead of expected utility, we have used a Markov model to calculate quality adjusted life expectancy as a maximization objective. Monte Carlo simulations over realistic ranges of parameters are used to explore different trial scenarios given the possible ranges of parameters. This modeling approach can be used to better inform the initial trial design so that it will more likely achieve clinical relevance.

Applying lessons from the ecohealth approach to make food ...

International Development Research Centre (IDRC) Digital Library (Canada)

Applying lessons from the ecohealth approach to make food systems healthier ... the biennial Ecohealth Congress of the International Association for Ecology and ... intersectoral policies that address the notable increase in obesity, diabetes, ...

Consequence Based Design. An approach for integrating computational collaborative models (Integrated Dynamic Models) in the building design phase

DEFF Research Database (Denmark)

Negendahl, Kristoffer

relies on various advancements in the area of integrated dynamic models. It also relies on the application and test of the approach in practice to evaluate the Consequence based design and the use of integrated dynamic models. As a result, the Consequence based design approach has been applied in five...... and define new ways to implement integrated dynamic models for the following project. In parallel, seven different developments of new methods, tools and algorithms have been performed to support the application of the approach. The developments concern: Decision diagrams – to clarify goals and the ability...... affect the design process and collaboration between building designers and simulationists. Within the limits of applying the approach of Consequence based design to five case studies, followed by documentation based on interviews, surveys and project related documentations derived from internal reports...

Apply Functional Modelling to Consequence Analysis in Supervision Systems

DEFF Research Database (Denmark)

Zhang, Xinxin; Lind, Morten; Gola, Giulio

2013-01-01

This paper will first present the purpose and goals of applying functional modelling approach to consequence analysis by adopting Multilevel Flow Modelling (MFM). MFM Models describe a complex system in multiple abstraction levels in both means-end dimension and whole-part dimension. It contains...... consequence analysis to practical or online applications in supervision systems. It will also suggest a multiagent solution as the integration architecture for developing tools to facilitate the utilization results of functional consequence analysis. Finally a prototype of the multiagent reasoning system...... causal relations between functions and goals. A rule base system can be developed to trace the causal relations and perform consequence propagations. This paper will illustrate how to use MFM for consequence reasoning by using rule base technology and describe the challenges for integrating functional...

Geothermal potential assessment for a low carbon strategy : A new systematic approach applied in southern Italy

NARCIS (Netherlands)

Trumpy, E.; Botteghi, S.; Caiozzi, F.; Donato, A.; Gola, G.; Montanari, D.; Pluymaekers, M. P D; Santilano, A.; van Wees, J. D.; Manzella, A.

2016-01-01

In this study a new approach to geothermal potential assessment was set up and applied in four regions in southern Italy. Our procedure, VIGORThermoGIS, relies on the volume method of assessment and uses a 3D model of the subsurface to integrate thermal, geological and petro-physical data. The

Geothermal potential assessment for a low carbon strategy: A new systematic approach applied in southern Italy

NARCIS (Netherlands)

Trumpy, E.; Botteghi, S.; Caiozzi, F.; Donato, A.; Gola, G.; Montanari, D.; Pluymaekers, M.P.D.; Santilano, A.; Wees, J.D. van; Manzella, A.

2016-01-01

In this study a new approach to geothermal potential assessment was set up and applied in four regions in southern Italy. Our procedure, VIGORThermoGIS, relies on the volume method of assessment and uses a 3D model of the subsurface to integrate thermal, geological and petro-physical data. The

A generalized approach for historical mock-up acquisition and data modelling: Towards historically enriched 3D city models

Science.gov (United States)

Hervy, B.; Billen, R.; Laroche, F.; Carré, C.; Servières, M.; Van Ruymbeke, M.; Tourre, V.; Delfosse, V.; Kerouanton, J.-L.

2012-10-01

Museums are filled with hidden secrets. One of those secrets lies behind historical mock-ups whose signification goes far behind a simple representation of a city. We face the challenge of designing, storing and showing knowledge related to these mock-ups in order to explain their historical value. Over the last few years, several mock-up digitalisation projects have been realised. Two of them, Nantes 1900 and Virtual Leodium, propose innovative approaches that present a lot of similarities. This paper presents a framework to go one step further by analysing their data modelling processes and extracting what could be a generalized approach to build a numerical mock-up and the knowledge database associated. Geometry modelling and knowledge modelling influence each other and are conducted in a parallel process. Our generalized approach describes a global overview of what can be a data modelling process. Our next goal is obviously to apply this global approach on other historical mock-up, but we also think about applying it to other 3D objects that need to embed semantic data, and approaching historically enriched 3D city models.

A Cointegrated Regime-Switching Model Approach with Jumps Applied to Natural Gas Futures Prices

Directory of Open Access Journals (Sweden)

Daniel Leonhardt

2017-09-01

Full Text Available Energy commodities and their futures naturally show cointegrated price movements. However, there is empirical evidence that the prices of futures with different maturities might have, e.g., different jump behaviours in different market situations. Observing commodity futures over time, there is also evidence for different states of the underlying volatility of the futures. In this paper, we therefore allow for cointegration of the term structure within a multi-factor model, which includes seasonality, as well as joint and individual jumps in the price processes of futures with different maturities. The seasonality in this model is realized via a deterministic function, and the jumps are represented with thinned-out compound Poisson processes. The model also includes a regime-switching approach that is modelled through a Markov chain and extends the class of geometric models. We show how the model can be calibrated to empirical data and give some practical applications.

FDTD-based Transcranial Magnetic Stimulation model applied to specific neurodegenerative disorders.

Science.gov (United States)

Fanjul-Vélez, Félix; Salas-García, Irene; Ortega-Quijano, Noé; Arce-Diego, José Luis

2015-01-01

Non-invasive treatment of neurodegenerative diseases is particularly challenging in Western countries, where the population age is increasing. In this work, magnetic propagation in human head is modelled by Finite-Difference Time-Domain (FDTD) method, taking into account specific characteristics of Transcranial Magnetic Stimulation (TMS) in neurodegenerative diseases. It uses a realistic high-resolution three-dimensional human head mesh. The numerical method is applied to the analysis of magnetic radiation distribution in the brain using two realistic magnetic source models: a circular coil and a figure-8 coil commonly employed in TMS. The complete model was applied to the study of magnetic stimulation in Alzheimer and Parkinson Diseases (AD, PD). The results show the electrical field distribution when magnetic stimulation is supplied to those brain areas of specific interest for each particular disease. Thereby the current approach entails a high potential for the establishment of the current underdeveloped TMS dosimetry in its emerging application to AD and PD. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

Bridging process-based and empirical approaches to modeling tree growth

Science.gov (United States)

Harry T. Valentine; Annikki Makela; Annikki Makela

2005-01-01

The gulf between process-based and empirical approaches to modeling tree growth may be bridged, in part, by the use of a common model. To this end, we have formulated a process-based model of tree growth that can be fitted and applied in an empirical mode. The growth model is grounded in pipe model theory and an optimal control model of crown development. Together, the...

The two-capacitor problem revisited: a mechanical harmonic oscillator model approach

International Nuclear Information System (INIS)

Lee, Keeyung

2009-01-01

The well-known two-capacitor problem, in which exactly half the stored energy disappears when a charged capacitor is connected to an identical capacitor, is discussed based on the mechanical harmonic oscillator model approach. In the mechanical harmonic oscillator model, it is shown first that exactly half the work done by a constant applied force is dissipated irrespective of the form of dissipation mechanism when the system comes to a new equilibrium after a constant force is abruptly applied. This model is then applied to the energy loss mechanism in the capacitor charging problem or the two-capacitor problem. This approach allows a simple explanation of the energy dissipation mechanism in these problems and shows that the dissipated energy should always be exactly half the supplied energy whether that is caused by the Joule heat or by the radiation. This paper, which provides a simple treatment of the energy dissipation mechanism in the two-capacitor problem, is suitable for all undergraduate levels

Embracing uncertainty in applied ecology.

Science.gov (United States)

Milner-Gulland, E J; Shea, K

2017-12-01

Applied ecologists often face uncertainty that hinders effective decision-making.Common traps that may catch the unwary are: ignoring uncertainty, acknowledging uncertainty but ploughing on, focussing on trivial uncertainties, believing your models, and unclear objectives.We integrate research insights and examples from a wide range of applied ecological fields to illustrate advances that are generally underused, but could facilitate ecologists' ability to plan and execute research to support management.Recommended approaches to avoid uncertainty traps are: embracing models, using decision theory, using models more effectively, thinking experimentally, and being realistic about uncertainty. Synthesis and applications . Applied ecologists can become more effective at informing management by using approaches that explicitly take account of uncertainty.

Evaluating tidal marsh sustainability in the face of sea-level rise: a hybrid modeling approach applied to San Francisco Bay.

Directory of Open Access Journals (Sweden)

Diana Stralberg

Full Text Available Tidal marshes will be threatened by increasing rates of sea-level rise (SLR over the next century. Managers seek guidance on whether existing and restored marshes will be resilient under a range of potential future conditions, and on prioritizing marsh restoration and conservation activities.Building upon established models, we developed a hybrid approach that involves a mechanistic treatment of marsh accretion dynamics and incorporates spatial variation at a scale relevant for conservation and restoration decision-making. We applied this model to San Francisco Bay, using best-available elevation data and estimates of sediment supply and organic matter accumulation developed for 15 Bay subregions. Accretion models were run over 100 years for 70 combinations of starting elevation, mineral sediment, organic matter, and SLR assumptions. Results were applied spatially to evaluate eight Bay-wide climate change scenarios.Model results indicated that under a high rate of SLR (1.65 m/century, short-term restoration of diked subtidal baylands to mid marsh elevations (-0.2 m MHHW could be achieved over the next century with sediment concentrations greater than 200 mg/L. However, suspended sediment concentrations greater than 300 mg/L would be required for 100-year mid marsh sustainability (i.e., no elevation loss. Organic matter accumulation had minimal impacts on this threshold. Bay-wide projections of marsh habitat area varied substantially, depending primarily on SLR and sediment assumptions. Across all scenarios, however, the model projected a shift in the mix of intertidal habitats, with a loss of high marsh and gains in low marsh and mudflats.Results suggest a bleak prognosis for long-term natural tidal marsh sustainability under a high-SLR scenario. To minimize marsh loss, we recommend conserving adjacent uplands for marsh migration, redistributing dredged sediment to raise elevations, and concentrating restoration efforts in sediment-rich areas

Applying Petri nets in modelling the human factor

International Nuclear Information System (INIS)

Bedreaga, Luminita; Constntinescu, Cristina; Guzun, Basarab

2007-01-01

Usually, in the reliability analysis performed for complex systems, we determine the success probability to work with other performance indices, i.e. the likelihood associated with a given state. The possible values assigned to system states can be derived using inductive methods. If one wants to calculate the probability to occur a particular event in the system, then deductive methods should be applied. In the particular case of the human reliability analysis, as part of probabilistic safety analysis, the international regulatory commission have developed specific guides and procedures to perform such assessments. The paper presents the modality to obtain the human reliability quantification using the Petri nets approach. This is an efficient means to assess reliability systems because of their specific features. The examples showed in the paper are from human reliability documentation without a detailed human factor analysis (qualitative). We present human action modelling using event trees and Petri nets approach. The obtained results by these two kinds of methods are in good concordance. (authors)

An approach to computing discrete adjoints for MPI-parallelized models applied to Ice Sheet System Model 4.11

Directory of Open Access Journals (Sweden)

E. Larour

2016-11-01

Full Text Available Within the framework of sea-level rise projections, there is a strong need for hindcast validation of the evolution of polar ice sheets in a way that tightly matches observational records (from radar, gravity, and altimetry observations mainly. However, the computational requirements for making hindcast reconstructions possible are severe and rely mainly on the evaluation of the adjoint state of transient ice-flow models. Here, we look at the computation of adjoints in the context of the NASA/JPL/UCI Ice Sheet System Model (ISSM, written in C++ and designed for parallel execution with MPI. We present the adaptations required in the way the software is designed and written, but also generic adaptations in the tools facilitating the adjoint computations. We concentrate on the use of operator overloading coupled with the AdjoinableMPI library to achieve the adjoint computation of the ISSM. We present a comprehensive approach to (1 carry out type changing through the ISSM, hence facilitating operator overloading, (2 bind to external solvers such as MUMPS and GSL-LU, and (3 handle MPI-based parallelism to scale the capability. We demonstrate the success of the approach by computing sensitivities of hindcast metrics such as the misfit to observed records of surface altimetry on the northeastern Greenland Ice Stream, or the misfit to observed records of surface velocities on Upernavik Glacier, central West Greenland. We also provide metrics for the scalability of the approach, and the expected performance. This approach has the potential to enable a new generation of hindcast-validated projections that make full use of the wealth of datasets currently being collected, or already collected, in Greenland and Antarctica.

Developing scenarios to assess future landslide risks: a model-based approach applied to mountainous regions

Science.gov (United States)

Vacquie, Laure; Houet, Thomas

2016-04-01

In the last century, European mountain landscapes have experienced significant transformations. Natural and anthropogenic changes, climate changes, touristic and industrial development, socio-economic interactions, and their implications in terms of LUCC (land use and land cover changes) have directly influenced the spatial organization and vulnerability of mountain landscapes. This study is conducted as part of the SAMCO project founded by the French National Science Agency (ANR). It aims at developing a methodological approach, combining various tools, modelling platforms and methods, to identify vulnerable regions to landslide hazards accounting for futures LUCC. It presents an integrated approach combining participative scenarios and a LULC changes simulation models to assess the combined effects of LUCC and climate change on landslide risks in the Cauterets valley (French Pyrenees Mountains) up to 2100. Through vulnerability and risk mapping, the objective is to gather information to support landscape planning and implement land use strategies with local stakeholders for risk management. Four contrasting scenarios are developed and exhibit contrasting trajectories of socio-economic development. Prospective scenarios are based on national and international socio-economic contexts relying on existing assessment reports. The methodological approach integrates knowledge from local stakeholders to refine each scenario during their construction and to reinforce their plausibility and relevance by accounting for local specificities, e.g. logging and pastoral activities, touristic development, urban planning, etc. A process-based model, the Forecasting Scenarios for Mountains (ForeSceM) model, developed on the Dinamica Ego modelling platform is used to spatially allocate futures LUCC for each prospective scenario. Concurrently, a spatial decision support tool, i.e. the SYLVACCESS model, is used to identify accessible areas for forestry in scenario projecting logging

An Alternative Approach to the Extended Drude Model

Science.gov (United States)

Gantzler, N. J.; Dordevic, S. V.

2018-05-01

The original Drude model, proposed over a hundred years ago, is still used today for the analysis of optical properties of solids. Within this model, both the plasma frequency and quasiparticle scattering rate are constant, which makes the model rather inflexible. In order to circumvent this problem, the so-called extended Drude model was proposed, which allowed for the frequency dependence of both the quasiparticle scattering rate and the effective mass. In this work we will explore an alternative approach to the extended Drude model. Here, one also assumes that the quasiparticle scattering rate is frequency dependent; however, instead of the effective mass, the plasma frequency becomes frequency-dependent. This alternative model is applied to the high Tc superconductor Bi2Sr2CaCu2O8+δ (Bi2212) with Tc = 92 K, and the results are compared and contrasted with the ones obtained from the conventional extended Drude model. The results point to several advantages of this alternative approach to the extended Drude model.

Challenges and opportunities for integrating lake ecosystem modelling approaches

Science.gov (United States)

Mooij, Wolf M.; Trolle, Dennis; Jeppesen, Erik; Arhonditsis, George; Belolipetsky, Pavel V.; Chitamwebwa, Deonatus B.R.; Degermendzhy, Andrey G.; DeAngelis, Donald L.; Domis, Lisette N. De Senerpont; Downing, Andrea S.; Elliott, J. Alex; Ruberto, Carlos Ruberto; Gaedke, Ursula; Genova, Svetlana N.; Gulati, Ramesh D.; Hakanson, Lars; Hamilton, David P.; Hipsey, Matthew R.; Hoen, Jochem 't; Hulsmann, Stephan; Los, F. Hans; Makler-Pick, Vardit; Petzoldt, Thomas; Prokopkin, Igor G.; Rinke, Karsten; Schep, Sebastiaan A.; Tominaga, Koji; Van Dam, Anne A.; Van Nes, Egbert H.; Wells, Scott A.; Janse, Jan H.

2010-01-01

A large number and wide variety of lake ecosystem models have been developed and published during the past four decades. We identify two challenges for making further progress in this field. One such challenge is to avoid developing more models largely following the concept of others ('reinventing the wheel'). The other challenge is to avoid focusing on only one type of model, while ignoring new and diverse approaches that have become available ('having tunnel vision'). In this paper, we aim at improving the awareness of existing models and knowledge of concurrent approaches in lake ecosystem modelling, without covering all possible model tools and avenues. First, we present a broad variety of modelling approaches. To illustrate these approaches, we give brief descriptions of rather arbitrarily selected sets of specific models. We deal with static models (steady state and regression models), complex dynamic models (CAEDYM, CE-QUAL-W2, Delft 3D-ECO, LakeMab, LakeWeb, MyLake, PCLake, PROTECH, SALMO), structurally dynamic models and minimal dynamic models. We also discuss a group of approaches that could all be classified as individual based: super-individual models (Piscator, Charisma), physiologically structured models, stage-structured models and trait-based models. We briefly mention genetic algorithms, neural networks, Kalman filters and fuzzy logic. Thereafter, we zoom in, as an in-depth example, on the multi-decadal development and application of the lake ecosystem model PCLake and related models (PCLake Metamodel, Lake Shira Model, IPH-TRIM3D-PCLake). In the discussion, we argue that while the historical development of each approach and model is understandable given its 'leading principle', there are many opportunities for combining approaches. We take the point of view that a single 'right' approach does not exist and should not be strived for. Instead, multiple modelling approaches, applied concurrently to a given problem, can help develop an integrative

Applied impulsive mathematical models

CERN Document Server

Stamova, Ivanka

2016-01-01

Using the theory of impulsive differential equations, this book focuses on mathematical models which reflect current research in biology, population dynamics, neural networks and economics. The authors provide the basic background from the fundamental theory and give a systematic exposition of recent results related to the qualitative analysis of impulsive mathematical models. Consisting of six chapters, the book presents many applicable techniques, making them available in a single source easily accessible to researchers interested in mathematical models and their applications. Serving as a valuable reference, this text is addressed to a wide audience of professionals, including mathematicians, applied researchers and practitioners.

Software sensors based on the grey-box modelling approach

DEFF Research Database (Denmark)

Carstensen, J.; Harremoës, P.; Strube, Rune

1996-01-01

In recent years the grey-box modelling approach has been applied to wastewater transportation and treatment Grey-box models are characterized by the combination of deterministic and stochastic terms to form a model where all the parameters are statistically identifiable from the on......-box model for the specific dynamics is identified. Similarly, an on-line software sensor for detecting the occurrence of backwater phenomena can be developed by comparing the dynamics of a flow measurement with a nearby level measurement. For treatment plants it is found that grey-box models applied to on......-line measurements. With respect to the development of software sensors, the grey-box models possess two important features. Firstly, the on-line measurements can be filtered according to the grey-box model in order to remove noise deriving from the measuring equipment and controlling devices. Secondly, the grey...

A steady state thermal duct model derived by fin-theory approach and applied on an unglazed solar collector

Energy Technology Data Exchange (ETDEWEB)

Stojanovic, B.; Hallberg, D.; Akander, J. [Building Materials Technology, KTH Research School, Centre for Built Environment, University of Gaevle, SE-801 76 Gaevle (Sweden)

2010-10-15

This paper presents the thermal modelling of an unglazed solar collector (USC) flat panel, with the aim of producing a detailed yet swift thermal steady-state model. The model is analytical, one-dimensional (1D) and derived by a fin-theory approach. It represents the thermal performance of an arbitrary duct with applied boundary conditions equal to those of a flat panel collector. The derived model is meant to be used for efficient optimisation and design of USC flat panels (or similar applications), as well as detailed thermal analysis of temperature fields and heat transfer distributions/variations at steady-state conditions; without requiring a large amount of computational power and time. Detailed surface temperatures are necessary features for durability studies of the surface coating, hence the effect of coating degradation on USC and system performance. The model accuracy and proficiency has been benchmarked against a detailed three-dimensional Finite Difference Model (3D FDM) and two simpler 1D analytical models. Results from the benchmarking test show that the fin-theory model has excellent capabilities of calculating energy performances and fluid temperature profiles, as well as detailed material temperature fields and heat transfer distributions/variations (at steady-state conditions), while still being suitable for component analysis in junction to system simulations as the model is analytical. The accuracy of the model is high in comparison to the 3D FDM (the prime benchmark), as long as the fin-theory assumption prevails (no 'or negligible' temperature gradient in the fin perpendicularly to the fin length). Comparison with the other models also shows that when the USC duct material has a high thermal conductivity, the cross-sectional material temperature adopts an isothermal state (for the assessed USC duct geometry), which makes the 1D isothermal model valid. When the USC duct material has a low thermal conductivity, the heat transfer

Views on Montessori Approach by Teachers Serving at Schools Applying the Montessori Approach

Science.gov (United States)

Atli, Sibel; Korkmaz, A. Merve; Tastepe, Taskin; Koksal Akyol, Aysel

2016-01-01

Problem Statement: Further studies on Montessori teachers are required on the grounds that the Montessori approach, which, having been applied throughout the world, holds an important place in the alternative education field. Yet it is novel for Turkey, and there are only a limited number of studies on Montessori teachers in Turkey. Purpose of…

A model-based approach to on-line process disturbance management

International Nuclear Information System (INIS)

Kim, I.S.

1988-01-01

The methodology developed can be applied to the design of a real-time expert system to aid control-room operators in coping with process abnormalities. The approach encompasses diverse functional aspects required for an effective on-line process disturbance management: (1) intelligent process monitoring and alarming, (2) on-line sensor data validation, (3) on-line sensor and hardware (except sensors) fault diagnosis, and (4) real-time corrective measure synthesis. Accomplishment of these functions is made possible through the application of various models, goal-tree success-tree, process monitor-tree, sensor failure diagnosis, and hardware failure diagnosis models. The models used in the methodology facilitate not only the knowledge-acquisition process - a bottleneck in the development of an expert system - but also the reasoning process of the knowledge-based system. These transparent models and model-based reasoning significantly enhance the maintainability of the real-time expert systems. The proposed approach was applied to the feedwater control system of a nuclear power plant, and implemented into a real-time expert system, MOAS II, using the expert system shell, PICON, on the LMI machine

The development of a curved beam element model applied to finite elements method

International Nuclear Information System (INIS)

Bento Filho, A.

1980-01-01

A procedure for the evaluation of the stiffness matrix for a thick curved beam element is developed, by means of the minimum potential energy principle, applied to finite elements. The displacement field is prescribed through polynomial expansions, and the interpolation model is determined by comparison of results obtained by the use of a sample of different expansions. As a limiting case of the curved beam, three cases of straight beams, with different dimensional ratios are analised, employing the approach proposed. Finally, an interpolation model is proposed and applied to a curved beam with great curvature. Desplacements and internal stresses are determined and the results are compared with those found in the literature. (Author) [pt

Active lubrication applied to radial gas journal bearings. Part 2: Modelling improvement and experimental validation

DEFF Research Database (Denmark)

Pierart, Fabián G.; Santos, Ilmar F.

2016-01-01

Actively-controlled lubrication techniques are applied to radial gas bearings aiming at enhancing one of their most critical drawbacks, their lack of damping. A model-based control design approach is presented using simple feedback control laws, i.e. proportional controllers. The design approach...... by finite element method and the global model is used as control design tool. Active lubrication allows for significant increase in damping factor of the rotor-bearing system. Very good agreement between theory and experiment is obtained, supporting the multi-physic design tool developed....

A robust quantitative near infrared modeling approach for blend monitoring.

Science.gov (United States)

Mohan, Shikhar; Momose, Wataru; Katz, Jeffrey M; Hossain, Md Nayeem; Velez, Natasha; Drennen, James K; Anderson, Carl A

2018-01-30

This study demonstrates a material sparing Near-Infrared modeling approach for powder blend monitoring. In this new approach, gram scale powder mixtures are subjected to compression loads to simulate the effect of scale using an Instron universal testing system. Models prepared by the new method development approach (small-scale method) and by a traditional method development (blender-scale method) were compared by simultaneously monitoring a 1kg batch size blend run. Both models demonstrated similar model performance. The small-scale method strategy significantly reduces the total resources expended to develop Near-Infrared calibration models for on-line blend monitoring. Further, this development approach does not require the actual equipment (i.e., blender) to which the method will be applied, only a similar optical interface. Thus, a robust on-line blend monitoring method can be fully developed before any large-scale blending experiment is viable, allowing the blend method to be used during scale-up and blend development trials. Copyright © 2017. Published by Elsevier B.V.

NEURO-FUZZY MODELING APPLIED IN PROGRAM MANAGEMENT TO INCREASE LOCAL PUBLIC ADMINISTRATION PERFORMANCE

Directory of Open Access Journals (Sweden)

Adrian-Mihai Zaharia-Radulescu

2016-07-01

Full Text Available One of the challenges in local public administration is dealing with an increasing number of competing requests coming from the communities they serve. The traditional approach would be to handle each request as a standalone project and be prioritized according to benefits and budget available. More and more nowadays program management is becoming a standard approach in managing the initiatives of local public administration. Program management approach is itself an enabler for performance in public sector organizations by allowing an organization to better coordinate its efforts and resources in managing a portfolio of projects. This paper aims to present how neuro-fuzzy modeling applied in program management can help an organization to increase its performance. Neuro-fuzzy modeling would lead organizations one step further by allowing them to simulate different scenarios and manage better the risks accompanying their initiatives. The research done by the authors is theoretical and combines knowledge from different areas and a neuro-fuzzy model is proposed and discussed.

Applied Bayesian modelling

CERN Document Server

Congdon, Peter

2014-01-01

This book provides an accessible approach to Bayesian computing and data analysis, with an emphasis on the interpretation of real data sets. Following in the tradition of the successful first edition, this book aims to make a wide range of statistical modeling applications accessible using tested code that can be readily adapted to the reader's own applications. The second edition has been thoroughly reworked and updated to take account of advances in the field. A new set of worked examples is included. The novel aspect of the first edition was the coverage of statistical modeling using WinBU

A MATHEMATICAL MODELLING APPROACH TO ONE-DAY CRICKET BATTING ORDERS

Directory of Open Access Journals (Sweden)

Matthews Ovens1

2006-12-01

Full Text Available While scoring strategies and player performance in cricket have been studied, there has been little published work about the influence of batting order with respect to One-Day cricket. We apply a mathematical modelling approach to compute efficiently the expected performance (runs distribution of a cricket batting order in an innings. Among other applications, our method enables one to solve for the probability of one team beating another or to find the optimal batting order for a set of 11 players. The influence of defence and bowling ability can be taken into account in a straightforward manner. In this presentation, we outline how we develop our Markov Chain approach to studying the progress of runs for a batting order of non- identical players along the lines of work in baseball modelling by Bukiet et al., 1997. We describe the issues that arise in applying such methods to cricket, discuss ideas for addressing these difficulties and note limitations on modelling batting order for One-Day cricket. By performing our analysis on a selected subset of the possible batting orders, we apply the model to quantify the influence of batting order in a game of One Day cricket using available real-world data for current players

Generalized structured component analysis a component-based approach to structural equation modeling

CERN Document Server

Hwang, Heungsun

2014-01-01

Winner of the 2015 Sugiyama Meiko Award (Publication Award) of the Behaviormetric Society of Japan Developed by the authors, generalized structured component analysis is an alternative to two longstanding approaches to structural equation modeling: covariance structure analysis and partial least squares path modeling. Generalized structured component analysis allows researchers to evaluate the adequacy of a model as a whole, compare a model to alternative specifications, and conduct complex analyses in a straightforward manner. Generalized Structured Component Analysis: A Component-Based Approach to Structural Equation Modeling provides a detailed account of this novel statistical methodology and its various extensions. The authors present the theoretical underpinnings of generalized structured component analysis and demonstrate how it can be applied to various empirical examples. The book enables quantitative methodologists, applied researchers, and practitioners to grasp the basic concepts behind this new a...

Applying the Network Simulation Method for testing chaos in a resistively and capacitively shunted Josephson junction model

Directory of Open Access Journals (Sweden)

Fernando Gimeno Bellver

Full Text Available In this paper, we explore the chaotic behavior of resistively and capacitively shunted Josephson junctions via the so-called Network Simulation Method. Such a numerical approach establishes a formal equivalence among physical transport processes and electrical networks, and hence, it can be applied to efficiently deal with a wide range of differential systems.The generality underlying that electrical equivalence allows to apply the circuit theory to several scientific and technological problems. In this work, the Fast Fourier Transform has been applied for chaos detection purposes and the calculations have been carried out in PSpice, an electrical circuit software.Overall, it holds that such a numerical approach leads to quickly computationally solve Josephson differential models. An empirical application regarding the study of the Josephson model completes the paper. Keywords: Electrical analogy, Network Simulation Method, Josephson junction, Chaos indicator, Fast Fourier Transform

multi-scale data assimilation approaches and error characterisation applied to the inverse modelling of atmospheric constituent emission fields

International Nuclear Information System (INIS)

Koohkan, Mohammad Reza

2012-01-01

Data assimilation in geophysical sciences aims at optimally estimating the state of the system or some parameters of the system's physical model. To do so, data assimilation needs three types of information: observations and background information, a physical/numerical model, and some statistical description that prescribes uncertainties to each component of the system. In my dissertation, new methodologies of data assimilation are used in atmospheric chemistry and physics: the joint use of a 4D-Var with a sub-grid statistical model to consistently account for representativeness errors, accounting for multiple scale in the BLUE estimation principle, and a better estimation of prior errors using objective estimation of hyper-parameters. These three approaches will be specifically applied to inverse modelling problems focusing on the emission fields of tracers or pollutants. First, in order to estimate the emission inventories of carbon monoxide over France, in-situ stations which are impacted by the representativeness errors are used. A sub-grid model is introduced and coupled with a 4D-Var to reduce the representativeness error. Indeed, the results of inverse modelling showed that the 4D-Var routine was not fit to handle the representativeness issues. The coupled data assimilation system led to a much better representation of the CO concentration variability, with a significant improvement of statistical indicators, and more consistent estimation of the CO emission inventory. Second, the evaluation of the potential of the IMS (International Monitoring System) radionuclide network is performed for the inversion of an accidental source. In order to assess the performance of the global network, a multi-scale adaptive grid is optimised using a criterion based on degrees of freedom for the signal (DFS). The results show that several specific regions remain poorly observed by the IMS network. Finally, the inversion of the surface fluxes of Volatile Organic Compounds

Experimental designs for autoregressive models applied to industrial maintenance

International Nuclear Information System (INIS)

Amo-Salas, M.; López-Fidalgo, J.; Pedregal, D.J.

2015-01-01

Some time series applications require data which are either expensive or technically difficult to obtain. In such cases scheduling the points in time at which the information should be collected is of paramount importance in order to optimize the resources available. In this paper time series models are studied from a new perspective, consisting in the use of Optimal Experimental Design setup to obtain the best times to take measurements, with the principal aim of saving costs or discarding useless information. The model and the covariance function are expressed in an explicit form to apply the usual techniques of Optimal Experimental Design. Optimal designs for various approaches are computed and their efficiencies are compared. The methods working in an application of industrial maintenance of a critical piece of equipment at a petrochemical plant are shown. This simple model allows explicit calculations in order to show openly the procedure to find the correlation structure, needed for computing the optimal experimental design. In this sense the techniques used in this paper to compute optimal designs may be transferred to other situations following the ideas of the paper, but taking into account the increasing difficulty of the procedure for more complex models. - Highlights: • Optimal experimental design theory is applied to AR models to reduce costs. • The first observation has an important impact on any optimal design. • Either the lack of precision or small starting observations claim for large times. • Reasonable optimal times were obtained relaxing slightly the efficiency. • Optimal designs were computed in a predictive maintenance context

Applying Emax model and bivariate thin plate splines to assess drug interactions.

Science.gov (United States)

Kong, Maiying; Lee, J Jack

2010-01-01

We review the semiparametric approach previously proposed by Kong and Lee and extend it to a case in which the dose-effect curves follow the Emax model instead of the median effect equation. When the maximum effects for the investigated drugs are different, we provide a procedure to obtain the additive effect based on the Loewe additivity model. Then, we apply a bivariate thin plate spline approach to estimate the effect beyond additivity along with its 95 per cent point-wise confidence interval as well as its 95 per cent simultaneous confidence interval for any combination dose. Thus, synergy, additivity, and antagonism can be identified. The advantages of the method are that it provides an overall assessment of the combination effect on the entire two-dimensional dose space spanned by the experimental doses, and it enables us to identify complex patterns of drug interaction in combination studies. In addition, this approach is robust to outliers. To illustrate this procedure, we analyzed data from two case studies.

A general diagnostic model applied to language testing data.

Science.gov (United States)

von Davier, Matthias

2008-11-01

Probabilistic models with one or more latent variables are designed to report on a corresponding number of skills or cognitive attributes. Multidimensional skill profiles offer additional information beyond what a single test score can provide, if the reported skills can be identified and distinguished reliably. Many recent approaches to skill profile models are limited to dichotomous data and have made use of computationally intensive estimation methods such as Markov chain Monte Carlo, since standard maximum likelihood (ML) estimation techniques were deemed infeasible. This paper presents a general diagnostic model (GDM) that can be estimated with standard ML techniques and applies to polytomous response variables as well as to skills with two or more proficiency levels. The paper uses one member of a larger class of diagnostic models, a compensatory diagnostic model for dichotomous and partial credit data. Many well-known models, such as univariate and multivariate versions of the Rasch model and the two-parameter logistic item response theory model, the generalized partial credit model, as well as a variety of skill profile models, are special cases of this GDM. In addition to an introduction to this model, the paper presents a parameter recovery study using simulated data and an application to real data from the field test for TOEFL Internet-based testing.

Dynamics and control of quadcopter using linear model predictive control approach

Science.gov (United States)

Islam, M.; Okasha, M.; Idres, M. M.

2017-12-01

This paper investigates the dynamics and control of a quadcopter using the Model Predictive Control (MPC) approach. The dynamic model is of high fidelity and nonlinear, with six degrees of freedom that include disturbances and model uncertainties. The control approach is developed based on MPC to track different reference trajectories ranging from simple ones such as circular to complex helical trajectories. In this control technique, a linearized model is derived and the receding horizon method is applied to generate the optimal control sequence. Although MPC is computer expensive, it is highly effective to deal with the different types of nonlinearities and constraints such as actuators’ saturation and model uncertainties. The MPC parameters (control and prediction horizons) are selected by trial-and-error approach. Several simulation scenarios are performed to examine and evaluate the performance of the proposed control approach using MATLAB and Simulink environment. Simulation results show that this control approach is highly effective to track a given reference trajectory.

An integrated modeling approach to age invariant face recognition

Science.gov (United States)

Alvi, Fahad Bashir; Pears, Russel

2015-03-01

This Research study proposes a novel method for face recognition based on Anthropometric features that make use of an integrated approach comprising of a global and personalized models. The system is aimed to at situations where lighting, illumination, and pose variations cause problems in face recognition. A Personalized model covers the individual aging patterns while a Global model captures general aging patterns in the database. We introduced a de-aging factor that de-ages each individual in the database test and training sets. We used the k nearest neighbor approach for building a personalized model and global model. Regression analysis was applied to build the models. During the test phase, we resort to voting on different features. We used FG-Net database for checking the results of our technique and achieved 65 percent Rank 1 identification rate.

Software engineering techniques applied to agricultural systems an object-oriented and UML approach

CERN Document Server

Papajorgji, Petraq J

2014-01-01

Software Engineering Techniques Applied to Agricultural Systems presents cutting-edge software engineering techniques for designing and implementing better agricultural software systems based on the object-oriented paradigm and the Unified Modeling Language (UML). The focus is on the presentation of  rigorous step-by-step approaches for modeling flexible agricultural and environmental systems, starting with a conceptual diagram representing elements of the system and their relationships. Furthermore, diagrams such as sequential and collaboration diagrams are used to explain the dynamic and static aspects of the software system.    This second edition includes: a new chapter on Object Constraint Language (OCL), a new section dedicated to the Model-VIEW-Controller (MVC) design pattern, new chapters presenting details of two MDA-based tools – the Virtual Enterprise and Olivia Nova, and a new chapter with exercises on conceptual modeling.  It may be highly useful to undergraduate and graduate students as t...

Applying the Sport Education Model to Tennis

Science.gov (United States)

Ayvazo, Shiri

2009-01-01

The physical education field abounds with theoretically sound curricular approaches such as fitness education, skill theme approach, tactical approach, and sport education. In an era that emphasizes authentic sport experiences, the Sport Education Model includes unique features that sets it apart from other curricular models and can be a valuable…

SLS Navigation Model-Based Design Approach

Science.gov (United States)

Oliver, T. Emerson; Anzalone, Evan; Geohagan, Kevin; Bernard, Bill; Park, Thomas

2018-01-01

The SLS Program chose to implement a Model-based Design and Model-based Requirements approach for managing component design information and system requirements. This approach differs from previous large-scale design efforts at Marshall Space Flight Center where design documentation alone conveyed information required for vehicle design and analysis and where extensive requirements sets were used to scope and constrain the design. The SLS Navigation Team has been responsible for the Program-controlled Design Math Models (DMMs) which describe and represent the performance of the Inertial Navigation System (INS) and the Rate Gyro Assemblies (RGAs) used by Guidance, Navigation, and Controls (GN&C). The SLS Navigation Team is also responsible for the navigation algorithms. The navigation algorithms are delivered for implementation on the flight hardware as a DMM. For the SLS Block 1-B design, the additional GPS Receiver hardware is managed as a DMM at the vehicle design level. This paper provides a discussion of the processes and methods used to engineer, design, and coordinate engineering trades and performance assessments using SLS practices as applied to the GN&C system, with a particular focus on the Navigation components. These include composing system requirements, requirements verification, model development, model verification and validation, and modeling and analysis approaches. The Model-based Design and Requirements approach does not reduce the effort associated with the design process versus previous processes used at Marshall Space Flight Center. Instead, the approach takes advantage of overlap between the requirements development and management process, and the design and analysis process by efficiently combining the control (i.e. the requirement) and the design mechanisms. The design mechanism is the representation of the component behavior and performance in design and analysis tools. The focus in the early design process shifts from the development and

Personalization of models with many model parameters: an efficient sensitivity analysis approach.

Science.gov (United States)

Donders, W P; Huberts, W; van de Vosse, F N; Delhaas, T

2015-10-01

Uncertainty quantification and global sensitivity analysis are indispensable for patient-specific applications of models that enhance diagnosis or aid decision-making. Variance-based sensitivity analysis methods, which apportion each fraction of the output uncertainty (variance) to the effects of individual input parameters or their interactions, are considered the gold standard. The variance portions are called the Sobol sensitivity indices and can be estimated by a Monte Carlo (MC) approach (e.g., Saltelli's method [1]) or by employing a metamodel (e.g., the (generalized) polynomial chaos expansion (gPCE) [2, 3]). All these methods require a large number of model evaluations when estimating the Sobol sensitivity indices for models with many parameters [4]. To reduce the computational cost, we introduce a two-step approach. In the first step, a subset of important parameters is identified for each output of interest using the screening method of Morris [5]. In the second step, a quantitative variance-based sensitivity analysis is performed using gPCE. Efficient sampling strategies are introduced to minimize the number of model runs required to obtain the sensitivity indices for models considering multiple outputs. The approach is tested using a model that was developed for predicting post-operative flows after creation of a vascular access for renal failure patients. We compare the sensitivity indices obtained with the novel two-step approach with those obtained from a reference analysis that applies Saltelli's MC method. The two-step approach was found to yield accurate estimates of the sensitivity indices at two orders of magnitude lower computational cost. Copyright © 2015 John Wiley & Sons, Ltd.

An assessment of econometric models applied to fossil fuel power generation

International Nuclear Information System (INIS)

Gracceva, F.; Quercioli, R.

2001-01-01

The main purpose of this report is to provide a general view of those studies, in which the econometric approach is applied to the selection of fuel in fossil fired power generation, focusing the attention to the key role played by the fuel prices. The report consists of a methodological analysis and a survey of the studies available in literature. The methodological analysis allows to assess the adequateness of the econometric approach, in the electrical power utilities policy. With this purpose, the fundamentals of microeconomics, which are the basis of the econometric models, are pointed out and discussed, and then the hypotheses, which are needed to be assumed for complying the economic theory, are verified in their actual implementation in the power generation sector. The survey of the available studies provides a detailed description of the Translog and Logit models, and the results achieved with their application. From these results, the estimated models show to fit the data with good approximation, a certain degree of interfuel substitution and a meaningful reaction to prices on demand side [it

Applying of an Ontology based Modeling Approach to Cultural Heritage Systems

Directory of Open Access Journals (Sweden)

POPOVICI, D.-M.

2011-08-01

Full Text Available Any virtual environment (VE built in a classical way is dedicated to a very specific domain. Its modification or even adaptation to another domain requires an expensive human intervention measured in time and money. This way, the product, that means the VE, returns at the first phases of the development process. In a previous work we proposed an approach that combines domain ontologies and conceptual modeling to construct more accurate VEs. Our method is based on the description of the domain knowledge in a standard format and the assisted creation (using these pieces of knowledge of the VE. This permits the explanation within the virtual reality (VR simulation of the semantic of the whole context and of each object. This knowledge may be then transferred to the public users. In this paper we prove the effectiveness of our method on the construction process of an VE that simulates the organization of a Greek-Roman colony situated on the Black Sea coast and the economic and social activities of its people.

Mechatronics by bond graphs an object-oriented approach to modelling and simulation

CERN Document Server

Damić, Vjekoslav

2015-01-01

This book presents a computer-aided approach to the design of mechatronic systems. Its subject is an integrated modeling and simulation in a visual computer environment. Since the first edition, the simulation software changed enormously, became more user-friendly and easier to use. Therefore, a second edition became necessary taking these improvements into account. The modeling is based on system top-down and bottom-up approach. The mathematical models are generated in a form of differential-algebraic equations and solved using numerical and symbolic algebra methods. The integrated approach developed is applied to mechanical, electrical and control systems, multibody dynamics, and continuous systems. .

Comparison of the Modeling Approach between Membrane Bioreactor and Conventional Activated Sludge Processes

DEFF Research Database (Denmark)

Jiang, Tao; Sin, Gürkan; Spanjers, Henri

2009-01-01

Activated sludge models (ASM) have been developed and largely applied in conventional activated sludge (CAS) systems. The applicability of ASM to model membrane bioreactors (MBR) and the differences in modeling approaches have not been studied in detail. A laboratory-scale MBR was modeled using ASM...

A model-data based systems approach to process intensification

DEFF Research Database (Denmark)

Gani, Rafiqul

. Their developments, however, are largely due to experiment based trial and error approaches and while they do not require validation, they can be time consuming and resource intensive. Also, one may ask, can a truly new intensified unit operation be obtained in this way? An alternative two-stage approach is to apply...... a model-based synthesis method to systematically generate and evaluate alternatives in the first stage and an experiment-model based validation in the second stage. In this way, the search for alternatives is done very quickly, reliably and systematically over a wide range, while resources are preserved...... for focused validation of only the promising candidates in the second-stage. This approach, however, would be limited to intensification based on “known” unit operations, unless the PI process synthesis/design is considered at a lower level of aggregation, namely the phenomena level. That is, the model-based...

Population Modeling Approach to Optimize Crop Harvest Strategy. The Case of Field Tomato.

Science.gov (United States)

Tran, Dinh T; Hertog, Maarten L A T M; Tran, Thi L H; Quyen, Nguyen T; Van de Poel, Bram; Mata, Clara I; Nicolaï, Bart M

2017-01-01

In this study, the aim is to develop a population model based approach to optimize fruit harvesting strategies with regard to fruit quality and its derived economic value. This approach was applied to the case of tomato fruit harvesting under Vietnamese conditions. Fruit growth and development of tomato (cv. "Savior") was monitored in terms of fruit size and color during both the Vietnamese winter and summer growing seasons. A kinetic tomato fruit growth model was applied to quantify biological fruit-to-fruit variation in terms of their physiological maturation. This model was successfully calibrated. Finally, the model was extended to translate the fruit-to-fruit variation at harvest into the economic value of the harvested crop. It can be concluded that a model based approach to the optimization of harvest date and harvest frequency with regard to economic value of the crop as such is feasible. This approach allows growers to optimize their harvesting strategy by harvesting the crop at more uniform maturity stages meeting the stringent retail demands for homogeneous high quality product. The total farm profit would still depend on the impact a change in harvesting strategy might have on related expenditures. This model based harvest optimisation approach can be easily transferred to other fruit and vegetable crops improving homogeneity of the postharvest product streams.

Eutrophication Modeling Using Variable Chlorophyll Approach

International Nuclear Information System (INIS)

Abdolabadi, H.; Sarang, A.; Ardestani, M.; Mahjoobi, E.

2016-01-01

In this study, eutrophication was investigated in Lake Ontario to identify the interactions among effective drivers. The complexity of such phenomenon was modeled using a system dynamics approach based on a consideration of constant and variable stoichiometric ratios. The system dynamics approach is a powerful tool for developing object-oriented models to simulate complex phenomena that involve feedback effects. Utilizing stoichiometric ratios is a method for converting the concentrations of state variables. During the physical segmentation of the model, Lake Ontario was divided into two layers, i.e., the epilimnion and hypolimnion, and differential equations were developed for each layer. The model structure included 16 state variables related to phytoplankton, herbivorous zooplankton, carnivorous zooplankton, ammonium, nitrate, dissolved phosphorus, and particulate and dissolved carbon in the epilimnion and hypolimnion during a time horizon of one year. The results of several tests to verify the model, close to 1 Nash-Sutcliff coefficient (0.98), the data correlation coefficient (0.98), and lower standard errors (0.96), have indicated well-suited model’s efficiency. The results revealed that there were significant differences in the concentrations of the state variables in constant and variable stoichiometry simulations. Consequently, the consideration of variable stoichiometric ratios in algae and nutrient concentration simulations may be applied in future modeling studies to enhance the accuracy of the results and reduce the likelihood of inefficient control policies.

Maximum likelihood approach for several stochastic volatility models

International Nuclear Information System (INIS)

Camprodon, Jordi; Perelló, Josep

2012-01-01

Volatility measures the amplitude of price fluctuations. Despite it being one of the most important quantities in finance, volatility is not directly observable. Here we apply a maximum likelihood method which assumes that price and volatility follow a two-dimensional diffusion process where volatility is the stochastic diffusion coefficient of the log-price dynamics. We apply this method to the simplest versions of the expOU, the OU and the Heston stochastic volatility models and we study their performance in terms of the log-price probability, the volatility probability, and its Mean First-Passage Time. The approach has some predictive power on the future returns amplitude by only knowing the current volatility. The assumed models do not consider long-range volatility autocorrelation and the asymmetric return-volatility cross-correlation but the method still yields very naturally these two important stylized facts. We apply the method to different market indices and with a good performance in all cases. (paper)

A whole-of-curriculum approach to improving nursing students' applied numeracy skills.

Science.gov (United States)

van de Mortel, Thea F; Whitehair, Leeann P; Irwin, Pauletta M

2014-03-01

Nursing students often perform poorly on numeracy tests. Whilst one-off interventions have been trialled with limited success, a whole-of-curriculum approach may provide a better means of improving applied numeracy skills. The objective of the study is to assess the efficacy of a whole-of-curriculum approach in improving nursing students' applied numeracy skills. Two cycles of assessment, implementation and evaluation of strategies were conducted following a high fail rate in the final applied numeracy examination in a Bachelor of Nursing (BN) programme. Strategies included an early diagnostic assessment followed by referral to remediation, setting the pass mark at 100% for each of six applied numeracy examinations across the programme, and employing a specialist mathematics teacher to provide consistent numeracy teaching. The setting of the study is one Australian university. 1035 second and third year nursing students enrolled in four clinical nursing courses (CNC III, CNC IV, CNC V and CNC VI) were included. Data on the percentage of students who obtained 100% in their applied numeracy examination in up to two attempts were collected from CNCs III, IV, V and VI between 2008 and 2011. A four by two χ(2) contingency table was used to determine if the differences in the proportion of students achieving 100% across two examination attempts in each CNC were significantly different between 2008 and 2011. The percentage of students who obtained 100% correct answers on the applied numeracy examinations was significantly higher in 2011 than in 2008 in CNC III (χ(2)=272, 3; p<0.001), IV (χ(2)=94.7, 3; p<0.001) and VI (χ(2)=76.3, 3; p<0.001). A whole-of-curriculum approach to developing applied numeracy skills in BN students resulted in a substantial improvement in these skills over four years. Copyright © 2013 Elsevier Ltd. All rights reserved.

Model output statistics applied to wind power prediction

Energy Technology Data Exchange (ETDEWEB)

Joensen, A; Giebel, G; Landberg, L [Risoe National Lab., Roskilde (Denmark); Madsen, H; Nielsen, H A [The Technical Univ. of Denmark, Dept. of Mathematical Modelling, Lyngby (Denmark)

1999-03-01

Being able to predict the output of a wind farm online for a day or two in advance has significant advantages for utilities, such as better possibility to schedule fossil fuelled power plants and a better position on electricity spot markets. In this paper prediction methods based on Numerical Weather Prediction (NWP) models are considered. The spatial resolution used in NWP models implies that these predictions are not valid locally at a specific wind farm. Furthermore, due to the non-stationary nature and complexity of the processes in the atmosphere, and occasional changes of NWP models, the deviation between the predicted and the measured wind will be time dependent. If observational data is available, and if the deviation between the predictions and the observations exhibits systematic behavior, this should be corrected for; if statistical methods are used, this approaches is usually referred to as MOS (Model Output Statistics). The influence of atmospheric turbulence intensity, topography, prediction horizon length and auto-correlation of wind speed and power is considered, and to take the time-variations into account, adaptive estimation methods are applied. Three estimation techniques are considered and compared, Extended Kalman Filtering, recursive least squares and a new modified recursive least squares algorithm. (au) EU-JOULE-3. 11 refs.

Dynamic model reduction using data-driven Loewner-framework applied to thermally morphing structures

Science.gov (United States)

Phoenix, Austin A.; Tarazaga, Pablo A.

2017-05-01

The work herein proposes the use of the data-driven Loewner-framework for reduced order modeling as applied to dynamic Finite Element Models (FEM) of thermally morphing structures. The Loewner-based modeling approach is computationally efficient and accurately constructs reduced models using analytical output data from a FEM. This paper details the two-step process proposed in the Loewner approach. First, a random vibration FEM simulation is used as the input for the development of a Single Input Single Output (SISO) data-based dynamic Loewner state space model. Second, an SVD-based truncation is used on the Loewner state space model, such that the minimal, dynamically representative, state space model is achieved. For this second part, varying levels of reduction are generated and compared. The work herein can be extended to model generation using experimental measurements by replacing the FEM output data in the first step and following the same procedure. This method will be demonstrated on two thermally morphing structures, a rigidly fixed hexapod in multiple geometric configurations and a low mass anisotropic morphing boom. This paper is working to detail the method and identify the benefits of the reduced model methodology.

METHODOLOGICAL APPROACHES FOR MODELING THE RURAL SETTLEMENT DEVELOPMENT

Directory of Open Access Journals (Sweden)

Gorbenkova Elena Vladimirovna

2017-10-01

Full Text Available Subject: the paper describes the research results on validation of a rural settlement developmental model. The basic methods and approaches for solving the problem of assessment of the urban and rural settlement development efficiency are considered. Research objectives: determination of methodological approaches to modeling and creating a model for the development of rural settlements. Materials and methods: domestic and foreign experience in modeling the territorial development of urban and rural settlements and settlement structures was generalized. The motivation for using the Pentagon-model for solving similar problems was demonstrated. Based on a systematic analysis of existing development models of urban and rural settlements as well as the authors-developed method for assessing the level of agro-towns development, the systems/factors that are necessary for a rural settlement sustainable development are identified. Results: we created the rural development model which consists of five major systems that include critical factors essential for achieving a sustainable development of a settlement system: ecological system, economic system, administrative system, anthropogenic (physical system and social system (supra-structure. The methodological approaches for creating an evaluation model of rural settlements development were revealed; the basic motivating factors that provide interrelations of systems were determined; the critical factors for each subsystem were identified and substantiated. Such an approach was justified by the composition of tasks for territorial planning of the local and state administration levels. The feasibility of applying the basic Pentagon-model, which was successfully used for solving the analogous problems of sustainable development, was shown. Conclusions: the resulting model can be used for identifying and substantiating the critical factors for rural sustainable development and also become the basis of

Quantitative assessment of key parameters in qualitative vulnerability methods applied in karst systems based on an integrated numerical modelling approach

Science.gov (United States)

Doummar, Joanna; Kassem, Assaad

2017-04-01

In the framework of a three-year PEER (USAID/NSF) funded project, flow in a Karst system in Lebanon (Assal) dominated by snow and semi arid conditions was simulated and successfully calibrated using an integrated numerical model (MIKE-She 2016) based on high resolution input data and detailed catchment characterization. Point source infiltration and fast flow pathways were simulated by a bypass function and a high conductive lens respectively. The approach consisted of identifying all the factors used in qualitative vulnerability methods (COP, EPIK, PI, DRASTIC, GOD) applied in karst systems and to assess their influence on recharge signals in the different hydrological karst compartments (Atmosphere, Unsaturated zone and Saturated zone) based on the integrated numerical model. These parameters are usually attributed different weights according to their estimated impact on Groundwater vulnerability. The aim of this work is to quantify the importance of each of these parameters and outline parameters that are not accounted for in standard methods, but that might play a role in the vulnerability of a system. The spatial distribution of the detailed evapotranspiration, infiltration, and recharge signals from atmosphere to unsaturated zone to saturated zone was compared and contrasted among different surface settings and under varying flow conditions (e.g., in varying slopes, land cover, precipitation intensity, and soil properties as well point source infiltration). Furthermore a sensitivity analysis of individual or coupled major parameters allows quantifying their impact on recharge and indirectly on vulnerability. The preliminary analysis yields a new methodology that accounts for most of the factors influencing vulnerability while refining the weights attributed to each one of them, based on a quantitative approach.

A comparison of various modelling approaches applied to Cholera ...

African Journals Online (AJOL)

linear models, ARIMA time series modelling, and dynamic regression are ... to certain environmental parameters, and to investigate the feasibility of .... in the SSA literature, the term noise is used to refer to both stochastic noise, as well as.

A Methodological Demonstration of Set-theoretical Approach to Social Media Maturity Models Using Necessary Condition Analysis

DEFF Research Database (Denmark)

Lasrado, Lester Allan; Vatrapu, Ravi; Andersen, Kim Normann

2016-01-01

Despite being widely accepted and applied across research domains, maturity models have been criticized for lacking academic rigor, especially methodologically rigorous and empirically grounded or tested maturity models are quite rare. Attempting to close this gap, we adopt a set-theoretic approach...... and evaluate some of arguments presented by previous conceptual focused social media maturity models....... by applying the Necessary Condition Analysis (NCA) technique to derive maturity stages and stage boundaries conditions. The ontology is to view stages (boundaries) in maturity models as a collection of necessary condition. Using social media maturity data, we demonstrate the strength of our approach...

Improving Baseline Model Assumptions: Evaluating the Impacts of Typical Methodological Approaches in Watershed Models

Science.gov (United States)

Muenich, R. L.; Kalcic, M. M.; Teshager, A. D.; Long, C. M.; Wang, Y. C.; Scavia, D.

2017-12-01

Thanks to the availability of open-source software, online tutorials, and advanced software capabilities, watershed modeling has expanded its user-base and applications significantly in the past thirty years. Even complicated models like the Soil and Water Assessment Tool (SWAT) are being used and documented in hundreds of peer-reviewed publications each year, and likely more applied in practice. These models can help improve our understanding of present, past, and future conditions, or analyze important "what-if" management scenarios. However, baseline data and methods are often adopted and applied without rigorous testing. In multiple collaborative projects, we have evaluated the influence of some of these common approaches on model results. Specifically, we examined impacts of baseline data and assumptions involved in manure application, combined sewer overflows, and climate data incorporation across multiple watersheds in the Western Lake Erie Basin. In these efforts, we seek to understand the impact of using typical modeling data and assumptions, versus using improved data and enhanced assumptions on model outcomes and thus ultimately, study conclusions. We provide guidance for modelers as they adopt and apply data and models for their specific study region. While it is difficult to quantitatively assess the full uncertainty surrounding model input data and assumptions, recognizing the impacts of model input choices is important when considering actions at the both the field and watershed scales.

An approach to ductile fracture resistance modelling in pipeline steels

Energy Technology Data Exchange (ETDEWEB)

Pussegoda, L.N.; Fredj, A. [BMT Fleet Technology Ltd., Kanata (Canada)

2009-07-01

Ductile fracture resistance studies of high grade steels in the pipeline industry often included analyses of the crack tip opening angle (CTOA) parameter using 3-point bend steel specimens. The CTOA is a function of specimen ligament size in high grade materials. Other resistance measurements may include steady state fracture propagation energy, critical fracture strain, and the adoption of damage mechanisms. Modelling approaches for crack propagation were discussed in this abstract. Tension tests were used to calibrate damage model parameters. Results from the tests were then applied to the crack propagation in a 3-point bend specimen using modern 1980 vintage steels. Limitations and approaches to overcome the difficulties associated with crack propagation modelling were discussed.

Challenges and Limitations of Applying an Emotion-driven Design Approach on Elderly Users

DEFF Research Database (Denmark)

Andersen, Casper L.; Gudmundsson, Hjalte P.; Achiche, Sofiane

2011-01-01

a competitive advantage for companies. In this paper, challenges of applying an emotion-driven design approach applied on elderly people, in order to identify their user needs towards walking frames, are discussed. The discussion will be based on the experiences and results obtained from the case study...... related to the participants’ age and cognitive abilities. The challenges encountered are discussed and guidelines on what should be taken into account to facilitate an emotion-driven design approach for elderly people are proposed....

Changes in speed distribution: Applying aggregated safety effect models to individual vehicle speeds.

Science.gov (United States)

Vadeby, Anna; Forsman, Åsa

2017-06-01

This study investigated the effect of applying two aggregated models (the Power model and the Exponential model) to individual vehicle speeds instead of mean speeds. This is of particular interest when the measure introduced affects different parts of the speed distribution differently. The aim was to examine how the estimated overall risk was affected when assuming the models are valid on an individual vehicle level. Speed data from two applications of speed measurements were used in the study: an evaluation of movable speed cameras and a national evaluation of new speed limits in Sweden. The results showed that when applied on individual vehicle speed level compared with aggregated level, there was essentially no difference between these for the Power model in the case of injury accidents. However, for fatalities the difference was greater, especially for roads with new cameras where those driving fastest reduced their speed the most. For the case with new speed limits, the individual approach estimated a somewhat smaller effect, reflecting that changes in the 15th percentile (P15) were somewhat larger than changes in P85 in this case. For the Exponential model there was also a clear, although small, difference between applying the model to mean speed changes and individual vehicle speed changes when speed cameras were used. This applied both for injury accidents and fatalities. There were also larger effects for the Exponential model than for the Power model, especially for injury accidents. In conclusion, applying the Power or Exponential model to individual vehicle speeds is an alternative that provides reasonable results in relation to the original Power and Exponential models, but more research is needed to clarify the shape of the individual risk curve. It is not surprising that the impact on severe traffic crashes was larger in situations where those driving fastest reduced their speed the most. Further investigations on use of the Power and/or the

Algebraic approach to small-world network models

Science.gov (United States)

Rudolph-Lilith, Michelle; Muller, Lyle E.

2014-01-01

We introduce an analytic model for directed Watts-Strogatz small-world graphs and deduce an algebraic expression of its defining adjacency matrix. The latter is then used to calculate the small-world digraph's asymmetry index and clustering coefficient in an analytically exact fashion, valid nonasymptotically for all graph sizes. The proposed approach is general and can be applied to all algebraically well-defined graph-theoretical measures, thus allowing for an analytical investigation of finite-size small-world graphs.

Nonlinear models applied to seed germination of Rhipsalis cereuscula Haw (Cactaceae

Directory of Open Access Journals (Sweden)

Terezinha Aparecida Guedes

2014-09-01

Full Text Available The objective of this analysis was to fit germination data of Rhipsalis cereuscula Haw seeds to the Weibull model with three parameters using Frequentist and Bayesian methods. Five parameterizations were compared using the Bayesian analysis to fit a prior distribution. The parameter estimates from the Frequentist method were similar to the Bayesian responses considering the following non-informative a priori distribution for the parameter vectors: gamma (10³, 10³ in the model M1, normal (0, 106 in the model M2, uniform (0, Lsup in the model M3, exp (μ in the model M4 and Lnormal (μ, 106 in the model M5. However, to achieve the convergence in the models M4 and M5, we applied the μ from the estimates of the Frequentist approach. The best models fitted by the Bayesian method were the M1 and M3. The adequacy of these models was based on the advantages over the Frequentist method such as the reduced computational efforts and the possibility of comparison.

Integrated modelling of nitrate loads to coastal waters and land rent applied to catchment scale water management

DEFF Research Database (Denmark)

Jacosen, T.; Refsgaard, A.; Jacobsen, Brian H.

Abstract The EU WFD requires an integrated approach to river basin management in order to meet environmental and ecological objectives. This paper presents concepts and full-scale application of an integrated modelling framework. The Ringkoebing Fjord basin is characterized by intensive agricultu...... in comprehensive, integrated modelling tools.......Abstract The EU WFD requires an integrated approach to river basin management in order to meet environmental and ecological objectives. This paper presents concepts and full-scale application of an integrated modelling framework. The Ringkoebing Fjord basin is characterized by intensive...... agricultural production and leakage of nitrate constitute a major pollution problem with respect groundwater aquifers (drinking water), fresh surface water systems (water quality of lakes) and coastal receiving waters (eutrophication). The case study presented illustrates an advanced modelling approach applied...

A moni-modelling approach to manage groundwater risk to pesticide leaching at regional scale.

Science.gov (United States)

Di Guardo, Andrea; Finizio, Antonio

2016-03-01

Historically, the approach used to manage risk of chemical contamination of water bodies is based on the use of monitoring programmes, which provide a snapshot of the presence/absence of chemicals in water bodies. Monitoring is required in the current EU regulations, such as the Water Framework Directive (WFD), as a tool to record temporal variation in the chemical status of water bodies. More recently, a number of models have been developed and used to forecast chemical contamination of water bodies. These models combine information of chemical properties, their use, and environmental scenarios. Both approaches are useful for risk assessors in decision processes. However, in our opinion, both show flaws and strengths when taken alone. This paper proposes an integrated approach (moni-modelling approach) where monitoring data and modelling simulations work together in order to provide a common decision framework for the risk assessor. This approach would be very useful, particularly for the risk management of pesticides at a territorial level. It fulfils the requirement of the recent Sustainable Use of Pesticides Directive. In fact, the moni-modelling approach could be used to identify sensible areas where implement mitigation measures or limitation of use of pesticides, but even to effectively re-design future monitoring networks or to better calibrate the pedo-climatic input data for the environmental fate models. A case study is presented, where the moni-modelling approach is applied in Lombardy region (North of Italy) to identify groundwater vulnerable areas to pesticides. The approach has been applied to six active substances with different leaching behaviour, in order to highlight the advantages in using the proposed methodology. Copyright © 2015 Elsevier B.V. All rights reserved.

A Monte Carlo approach applied to ultrasonic non-destructive testing

Science.gov (United States)

Mosca, I.; Bilgili, F.; Meier, T.; Sigloch, K.

2012-04-01

Non-destructive testing based on ultrasound allows us to detect, characterize and size discrete flaws in geotechnical and architectural structures and materials. This information is needed to determine whether such flaws can be tolerated in future service. In typical ultrasonic experiments, only the first-arriving P-wave is interpreted, and the remainder of the recorded waveform is neglected. Our work aims at understanding surface waves, which are strong signals in the later wave train, with the ultimate goal of full waveform tomography. At present, even the structural estimation of layered media is still challenging because material properties of the samples can vary widely, and good initial models for inversion do not often exist. The aim of the present study is to combine non-destructive testing with a theoretical data analysis and hence to contribute to conservation strategies of archaeological and architectural structures. We analyze ultrasonic waveforms measured at the surface of a variety of samples, and define the behaviour of surface waves in structures of increasing complexity. The tremendous potential of ultrasonic surface waves becomes an advantage only if numerical forward modelling tools are available to describe the waveforms accurately. We compute synthetic full seismograms as well as group and phase velocities for the data. We invert them for the elastic properties of the sample via a global search of the parameter space, using the Neighbourhood Algorithm. Such a Monte Carlo approach allows us to perform a complete uncertainty and resolution analysis, but the computational cost is high and increases quickly with the number of model parameters. Therefore it is practical only for defining the seismic properties of media with a limited number of degrees of freedom, such as layered structures. We have applied this approach to both synthetic layered structures and real samples. The former contributed to benchmark the propagation of ultrasonic surface

A stepwise approach for defining the applicability domain of SAR and QSAR models

DEFF Research Database (Denmark)

Dimitrov, Sabcho; Dimitrova, Gergana; Pavlov, Todor

2005-01-01

A stepwise approach for determining the model applicability domain is proposed. Four stages are applied to account for the diversity and complexity of the current SAR/QSAR models, reflecting their mechanistic rationality (including metabolic activation of chemicals) and transparency. General para...

Statistical modelling approach to derive quantitative nanowastes classification index; estimation of nanomaterials exposure

CSIR Research Space (South Africa)

Ntaka, L

2013-08-01

Full Text Available . In this work, statistical inference approach specifically the non-parametric bootstrapping and linear model were applied. Data used to develop the model were sourced from the literature. 104 data points with information on aggregation, natural organic matter...

Three novel approaches to structural identifiability analysis in mixed-effects models.

Science.gov (United States)

Janzén, David L I; Jirstrand, Mats; Chappell, Michael J; Evans, Neil D

2016-05-06

Structural identifiability is a concept that considers whether the structure of a model together with a set of input-output relations uniquely determines the model parameters. In the mathematical modelling of biological systems, structural identifiability is an important concept since biological interpretations are typically made from the parameter estimates. For a system defined by ordinary differential equations, several methods have been developed to analyse whether the model is structurally identifiable or otherwise. Another well-used modelling framework, which is particularly useful when the experimental data are sparsely sampled and the population variance is of interest, is mixed-effects modelling. However, established identifiability analysis techniques for ordinary differential equations are not directly applicable to such models. In this paper, we present and apply three different methods that can be used to study structural identifiability in mixed-effects models. The first method, called the repeated measurement approach, is based on applying a set of previously established statistical theorems. The second method, called the augmented system approach, is based on augmenting the mixed-effects model to an extended state-space form. The third method, called the Laplace transform mixed-effects extension, is based on considering the moment invariants of the systems transfer function as functions of random variables. To illustrate, compare and contrast the application of the three methods, they are applied to a set of mixed-effects models. Three structural identifiability analysis methods applicable to mixed-effects models have been presented in this paper. As method development of structural identifiability techniques for mixed-effects models has been given very little attention, despite mixed-effects models being widely used, the methods presented in this paper provides a way of handling structural identifiability in mixed-effects models previously not

A variable age of onset segregation model for linkage analysis, with correction for ascertainment, applied to glioma

DEFF Research Database (Denmark)

Sun, Xiangqing; Vengoechea, Jaime; Elston, Robert

2012-01-01

We propose a 2-step model-based approach, with correction for ascertainment, to linkage analysis of a binary trait with variable age of onset and apply it to a set of multiplex pedigrees segregating for adult glioma....

Multidisciplinary Management: Model of Excellence in the Management Applied to Products and Services

OpenAIRE

Guerreiro , Evandro ,; Costa Neto , Pedro ,; Moreira Filho , Ulysses ,

2014-01-01

Part 1: Knowledge-Based Performance Improvement; International audience; The Multidisciplinary Management is the guiding vision of modern organizations and the systems thinking which requires new approaches to organizational excellence and quality management process. The objective of this article is to present a model for multidisciplinary management of quality applied to products and services based on American, Japanese, and Brazilian National Quality Awards. The methodology used to build th...

A Thermodynamically-consistent FBA-based Approach to Biogeochemical Reaction Modeling

Science.gov (United States)

Shapiro, B.; Jin, Q.

2015-12-01

Microbial rates are critical to understanding biogeochemical processes in natural environments. Recently, flux balance analysis (FBA) has been applied to predict microbial rates in aquifers and other settings. FBA is a genome-scale constraint-based modeling approach that computes metabolic rates and other phenotypes of microorganisms. This approach requires a prior knowledge of substrate uptake rates, which is not available for most natural microbes. Here we propose to constrain substrate uptake rates on the basis of microbial kinetics. Specifically, we calculate rates of respiration (and fermentation) using a revised Monod equation; this equation accounts for both the kinetics and thermodynamics of microbial catabolism. Substrate uptake rates are then computed from the rates of respiration, and applied to FBA to predict rates of microbial growth. We implemented this method by linking two software tools, PHREEQC and COBRA Toolbox. We applied this method to acetotrophic methanogenesis by Methanosarcina barkeri, and compared the simulation results to previous laboratory observations. The new method constrains acetate uptake by accounting for the kinetics and thermodynamics of methanogenesis, and predicted well the observations of previous experiments. In comparison, traditional methods of dynamic-FBA constrain acetate uptake on the basis of enzyme kinetics, and failed to reproduce the experimental results. These results show that microbial rate laws may provide a better constraint than enzyme kinetics for applying FBA to biogeochemical reaction modeling.

A Bayesian Hierarchical Modeling Approach to Predicting Flow in Ungauged Basins

Science.gov (United States)

Gronewold, A.; Alameddine, I.; Anderson, R. M.

2009-12-01

Recent innovative approaches to identifying and applying regression-based relationships between land use patterns (such as increasing impervious surface area and decreasing vegetative cover) and rainfall-runoff model parameters represent novel and promising improvements to predicting flow from ungauged basins. In particular, these approaches allow for predicting flows under uncertain and potentially variable future conditions due to rapid land cover changes, variable climate conditions, and other factors. Despite the broad range of literature on estimating rainfall-runoff model parameters, however, the absence of a robust set of modeling tools for identifying and quantifying uncertainties in (and correlation between) rainfall-runoff model parameters represents a significant gap in current hydrological modeling research. Here, we build upon a series of recent publications promoting novel Bayesian and probabilistic modeling strategies for quantifying rainfall-runoff model parameter estimation uncertainty. Our approach applies alternative measures of rainfall-runoff model parameter joint likelihood (including Nash-Sutcliffe efficiency, among others) to simulate samples from the joint parameter posterior probability density function. We then use these correlated samples as response variables in a Bayesian hierarchical model with land use coverage data as predictor variables in order to develop a robust land use-based tool for forecasting flow in ungauged basins while accounting for, and explicitly acknowledging, parameter estimation uncertainty. We apply this modeling strategy to low-relief coastal watersheds of Eastern North Carolina, an area representative of coastal resource waters throughout the world because of its sensitive embayments and because of the abundant (but currently threatened) natural resources it hosts. Consequently, this area is the subject of several ongoing studies and large-scale planning initiatives, including those conducted through the United

Multi-scale Modeling Approach for Design and Optimization of Oleochemical Processes

DEFF Research Database (Denmark)

Jones, Mark Nicholas; Forero-Hernandez, Hector Alexander; Sarup, Bent

2017-01-01

The primary goal of this work is to present a systematic methodology and software frameworkfor a multi-level approach ranging from process synthesis and modeling throughproperty prediction, to sensitivity analysis, property parameter tuning and optimization.This framework is applied to the follow...

Effective modelling of percolation at the landscape scale using data-based approaches

Science.gov (United States)

Selle, Benny; Lischeid, Gunnar; Huwe, Bernd

2008-06-01

Process-based models have been extensively applied to assess the impact of landuse change on water quantity and quality at landscape scales. However, the routine application of those models suffers from large computational efforts, lack of transparency and the requirement of many input parameters. Data-based models such as Feed-Forward Multilayer Perceptrons (MLP) and Classification and Regression Trees (CART) may be used as effective models, i.e. simple approximations of complex process-based models. These data-based approaches can subsequently be applied for scenario analysis and as a transparent management tool provided climatic boundary conditions and the basic model assumptions of the process-based models do not change dramatically. In this study, we apply MLP, CART and Multiple Linear Regression (LR) to model the spatially distributed and spatially aggregated percolation in soils using weather, groundwater and soil data. The percolation data is obtained via numerical experiments with Hydrus1D. Thus, the complex process-based model is approximated using simpler data-based approaches. The MLP model explains most of the percolation variance in time and space without using any soil information. This reflects the effective dimensionality of the process-based model and suggests that percolation in the study area may be modelled much simpler than using Hydrus1D. The CART model shows that soil properties play a negligible role for percolation under wet climatic conditions. However, they become more important if the conditions turn drier. The LR method does not yield satisfactory predictions for the spatially distributed percolation however the spatially aggregated percolation is well approximated. This may indicate that the soils behave simpler (i.e. more linear) when percolation dynamics are upscaled.

Evaluation model applied to TRANSPETRO's Marine Terminals Standardization Program

Energy Technology Data Exchange (ETDEWEB)

Almeida, Maria Fatima Ludovico de; Mueller, Gabriela [Pontificia Universidade Catolica do Rio de Janeiro (PUC-Rio), Rio de Janeiro, RJ (Brazil). Instituto Tecnologico; Garcia, Luciano Maldonado [TRANSPETRO - PETROBRAS Transporte S.A., Rio de Janeiro, RJ (Brazil)

2009-07-01

This paper describes an innovative evaluation model applied to TRANSPETRO's 'Marine Terminals Standardization Program' based on updating approaches of programs evaluation and organizational learning. Since the program was launched in 2004, the need for having an evaluation model able to evaluate its implementation progress, to measure the degree of standards compliance and its potential economic, social and environmental impacts has become evident. Within a vision of safe and environmentally responsible operations of marine terminals, this evaluation model was jointly designed by TRANSPETRO and PUC-Rio to promote continuous improvement and learning in operational practices and in the standardization process itself. TRANSPETRO believes that standardization supports its services and management innovation capability by creating objective and internationally recognized parameters, targets and metrology for its business activities. The conceptual model and application guidelines for this important tool are presented in this paper, as well as the next steps towards its implementation. (author)

Applying a Global Sensitivity Analysis Workflow to Improve the Computational Efficiencies in Physiologically-Based Pharmacokinetic Modeling

Directory of Open Access Journals (Sweden)

Nan-Hung Hsieh

2018-06-01

Full Text Available Traditionally, the solution to reduce parameter dimensionality in a physiologically-based pharmacokinetic (PBPK model is through expert judgment. However, this approach may lead to bias in parameter estimates and model predictions if important parameters are fixed at uncertain or inappropriate values. The purpose of this study was to explore the application of global sensitivity analysis (GSA to ascertain which parameters in the PBPK model are non-influential, and therefore can be assigned fixed values in Bayesian parameter estimation with minimal bias. We compared the elementary effect-based Morris method and three variance-based Sobol indices in their ability to distinguish “influential” parameters to be estimated and “non-influential” parameters to be fixed. We illustrated this approach using a published human PBPK model for acetaminophen (APAP and its two primary metabolites APAP-glucuronide and APAP-sulfate. We first applied GSA to the original published model, comparing Bayesian model calibration results using all the 21 originally calibrated model parameters (OMP, determined by “expert judgment”-based approach vs. the subset of original influential parameters (OIP, determined by GSA from the OMP. We then applied GSA to all the PBPK parameters, including those fixed in the published model, comparing the model calibration results using this full set of 58 model parameters (FMP vs. the full set influential parameters (FIP, determined by GSA from FMP. We also examined the impact of different cut-off points to distinguish the influential and non-influential parameters. We found that Sobol indices calculated by eFAST provided the best combination of reliability (consistency with other variance-based methods and efficiency (lowest computational cost to achieve convergence in identifying influential parameters. We identified several originally calibrated parameters that were not influential, and could be fixed to improve computational

Model selection and inference a practical information-theoretic approach

CERN Document Server

Burnham, Kenneth P

1998-01-01

This book is unique in that it covers the philosophy of model-based data analysis and an omnibus strategy for the analysis of empirical data The book introduces information theoretic approaches and focuses critical attention on a priori modeling and the selection of a good approximating model that best represents the inference supported by the data Kullback-Leibler information represents a fundamental quantity in science and is Hirotugu Akaike's basis for model selection The maximized log-likelihood function can be bias-corrected to provide an estimate of expected, relative Kullback-Leibler information This leads to Akaike's Information Criterion (AIC) and various extensions and these are relatively simple and easy to use in practice, but little taught in statistics classes and far less understood in the applied sciences than should be the case The information theoretic approaches provide a unified and rigorous theory, an extension of likelihood theory, an important application of information theory, and are ...

Hierarchical mixture of experts and diagnostic modeling approach to reduce hydrologic model structural uncertainty: STRUCTURAL UNCERTAINTY DIAGNOSTICS

Energy Technology Data Exchange (ETDEWEB)

Moges, Edom [Civil and Environmental Engineering Department, Washington State University, Richland Washington USA; Demissie, Yonas [Civil and Environmental Engineering Department, Washington State University, Richland Washington USA; Li, Hong-Yi [Hydrology Group, Pacific Northwest National Laboratory, Richland Washington USA

2016-04-01

In most water resources applications, a single model structure might be inadequate to capture the dynamic multi-scale interactions among different hydrological processes. Calibrating single models for dynamic catchments, where multiple dominant processes exist, can result in displacement of errors from structure to parameters, which in turn leads to over-correction and biased predictions. An alternative to a single model structure is to develop local expert structures that are effective in representing the dominant components of the hydrologic process and adaptively integrate them based on an indicator variable. In this study, the Hierarchical Mixture of Experts (HME) framework is applied to integrate expert model structures representing the different components of the hydrologic process. Various signature diagnostic analyses are used to assess the presence of multiple dominant processes and the adequacy of a single model, as well as to identify the structures of the expert models. The approaches are applied for two distinct catchments, the Guadalupe River (Texas) and the French Broad River (North Carolina) from the Model Parameter Estimation Experiment (MOPEX), using different structures of the HBV model. The results show that the HME approach has a better performance over the single model for the Guadalupe catchment, where multiple dominant processes are witnessed through diagnostic measures. Whereas, the diagnostics and aggregated performance measures prove that French Broad has a homogeneous catchment response, making the single model adequate to capture the response.

Ab initio approach to the non-perturbative scalar Yukawa model

OpenAIRE

Li, YangDepartment of Physics and Astronomy, Iowa State University, Ames, IA, 50011, USA; Karmanov, V.A.(Lebedev Physical Institute, Leninsky Prospekt 53, Moscow, 119991, Russia); Maris, P.(Department of Physics and Astronomy, Iowa State University, Ames, IA, 50011, USA); Vary, J.P.(Department of Physics and Astronomy, Iowa State University, Ames, IA, 50011, USA)

2015-01-01

We report on the first non-perturbative calculation of the scalar Yukawa model in the single-nucleon sector up to four-body Fock sector truncation (one "scalar nucleon" and three "scalar pions"). The light-front Hamiltonian approach with a systematic non-perturbative renormalization is applied. We study the $n$-body norms and the electromagnetic form factor. We find that the one- and two-body contributions dominate up to coupling $\\alpha \\approx 1.7$. As we approach the coupling $\\alpha \\appr...

Verification of short lead time forecast models: applied to Kp and Dst forecasting

Science.gov (United States)

Wintoft, Peter; Wik, Magnus

2016-04-01

In the ongoing EU/H2020 project PROGRESS models that predicts Kp, Dst, and AE from L1 solar wind data will be used as inputs to radiation belt models. The possible lead times from L1 measurements are shorter (10s of minutes to hours) than the typical duration of the physical phenomena that should be forecast. Under these circumstances several metrics fail to single out trivial cases, such as persistence. In this work we explore metrics and approaches for short lead time forecasts. We apply these to current Kp and Dst forecast models. This project has received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement No 637302.

Continuum modeling an approach through practical examples

CERN Document Server

Muntean, Adrian

2015-01-01

This book develops continuum modeling skills and approaches the topic from three sides: (1) derivation of global integral laws together with the associated local differential equations, (2) design of constitutive laws and (3) modeling boundary processes. The focus of this presentation lies on many practical examples covering aspects such as coupled flow, diffusion and reaction in porous media or microwave heating of a pizza, as well as traffic issues in bacterial colonies and energy harvesting from geothermal wells. The target audience comprises primarily graduate students in pure and applied mathematics as well as working practitioners in engineering who are faced by nonstandard rheological topics like those typically arising in the food industry.

Equivalent electrical network model approach applied to a double acting low temperature differential Stirling engine

International Nuclear Information System (INIS)

Formosa, Fabien; Badel, Adrien; Lottin, Jacques

2014-01-01

Highlights: • An equivalent electrical network modeling of Stirling engine is proposed. • This model is applied to a membrane low temperate double acting Stirling engine. • The operating conditions (self-startup and steady state behavior) are defined. • An experimental engine is presented and tested. • The model is validated against experimental results. - Abstract: This work presents a network model to simulate the periodic behavior of a double acting free piston type Stirling engine. Each component of the engine is considered independently and its equivalent electrical circuit derived. When assembled in a global electrical network, a global model of the engine is established. Its steady behavior can be obtained by the analysis of the transfer function for one phase from the piston to the expansion chamber. It is then possible to simulate the dynamic (steady state stroke and operation frequency) as well as the thermodynamic performances (output power and efficiency) for given mean pressure, heat source and heat sink temperatures. The motion amplitude especially can be determined by the spring-mass properties of the moving parts and the main nonlinear effects which are taken into account in the model. The thermodynamic features of the model have then been validated using the classical isothermal Schmidt analysis for a given stroke. A three-phase low temperature differential double acting free membrane architecture has been built and tested. The experimental results are compared with the model and a satisfactory agreement is obtained. The stroke and operating frequency are predicted with less than 2% error whereas the output power discrepancy is of about 30%. Finally, some optimization routes are suggested to improve the design and maximize the performances aiming at waste heat recovery applications

Agent-based modeling: a new approach for theory building in social psychology.

Science.gov (United States)

Smith, Eliot R; Conrey, Frederica R

2007-02-01

Most social and psychological phenomena occur not as the result of isolated decisions by individuals but rather as the result of repeated interactions between multiple individuals over time. Yet the theory-building and modeling techniques most commonly used in social psychology are less than ideal for understanding such dynamic and interactive processes. This article describes an alternative approach to theory building, agent-based modeling (ABM), which involves simulation of large numbers of autonomous agents that interact with each other and with a simulated environment and the observation of emergent patterns from their interactions. The authors believe that the ABM approach is better able than prevailing approaches in the field, variable-based modeling (VBM) techniques such as causal modeling, to capture types of complex, dynamic, interactive processes so important in the social world. The article elaborates several important contrasts between ABM and VBM and offers specific recommendations for learning more and applying the ABM approach.

Applying Digital Sensor Technology: A Problem-Solving Approach

Science.gov (United States)

Seedhouse, Paul; Knight, Dawn

2016-01-01

There is currently an explosion in the number and range of new devices coming onto the technology market that use digital sensor technology to track aspects of human behaviour. In this article, we present and exemplify a three-stage model for the application of digital sensor technology in applied linguistics that we have developed, namely,…

A survey on control schemes for distributed solar collector fields. Part I: Modeling and basic control approaches

Energy Technology Data Exchange (ETDEWEB)

Camacho, E.F.; Rubio, F.R. [Universidad de Sevilla, Escuela Superior de Ingenieros, Departamento de Ingenieria de Sistemas y Automatica, Camino de Los Descubrimientos s/n, E-41092, Sevilla (Spain); Berenguel, M. [Universidad de Almeria, Departamento de Lenguajes y Computacion, Area de Ingenieria de Sistemas y Automatica, Carretera Sacramento s/n, E-04120 La Canada, Almeria (Spain); Valenzuela, L. [Plataforma Solar de Almeria - CIEMAT, Carretera Senes s/n, P.O. Box 22, E-04200 Tabernas, Almeria (Spain)

2007-10-15

This article presents a survey of the different automatic control techniques that have been applied to control the outlet temperature of solar plants with distributed collectors during the last 25 years. Different aspects of the control problem involved in this kind of plants are treated, from modeling and simulation approaches to the different basic control schemes developed and successfully applied in real solar plants. A classification of the modeling and control approaches is used to explain the main features of each strategy. (author)

Applying the WEAP Model to Water Resource

DEFF Research Database (Denmark)

Gao, Jingjing; Christensen, Per; Li, Wei

efficiency, treatment and reuse of water. The WEAP model was applied to the Ordos catchment where it was used for the first time in China. The changes in water resource utilization in Ordos basin were assessed with the model. It was found that the WEAP model is a useful tool for water resource assessment......Water resources assessment is a tool to provide decision makers with an appropriate basis to make informed judgments regarding the objectives and targets to be addressed during the Strategic Environmental Assessment (SEA) process. The study shows how water resources assessment can be applied in SEA...... in assessing the effects on water resources using a case study on a Coal Industry Development Plan in an arid region in North Western China. In the case the WEAP model (Water Evaluation And Planning System) were used to simulate various scenarios using a diversity of technological instruments like irrigation...

Comprehensive Approach to Verification and Validation of CFD Simulations Applied to Backward Facing Step-Application of CFD Uncertainty Analysis

Science.gov (United States)

Groves, Curtis E.; LLie, Marcel; Shallhorn, Paul A.

2012-01-01

There are inherent uncertainties and errors associated with using Computational Fluid Dynamics (CFD) to predict the flow field and there is no standard method for evaluating uncertainty in the CFD community. This paper describes an approach to -validate the . uncertainty in using CFD. The method will use the state of the art uncertainty analysis applying different turbulence niodels and draw conclusions on which models provide the least uncertainty and which models most accurately predict the flow of a backward facing step.

Applying the health action process approach (HAPA) to the choice of health products: An exploratory study

DEFF Research Database (Denmark)

Krutulyte, Rasa; Grunert, Klaus G.; Scholderer, Joachim

This paper presents the results of a qualitative pilot study that aimed to uncovering Danish consumers' motives for choosing health food. Schwarzer's (1992) health action process approach (HAPA) was applied to understand the process by which people chose health products. The research focused...... on the role of the behavioural intention predictors such as risk perception, outcome expectations and self-efficacy. The model has been proved to be a useful framework for understanding consumer choosing health food and is substantial in the further application of dietary choice issues....

A fuzzy logic approach to modeling the underground economy in Taiwan

Science.gov (United States)

Yu, Tiffany Hui-Kuang; Wang, David Han-Min; Chen, Su-Jane

2006-04-01

The size of the ‘underground economy’ (UE) is valuable information in the formulation of macroeconomic and fiscal policy. This study applies fuzzy set theory and fuzzy logic to model Taiwan's UE over the period from 1960 to 2003. Two major factors affecting the size of the UE, the effective tax rate and the degree of government regulation, are used. The size of Taiwan's UE is scaled and compared with those of other models. Although our approach yields different estimates, similar patterns and leading are exhibited throughout the period. The advantage of applying fuzzy logic is twofold. First, it can avoid the complex calculations in conventional econometric models. Second, fuzzy rules with linguistic terms are easy for human to understand.

On quantum approach to modeling of plasmon photovoltaic effect

DEFF Research Database (Denmark)

Kluczyk, Katarzyna; David, Christin; Jacak, Witold Aleksander

2017-01-01

Surface plasmons in metallic nanostructures including metallically nanomodified solar cells are conventionally studied and modeled by application of the Mie approach to plasmons or by the finite element solution of differential Maxwell equations with imposed boundary and material constraints (e...... to the semiconductor solar cell mediated by surface plasmons in metallic nanoparticles deposited on the top of the battery. In addition, short-ranged electron-electron interaction in metals is discussed in the framework of the semiclassical hydrodynamic model. The significance of the related quantum corrections......-aided photovoltaic phenomena. Quantum corrections considerably improve both the Mie and COMSOL approaches in this case. We present the semiclassical random phase approximation description of plasmons in metallic nanoparticles and apply the quantumFermi golden rule scheme to assess the sunlight energy transfer...

Applying ecological models to communities of genetic elements: the case of neutral theory.

Science.gov (United States)

Linquist, Stefan; Cottenie, Karl; Elliott, Tyler A; Saylor, Brent; Kremer, Stefan C; Gregory, T Ryan

2015-07-01

A promising recent development in molecular biology involves viewing the genome as a mini-ecosystem, where genetic elements are compared to organisms and the surrounding cellular and genomic structures are regarded as the local environment. Here, we critically evaluate the prospects of ecological neutral theory (ENT), a popular model in ecology, as it applies at the genomic level. This assessment requires an overview of the controversy surrounding neutral models in community ecology. In particular, we discuss the limitations of using ENT both as an explanation of community dynamics and as a null hypothesis. We then analyse a case study in which ENT has been applied to genomic data. Our central finding is that genetic elements do not conform to the requirements of ENT once its assumptions and limitations are made explicit. We further compare this genome-level application of ENT to two other, more familiar approaches in genomics that rely on neutral mechanisms: Kimura's molecular neutral theory and Lynch's mutational-hazard model. Interestingly, this comparison reveals that there are two distinct concepts of neutrality associated with these models, which we dub 'fitness neutrality' and 'competitive neutrality'. This distinction helps to clarify the various roles for neutral models in genomics, for example in explaining the evolution of genome size. © 2015 John Wiley & Sons Ltd.

Modeling of correlated data with informative cluster sizes: An evaluation of joint modeling and within-cluster resampling approaches.

Science.gov (United States)

Zhang, Bo; Liu, Wei; Zhang, Zhiwei; Qu, Yanping; Chen, Zhen; Albert, Paul S

2017-08-01

Joint modeling and within-cluster resampling are two approaches that are used for analyzing correlated data with informative cluster sizes. Motivated by a developmental toxicity study, we examined the performances and validity of these two approaches in testing covariate effects in generalized linear mixed-effects models. We show that the joint modeling approach is robust to the misspecification of cluster size models in terms of Type I and Type II errors when the corresponding covariates are not included in the random effects structure; otherwise, statistical tests may be affected. We also evaluate the performance of the within-cluster resampling procedure and thoroughly investigate the validity of it in modeling correlated data with informative cluster sizes. We show that within-cluster resampling is a valid alternative to joint modeling for cluster-specific covariates, but it is invalid for time-dependent covariates. The two methods are applied to a developmental toxicity study that investigated the effect of exposure to diethylene glycol dimethyl ether.

Exploiting neurovascular coupling: a Bayesian sequential Monte Carlo approach applied to simulated EEG fNIRS data

Science.gov (United States)

Croce, Pierpaolo; Zappasodi, Filippo; Merla, Arcangelo; Chiarelli, Antonio Maria

2017-08-01

Objective. Electrical and hemodynamic brain activity are linked through the neurovascular coupling process and they can be simultaneously measured through integration of electroencephalography (EEG) and functional near-infrared spectroscopy (fNIRS). Thanks to the lack of electro-optical interference, the two procedures can be easily combined and, whereas EEG provides electrophysiological information, fNIRS can provide measurements of two hemodynamic variables, such as oxygenated and deoxygenated hemoglobin. A Bayesian sequential Monte Carlo approach (particle filter, PF) was applied to simulated recordings of electrical and neurovascular mediated hemodynamic activity, and the advantages of a unified framework were shown. Approach. Multiple neural activities and hemodynamic responses were simulated in the primary motor cortex of a subject brain. EEG and fNIRS recordings were obtained by means of forward models of volume conduction and light propagation through the head. A state space model of combined EEG and fNIRS data was built and its dynamic evolution was estimated through a Bayesian sequential Monte Carlo approach (PF). Main results. We showed the feasibility of the procedure and the improvements in both electrical and hemodynamic brain activity reconstruction when using the PF on combined EEG and fNIRS measurements. Significance. The investigated procedure allows one to combine the information provided by the two methodologies, and, by taking advantage of a physical model of the coupling between electrical and hemodynamic response, to obtain a better estimate of brain activity evolution. Despite the high computational demand, application of such an approach to in vivo recordings could fully exploit the advantages of this combined brain imaging technology.

An approach to model validation and model-based prediction -- polyurethane foam case study.

Energy Technology Data Exchange (ETDEWEB)

Dowding, Kevin J.; Rutherford, Brian Milne

2003-07-01

Enhanced software methodology and improved computing hardware have advanced the state of simulation technology to a point where large physics-based codes can be a major contributor in many systems analyses. This shift toward the use of computational methods has brought with it new research challenges in a number of areas including characterization of uncertainty, model validation, and the analysis of computer output. It is these challenges that have motivated the work described in this report. Approaches to and methods for model validation and (model-based) prediction have been developed recently in the engineering, mathematics and statistical literatures. In this report we have provided a fairly detailed account of one approach to model validation and prediction applied to an analysis investigating thermal decomposition of polyurethane foam. A model simulates the evolution of the foam in a high temperature environment as it transforms from a solid to a gas phase. The available modeling and experimental results serve as data for a case study focusing our model validation and prediction developmental efforts on this specific thermal application. We discuss several elements of the ''philosophy'' behind the validation and prediction approach: (1) We view the validation process as an activity applying to the use of a specific computational model for a specific application. We do acknowledge, however, that an important part of the overall development of a computational simulation initiative is the feedback provided to model developers and analysts associated with the application. (2) We utilize information obtained for the calibration of model parameters to estimate the parameters and quantify uncertainty in the estimates. We rely, however, on validation data (or data from similar analyses) to measure the variability that contributes to the uncertainty in predictions for specific systems or units (unit-to-unit variability). (3) We perform statistical

Penalising Model Component Complexity: A Principled, Practical Approach to Constructing Priors

KAUST Repository

Simpson, Daniel

2017-04-06

In this paper, we introduce a new concept for constructing prior distributions. We exploit the natural nested structure inherent to many model components, which defines the model component to be a flexible extension of a base model. Proper priors are defined to penalise the complexity induced by deviating from the simpler base model and are formulated after the input of a user-defined scaling parameter for that model component, both in the univariate and the multivariate case. These priors are invariant to repa-rameterisations, have a natural connection to Jeffreys\\' priors, are designed to support Occam\\'s razor and seem to have excellent robustness properties, all which are highly desirable and allow us to use this approach to define default prior distributions. Through examples and theoretical results, we demonstrate the appropriateness of this approach and how it can be applied in various situations.

Penalising Model Component Complexity: A Principled, Practical Approach to Constructing Priors

KAUST Repository

Simpson, Daniel; Rue, Haavard; Riebler, Andrea; Martins, Thiago G.; Sø rbye, Sigrunn H.

2017-01-01

In this paper, we introduce a new concept for constructing prior distributions. We exploit the natural nested structure inherent to many model components, which defines the model component to be a flexible extension of a base model. Proper priors are defined to penalise the complexity induced by deviating from the simpler base model and are formulated after the input of a user-defined scaling parameter for that model component, both in the univariate and the multivariate case. These priors are invariant to repa-rameterisations, have a natural connection to Jeffreys' priors, are designed to support Occam's razor and seem to have excellent robustness properties, all which are highly desirable and allow us to use this approach to define default prior distributions. Through examples and theoretical results, we demonstrate the appropriateness of this approach and how it can be applied in various situations.

Reynolds stress turbulence model applied to two-phase pressurized thermal shocks in nuclear power plant

Energy Technology Data Exchange (ETDEWEB)

Mérigoux, Nicolas, E-mail: nicolas.merigoux@edf.fr; Laviéville, Jérôme; Mimouni, Stéphane; Guingo, Mathieu; Baudry, Cyril

2016-04-01

Highlights: • NEPTUNE-CFD is used to model two-phase PTS. • k-ε model did produce some satisfactory results but also highlights some weaknesses. • A more advanced turbulence model has been developed, validated and applied for PTS. • Coupled with LIM, the first results confirmed the increased accuracy of the approach. - Abstract: Nuclear power plants are subjected to a variety of ageing mechanisms and, at the same time, exposed to potential pressurized thermal shock (PTS) – characterized by a rapid cooling of the internal Reactor Pressure Vessel (RPV) surface. In this context, NEPTUNE-CFD is used to model two-phase PTS and give an assessment on the structural integrity of the RPV. The first available choice was to use standard first order turbulence model (k-ε) to model high-Reynolds number flows encountered in Pressurized Water Reactor (PWR) primary circuits. In a first attempt, the use of k-ε model did produce some satisfactory results in terms of condensation rate and temperature field distribution on integral experiments, but also highlights some weaknesses in the way to model highly anisotropic turbulence. One way to improve the turbulence prediction – and consequently the temperature field distribution – is to opt for more advanced Reynolds Stress turbulence Model. After various verification and validation steps on separated effects cases – co-current air/steam-water stratified flows in rectangular channels, water jet impingements on water pool free surfaces – this Reynolds Stress turbulence Model (R{sub ij}-ε SSG) has been applied for the first time to thermal free surface flows under industrial conditions on COSI and TOPFLOW-PTS experiments. Coupled with the Large Interface Model, the first results confirmed the adequacy and increased accuracy of the approach in an industrial context.

Next-Generation Mitogenomics: A Comparison of Approaches Applied to Caecilian Amphibian Phylogeny

OpenAIRE

Maddock, Simon T.; Briscoe, Andrew G.; Wilkinson, Mark; Waeschenbach, Andrea; San Mauro, Diego; Day, Julia J.; Littlewood, D. Tim J.; Foster, Peter G.; Nussbaum, Ronald A.; Gower, David J.

2016-01-01

Mitochondrial genome (mitogenome) sequences are being generated with increasing speed due to the advances of next-generation sequencing (NGS) technology and associated analytical tools. However, detailed comparisons to explore the utility of alternative NGS approaches applied to the same taxa have not been undertaken. We compared a ‘traditional’ Sanger sequencing method with two NGS approaches (shotgun sequencing and non-indexed, multiplex amplicon sequencing) on four different sequencing pla...

Geostatistical methods applied to field model residuals

DEFF Research Database (Denmark)

Maule, Fox; Mosegaard, K.; Olsen, Nils

consists of measurement errors and unmodelled signal), and is typically assumed to be uncorrelated and Gaussian distributed. We have applied geostatistical methods to analyse the residuals of the Oersted(09d/04) field model [http://www.dsri.dk/Oersted/Field_models/IGRF_2005_candidates/], which is based...

A Model-Based Prognostics Approach Applied to Pneumatic Valves

Data.gov (United States)

National Aeronautics and Space Administration — Within the area of systems health management, the task of prognostics centers on predicting when components will fail. Model-based prognostics exploits domain...

A Model-based Prognostics Approach Applied to Pneumatic Valves

Data.gov (United States)

National Aeronautics and Space Administration — Within the area of systems health management, the task of prognostics centers on predicting when components will fail. Model-based prognostics exploits domain...

A model predictive speed tracking control approach for autonomous ground vehicles

Science.gov (United States)

Zhu, Min; Chen, Huiyan; Xiong, Guangming

2017-03-01

This paper presents a novel speed tracking control approach based on a model predictive control (MPC) framework for autonomous ground vehicles. A switching algorithm without calibration is proposed to determine the drive or brake control. Combined with a simple inverse longitudinal vehicle model and adaptive regulation of MPC, this algorithm can make use of the engine brake torque for various driving conditions and avoid high frequency oscillations automatically. A simplified quadratic program (QP) solving algorithm is used to reduce the computational time, and the approach has been applied in a 16-bit microcontroller. The performance of the proposed approach is evaluated via simulations and vehicle tests, which were carried out in a range of speed-profile tracking tasks. With a well-designed system structure, high-precision speed control is achieved. The system can robustly model uncertainty and external disturbances, and yields a faster response with less overshoot than a PI controller.

The redshift distribution of cosmological samples: a forward modeling approach

Energy Technology Data Exchange (ETDEWEB)

Herbel, Jörg; Kacprzak, Tomasz; Amara, Adam; Refregier, Alexandre; Bruderer, Claudio; Nicola, Andrina, E-mail: joerg.herbel@phys.ethz.ch, E-mail: tomasz.kacprzak@phys.ethz.ch, E-mail: adam.amara@phys.ethz.ch, E-mail: alexandre.refregier@phys.ethz.ch, E-mail: claudio.bruderer@phys.ethz.ch, E-mail: andrina.nicola@phys.ethz.ch [Institute for Astronomy, Department of Physics, ETH Zürich, Wolfgang-Pauli-Strasse 27, 8093 Zürich (Switzerland)

2017-08-01

Determining the redshift distribution n ( z ) of galaxy samples is essential for several cosmological probes including weak lensing. For imaging surveys, this is usually done using photometric redshifts estimated on an object-by-object basis. We present a new approach for directly measuring the global n ( z ) of cosmological galaxy samples, including uncertainties, using forward modeling. Our method relies on image simulations produced using \\textsc(UFig) (Ultra Fast Image Generator) and on ABC (Approximate Bayesian Computation) within the MCCL (Monte-Carlo Control Loops) framework. The galaxy population is modeled using parametric forms for the luminosity functions, spectral energy distributions, sizes and radial profiles of both blue and red galaxies. We apply exactly the same analysis to the real data and to the simulated images, which also include instrumental and observational effects. By adjusting the parameters of the simulations, we derive a set of acceptable models that are statistically consistent with the data. We then apply the same cuts to the simulations that were used to construct the target galaxy sample in the real data. The redshifts of the galaxies in the resulting simulated samples yield a set of n ( z ) distributions for the acceptable models. We demonstrate the method by determining n ( z ) for a cosmic shear like galaxy sample from the 4-band Subaru Suprime-Cam data in the COSMOS field. We also complement this imaging data with a spectroscopic calibration sample from the VVDS survey. We compare our resulting posterior n ( z ) distributions to the one derived from photometric redshifts estimated using 36 photometric bands in COSMOS and find good agreement. This offers good prospects for applying our approach to current and future large imaging surveys.

A Mathematical Modelling Approach to One-Day Cricket Batting Orders

Science.gov (United States)

Bukiet, Bruce; Ovens, Matthews

2006-01-01

While scoring strategies and player performance in cricket have been studied, there has been little published work about the influence of batting order with respect to One-Day cricket. We apply a mathematical modelling approach to compute efficiently the expected performance (runs distribution) of a cricket batting order in an innings. Among other applications, our method enables one to solve for the probability of one team beating another or to find the optimal batting order for a set of 11 players. The influence of defence and bowling ability can be taken into account in a straightforward manner. In this presentation, we outline how we develop our Markov Chain approach to studying the progress of runs for a batting order of non- identical players along the lines of work in baseball modelling by Bukiet et al., 1997. We describe the issues that arise in applying such methods to cricket, discuss ideas for addressing these difficulties and note limitations on modelling batting order for One-Day cricket. By performing our analysis on a selected subset of the possible batting orders, we apply the model to quantify the influence of batting order in a game of One Day cricket using available real-world data for current players. Key Points Batting order does effect the expected runs distribution in one-day cricket. One-day cricket has fewer data points than baseball, thus extreme values have greater effect on estimated probabilities. Dismissals rare and probabilities very small by comparison to baseball. Probability distribution for lower order batsmen is potentially skewed due to increased risk taking. Full enumeration of all possible line-ups is impractical using a single average computer. PMID:24357943

The redshift distribution of cosmological samples: a forward modeling approach

Science.gov (United States)

Herbel, Jörg; Kacprzak, Tomasz; Amara, Adam; Refregier, Alexandre; Bruderer, Claudio; Nicola, Andrina

2017-08-01

Determining the redshift distribution n(z) of galaxy samples is essential for several cosmological probes including weak lensing. For imaging surveys, this is usually done using photometric redshifts estimated on an object-by-object basis. We present a new approach for directly measuring the global n(z) of cosmological galaxy samples, including uncertainties, using forward modeling. Our method relies on image simulations produced using \\textsc{UFig} (Ultra Fast Image Generator) and on ABC (Approximate Bayesian Computation) within the MCCL (Monte-Carlo Control Loops) framework. The galaxy population is modeled using parametric forms for the luminosity functions, spectral energy distributions, sizes and radial profiles of both blue and red galaxies. We apply exactly the same analysis to the real data and to the simulated images, which also include instrumental and observational effects. By adjusting the parameters of the simulations, we derive a set of acceptable models that are statistically consistent with the data. We then apply the same cuts to the simulations that were used to construct the target galaxy sample in the real data. The redshifts of the galaxies in the resulting simulated samples yield a set of n(z) distributions for the acceptable models. We demonstrate the method by determining n(z) for a cosmic shear like galaxy sample from the 4-band Subaru Suprime-Cam data in the COSMOS field. We also complement this imaging data with a spectroscopic calibration sample from the VVDS survey. We compare our resulting posterior n(z) distributions to the one derived from photometric redshifts estimated using 36 photometric bands in COSMOS and find good agreement. This offers good prospects for applying our approach to current and future large imaging surveys.

The redshift distribution of cosmological samples: a forward modeling approach

International Nuclear Information System (INIS)

Herbel, Jörg; Kacprzak, Tomasz; Amara, Adam; Refregier, Alexandre; Bruderer, Claudio; Nicola, Andrina

2017-01-01

Determining the redshift distribution n ( z ) of galaxy samples is essential for several cosmological probes including weak lensing. For imaging surveys, this is usually done using photometric redshifts estimated on an object-by-object basis. We present a new approach for directly measuring the global n ( z ) of cosmological galaxy samples, including uncertainties, using forward modeling. Our method relies on image simulations produced using \\textsc(UFig) (Ultra Fast Image Generator) and on ABC (Approximate Bayesian Computation) within the MCCL (Monte-Carlo Control Loops) framework. The galaxy population is modeled using parametric forms for the luminosity functions, spectral energy distributions, sizes and radial profiles of both blue and red galaxies. We apply exactly the same analysis to the real data and to the simulated images, which also include instrumental and observational effects. By adjusting the parameters of the simulations, we derive a set of acceptable models that are statistically consistent with the data. We then apply the same cuts to the simulations that were used to construct the target galaxy sample in the real data. The redshifts of the galaxies in the resulting simulated samples yield a set of n ( z ) distributions for the acceptable models. We demonstrate the method by determining n ( z ) for a cosmic shear like galaxy sample from the 4-band Subaru Suprime-Cam data in the COSMOS field. We also complement this imaging data with a spectroscopic calibration sample from the VVDS survey. We compare our resulting posterior n ( z ) distributions to the one derived from photometric redshifts estimated using 36 photometric bands in COSMOS and find good agreement. This offers good prospects for applying our approach to current and future large imaging surveys.

Bayesian approach to errors-in-variables in regression models

Science.gov (United States)

Rozliman, Nur Aainaa; Ibrahim, Adriana Irawati Nur; Yunus, Rossita Mohammad

2017-05-01

In many applications and experiments, data sets are often contaminated with error or mismeasured covariates. When at least one of the covariates in a model is measured with error, Errors-in-Variables (EIV) model can be used. Measurement error, when not corrected, would cause misleading statistical inferences and analysis. Therefore, our goal is to examine the relationship of the outcome variable and the unobserved exposure variable given the observed mismeasured surrogate by applying the Bayesian formulation to the EIV model. We shall extend the flexible parametric method proposed by Hossain and Gustafson (2009) to another nonlinear regression model which is the Poisson regression model. We shall then illustrate the application of this approach via a simulation study using Markov chain Monte Carlo sampling methods.

Applying dynamic priority scheduling scheme to static systems of pinwheel task model in power-aware scheduling.

Science.gov (United States)

Seol, Ye-In; Kim, Young-Kuk

2014-01-01

Power-aware scheduling reduces CPU energy consumption in hard real-time systems through dynamic voltage scaling (DVS). In this paper, we deal with pinwheel task model which is known as static and predictable task model and could be applied to various embedded or ubiquitous systems. In pinwheel task model, each task's priority is static and its execution sequence could be predetermined. There have been many static approaches to power-aware scheduling in pinwheel task model. But, in this paper, we will show that the dynamic priority scheduling results in power-aware scheduling could be applied to pinwheel task model. This method is more effective than adopting the previous static priority scheduling methods in saving energy consumption and, for the system being still static, it is more tractable and applicable to small sized embedded or ubiquitous computing. Also, we introduce a novel power-aware scheduling algorithm which exploits all slacks under preemptive earliest-deadline first scheduling which is optimal in uniprocessor system. The dynamic priority method presented in this paper could be applied directly to static systems of pinwheel task model. The simulation results show that the proposed algorithm with the algorithmic complexity of O(n) reduces the energy consumption by 10-80% over the existing algorithms.

Comparison of various modelling approaches applied to cholera case data

CSIR Research Space (South Africa)

Van Den Bergh, F

2008-06-01

Full Text Available cross-wavelet technique, which is used to compute lead times for co-varying variables, and suggests transformations that enhance co-varying behaviour. Several statistical modelling techniques, including generalised linear models, ARIMA time series...

Applied Mathematics, Modelling and Computational Science

CERN Document Server

Kotsireas, Ilias; Makarov, Roman; Melnik, Roderick; Shodiev, Hasan

2015-01-01

The Applied Mathematics, Modelling, and Computational Science (AMMCS) conference aims to promote interdisciplinary research and collaboration. The contributions in this volume cover the latest research in mathematical and computational sciences, modeling, and simulation as well as their applications in natural and social sciences, engineering and technology, industry, and finance. The 2013 conference, the second in a series of AMMCS meetings, was held August 26–30 and organized in cooperation with AIMS and SIAM, with support from the Fields Institute in Toronto, and Wilfrid Laurier University. There were many young scientists at AMMCS-2013, both as presenters and as organizers. This proceedings contains refereed papers contributed by the participants of the AMMCS-2013 after the conference. This volume is suitable for researchers and graduate students, mathematicians and engineers, industrialists, and anyone who would like to delve into the interdisciplinary research of applied and computational mathematics ...

Validation of radiological efficiency model applied for the crops/soils contaminated by radiocaesium

International Nuclear Information System (INIS)

Montero, M.; Vazquez, C.; Moraleda, M.; Claver, F.

2000-01-01

The differences shown in the radiological efficiency applying the same agrochemical interventions on a range of contaminated agricultural scenarios by long-live radionuclides have conducted the radioecological studies to quantify the influence of local characteristics on the soil-to-plant transference. In the framework of the Decision Support Systems for post-accidental environmental restoration, a semi-mechanistic approach has been developed to estimate the soil-to-plant transfer factor from the major properties underlying the bioavailability of radiocaesium in soils and the absorption capacity by the crop. The model describes, for each soil texture class, the effects of time and K status on the transference of radiocaesium to plants. The approach lets to estimate the actual and the available minimum transference and to calculate the optimum amendment warranting the maximum radiological efficiency on an specific soil-crop combination. The parameterization and validation of the model from a database providing information about experimental transference studies for a collection of soil-crop combinations are shown. (Author) 4 refs

An extended risk assessment approach for chemical plants applied to a study related to pipe ruptures

International Nuclear Information System (INIS)

Milazzo, Maria Francesca; Aven, Terje

2012-01-01

Risk assessments and Quantitative Risk Assessment (QRA) in particular have been used in the chemical industry for many years to support decision-making on the choice of arrangements and measures associated with chemical processes, transportation and storage of dangerous substances. The assessments have been founded on a risk perspective seeing risk as a function of frequency of events (probability) and associated consequences. In this paper we point to the need for extending this approach to place a stronger emphasis on uncertainties. A recently developed risk framework designed to better reflect such uncertainties is presented and applied to a chemical plant and specifically the analysis of accidental events related to the rupture of pipes. Two different ways of implementing the framework are presented, one based on the introduction of probability models and one without. The differences between the standard approach and the extended approaches are discussed from a theoretical point of view as well as from a practical risk analyst perspective.

MODELS OF TECHNOLOGY ADOPTION: AN INTEGRATIVE APPROACH

Directory of Open Access Journals (Sweden)

Andrei OGREZEANU

2015-06-01

Full Text Available The interdisciplinary study of information technology adoption has developed rapidly over the last 30 years. Various theoretical models have been developed and applied such as: the Technology Acceptance Model (TAM, Innovation Diffusion Theory (IDT, Theory of Planned Behavior (TPB, etc. The result of these many years of research is thousands of contributions to the field, which, however, remain highly fragmented. This paper develops a theoretical model of technology adoption by integrating major theories in the field: primarily IDT, TAM, and TPB. To do so while avoiding mess, an approach that goes back to basics in independent variable type’s development is proposed; emphasizing: 1 the logic of classification, and 2 psychological mechanisms behind variable types. Once developed these types are then populated with variables originating in empirical research. Conclusions are developed on which types are underpopulated and present potential for future research. I end with a set of methodological recommendations for future application of the model.

A Multi-State Physics Modeling approach for the reliability assessment of Nuclear Power Plants piping systems

International Nuclear Information System (INIS)

Di Maio, Francesco; Colli, Davide; Zio, Enrico; Tao, Liu; Tong, Jiejuan

2015-01-01

Highlights: • We model piping systems degradation of Nuclear Power Plants under uncertainty. • We use Multi-State Physics Modeling (MSPM) to describe a continuous degradation process. • We propose a Monte Carlo (MC) method for calculating time-dependent transition rates. • We apply MSPM to a piping system undergoing thermal fatigue. - Abstract: A Multi-State Physics Modeling (MSPM) approach is here proposed for degradation modeling and failure probability quantification of Nuclear Power Plants (NPPs) piping systems. This approach integrates multi-state modeling to describe the degradation process by transitions among discrete states (e.g., no damage, micro-crack, flaw, rupture, etc.), with physics modeling by (physic) equations to describe the continuous degradation process within the states. We propose a Monte Carlo (MC) simulation method for the evaluation of the time-dependent transition rates between the states of the MSPM. Accountancy is given for the uncertainty in the parameters and external factors influencing the degradation process. The proposed modeling approach is applied to a benchmark problem of a piping system of a Pressurized Water Reactor (PWR) undergoing thermal fatigue. The results are compared with those obtained by a continuous-time homogeneous Markov Chain Model

Time series modeling by a regression approach based on a latent process.

Science.gov (United States)

Chamroukhi, Faicel; Samé, Allou; Govaert, Gérard; Aknin, Patrice

2009-01-01

Time series are used in many domains including finance, engineering, economics and bioinformatics generally to represent the change of a measurement over time. Modeling techniques may then be used to give a synthetic representation of such data. A new approach for time series modeling is proposed in this paper. It consists of a regression model incorporating a discrete hidden logistic process allowing for activating smoothly or abruptly different polynomial regression models. The model parameters are estimated by the maximum likelihood method performed by a dedicated Expectation Maximization (EM) algorithm. The M step of the EM algorithm uses a multi-class Iterative Reweighted Least-Squares (IRLS) algorithm to estimate the hidden process parameters. To evaluate the proposed approach, an experimental study on simulated data and real world data was performed using two alternative approaches: a heteroskedastic piecewise regression model using a global optimization algorithm based on dynamic programming, and a Hidden Markov Regression Model whose parameters are estimated by the Baum-Welch algorithm. Finally, in the context of the remote monitoring of components of the French railway infrastructure, and more particularly the switch mechanism, the proposed approach has been applied to modeling and classifying time series representing the condition measurements acquired during switch operations.

Fractional calculus model of electrical impedance applied to human skin.

Science.gov (United States)

Vosika, Zoran B; Lazovic, Goran M; Misevic, Gradimir N; Simic-Krstic, Jovana B

2013-01-01

Fractional calculus is a mathematical approach dealing with derivatives and integrals of arbitrary and complex orders. Therefore, it adds a new dimension to understand and describe basic nature and behavior of complex systems in an improved way. Here we use the fractional calculus for modeling electrical properties of biological systems. We derived a new class of generalized models for electrical impedance and applied them to human skin by experimental data fitting. The primary model introduces new generalizations of: 1) Weyl fractional derivative operator, 2) Cole equation, and 3) Constant Phase Element (CPE). These generalizations were described by the novel equation which presented parameter [Formula: see text] related to remnant memory and corrected four essential parameters [Formula: see text] We further generalized single generalized element by introducing specific partial sum of Maclaurin series determined by parameters [Formula: see text] We defined individual primary model elements and their serial combination models by the appropriate equations and electrical schemes. Cole equation is a special case of our generalized class of models for[Formula: see text] Previous bioimpedance data analyses of living systems using basic Cole and serial Cole models show significant imprecisions. Our new class of models considerably improves the quality of fitting, evaluated by mean square errors, for bioimpedance data obtained from human skin. Our models with new parameters presented in specific partial sum of Maclaurin series also extend representation, understanding and description of complex systems electrical properties in terms of remnant memory effects.

Fractional calculus model of electrical impedance applied to human skin.

Directory of Open Access Journals (Sweden)

Zoran B Vosika

Full Text Available Fractional calculus is a mathematical approach dealing with derivatives and integrals of arbitrary and complex orders. Therefore, it adds a new dimension to understand and describe basic nature and behavior of complex systems in an improved way. Here we use the fractional calculus for modeling electrical properties of biological systems. We derived a new class of generalized models for electrical impedance and applied them to human skin by experimental data fitting. The primary model introduces new generalizations of: 1 Weyl fractional derivative operator, 2 Cole equation, and 3 Constant Phase Element (CPE. These generalizations were described by the novel equation which presented parameter [Formula: see text] related to remnant memory and corrected four essential parameters [Formula: see text] We further generalized single generalized element by introducing specific partial sum of Maclaurin series determined by parameters [Formula: see text] We defined individual primary model elements and their serial combination models by the appropriate equations and electrical schemes. Cole equation is a special case of our generalized class of models for[Formula: see text] Previous bioimpedance data analyses of living systems using basic Cole and serial Cole models show significant imprecisions. Our new class of models considerably improves the quality of fitting, evaluated by mean square errors, for bioimpedance data obtained from human skin. Our models with new parameters presented in specific partial sum of Maclaurin series also extend representation, understanding and description of complex systems electrical properties in terms of remnant memory effects.

A statistical method for model extraction and model selection applied to the temperature scaling of the L–H transition

International Nuclear Information System (INIS)

Peluso, E; Gelfusa, M; Gaudio, P; Murari, A

2014-01-01

Access to the H mode of confinement in tokamaks is characterized by an abrupt transition, which has been the subject of continuous investigation for decades. Various theoretical models have been developed and multi-machine databases of experimental data have been collected. In this paper, a new methodology is reviewed for the investigation of the scaling laws for the temperature threshold to access the H mode. The approach is based on symbolic regression via genetic programming and allows first the extraction of the most statistically reliable models from the available experimental data. Nonlinear fitting is then applied to the mathematical expressions found by symbolic regression; this second step permits to easily compare the quality of the data-driven scalings with the most widely accepted theoretical models. The application of a complete set of statistical indicators shows that the data-driven scaling laws are qualitatively better than the theoretical models. The main limitations of the theoretical models are that they are all expressed as power laws, which are too rigid to fit the available experimental data and to extrapolate to ITER. The proposed method is absolutely general and can be applied to the extraction or scaling law from any experimental database of sufficient statistical relevance. (paper)

A comparison of various modelling approaches applied to Cholera ...

African Journals Online (AJOL)

The analyses are demonstrated on data collected from Beira, Mozambique. Dynamic regression was found to be the preferred forecasting method for this data set. Keywords:Cholera, modelling, signal processing, dynamic regression, negative binomial regression, wavelet analysis, cross-wavelet analysis. ORiON Vol.

A diagnosis method for physical systems using a multi-modeling approach

International Nuclear Information System (INIS)

Thetiot, R.

2000-01-01

In this thesis we propose a method for diagnosis problem solving. This method is based on a multi-modeling approach describing both normal and abnormal behavior of a system. This modeling approach allows to represent a system at different abstraction levels (behavioral, functional and teleological. Fundamental knowledge is described according to a bond-graph representation. We show that bond-graph representation can be exploited in order to generate (completely or partially) the functional models. The different models of the multi-modeling approach allows to define the functional state of a system at different abstraction levels. We exploit this property to exonerate sub-systems for which the expected behavior is observed. The behavioral and functional descriptions of the remaining sub-systems are exploited hierarchically in a two steps process. In a first step, the abnormal behaviors explaining some observations are identified. In a second step, the remaining unexplained observations are used to generate conflict sets and thus the consistency based diagnoses. The modeling method and the diagnosis process have been applied to a Reactor Coolant Pump Sets. This application illustrates the concepts described in this thesis and shows its potentialities. (authors)

Capturing ecology in modeling approaches applied to environmental risk assessment of endocrine active chemicals in fish.

Science.gov (United States)

Mintram, Kate S; Brown, A Ross; Maynard, Samuel K; Thorbek, Pernille; Tyler, Charles R

2018-02-01

Endocrine active chemicals (EACs) are widespread in freshwater environments and both laboratory and field based studies have shown reproductive effects in fish at environmentally relevant exposures. Environmental risk assessment (ERA) seeks to protect wildlife populations and prospective assessments rely on extrapolation from individual-level effects established for laboratory fish species to populations of wild fish using arbitrary safety factors. Population susceptibility to chemical effects, however, depends on exposure risk, physiological susceptibility, and population resilience, each of which can differ widely between fish species. Population models have significant potential to address these shortfalls and to include individual variability relating to life-history traits, demographic and density-dependent vital rates, and behaviors which arise from inter-organism and organism-environment interactions. Confidence in population models has recently resulted in the EU Commission stating that results derived from reliable models may be considered when assessing the relevance of adverse effects of EACs at the population level. This review critically assesses the potential risks posed by EACs for fish populations, considers the ecological factors influencing these risks and explores the benefits and challenges of applying population modeling (including individual-based modeling) in ERA for EACs in fish. We conclude that population modeling offers a way forward for incorporating greater environmental relevance in assessing the risks of EACs for fishes and for identifying key risk factors through sensitivity analysis. Individual-based models (IBMs) allow for the incorporation of physiological and behavioral endpoints relevant to EAC exposure effects, thus capturing both direct and indirect population-level effects.

Automated parameter tuning applied to sea ice in a global climate model

Science.gov (United States)

Roach, Lettie A.; Tett, Simon F. B.; Mineter, Michael J.; Yamazaki, Kuniko; Rae, Cameron D.

2018-01-01

This study investigates the hypothesis that a significant portion of spread in climate model projections of sea ice is due to poorly-constrained model parameters. New automated methods for optimization are applied to historical sea ice in a global coupled climate model (HadCM3) in order to calculate the combination of parameters required to reduce the difference between simulation and observations to within the range of model noise. The optimized parameters result in a simulated sea-ice time series which is more consistent with Arctic observations throughout the satellite record (1980-present), particularly in the September minimum, than the standard configuration of HadCM3. Divergence from observed Antarctic trends and mean regional sea ice distribution reflects broader structural uncertainty in the climate model. We also find that the optimized parameters do not cause adverse effects on the model climatology. This simple approach provides evidence for the contribution of parameter uncertainty to spread in sea ice extent trends and could be customized to investigate uncertainties in other climate variables.

An integrated approach to permeability modeling using micro-models

Energy Technology Data Exchange (ETDEWEB)

Hosseini, A.H.; Leuangthong, O.; Deutsch, C.V. [Society of Petroleum Engineers, Canadian Section, Calgary, AB (Canada)]|[Alberta Univ., Edmonton, AB (Canada)

2008-10-15

An important factor in predicting the performance of steam assisted gravity drainage (SAGD) well pairs is the spatial distribution of permeability. Complications that make the inference of a reliable porosity-permeability relationship impossible include the presence of short-scale variability in sand/shale sequences; preferential sampling of core data; and uncertainty in upscaling parameters. Micro-modelling is a simple and effective method for overcoming these complications. This paper proposed a micro-modeling approach to account for sampling bias, small laminated features with high permeability contrast, and uncertainty in upscaling parameters. The paper described the steps and challenges of micro-modeling and discussed the construction of binary mixture geo-blocks; flow simulation and upscaling; extended power law formalism (EPLF); and the application of micro-modeling and EPLF. An extended power-law formalism to account for changes in clean sand permeability as a function of macroscopic shale content was also proposed and tested against flow simulation results. There was close agreement between the model and simulation results. The proposed methodology was also applied to build the porosity-permeability relationship for laminated and brecciated facies of McMurray oil sands. Experimental data was in good agreement with the experimental data. 8 refs., 17 figs.

Applying a realistic evaluation model to occupational safety interventions

DEFF Research Database (Denmark)

Pedersen, Louise Møller

2018-01-01

Background: Recent literature characterizes occupational safety interventions as complex social activities, applied in complex and dynamic social systems. Hence, the actual outcomes of an intervention will vary, depending on the intervention, the implementation process, context, personal characte......Background: Recent literature characterizes occupational safety interventions as complex social activities, applied in complex and dynamic social systems. Hence, the actual outcomes of an intervention will vary, depending on the intervention, the implementation process, context, personal...... and qualitative methods. This revised model has, however, not been applied in a real life context. Method: The model is applied in a controlled, four-component, integrated behaviour-based and safety culture-based safety intervention study (2008-2010) in a medium-sized wood manufacturing company. The interventions...... involve the company’s safety committee, safety manager, safety groups and 130 workers. Results: The model provides a framework for more valid evidence of what works within injury prevention. Affective commitment and role behaviour among key actors are identified as crucial for the implementation...

Multimodal Approach for Automatic Emotion Recognition Applied to the Tension Levels Study in TV Newscasts

Directory of Open Access Journals (Sweden)

Moisés Henrique Ramos Pereira

2015-12-01

Full Text Available This article addresses a multimodal approach to automatic emotion recognition in participants of TV newscasts (presenters, reporters, commentators and others able to assist the tension levels study in narratives of events in this television genre. The methodology applies state-of-the-art computational methods to process and analyze facial expressions, as well as speech signals. The proposed approach contributes to semiodiscoursive study of TV newscasts and their enunciative praxis, assisting, for example, the identification of the communication strategy of these programs. To evaluate the effectiveness of the proposed approach was applied it in a video related to a report displayed on a Brazilian TV newscast great popularity in the state of Minas Gerais. The experimental results are promising on the recognition of emotions on the facial expressions of tele journalists and are in accordance with the distribution of audiovisual indicators extracted over a TV newscast, demonstrating the potential of the approach to support the TV journalistic discourse analysis.This article addresses a multimodal approach to automatic emotion recognition in participants of TV newscasts (presenters, reporters, commentators and others able to assist the tension levels study in narratives of events in this television genre. The methodology applies state-of-the-art computational methods to process and analyze facial expressions, as well as speech signals. The proposed approach contributes to semiodiscoursive study of TV newscasts and their enunciative praxis, assisting, for example, the identification of the communication strategy of these programs. To evaluate the effectiveness of the proposed approach was applied it in a video related to a report displayed on a Brazilian TV newscast great popularity in the state of Minas Gerais. The experimental results are promising on the recognition of emotions on the facial expressions of tele journalists and are in accordance

Accurate phenotyping: Reconciling approaches through Bayesian model averaging.

Directory of Open Access Journals (Sweden)

Carla Chia-Ming Chen

Full Text Available Genetic research into complex diseases is frequently hindered by a lack of clear biomarkers for phenotype ascertainment. Phenotypes for such diseases are often identified on the basis of clinically defined criteria; however such criteria may not be suitable for understanding the genetic composition of the diseases. Various statistical approaches have been proposed for phenotype definition; however our previous studies have shown that differences in phenotypes estimated using different approaches have substantial impact on subsequent analyses. Instead of obtaining results based upon a single model, we propose a new method, using Bayesian model averaging to overcome problems associated with phenotype definition. Although Bayesian model averaging has been used in other fields of research, this is the first study that uses Bayesian model averaging to reconcile phenotypes obtained using multiple models. We illustrate the new method by applying it to simulated genetic and phenotypic data for Kofendred personality disorder-an imaginary disease with several sub-types. Two separate statistical methods were used to identify clusters of individuals with distinct phenotypes: latent class analysis and grade of membership. Bayesian model averaging was then used to combine the two clusterings for the purpose of subsequent linkage analyses. We found that causative genetic loci for the disease produced higher LOD scores using model averaging than under either individual model separately. We attribute this improvement to consolidation of the cores of phenotype clusters identified using each individual method.

Power to the People! Meta-algorithmic modelling in applied data science

NARCIS (Netherlands)

Spruit, M.; Jagesar, R.

2016-01-01

This position paper first defines the research field of applied data science at the intersection of domain expertise, data mining, and engineering capabilities, with particular attention to analytical applications. We then propose a meta-algorithmic approach for applied data science with societal

Economic and ecological impacts of bioenergy crop production—a modeling approach applied in Southwestern Germany

Directory of Open Access Journals (Sweden)

Hans-Georg Schwarz-v. Raumer

2017-03-01

Full Text Available This paper considers scenarios of cultivating energy crops in the German Federal State of Baden-Württemberg to identify potentials and limitations of a sustainable bioenergy production. Trade-offs are analyzed among income and production structure in agriculture, bioenergy crop production, greenhouse gas emissions, and the interests of soil, water and species habitat protection. An integrated modelling approach (IMA was implemented coupling ecological and economic models in a model chain. IMA combines the Economic Farm Emission Model (EFEM; key input: parameter sets on farm production activities, the Environmental Policy Integrated Climate model (EPIC; key input: parameter sets on environmental cropping effects and GIS geo-processing models. EFEM is a supply model that maximizes total gross margins on farm level with simultaneous calculation of greenhouse gas emission from agriculture production. Calculations by EPIC result in estimates for soil erosion by water, nitrate leaching, Soil Organic Carbon and greenhouse gas emissions from soil. GIS routines provide land suitability analyses, scenario settings concerning nature conservation and habitat models for target species and help to enable spatial explicit results. The model chain is used to calculate scenarios representing different intensities of energy crop cultivation. To design scenarios which are detailed and in step to practice, comprehensive data research as well as fact and effect analyses were carried out. The scenarios indicate that, not in general but when considering specific farm types, energy crop share extremely increases if not restricted and leads to an increase in income. If so this leads to significant increase in soil erosion by water, nitrate leaching and greenhouse gas emissions. It has to be expected that an extension of nature conservation leads to an intensification of the remaining grassland and of the arable land, which were not part of nature conservation measures

Hybrid approach for the assessment of PSA models by means of binary decision diagrams

International Nuclear Information System (INIS)

Ibanez-Llano, Cristina; Rauzy, Antoine; Melendez, Enrique; Nieto, Francisco

2010-01-01

Binary decision diagrams are a well-known alternative to the minimal cutsets approach to assess the reliability Boolean models. They have been applied successfully to improve the fault trees models assessment. However, its application to solve large models, and in particular the event trees coming from the PSA studies of the nuclear industry, remains to date out of reach of an exact evaluation. For many real PSA models it may be not possible to compute the BDD within reasonable amount of time and memory without considering the truncation or simplification of the model. This paper presents a new approach to estimate the exact probabilistic quantification results (probability/frequency) based on combining the calculation of the MCS and the truncation limits, with the BDD approach, in order to have a better control on the reduction of the model and to properly account for the success branches. The added value of this methodology is that it is possible to ensure a real confidence interval of the exact value and therefore an explicit knowledge of the error bound. Moreover, it can be used to measure the acceptability of the results obtained with traditional techniques. The new method was applied to a real life PSA study and the results obtained confirm the applicability of the methodology and open a new viewpoint for further developments.

Hybrid approach for the assessment of PSA models by means of binary decision diagrams

Energy Technology Data Exchange (ETDEWEB)

Ibanez-Llano, Cristina, E-mail: cristina.ibanez@iit.upcomillas.e [Instituto de Investigacion Tecnologica (IIT), Escuela Tecnica Superior de Ingenieria ICAI, Universidad Pontificia Comillas, C/Santa Cruz de Marcenado 26, 28015 Madrid (Spain); Rauzy, Antoine, E-mail: Antoine.RAUZY@3ds.co [Dassault Systemes, 10 rue Marcel Dassault CS 40501, 78946 Velizy Villacoublay Cedex (France); Melendez, Enrique, E-mail: ema@csn.e [Consejo de Seguridad Nuclear (CSN), C/Justo Dorado 11, 28040 Madrid (Spain); Nieto, Francisco, E-mail: nieto@iit.upcomillas.e [Instituto de Investigacion Tecnologica (IIT), Escuela Tecnica Superior de Ingenieria ICAI, Universidad Pontificia Comillas, C/Santa Cruz de Marcenado 26, 28015 Madrid (Spain)

2010-10-15

Binary decision diagrams are a well-known alternative to the minimal cutsets approach to assess the reliability Boolean models. They have been applied successfully to improve the fault trees models assessment. However, its application to solve large models, and in particular the event trees coming from the PSA studies of the nuclear industry, remains to date out of reach of an exact evaluation. For many real PSA models it may be not possible to compute the BDD within reasonable amount of time and memory without considering the truncation or simplification of the model. This paper presents a new approach to estimate the exact probabilistic quantification results (probability/frequency) based on combining the calculation of the MCS and the truncation limits, with the BDD approach, in order to have a better control on the reduction of the model and to properly account for the success branches. The added value of this methodology is that it is possible to ensure a real confidence interval of the exact value and therefore an explicit knowledge of the error bound. Moreover, it can be used to measure the acceptability of the results obtained with traditional techniques. The new method was applied to a real life PSA study and the results obtained confirm the applicability of the methodology and open a new viewpoint for further developments.

Variational approach for the N-state spin and gauge Potts model

International Nuclear Information System (INIS)

Masperi, L.; Omero, C.

1981-05-01

A hamiltonian variational treatment is applied both to the spin Potts model and to its gauge version for any number of states N and spatial dimensions d>=2. Regarding the former we reproduce correct critical coupling and latent heat for not too low N and d. For the latter, our approach turns the gauge theory into an equivalent d-dimensional classical spin model, which evaluated for d+1=4 gives results in agreement with 1/N expansions. (author)

A predictive modeling approach to increasing the economic effectiveness of disease management programs.

Science.gov (United States)

Bayerstadler, Andreas; Benstetter, Franz; Heumann, Christian; Winter, Fabian

2014-09-01

Predictive Modeling (PM) techniques are gaining importance in the worldwide health insurance business. Modern PM methods are used for customer relationship management, risk evaluation or medical management. This article illustrates a PM approach that enables the economic potential of (cost-) effective disease management programs (DMPs) to be fully exploited by optimized candidate selection as an example of successful data-driven business management. The approach is based on a Generalized Linear Model (GLM) that is easy to apply for health insurance companies. By means of a small portfolio from an emerging country, we show that our GLM approach is stable compared to more sophisticated regression techniques in spite of the difficult data environment. Additionally, we demonstrate for this example of a setting that our model can compete with the expensive solutions offered by professional PM vendors and outperforms non-predictive standard approaches for DMP selection commonly used in the market.

Agent-based modelling in applied ethology: an exploratory case study of behavioural dynamics in tail biting in pigs

NARCIS (Netherlands)

Boumans, I.J.M.M.; Hofstede, G.J.; Bolhuis, J.E.; Boer, de I.J.M.; Bokkers, E.A.M.

2016-01-01

Understanding behavioural dynamics in pigs is important to assess pig welfare in current intensive pig production systems. Agent-based modelling (ABM) is an approach to gain insight into behavioural dynamics in pigs, but its use in applied ethology and animal welfare science has been limited so far.

Analytic model of Applied-B ion diode impedance behavior

International Nuclear Information System (INIS)

Miller, P.A.; Mendel, C.W. Jr.

1987-01-01

An empirical analysis of impedance data from Applied-B ion diodes used in seven inertial confinement fusion research experiments was published recently. The diodes all operated with impedance values well below the Child's-law value. The analysis uncovered an unusual unifying relationship among data from the different experiments. The analysis suggested that closure of the anode-cathode gap by electrode plasma was not a dominant factor in the experiments, but was not able to elaborate the underlying physics. Here we present a new analytic model of Applied-B ion diodes coupled to accelerators. A critical feature of the diode model is based on magnetic insulation theory. The model successfully describes impedance behavior of these diodes and supports stimulating new viewpoints of the physics of Applied-B ion diode operation

Hierarchic stochastic modelling applied to intracellular Ca(2+ signals.

Directory of Open Access Journals (Sweden)

Gregor Moenke

Full Text Available Important biological processes like cell signalling and gene expression have noisy components and are very complex at the same time. Mathematical analysis of such systems has often been limited to the study of isolated subsystems, or approximations are used that are difficult to justify. Here we extend a recently published method (Thurley and Falcke, PNAS 2011 which is formulated in observable system configurations instead of molecular transitions. This reduces the number of system states by several orders of magnitude and avoids fitting of kinetic parameters. The method is applied to Ca(2+ signalling. Ca(2+ is a ubiquitous second messenger transmitting information by stochastic sequences of concentration spikes, which arise by coupling of subcellular Ca(2+ release events (puffs. We derive analytical expressions for a mechanistic Ca(2+ model, based on recent data from live cell imaging, and calculate Ca(2+ spike statistics in dependence on cellular parameters like stimulus strength or number of Ca(2+ channels. The new approach substantiates a generic Ca(2+ model, which is a very convenient way to simulate Ca(2+ spike sequences with correct spiking statistics.

Approaches to surface complexation modeling of Uranium(VI) adsorption on aquifer sediments

Science.gov (United States)

Davis, J.A.; Meece, D.E.; Kohler, M.; Curtis, G.P.

2004-01-01

Uranium(VI) adsorption onto aquifer sediments was studied in batch experiments as a function of pH and U(VI) and dissolved carbonate concentrations in artificial groundwater solutions. The sediments were collected from an alluvial aquifer at a location upgradient of contamination from a former uranium mill operation at Naturita, Colorado (USA). The ranges of aqueous chemical conditions used in the U(VI) adsorption experiments (pH 6.9 to 7.9; U(VI) concentration 2.5 ?? 10-8 to 1 ?? 10-5 M; partial pressure of carbon dioxide gas 0.05 to 6.8%) were based on the spatial variation in chemical conditions observed in 1999-2000 in the Naturita alluvial aquifer. The major minerals in the sediments were quartz, feldspars, and calcite, with minor amounts of magnetite and clay minerals. Quartz grains commonly exhibited coatings that were greater than 10 nm in thickness and composed of an illite-smectite clay with occluded ferrihydrite and goethite nanoparticles. Chemical extractions of quartz grains removed from the sediments were used to estimate the masses of iron and aluminum present in the coatings. Various surface complexation modeling approaches were compared in terms of the ability to describe the U(VI) experimental data and the data requirements for model application to the sediments. Published models for U(VI) adsorption on reference minerals were applied to predict U(VI) adsorption based on assumptions about the sediment surface composition and physical properties (e.g., surface area and electrical double layer). Predictions from these models were highly variable, with results overpredicting or underpredicting the experimental data, depending on the assumptions used to apply the model. Although the models for reference minerals are supported by detailed experimental studies (and in ideal cases, surface spectroscopy), the results suggest that errors are caused in applying the models directly to the sediments by uncertain knowledge of: 1) the proportion and types of

Applied probability models with optimization applications

CERN Document Server

Ross, Sheldon M

1992-01-01

Concise advanced-level introduction to stochastic processes that frequently arise in applied probability. Largely self-contained text covers Poisson process, renewal theory, Markov chains, inventory theory, Brownian motion and continuous time optimization models, much more. Problems and references at chapter ends. ""Excellent introduction."" - Journal of the American Statistical Association. Bibliography. 1970 edition.

Applying an Archetype-Based Approach to Electroencephalography/Event-Related Potential Experiments in the EEGBase Resource.

Science.gov (United States)

Papež, Václav; Mouček, Roman

2017-01-01

The purpose of this study is to investigate the feasibility of applying openEHR (an archetype-based approach for electronic health records representation) to modeling data stored in EEGBase, a portal for experimental electroencephalography/event-related potential (EEG/ERP) data management. The study evaluates re-usage of existing openEHR archetypes and proposes a set of new archetypes together with the openEHR templates covering the domain. The main goals of the study are to (i) link existing EEGBase data/metadata and openEHR archetype structures and (ii) propose a new openEHR archetype set describing the EEG/ERP domain since this set of archetypes currently does not exist in public repositories. The main methodology is based on the determination of the concepts obtained from EEGBase experimental data and metadata that are expressible structurally by the openEHR reference model and semantically by openEHR archetypes. In addition, templates as the third openEHR resource allow us to define constraints over archetypes. Clinical Knowledge Manager (CKM), a public openEHR archetype repository, was searched for the archetypes matching the determined concepts. According to the search results, the archetypes already existing in CKM were applied and the archetypes not existing in the CKM were newly developed. openEHR archetypes support linkage to external terminologies. To increase semantic interoperability of the new archetypes, binding with the existing odML electrophysiological terminology was assured. Further, to increase structural interoperability, also other current solutions besides EEGBase were considered during the development phase. Finally, a set of templates using the selected archetypes was created to meet EEGBase requirements. A set of eleven archetypes that encompassed the domain of experimental EEG/ERP measurements were identified. Of these, six were reused without changes, one was extended, and four were newly created. All archetypes were arranged in the

Applying a Problem Based Learning Approach to Land Management Education

DEFF Research Database (Denmark)

Enemark, Stig

Land management covers a wide range activities associated with the management of land and natural resources that are required to fulfil political objectives and achieve sustainable development. This paper presents an overall understanding of the land management paradigm and the benefits of good...... land governance to society. A land administration system provides a country with the infrastructure to implement land-related policies and land management strategies. By applying this land management profile to surveying education, this paper suggests that there is a need to move away from an exclusive...... engineering focus toward adopting an interdisciplinary and problem-based approach to ensure that academic programmes can cope with the wide range of land administration functions and challenges. An interdisciplinary approach to surveying education calls for the need to address issues and problems in a real...

A semiparametric graphical modelling approach for large-scale equity selection.

Science.gov (United States)

Liu, Han; Mulvey, John; Zhao, Tianqi

2016-01-01

We propose a new stock selection strategy that exploits rebalancing returns and improves portfolio performance. To effectively harvest rebalancing gains, we apply ideas from elliptical-copula graphical modelling and stability inference to select stocks that are as independent as possible. The proposed elliptical-copula graphical model has a latent Gaussian representation; its structure can be effectively inferred using the regularized rank-based estimators. The resulting algorithm is computationally efficient and scales to large data-sets. To show the efficacy of the proposed method, we apply it to conduct equity selection based on a 16-year health care stock data-set and a large 34-year stock data-set. Empirical tests show that the proposed method is superior to alternative strategies including a principal component analysis-based approach and the classical Markowitz strategy based on the traditional buy-and-hold assumption.

Systems approach to modeling the Token Bucket algorithm in computer networks

Directory of Open Access Journals (Sweden)

Ahmed N. U.

2002-01-01

Full Text Available In this paper, we construct a new dynamic model for the Token Bucket (TB algorithm used in computer networks and use systems approach for its analysis. This model is then augmented by adding a dynamic model for a multiplexor at an access node where the TB exercises a policing function. In the model, traffic policing, multiplexing and network utilization are formally defined. Based on the model, we study such issues as (quality of service QoS, traffic sizing and network dimensioning. Also we propose an algorithm using feedback control to improve QoS and network utilization. Applying MPEG video traces as the input traffic to the model, we verify the usefulness and effectiveness of our model.

Model-fitting approach to kinetic analysis of non-isothermal oxidation of molybdenite

International Nuclear Information System (INIS)

Ebrahimi Kahrizsangi, R.; Abbasi, M. H.; Saidi, A.

2007-01-01

The kinetics of molybdenite oxidation was studied by non-isothermal TGA-DTA with heating rate 5 d eg C .min -1 . The model-fitting kinetic approach applied to TGA data. The Coats-Redfern method used of model fitting. The popular model-fitting gives excellent fit non-isothermal data in chemically controlled regime. The apparent activation energy was determined to be about 34.2 kcalmol -1 With pre-exponential factor about 10 8 sec -1 for extent of reaction less than 0.5

LEARNING SEMANTICS-ENHANCED LANGUAGE MODELS APPLIED TO UNSUEPRVISED WSD

Energy Technology Data Exchange (ETDEWEB)

VERSPOOR, KARIN [Los Alamos National Laboratory; LIN, SHOU-DE [Los Alamos National Laboratory

2007-01-29

An N-gram language model aims at capturing statistical syntactic word order information from corpora. Although the concept of language models has been applied extensively to handle a variety of NLP problems with reasonable success, the standard model does not incorporate semantic information, and consequently limits its applicability to semantic problems such as word sense disambiguation. We propose a framework that integrates semantic information into the language model schema, allowing a system to exploit both syntactic and semantic information to address NLP problems. Furthermore, acknowledging the limited availability of semantically annotated data, we discuss how the proposed model can be learned without annotated training examples. Finally, we report on a case study showing how the semantics-enhanced language model can be applied to unsupervised word sense disambiguation with promising results.

A Systematic Approach to Determining the Identifiability of Multistage Carcinogenesis Models.

Science.gov (United States)

Brouwer, Andrew F; Meza, Rafael; Eisenberg, Marisa C

2017-07-01

Multistage clonal expansion (MSCE) models of carcinogenesis are continuous-time Markov process models often used to relate cancer incidence to biological mechanism. Identifiability analysis determines what model parameter combinations can, theoretically, be estimated from given data. We use a systematic approach, based on differential algebra methods traditionally used for deterministic ordinary differential equation (ODE) models, to determine identifiable combinations for a generalized subclass of MSCE models with any number of preinitation stages and one clonal expansion. Additionally, we determine the identifiable combinations of the generalized MSCE model with up to four clonal expansion stages, and conjecture the results for any number of clonal expansion stages. The results improve upon previous work in a number of ways and provide a framework to find the identifiable combinations for further variations on the MSCE models. Finally, our approach, which takes advantage of the Kolmogorov backward equations for the probability generating functions of the Markov process, demonstrates that identifiability methods used in engineering and mathematics for systems of ODEs can be applied to continuous-time Markov processes. © 2016 Society for Risk Analysis.

Setting research priorities by applying the combined approach matrix.

Science.gov (United States)

Ghaffar, Abdul

2009-04-01

Priority setting in health research is a dynamic process. Different organizations and institutes have been working in the field of research priority setting for many years. In 1999 the Global Forum for Health Research presented a research priority setting tool called the Combined Approach Matrix or CAM. Since its development, the CAM has been successfully applied to set research priorities for diseases, conditions and programmes at global, regional and national levels. This paper briefly explains the CAM methodology and how it could be applied in different settings, giving examples and describing challenges encountered in the process of setting research priorities and providing recommendations for further work in this field. The construct and design of the CAM is explained along with different steps needed, including planning and organization of a priority-setting exercise and how it could be applied in different settings. The application of the CAM are described by using three examples. The first concerns setting research priorities for a global programme, the second describes application at the country level and the third setting research priorities for diseases. Effective application of the CAM in different and diverse environments proves its utility as a tool for setting research priorities. Potential challenges encountered in the process of research priority setting are discussed and some recommendations for further work in this field are provided.

Application of declarative modeling approaches for external events

International Nuclear Information System (INIS)

Anoba, R.C.

2005-01-01

Probabilistic Safety Assessments (PSAs) are increasingly being used as a tool for supporting the acceptability of design, procurement, construction, operation, and maintenance activities at Nuclear Power Plants. Since the issuance of Generic Letter 88-20 and subsequent IPE/IPEEE assessments, the NRC has issued several Regulatory Guides such as RG 1.174 to describe the use of PSA in risk-informed regulation activities. Most PSA have the capability to address internal events including internal floods. As the more demands are being placed for using the PSA to support risk-informed applications, there has been a growing need to integrate other eternal events (Seismic, Fire, etc.) into the logic models. Most external events involve spatial dependencies and usually impact the logic models at the component level. Therefore, manual insertion of external events impacts into a complex integrated fault tree model may be too cumbersome for routine uses of the PSA. Within the past year, a declarative modeling approach has been developed to automate the injection of external events into the PSA. The intent of this paper is to introduce the concept of declarative modeling in the context of external event applications. A declarative modeling approach involves the definition of rules for injection of external event impacts into the fault tree logic. A software tool such as the EPRI's XInit program can be used to interpret the pre-defined rules and automatically inject external event elements into the PSA. The injection process can easily be repeated, as required, to address plant changes, sensitivity issues, changes in boundary conditions, etc. External event elements may include fire initiating events, seismic initiating events, seismic fragilities, fire-induced hot short events, special human failure events, etc. This approach has been applied at a number of US nuclear power plants including a nuclear power plant in Romania. (authors)

Surrogate based approaches to parameter inference in ocean models

KAUST Repository

Knio, Omar

2016-01-06

This talk discusses the inference of physical parameters using model surrogates. Attention is focused on the use of sampling schemes to build suitable representations of the dependence of the model response on uncertain input data. Non-intrusive spectral projections and regularized regressions are used for this purpose. A Bayesian inference formalism is then applied to update the uncertain inputs based on available measurements or observations. To perform the update, we consider two alternative approaches, based on the application of Markov Chain Monte Carlo methods or of adjoint-based optimization techniques. We outline the implementation of these techniques to infer dependence of wind drag, bottom drag, and internal mixing coefficients.

Surrogate based approaches to parameter inference in ocean models

KAUST Repository

Knio, Omar

2016-01-01

This talk discusses the inference of physical parameters using model surrogates. Attention is focused on the use of sampling schemes to build suitable representations of the dependence of the model response on uncertain input data. Non-intrusive spectral projections and regularized regressions are used for this purpose. A Bayesian inference formalism is then applied to update the uncertain inputs based on available measurements or observations. To perform the update, we consider two alternative approaches, based on the application of Markov Chain Monte Carlo methods or of adjoint-based optimization techniques. We outline the implementation of these techniques to infer dependence of wind drag, bottom drag, and internal mixing coefficients.

Applying nonlinear MODM model to supply chain management with quantity discount policy under complex fuzzy environment

Directory of Open Access Journals (Sweden)

Zhe Zhang

2014-06-01

Full Text Available Purpose: The aim of this paper is to deal with the supply chain management (SCM with quantity discount policy under the complex fuzzy environment, which is characterized as the bi-fuzzy variables. By taking into account the strategy and the process of decision making, a bi-fuzzy nonlinear multiple objective decision making (MODM model is presented to solve the proposed problem.Design/methodology/approach: The bi-fuzzy variables in the MODM model are transformed into the trapezoidal fuzzy variables by the DMs's degree of optimism ?1 and ?2, which are de-fuzzified by the expected value index subsequently. For solving the complex nonlinear model, a multi-objective adaptive particle swarm optimization algorithm (MO-APSO is designed as the solution method.Findings: The proposed model and algorithm are applied to a typical example of SCM problem to illustrate the effectiveness. Based on the sensitivity analysis of the results, the bi-fuzzy nonlinear MODM SCM model is proved to be sensitive to the possibility level ?1.Practical implications: The study focuses on the SCM under complex fuzzy environment in SCM, which has a great practical significance. Therefore, the bi-fuzzy MODM model and MO-APSO can be further applied in SCM problem with quantity discount policy.Originality/value: The bi-fuzzy variable is employed in the nonlinear MODM model of SCM to characterize the hybrid uncertain environment, and this work is original. In addition, the hybrid crisp approach is proposed to transferred to model to an equivalent crisp one by the DMs's degree of optimism and the expected value index. Since the MODM model consider the bi-fuzzy environment and quantity discount policy, so this paper has a great practical significance.

The systems approach for applying artificial intelligence to space station automation (Invited Paper)

Science.gov (United States)

Grose, Vernon L.

1985-12-01

The progress of technology is marked by fragmentation -- dividing research and development into ever narrower fields of specialization. Ultimately, specialists know everything about nothing. And hope for integrating those slender slivers of specialty into a whole fades. Without an integrated, all-encompassing perspective, technology becomes applied in a lopsided and often inefficient manner. A decisionary model, developed and applied for NASA's Chief Engineer toward establishment of commercial space operations, can be adapted to the identification, evaluation, and selection of optimum application of artificial intelligence for space station automation -- restoring wholeness to a situation that is otherwise chaotic due to increasing subdivision of effort. Issues such as functional assignments for space station task, domain, and symptom modules can be resolved in a manner understood by all parties rather than just the person with assigned responsibility -- and ranked by overall significance to mission accomplishment. Ranking is based on the three basic parameters of cost, performance, and schedule. This approach has successfully integrated many diverse specialties in situations like worldwide terrorism control, coal mining safety, medical malpractice risk, grain elevator explosion prevention, offshore drilling hazards, and criminal justice resource allocation -- all of which would have otherwise been subject to "squeaky wheel" emphasis and support of decision-makers.

Applying a social network analysis (SNA) approach to understanding radiologists' performance in reading mammograms

Science.gov (United States)

Tavakoli Taba, Seyedamir; Hossain, Liaquat; Heard, Robert; Brennan, Patrick; Lee, Warwick; Lewis, Sarah

2017-03-01

Rationale and objectives: Observer performance has been widely studied through examining the characteristics of individuals. Applying a systems perspective, while understanding of the system's output, requires a study of the interactions between observers. This research explains a mixed methods approach to applying a social network analysis (SNA), together with a more traditional approach of examining personal/ individual characteristics in understanding observer performance in mammography. Materials and Methods: Using social networks theories and measures in order to understand observer performance, we designed a social networks survey instrument for collecting personal and network data about observers involved in mammography performance studies. We present the results of a study by our group where 31 Australian breast radiologists originally reviewed 60 mammographic cases (comprising of 20 abnormal and 40 normal cases) and then completed an online questionnaire about their social networks and personal characteristics. A jackknife free response operating characteristic (JAFROC) method was used to measure performance of radiologists. JAFROC was tested against various personal and network measures to verify the theoretical model. Results: The results from this study suggest a strong association between social networks and observer performance for Australian radiologists. Network factors accounted for 48% of variance in observer performance, in comparison to 15.5% for the personal characteristics for this study group. Conclusion: This study suggest a strong new direction for research into improving observer performance. Future studies in observer performance should consider social networks' influence as part of their research paradigm, with equal or greater vigour than traditional constructs of personal characteristics.

A trust region approach with multivariate Padé model for optimal circuit design

Science.gov (United States)

Abdel-Malek, Hany L.; Ebid, Shaimaa E. K.; Mohamed, Ahmed S. A.

2017-11-01

Since the optimization process requires a significant number of consecutive function evaluations, it is recommended to replace the function by an easily evaluated approximation model during the optimization process. The model suggested in this article is based on a multivariate Padé approximation. This model is constructed using data points of ?, where ? is the number of parameters. The model is updated over a sequence of trust regions. This model avoids the slow convergence of linear models of ? and has features of quadratic models that need interpolation data points of ?. The proposed approach is tested by applying it to several benchmark problems. Yield optimization using such a direct method is applied to some practical circuit examples. Minimax solution leads to a suitable initial point to carry out the yield optimization process. The yield is optimized by the proposed derivative-free method for active and passive filter examples.

Quantum correlated cluster mean-field theory applied to the transverse Ising model.

Science.gov (United States)

Zimmer, F M; Schmidt, M; Maziero, Jonas

2016-06-01

Mean-field theory (MFT) is one of the main available tools for analytical calculations entailed in investigations regarding many-body systems. Recently, there has been a surge of interest in ameliorating this kind of method, mainly with the aim of incorporating geometric and correlation properties of these systems. The correlated cluster MFT (CCMFT) is an improvement that succeeded quite well in doing that for classical spin systems. Nevertheless, even the CCMFT presents some deficiencies when applied to quantum systems. In this article, we address this issue by proposing the quantum CCMFT (QCCMFT), which, in contrast to its former approach, uses general quantum states in its self-consistent mean-field equations. We apply the introduced QCCMFT to the transverse Ising model in honeycomb, square, and simple cubic lattices and obtain fairly good results both for the Curie temperature of thermal phase transition and for the critical field of quantum phase transition. Actually, our results match those obtained via exact solutions, series expansions or Monte Carlo simulations.

An application of the Health Action Process Approach model to oral hygiene behaviour and dental plaque in adolescents with fixed orthodontic appliances

NARCIS (Netherlands)

Scheerman, J.F.M.; Empelen, P. van; Loveren, C. van; Pakpour, A.H.; Meijel, B. van; Gholami, M.; Mierzaie, Z.; Braak, M.C.T. van; Verrips, G.H.W.

2017-01-01

Background. The Health Action Process Approach (HAPA) model addresses health behaviours, but it has never been applied to model adolescents’ oral hygiene behaviour during fixed orthodontic treatment. Aim. This study aimed to apply the HAPA model to explain adolescents’ oral hygiene behaviour and

Modeling energy fluxes in heterogeneous landscapes employing a mosaic approach

Science.gov (United States)

Klein, Christian; Thieme, Christoph; Priesack, Eckart

2015-04-01

Recent studies show that uncertainties in regional and global climate and weather simulations are partly due to inadequate descriptions of the energy flux exchanges between the land surface and the atmosphere. One major shortcoming is the limitation of the grid-cell resolution, which is recommended to be about at least 3x3 km² in most models due to limitations in the model physics. To represent each individual grid cell most models select one dominant soil type and one dominant land use type. This resolution, however, is often too coarse in regions where the spatial diversity of soil and land use types are high, e.g. in Central Europe. An elegant method to avoid the shortcoming of grid cell resolution is the so called mosaic approach. This approach is part of the recently developed ecosystem model framework Expert-N 5.0. The aim of this study was to analyze the impact of the characteristics of two managed fields, planted with winter wheat and potato, on the near surface soil moistures and on the near surface energy flux exchanges of the soil-plant-atmosphere interface. The simulated energy fluxes were compared with eddy flux tower measurements between the respective fields at the research farm Scheyern, North-West of Munich, Germany. To perform these simulations, we coupled the ecosystem model Expert-N 5.0 to an analytical footprint model. The coupled model system has the ability to calculate the mixing ratio of the surface energy fluxes at a given point within one grid cell (in this case at the flux tower between the two fields). This approach accounts for the differences of the two soil types, of land use managements, and of canopy properties due to footprint size dynamics. Our preliminary simulation results show that a mosaic approach can improve modeling and analyzing energy fluxes when the land surface is heterogeneous. In this case our applied method is a promising approach to extend weather and climate models on the regional and on the global scale.

A feature-based approach to modeling protein-DNA interactions.

Directory of Open Access Journals (Sweden)

Eilon Sharon

Full Text Available Transcription factor (TF binding to its DNA target site is a fundamental regulatory interaction. The most common model used to represent TF binding specificities is a position specific scoring matrix (PSSM, which assumes independence between binding positions. However, in many cases, this simplifying assumption does not hold. Here, we present feature motif models (FMMs, a novel probabilistic method for modeling TF-DNA interactions, based on log-linear models. Our approach uses sequence features to represent TF binding specificities, where each feature may span multiple positions. We develop the mathematical formulation of our model and devise an algorithm for learning its structural features from binding site data. We also developed a discriminative motif finder, which discovers de novo FMMs that are enriched in target sets of sequences compared to background sets. We evaluate our approach on synthetic data and on the widely used TF chromatin immunoprecipitation (ChIP dataset of Harbison et al. We then apply our algorithm to high-throughput TF ChIP data from mouse and human, reveal sequence features that are present in the binding specificities of mouse and human TFs, and show that FMMs explain TF binding significantly better than PSSMs. Our FMM learning and motif finder software are available at http://genie.weizmann.ac.il/.

Learning to Apply Models of Materials While Explaining Their Properties

Science.gov (United States)

Karpin, Tiia; Juuti, Kalle; Lavonen, Jari

2014-01-01

Background: Applying structural models is important to chemistry education at the upper secondary level, but it is considered one of the most difficult topics to learn. Purpose: This study analyses to what extent in designed lessons students learned to apply structural models in explaining the properties and behaviours of various materials.…

Modelling and simulating retail management practices: a first approach

OpenAIRE

Siebers, Peer-Olaf; Aickelin, Uwe; Celia, Helen; Clegg, Chris

2010-01-01

Multi-agent systems offer a new and exciting way of understanding the world of work. We apply agent-based modeling and simulation to investigate a set of problems\\ud in a retail context. Specifically, we are working to understand the relationship between people management practices on the shop-floor and retail performance. Despite the fact we are working within a relatively novel and complex domain, it is clear that using an agent-based approach offers great potential for improving organizati...

Responses of mink to auditory stimuli: Prerequisites for applying the ‘cognitive bias’ approach

DEFF Research Database (Denmark)

Svendsen, Pernille Maj; Malmkvist, Jens; Halekoh, Ulrich

2012-01-01

The aim of the study was to determine and validate prerequisites for applying a cognitive (judgement) bias approach to assessing welfare in farmed mink (Neovison vison). We investigated discrimination ability and associative learning ability using auditory cues. The mink (n = 15 females) were...... farmed mink in a judgement bias approach would thus appear to be feasible. However several specific issues are to be considered in order to successfully adapt a cognitive bias approach to mink, and these are discussed....

A modular approach to inverse modelling of a district heating facility with seasonal thermal energy storage

DEFF Research Database (Denmark)

Tordrup, Karl Woldum; Poulsen, Uffe Vestergaard; Nielsen, Carsten

2017-01-01

We use a modular approach to develop a TRNSYS model for a district heating facility by applying inverse modelling to one year of operational data for individual components. We assemble the components into a single TRNSYS model for the full system using the accumulation tanks as a central hub conn...

Modeling of scale-dependent bacterial growth by chemical kinetics approach.

Science.gov (United States)

Martínez, Haydee; Sánchez, Joaquín; Cruz, José-Manuel; Ayala, Guadalupe; Rivera, Marco; Buhse, Thomas

2014-01-01

We applied the so-called chemical kinetics approach to complex bacterial growth patterns that were dependent on the liquid-surface-area-to-volume ratio (SA/V) of the bacterial cultures. The kinetic modeling was based on current experimental knowledge in terms of autocatalytic bacterial growth, its inhibition by the metabolite CO2, and the relief of inhibition through the physical escape of the inhibitor. The model quantitatively reproduces kinetic data of SA/V-dependent bacterial growth and can discriminate between differences in the growth dynamics of enteropathogenic E. coli, E. coli JM83, and Salmonella typhimurium on one hand and Vibrio cholerae on the other hand. Furthermore, the data fitting procedures allowed predictions about the velocities of the involved key processes and the potential behavior in an open-flow bacterial chemostat, revealing an oscillatory approach to the stationary states.

Modeling of Scale-Dependent Bacterial Growth by Chemical Kinetics Approach

Directory of Open Access Journals (Sweden)

Haydee Martínez

2014-01-01

Full Text Available We applied the so-called chemical kinetics approach to complex bacterial growth patterns that were dependent on the liquid-surface-area-to-volume ratio (SA/V of the bacterial cultures. The kinetic modeling was based on current experimental knowledge in terms of autocatalytic bacterial growth, its inhibition by the metabolite CO2, and the relief of inhibition through the physical escape of the inhibitor. The model quantitatively reproduces kinetic data of SA/V-dependent bacterial growth and can discriminate between differences in the growth dynamics of enteropathogenic E. coli, E. coli  JM83, and Salmonella typhimurium on one hand and Vibrio cholerae on the other hand. Furthermore, the data fitting procedures allowed predictions about the velocities of the involved key processes and the potential behavior in an open-flow bacterial chemostat, revealing an oscillatory approach to the stationary states.

Scientific Approach and Inquiry Learning Model in the Topic of Buffer Solution: A Content Analysis

Science.gov (United States)

Kusumaningrum, I. A.; Ashadi, A.; Indriyanti, N. Y.

2017-09-01

Many concepts in buffer solution cause student’s misconception. Understanding science concepts should apply the scientific approach. One of learning models which is suitable with this approach is inquiry. Content analysis was used to determine textbook compatibility with scientific approach and inquiry learning model in the concept of buffer solution. By using scientific indicator tools (SIT) and Inquiry indicator tools (IIT), we analyzed three chemistry textbooks grade 11 of senior high school labeled as P, Q, and R. We described how textbook compatibility with scientific approach and inquiry learning model in the concept of buffer solution. The results show that textbook P and Q were very poor and book R was sufficient because the textbook still in procedural level. Chemistry textbooks used at school are needed to be improved in term of scientific approach and inquiry learning model. The result of these analyses might be of interest in order to write future potential textbooks.

FEM-based neural-network approach to nonlinear modeling with application to longitudinal vehicle dynamics control.

Science.gov (United States)

Kalkkuhl, J; Hunt, K J; Fritz, H

1999-01-01

An finite-element methods (FEM)-based neural-network approach to Nonlinear AutoRegressive with eXogenous input (NARX) modeling is presented. The method uses multilinear interpolation functions on C0 rectangular elements. The local and global structure of the resulting model is analyzed. It is shown that the model can be interpreted both as a local model network and a single layer feedforward neural network. The main aim is to use the model for nonlinear control design. The proposed FEM NARX description is easily accessible to feedback linearizing control techniques. Its use with a two-degrees of freedom nonlinear internal model controller is discussed. The approach is applied to modeling of the nonlinear longitudinal dynamics of an experimental lorry, using measured data. The modeling results are compared with local model network and multilayer perceptron approaches. A nonlinear speed controller was designed based on the identified FEM model. The controller was implemented in a test vehicle, and several experimental results are presented.

Electrochemo-hydrodynamics modeling approach for a uranium electrowinning cell

Energy Technology Data Exchange (ETDEWEB)

Kim, K.R.; Paek, S.; Ahn, D.H., E-mail: krkim1@kaeri.re.kr, E-mail: swpaek@kaeri.re.kr, E-mail: dhahn2@kaeri.re.kr [Korea Atomic Energy Research Institute, Daejeon (Korea, Republic of); Park, J.Y.; Hwang, I.S., E-mail: d486916@snu.ac.kr, E-mail: hisline@snu.ac.kr [Department of Nuclear Engineering, Seoul National University (Korea, Republic of)

2011-07-01

This study demonstrated a simulation based on fully coupling of electrochemical kinetics with 3- dimensional transport of ionic species in a flowing molten-salt electrolyte through a simplified channel cell of uranium electro winner. Dependences of ionic electro-transport on the velocity of stationary electrolyte flow were studied using a coupling approach of electrochemical reaction model. The present model was implemented in a commercially available computational fluid dynamics (CFD) platform, Ansys-CFX, using its customization ability via user defined functions. The main parameters characterizing the effect of the turbulent flow of an electrolyte between two planar electrodes were demonstrated by means of CFD-based multiphysics simulation approach. Simulation was carried out for the case of uranium electrowinning characteristics in a stream of molten salt electrolyte. This approach was taken into account the concentration profile at the electrode surface, to represent the variation of the diffusion limited current density as a function of the flow characteristics and of applied current density. It was able to predict conventional current voltage relation in addition to details of electrolyte fluid dynamics and electrochemical variable, such as flow field, species concentrations, potential, and current distributions throughout the current driven cell. (author)

Electrochemo-hydrodynamics modeling approach for a uranium electrowinning cell

International Nuclear Information System (INIS)

Kim, K.R.; Paek, S.; Ahn, D.H.; Park, J.Y.; Hwang, I.S.

2011-01-01

This study demonstrated a simulation based on fully coupling of electrochemical kinetics with 3- dimensional transport of ionic species in a flowing molten-salt electrolyte through a simplified channel cell of uranium electro winner. Dependences of ionic electro-transport on the velocity of stationary electrolyte flow were studied using a coupling approach of electrochemical reaction model. The present model was implemented in a commercially available computational fluid dynamics (CFD) platform, Ansys-CFX, using its customization ability via user defined functions. The main parameters characterizing the effect of the turbulent flow of an electrolyte between two planar electrodes were demonstrated by means of CFD-based multiphysics simulation approach. Simulation was carried out for the case of uranium electrowinning characteristics in a stream of molten salt electrolyte. This approach was taken into account the concentration profile at the electrode surface, to represent the variation of the diffusion limited current density as a function of the flow characteristics and of applied current density. It was able to predict conventional current voltage relation in addition to details of electrolyte fluid dynamics and electrochemical variable, such as flow field, species concentrations, potential, and current distributions throughout the current driven cell. (author)

Lattice Hamiltonian approach to the massless Schwinger model. Precise extraction of the mass gap

International Nuclear Information System (INIS)

Cichy, Krzysztof; Poznan Univ.; Kujawa-Cichy, Agnieszka; Szyniszewski, Marcin; Manchester Univ.

2012-12-01

We present results of applying the Hamiltonian approach to the massless Schwinger model. A finite basis is constructed using the strong coupling expansion to a very high order. Using exact diagonalization, the continuum limit can be reliably approached. This allows to reproduce the analytical results for the ground state energy, as well as the vector and scalar mass gaps to an outstanding precision better than 10 -6 %.

International Conference on Applied Mathematics, Modeling and Computational Science & Annual meeting of the Canadian Applied and Industrial Mathematics

CERN Document Server

Bélair, Jacques; Kunze, Herb; Makarov, Roman; Melnik, Roderick; Spiteri, Raymond J

2016-01-01

Focusing on five main groups of interdisciplinary problems, this book covers a wide range of topics in mathematical modeling, computational science and applied mathematics. It presents a wealth of new results in the development of modeling theories and methods, advancing diverse areas of applications and promoting interdisciplinary interactions between mathematicians, scientists, engineers and representatives from other disciplines. The book offers a valuable source of methods, ideas, and tools developed for a variety of disciplines, including the natural and social sciences, medicine, engineering, and technology. Original results are presented on both the fundamental and applied level, accompanied by an ample number of real-world problems and examples emphasizing the interdisciplinary nature and universality of mathematical modeling, and providing an excellent outline of today’s challenges. Mathematical modeling, with applied and computational methods and tools, plays a fundamental role in modern science a...

A computational approach to compare regression modelling strategies in prediction research.

Science.gov (United States)

Pajouheshnia, Romin; Pestman, Wiebe R; Teerenstra, Steven; Groenwold, Rolf H H

2016-08-25

It is often unclear which approach to fit, assess and adjust a model will yield the most accurate prediction model. We present an extension of an approach for comparing modelling strategies in linear regression to the setting of logistic regression and demonstrate its application in clinical prediction research. A framework for comparing logistic regression modelling strategies by their likelihoods was formulated using a wrapper approach. Five different strategies for modelling, including simple shrinkage methods, were compared in four empirical data sets to illustrate the concept of a priori strategy comparison. Simulations were performed in both randomly generated data and empirical data to investigate the influence of data characteristics on strategy performance. We applied the comparison framework in a case study setting. Optimal strategies were selected based on the results of a priori comparisons in a clinical data set and the performance of models built according to each strategy was assessed using the Brier score and calibration plots. The performance of modelling strategies was highly dependent on the characteristics of the development data in both linear and logistic regression settings. A priori comparisons in four empirical data sets found that no strategy consistently outperformed the others. The percentage of times that a model adjustment strategy outperformed a logistic model ranged from 3.9 to 94.9 %, depending on the strategy and data set. However, in our case study setting the a priori selection of optimal methods did not result in detectable improvement in model performance when assessed in an external data set. The performance of prediction modelling strategies is a data-dependent process and can be highly variable between data sets within the same clinical domain. A priori strategy comparison can be used to determine an optimal logistic regression modelling strategy for a given data set before selecting a final modelling approach.

A multicriteria decision making approach applied to improving maintenance policies in healthcare organizations.

Science.gov (United States)

Carnero, María Carmen; Gómez, Andrés

2016-04-23

Healthcare organizations have far greater maintenance needs for their medical equipment than other organization, as many are used directly with patients. However, the literature on asset management in healthcare organizations is very limited. The aim of this research is to provide more rational application of maintenance policies, leading to an increase in quality of care. This article describes a multicriteria decision-making approach which integrates Markov chains with the multicriteria Measuring Attractiveness by a Categorical Based Evaluation Technique (MACBETH), to facilitate the best choice of combination of maintenance policies by using the judgements of a multi-disciplinary decision group. The proposed approach takes into account the level of acceptance that a given alternative would have among professionals. It also takes into account criteria related to cost, quality of care and impact of care cover. This multicriteria approach is applied to four dialysis subsystems: patients infected with hepatitis C, infected with hepatitis B, acute and chronic; in all cases, the maintenance strategy obtained consists of applying corrective and preventive maintenance plus two reserve machines. The added value in decision-making practices from this research comes from: (i) integrating the use of Markov chains to obtain the alternatives to be assessed by a multicriteria methodology; (ii) proposing the use of MACBETH to make rational decisions on asset management in healthcare organizations; (iii) applying the multicriteria approach to select a set or combination of maintenance policies in four dialysis subsystems of a health care organization. In the multicriteria decision making approach proposed, economic criteria have been used, related to the quality of care which is desired for patients (availability), and the acceptance that each alternative would have considering the maintenance and healthcare resources which exist in the organization, with the inclusion of a

Applying a Modified Triad Approach to Investigate Wastewater lines

International Nuclear Information System (INIS)

Pawlowicz, R.; Urizar, L.; Blanchard, S.; Jacobsen, K.; Scholfield, J.

2006-01-01

Approximately 20 miles of wastewater lines are below grade at an active military Base. This piping network feeds or fed domestic or industrial wastewater treatment plants on the Base. Past wastewater line investigations indicated potential contaminant releases to soil and groundwater. Further environmental assessment was recommended to characterize the lines because of possible releases. A Remedial Investigation (RI) using random sampling or use of sampling points spaced at predetermined distances along the entire length of the wastewater lines, however, would be inefficient and cost prohibitive. To accomplish RI goals efficiently and within budget, a modified Triad approach was used to design a defensible sampling and analysis plan and perform the investigation. The RI task was successfully executed and resulted in a reduced fieldwork schedule, and sampling and analytical costs. Results indicated that no major releases occurred at the biased sampling points. It was reasonably extrapolated that since releases did not occur at the most likely locations, then the entire length of a particular wastewater line segment was unlikely to have contaminated soil or groundwater and was recommended for no further action. A determination of no further action was recommended for the majority of the waste lines after completing the investigation. The modified Triad approach was successful and a similar approach could be applied to investigate wastewater lines on other United States Department of Defense or Department of Energy facilities. (authors)

A new kinetic biphasic approach applied to biodiesel process intensification

Energy Technology Data Exchange (ETDEWEB)

Russo, V.; Tesser, R.; Di Serio, M.; Santacesaria, E. [Naples Univ. (Italy). Dept. of Chemistry

2012-07-01

Many different papers have been published on the kinetics of the transesterification of vegetable oil with methanol, in the presence of alkaline catalysts to produce biodiesel. All the proposed approaches are based on the assumption of a pseudo-monophasic system. The consequence of these approaches is that some experimental aspects cannot be described. For the reaction performed in batch conditions, for example, the monophasic approach is not able to reproduce the different plateau obtained by using different amount of catalyst or the induction time observed at low stirring rates. Moreover, it has been observed by operating in continuous reactors that micromixing has a dramatic effect on the reaction rate. At this purpose, we have recently observed that is possible to obtain a complete conversion to biodiesel in less than 10 seconds of reaction time. This observation is confirmed also by other authors using different types of reactors like: static mixers, micro-reactors, oscillatory flow reactors, cavitational reactors, microwave reactors or centrifugal contactors. In this work we will show that a recently proposed biphasic kinetic approach is able to describe all the aspects before mentioned that cannot be described by the monophasic kinetic model. In particular, we will show that the biphasic kinetic model can describe both the induction time observed in the batch reactors, at low stirring rate, and the very high conversions obtainable in a micro-channel reactor. The adopted biphasic kinetic model is based on a reliable reaction mechanism that will be validated by the experimental evidences reported in this work. (orig.)

A Multiobjective Approach Applied to the Protein Structure Prediction Problem

Science.gov (United States)

2002-03-07

local conformations [38]. Moreover, all these models have the same theme in trying to define the properties a real protein has when folding. Today , it...attempted to solve the PSP problem with a real valued GA and found better results than a competitor (Scheraga, et al) [50]; however, today we know that...ACM Symposium on Applied computing (SAC01) (March 11-14 2001). Las Vegas, Nevada. [22] Derrida , B. “Random Energy Model: Limit of a Family of

Analyzing energy consumption of wireless networks. A model-based approach

Energy Technology Data Exchange (ETDEWEB)

Yue, Haidi

2013-03-04

During the last decades, wireless networking has been continuously a hot topic both in academy and in industry. Many different wireless networks have been introduced like wireless local area networks, wireless personal networks, wireless ad hoc networks, and wireless sensor networks. If these networks want to have a long term usability, the power consumed by the wireless devices in each of these networks needs to be managed efficiently. Hence, a lot of effort has been carried out for the analysis and improvement of energy efficiency, either for a specific network layer (protocol), or new cross-layer designs. In this thesis, we apply model-based approach for the analysis of energy consumption of different wireless protocols. The protocols under consideration are: one leader election protocol, one routing protocol, and two medium access control protocols. By model-based approach we mean that all these four protocols are formalized as some formal models, more precisely, as discrete-time Markov chains (DTMCs), Markov decision processes (MDPs), or stochastic timed automata (STA). For the first two models, DTMCs and MDPs, we model them in PRISM, a prominent model checker for probabilistic model checking, and apply model checking technique to analyze them. Model checking belongs to the family of formal methods. It discovers exhaustively all possible (reachable) states of the models, and checks whether these models meet a given specification. Specifications are system properties that we want to study, usually expressed by some logics, for instance, probabilistic computer tree logic (PCTL). However, while model checking relies on rigorous mathematical foundations and automatically explores the entire state space of a model, its applicability is also limited by the so-called state space explosion problem -- even systems of moderate size often yield models with an exponentially larger state space that thwart their analysis. Hence for the STA models in this thesis, since there

Nonlinear Eddy Viscosity Models applied to Wind Turbine Wakes

DEFF Research Database (Denmark)

Laan, van der, Paul Maarten; Sørensen, Niels N.; Réthoré, Pierre-Elouan

2013-01-01

The linear k−ε eddy viscosity model and modified versions of two existing nonlinear eddy viscosity models are applied to single wind turbine wake simulations using a Reynolds Averaged Navier-Stokes code. Results are compared with field wake measurements. The nonlinear models give better results...

Setting conservation management thresholds using a novel participatory modeling approach.

Science.gov (United States)

Addison, P F E; de Bie, K; Rumpff, L

2015-10-01

We devised a participatory modeling approach for setting management thresholds that show when management intervention is required to address undesirable ecosystem changes. This approach was designed to be used when management thresholds: must be set for environmental indicators in the face of multiple competing objectives; need to incorporate scientific understanding and value judgments; and will be set by participants with limited modeling experience. We applied our approach to a case study where management thresholds were set for a mat-forming brown alga, Hormosira banksii, in a protected area management context. Participants, including management staff and scientists, were involved in a workshop to test the approach, and set management thresholds to address the threat of trampling by visitors to an intertidal rocky reef. The approach involved trading off the environmental objective, to maintain the condition of intertidal reef communities, with social and economic objectives to ensure management intervention was cost-effective. Ecological scenarios, developed using scenario planning, were a key feature that provided the foundation for where to set management thresholds. The scenarios developed represented declines in percent cover of H. banksii that may occur under increased threatening processes. Participants defined 4 discrete management alternatives to address the threat of trampling and estimated the effect of these alternatives on the objectives under each ecological scenario. A weighted additive model was used to aggregate participants' consequence estimates. Model outputs (decision scores) clearly expressed uncertainty, which can be considered by decision makers and used to inform where to set management thresholds. This approach encourages a proactive form of conservation, where management thresholds and associated actions are defined a priori for ecological indicators, rather than reacting to unexpected ecosystem changes in the future. © 2015 The

A Toolkit Modeling Approach for Sustainable Forest Management Planning: Achieving Balance between Science and Local Needs

Directory of Open Access Journals (Sweden)

Brian R. Sturtevant

2007-12-01

Full Text Available To assist forest managers in balancing an increasing diversity of resource objectives, we developed a toolkit modeling approach for sustainable forest management (SFM. The approach inserts a meta-modeling strategy into a collaborative modeling framework grounded in adaptive management philosophy that facilitates participation among stakeholders, decision makers, and local domain experts in the meta-model building process. The modeling team works iteratively with each of these groups to define essential questions, identify data resources, and then determine whether available tools can be applied or adapted, or whether new tools can be rapidly created to fit the need. The desired goal of the process is a linked series of domain-specific models (tools that balances generalized "top-down" models (i.e., scientific models developed without input from the local system with case-specific customized "bottom-up" models that are driven primarily by local needs. Information flow between models is organized according to vertical (i.e., between scale and horizontal (i.e., within scale dimensions. We illustrate our approach within a 2.1 million hectare forest planning district in central Labrador, a forested landscape where social and ecological values receive a higher priority than economic values. However, the focus of this paper is on the process of how SFM modeling tools and concepts can be rapidly assembled and applied in new locations, balancing efficient transfer of science with adaptation to local needs. We use the Labrador case study to illustrate strengths and challenges uniquely associated with a meta-modeling approach to integrated modeling as it fits within the broader collaborative modeling framework. Principle advantages of the approach include the scientific rigor introduced by peer-reviewed models, combined with the adaptability of meta-modeling. A key challenge is the limited transparency of scientific models to different participatory groups

An agent-based approach to model land-use change at a regional scale

NARCIS (Netherlands)

Valbuena, D.F.; Verburg, P.H.; Bregt, A.K.; Ligtenberg, A.

2010-01-01

Land-use/cover change (LUCC) is a complex process that includes actors and factors at different social and spatial levels. A common approach to analyse and simulate LUCC as the result of individual decisions is agent-based modelling (ABM). However, ABM is often applied to simulate processes at local

Towards a realistic approach to validation of reactive transport models for performance assessment

International Nuclear Information System (INIS)

Siegel, M.D.

1993-01-01

Performance assessment calculations are based on geochemical models that assume that interactions among radionuclides, rocks and groundwaters under natural conditions, can be estimated or bound by data obtained from laboratory-scale studies. The data include radionuclide distribution coefficients, measured in saturated batch systems of powdered rocks, and retardation factors measured in short-term column experiments. Traditional approaches to model validation cannot be applied in a straightforward manner to the simple reactive transport models that use these data. An approach to model validation in support of performance assessment is described in this paper. It is based on a recognition of different levels of model validity and is compatible with the requirements of current regulations for high-level waste disposal. Activities that are being carried out in support of this approach include (1) laboratory and numerical experiments to test the validity of important assumptions inherent in current performance assessment methodologies,(2) integrated transport experiments, and (3) development of a robust coupled reaction/transport code for sensitivity analyses using massively parallel computers

Uncharted territory: A complex systems approach as an emerging paradigm in applied linguistics

Directory of Open Access Journals (Sweden)

Weideman, Albert J

2009-12-01

Full Text Available Developing a theory of applied linguistics is a top priority for the discipline today. The emergence of a new paradigm - a complex systems approach - in applied linguistics presents us with a unique opportunity to give prominence to the development of a foundational framework for this design discipline. Far from being a mere philosophical exercise, such a framework will find application in the training and induction of new entrants into the discipline within the developing context of South Africa, as well as internationally.

Does having the right visitor mix do the job? Applying an econometric shift-share model to regional tourism developments

OpenAIRE

Firgo, Matthias; Fritz, Oliver

2016-01-01

This paper is the first to apply an econometric shift-share model to tourism. The approach allows us to isolate the growth contributions of changes in regional touristic attractiveness from those induced by the structure of visitors, but does not share the caveats of the conventional shift-share approach. Our application to regional tourism in Austria reveals important results: First, differences in long-run performance between regions are mostly related to idiosyncratic changes in the touris...

What can the treatment of Parkinson's disease learn from dementia care; applying a bio-psycho-social approach to Parkinson's disease.

Science.gov (United States)

Gibson, Grant

2017-12-01

Within contemporary medical practice, Parkinson's disease (PD) is treated using a biomedical, neurological approach, which although bringing numerous benefits can struggle to engage with how people with PD experience the disease. A bio-psycho-social approach has not yet been established in PD; however, bio-psycho-social approaches adopted within dementia care practice could bring significant benefit to PD care. This paper summarises existing bio-psycho-social models of dementia care and explores how these models could also usefully be applied to care for PD. Specifically, this paper adapts the bio-psycho-social model for dementia developed by Spector and Orrell (), to suggest a bio-psycho-social model, which could be used to inform routine care in PD. Drawing on the biopsychosocial model of Dementia put forward by Spector and Orrell (), this paper explores the application of a bio-psycho-social model of PD. This model conceptualises PD as a trajectory, in which several interrelated fixed and tractable factors influence both PD's symptomology and the various biological and psychosocial challenges individuals will face as their disease progresses. Using an individual case study, this paper then illustrates how such a model can assist clinicians in identifying suitable interventions for people living with PD. This model concludes by discussing how a bio-psycho-social model could be used as a tool in PD's routine care. The model also encourages the development of a theoretical and practical framework for the future development of the role of the PD specialist nurse within routine practice. A biopsychosocial approach to Parkinson's Disease provides an opportunity to move towards a holistic model of care practice which addresses a wider range of factors affecting people living with PD. The paper puts forward a framework through which PD care practice can move towards a biopsychosocial perspective. PD specialist nurses are particularly well placed to adopt such a model

Modelling of ductile and cleavage fracture by local approach

International Nuclear Information System (INIS)

Samal, M.K.; Dutta, B.K.; Kushwaha, H.S.

2000-08-01

This report describes the modelling of ductile and cleavage fracture processes by local approach. It is now well known that the conventional fracture mechanics method based on single parameter criteria is not adequate to model the fracture processes. It is because of the existence of effect of size and geometry of flaw, loading type and rate on the fracture resistance behaviour of any structure. Hence, it is questionable to use same fracture resistance curves as determined from standard tests in the analysis of real life components because of existence of all the above effects. So, there is need to have a method in which the parameters used for the analysis will be true material properties, i.e. independent of geometry and size. One of the solutions to the above problem is the use of local approaches. These approaches have been extensively studied and applied to different materials (including SA33 Gr.6) in this report. Each method has been studied and reported in a separate section. This report has been divided into five sections. Section-I gives a brief review of the fundamentals of fracture process. Section-II deals with modelling of ductile fracture by locally uncoupled type of models. In this section, the critical cavity growth parameters of the different models have been determined for the primary heat transport (PHT) piping material of Indian pressurised heavy water reactor (PHWR). A comparative study has been done among different models. The dependency of the critical parameters on stress triaxiality factor has also been studied. It is observed that Rice and Tracey's model is the most suitable one. But, its parameters are not fully independent of triaxiality factor. For this purpose, a modification to Rice and Tracery's model is suggested in Section-III. Section-IV deals with modelling of ductile fracture process by locally coupled type of models. Section-V deals with the modelling of cleavage fracture process by Beremins model, which is based on Weibulls

Lattice Hamiltonian approach to the massless Schwinger model. Precise extraction of the mass gap

Energy Technology Data Exchange (ETDEWEB)

Cichy, Krzysztof [Deutsches Elektronen-Synchrotron (DESY), Zeuthen (Germany). John von Neumann-Inst. fuer Computing NIC; Poznan Univ. (Poland). Faculty of Physics; Kujawa-Cichy, Agnieszka [Poznan Univ. (Poland). Faculty of Physics; Szyniszewski, Marcin [Poznan Univ. (Poland). Faculty of Physics; Manchester Univ. (United Kingdom). NOWNano DTC

2012-12-15

We present results of applying the Hamiltonian approach to the massless Schwinger model. A finite basis is constructed using the strong coupling expansion to a very high order. Using exact diagonalization, the continuum limit can be reliably approached. This allows to reproduce the analytical results for the ground state energy, as well as the vector and scalar mass gaps to an outstanding precision better than 10{sup -6} %.

Regional LLRW processing alternatives applying the DOE REGINALT systems analysis model

International Nuclear Information System (INIS)

Beers, G.H.

1987-01-01

The DOE Low-Level Waste Management Program has developed a computer-based decision support system of models that may be used by nonprogrammers to evaluate a comprehensive approach to commercial low-level radioactive waste (LLRW) management. REGINALT (Regional Waste Management Alternatives Analysis Model) implementation will be described as the model is applied to hypothetical regional compact for the purpose of examining the technical and economic potential of two waste processing alternatives. Using waste from a typical regional compact, two specific regional waste processing centers are compared for feasibility. Example 1 assumes that a regional supercompaction facility is being developed for the region. Example 2 assumes that a regional facility with both supercompaction and incineration is specified. Both examples include identical disposal facilities, except that capacity may differ due to variation in volume reduction achieved. The two examples are compared with regard to volume reduction achieved, estimated occupational exposure for the processing facilities, and life cycle costs per generated unit waste. A base case also illustrates current disposal practices. The results of the comparisons evaluated, and other steps, if necessary, for additional decision support are identified

A comparison of scope for growth (SFG) and dynamic energy budget (DEB) models applied to the blue mussel ( Mytilus edulis)

Science.gov (United States)

Filgueira, Ramón; Rosland, Rune; Grant, Jon

2011-11-01

Growth of Mytilus edulis was simulated using individual based models following both Scope For Growth (SFG) and Dynamic Energy Budget (DEB) approaches. These models were parameterized using independent studies and calibrated for each dataset by adjusting the half-saturation coefficient of the food ingestion function term, XK, a common parameter in both approaches related to feeding behavior. Auto-calibration was carried out using an optimization tool, which provides an objective way of tuning the model. Both approaches yielded similar performance, suggesting that although the basis for constructing the models is different, both can successfully reproduce M. edulis growth. The good performance of both models in different environments achieved by adjusting a single parameter, XK, highlights the potential of these models for (1) producing prospective analysis of mussel growth and (2) investigating mussel feeding response in different ecosystems. Finally, we emphasize that the convergence of two different modeling approaches via calibration of XK, indicates the importance of the feeding behavior and local trophic conditions for bivalve growth performance. Consequently, further investigations should be conducted to explore the relationship of XK to environmental variables and/or to the sophistication of the functional response to food availability with the final objective of creating a general model that can be applied to different ecosystems without the need for calibration.

Applying discursive approaches to health psychology.

Science.gov (United States)

Seymour-Smith, Sarah

2015-04-01

The aim of this paper is to outline the contribution of two strands of discursive research, glossed as 'macro' and 'micro,' to the field of health psychology. A further goal is to highlight some contemporary debates in methodology associated with the use of interview data versus more naturalistic data in qualitative health research. Discursive approaches provide a way of analyzing talk as a social practice that considers how descriptions are put together and what actions they achieve. A selection of recent examples of discursive research from one applied area of health psychology, studies of diet and obesity, are drawn upon in order to illustrate the specifics of both strands. 'Macro' discourse work in psychology incorporates a Foucauldian focus on the way that discourses regulate subjectivities, whereas the concept of interpretative repertoires affords more agency to the individual: both are useful for identifying the cultural context of talk. Both 'macro' and 'micro' strands focus on accountability to varying degrees. 'Micro' Discursive Psychology, however, pays closer attention to the sequential organization of constructions and focuses on naturalistic settings that allow for the inclusion of an analysis of the health professional. Diets are typically depicted as an individual responsibility in mainstream health psychology, but discursive research highlights how discourses are collectively produced and bound up with social practices. (c) 2015 APA, all rights reserved).

An empirical Bayesian approach for model-based inference of cellular signaling networks

Directory of Open Access Journals (Sweden)

Klinke David J

2009-11-01

Full Text Available Abstract Background A common challenge in systems biology is to infer mechanistic descriptions of biological process given limited observations of a biological system. Mathematical models are frequently used to represent a belief about the causal relationships among proteins within a signaling network. Bayesian methods provide an attractive framework for inferring the validity of those beliefs in the context of the available data. However, efficient sampling of high-dimensional parameter space and appropriate convergence criteria provide barriers for implementing an empirical Bayesian approach. The objective of this study was to apply an Adaptive Markov chain Monte Carlo technique to a typical study of cellular signaling pathways. Results As an illustrative example, a kinetic model for the early signaling events associated with the epidermal growth factor (EGF signaling network was calibrated against dynamic measurements observed in primary rat hepatocytes. A convergence criterion, based upon the Gelman-Rubin potential scale reduction factor, was applied to the model predictions. The posterior distributions of the parameters exhibited complicated structure, including significant covariance between specific parameters and a broad range of variance among the parameters. The model predictions, in contrast, were narrowly distributed and were used to identify areas of agreement among a collection of experimental studies. Conclusion In summary, an empirical Bayesian approach was developed for inferring the confidence that one can place in a particular model that describes signal transduction mechanisms and for inferring inconsistencies in experimental measurements.

The threshold bias model: a mathematical model for the nomothetic approach of suicide.

Science.gov (United States)

Folly, Walter Sydney Dutra

2011-01-01

Comparative and predictive analyses of suicide data from different countries are difficult to perform due to varying approaches and the lack of comparative parameters. A simple model (the Threshold Bias Model) was tested for comparative and predictive analyses of suicide rates by age. The model comprises of a six parameter distribution that was applied to the USA suicide rates by age for the years 2001 and 2002. Posteriorly, linear extrapolations are performed of the parameter values previously obtained for these years in order to estimate the values corresponding to the year 2003. The calculated distributions agreed reasonably well with the aggregate data. The model was also used to determine the age above which suicide rates become statistically observable in USA, Brazil and Sri Lanka. The Threshold Bias Model has considerable potential applications in demographic studies of suicide. Moreover, since the model can be used to predict the evolution of suicide rates based on information extracted from past data, it will be of great interest to suicidologists and other researchers in the field of mental health.

Convex models and probabilistic approach of nonlinear fatigue failure

International Nuclear Information System (INIS)

Qiu Zhiping; Lin Qiang; Wang Xiaojun

2008-01-01

This paper is concerned with the nonlinear fatigue failure problem with uncertainties in the structural systems. In the present study, in order to solve the nonlinear problem by convex models, the theory of ellipsoidal algebra with the help of the thought of interval analysis is applied. In terms of the inclusion monotonic property of ellipsoidal functions, the nonlinear fatigue failure problem with uncertainties can be solved. A numerical example of 25-bar truss structures is given to illustrate the efficiency of the presented method in comparison with the probabilistic approach

Modeling Organizational Design - Applying A Formalism Model From Theoretical Physics

Directory of Open Access Journals (Sweden)

Robert Fabac

2008-06-01

Full Text Available Modern organizations are exposed to diverse external environment influences. Currently accepted concepts of organizational design take into account structure, its interaction with strategy, processes, people, etc. Organization design and planning aims to align this key organizational design variables. At the higher conceptual level, however, completely satisfactory formulation for this alignment doesn’t exist. We develop an approach originating from the application of concepts of theoretical physics to social systems. Under this approach, the allocation of organizational resources is analyzed in terms of social entropy, social free energy and social temperature. This allows us to formalize the dynamic relationship between organizational design variables. In this paper we relate this model to Galbraith's Star Model and we also suggest improvements in the procedure of the complex analytical method in organizational design.

Tennis: Applied Examples of a Game-Based Teaching Approach

Science.gov (United States)

Crespo, Miguel; Reid, Machar M.; Miley, Dave

2004-01-01

In this article, the authors reveal that tennis has been increasingly taught with a tactical model or game-based approach, which emphasizes learning through practice in match-like drills and actual play, rather than in practicing strokes for exact technical execution. Its goal is to facilitate the player's understanding of the tactical, physical…

Comparison of two multiaxial fatigue models applied to dental implants

Directory of Open Access Journals (Sweden)

JM. Ayllon

2015-07-01

Full Text Available This paper presents two multiaxial fatigue life prediction models applied to a commercial dental implant. One model is called Variable Initiation Length Model and takes into account both the crack initiation and propagation phases. The second model combines the Theory of Critical Distance with a critical plane damage model to characterise the initiation and initial propagation of micro/meso cracks in the material. This paper discusses which material properties are necessary for the implementation of these models and how to obtain them in the laboratory from simple test specimens. It also describes the FE models developed for the stress/strain and stress intensity factor characterisation in the implant. The results of applying both life prediction models are compared with experimental results arising from the application of ISO-14801 standard to a commercial dental implant.

Safety constraints applied to an adaptive Bayesian condition-based maintenance optimization model

International Nuclear Information System (INIS)

Flage, Roger; Coit, David W.; Luxhøj, James T.; Aven, Terje

2012-01-01

A model is described that determines an optimal inspection and maintenance scheme for a deteriorating unit with a stochastic degradation process with independent and stationary increments and for which the parameters are uncertain. This model and resulting maintenance plans offers some distinct benefits compared to prior research because the uncertainty of the degradation process is accommodated by a Bayesian approach and two new safety constraints have been applied to the problem: (1) with a given subjective probability (degree of belief), the limiting relative frequency of one or more failures during a fixed time interval is bounded; or (2) the subjective probability of one or more failures during a fixed time interval is bounded. In the model, the parameter(s) of a condition-based inspection scheduling function and a preventive replacement threshold are jointly optimized upon each replacement and inspection such as to minimize the expected long run cost per unit of time, but also considering one of the specified safety constraints. A numerical example is included to illustrate the effect of imposing each of the two different safety constraints.

Burnout of pulverized biomass particles in large scale boiler - Single particle model approach

Energy Technology Data Exchange (ETDEWEB)

Saastamoinen, Jaakko; Aho, Martti; Moilanen, Antero [VTT Technical Research Centre of Finland, Box 1603, 40101 Jyvaeskylae (Finland); Soerensen, Lasse Holst [ReaTech/ReAddit, Frederiksborgsveij 399, Niels Bohr, DK-4000 Roskilde (Denmark); Clausen, Soennik [Risoe National Laboratory, DK-4000 Roskilde (Denmark); Berg, Mogens [ENERGI E2 A/S, A.C. Meyers Vaenge 9, DK-2450 Copenhagen SV (Denmark)

2010-05-15

Burning of coal and biomass particles are studied and compared by measurements in an entrained flow reactor and by modelling. The results are applied to study the burning of pulverized biomass in a large scale utility boiler originally planned for coal. A simplified single particle approach, where the particle combustion model is coupled with one-dimensional equation of motion of the particle, is applied for the calculation of the burnout in the boiler. The particle size of biomass can be much larger than that of coal to reach complete burnout due to lower density and greater reactivity. The burner location and the trajectories of the particles might be optimised to maximise the residence time and burnout. (author)

Applying MDA to SDR for Space to Model Real-time Issues

Science.gov (United States)

Blaser, Tammy M.

2007-01-01

NASA space communications systems have the challenge of designing SDRs with highly-constrained Size, Weight and Power (SWaP) resources. A study is being conducted to assess the effectiveness of applying the MDA Platform-Independent Model (PIM) and one or more Platform-Specific Models (PSM) specifically to address NASA space domain real-time issues. This paper will summarize our experiences with applying MDA to SDR for Space to model real-time issues. Real-time issues to be examined, measured, and analyzed are: meeting waveform timing requirements and efficiently applying Real-time Operating System (RTOS) scheduling algorithms, applying safety control measures, and SWaP verification. Real-time waveform algorithms benchmarked with the worst case environment conditions under the heaviest workload will drive the SDR for Space real-time PSM design.

Takagi-Sugeno Fuzzy Model of a One-Half Semiactive Vehicle Suspension: Lateral Approach

Directory of Open Access Journals (Sweden)

L. C. Félix-Herrán

2015-01-01

Full Text Available This work presents a novel semiactive model of a one-half lateral vehicle suspension. The contribution of this research is the inclusion of actuator dynamics (two magnetorheological nonlinear dampers in the modelling, which means that more realistic outcomes will be obtained, because, in real life, actuators have physical limitations. Takagi-Sugeno (T-S fuzzy approach is applied to a four-degree-of-freedom (4-DOF lateral one-half vehicle suspension. The system has two magnetorheological (MR dampers, whose numerical values come from a real characterization. T-S allows handling suspension’s components and actuator’s nonlinearities (hysteresis, saturation, and viscoplasticity by means of a set of linear subsystems interconnected via fuzzy membership functions. Due to their linearity, each subsystem can be handled with the very well-known control theory, for example, stability and performance indexes (this is an advantage of the T-S approach. To the best of authors’ knowledge, reported work does not include the aforementioned nonlinearities in the modelling. The generated model is validated via a case of study with simulation results. This research is paramount because it introduces a more accurate (the actuator dynamics, a complex nonlinear subsystem model that could be applied to one-half vehicle suspension control purposes. Suspension systems are extremely important for passenger comfort and stability in ground vehicles.

A novel approach to multihazard modeling and simulation.

Science.gov (United States)

Smith, Silas W; Portelli, Ian; Narzisi, Giuseppe; Nelson, Lewis S; Menges, Fabian; Rekow, E Dianne; Mincer, Joshua S; Mishra, Bhubaneswar; Goldfrank, Lewis R

2009-06-01

To develop and apply a novel modeling approach to support medical and public health disaster planning and response using a sarin release scenario in a metropolitan environment. An agent-based disaster simulation model was developed incorporating the principles of dose response, surge response, and psychosocial characteristics superimposed on topographically accurate geographic information system architecture. The modeling scenarios involved passive and active releases of sarin in multiple transportation hubs in a metropolitan city. Parameters evaluated included emergency medical services, hospital surge capacity (including implementation of disaster plan), and behavioral and psychosocial characteristics of the victims. In passive sarin release scenarios of 5 to 15 L, mortality increased nonlinearly from 0.13% to 8.69%, reaching 55.4% with active dispersion, reflecting higher initial doses. Cumulative mortality rates from releases in 1 to 3 major transportation hubs similarly increased nonlinearly as a function of dose and systemic stress. The increase in mortality rate was most pronounced in the 80% to 100% emergency department occupancy range, analogous to the previously observed queuing phenomenon. Effective implementation of hospital disaster plans decreased mortality and injury severity. Decreasing ambulance response time and increasing available responding units reduced mortality among potentially salvageable patients. Adverse psychosocial characteristics (excess worry and low compliance) increased demands on health care resources. Transfer to alternative urban sites was possible. An agent-based modeling approach provides a mechanism to assess complex individual and systemwide effects in rare events.

Vector-model-supported approach in prostate plan optimization

International Nuclear Information System (INIS)

Liu, Eva Sau Fan; Wu, Vincent Wing Cheung; Harris, Benjamin; Lehman, Margot; Pryor, David; Chan, Lawrence Wing Chi

2017-01-01

Lengthy time consumed in traditional manual plan optimization can limit the use of step-and-shoot intensity-modulated radiotherapy/volumetric-modulated radiotherapy (S&S IMRT/VMAT). A vector model base, retrieving similar radiotherapy cases, was developed with respect to the structural and physiologic features extracted from the Digital Imaging and Communications in Medicine (DICOM) files. Planning parameters were retrieved from the selected similar reference case and applied to the test case to bypass the gradual adjustment of planning parameters. Therefore, the planning time spent on the traditional trial-and-error manual optimization approach in the beginning of optimization could be reduced. Each S&S IMRT/VMAT prostate reference database comprised 100 previously treated cases. Prostate cases were replanned with both traditional optimization and vector-model-supported optimization based on the oncologists' clinical dose prescriptions. A total of 360 plans, which consisted of 30 cases of S&S IMRT, 30 cases of 1-arc VMAT, and 30 cases of 2-arc VMAT plans including first optimization and final optimization with/without vector-model-supported optimization, were compared using the 2-sided t-test and paired Wilcoxon signed rank test, with a significance level of 0.05 and a false discovery rate of less than 0.05. For S&S IMRT, 1-arc VMAT, and 2-arc VMAT prostate plans, there was a significant reduction in the planning time and iteration with vector-model-supported optimization by almost 50%. When the first optimization plans were compared, 2-arc VMAT prostate plans had better plan quality than 1-arc VMAT plans. The volume receiving 35 Gy in the femoral head for 2-arc VMAT plans was reduced with the vector-model-supported optimization compared with the traditional manual optimization approach. Otherwise, the quality of plans from both approaches was comparable. Vector-model-supported optimization was shown to offer much shortened planning time and iteration

Vector-model-supported approach in prostate plan optimization

Energy Technology Data Exchange (ETDEWEB)

Liu, Eva Sau Fan [Department of Radiation Oncology, Princess Alexandra Hospital, Brisbane (Australia); Department of Health Technology and Informatics, The Hong Kong Polytechnic University (Hong Kong); Wu, Vincent Wing Cheung [Department of Health Technology and Informatics, The Hong Kong Polytechnic University (Hong Kong); Harris, Benjamin [Department of Radiation Oncology, Princess Alexandra Hospital, Brisbane (Australia); Lehman, Margot; Pryor, David [Department of Radiation Oncology, Princess Alexandra Hospital, Brisbane (Australia); School of Medicine, University of Queensland (Australia); Chan, Lawrence Wing Chi, E-mail: wing.chi.chan@polyu.edu.hk [Department of Health Technology and Informatics, The Hong Kong Polytechnic University (Hong Kong)

2017-07-01

Lengthy time consumed in traditional manual plan optimization can limit the use of step-and-shoot intensity-modulated radiotherapy/volumetric-modulated radiotherapy (S&S IMRT/VMAT). A vector model base, retrieving similar radiotherapy cases, was developed with respect to the structural and physiologic features extracted from the Digital Imaging and Communications in Medicine (DICOM) files. Planning parameters were retrieved from the selected similar reference case and applied to the test case to bypass the gradual adjustment of planning parameters. Therefore, the planning time spent on the traditional trial-and-error manual optimization approach in the beginning of optimization could be reduced. Each S&S IMRT/VMAT prostate reference database comprised 100 previously treated cases. Prostate cases were replanned with both traditional optimization and vector-model-supported optimization based on the oncologists' clinical dose prescriptions. A total of 360 plans, which consisted of 30 cases of S&S IMRT, 30 cases of 1-arc VMAT, and 30 cases of 2-arc VMAT plans including first optimization and final optimization with/without vector-model-supported optimization, were compared using the 2-sided t-test and paired Wilcoxon signed rank test, with a significance level of 0.05 and a false discovery rate of less than 0.05. For S&S IMRT, 1-arc VMAT, and 2-arc VMAT prostate plans, there was a significant reduction in the planning time and iteration with vector-model-supported optimization by almost 50%. When the first optimization plans were compared, 2-arc VMAT prostate plans had better plan quality than 1-arc VMAT plans. The volume receiving 35 Gy in the femoral head for 2-arc VMAT plans was reduced with the vector-model-supported optimization compared with the traditional manual optimization approach. Otherwise, the quality of plans from both approaches was comparable. Vector-model-supported optimization was shown to offer much shortened planning time and iteration

Risk matrix model applied to the outsourcing of logistics' activities

Directory of Open Access Journals (Sweden)

Fouad Jawab

2015-09-01

Full Text Available Purpose: This paper proposes the application of the risk matrix model in the field of logistics outsourcing. Such an application can serve as the basis for decision making regarding the conduct of a risk management in the logistics outsourcing process and allow its prevention. Design/methodology/approach: This study is based on the risk management of logistics outsourcing in the field of the retail sector in Morocco. The authors identify all possible risks and then classify and prioritize them using the Risk Matrix Model. Finally, we have come to four possible decisions for the identified risks. The analysis was made possible through interviews and discussions with the heads of departments and agents who are directly involved in each outsourced activity. Findings and Originality/value: It is possible to improve the risk matrix model by proposing more personalized prevention measures according to each company that operates in the mass-market retailing. Originality/value: This study is the only one made in the process of logistics outsourcing in the retail sector in Morocco through Label’vie as a case study. First, we had identified as thorough as we could all possible risks, then we applied the Risk Matrix Model to sort them out in an ascending order of importance and criticality. As a result, we could hand out to the decision-makers the mapping for an effective control of risks and a better guiding of the process of risk management.

Different approaches in Partial Least Squares and Artificial Neural Network models applied for the analysis of a ternary mixture of Amlodipine, Valsartan and Hydrochlorothiazide

Science.gov (United States)

Darwish, Hany W.; Hassan, Said A.; Salem, Maissa Y.; El-Zeany, Badr A.

2014-03-01

Different chemometric models were applied for the quantitative analysis of Amlodipine (AML), Valsartan (VAL) and Hydrochlorothiazide (HCT) in ternary mixture, namely, Partial Least Squares (PLS) as traditional chemometric model and Artificial Neural Networks (ANN) as advanced model. PLS and ANN were applied with and without variable selection procedure (Genetic Algorithm GA) and data compression procedure (Principal Component Analysis PCA). The chemometric methods applied are PLS-1, GA-PLS, ANN, GA-ANN and PCA-ANN. The methods were used for the quantitative analysis of the drugs in raw materials and pharmaceutical dosage form via handling the UV spectral data. A 3-factor 5-level experimental design was established resulting in 25 mixtures containing different ratios of the drugs. Fifteen mixtures were used as a calibration set and the other ten mixtures were used as validation set to validate the prediction ability of the suggested methods. The validity of the proposed methods was assessed using the standard addition technique.

First-Principles Approach to Model Electrochemical Reactions: Understanding the Fundamental Mechanisms behind Mg Corrosion

Science.gov (United States)

Surendralal, Sudarsan; Todorova, Mira; Finnis, Michael W.; Neugebauer, Jörg

2018-06-01

Combining concepts of semiconductor physics and corrosion science, we develop a novel approach that allows us to perform ab initio calculations under controlled potentiostat conditions for electrochemical systems. The proposed approach can be straightforwardly applied in standard density functional theory codes. To demonstrate the performance and the opportunities opened by this approach, we study the chemical reactions that take place during initial corrosion at the water-Mg interface under anodic polarization. Based on this insight, we derive an atomistic model that explains the origin of the anodic hydrogen evolution.

Applied Control Systems Design

CERN Document Server

Mahmoud, Magdi S

2012-01-01

Applied Control System Design examines several methods for building up systems models based on real experimental data from typical industrial processes and incorporating system identification techniques. The text takes a comparative approach to the models derived in this way judging their suitability for use in different systems and under different operational circumstances. A broad spectrum of control methods including various forms of filtering, feedback and feedforward control is applied to the models and the guidelines derived from the closed-loop responses are then composed into a concrete self-tested recipe to serve as a check-list for industrial engineers or control designers. System identification and control design are given equal weight in model derivation and testing to reflect their equality of importance in the proper design and optimization of high-performance control systems. Readers’ assimilation of the material discussed is assisted by the provision of problems and examples. Most of these e...

Model-Assisted Estimation of Tropical Forest Biomass Change: A Comparison of Approaches

Directory of Open Access Journals (Sweden)

Nikolai Knapp

2018-05-01

Full Text Available Monitoring of changes in forest biomass requires accurate transfer functions between remote sensing-derived changes in canopy height (ΔH and the actual changes in aboveground biomass (ΔAGB. Different approaches can be used to accomplish this task: direct approaches link ΔH directly to ΔAGB, while indirect approaches are based on deriving AGB stock estimates for two points in time and calculating the difference. In some studies, direct approaches led to more accurate estimations, while, in others, indirect approaches led to more accurate estimations. It is unknown how each approach performs under different conditions and over the full range of possible changes. Here, we used a forest model (FORMIND to generate a large dataset (>28,000 ha of natural and disturbed forest stands over time. Remote sensing of forest height was simulated on these stands to derive canopy height models for each time step. Three approaches for estimating ΔAGB were compared: (i the direct approach; (ii the indirect approach and (iii an enhanced direct approach (dir+tex, using ΔH in combination with canopy texture. Total prediction accuracies of the three approaches measured as root mean squared errors (RMSE were RMSEdirect = 18.7 t ha−1, RMSEindirect = 12.6 t ha−1 and RMSEdir+tex = 12.4 t ha−1. Further analyses revealed height-dependent biases in the ΔAGB estimates of the direct approach, which did not occur with the other approaches. Finally, the three approaches were applied on radar-derived (TanDEM-X canopy height changes on Barro Colorado Island (Panama. The study demonstrates the potential of forest modeling for improving the interpretation of changes observed in remote sensing data and for comparing different methodologies.

Bayesian Multi-Energy Computed Tomography reconstruction approaches based on decomposition models

International Nuclear Information System (INIS)

Cai, Caifang

2013-01-01

necessary to have the accurate spectrum information about the source-detector system. When dealing with experimental data, the spectrum can be predicted by a Monte Carlo simulator. For a variety of materials, less than 5% estimation errors are observed on their average decomposition fractions.The proposed approach is a statistical reconstruction approach based on a non-linear forward model counting the full beam poly-chromaticity and applied directly to the projections without taking negative-log. Compared to the approaches based on linear forward models and the BHA correction approaches, it has advantages in noise robustness and reconstruction accuracy. (author) [fr

A nationwide modelling approach to decommissioning - 16182

International Nuclear Information System (INIS)

Kelly, Bernard; Lowe, Andy; Mort, Paul

2009-01-01

In this paper we describe a proposed UK national approach to modelling decommissioning. For the first time, we shall have an insight into optimizing the safety and efficiency of a national decommissioning strategy. To do this we use the General Case Integrated Waste Algorithm (GIA), a universal model of decommissioning nuclear plant, power plant, waste arisings and the associated knowledge capture. The model scales from individual items of plant through cells, groups of cells, buildings, whole sites and then on up to a national scale. We describe the national vision for GIA which can be broken down into three levels: 1) the capture of the chronological order of activities that an experienced decommissioner would use to decommission any nuclear facility anywhere in the world - this is Level 1 of GIA; 2) the construction of an Operational Research (OR) model based on Level 1 to allow rapid what if scenarios to be tested quickly (Level 2); 3) the construction of a state of the art knowledge capture capability that allows future generations to learn from our current decommissioning experience (Level 3). We show the progress to date in developing GIA in levels 1 and 2. As part of level 1, GIA has assisted in the development of an IMechE professional decommissioning qualification. Furthermore, we describe GIA as the basis of a UK-Owned database of decommissioning norms for such things as costs, productivity, durations etc. From level 2, we report on a pilot study that has successfully tested the basic principles for the OR numerical simulation of the algorithm. We then highlight the advantages of applying the OR modelling approach nationally. In essence, a series of 'what if...' scenarios can be tested that will improve the safety and efficiency of decommissioning. (authors)

Distribution function approach to redshift space distortions. Part V: perturbation theory applied to dark matter halos

Energy Technology Data Exchange (ETDEWEB)

Vlah, Zvonimir; Seljak, Uroš [Institute for Theoretical Physics, University of Zürich, Zürich (Switzerland); Okumura, Teppei [Institute for the Early Universe, Ewha Womans University, Seoul, S. Korea (Korea, Republic of); Desjacques, Vincent, E-mail: zvlah@physik.uzh.ch, E-mail: seljak@physik.uzh.ch, E-mail: teppei@ewha.ac.kr, E-mail: Vincent.Desjacques@unige.ch [Département de Physique Théorique and Center for Astroparticle Physics (CAP) Université de Genéve, Genéve (Switzerland)

2013-10-01

Numerical simulations show that redshift space distortions (RSD) introduce strong scale dependence in the power spectra of halos, with ten percent deviations relative to linear theory predictions even on relatively large scales (k < 0.1h/Mpc) and even in the absence of satellites (which induce Fingers-of-God, FoG, effects). If unmodeled these effects prevent one from extracting cosmological information from RSD surveys. In this paper we use Eulerian perturbation theory (PT) and Eulerian halo biasing model and apply it to the distribution function approach to RSD, in which RSD is decomposed into several correlators of density weighted velocity moments. We model each of these correlators using PT and compare the results to simulations over a wide range of halo masses and redshifts. We find that with an introduction of a physically motivated halo biasing, and using dark matter power spectra from simulations, we can reproduce the simulation results at a percent level on scales up to k ∼ 0.15h/Mpc at z = 0, without the need to have free FoG parameters in the model.

Bottom-up modeling approach for the quantitative estimation of parameters in pathogen-host interactions.

Science.gov (United States)

Lehnert, Teresa; Timme, Sandra; Pollmächer, Johannes; Hünniger, Kerstin; Kurzai, Oliver; Figge, Marc Thilo

2015-01-01

Opportunistic fungal pathogens can cause bloodstream infection and severe sepsis upon entering the blood stream of the host. The early immune response in human blood comprises the elimination of pathogens by antimicrobial peptides and innate immune cells, such as neutrophils or monocytes. Mathematical modeling is a predictive method to examine these complex processes and to quantify the dynamics of pathogen-host interactions. Since model parameters are often not directly accessible from experiment, their estimation is required by calibrating model predictions with experimental data. Depending on the complexity of the mathematical model, parameter estimation can be associated with excessively high computational costs in terms of run time and memory. We apply a strategy for reliable parameter estimation where different modeling approaches with increasing complexity are used that build on one another. This bottom-up modeling approach is applied to an experimental human whole-blood infection assay for Candida albicans. Aiming for the quantification of the relative impact of different routes of the immune response against this human-pathogenic fungus, we start from a non-spatial state-based model (SBM), because this level of model complexity allows estimating a priori unknown transition rates between various system states by the global optimization method simulated annealing. Building on the non-spatial SBM, an agent-based model (ABM) is implemented that incorporates the migration of interacting cells in three-dimensional space. The ABM takes advantage of estimated parameters from the non-spatial SBM, leading to a decreased dimensionality of the parameter space. This space can be scanned using a local optimization approach, i.e., least-squares error estimation based on an adaptive regular grid search, to predict cell migration parameters that are not accessible in experiment. In the future, spatio-temporal simulations of whole-blood samples may enable timely

Evaluation of different approaches for modeling effects of acid rain on soils in China

International Nuclear Information System (INIS)

Larssen, T.; Schnoor, J.L.; Seip, H.M.; Dawei, Z.

2000-01-01

Acid deposition is an environmental problem of increasing concern in China. Acidic soils are common in the southern part of the country and soil acidification caused by acid deposition is expected to occur. Here we test and apply two different approaches for modeling effects of acid deposition and compare results with observed data from sites throughout southern China. The dynamic model MAGIC indicates that, during the last few decades, soil acidification rates have increased considerably due to acid deposition. This acidification will continue if sulfur deposition is not reduced, and if reduced more rapidly than base cation deposition. With the Steady State Mass Balance model (SSMB), and assuming that a molar ratio of Ca 2+ /Al 3+ <1 in soil water is harmful to vegetation, we estimate a slight probability for exceedance of the critical load for present deposition rates. Results from both modeling approaches show a strong dependence with deposition of base cations as well as sulfur. Hence, according to the models, changes in emission control of alkaline particulate matter prior to sulfur dioxide will be detrimental to the environment. Model calculations are, however, uncertain, particularly because available data on base cation deposition fluxes are scarce, and that model formulation of aluminum chemistry does not fully reproduce observations. An effort should be made to improve our present knowledge regarding deposition fluxes. Improvements to the model are suggested. Our work indicates that the critical loads presented in the regional acid deposition assessment model RAINS-Asia are too stringent. We find weaknesses in the SSMB approach, developed for northern European conditions, when applying it to Chinese conditions. We suggest an improved effort to revise the risk parameters for use in critical load estimates in China

Hybrid surrogate-model-based multi-fidelity efficient global optimization applied to helicopter blade design

Science.gov (United States)

Ariyarit, Atthaphon; Sugiura, Masahiko; Tanabe, Yasutada; Kanazaki, Masahiro

2018-06-01

A multi-fidelity optimization technique by an efficient global optimization process using a hybrid surrogate model is investigated for solving real-world design problems. The model constructs the local deviation using the kriging method and the global model using a radial basis function. The expected improvement is computed to decide additional samples that can improve the model. The approach was first investigated by solving mathematical test problems. The results were compared with optimization results from an ordinary kriging method and a co-kriging method, and the proposed method produced the best solution. The proposed method was also applied to aerodynamic design optimization of helicopter blades to obtain the maximum blade efficiency. The optimal shape obtained by the proposed method achieved performance almost equivalent to that obtained using the high-fidelity, evaluation-based single-fidelity optimization. Comparing all three methods, the proposed method required the lowest total number of high-fidelity evaluation runs to obtain a converged solution.

A multi-model ensemble approach to seabed mapping

Science.gov (United States)

Diesing, Markus; Stephens, David

2015-06-01

Seabed habitat mapping based on swath acoustic data and ground-truth samples is an emergent and active marine science discipline. Significant progress could be achieved by transferring techniques and approaches that have been successfully developed and employed in such fields as terrestrial land cover mapping. One such promising approach is the multiple classifier system, which aims at improving classification performance by combining the outputs of several classifiers. Here we present results of a multi-model ensemble applied to multibeam acoustic data covering more than 5000 km2 of seabed in the North Sea with the aim to derive accurate spatial predictions of seabed substrate. A suite of six machine learning classifiers (k-Nearest Neighbour, Support Vector Machine, Classification Tree, Random Forest, Neural Network and Naïve Bayes) was trained with ground-truth sample data classified into seabed substrate classes and their prediction accuracy was assessed with an independent set of samples. The three and five best performing models were combined to classifier ensembles. Both ensembles led to increased prediction accuracy as compared to the best performing single classifier. The improvements were however not statistically significant at the 5% level. Although the three-model ensemble did not perform significantly better than its individual component models, we noticed that the five-model ensemble did perform significantly better than three of the five component models. A classifier ensemble might therefore be an effective strategy to improve classification performance. Another advantage is the fact that the agreement in predicted substrate class between the individual models of the ensemble could be used as a measure of confidence. We propose a simple and spatially explicit measure of confidence that is based on model agreement and prediction accuracy.

Global energy modeling - A biophysical approach

Energy Technology Data Exchange (ETDEWEB)

Dale, Michael

2010-09-15

This paper contrasts the standard economic approach to energy modelling with energy models using a biophysical approach. Neither of these approaches includes changing energy-returns-on-investment (EROI) due to declining resource quality or the capital intensive nature of renewable energy sources. Both of these factors will become increasingly important in the future. An extension to the biophysical approach is outlined which encompasses a dynamic EROI function that explicitly incorporates technological learning. The model is used to explore several scenarios of long-term future energy supply especially concerning the global transition to renewable energy sources in the quest for a sustainable energy system.

System approach to modeling of industrial technologies

Science.gov (United States)

Toropov, V. S.; Toropov, E. S.

2018-03-01

The authors presented a system of methods for modeling and improving industrial technologies. The system consists of information and software. The information part is structured information about industrial technologies. The structure has its template. The template has several essential categories used to improve the technological process and eliminate weaknesses in the process chain. The base category is the physical effect that takes place when the technical process proceeds. The programming part of the system can apply various methods of creative search to the content stored in the information part of the system. These methods pay particular attention to energy transformations in the technological process. The system application will allow us to systematize the approach to improving technologies and obtaining new technical solutions.

Model Proposition for the Fiscal Policies Analysis Applied in Economic Field

Directory of Open Access Journals (Sweden)

Larisa Preda

2007-05-01

Full Text Available This paper presents a study about fiscal policy applied in economic development. Correlations between macroeconomics and fiscal indicators signify the first steep in our analysis. Next step is a new model proposal for the fiscal and budgetary choices. This model is applied on the date of the Romanian case.

A Model-Based Anomaly Detection Approach for Analyzing Streaming Aircraft Engine Measurement Data

Science.gov (United States)

Simon, Donald L.; Rinehart, Aidan Walker

2015-01-01

This paper presents a model-based anomaly detection architecture designed for analyzing streaming transient aircraft engine measurement data. The technique calculates and monitors residuals between sensed engine outputs and model predicted outputs for anomaly detection purposes. Pivotal to the performance of this technique is the ability to construct a model that accurately reflects the nominal operating performance of the engine. The dynamic model applied in the architecture is a piecewise linear design comprising steady-state trim points and dynamic state space matrices. A simple curve-fitting technique for updating the model trim point information based on steadystate information extracted from available nominal engine measurement data is presented. Results from the application of the model-based approach for processing actual engine test data are shown. These include both nominal fault-free test case data and seeded fault test case data. The results indicate that the updates applied to improve the model trim point information also improve anomaly detection performance. Recommendations for follow-on enhancements to the technique are also presented and discussed.

Modeling of delays in PKPD: classical approaches and a tutorial for delay differential equations.

Science.gov (United States)

Koch, Gilbert; Krzyzanski, Wojciech; Pérez-Ruixo, Juan Jose; Schropp, Johannes

2014-08-01

In pharmacokinetics/pharmacodynamics (PKPD) the measured response is often delayed relative to drug administration, individuals in a population have a certain lifespan until they maturate or the change of biomarkers does not immediately affects the primary endpoint. The classical approach in PKPD is to apply transit compartment models (TCM) based on ordinary differential equations to handle such delays. However, an alternative approach to deal with delays are delay differential equations (DDE). DDEs feature additional flexibility and properties, realize more complex dynamics and can complementary be used together with TCMs. We introduce several delay based PKPD models and investigate mathematical properties of general DDE based models, which serve as subunits in order to build larger PKPD models. Finally, we review current PKPD software with respect to the implementation of DDEs for PKPD analysis.

Models and Approaches for Integrating Protected Areas with Their Surroundings: A Review of the Literature

Directory of Open Access Journals (Sweden)

Wenwu Du

2015-06-01

Full Text Available Several studies have identified threats that originate in areas surrounding protected areas (PAs. While there have been various efforts to integrate PAs with their surroundings, considerable challenges remain. Here we summarize these efforts to date, discuss their effectiveness, and provide recommendations for future research. Based on a broad literature review of theoretical and applied approaches, we have outlined 68 models for balancing conservation and sustainable development in PAs. We comprehensively analyzed 23 of these models for integrating PAs with their surroundings. They were divided into two categories: area-oriented and process-oriented approaches. This review reveals the absolute necessity of combining these two approaches for future conservation and sustainable development of PAs.

A Regional Guidebook for Applying The Approach to Assessing Wetland Functions of Depressed Wetlands in Peninsular, Florida

National Research Council Canada - National Science Library

Noble, Chris

2004-01-01

The Hydrogeomophic (HGM) Approach is a method for developing functional indices and the protocols used to apply these indices to the assessment of wetland functions at a site-specific scale The HGM Approach was initially...

The Limitations of Applying Rational Decision-Making Models

African Journals Online (AJOL)

decision-making models as applied to child spacing and more. specificaDy to the use .... also assumes that the individual operates as a rational decision- making organism in ..... work involves: Motivation; Counselling; Distribution ofIEC mate-.

Linear mixing model applied to coarse resolution satellite data

Science.gov (United States)

Holben, Brent N.; Shimabukuro, Yosio E.

1992-01-01

A linear mixing model typically applied to high resolution data such as Airborne Visible/Infrared Imaging Spectrometer, Thematic Mapper, and Multispectral Scanner System is applied to the NOAA Advanced Very High Resolution Radiometer coarse resolution satellite data. The reflective portion extracted from the middle IR channel 3 (3.55 - 3.93 microns) is used with channels 1 (0.58 - 0.68 microns) and 2 (0.725 - 1.1 microns) to run the Constrained Least Squares model to generate fraction images for an area in the west central region of Brazil. The derived fraction images are compared with an unsupervised classification and the fraction images derived from Landsat TM data acquired in the same day. In addition, the relationship betweeen these fraction images and the well known NDVI images are presented. The results show the great potential of the unmixing techniques for applying to coarse resolution data for global studies.

Comparative review of three cost-effectiveness models for rotavirus vaccines in national immunization programs; a generic approach applied to various regions in the world

Directory of Open Access Journals (Sweden)

Tu Hong-Anh

2011-07-01

Full Text Available Abstract Background This study aims to critically review available cost-effectiveness models for rotavirus vaccination, compare their designs using a standardized approach and compare similarities and differences in cost-effectiveness outcomes using a uniform set of input parameters. Methods We identified various models used to estimate the cost-effectiveness of rotavirus vaccination. From these, results using a standardized dataset for four regions in the world could be obtained for three specific applications. Results Despite differences in the approaches and individual constituting elements including costs, QALYs Quality Adjusted Life Years and deaths, cost-effectiveness results of the models were quite similar. Differences between the models on the individual components of cost-effectiveness could be related to some specific features of the respective models. Sensitivity analysis revealed that cost-effectiveness of rotavirus vaccination is highly sensitive to vaccine prices, rotavirus-associated mortality and discount rates, in particular that for QALYs. Conclusions The comparative approach followed here is helpful in understanding the various models selected and will thus benefit (low-income countries in designing their own cost-effectiveness analyses using new or adapted existing models. Potential users of the models in low and middle income countries need to consider results from existing studies and reviews. There will be a need for contextualization including the use of country specific data inputs. However, given that the underlying biological and epidemiological mechanisms do not change between countries, users are likely to be able to adapt existing model designs rather than developing completely new approaches. Also, the communication established between the individual researchers involved in the three models is helpful in the further development of these individual models. Therefore, we recommend that this kind of comparative study

Applying the Business Process and Practice Alignment Meta-model: Daily Practices and Process Modelling

Directory of Open Access Journals (Sweden)

Ventura Martins Paula

2017-03-01

Full Text Available Background: Business Process Modelling (BPM is one of the most important phases of information system design. Business Process (BP meta-models allow capturing informational and behavioural aspects of business processes. Unfortunately, standard BP meta-modelling approaches focus just on process description, providing different BP models. It is not possible to compare and identify related daily practices in order to improve BP models. This lack of information implies that further research in BP meta-models is needed to reflect the evolution/change in BP. Considering this limitation, this paper introduces a new BP meta-model designed by Business Process and Practice Alignment Meta-model (BPPAMeta-model. Our intention is to present a meta-model that addresses features related to the alignment between daily work practices and BP descriptions. Objectives: This paper intends to present a metamodel which is going to integrate daily work information into coherent and sound process definitions. Methods/Approach: The methodology employed in the research follows a design-science approach. Results: The results of the case study are related to the application of the proposed meta-model to align the specification of a BP model with work practices models. Conclusions: This meta-model can be used within the BPPAM methodology to specify or improve business processes models based on work practice descriptions.

Unitary-model-operator approach to Λ17O and lambda-nucleon effective interaction

International Nuclear Information System (INIS)

Fujii, Shinichiro; Okamoto, Ryoji; Suzuki, Kenji

1998-01-01

The unitary-model-operator approach (UMOA) is applied to Λ 17 O. A lambda-nucleon effective interaction is derived, taking the coupling of the sigma-nucleon channel into account. The lambda single-particle energies are calculated for the Os 1/2 , Op 3/2 and Op 1/2 states employing the Nijmegen soft-core potential. (author)

Comparisons of Multilevel Modeling and Structural Equation Modeling Approaches to Actor-Partner Interdependence Model.

Science.gov (United States)

Hong, Sehee; Kim, Soyoung

2018-01-01

There are basically two modeling approaches applicable to analyzing an actor-partner interdependence model: the multilevel modeling (hierarchical linear model) and the structural equation modeling. This article explains how to use these two models in analyzing an actor-partner interdependence model and how these two approaches work differently. As an empirical example, marital conflict data were used to analyze an actor-partner interdependence model. The multilevel modeling and the structural equation modeling produced virtually identical estimates for a basic model. However, the structural equation modeling approach allowed more realistic assumptions on measurement errors and factor loadings, rendering better model fit indices.

A Single-column Model Ensemble Approach Applied to the TWP-ICE Experiment

Science.gov (United States)

Davies, L.; Jakob, C.; Cheung, K.; DelGenio, A.; Hill, A.; Hume, T.; Keane, R. J.; Komori, T.; Larson, V. E.; Lin, Y.;

A self-organizing state-space-model approach for parameter estimation in hodgkin-huxley-type models of single neurons.

Directory of Open Access Journals (Sweden)

Dimitrios V Vavoulis

Full Text Available Traditional approaches to the problem of parameter estimation in biophysical models of neurons and neural networks usually adopt a global search algorithm (for example, an evolutionary algorithm, often in combination with a local search method (such as gradient descent in order to minimize the value of a cost function, which measures the discrepancy between various features of the available experimental data and model output. In this study, we approach the problem of parameter estimation in conductance-based models of single neurons from a different perspective. By adopting a hidden-dynamical-systems formalism, we expressed parameter estimation as an inference problem in these systems, which can then be tackled using a range of well-established statistical inference methods. The particular method we used was Kitagawa's self-organizing state-space model, which was applied on a number of Hodgkin-Huxley-type models using simulated or actual electrophysiological data. We showed that the algorithm can be used to estimate a large number of parameters, including maximal conductances, reversal potentials, kinetics of ionic currents, measurement and intrinsic noise, based on low-dimensional experimental data and sufficiently informative priors in the form of pre-defined constraints imposed on model parameters. The algorithm remained operational even when very noisy experimental data were used. Importantly, by combining the self-organizing state-space model with an adaptive sampling algorithm akin to the Covariance Matrix Adaptation Evolution Strategy, we achieved a significant reduction in the variance of parameter estimates. The algorithm did not require the explicit formulation of a cost function and it was straightforward to apply on compartmental models and multiple data sets. Overall, the proposed methodology is particularly suitable for resolving high-dimensional inference problems based on noisy electrophysiological data and, therefore, a

Unified Modeling of Discrete Event and Control Systems Applied in Manufacturing

Directory of Open Access Journals (Sweden)

Amanda Arêas de Souza

2015-05-01

Full Text Available For the development of both a simulation modeland a control system, it is necessary to build, inadvance, a conceptual model. This is what isusually suggested by the methodologies applied inprojects of this nature. Some conceptual modelingtechniques allow for a better understanding ofthe simulation model, and a clear descriptionof the logic of control systems. Therefore, thispaper aims to present and evaluate conceptuallanguages for unified modeling of models ofdiscrete event simulation and control systemsapplied in manufacturing. The results show thatthe IDEF-SIM language can be applied both insimulation systems and in process control.

Applying the archetype approach to the database of a biobank information management system.

Science.gov (United States)

Späth, Melanie Bettina; Grimson, Jane

2011-03-01

The purpose of this study is to investigate the feasibility of applying the openEHR archetype approach to modelling the data in the database of an existing proprietary biobank information management system. A biobank information management system stores the clinical/phenotypic data of the sample donor and sample related information. The clinical/phenotypic data is potentially sourced from the donor's electronic health record (EHR). The study evaluates the reuse of openEHR archetypes that have been developed for the creation of an interoperable EHR in the context of biobanking, and proposes a new set of archetypes specifically for biobanks. The ultimate goal of the research is the development of an interoperable electronic biomedical research record (eBMRR) to support biomedical knowledge discovery. The database of the prostate cancer biobank of the Irish Prostate Cancer Research Consortium (PCRC), which supports the identification of novel biomarkers for prostate cancer, was taken as the basis for the modelling effort. First the database schema of the biobank was analyzed and reorganized into archetype-friendly concepts. Then, archetype repositories were searched for matching archetypes. Some existing archetypes were reused without change, some were modified or specialized, and new archetypes were developed where needed. The fields of the biobank database schema were then mapped to the elements in the archetypes. Finally, the archetypes were arranged into templates specifically to meet the requirements of the PCRC biobank. A set of 47 archetypes was found to cover all the concepts used in the biobank. Of these, 29 (62%) were reused without change, 6 were modified and/or extended, 1 was specialized, and 11 were newly defined. These archetypes were arranged into 8 templates specifically required for this biobank. A number of issues were encountered in this research. Some arose from the immaturity of the archetype approach, such as immature modelling support tools

A combined disease management and process modeling approach for assessing and improving care processes: a fall management case-study.

Science.gov (United States)

Askari, Marjan; Westerhof, Richard; Eslami, Saied; Medlock, Stephanie; de Rooij, Sophia E; Abu-Hanna, Ameen

2013-10-01

To propose a combined disease management and process modeling approach for evaluating and improving care processes, and demonstrate its usability and usefulness in a real-world fall management case study. We identified essential disease management related concepts and mapped them into explicit questions meant to expose areas for improvement in the respective care processes. We applied the disease management oriented questions to a process model of a comprehensive real world fall prevention and treatment program covering primary and secondary care. We relied on interviews and observations to complete the process models, which were captured in UML activity diagrams. A preliminary evaluation of the usability of our approach by gauging the experience of the modeler and an external validator was conducted, and the usefulness of the method was evaluated by gathering feedback from stakeholders at an invitational conference of 75 attendees. The process model of the fall management program was organized around the clinical tasks of case finding, risk profiling, decision making, coordination and interventions. Applying the disease management questions to the process models exposed weaknesses in the process including: absence of program ownership, under-detection of falls in primary care, and lack of efficient communication among stakeholders due to missing awareness about other stakeholders' workflow. The modelers experienced the approach as usable and the attendees of the invitational conference found the analysis results to be valid. The proposed disease management view of process modeling was usable and useful for systematically identifying areas of improvement in a fall management program. Although specifically applied to fall management, we believe our case study is characteristic of various disease management settings, suggesting the wider applicability of the approach. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

Regression models for categorical, count, and related variables an applied approach

CERN Document Server

Hoffmann, John P

2016-01-01

Social science and behavioral science students and researchers are often confronted with data that are categorical, count a phenomenon, or have been collected over time. Sociologists examining the likelihood of interracial marriage, political scientists studying voting behavior, criminologists counting the number of offenses people commit, health scientists studying the number of suicides across neighborhoods, and psychologists modeling mental health treatment success are all interested in outcomes that are not continuous. Instead, they must measure and analyze these events and phenomena in a discrete manner.   This book provides an introduction and overview of several statistical models designed for these types of outcomes--all presented with the assumption that the reader has only a good working knowledge of elementary algebra and has taken introductory statistics and linear regression analysis.   Numerous examples from the social sciences demonstrate the practical applications of these models. The chapte...

Practical Findings from Applying the PSD Model for Evaluating Software Design Specifications

Science.gov (United States)

Räisänen, Teppo; Lehto, Tuomas; Oinas-Kukkonen, Harri

This paper presents practical findings from applying the PSD model to evaluating the support for persuasive features in software design specifications for a mobile Internet device. On the one hand, our experiences suggest that the PSD model fits relatively well for evaluating design specifications. On the other hand, the model would benefit from more specific heuristics for evaluating each technique to avoid unnecessary subjectivity. Better distinction between the design principles in the social support category would also make the model easier to use. Practitioners who have no theoretical background can apply the PSD model to increase the persuasiveness of the systems they design. The greatest benefit of the PSD model for researchers designing new systems may be achieved when it is applied together with a sound theory, such as the Elaboration Likelihood Model. Using the ELM together with the PSD model, one may increase the chances for attitude change.

Optimal design of supply chain network under uncertainty environment using hybrid analytical and simulation modeling approach

Science.gov (United States)

Chiadamrong, N.; Piyathanavong, V.

2017-12-01

Models that aim to optimize the design of supply chain networks have gained more interest in the supply chain literature. Mixed-integer linear programming and discrete-event simulation are widely used for such an optimization problem. We present a hybrid approach to support decisions for supply chain network design using a combination of analytical and discrete-event simulation models. The proposed approach is based on iterative procedures until the difference between subsequent solutions satisfies the pre-determined termination criteria. The effectiveness of proposed approach is illustrated by an example, which shows closer to optimal results with much faster solving time than the results obtained from the conventional simulation-based optimization model. The efficacy of this proposed hybrid approach is promising and can be applied as a powerful tool in designing a real supply chain network. It also provides the possibility to model and solve more realistic problems, which incorporate dynamism and uncertainty.

Generalised additive modelling approach to the fermentation process of glutamate.

Science.gov (United States)

Liu, Chun-Bo; Li, Yun; Pan, Feng; Shi, Zhong-Ping

2011-03-01

In this work, generalised additive models (GAMs) were used for the first time to model the fermentation of glutamate (Glu). It was found that three fermentation parameters fermentation time (T), dissolved oxygen (DO) and oxygen uptake rate (OUR) could capture 97% variance of the production of Glu during the fermentation process through a GAM model calibrated using online data from 15 fermentation experiments. This model was applied to investigate the individual and combined effects of T, DO and OUR on the production of Glu. The conditions to optimize the fermentation process were proposed based on the simulation study from this model. Results suggested that the production of Glu can reach a high level by controlling concentration levels of DO and OUR to the proposed optimization conditions during the fermentation process. The GAM approach therefore provides an alternative way to model and optimize the fermentation process of Glu. Crown Copyright © 2010. Published by Elsevier Ltd. All rights reserved.

A new epidemic modeling approach: Multi-regions discrete-time model with travel-blocking vicinity optimal control strategy.

Science.gov (United States)

Zakary, Omar; Rachik, Mostafa; Elmouki, Ilias

2017-08-01

First, we devise in this paper, a multi-regions discrete-time model which describes the spatial-temporal spread of an epidemic which starts from one region and enters to regions which are connected with their neighbors by any kind of anthropological movement. We suppose homogeneous Susceptible-Infected-Removed (SIR) populations, and we consider in our simulations, a grid of colored cells, which represents the whole domain affected by the epidemic while each cell can represent a sub-domain or region. Second, in order to minimize the number of infected individuals in one region, we propose an optimal control approach based on a travel-blocking vicinity strategy which aims to control only one cell by restricting movements of infected people coming from all neighboring cells. Thus, we show the influence of the optimal control approach on the controlled cell. We should also note that the cellular modeling approach we propose here, can also describes infection dynamics of regions which are not necessarily attached one to an other, even if no empty space can be viewed between cells. The theoretical method we follow for the characterization of the travel-locking optimal controls, is based on a discrete version of Pontryagin's maximum principle while the numerical approach applied to the multi-points boundary value problems we obtain here, is based on discrete progressive-regressive iterative schemes. We illustrate our modeling and control approaches by giving an example of 100 regions.

Applied research in uncertainty modeling and analysis

CERN Document Server

Ayyub, Bilal

2005-01-01

Uncertainty has been a concern to engineers, managers, and scientists for many years. For a long time uncertainty has been considered synonymous with random, stochastic, statistic, or probabilistic. Since the early sixties views on uncertainty have become more heterogeneous. In the past forty years numerous tools that model uncertainty, above and beyond statistics, have been proposed by several engineers and scientists. The tool/method to model uncertainty in a specific context should really be chosen by considering the features of the phenomenon under consideration, not independent of what is known about the system and what causes uncertainty. In this fascinating overview of the field, the authors provide broad coverage of uncertainty analysis/modeling and its application. Applied Research in Uncertainty Modeling and Analysis presents the perspectives of various researchers and practitioners on uncertainty analysis and modeling outside their own fields and domain expertise. Rather than focusing explicitly on...

A coordination chemistry approach for modeling trace element adsorption

International Nuclear Information System (INIS)

Bourg, A.C.M.

1986-01-01

The traditional distribution coefficient, Kd, is highly dependent on the water chemistry and the surface properties of the geological system being studied and is therefore quite inappropriate for use in predictive models. Adsorption, one of the many processes included in Kd values, is described here using a coordination chemistry approach. The concept of adsorption of cationic trace elements by solid hydrous oxides can be applied to natural solids. The adsorption process is thus understood in terms of a classical complexation leading to the formation of surface (heterogeneous) ligands. Applications of this concept to some freshwater, estuarine and marine environments are discussed. (author)

A Modelling Approach for Integrated Planning of Port Capacity- Trade-Offs in Rotterdam Investment Planning

Directory of Open Access Journals (Sweden)

Sander Dekker

2006-03-01

Full Text Available This paper presents a modelling approach for planning ofport capacity. The approach integrates port commercial andpublic interests. It further incorporates route competition andautonomous demand growth. It is applied to port expansion,which can be considered as a strategy for an individual port todeal with route competition. The basis for solving this planningproblem comprises an analysis of port demand and supply in apartial equilibrium model. With such an approach, the reactionof a single port on the change in a transport network comprisingalternative routes to a hinterland destination can be simulated.To establish the optimal expansion strategy, port expansion iscombined with congestion pricing. This is used for the simultaneousdetermination of 1 optimal expansion size, and 2 investmentrecovery period. The modelling approach will be appliedto Rotterdam port focusing on port expansion by means ofland reclamation. The scenmio of the entry of a new competingroute via the Italian port Gioia Tauro is used to address sometrade-offs in Rotterdam investment planning.

MODELLING AND SIMULATING RISKS IN THE TRAINING OF THE HUMAN RESOURCES BY APPLYING THE CHAOS THEORY

OpenAIRE

Eugen ROTARESCU

2012-01-01

The article approaches the modelling and simulation of risks in the training of the human resources, as well as the forecast of the degree of human resources training impacted by risks by applying the mathematical tools offered by the Chaos Theory and mathematical statistics. We will highlight that the level of knowledge, skills and abilities of the human resources from an organization are autocorrelated in time and they depend on the level of a previous moment of the training, as well as on ...

Applying innovative approach “Nature of Science (NoS) within inquiry” for developing scientific literacy in the student worksheet

Science.gov (United States)

Widowati, A.; Anjarsari, P.; Zuhdan, K. P.; Dita, A.

2018-03-01

The challenges of the 21st century require innovative solutions. Education must able to make an understanding of science learning that leads to the formation of scientific literacy learners. This research was conducted to produce the prototype as science worksheet based on Nature of Science (NoS) within inquiry approach and to know the effectiveness its product for developing scientific literacy. This research was the development and research design, by pointing to Four D models and Borg & Gall Model. There were 4 main phases (define, design, develop, disseminate) and additional phases (preliminary field testing, main product revision, main field testing, and operational product revision). Research subjects were students of the junior high school in Yogyakarta. The instruments used included questionnaire sheet product validation and scientific literacy test. For the validation data were analyzed descriptively. The test result was analyzed by an N-gain score. The results showed that the appropriateness of worksheet applying NoS within inquiry-based learning approach is eligible based on the assessment from excellent by experts and teachers, students’ scientific literacy can improve high category of the N-gain score at 0.71 by using student worksheet with Nature of Science (NoS) within inquiry approach.

Fatigue damage approach applied to Li-ion batteries ageing characterization

Energy Technology Data Exchange (ETDEWEB)

Dudézert, C. [Renault, Technocentre, Guyancourt (France); Université Paris Sud/Université Paris-Saclay, ICMMO (UMR CNRS 8182), Orsay (France); CEA/LITEN, Grenoble (France); Reynier, Y. [CEA/LITEN, Grenoble (France); Duffault, J.-M. [Université Paris Sud/Université Paris-Saclay, ICMMO (UMR CNRS 8182), Orsay (France); Franger, S., E-mail: sylvain.franger@u-psud.fr [Université Paris Sud/Université Paris-Saclay, ICMMO (UMR CNRS 8182), Orsay (France)

2016-11-15

Reliability of energy storage devices is one of the foremost concerns in electric vehicles (EVs) development. Battery ageing, i.e. the degradation of battery energy and power, depends mainly on time, on the environmental conditions and on the in-use solicitations endured by the storage system. In case of EV, the heavy dependence of the battery use with the car performance, the driving cycles, and the weather conditions make the battery life prediction an intricate issue. Mechanical physicists have developed a quick and exhaustive methodology to diagnose reliability of complex structures enduring complex loads. This “fatigue” approach expresses the performance fading due to a complex load through the evolution corresponding to basic ones. Thus, a state of health variable named “damage” binds the load history and ageing. The battery ageing study described here consists in applying this mechanical approach to electrochemical systems by connecting the ageing factors with the battery characteristics evolutions. In that way, a specific “fatigue” test protocol has been established. This experimental confrontation has led to distinguishing calendar from cycling ageing mechanisms.

Fatigue damage approach applied to Li-ion batteries ageing characterization

International Nuclear Information System (INIS)

Dudézert, C.; Reynier, Y.; Duffault, J.-M.; Franger, S.

2016-01-01

Reliability of energy storage devices is one of the foremost concerns in electric vehicles (EVs) development. Battery ageing, i.e. the degradation of battery energy and power, depends mainly on time, on the environmental conditions and on the in-use solicitations endured by the storage system. In case of EV, the heavy dependence of the battery use with the car performance, the driving cycles, and the weather conditions make the battery life prediction an intricate issue. Mechanical physicists have developed a quick and exhaustive methodology to diagnose reliability of complex structures enduring complex loads. This “fatigue” approach expresses the performance fading due to a complex load through the evolution corresponding to basic ones. Thus, a state of health variable named “damage” binds the load history and ageing. The battery ageing study described here consists in applying this mechanical approach to electrochemical systems by connecting the ageing factors with the battery characteristics evolutions. In that way, a specific “fatigue” test protocol has been established. This experimental confrontation has led to distinguishing calendar from cycling ageing mechanisms.

Nested 1D-2D approach for urban surface flood modeling

Science.gov (United States)

Murla, Damian; Willems, Patrick

2015-04-01

Floods in urban areas as a consequence of sewer capacity exceedance receive increased attention because of trends in urbanization (increased population density and impermeability of the surface) and climate change. Despite the strong recent developments in numerical modeling of water systems, urban surface flood modeling is still a major challenge. Whereas very advanced and accurate flood modeling systems are in place and operation by many river authorities in support of flood management along rivers, this is not yet the case in urban water management. Reasons include the small scale of the urban inundation processes, the need to have very high resolution topographical information available, and the huge computational demands. Urban drainage related inundation modeling requires a 1D full hydrodynamic model of the sewer network to be coupled with a 2D surface flood model. To reduce the computational times, 0D (flood cones), 1D/quasi-2D surface flood modeling approaches have been developed and applied in some case studies. In this research, a nested 1D/2D hydraulic model has been developed for an urban catchment at the city of Gent (Belgium), linking the underground sewer (minor system) with the overland surface (major system). For the overland surface flood modelling, comparison was made of 0D, 1D/quasi-2D and full 2D approaches. The approaches are advanced by considering nested 1D-2D approaches, including infiltration in the green city areas, and allowing the effects of surface storm water storage to be simulated. An optimal nested combination of three different mesh resolutions was identified; based on a compromise between precision and simulation time for further real-time flood forecasting, warning and control applications. Main streets as mesh zones together with buildings as void regions constitute one of these mesh resolution (3.75m2 - 15m2); they have been included since they channel most of the flood water from the manholes and they improve the accuracy of

Differential Evolution algorithm applied to FSW model calibration

Science.gov (United States)

Idagawa, H. S.; Santos, T. F. A.; Ramirez, A. J.

2014-03-01

Friction Stir Welding (FSW) is a solid state welding process that can be modelled using a Computational Fluid Dynamics (CFD) approach. These models use adjustable parameters to control the heat transfer and the heat input to the weld. These parameters are used to calibrate the model and they are generally determined using the conventional trial and error approach. Since this method is not very efficient, we used the Differential Evolution (DE) algorithm to successfully determine these parameters. In order to improve the success rate and to reduce the computational cost of the method, this work studied different characteristics of the DE algorithm, such as the evolution strategy, the objective function, the mutation scaling factor and the crossover rate. The DE algorithm was tested using a friction stir weld performed on a UNS S32205 Duplex Stainless Steel.

Development of hydrogeological modelling approaches for assessment of consequences of hazardous accidents at nuclear power plants

International Nuclear Information System (INIS)

Rumynin, V.G.; Mironenko, V.A.; Konosavsky, P.K.; Pereverzeva, S.A.

1994-07-01

This paper introduces some modeling approaches for predicting the influence of hazardous accidents at nuclear reactors on groundwater quality. Possible pathways for radioactive releases from nuclear power plants were considered to conceptualize boundary conditions for solving the subsurface radionuclides transport problems. Some approaches to incorporate physical-and-chemical interactions into transport simulators have been developed. The hydrogeological forecasts were based on numerical and semi-analytical scale-dependent models. They have been applied to assess the possible impact of the nuclear power plants designed in Russia on groundwater reservoirs

On the choice of electromagnetic model for short high-intensity arcs, applied to welding

International Nuclear Information System (INIS)

Choquet, Isabelle; Shirvan, Alireza Javidi; Nilsson, Håkan

2012-01-01

We have considered four different approaches for modelling the electromagnetic fields of high-intensity electric arcs: (i) three-dimensional, (ii) two-dimensional axi-symmetric, (iii) the electric potential formulation and (iv) the magnetic field formulation. The underlying assumptions and the differences between these models are described in detail. Models (i) to (iii) reduce to the same limit for an axi-symmetric configuration with negligible radial current density, contrary to model (iv). Models (i) to (iii) were retained and implemented in the open source CFD software OpenFOAM. The simulation results were first validated against the analytic solution of an infinite electric rod. Perfect agreement was obtained for all the models tested. The electromagnetic models (i) to (iii) were then coupled with thermal fluid mechanics, and applied to axi-symmetric gas tungsten arc welding test cases with short arc (2, 3 and 5 mm) and truncated conical electrode tip. Models (i) and (ii) lead to the same simulation results, but not model (iii). Model (iii) is suited in the specific limit of long axi-symmetric arc with negligible electrode tip effect, i.e. negligible radial current density. For short axi-symmetric arc with significant electrode tip effect, the more general axi-symmetric formulation of model (ii) should instead be used. (paper)

Nonlinear model updating applied to the IMAC XXXII Round Robin benchmark system

Science.gov (United States)

Kurt, Mehmet; Moore, Keegan J.; Eriten, Melih; McFarland, D. Michael; Bergman, Lawrence A.; Vakakis, Alexander F.

2017-05-01

We consider the application of a new nonlinear model updating strategy to a computational benchmark system. The approach relies on analyzing system response time series in the frequency-energy domain by constructing both Hamiltonian and forced and damped frequency-energy plots (FEPs). The system parameters are then characterized and updated by matching the backbone branches of the FEPs with the frequency-energy wavelet transforms of experimental and/or computational time series. The main advantage of this method is that no nonlinearity model is assumed a priori, and the system model is updated solely based on simulation and/or experimental measured time series. By matching the frequency-energy plots of the benchmark system and its reduced-order model, we show that we are able to retrieve the global strongly nonlinear dynamics in the frequency and energy ranges of interest, identify bifurcations, characterize local nonlinearities, and accurately reconstruct time series. We apply the proposed methodology to a benchmark problem, which was posed to the system identification community prior to the IMAC XXXII (2014) and XXXIII (2015) Conferences as a "Round Robin Exercise on Nonlinear System Identification". We show that we are able to identify the parameters of the non-linear element in the problem with a priori knowledge about its position.

Modeling of hydrothermal circulation applied to active volcanic areas. The case of Vulcano (Italy)

Energy Technology Data Exchange (ETDEWEB)

Todesco, M. [Dip. Scienze della Terra, Posa (Italy)

1995-03-01

Modeling of fluid and heat flows through porous media has been diffusely applied up to date to the study of geothermal reservoirs. Much less has been done to apply the same methodology to the study of active volcanoes and of the associated volcanic hazard. Hydrothermal systems provide direct information on dormant eruptive centers and significant insights on their state of activity and current evolution. For this reason, the evaluation of volcanic hazard is also based on monitoring of hydrothermal activity. Such monitoring, however, provides measurements of surface parameters, such as fluid temperature or composition, that often are only representative of the shallower portion of the system. The interpretation of these data in terms of global functioning of the hydrothermal circulation can therefore be highly misleading. Numerical modeling of hydrothermal activity provides a physical approach to the description of fluid circulation and can contribute to its understanding and to the interpretation of monitoring data. In this work, the TOUGH2 simulator has been applied to study the hydrothermal activity at Vulcano (Italy). Simulations involved an axisymmetric domain heated from below, and focused on the effects of permeability distribution and carbon dioxide. Results are consistent with the present knowledge of the volcanic system and suggest that permeability distribution plays a major role in the evolution of fluid circulation. This parameter should be considered in the interpretation of monitoring data and in the evaluation of volcanic hazard at Vulcano.

Geological modeling by an indicator kriging approach applied to a limestone deposit in Indiara city - Goiás

Directory of Open Access Journals (Sweden)

Paulo Elias Carneiro Pereira

Full Text Available Abstract The mineral exploration activity consists of a set of successive stages that are interdependent on each other, in which the main goal is to discover and subsequently evaluate a mineral deposit for the feasibility of its extraction. This process involves setting the shape, dimensions and grades for eventual production. Geological modeling determines the orebody's possible format in subsoil, which can be done by two approaches: vertical sections (deterministic methods or geostatistical methods. The latter approach is currently being preferred, as it is a more accurate alternative and therefore, more reliable for establishing the physical format of orebodies, especially in instances where geologic boundaries are soft and/or with widely spaced sample information. This study uses the concept of indicator kriging (IK to model the geologic boundaries of a limestone deposit located at Indiara city, Goiás State, Brazil. In general, the results indicated a good adherence in relation to samples. However, there are reasonable differences, particularly in lithological domains with a small number of samples in relation to the total amount sampled. Therefore, the results showed that there is a need for additional sampling to better delineate the geological contacts, especially between carbonate and non-carbonate rocks. Uncertainty maps confirmed this necessity and also indicated potential sites for future sampling; information that would not be obtained by usage of deterministic methods.

Teaching and Learning Ecological Modeling over the Web: a Collaborative Approach

Directory of Open Access Journals (Sweden)

Alexey Voinov

2002-06-01

Full Text Available A framework for web-based collaborative teaching has been created. This framework is implemented as an ecological modeling course (http://iee.umces.edu/AV/Simmod.html, but should be flexible enough to apply to other disciplines. I have developed a series of tools to facilitate interactive communication between students and instructors, and among students taking the course. The course content consists of reading materials that describe the theory of systems analysis and modeling, guidelines on how models can be built, and numerous examples and illustrations. The interactive part includes exercises that can be discussed with and evaluated by the instructor, and provides a means to mimic class discussions. To what extent this approach can replace conventional in-class tutoring has yet to be tested, but the preliminary applications show great promise. I offer this course format as a framework and a prototype for collaborative "open-source" approaches to education, in which the web provides the means to communicate knowledge and skills asynchronously between geographically dispersed educators and students.

Comparison of two model approaches in the Zambezi river basin with regard to model reliability and identifiability

Directory of Open Access Journals (Sweden)

H. C. Winsemius

2006-01-01

Full Text Available Variations of water stocks in the upper Zambezi river basin have been determined by 2 different hydrological modelling approaches. The purpose was to provide preliminary terrestrial storage estimates in the upper Zambezi, which will be compared with estimates derived from the Gravity Recovery And Climate Experiment (GRACE in a future study. The first modelling approach is GIS-based, distributed and conceptual (STREAM. The second approach uses Lumped Elementary Watersheds identified and modelled conceptually (LEW. The STREAM model structure has been assessed using GLUE (Generalized Likelihood Uncertainty Estimation a posteriori to determine parameter identifiability. The LEW approach could, in addition, be tested for model structure, because computational efforts of LEW are low. Both models are threshold models, where the non-linear behaviour of the Zambezi river basin is explained by a combination of thresholds and linear reservoirs. The models were forced by time series of gauged and interpolated rainfall. Where available, runoff station data was used to calibrate the models. Ungauged watersheds were generally given the same parameter sets as their neighbouring calibrated watersheds. It appeared that the LEW model structure could be improved by applying GLUE iteratively. Eventually, it led to better identifiability of parameters and consequently a better model structure than the STREAM model. Hence, the final model structure obtained better represents the true hydrology. After calibration, both models show a comparable efficiency in representing discharge. However the LEW model shows a far greater storage amplitude than the STREAM model. This emphasizes the storage uncertainty related to hydrological modelling in data-scarce environments such as the Zambezi river basin. It underlines the need and potential for independent observations of terrestrial storage to enhance our understanding and modelling capacity of the hydrological processes. GRACE

Applying a learning design methodology in the flipped classroom approach – empowering teachers to reflect

DEFF Research Database (Denmark)

Triantafyllou, Evangelia; Kofoed, Lise; Purwins, Hendrik

2016-01-01

One of the recent developments in teaching that heavily relies on current technology is the “flipped classroom” approach. In a flipped classroom the traditional lecture and homework sessions are inverted. Students are provided with online material in order to gain necessary knowledge before class......, while class time is devoted to clarifications and application of this knowledge. The hypothesis is that there could be deep and creative discussions when teacher and students physically meet. This paper discusses how the learning design methodology can be applied to represent, share and guide educators...... and values of different stakeholders (i.e. institutions, educators, learners, and external agents), which influence the design and success of flipped classrooms. Moreover, it looks at the teaching cycle from a flipped instruction model perspective and adjusts it to cater for the reflection loops educators...

A multi-objective approach to improve SWAT model calibration in alpine catchments

Science.gov (United States)

Tuo, Ye; Marcolini, Giorgia; Disse, Markus; Chiogna, Gabriele

2018-04-01

Multi-objective hydrological model calibration can represent a valuable solution to reduce model equifinality and parameter uncertainty. The Soil and Water Assessment Tool (SWAT) model is widely applied to investigate water quality and water management issues in alpine catchments. However, the model calibration is generally based on discharge records only, and most of the previous studies have defined a unique set of snow parameters for an entire basin. Only a few studies have considered snow observations to validate model results or have taken into account the possible variability of snow parameters for different subbasins. This work presents and compares three possible calibration approaches. The first two procedures are single-objective calibration procedures, for which all parameters of the SWAT model were calibrated according to river discharge alone. Procedures I and II differ from each other by the assumption used to define snow parameters: The first approach assigned a unique set of snow parameters to the entire basin, whereas the second approach assigned different subbasin-specific sets of snow parameters to each subbasin. The third procedure is a multi-objective calibration, in which we considered snow water equivalent (SWE) information at two different spatial scales (i.e. subbasin and elevation band), in addition to discharge measurements. We tested these approaches in the Upper Adige river basin where a dense network of snow depth measurement stations is available. Only the set of parameters obtained with this multi-objective procedure provided an acceptable prediction of both river discharge and SWE. These findings offer the large community of SWAT users a strategy to improve SWAT modeling in alpine catchments.

Uncertainty Aware Structural Topology Optimization Via a Stochastic Reduced Order Model Approach

Science.gov (United States)

Aguilo, Miguel A.; Warner, James E.

2017-01-01

This work presents a stochastic reduced order modeling strategy for the quantification and propagation of uncertainties in topology optimization. Uncertainty aware optimization problems can be computationally complex due to the substantial number of model evaluations that are necessary to accurately quantify and propagate uncertainties. This computational complexity is greatly magnified if a high-fidelity, physics-based numerical model is used for the topology optimization calculations. Stochastic reduced order model (SROM) methods are applied here to effectively 1) alleviate the prohibitive computational cost associated with an uncertainty aware topology optimization problem; and 2) quantify and propagate the inherent uncertainties due to design imperfections. A generic SROM framework that transforms the uncertainty aware, stochastic topology optimization problem into a deterministic optimization problem that relies only on independent calls to a deterministic numerical model is presented. This approach facilitates the use of existing optimization and modeling tools to accurately solve the uncertainty aware topology optimization problems in a fraction of the computational demand required by Monte Carlo methods. Finally, an example in structural topology optimization is presented to demonstrate the effectiveness of the proposed uncertainty aware structural topology optimization approach.

Finite mixture model applied in the analysis of a turbulent bistable flow on two parallel circular cylinders

Energy Technology Data Exchange (ETDEWEB)

Paula, A.V. de, E-mail: vagtinski@mecanica.ufrgs.br [PROMEC – Programa de Pós Graduação em Engenharia Mecânica, UFRGS – Universidade Federal do Rio Grande do Sul, Porto Alegre, RS (Brazil); Möller, S.V., E-mail: svmoller@ufrgs.br [PROMEC – Programa de Pós Graduação em Engenharia Mecânica, UFRGS – Universidade Federal do Rio Grande do Sul, Porto Alegre, RS (Brazil)

2013-11-15

This paper presents a study of the bistable phenomenon which occurs in the turbulent flow impinging on circular cylinders placed side-by-side. Time series of axial and transversal velocity obtained with the constant temperature hot wire anemometry technique in an aerodynamic channel are used as input data in a finite mixture model, to classify the observed data according to a family of probability density functions. Wavelet transforms are applied to analyze the unsteady turbulent signals. Results of flow visualization show that the flow is predominantly two-dimensional. A double-well energy model is suggested to describe the behavior of the bistable phenomenon in this case. -- Highlights: ► Bistable flow on two parallel cylinders is studied with hot wire anemometry as a first step for the application on the analysis to tube bank flow. ► The method of maximum likelihood estimation is applied to hot wire experimental series to classify the data according to PDF functions in a mixture model approach. ► Results show no evident correlation between the changes of flow modes with time. ► An energy model suggests the presence of more than two flow modes.

A Generalized Hybrid Multiscale Modeling Approach for Flow and Reactive Transport in Porous Media

Science.gov (United States)

Yang, X.; Meng, X.; Tang, Y. H.; Guo, Z.; Karniadakis, G. E.

2017-12-01

Using emerging understanding of biological and environmental processes at fundamental scales to advance predictions of the larger system behavior requires the development of multiscale approaches, and there is strong interest in coupling models at different scales together in a hybrid multiscale simulation framework. A limited number of hybrid multiscale simulation methods have been developed for subsurface applications, mostly using application-specific approaches for model coupling. The proposed generalized hybrid multiscale approach is designed with minimal intrusiveness to the at-scale simulators (pre-selected) and provides a set of lightweight C++ scripts to manage a complex multiscale workflow utilizing a concurrent coupling approach. The workflow includes at-scale simulators (using the lattice-Boltzmann method, LBM, at the pore and Darcy scale, respectively), scripts for boundary treatment (coupling and kriging), and a multiscale universal interface (MUI) for data exchange. The current study aims to apply the generalized hybrid multiscale modeling approach to couple pore- and Darcy-scale models for flow and mixing-controlled reaction with precipitation/dissolution in heterogeneous porous media. The model domain is packed heterogeneously that the mixing front geometry is more complex and not known a priori. To address those challenges, the generalized hybrid multiscale modeling approach is further developed to 1) adaptively define the locations of pore-scale subdomains, 2) provide a suite of physical boundary coupling schemes and 3) consider the dynamic change of the pore structures due to mineral precipitation/dissolution. The results are validated and evaluated by comparing with single-scale simulations in terms of velocities, reactive concentrations and computing cost.

Mechanical disequilibria in two-phase flow models: approaches by relaxation and by a reduced model

International Nuclear Information System (INIS)

Labois, M.

2008-10-01

This thesis deals with hyperbolic models for the simulation of compressible two-phase flows, to find alternatives to the classical bi-fluid model. We first establish a hierarchy of two-phase flow models, obtained according to equilibrium hypothesis between the physical variables of each phase. The use of Chapman-Enskog expansions enables us to link the different existing models to each other. Moreover, models that take into account small physical unbalances are obtained by means of expansion to the order one. The second part of this thesis focuses on the simulation of flows featuring velocity unbalances and pressure balances, in two different ways. First, a two-velocity two-pressure model is used, where non-instantaneous velocity and pressure relaxations are applied so that a balancing of these variables is obtained. A new one-velocity one-pressure dissipative model is then proposed, where the arising of second-order terms enables us to take into account unbalances between the phase velocities. We develop a numerical method based on a fractional step approach for this model. (author)

Towards modeling of nonlinear laser-plasma interactions with hydrocodes: The thick-ray approach

Science.gov (United States)

Colaïtis, A.; Duchateau, G.; Nicolaï, P.; Tikhonchuk, V.

2014-03-01

This paper deals with the computation of laser beam intensity in large-scale radiative hydrocodes applied to the modeling of nonlinear laser-plasma interactions (LPIs) in inertial confinement fusion (ICF). The paraxial complex geometrical optics (PCGO) is adapted for light waves in an inhomogeneous medium and modified to include the inverse bremsstrahlung absorption and the ponderomotive force. This thick-ray model is compared to the standard ray-tracing (RT) approach, both in the chic code. The PCGO model leads to different power deposition patterns and better diffraction modeling compared to standard RT codes. The intensity-reconstruction technique used in RT codes to model nonlinear LPI leads to artificial filamentation and fails to reproduce realistic ponderomotive self-focusing distances, intensity amplifications, and density channel depletions, whereas PCGO succeeds. Bundles of Gaussian thick rays can be used to model realistic non-Gaussian ICF beams. The PCGO approach is expected to improve the accuracy of ICF simulations and serve as a basis to implement diverse LPI effects in large-scale hydrocodes.

Approaches for modeling within subject variability in pharmacometric count data analysis: dynamic inter-occasion variability and stochastic differential equations.

Science.gov (United States)

Deng, Chenhui; Plan, Elodie L; Karlsson, Mats O

2016-06-01

Parameter variation in pharmacometric analysis studies can be characterized as within subject parameter variability (WSV) in pharmacometric models. WSV has previously been successfully modeled using inter-occasion variability (IOV), but also stochastic differential equations (SDEs). In this study, two approaches, dynamic inter-occasion variability (dIOV) and adapted stochastic differential equations, were proposed to investigate WSV in pharmacometric count data analysis. These approaches were applied to published count models for seizure counts and Likert pain scores. Both approaches improved the model fits significantly. In addition, stochastic simulation and estimation were used to explore further the capability of the two approaches to diagnose and improve models where existing WSV is not recognized. The results of simulations confirmed the gain in introducing WSV as dIOV and SDEs when parameters vary randomly over time. Further, the approaches were also informative as diagnostics of model misspecification, when parameters changed systematically over time but this was not recognized in the structural model. The proposed approaches in this study offer strategies to characterize WSV and are not restricted to count data.

Excellent approach to modeling urban expansion by fuzzy cellular automata: agent base model

Science.gov (United States)

Khajavigodellou, Yousef; Alesheikh, Ali A.; Mohammed, Abdulrazak A. S.; Chapi, Kamran

2014-09-01

Recently, the interaction between humans and their environment is the one of important challenges in the world. Landuse/ cover change (LUCC) is a complex process that includes actors and factors at different social and spatial levels. The complexity and dynamics of urban systems make the applicable practice of urban modeling very difficult. With the increased computational power and the greater availability of spatial data, micro-simulation such as the agent based and cellular automata simulation methods, has been developed by geographers, planners, and scholars, and it has shown great potential for representing and simulating the complexity of the dynamic processes involved in urban growth and land use change. This paper presents Fuzzy Cellular Automata in Geospatial Information System and remote Sensing to simulated and predicted urban expansion pattern. These FCA-based dynamic spatial urban models provide an improved ability to forecast and assess future urban growth and to create planning scenarios, allowing us to explore the potential impacts of simulations that correspond to urban planning and management policies. A fuzzy inference guided cellular automata approach. Semantic or linguistic knowledge on Land use change is expressed as fuzzy rules, based on which fuzzy inference is applied to determine the urban development potential for each pixel. The model integrates an ABM (agent-based model) and FCA (Fuzzy Cellular Automata) to investigate a complex decision-making process and future urban dynamic processes. Based on this model rapid development and green land protection under the influences of the behaviors and decision modes of regional authority agents, real estate developer agents, resident agents and non- resident agents and their interactions have been applied to predict the future development patterns of the Erbil metropolitan region.

RISCOM Applied to the Belgian Partnership Model: More and Deeper Levels

International Nuclear Information System (INIS)

Bombaerts, Gunter; Bovy, Michel; Laes, Erik

2006-01-01

Technology participation is not a new concept. It has been applied in different settings in different countries. In this article, we report a comparing analysis of the RISCOM model in Sweden and the Belgian partnership model for low and intermediate short-lived nuclear waste. After a brief description of the partnerships and the RISCOM model, we apply the latter to the first and come to recommendations for the partnership model. The strength of the partnership approach is at the community level. In one of the villages, up to one percent of the population was motivated to discuss at least once a month for four years the nuts and bolts of the repository concept. The stress on the community level and the lack of a guardian includes a weakness as well. First of all, if communities come into competition, the inter-community discussions can start resembling local politics and can become less transparent. Local actors are concerned actors but actors at the national level are concerned as well. The local decisions influence how the waste will be transported. The local decisions also determine an extra cost of electricity. We therefore recommend a broad (in terms of territory) public debate on the participation experiments preceding and concluding the local participation process in which this local process maintains an important position. The conclusions of our comparative analysis are: (1) The guardian of the process at the national level is missing. Since the Belgian nuclear regulator plays a controlling role after the process, we recommend a technology assessment institute at the federal level. (2) We state that stretching in the partnership model can happen more profoundly and recommend a 'counter institute' at the European level. The role of non-participative actors should be valued. (3) Recursion levels can be taken as a point of departure for discussion about the problem framing. If people accept them, there is no problem. If people clearly mention issues that are

RISCOM Applied to the Belgian Partnership Model: More and Deeper Levels

Energy Technology Data Exchange (ETDEWEB)

Bombaerts, Gunter; Bovy, Michel; Laes, Erik [SCKCEN, Mol (Belgium). PISA

2006-09-15

Technology participation is not a new concept. It has been applied in different settings in different countries. In this article, we report a comparing analysis of the RISCOM model in Sweden and the Belgian partnership model for low and intermediate short-lived nuclear waste. After a brief description of the partnerships and the RISCOM model, we apply the latter to the first and come to recommendations for the partnership model. The strength of the partnership approach is at the community level. In one of the villages, up to one percent of the population was motivated to discuss at least once a month for four years the nuts and bolts of the repository concept. The stress on the community level and the lack of a guardian includes a weakness as well. First of all, if communities come into competition, the inter-community discussions can start resembling local politics and can become less transparent. Local actors are concerned actors but actors at the national level are concerned as well. The local decisions influence how the waste will be transported. The local decisions also determine an extra cost of electricity. We therefore recommend a broad (in terms of territory) public debate on the participation experiments preceding and concluding the local participation process in which this local process maintains an important position. The conclusions of our comparative analysis are: (1) The guardian of the process at the national level is missing. Since the Belgian nuclear regulator plays a controlling role after the process, we recommend a technology assessment institute at the federal level. (2) We state that stretching in the partnership model can happen more profoundly and recommend a 'counter institute' at the European level. The role of non-participative actors should be valued. (3) Recursion levels can be taken as a point of departure for discussion about the problem framing. If people accept them, there is no problem. If people clearly mention issues

Magnetic field approaches in dc thermal plasma modelling

International Nuclear Information System (INIS)

Freton, P; Gonzalez, J J; Masquere, M; Reichert, Frank

2011-01-01

The self-induced magnetic field has an important role in thermal plasma configurations generated by electric arcs as it generates velocity through Lorentz forces. In the models a good representation of the magnetic field is thus necessary. Several approaches exist to calculate the self-induced magnetic field such as the Maxwell-Ampere formulation, the vector potential approach combined with different kinds of boundary conditions or the Biot and Savart (B and S) formulation. The calculation of the self-induced magnetic field is alone a difficult problem and only few papers of the thermal plasma community speak on this subject. In this study different approaches with different boundary conditions are applied on two geometries to compare the methods and their limitations. The calculation time is also one of the criteria for the choice of the method and a compromise must be found between method precision and computation time. The study shows the importance of the current carrying path representation in the electrode on the deduced magnetic field. The best compromise consists of using the B and S formulation on the walls and/or edges of the calculation domain to determine the boundary conditions and to solve the vector potential in a 2D system. This approach provides results identical to those obtained using the B and S formulation over the entire domain but with a considerable decrease in calculation time.

A classical Master equation approach to modeling an artificial protein motor

International Nuclear Information System (INIS)

Kuwada, Nathan J.; Blab, Gerhard A.; Linke, Heiner

2010-01-01

Inspired by biomolecular motors, as well as by theoretical concepts for chemically driven nanomotors, there is significant interest in constructing artificial molecular motors. One driving force is the opportunity to create well-controlled model systems that are simple enough to be modeled in detail. A remaining challenge is the fact that such models need to take into account processes on many different time scales. Here we describe use of a classical Master equation approach, integrated with input from Langevin and molecular dynamics modeling, to stochastically model an existing artificial molecular motor concept, the Tumbleweed, across many time scales. This enables us to study how interdependencies between motor processes, such as center-of-mass diffusion and track binding/unbinding, affect motor performance. Results from our model help guide the experimental realization of the proposed motor, and potentially lead to insights that apply to a wider class of molecular motors.

Effects produced by oscillations applied to nonlinear dynamic systems: a general approach and examples

DEFF Research Database (Denmark)

Blekhman, I. I.; Sorokin, V. S.

2016-01-01

A general approach to study effects produced by oscillations applied to nonlinear dynamic systems is developed. It implies a transition from initial governing equations of motion to much more simple equations describing only the main slow component of motions (the vibro-transformed dynamics.......g., the requirement for the involved nonlinearities to be weak. The approach is illustrated by several relevant examples from various fields of science, e.g., mechanics, physics, chemistry and biophysics....... equations). The approach is named as the oscillatory strobodynamics, since motions are perceived as under a stroboscopic light. The vibro-transformed dynamics equations comprise terms that capture the averaged effect of oscillations. The method of direct separation of motions appears to be an efficient...

Review of hardware cost estimation methods, models and tools applied to early phases of space mission planning

Science.gov (United States)

Trivailo, O.; Sippel, M.; Şekercioğlu, Y. A.

2012-08-01

The primary purpose of this paper is to review currently existing cost estimation methods, models, tools and resources applicable to the space sector. While key space sector methods are outlined, a specific focus is placed on hardware cost estimation on a system level, particularly for early mission phases during which specifications and requirements are not yet crystallised, and information is limited. For the space industry, cost engineering within the systems engineering framework is an integral discipline. The cost of any space program now constitutes a stringent design criterion, which must be considered and carefully controlled during the entire program life cycle. A first step to any program budget is a representative cost estimate which usually hinges on a particular estimation approach, or methodology. Therefore appropriate selection of specific cost models, methods and tools is paramount, a difficult task given the highly variable nature, scope as well as scientific and technical requirements applicable to each program. Numerous methods, models and tools exist. However new ways are needed to address very early, pre-Phase 0 cost estimation during the initial program research and establishment phase when system specifications are limited, but the available research budget needs to be established and defined. Due to their specificity, for vehicles such as reusable launchers with a manned capability, a lack of historical data implies that using either the classic heuristic approach such as parametric cost estimation based on underlying CERs, or the analogy approach, is therefore, by definition, limited. This review identifies prominent cost estimation models applied to the space sector, and their underlying cost driving parameters and factors. Strengths, weaknesses, and suitability to specific mission types and classes are also highlighted. Current approaches which strategically amalgamate various cost estimation strategies both for formulation and validation

A Goal Oriented Approach for Modeling and Analyzing Security Trade-Offs

Science.gov (United States)

Elahi, Golnaz; Yu, Eric

In designing software systems, security is typically only one design objective among many. It may compete with other objectives such as functionality, usability, and performance. Too often, security mechanisms such as firewalls, access control, or encryption are adopted without explicit recognition of competing design objectives and their origins in stakeholder interests. Recently, there is increasing acknowledgement that security is ultimately about trade-offs. One can only aim for "good enough" security, given the competing demands from many parties. In this paper, we examine how conceptual modeling can provide explicit and systematic support for analyzing security trade-offs. After considering the desirable criteria for conceptual modeling methods, we examine several existing approaches for dealing with security trade-offs. From analyzing the limitations of existing methods, we propose an extension to the i* framework for security trade-off analysis, taking advantage of its multi-agent and goal orientation. The method was applied to several case studies used to exemplify existing approaches.

Modeling human diseases: an education in interactions and interdisciplinary approaches

Directory of Open Access Journals (Sweden)

Leonard Zon

2016-06-01

Full Text Available Traditionally, most investigators in the biomedical arena exploit one model system in the course of their careers. Occasionally, an investigator will switch models. The selection of a suitable model system is a crucial step in research design. Factors to consider include the accuracy of the model as a reflection of the human disease under investigation, the numbers of animals needed and ease of husbandry, its physiology and developmental biology, and the ability to apply genetics and harness the model for drug discovery. In my lab, we have primarily used the zebrafish but combined it with other animal models and provided a framework for others to consider the application of developmental biology for therapeutic discovery. Our interdisciplinary approach has led to many insights into human diseases and to the advancement of candidate drugs to clinical trials. Here, I draw on my experiences to highlight the importance of combining multiple models, establishing infrastructure and genetic tools, forming collaborations, and interfacing with the medical community for successful translation of basic findings to the clinic.

A model-guided symbolic execution approach for network protocol implementations and vulnerability detection.

Science.gov (United States)

Wen, Shameng; Meng, Qingkun; Feng, Chao; Tang, Chaojing

2017-01-01

Formal techniques have been devoted to analyzing whether network protocol specifications violate security policies; however, these methods cannot detect vulnerabilities in the implementations of the network protocols themselves. Symbolic execution can be used to analyze the paths of the network protocol implementations, but for stateful network protocols, it is difficult to reach the deep states of the protocol. This paper proposes a novel model-guided approach to detect vulnerabilities in network protocol implementations. Our method first abstracts a finite state machine (FSM) model, then utilizes the model to guide the symbolic execution. This approach achieves high coverage of both the code and the protocol states. The proposed method is implemented and applied to test numerous real-world network protocol implementations. The experimental results indicate that the proposed method is more effective than traditional fuzzing methods such as SPIKE at detecting vulnerabilities in the deep states of network protocol implementations.

Applied Computational Mathematics in Social Sciences

CERN Document Server

Damaceanu, Romulus-Catalin

2010-01-01

Applied Computational Mathematics in Social Sciences adopts a modern scientific approach that combines knowledge from mathematical modeling with various aspects of social science. Special algorithms can be created to simulate an artificial society and a detailed analysis can subsequently be used to project social realities. This Ebook specifically deals with computations using the NetLogo platform, and is intended for researchers interested in advanced human geography and mathematical modeling studies.

Approaches and models of intercultural education

Directory of Open Access Journals (Sweden)

Iván Manuel Sánchez Fontalvo

2013-10-01

Full Text Available Needed to be aware of the need to build an intercultural society, awareness must be assumed in all social spheres, where stands the role play education. A role of transcendental, since it must promote educational spaces to form people with virtues and powers that allow them to live together / as in multicultural contexts and social diversities (sometimes uneven in an increasingly globalized and interconnected world, and foster the development of feelings of civic belonging shared before the neighborhood, city, region and country, allowing them concern and critical judgement to marginalization, poverty, misery and inequitable distribution of wealth, causes of structural violence, but at the same time, wanting to work for the welfare and transformation of these scenarios. Since these budgets, it is important to know the approaches and models of intercultural education that have been developed so far, analysing their impact on the contexts educational where apply.   

Stability of rotor systems: A complex modelling approach

DEFF Research Database (Denmark)

Kliem, Wolfhard; Pommer, Christian; Stoustrup, Jakob

1998-01-01

The dynamics of a large class of rotor systems can be modelled by a linearized complex matrix differential equation of second order, Mz + (D + iG)(z) over dot + (K + iN)z = 0, where the system matrices M, D, G, K and N are real symmetric. Moreover M and K are assumed to be positive definite and D...... approach applying bounds of appropriate Rayleigh quotients. The rotor systems tested are: a simple Laval rotor, a Laval rotor with additional elasticity and damping in the bearings, and a number of rotor systems with complex symmetric 4 x 4 randomly generated matrices.......The dynamics of a large class of rotor systems can be modelled by a linearized complex matrix differential equation of second order, Mz + (D + iG)(z) over dot + (K + iN)z = 0, where the system matrices M, D, G, K and N are real symmetric. Moreover M and K are assumed to be positive definite and D...

Optimized Structure of the Traffic Flow Forecasting Model With a Deep Learning Approach.

Science.gov (United States)

Yang, Hao-Fan; Dillon, Tharam S; Chen, Yi-Ping Phoebe

2017-10-01

Forecasting accuracy is an important issue for successful intelligent traffic management, especially in the domain of traffic efficiency and congestion reduction. The dawning of the big data era brings opportunities to greatly improve prediction accuracy. In this paper, we propose a novel model, stacked autoencoder Levenberg-Marquardt model, which is a type of deep architecture of neural network approach aiming to improve forecasting accuracy. The proposed model is designed using the Taguchi method to develop an optimized structure and to learn traffic flow features through layer-by-layer feature granulation with a greedy layerwise unsupervised learning algorithm. It is applied to real-world data collected from the M6 freeway in the U.K. and is compared with three existing traffic predictors. To the best of our knowledge, this is the first time that an optimized structure of the traffic flow forecasting model with a deep learning approach is presented. The evaluation results demonstrate that the proposed model with an optimized structure has superior performance in traffic flow forecasting.

A satellite simulator for TRMM PR applied to climate model simulations

Science.gov (United States)

Spangehl, T.; Schroeder, M.; Bodas-Salcedo, A.; Hollmann, R.; Riley Dellaripa, E. M.; Schumacher, C.

2017-12-01

Climate model simulations have to be compared against observation based datasets in order to assess their skill in representing precipitation characteristics. Here we use a satellite simulator for TRMM PR in order to evaluate simulations performed with MPI-ESM (Earth system model of the Max Planck Institute for Meteorology in Hamburg, Germany) performed within the MiKlip project (https://www.fona-miklip.de/, funded by Federal Ministry of Education and Research in Germany). While classical evaluation methods focus on geophysical parameters such as precipitation amounts, the application of the satellite simulator enables an evaluation in the instrument's parameter space thereby reducing uncertainties on the reference side. The CFMIP Observation Simulator Package (COSP) provides a framework for the application of satellite simulators to climate model simulations. The approach requires the introduction of sub-grid cloud and precipitation variability. Radar reflectivities are obtained by applying Mie theory, with the microphysical assumptions being chosen to match the atmosphere component of MPI-ESM (ECHAM6). The results are found to be sensitive to the methods used to distribute the convective precipitation over the sub-grid boxes. Simple parameterization methods are used to introduce sub-grid variability of convective clouds and precipitation. In order to constrain uncertainties a comprehensive comparison with sub-grid scale convective precipitation variability which is deduced from TRMM PR observations is carried out.

Possibilities and limitations of applying software reliability growth models to safety-critical software

International Nuclear Information System (INIS)

Kim, Man Cheol; Jang, Seung Cheol; Ha, Jae Joo

2007-01-01

It is generally known that software reliability growth models such as the Jelinski-Moranda model and the Goel-Okumoto's Non-Homogeneous Poisson Process (NHPP) model cannot be applied to safety-critical software due to a lack of software failure data. In this paper, by applying two of the most widely known software reliability growth models to sample software failure data, we demonstrate the possibility of using the software reliability growth models to prove the high reliability of safety-critical software. The high sensitivity of a piece of software's reliability to software failure data, as well as a lack of sufficient software failure data, is also identified as a possible limitation when applying the software reliability growth models to safety-critical software

TU-G-210-02: TRANS-FUSIMO - An Integrative Approach to Model-Based Treatment Planning of Liver FUS

Energy Technology Data Exchange (ETDEWEB)

Preusser, T. [Fraunhofer MEVIS & Jacobs University (Germany)

2015-06-15

Modeling can play a vital role in predicting, optimizing and analyzing the results of therapeutic ultrasound treatments. Simulating the propagating acoustic beam in various targeted regions of the body allows for the prediction of the resulting power deposition and temperature profiles. In this session we will apply various modeling approaches to breast, abdominal organ and brain treatments. Of particular interest is the effectiveness of procedures for correcting for phase aberrations caused by intervening irregular tissues, such as the skull in transcranial applications or inhomogeneous breast tissues. Also described are methods to compensate for motion in targeted abdominal organs such as the liver or kidney. Douglas Christensen – Modeling for Breast and Brain HIFU Treatment Planning Tobias Preusser – TRANS-FUSIMO – An Integrative Approach to Model-Based Treatment Planning of Liver FUS Tobias Preusser – TRANS-FUSIMO – An Integrative Approach to Model-Based Treatment Planning of Liver FUS Learning Objectives: Understand the role of acoustic beam modeling for predicting the effectiveness of therapeutic ultrasound treatments. Apply acoustic modeling to specific breast, liver, kidney and transcranial anatomies. Determine how to obtain appropriate acoustic modeling parameters from clinical images. Understand the separate role of absorption and scattering in energy delivery to tissues. See how organ motion can be compensated for in ultrasound therapies. Compare simulated data with clinical temperature measurements in transcranial applications. Supported by NIH R01 HL172787 and R01 EB013433 (DC); EU Seventh Framework Programme (FP7/2007-2013) under 270186 (FUSIMO) and 611889 (TRANS-FUSIMO)(TP); and P01 CA159992, GE, FUSF and InSightec (UV)

TU-G-210-02: TRANS-FUSIMO - An Integrative Approach to Model-Based Treatment Planning of Liver FUS

International Nuclear Information System (INIS)

Preusser, T.

2015-01-01

Modeling can play a vital role in predicting, optimizing and analyzing the results of therapeutic ultrasound treatments. Simulating the propagating acoustic beam in various targeted regions of the body allows for the prediction of the resulting power deposition and temperature profiles. In this session we will apply various modeling approaches to breast, abdominal organ and brain treatments. Of particular interest is the effectiveness of procedures for correcting for phase aberrations caused by intervening irregular tissues, such as the skull in transcranial applications or inhomogeneous breast tissues. Also described are methods to compensate for motion in targeted abdominal organs such as the liver or kidney. Douglas Christensen – Modeling for Breast and Brain HIFU Treatment Planning Tobias Preusser – TRANS-FUSIMO – An Integrative Approach to Model-Based Treatment Planning of Liver FUS Tobias Preusser – TRANS-FUSIMO – An Integrative Approach to Model-Based Treatment Planning of Liver FUS Learning Objectives: Understand the role of acoustic beam modeling for predicting the effectiveness of therapeutic ultrasound treatments. Apply acoustic modeling to specific breast, liver, kidney and transcranial anatomies. Determine how to obtain appropriate acoustic modeling parameters from clinical images. Understand the separate role of absorption and scattering in energy delivery to tissues. See how organ motion can be compensated for in ultrasound therapies. Compare simulated data with clinical temperature measurements in transcranial applications. Supported by NIH R01 HL172787 and R01 EB013433 (DC); EU Seventh Framework Programme (FP7/2007-2013) under 270186 (FUSIMO) and 611889 (TRANS-FUSIMO)(TP); and P01 CA159992, GE, FUSF and InSightec (UV)

Depletion benchmarks calculation of random media using explicit modeling approach of RMC

International Nuclear Information System (INIS)

Liu, Shichang; She, Ding; Liang, Jin-gang; Wang, Kan

2016-01-01

Highlights: • Explicit modeling of RMC is applied to depletion benchmark for HTGR fuel element. • Explicit modeling can provide detailed burnup distribution and burnup heterogeneity. • The results would serve as a supplement for the HTGR fuel depletion benchmark. • The method of adjacent burnup regions combination is proposed for full-core problems. • The combination method can reduce memory footprint, keeping the computing accuracy. - Abstract: Monte Carlo method plays an important role in accurate simulation of random media, owing to its advantages of the flexible geometry modeling and the use of continuous-energy nuclear cross sections. Three stochastic geometry modeling methods including Random Lattice Method, Chord Length Sampling and explicit modeling approach with mesh acceleration technique, have been implemented in RMC to simulate the particle transport in the dispersed fuels, in which the explicit modeling method is regarded as the best choice. In this paper, the explicit modeling method is applied to the depletion benchmark for HTGR fuel element, and the method of combination of adjacent burnup regions has been proposed and investigated. The results show that the explicit modeling can provide detailed burnup distribution of individual TRISO particles, and this work would serve as a supplement for the HTGR fuel depletion benchmark calculations. The combination of adjacent burnup regions can effectively reduce the memory footprint while keeping the computational accuracy.

Modeling of annular two-phase flow using a unified CFD approach

Energy Technology Data Exchange (ETDEWEB)

Li, Haipeng, E-mail: haipengl@kth.se; Anglart, Henryk, E-mail: henryk@kth.se

2016-07-15

Highlights: • Annular two-phase flow has been modeled using a unified CFD approach. • Liquid film was modeled based on a two-dimensional thin film assumption. • Both Eulerian and Lagrangian methods were employed for the gas core flow modeling. - Abstract: A mechanistic model of annular flow with evaporating liquid film has been developed using computational fluid dynamics (CFD). The model is employing a separate solver with two-dimensional conservation equations to predict propagation of a thin boiling liquid film on solid walls. The liquid film model is coupled to a solver of three-dimensional conservation equations describing the gas core, which is assumed to contain a saturated mixture of vapor and liquid droplets. Both the Eulerian–Eulerian and the Eulerian–Lagrangian approach are used to describe the droplet and vapor motion in the gas core. All the major interaction phenomena between the liquid film and the gas core flow have been accounted for, including the liquid film evaporation as well as the droplet deposition and entrainment. The resultant unified framework for annular flow has been applied to the steam-water flow with conditions typical for a Boiling Water Reactor (BWR). The simulation results for the liquid film flow rate show good agreement with the experimental data, with the potential to predict the dryout occurrence based on criteria of critical film thickness or critical film flow rate.

Modeling of annular two-phase flow using a unified CFD approach

International Nuclear Information System (INIS)

Li, Haipeng; Anglart, Henryk

2016-01-01

Highlights: • Annular two-phase flow has been modeled using a unified CFD approach. • Liquid film was modeled based on a two-dimensional thin film assumption. • Both Eulerian and Lagrangian methods were employed for the gas core flow modeling. - Abstract: A mechanistic model of annular flow with evaporating liquid film has been developed using computational fluid dynamics (CFD). The model is employing a separate solver with two-dimensional conservation equations to predict propagation of a thin boiling liquid film on solid walls. The liquid film model is coupled to a solver of three-dimensional conservation equations describing the gas core, which is assumed to contain a saturated mixture of vapor and liquid droplets. Both the Eulerian–Eulerian and the Eulerian–Lagrangian approach are used to describe the droplet and vapor motion in the gas core. All the major interaction phenomena between the liquid film and the gas core flow have been accounted for, including the liquid film evaporation as well as the droplet deposition and entrainment. The resultant unified framework for annular flow has been applied to the steam-water flow with conditions typical for a Boiling Water Reactor (BWR). The simulation results for the liquid film flow rate show good agreement with the experimental data, with the potential to predict the dryout occurrence based on criteria of critical film thickness or critical film flow rate.

A combined triggering-propagation modeling approach for the assessment of rainfall induced debris flow susceptibility

Science.gov (United States)

Stancanelli, Laura Maria; Peres, David Johnny; Cancelliere, Antonino; Foti, Enrico

2017-07-01

Rainfall-induced shallow slides can evolve into debris flows that move rapidly downstream with devastating consequences. Mapping the susceptibility to debris flow is an important aid for risk mitigation. We propose a novel practical approach to derive debris flow inundation maps useful for susceptibility assessment, that is based on the integrated use of DEM-based spatially-distributed hydrological and slope stability models with debris flow propagation models. More specifically, the TRIGRS infiltration and infinite slope stability model and the FLO-2D model for the simulation of the related debris flow propagation and deposition are combined. An empirical instability-to-debris flow triggering threshold calibrated on the basis of observed events, is applied to link the two models and to accomplish the task of determining the amount of unstable mass that develops as a debris flow. Calibration of the proposed methodology is carried out based on real data of the debris flow event occurred on 1 October 2009, in the Peloritani mountains area (Italy). Model performance, assessed by receiver-operating-characteristics (ROC) indexes, evidences fairly good reproduction of the observed event. Comparison with the performance of the traditional debris flow modeling procedure, in which sediment and water hydrographs are inputed as lumped at selected points on top of the streams, is also performed, in order to assess quantitatively the limitations of such commonly applied approach. Results show that the proposed method, besides of being more process-consistent than the traditional hydrograph-based approach, can potentially provide a more accurate simulation of debris-flow phenomena, in terms of spatial patterns of erosion and deposition as well on the quantification of mobilized volumes and depths, avoiding overestimation of debris flow triggering volume and, thus, of maximum inundation flow depths.

A new approach for modeling the peak utility impacts from a proposed CUAC standard

Energy Technology Data Exchange (ETDEWEB)

LaCommare, Kristina Hamachi; Gumerman, Etan; Marnay, Chris; Chan, Peter; Coughlin, Katie

2004-08-01

This report describes a new Berkeley Lab approach for modeling the likely peak electricity load reductions from proposed energy efficiency programs in the National Energy Modeling System (NEMS). This method is presented in the context of the commercial unitary air conditioning (CUAC) energy efficiency standards. A previous report investigating the residential central air conditioning (RCAC) load shapes in NEMS revealed that the peak reduction results were lower than expected. This effect was believed to be due in part to the presence of the squelch, a program algorithm designed to ensure changes in the system load over time are consistent with the input historic trend. The squelch applies a system load-scaling factor that scales any differences between the end-use bottom-up and system loads to maintain consistency with historic trends. To obtain more accurate peak reduction estimates, a new approach for modeling the impact of peaky end uses in NEMS-BT has been developed. The new approach decrements the system load directly, reducing the impact of the squelch on the final results. This report also discusses a number of additional factors, in particular non-coincidence between end-use loads and system loads as represented within NEMS, and their impacts on the peak reductions calculated by NEMS. Using Berkeley Lab's new double-decrement approach reduces the conservation load factor (CLF) on an input load decrement from 25% down to 19% for a SEER 13 CUAC trial standard level, as seen in NEMS-BT output. About 4 GW more in peak capacity reduction results from this new approach as compared to Berkeley Lab's traditional end-use decrement approach, which relied solely on lowering end use energy consumption. The new method has been fully implemented and tested in the Annual Energy Outlook 2003 (AEO2003) version of NEMS and will routinely be applied to future versions. This capability is now available for use in future end-use efficiency or other policy analysis

Model-free adaptive control optimization using a chaotic particle swarm approach

Energy Technology Data Exchange (ETDEWEB)

Santos Coelho, Leandro dos [Industrial and Systems Engineering Graduate Program, LAS/PPGEPS, Pontifical Catholic University of Parana, PUCPR, Imaculada Conceicao, 1155, 80215-901 Curitiba, Parana (Brazil)], E-mail: leandro.coelho@pucpr.br; Rodrigues Coelho, Antonio Augusto [Department of Automation and Systems, Federal University of Santa Catarina, Box 476, 88040-900 Florianopolis, Santa Catarina (Brazil)], E-mail: aarc@das.ufsc.br

2009-08-30

It is well known that conventional control theories are widely suited for applications where the processes can be reasonably described in advance. However, when the plant's dynamics are hard to characterize precisely or are subject to environmental uncertainties, one may encounter difficulties in applying the conventional controller design methodologies. Despite the difficulty in achieving high control performance, the fine tuning of controller parameters is a tedious task that always requires experts with knowledge in both control theory and process information. Nowadays, more and more studies have focused on the development of adaptive control algorithms that can be directly applied to complex processes whose dynamics are poorly modeled and/or have severe nonlinearities. In this context, the design of a Model-Free Learning Adaptive Control (MFLAC) based on pseudo-gradient concepts and optimization procedure by a Particle Swarm Optimization (PSO) approach using constriction coefficient and Henon chaotic sequences (CPSOH) is presented in this paper. PSO is a stochastic global optimization technique inspired by social behavior of bird flocking. The PSO models the exploration of a problem space by a population of particles. Each particle in PSO has a randomized velocity associated to it, which moves through the space of the problem. Since chaotic mapping enjoys certainty, ergodicity and the stochastic property, the proposed CPSOH introduces chaos mapping which introduces some flexibility in particle movements in each iteration. The chaotic sequences allow also explorations at early stages and exploitations at later stages during the search procedure of CPSOH. Motivation for application of CPSOH approach is to overcome the limitation of the conventional MFLAC design, which cannot guarantee satisfactory control performance when the plant has different gains for the operational range when designed by trial-and-error by user. Numerical results of the MFLAC with

Model-free adaptive control optimization using a chaotic particle swarm approach

International Nuclear Information System (INIS)

Santos Coelho, Leandro dos; Rodrigues Coelho, Antonio Augusto

2009-01-01

It is well known that conventional control theories are widely suited for applications where the processes can be reasonably described in advance. However, when the plant's dynamics are hard to characterize precisely or are subject to environmental uncertainties, one may encounter difficulties in applying the conventional controller design methodologies. Despite the difficulty in achieving high control performance, the fine tuning of controller parameters is a tedious task that always requires experts with knowledge in both control theory and process information. Nowadays, more and more studies have focused on the development of adaptive control algorithms that can be directly applied to complex processes whose dynamics are poorly modeled and/or have severe nonlinearities. In this context, the design of a Model-Free Learning Adaptive Control (MFLAC) based on pseudo-gradient concepts and optimization procedure by a Particle Swarm Optimization (PSO) approach using constriction coefficient and Henon chaotic sequences (CPSOH) is presented in this paper. PSO is a stochastic global optimization technique inspired by social behavior of bird flocking. The PSO models the exploration of a problem space by a population of particles. Each particle in PSO has a randomized velocity associated to it, which moves through the space of the problem. Since chaotic mapping enjoys certainty, ergodicity and the stochastic property, the proposed CPSOH introduces chaos mapping which introduces some flexibility in particle movements in each iteration. The chaotic sequences allow also explorations at early stages and exploitations at later stages during the search procedure of CPSOH. Motivation for application of CPSOH approach is to overcome the limitation of the conventional MFLAC design, which cannot guarantee satisfactory control performance when the plant has different gains for the operational range when designed by trial-and-error by user. Numerical results of the MFLAC with CPSOH

Recent progress and modern challenges in applied mathematics, modeling and computational science

CERN Document Server

Makarov, Roman; Belair, Jacques

2017-01-01

This volume is an excellent resource for professionals in various areas of applications of mathematics, modeling, and computational science. It focuses on recent progress and modern challenges in these areas. The volume provides a balance between fundamental theoretical and applied developments, emphasizing the interdisciplinary nature of modern trends and detailing state-of-the-art achievements in Applied Mathematics, Modeling, and Computational Science.  The chapters have been authored by international experts in their respective fields, making this book ideal for researchers in academia, practitioners, and graduate students. It can also serve as a reference in the diverse selected areas of applied mathematics, modelling, and computational sciences, and is ideal for interdisciplinary collaborations.

Evolutionary modeling-based approach for model errors correction

Directory of Open Access Journals (Sweden)

S. Q. Wan

2012-08-01

Full Text Available The inverse problem of using the information of historical data to estimate model errors is one of the science frontier research topics. In this study, we investigate such a problem using the classic Lorenz (1963 equation as a prediction model and the Lorenz equation with a periodic evolutionary function as an accurate representation of reality to generate "observational data."

On the basis of the intelligent features of evolutionary modeling (EM, including self-organization, self-adaptive and self-learning, the dynamic information contained in the historical data can be identified and extracted by computer automatically. Thereby, a new approach is proposed to estimate model errors based on EM in the present paper. Numerical tests demonstrate the ability of the new approach to correct model structural errors. In fact, it can actualize the combination of the statistics and dynamics to certain extent.

Identifying the optimal supply temperature in district heating networks - A modelling approach

DEFF Research Database (Denmark)

Mohammadi, Soma; Bojesen, Carsten

2014-01-01

of this study is to develop a model for thermo-hydraulic calculation of low temperature DH system. The modelling is performed with emphasis on transient heat transfer in pipe networks. The pseudo-dynamic approach is adopted to model the District Heating Network [DHN] behaviour which estimates the temperature...... dynamically while the flow and pressure are calculated on the basis of steady state conditions. The implicit finite element method is applied to simulate the transient temperature behaviour in the network. Pipe network heat losses, pressure drop in the network and return temperature to the plant...... are calculated in the developed model. The model will serve eventually as a basis to find out the optimal supply temperature in an existing DHN in later work. The modelling results are used as decision support for existing DHN; proposing possible modifications to operate at optimal supply temperature....

HEDR modeling approach

International Nuclear Information System (INIS)

Shipler, D.B.; Napier, B.A.

1992-07-01

This report details the conceptual approaches to be used in calculating radiation doses to individuals throughout the various periods of operations at the Hanford Site. The report considers the major environmental transport pathways--atmospheric, surface water, and ground water--and projects and appropriate modeling technique for each. The modeling sequence chosen for each pathway depends on the available data on doses, the degree of confidence justified by such existing data, and the level of sophistication deemed appropriate for the particular pathway and time period being considered

Global Environmental Change: An integrated modelling approach

International Nuclear Information System (INIS)

Den Elzen, M.

1993-01-01

Two major global environmental problems are dealt with: climate change and stratospheric ozone depletion (and their mutual interactions), briefly surveyed in part 1. In Part 2 a brief description of the integrated modelling framework IMAGE 1.6 is given. Some specific parts of the model are described in more detail in other Chapters, e.g. the carbon cycle model, the atmospheric chemistry model, the halocarbon model, and the UV-B impact model. In Part 3 an uncertainty analysis of climate change and stratospheric ozone depletion is presented (Chapter 4). Chapter 5 briefly reviews the social and economic uncertainties implied by future greenhouse gas emissions. Chapters 6 and 7 describe a model and sensitivity analysis pertaining to the scientific uncertainties and/or lacunae in the sources and sinks of methane and carbon dioxide, and their biogeochemical feedback processes. Chapter 8 presents an uncertainty and sensitivity analysis of the carbon cycle model, the halocarbon model, and the IMAGE model 1.6 as a whole. Part 4 presents the risk assessment methodology as applied to the problems of climate change and stratospheric ozone depletion more specifically. In Chapter 10, this methodology is used as a means with which to asses current ozone policy and a wide range of halocarbon policies. Chapter 11 presents and evaluates the simulated globally-averaged temperature and sea level rise (indicators) for the IPCC-1990 and 1992 scenarios, concluding with a Low Risk scenario, which would meet the climate targets. Chapter 12 discusses the impact of sea level rise on the frequency of the Dutch coastal defence system (indicator) for the IPCC-1990 scenarios. Chapter 13 presents projections of mortality rates due to stratospheric ozone depletion based on model simulations employing the UV-B chain model for a number of halocarbon policies. Chapter 14 presents an approach for allocating future emissions of CO 2 among regions. (Abstract Truncated)

Inverse geothermal modelling applied to Danish sedimentary basins

Science.gov (United States)

Poulsen, Søren E.; Balling, Niels; Bording, Thue S.; Mathiesen, Anders; Nielsen, Søren B.

2017-10-01

This paper presents a numerical procedure for predicting subsurface temperatures and heat-flow distribution in 3-D using inverse calibration methodology. The procedure is based on a modified version of the groundwater code MODFLOW by taking advantage of the mathematical similarity between confined groundwater flow (Darcy's law) and heat conduction (Fourier's law). Thermal conductivity, heat production and exponential porosity-depth relations are specified separately for the individual geological units of the model domain. The steady-state temperature model includes a model-based transient correction for the long-term palaeoclimatic thermal disturbance of the subsurface temperature regime. Variable model parameters are estimated by inversion of measured borehole temperatures with uncertainties reflecting their quality. The procedure facilitates uncertainty estimation for temperature predictions. The modelling procedure is applied to Danish onshore areas containing deep sedimentary basins. A 3-D voxel-based model, with 14 lithological units from surface to 5000 m depth, was built from digital geological maps derived from combined analyses of reflection seismic lines and borehole information. Matrix thermal conductivity of model lithologies was estimated by inversion of all available deep borehole temperature data and applied together with prescribed background heat flow to derive the 3-D subsurface temperature distribution. Modelled temperatures are found to agree very well with observations. The numerical model was utilized for predicting and contouring temperatures at 2000 and 3000 m depths and for two main geothermal reservoir units, the Gassum (Lower Jurassic-Upper Triassic) and Bunter/Skagerrak (Triassic) reservoirs, both currently utilized for geothermal energy production. Temperature gradients to depths of 2000-3000 m are generally around 25-30 °C km-1, locally up to about 35 °C km-1. Large regions have geothermal reservoirs with characteristic temperatures

Computation of External Quality Factors for RF Structures by Means of Model Order Reduction and a Perturbation Approach

CERN Document Server

Flisgen, Thomas; van Rienen, Ursula

2016-01-01

External quality factors are significant quantities to describe losses via waveguide ports in radio frequency resonators. The current contribution presents a novel approach to determine external quality factors by means of a two-step procedure: First, a state-space model for the lossless radio frequency structure is generated and its model order is reduced. Subsequently, a perturbation method is applied on the reduced model so that external losses are accounted for. The advantage of this approach results from the fact that the challenges in dealing with lossy systems are shifted to the reduced order model. This significantly saves computational costs. The present paper provides a short overview on existing methods to compute external quality factors. Then, the novel approach is introduced and validated in terms of accuracy and computational time by means of commercial software.

A Bayesian Approach for Structural Learning with Hidden Markov Models

Directory of Open Access Journals (Sweden)

Cen Li

2002-01-01

Full Text Available Hidden Markov Models(HMM have proved to be a successful modeling paradigm for dynamic and spatial processes in many domains, such as speech recognition, genomics, and general sequence alignment. Typically, in these applications, the model structures are predefined by domain experts. Therefore, the HMM learning problem focuses on the learning of the parameter values of the model to fit the given data sequences. However, when one considers other domains, such as, economics and physiology, model structure capturing the system dynamic behavior is not available. In order to successfully apply the HMM methodology in these domains, it is important that a mechanism is available for automatically deriving the model structure from the data. This paper presents a HMM learning procedure that simultaneously learns the model structure and the maximum likelihood parameter values of a HMM from data. The HMM model structures are derived based on the Bayesian model selection methodology. In addition, we introduce a new initialization procedure for HMM parameter value estimation based on the K-means clustering method. Experimental results with artificially generated data show the effectiveness of the approach.

Making Faces - State-Space Models Applied to Multi-Modal Signal Processing

DEFF Research Database (Denmark)

Lehn-Schiøler, Tue

2005-01-01

The two main focus areas of this thesis are State-Space Models and multi modal signal processing. The general State-Space Model is investigated and an addition to the class of sequential sampling methods is proposed. This new algorithm is denoted as the Parzen Particle Filter. Furthermore...... optimizer can be applied to speed up convergence. The linear version of the State-Space Model, the Kalman Filter, is applied to multi modal signal processing. It is demonstrated how a State-Space Model can be used to map from speech to lip movements. Besides the State-Space Model and the multi modal...... application an information theoretic vector quantizer is also proposed. Based on interactions between particles, it is shown how a quantizing scheme based on an analytic cost function can be derived....

A practical approach to parameter estimation applied to model predicting heart rate regulation

DEFF Research Database (Denmark)

Olufsen, Mette; Ottesen, Johnny T.

2013-01-01

Mathematical models have long been used for prediction of dynamics in biological systems. Recently, several efforts have been made to render these models patient specific. One way to do so is to employ techniques to estimate parameters that enable model based prediction of observed quantities....... Knowledge of variation in parameters within and between groups of subjects have potential to provide insight into biological function. Often it is not possible to estimate all parameters in a given model, in particular if the model is complex and the data is sparse. However, it may be possible to estimate...... a subset of model parameters reducing the complexity of the problem. In this study, we compare three methods that allow identification of parameter subsets that can be estimated given a model and a set of data. These methods will be used to estimate patient specific parameters in a model predicting...

An extended gravity model with substitution applied to international trade

NARCIS (Netherlands)

Bikker, J.A.|info:eu-repo/dai/nl/06912261X

The traditional gravity model has been applied many times to international trade flows, especially in order to analyze trade creation and trade diversion. However, there are two fundamental objections to the model: it cannot describe substitutions between flows and it lacks a cogent theoretical

Surface complexation modelling applied to the sorption of nickel on silica

International Nuclear Information System (INIS)

Olin, M.

1995-10-01

The modelling based on a mechanistic approach, of a sorption experiment is presented in the report. The system chosen for experiments (nickel + silica) is modelled by using literature values for some parameters, the remainder being fitted by existing experimental results. All calculations are performed by HYDRAQL, a model planned especially for surface complexation modelling. Allmost all the calculations are made by using the Triple-Layer Model (TLM) approach, which appeared to be sufficiently flexible for the silica system. The report includes a short description of mechanistic sorption models, input data, experimental results and modelling results (mostly graphical presentations). (13 refs., 40 figs., 4 tabs.)

Metric-based approach and tool for modeling the I and C system using Markov chains

International Nuclear Information System (INIS)

Butenko, Valentyna; Kharchenko, Vyacheslav; Odarushchenko, Elena; Butenko, Dmitriy

2015-01-01

Markov's chains (MC) are well-know and widely applied in dependability and performability analysis of safety-critical systems, because of the flexible representation of system components dependencies and synchronization. There are few radblocks for greater application of the MC: accounting the additional system components increases the model state-space and complicates analysis; the non-numerically sophisticated user may find it difficult to decide between the variety of numerical methods to determine the most suitable and accurate for their application. Thus obtaining the high accurate and trusted modeling results becomes a nontrivial task. In this paper, we present the metric-based approach for selection of the applicable solution approach, based on the analysis of MCs stiffness, decomposability, sparsity and fragmentedness. Using this selection procedure the modeler can provide the verification of earlier obtained results. The presented approach was implemented in utility MSMC, which supports the MC construction, metric-based analysis, recommendations shaping and model solution. The model can be exported to the wall-known off-the-shelf mathematical packages for verification. The paper presents the case study of the industrial NPP I and C system, manufactured by RPC Radiy. The paper shows an application of metric-based approach and MSMC fool for dependability and safety analysis of RTS, and procedure of results verification. (author)

Modeling drug- and chemical- induced hepatotoxicity with systems biology approaches

Directory of Open Access Journals (Sweden)

Sudin eBhattacharya

2012-12-01

Full Text Available We provide an overview of computational systems biology approaches as applied to the study of chemical- and drug-induced toxicity. The concept of ‘toxicity pathways’ is described in the context of the 2007 US National Academies of Science report, Toxicity testing in the 21st Century: A Vision and A Strategy. Pathway mapping and modeling based on network biology concepts are a key component of the vision laid out in this report for a more biologically-based analysis of dose-response behavior and the safety of chemicals and drugs. We focus on toxicity of the liver (hepatotoxicity – a complex phenotypic response with contributions from a number of different cell types and biological processes. We describe three case studies of complementary multi-scale computational modeling approaches to understand perturbation of toxicity pathways in the human liver as a result of exposure to environmental contaminants and specific drugs. One approach involves development of a spatial, multicellular virtual tissue model of the liver lobule that combines molecular circuits in individual hepatocytes with cell-cell interactions and blood-mediated transport of toxicants through hepatic sinusoids, to enable quantitative, mechanistic prediction of hepatic dose-response for activation of the AhR toxicity pathway. Simultaneously, methods are being developing to extract quantitative maps of intracellular signaling and transcriptional regulatory networks perturbed by environmental contaminants, using a combination of gene expression and genome-wide protein-DNA interaction data. A predictive physiological model (DILIsymTM to understand drug-induced liver injury (DILI, the most common adverse event leading to termination of clinical development programs and regulatory actions on drugs, is also described. The model initially focuses on reactive metabolite-induced DILI in response to administration of acetaminophen, and spans multiple biological scales.

Numerical Approach to Spatial Deterministic-Stochastic Models Arising in Cell Biology.

Science.gov (United States)

Schaff, James C; Gao, Fei; Li, Ye; Novak, Igor L; Slepchenko, Boris M

2016-12-01

Hybrid deterministic-stochastic methods provide an efficient alternative to a fully stochastic treatment of models which include components with disparate levels of stochasticity. However, general-purpose hybrid solvers for spatially resolved simulations of reaction-diffusion systems are not widely available. Here we describe fundamentals of a general-purpose spatial hybrid method. The method generates realizations of a spatially inhomogeneous hybrid system by appropriately integrating capabilities of a deterministic partial differential equation solver with a popular particle-based stochastic simulator, Smoldyn. Rigorous validation of the algorithm is detailed, using a simple model of calcium 'sparks' as a testbed. The solver is then applied to a deterministic-stochastic model of spontaneous emergence of cell polarity. The approach is general enough to be implemented within biologist-friendly software frameworks such as Virtual Cell.

Groundwater potentiality mapping using geoelectrical-based aquifer hydraulic parameters: A GIS-based multi-criteria decision analysis modeling approach

Directory of Open Access Journals (Sweden)

Kehinde Anthony Mogaji Hwee San Lim

2017-01-01

Full Text Available This study conducted a robust analysis on acquired 2D resistivity imaging data and borehole pumping test records to optimize groundwater potentiality mapping in Perak province, Malaysia using derived aquifer hydraulic properties. The transverse resistance (TR parameter was determined from the interpreted 2D resistivity imaging data by applying the Dar-Zarrouk parameter equation. Linear regression and GIS techniques were used to regress the estimated values for TR parameters with the aquifer transmissivity values extracted from the geospatially produced BPT records-based aquifer transmissivity map to develop the aquifer transmissivity parameter predictive (ATPP model. The reliability evaluated ATPP model using the Theil inequality coefficient measurement approach was used to establish geoelectrical-based hydraulic parameters (GHP modeling equations for the modeling of transmissivity (Tr, hydraulic conductivity (K, storativity (St, and hydraulic diffusivity (D properties. The applied GHP modeling equation results to the delineated aquifer media was used to produce aquifer potential conditioning factor maps for Tr, K, St, and D. The maps were modeled to develop an aquifer potential mapping index (APMI model via applying the multi-criteria decision analysis-analytic hierarchy process principle. The area groundwater reservoir productivity potential model map produced based on the processed APMI model estimates in the GIS environment was found to be 71% accurate. This study establishes a good alternative approach to determine aquifer hydraulic parameters even in areas where pumping test information is unavailable using a cost effective geophysical data. The produced map can be explored for hydrological decision making.

A Statistical Approach For Modeling Tropical Cyclones. Synthetic Hurricanes Generator Model

Energy Technology Data Exchange (ETDEWEB)

Pasqualini, Donatella [Los Alamos National Lab. (LANL), Los Alamos, NM (United States)

2016-05-11

This manuscript brie y describes a statistical ap- proach to generate synthetic tropical cyclone tracks to be used in risk evaluations. The Synthetic Hur- ricane Generator (SynHurG) model allows model- ing hurricane risk in the United States supporting decision makers and implementations of adaptation strategies to extreme weather. In the literature there are mainly two approaches to model hurricane hazard for risk prediction: deterministic-statistical approaches, where the storm key physical parameters are calculated using physi- cal complex climate models and the tracks are usually determined statistically from historical data; and sta- tistical approaches, where both variables and tracks are estimated stochastically using historical records. SynHurG falls in the second category adopting a pure stochastic approach.

Remarks on orthotropic elastic models applied to wood

Directory of Open Access Journals (Sweden)

Nilson Tadeu Mascia

2006-09-01

Full Text Available Wood is generally considered an anisotropic material. In terms of engineering elastic models, wood is usually treated as an orthotropic material. This paper presents an analysis of two principal anisotropic elastic models that are usually applied to wood. The first one, the linear orthotropic model, where the material axes L (Longitudinal, R( radial and T(tangential are coincident with the Cartesian axes (x, y, z, is more accepted as wood elastic model. The other one, the cylindrical orthotropic model is more adequate of the growth caracteristics of wood but more mathematically complex to be adopted in practical terms. Specifically due to its importance in wood elastic parameters, this paper deals with the fiber orientation influence in these models through adequate transformation of coordinates. As a final result, some examples of the linear model, which show the variation of elastic moduli, i.e., Young´s modulus and shear modulus, with fiber orientation are presented.

A model-guided symbolic execution approach for network protocol implementations and vulnerability detection.

Directory of Open Access Journals (Sweden)

Shameng Wen

Full Text Available Formal techniques have been devoted to analyzing whether network protocol specifications violate security policies; however, these methods cannot detect vulnerabilities in the implementations of the network protocols themselves. Symbolic execution can be used to analyze the paths of the network protocol implementations, but for stateful network protocols, it is difficult to reach the deep states of the protocol. This paper proposes a novel model-guided approach to detect vulnerabilities in network protocol implementations. Our method first abstracts a finite state machine (FSM model, then utilizes the model to guide the symbolic execution. This approach achieves high coverage of both the code and the protocol states. The proposed method is implemented and applied to test numerous real-world network protocol implementations. The experimental results indicate that the proposed method is more effective than traditional fuzzing methods such as SPIKE at detecting vulnerabilities in the deep states of network protocol implementations.

Application of various FLD modelling approaches

Science.gov (United States)

Banabic, D.; Aretz, H.; Paraianu, L.; Jurco, P.

2005-07-01

This paper focuses on a comparison between different modelling approaches to predict the forming limit diagram (FLD) for sheet metal forming under a linear strain path using the recently introduced orthotropic yield criterion BBC2003 (Banabic D et al 2005 Int. J. Plasticity 21 493-512). The FLD models considered here are a finite element based approach, the well known Marciniak-Kuczynski model, the modified maximum force criterion according to Hora et al (1996 Proc. Numisheet'96 Conf. (Dearborn/Michigan) pp 252-6), Swift's diffuse (Swift H W 1952 J. Mech. Phys. Solids 1 1-18) and Hill's classical localized necking approach (Hill R 1952 J. Mech. Phys. Solids 1 19-30). The FLD of an AA5182-O aluminium sheet alloy has been determined experimentally in order to quantify the predictive capabilities of the models mentioned above.

Applying the reasoned action approach to understanding health protection and health risk behaviors.

Science.gov (United States)

Conner, Mark; McEachan, Rosemary; Lawton, Rebecca; Gardner, Peter

2017-12-01

The Reasoned Action Approach (RAA) developed out of the Theory of Reasoned Action and Theory of Planned Behavior but has not yet been widely applied to understanding health behaviors. The present research employed the RAA in a prospective design to test predictions of intention and action for groups of protection and risk behaviors separately in the same sample. To test the RAA for health protection and risk behaviors. Measures of RAA components plus past behavior were taken in relation to eight protection and six risk behaviors in 385 adults. Self-reported behavior was assessed one month later. Multi-level modelling showed instrumental attitude, experiential attitude, descriptive norms, capacity and past behavior were significant positive predictors of intentions to engage in protection or risk behaviors. Injunctive norms were only significant predictors of intention in protection behaviors. Autonomy was a significant positive predictor of intentions in protection behaviors and a negative predictor in risk behaviors (the latter relationship became non-significant when controlling for past behavior). Multi-level modelling showed that intention, capacity, and past behavior were significant positive predictors of action for both protection and risk behaviors. Experiential attitude and descriptive norm were additional significant positive predictors of risk behaviors. The RAA has utility in predicting both protection and risk health behaviors although the power of predictors may vary across these types of health behavior. Copyright © 2017 Elsevier Ltd. All rights reserved.

A Unified Approach to Modeling and Programming

DEFF Research Database (Denmark)

Madsen, Ole Lehrmann; Møller-Pedersen, Birger

2010-01-01

of this paper is to go back to the future and get inspiration from SIMULA and propose a unied approach. In addition to reintroducing the contributions of SIMULA and the Scandinavian approach to object-oriented programming, we do this by discussing a number of issues in modeling and programming and argue3 why we......SIMULA was a language for modeling and programming and provided a unied approach to modeling and programming in contrast to methodologies based on structured analysis and design. The current development seems to be going in the direction of separation of modeling and programming. The goal...

Technical note: Comparison of methane ebullition modelling approaches used in terrestrial wetland models

Science.gov (United States)

Peltola, Olli; Raivonen, Maarit; Li, Xuefei; Vesala, Timo

2018-02-01

Emission via bubbling, i.e. ebullition, is one of the main methane (CH4) emission pathways from wetlands to the atmosphere. Direct measurement of gas bubble formation, growth and release in the peat-water matrix is challenging and in consequence these processes are relatively unknown and are coarsely represented in current wetland CH4 emission models. In this study we aimed to evaluate three ebullition modelling approaches and their effect on model performance. This was achieved by implementing the three approaches in one process-based CH4 emission model. All the approaches were based on some kind of threshold: either on CH4 pore water concentration (ECT), pressure (EPT) or free-phase gas volume (EBG) threshold. The model was run using 4 years of data from a boreal sedge fen and the results were compared with eddy covariance measurements of CH4 fluxes.Modelled annual CH4 emissions were largely unaffected by the different ebullition modelling approaches; however, temporal variability in CH4 emissions varied an order of magnitude between the approaches. Hence the ebullition modelling approach drives the temporal variability in modelled CH4 emissions and therefore significantly impacts, for instance, high-frequency (daily scale) model comparison and calibration against measurements. The modelling approach based on the most recent knowledge of the ebullition process (volume threshold, EBG) agreed the best with the measured fluxes (R2 = 0.63) and hence produced the most reasonable results, although there was a scale mismatch between the measurements (ecosystem scale with heterogeneous ebullition locations) and model results (single horizontally homogeneous peat column). The approach should be favoured over the two other more widely used ebullition modelling approaches and researchers are encouraged to implement it into their CH4 emission models.

Integrated water flow model and modflow-farm process: A comparison of theory, approaches, and features of two integrated hydrologic models

Science.gov (United States)

Dogrul, Emin C.; Schmid, Wolfgang; Hanson, Randall T.; Kadir, Tariq; Chung, Francis

2016-01-01

Effective modeling of conjunctive use of surface and subsurface water resources requires simulation of land use-based root zone and surface flow processes as well as groundwater flows, streamflows, and their interactions. Recently, two computer models developed for this purpose, the Integrated Water Flow Model (IWFM) from the California Department of Water Resources and the MODFLOW with Farm Process (MF-FMP) from the US Geological Survey, have been applied to complex basins such as the Central Valley of California. As both IWFM and MFFMP are publicly available for download and can be applied to other basins, there is a need to objectively compare the main approaches and features used in both models. This paper compares the concepts, as well as the method and simulation features of each hydrologic model pertaining to groundwater, surface water, and landscape processes. The comparison is focused on the integrated simulation of water demand and supply, water use, and the flow between coupled hydrologic processes. The differences in the capabilities and features of these two models could affect the outcome and types of water resource problems that can be simulated.

Exploring a model-driven architecture (MDA) approach to health care information systems development.

Science.gov (United States)

Raghupathi, Wullianallur; Umar, Amjad

2008-05-01

To explore the potential of the model-driven architecture (MDA) in health care information systems development. An MDA is conceptualized and developed for a health clinic system to track patient information. A prototype of the MDA is implemented using an advanced MDA tool. The UML provides the underlying modeling support in the form of the class diagram. The PIM to PSM transformation rules are applied to generate the prototype application from the model. The result of the research is a complete MDA methodology to developing health care information systems. Additional insights gained include development of transformation rules and documentation of the challenges in the application of MDA to health care. Design guidelines for future MDA applications are described. The model has the potential for generalizability. The overall approach supports limited interoperability and portability. The research demonstrates the applicability of the MDA approach to health care information systems development. When properly implemented, it has the potential to overcome the challenges of platform (vendor) dependency, lack of open standards, interoperability, portability, scalability, and the high cost of implementation.

Physiology-based modelling approaches to characterize fish habitat suitability: Their usefulness and limitations

Science.gov (United States)

Teal, Lorna R.; Marras, Stefano; Peck, Myron A.; Domenici, Paolo

2018-02-01

empirical relationships which can be found consistently within physiological data across the animal kingdom. The advantages of the DEB models are that they make use of the generalities found in terms of animal physiology and can therefore be applied to species for which little data or empirical observations are available. In addition, the limitations as well as useful potential refinements of these and other physiology-based modelling approaches are discussed. Inclusion of the physiological response of various life stages and modelling the patterns of extreme events observed in nature are suggested for future work.

Exponential models applied to automated processing of radioimmunoassay standard curves

International Nuclear Information System (INIS)

Morin, J.F.; Savina, A.; Caroff, J.; Miossec, J.; Legendre, J.M.; Jacolot, G.; Morin, P.P.

1979-01-01

An improved computer processing is described for fitting of radio-immunological standard curves by means of an exponential model on a desk-top calculator. This method has been applied to a variety of radioassays and the results are in accordance with those obtained by more sophisticated models [fr

Liquid-drop model applied to heavy ions irradiation

International Nuclear Information System (INIS)

De Cicco, Hernan; Alurralde, Martin A.; Saint-Martin, Maria L. G.; Bernaola, Omar A.

1999-01-01

Liquid-drop model is used, previously applied in the study of radiation damage in metals, in an energy range not covered by molecular dynamics, in order to understand experimental data of particle tracks in an organic material (Makrofol E), which cannot be accurately described by the existing theoretical methods. The nuclear and electronic energy depositions are considered for each ion considered and the evolution of the thermal explosion is evaluated. The experimental observation of particle tracks in a region previously considered as 'prohibited' are justified. Although the model used has free parameters and some discrepancies with the experimental diametrical values exist, the agreement obtained is highly superior than that of other existing models. (author)

Surface-bounded growth modeling applied to human mandibles

DEFF Research Database (Denmark)

Andresen, Per Rønsholt

1999-01-01

This thesis presents mathematical and computational techniques for three dimensional growth modeling applied to human mandibles. The longitudinal shape changes make the mandible a complex bone. The teeth erupt and the condylar processes change direction, from pointing predominantly backward...... of the common features. 3.model the process that moves the matched points (growth modeling). A local shape feature called crest line has shown itself to be structurally stable on mandibles. Registration of crest lines (from different mandibles) results in a sparse deformation field, which must be interpolated...... old mandible based on the 3 month old scan. When using successively more recent scans as basis for the model the error drops to 2.0 mm for the 11 years old scan. Thus, it seems reasonable to assume that the mandibular growth is linear....

Testing adaptive toolbox models: a Bayesian hierarchical approach.

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Scheibehenne, Benjamin; Rieskamp, Jörg; Wagenmakers, Eric-Jan

2013-01-01

Many theories of human cognition postulate that people are equipped with a repertoire of strategies to solve the tasks they face. This theoretical framework of a cognitive toolbox provides a plausible account of intra- and interindividual differences in human behavior. Unfortunately, it is often unclear how to rigorously test the toolbox framework. How can a toolbox model be quantitatively specified? How can the number of toolbox strategies be limited to prevent uncontrolled strategy sprawl? How can a toolbox model be formally tested against alternative theories? The authors show how these challenges can be met by using Bayesian inference techniques. By means of parameter recovery simulations and the analysis of empirical data across a variety of domains (i.e., judgment and decision making, children's cognitive development, function learning, and perceptual categorization), the authors illustrate how Bayesian inference techniques allow toolbox models to be quantitatively specified, strategy sprawl to be contained, and toolbox models to be rigorously tested against competing theories. The authors demonstrate that their approach applies at the individual level but can also be generalized to the group level with hierarchical Bayesian procedures. The suggested Bayesian inference techniques represent a theoretical and methodological advancement for toolbox theories of cognition and behavior.

THE FAIRSHARES MODEL: AN ETHICAL APPROACH TO SOCIAL ENTERPRISE DEVELOPMENT?

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Rory James Ridley-Duff

2015-07-01

Full Text Available This paper is based on the keynote address to the 14th International Association of Public and Non-Profit Marketing (IAPNM conference. It explore the question "What impact do ethical values in the FairShares Model have on social entrepreneurial behaviour?" In the first part, three broad approaches to social enterprise are set out: co-operative and mutual enterprises (CMEs, social and responsible businesses (SRBs and charitable trading activities (CTAs. The ethics that guide each approach are examined to provide a conceptual framework for examining FairShares as a case study. In the second part, findings are scrutinised in terms of the ethical values and principles that are activated when FairShares is applied to practice. The paper contributes to knowledge by giving an example of the way OpenSource technology (Loomio has been used to translate 'espoused theories' into 'theories in use' to advance social enterprise development. The review of FairShares using the conceptual framework suggests there is a fourth approach based on multi-stakeholder co-operation to create 'associative democracy' in the workplace.

System Behavior Models: A Survey of Approaches

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2016-06-01

OF FIGURES Spiral Model .................................................................................................3 Figure 1. Approaches in... spiral model was chosen for researching and structuring this thesis, shown in Figure 1. This approach allowed multiple iterations of source material...applications and refining through iteration. 3 Spiral Model Figure 1. D. SCOPE The research is limited to a literature review, limited