Internal variability in a 1000-yr control simulation with the coupled climate model ECHO-G - I. Near-surface temperature, precipitation and mean sea level pressure.

Energy Technology Data Exchange (ETDEWEB)

Min, Seung-Ki; Hense, Andreas [Univ. of Bonn (Germany). Meteorological Inst.; Legutke, Stephanie [Max Planck Inst. for Meteorology, Hamburg (Germany); Kwon, Won-Tae [Meteorological Research Inst., Seoul (Korea, Republic of)

2005-08-01

The internal variability in a 1000-yr control simulation with the coupled atmosphere/ocean global climate model ECHO-G is analysed using near-surface temperature, precipitation and mean sea level pressure variables, and is compared with observations and other coupled climate model simulations. ECHO-G requires annual mean flux adjustments for heat and freshwater in order to simulate no significant climate drift for 1000 yr, but no flux adjustments for momentum. The ECHO-G control run captures well most aspects of the observed seasonal and annual climatology and of the interannual to decadal variability of the three variables. Model biases are very close to those in ECHAM4 (atmospheric component of ECHO-G) stand-alone integrations with prescribed observed sea surface temperature. A trend comparison between observed and modelled near-surface temperatures shows that the observed near-surface global warming is larger than internal variability produced by ECHO-G, supporting previous studies. The simulated global mean near-surface temperatures, however, show a 2-yr spectral peak which is linked with a strong biennial bias of energy in the El Nino Southern Oscillation signal. Consequently, the interannual variability (39 yr) is underestimated.

Response of ENSO amplitude to global warming in CESM large ensemble: uncertainty due to internal variability

Science.gov (United States)

Zheng, Xiao-Tong; Hui, Chang; Yeh, Sang-Wook

2018-06-01

El Niño-Southern Oscillation (ENSO) is the dominant mode of variability in the coupled ocean-atmospheric system. Future projections of ENSO change under global warming are highly uncertain among models. In this study, the effect of internal variability on ENSO amplitude change in future climate projections is investigated based on a 40-member ensemble from the Community Earth System Model Large Ensemble (CESM-LE) project. A large uncertainty is identified among ensemble members due to internal variability. The inter-member diversity is associated with a zonal dipole pattern of sea surface temperature (SST) change in the mean along the equator, which is similar to the second empirical orthogonal function (EOF) mode of tropical Pacific decadal variability (TPDV) in the unforced control simulation. The uncertainty in CESM-LE is comparable in magnitude to that among models of the Coupled Model Intercomparison Project phase 5 (CMIP5), suggesting the contribution of internal variability to the intermodel uncertainty in ENSO amplitude change. However, the causations between changes in ENSO amplitude and the mean state are distinct between CESM-LE and CMIP5 ensemble. The CESM-LE results indicate that a large ensemble of 15 members is needed to separate the relative contributions to ENSO amplitude change over the twenty-first century between forced response and internal variability.

Sensitivity of Climate Change Detection and Attribution to the Characterization of Internal Climate Variability

KAUST Repository

Imbers, Jara; Lopez, Ana; Huntingford, Chris; Allen, Myles

2014-01-01

The Intergovernmental Panel on Climate Change's (IPCC) "very likely" statement that anthropogenic emissions are affecting climate is based on a statistical detection and attribution methodology that strongly depends on the characterization of internal climate variability. In this paper, the authors test the robustness of this statement in the case of global mean surface air temperature, under different representations of such variability. The contributions of the different natural and anthropogenic forcings to the global mean surface air temperature response are computed using a box diffusion model. Representations of internal climate variability are explored using simple stochastic models that nevertheless span a representative range of plausible temporal autocorrelation structures, including the short-memory first-order autoregressive [AR(1)] process and the long-memory fractionally differencing process. The authors find that, independently of the representation chosen, the greenhouse gas signal remains statistically significant under the detection model employed in this paper. The results support the robustness of the IPCC detection and attribution statement for global mean temperature change under different characterizations of internal variability, but they also suggest that a wider variety of robustness tests, other than simple comparisons of residual variance, should be performed when dealing with other climate variables and/or different spatial scales. © 2014 American Meteorological Society.

Sensitivity of Climate Change Detection and Attribution to the Characterization of Internal Climate Variability

KAUST Repository

Imbers, Jara

2014-05-01

The Intergovernmental Panel on Climate Change\\'s (IPCC) "very likely" statement that anthropogenic emissions are affecting climate is based on a statistical detection and attribution methodology that strongly depends on the characterization of internal climate variability. In this paper, the authors test the robustness of this statement in the case of global mean surface air temperature, under different representations of such variability. The contributions of the different natural and anthropogenic forcings to the global mean surface air temperature response are computed using a box diffusion model. Representations of internal climate variability are explored using simple stochastic models that nevertheless span a representative range of plausible temporal autocorrelation structures, including the short-memory first-order autoregressive [AR(1)] process and the long-memory fractionally differencing process. The authors find that, independently of the representation chosen, the greenhouse gas signal remains statistically significant under the detection model employed in this paper. The results support the robustness of the IPCC detection and attribution statement for global mean temperature change under different characterizations of internal variability, but they also suggest that a wider variety of robustness tests, other than simple comparisons of residual variance, should be performed when dealing with other climate variables and/or different spatial scales. © 2014 American Meteorological Society.

Internal and external variability in regional simulations of the Iberian Peninsula climate over the last millennium

Directory of Open Access Journals (Sweden)

J. J. Gómez-Navarro

2012-01-01

Full Text Available In this study we analyse the role of internal variability in regional climate simulations through a comparison of two regional paleoclimate simulations for the last millennium. They share the same external forcings and model configuration, differing only in the initial condition used to run the driving global model simulation. A comparison of these simulations allows us to study the role of internal variability in climate models at regional scales, and how it affects the long-term evolution of climate variables such as temperature and precipitation. The results indicate that, although temperature is homogeneously sensitive to the effect of external forcings, the evolution of precipitation is more strongly governed by random unpredictable internal dynamics. There are, however, some areas where the role of internal variability is lower than expected, allowing precipitation to respond to the external forcings. In this respect, we explore the underlying physical mechanisms responsible for it. This study identifies areas, depending on the season, in which a direct comparison between model simulations of precipitation and climate reconstructions would be meaningful, but also other areas where good agreement between them should not be expected even if both are perfect.

On the role of "internal variability" on soil erosion assessment

Science.gov (United States)

Kim, Jongho; Ivanov, Valeriy; Fatichi, Simone

2017-04-01

Empirical data demonstrate that soil loss is highly non-unique with respect to meteorological or even runoff forcing and its frequency distributions exhibit heavy tails. However, all current erosion assessments do not describe the large associated uncertainties of temporal erosion variability and make unjustified assumptions by relying on central tendencies. Thus, the predictive skill of prognostic models and reliability of national-scale assessments have been repeatedly questioned. In this study, we attempt to reveal that the high variability in soil losses can be attributed to two sources: (1) 'external variability' referring to the uncertainties originating at macro-scale, such as climate, topography, and land use, which has been extensively studied; (2) 'geomorphic internal variability' referring to the micro-scale variations of pedologic properties (e.g., surface erodibility in soils with multi-sized particles), hydrologic properties (e.g., soil structure and degree of saturation), and hydraulic properties (e.g., surface roughness and surface topography). Using data and a physical hydraulic, hydrologic, and erosion and sediment transport model, we show that the geomorphic internal variability summarized by spatio-temporal variability in surface erodibility properties is a considerable source of uncertainty in erosion estimates and represents an overlooked but vital element of geomorphic response. The conclusion is that predictive frameworks of soil erosion should embed stochastic components together with deterministic assessments, if they do not want to largely underestimate uncertainty. Acknowledgement: This study was supported by the Basic Science Research Program of the National Research Foundation of Korea funded by the Ministry of Education (2016R1D1A1B03931886).

Electrochemical state and internal variables estimation using a reduced-order physics-based model of a lithium-ion cell and an extended Kalman filter

Energy Technology Data Exchange (ETDEWEB)

Stetzel, KD; Aldrich, LL; Trimboli, MS; Plett, GL

2015-03-15

This paper addresses the problem of estimating the present value of electrochemical internal variables in a lithium-ion cell in real time, using readily available measurements of cell voltage, current, and temperature. The variables that can be estimated include any desired set of reaction flux and solid and electrolyte potentials and concentrations at any set of one-dimensional spatial locations, in addition to more standard quantities such as state of charge. The method uses an extended Kalman filter along with a one-dimensional physics-based reduced-order model of cell dynamics. Simulations show excellent and robust predictions having dependable error bounds for most internal variables. (C) 2014 Elsevier B.V. All rights reserved.

Current and Future Decadal Trends in the Oceanic Carbon Uptake Are Dominated by Internal Variability

Science.gov (United States)

Li, Hongmei; Ilyina, Tatiana

2018-01-01

We investigate the internal decadal variability of the ocean carbon uptake using 100 ensemble simulations based on the Max Planck Institute Earth system model (MPI-ESM). We find that on decadal time scales, internal variability (ensemble spread) is as large as the forced temporal variability (ensemble mean), and the largest internal variability is found in major carbon sink regions, that is, the 50-65°S band of the Southern Ocean, the North Pacific, and the North Atlantic. The MPI-ESM ensemble produces both positive and negative 10 year trends in the ocean carbon uptake in agreement with observational estimates. Negative decadal trends are projected to occur in the future under RCP4.5 scenario. Due to the large internal variability, the Southern Ocean and the North Pacific require the most ensemble members (more than 53 and 46, respectively) to reproduce the forced decadal trends. This number increases up to 79 in future decades as CO2 emission trajectory changes.

A class of constitutive relations with internal variable derivatives: derivation from homogenization and initial value problem

International Nuclear Information System (INIS)

Andrieux, S.; Joussemet, M.; Lorentz, E.

1996-01-01

When they are subjected to excessive loads, some materials may exhibit a softening behaviour resulting from the deterioration of their mechanical properties. To idealize such behaviours, constitutive relations with softening are introduced, for which the size of the domain of reversibility in the stress-space decreases. These models feature a strain localization within the material, in agreement with experiments, but cannot predict the subsequent behaviour because they lead to shear bands the width of which is equal to zero, physically unacceptable and numerically troublesome. It has been proposed in the literature to overcome these difficulties by adding to the list of internal variable the spatial gradients of some of them. This procedure suffers from lack of firm methodological basis. Although, some quantitative justification have been advanced relying on some kind of microscopic analysis. Therefore, we propose to extend the classical (local) models by introducing the internal state variable first gradients. Given local model within the framework of standard generalized materials, consistent homogenization procedure is put forward to derive macroscopic free energy and dissipation potentials. The standard generalized character is preserved, with an extended set of state variables, containing not only the strain and the internal variables but also the internal variable derivatives. Nevertheless, when dealing with the whole structure, the independence between the new state variables is lost. We propose then to generalize the constitutive relations, leading to a new variational principle that ensures the Clausius-Duhem inequality at the structure scale. (authors)

Modelling internal migration in Kenya: an econometric analysis with limited data.

Science.gov (United States)

Barber, G M; Milne, W J

1988-09-01

"In this paper the determinants of internal migration in Kenya are analyzed on the basis of a human capital model. Explanatory variables included in the specification are both economic (wage rates and employment rates) and noneconomic (for example, population density and educational attainment). Also incorporated are variables which reflect intervening opportunities.... The econometric results show that destination variables are important determinants of internal migration, as is distance between the districts. Further, the variables for the intervening opportunities add significantly to the explanatory power of the model." excerpt

Kilometric Scale Modeling of the North West European Shelf Seas: Exploring the Spatial and Temporal Variability of Internal Tides

Science.gov (United States)

Guihou, K.; Polton, J.; Harle, J.; Wakelin, S.; O'Dea, E.; Holt, J.

2018-01-01

The North West European Shelf break acts as a barrier to the transport and exchange between the open ocean and the shelf seas. The strong spatial variability of these exchange processes is hard to fully explore using observations, and simulations generally are too coarse to simulate the fine-scale processes over the whole region. In this context, under the FASTNEt program, a new NEMO configuration of the North West European Shelf and Atlantic Margin at 1/60° (˜1.8 km) has been developed, with the objective to better understand and quantify the seasonal and interannual variability of shelf break processes. The capability of this configuration to reproduce the seasonal cycle in SST, the barotropic tide, and fine-resolution temperature profiles is assessed against a basin-scale (1/12°, ˜9 km) configuration and a standard regional configuration (7 km resolution). The seasonal cycle is well reproduced in all configurations though the fine-resolution allows the simulation of smaller scale processes. Time series of temperature at various locations on the shelf show the presence of internal waves with a strong spatiotemporal variability. Spectral analysis of the internal waves reveals peaks at the diurnal, semidiurnal, inertial, and quarter-diurnal bands, which are only realistically reproduced in the new configuration. Tidally induced pycnocline variability is diagnosed in the model and shown to vary with the spring neap cycle with mean displacement amplitudes in excess of 2 m for 30% of the stratified domain. With sufficiently fine resolution, internal tides are shown to be generated at numerous bathymetric features resulting in a complex pycnocline displacement superposition pattern.

Uncertainty in Indian Ocean Dipole response to global warming: the role of internal variability

Science.gov (United States)

Hui, Chang; Zheng, Xiao-Tong

2018-01-01

The Indian Ocean Dipole (IOD) is one of the leading modes of interannual sea surface temperature (SST) variability in the tropical Indian Ocean (TIO). The response of IOD to global warming is quite uncertain in climate model projections. In this study, the uncertainty in IOD change under global warming, especially that resulting from internal variability, is investigated based on the community earth system model large ensemble (CESM-LE). For the IOD amplitude change, the inter-member uncertainty in CESM-LE is about 50% of the intermodel uncertainty in the phase 5 of the coupled model intercomparison project (CMIP5) multimodel ensemble, indicating the important role of internal variability in IOD future projection. In CESM-LE, both the ensemble mean and spread in mean SST warming show a zonal positive IOD-like (pIOD-like) pattern in the TIO. This pIOD-like mean warming regulates ocean-atmospheric feedbacks of the interannual IOD mode, and weakens the skewness of the interannual variability. However, as the changes in oceanic and atmospheric feedbacks counteract each other, the inter-member variability in IOD amplitude change is not correlated with that of the mean state change. Instead, the ensemble spread in IOD amplitude change is correlated with that in ENSO amplitude change in CESM-LE, reflecting the close inter-basin relationship between the tropical Pacific and Indian Ocean in this model.

Internally generated natural variability of global-mean temperatures

International Nuclear Information System (INIS)

Wigley, T.M.L.; Raper, S.C.B.

1990-01-01

Quantitative frequency-domain and time-domain estimates are made of an important aspect of natural variability of global-mean temperatures, namely, passive internal variability resulting from the modulation of atmospheric variability by the ocean. The results are derived using an upwelling-diffusion, energy-balance climate model. In the frequency domain, analytical spectral results show a transition from a high-frequency region in which the response is determined by the mixed-layer heat capacity and is independent of the climate sensitivity (time scales less than around 10 years), to a low-frequency region in which the response depends only on the climate sensitivity. In the former region the spectral power is proportional to f -2 , where f is the frequency, while in the latter the power is independent of frequency. The range of validity of these results depends on the components of the climate system that are included in the model. In this case these restrict the low-frequency results to time scales less than about 1,000 years. A qualitative extrapolation is presented in an attempt to explain the observed low-frequency power spectra from deep-sea-core δ 18 O time series. The spectral results are also used to estimate the effective heat capacity of the ocean as a function of frequency. At low frequencies, this can range up to 50 times greater than the heat capacity of the mixed layer. Results in the time domain are obtained by solving the model equations numerically

Cutting-in control of the variable speed constant frequency wind power generator based on internal model controller

Energy Technology Data Exchange (ETDEWEB)

Guo Jindong; Xu Honghua; Zhao Dongli [Inst. of Electrical Engineering, CAS, BJ (China)

2008-07-01

The no-impact-current cutting-in-network control is the key of variable speed constant frequency (VSCF) wind power control system. Based on the stator flux linkage oriented control theory of doubly fed induction generator (DFIG), the field-oriented vector control technique and the internal model controller (IMC) are transplanted into the voltage control of DFIG and a novel cutting-in control strategy is obtained. The strategy does not need the exact inductor generator model, and has perfect performance without overshoot. The structure of the controller is simple, and the only parameter to be adjusted is directly related to system performance, so the strategy is easy to realize. Finally the strategy is studied by simulation using Matlab, the results of the simulation show that the control strategy can effectively control the stator voltage. (orig.)

A Non-Gaussian Spatial Generalized Linear Latent Variable Model

KAUST Repository

Irincheeva, Irina; Cantoni, Eva; Genton, Marc G.

2012-01-01

We consider a spatial generalized linear latent variable model with and without normality distributional assumption on the latent variables. When the latent variables are assumed to be multivariate normal, we apply a Laplace approximation. To relax the assumption of marginal normality in favor of a mixture of normals, we construct a multivariate density with Gaussian spatial dependence and given multivariate margins. We use the pairwise likelihood to estimate the corresponding spatial generalized linear latent variable model. The properties of the resulting estimators are explored by simulations. In the analysis of an air pollution data set the proposed methodology uncovers weather conditions to be a more important source of variability than air pollution in explaining all the causes of non-accidental mortality excluding accidents. © 2012 International Biometric Society.

A Non-Gaussian Spatial Generalized Linear Latent Variable Model

KAUST Repository

Irincheeva, Irina

2012-08-03

We consider a spatial generalized linear latent variable model with and without normality distributional assumption on the latent variables. When the latent variables are assumed to be multivariate normal, we apply a Laplace approximation. To relax the assumption of marginal normality in favor of a mixture of normals, we construct a multivariate density with Gaussian spatial dependence and given multivariate margins. We use the pairwise likelihood to estimate the corresponding spatial generalized linear latent variable model. The properties of the resulting estimators are explored by simulations. In the analysis of an air pollution data set the proposed methodology uncovers weather conditions to be a more important source of variability than air pollution in explaining all the causes of non-accidental mortality excluding accidents. © 2012 International Biometric Society.

Rapid grounding line migration induced by internal variability of a marine-terminating ice stream

Science.gov (United States)

Robel, A.; Schoof, C.; Tziperman, E.

2013-12-01

Numerous studies have found significant variability in the velocity of ice streams to be a prominent feature of geomorphologic records in the Siple Coast (Catania et al. 2012) and other regions in West Antarctica (Dowdeswell et al. 2008). Observations indicate that grounding line position is strongly influenced by ice stream variability, producing rapid grounding line migration in the recent past (Catania et al. 2006) and the modern (Joughin & Tulaczyk 2002). We analyze the interaction of grounding line mass flux and position in a marine-terminating ice stream using a stretch-coordinate flowline model. This model is based on that described in Schoof (2007), with a mesh refined near the grounding line to ensure accurate resolution of the mechanical transition zone. Here we have added lateral shear stress (Dupont & Alley 2005) and an undrained plastic bed (Tulaczyk et al. 2000). The parameter dependence of ice stream variability seen in this model compares favorably to both simpler (Robel et al. 2013) and more complex (van der Wel et al. 2013) models, though with some key differences. We find that thermally-induced internal ice stream variability can cause very rapid grounding line migration even in the absence of retrograde bed slopes or external forcing. Activation waves propagate along the ice stream length and trigger periods of rapid grounding line migration. We compare the behavior of the grounding line due to internal ice stream variability to changes triggered externally at the grounding line such as the rapid disintegration of buttressing ice shelves. Implications for Heinrich events and the Marine Ice Sheet Instability are discussed.

Local-scale changes in mean and heavy precipitation in Western Europe, climate change or internal variability?

Science.gov (United States)

Aalbers, Emma E.; Lenderink, Geert; van Meijgaard, Erik; van den Hurk, Bart J. J. M.

2017-09-01

High-resolution climate information provided by e.g. regional climate models (RCMs) is valuable for exploring the changing weather under global warming, and assessing the local impact of climate change. While there is generally more confidence in the representativeness of simulated processes at higher resolutions, internal variability of the climate system—`noise', intrinsic to the chaotic nature of atmospheric and oceanic processes—is larger at smaller spatial scales as well, limiting the predictability of the climate signal. To quantify the internal variability and robustly estimate the climate signal, large initial-condition ensembles of climate simulations conducted with a single model provide essential information. We analyze a regional downscaling of a 16-member initial-condition ensemble over western Europe and the Alps at 0.11° resolution, similar to the highest resolution EURO-CORDEX simulations. We examine the strength of the forced climate response (signal) in mean and extreme daily precipitation with respect to noise due to internal variability, and find robust small-scale geographical features in the forced response, indicating regional differences in changes in the probability of events. However, individual ensemble members provide only limited information on the forced climate response, even for high levels of global warming. Although the results are based on a single RCM-GCM chain, we believe that they have general value in providing insight in the fraction of the uncertainty in high-resolution climate information that is irreducible, and can assist in the correct interpretation of fine-scale information in multi-model ensembles in terms of a forced response and noise due to internal variability.

Local-scale changes in mean and heavy precipitation in Western Europe, climate change or internal variability?

Science.gov (United States)

Aalbers, Emma E.; Lenderink, Geert; van Meijgaard, Erik; van den Hurk, Bart J. J. M.

2018-06-01

High-resolution climate information provided by e.g. regional climate models (RCMs) is valuable for exploring the changing weather under global warming, and assessing the local impact of climate change. While there is generally more confidence in the representativeness of simulated processes at higher resolutions, internal variability of the climate system—`noise', intrinsic to the chaotic nature of atmospheric and oceanic processes—is larger at smaller spatial scales as well, limiting the predictability of the climate signal. To quantify the internal variability and robustly estimate the climate signal, large initial-condition ensembles of climate simulations conducted with a single model provide essential information. We analyze a regional downscaling of a 16-member initial-condition ensemble over western Europe and the Alps at 0.11° resolution, similar to the highest resolution EURO-CORDEX simulations. We examine the strength of the forced climate response (signal) in mean and extreme daily precipitation with respect to noise due to internal variability, and find robust small-scale geographical features in the forced response, indicating regional differences in changes in the probability of events. However, individual ensemble members provide only limited information on the forced climate response, even for high levels of global warming. Although the results are based on a single RCM-GCM chain, we believe that they have general value in providing insight in the fraction of the uncertainty in high-resolution climate information that is irreducible, and can assist in the correct interpretation of fine-scale information in multi-model ensembles in terms of a forced response and noise due to internal variability.

Towards multi-resolution global climate modeling with ECHAM6-FESOM. Part II: climate variability

Science.gov (United States)

Rackow, T.; Goessling, H. F.; Jung, T.; Sidorenko, D.; Semmler, T.; Barbi, D.; Handorf, D.

2018-04-01

This study forms part II of two papers describing ECHAM6-FESOM, a newly established global climate model with a unique multi-resolution sea ice-ocean component. While part I deals with the model description and the mean climate state, here we examine the internal climate variability of the model under constant present-day (1990) conditions. We (1) assess the internal variations in the model in terms of objective variability performance indices, (2) analyze variations in global mean surface temperature and put them in context to variations in the observed record, with particular emphasis on the recent warming slowdown, (3) analyze and validate the most common atmospheric and oceanic variability patterns, (4) diagnose the potential predictability of various climate indices, and (5) put the multi-resolution approach to the test by comparing two setups that differ only in oceanic resolution in the equatorial belt, where one ocean mesh keeps the coarse 1° resolution applied in the adjacent open-ocean regions and the other mesh is gradually refined to 0.25°. Objective variability performance indices show that, in the considered setups, ECHAM6-FESOM performs overall favourably compared to five well-established climate models. Internal variations of the global mean surface temperature in the model are consistent with observed fluctuations and suggest that the recent warming slowdown can be explained as a once-in-one-hundred-years event caused by internal climate variability; periods of strong cooling in the model (`hiatus' analogs) are mainly associated with ENSO-related variability and to a lesser degree also to PDO shifts, with the AMO playing a minor role. Common atmospheric and oceanic variability patterns are simulated largely consistent with their real counterparts. Typical deficits also found in other models at similar resolutions remain, in particular too weak non-seasonal variability of SSTs over large parts of the ocean and episodic periods of almost absent

International Nuclear Model personal computer (PCINM): Model documentation

International Nuclear Information System (INIS)

1992-08-01

The International Nuclear Model (INM) was developed to assist the Energy Information Administration (EIA), U.S. Department of Energy (DOE) in producing worldwide projections of electricity generation, fuel cycle requirements, capacities, and spent fuel discharges from commercial nuclear reactors. The original INM was developed, maintained, and operated on a mainframe computer system. In spring 1992, a streamlined version of INM was created for use on a microcomputer utilizing CLIPPER and PCSAS software. This new version is known as PCINM. This documentation is based on the new PCINM version. This document is designed to satisfy the requirements of several categories of users of the PCINM system including technical analysts, theoretical modelers, and industry observers. This document assumes the reader is familiar with the nuclear fuel cycle and each of its components. This model documentation contains four chapters and seven appendices. Chapter Two presents the model overview containing the PCINM structure and process flow, the areas for which projections are made, and input data and output reports. Chapter Three presents the model technical specifications showing all model equations, algorithms, and units of measure. Chapter Four presents an overview of all parameters, variables, and assumptions used in PCINM. The appendices present the following detailed information: variable and parameter listings, variable and equation cross reference tables, source code listings, file layouts, sample report outputs, and model run procedures. 2 figs

Homogenization of linear viscoelastic three phase media: internal variable formulation versus full-field computation

International Nuclear Information System (INIS)

Blanc, V.; Barbie, L.; Masson, R.

2011-01-01

Homogenization of linear viscoelastic heterogeneous media is here extended from two phase inclusion-matrix media to three phase inclusion-matrix media. Each phase obeying to a compressible Maxwellian behaviour, this analytic method leads to an equivalent elastic homogenization problem in the Laplace-Carson space. For some particular microstructures, such as the Hashin composite sphere assemblage, an exact solution is obtained. The inversion of the Laplace-Carson transforms of the overall stress-strain behaviour gives in such cases an internal variable formulation. As expected, the number of these internal variables and their evolution laws are modified to take into account the third phase. Moreover, evolution laws of averaged stresses and strains per phase can still be derived for three phase media. Results of this model are compared to full fields computations of representative volume elements using finite element method, for various concentrations and sizes of inclusion. Relaxation and creep test cases are performed in order to compare predictions of the effective response. The internal variable formulation is shown to yield accurate prediction in both cases. (authors)

The mechanism behind internally generated centennial-to-millennial scale climate variability in an earth system model of intermediate complexity

Directory of Open Access Journals (Sweden)

T. Friedrich

2010-08-01

Full Text Available The mechanism triggering centennial-to-millennial-scale variability of the Atlantic Meridional Overturning Circulation (AMOC in the earth system model of intermediate complexity LOVECLIM is investigated. It is found that for several climate boundary conditions such as low obliquity values (~22.1° or LGM-albedo, internally generated centennial-to-millennial-scale variability occurs in the North Atlantic region. Stochastic excitations of the density-driven overturning circulation in the Nordic Seas can create regional sea-ice anomalies and a subsequent reorganization of the atmospheric circulation. The resulting remote atmospheric anomalies over the Hudson Bay can release freshwater pulses into the Labrador Sea and significantly increase snow fall in this region leading to a subsequent reduction of convective activity. The millennial-scale AMOC oscillations disappear if LGM bathymetry (with closed Hudson Bay is prescribed or if freshwater pulses are suppressed artificially. Furthermore, our study documents the process of the AMOC recovery as well as the global marine and terrestrial carbon cycle response to centennial-to-millennial-scale AMOC variability.

Internal variability of a dynamically downscaled climate over North America

Energy Technology Data Exchange (ETDEWEB)

Wang, Jiali; Bessac, Julie; Kotamarthi, Rao; Constantinescu, Emil; Drewniak, Beth

2017-09-08

This study investigates the internal variability (IV) of a regional climate model, and considers the impacts of horizontal resolution and spectral nudging on the IV. A 16-member simulation ensemble was conducted using the Weather Research Forecasting model for three model configurations. Ensemble members included simulations at spatial resolutions of 50 km and 12 km without spectral nudging and simulations at a spatial resolution of 12 km with spectral nudging. All the simulations were generated over the same domain, which covered much of North America. The degree of IV was measured as the spread between the individual members of the ensemble during the integration period. The IV of the 12 km simulation with spectral nudging was also compared with a future climate change simulation projected by the same model configuration. The variables investigated focus on precipitation and near-surface air temperature. While the IVs show a clear annual cycle with larger values in summer and smaller values in winter, the seasonal IV is smaller for a 50-km spatial resolution than for a 12-km resolution when nudging is not applied. Applying a nudging technique to the 12-km simulation reduces the IV by a factor of two, and produces smaller IV than the simulation at 50 km without nudging. Applying a nudging technique also changes the geographic distributions of IV in all examined variables. The IV is much smaller than the inter-annual variability at seasonal scales for regionally averaged temperature and precipitation. The IV is also smaller than the projected changes in air-temperature for the mid- and late 21st century. However, the IV is larger than the projected changes in precipitation for the mid- and late 21st century.

Internal variability of a dynamically downscaled climate over North America

Energy Technology Data Exchange (ETDEWEB)

Wang, Jiali; Bessac, Julie; Kotamarthi, Rao; Constantinescu, Emil; Drewniak, Beth

2017-09-08

This study investigates the internal variability (IV) of a regional climate model, and considers the impacts of horizontal resolution and spectral nudging on the IV. A 16-member simulation ensemble was conducted using the Weather Research Forecasting model for three model configurations. Ensemble members included simulations at spatial resolutions of 50 and 12 km without spectral nudging and simulations at a spatial resolution of 12 km with spectral nudging. All the simulations were generated over the same domain, which covered much of North America. The degree of IV was measured as the spread between the individual members of the ensemble during the integration period. The IV of the 12 km simulation with spectral nudging was also compared with a future climate change simulation projected by the same model configuration. The variables investigated focus on precipitation and near-surface air temperature. While the IVs show a clear annual cycle with larger values in summer and smaller values in winter, the seasonal IV is smaller for a 50-km spatial resolution than for a 12-km resolution when nudging is not applied. Applying a nudging technique to the 12-km simulation reduces the IV by a factor of two, and produces smaller IV than the simulation at 50 km without nudging. Applying a nudging technique also changes the geographic distributions of IV in all examined variables. The IV is much smaller than the inter-annual variability at seasonal scales for regionally averaged temperature and precipitation. The IV is also smaller than the projected changes in air-temperature for the mid- and late twenty-first century. However, the IV is larger than the projected changes in precipitation for the mid- and late twenty-first century.

Internal variability of a dynamically downscaled climate over North America

Science.gov (United States)

Wang, Jiali; Bessac, Julie; Kotamarthi, Rao; Constantinescu, Emil; Drewniak, Beth

2017-09-01

This study investigates the internal variability (IV) of a regional climate model, and considers the impacts of horizontal resolution and spectral nudging on the IV. A 16-member simulation ensemble was conducted using the Weather Research Forecasting model for three model configurations. Ensemble members included simulations at spatial resolutions of 50 and 12 km without spectral nudging and simulations at a spatial resolution of 12 km with spectral nudging. All the simulations were generated over the same domain, which covered much of North America. The degree of IV was measured as the spread between the individual members of the ensemble during the integration period. The IV of the 12 km simulation with spectral nudging was also compared with a future climate change simulation projected by the same model configuration. The variables investigated focus on precipitation and near-surface air temperature. While the IVs show a clear annual cycle with larger values in summer and smaller values in winter, the seasonal IV is smaller for a 50-km spatial resolution than for a 12-km resolution when nudging is not applied. Applying a nudging technique to the 12-km simulation reduces the IV by a factor of two, and produces smaller IV than the simulation at 50 km without nudging. Applying a nudging technique also changes the geographic distributions of IV in all examined variables. The IV is much smaller than the inter-annual variability at seasonal scales for regionally averaged temperature and precipitation. The IV is also smaller than the projected changes in air-temperature for the mid- and late twenty-first century. However, the IV is larger than the projected changes in precipitation for the mid- and late twenty-first century.

Internal variability of a dynamically downscaled climate over North America

Science.gov (United States)

Wang, Jiali; Bessac, Julie; Kotamarthi, Rao; Constantinescu, Emil; Drewniak, Beth

2018-06-01

This study investigates the internal variability (IV) of a regional climate model, and considers the impacts of horizontal resolution and spectral nudging on the IV. A 16-member simulation ensemble was conducted using the Weather Research Forecasting model for three model configurations. Ensemble members included simulations at spatial resolutions of 50 and 12 km without spectral nudging and simulations at a spatial resolution of 12 km with spectral nudging. All the simulations were generated over the same domain, which covered much of North America. The degree of IV was measured as the spread between the individual members of the ensemble during the integration period. The IV of the 12 km simulation with spectral nudging was also compared with a future climate change simulation projected by the same model configuration. The variables investigated focus on precipitation and near-surface air temperature. While the IVs show a clear annual cycle with larger values in summer and smaller values in winter, the seasonal IV is smaller for a 50-km spatial resolution than for a 12-km resolution when nudging is not applied. Applying a nudging technique to the 12-km simulation reduces the IV by a factor of two, and produces smaller IV than the simulation at 50 km without nudging. Applying a nudging technique also changes the geographic distributions of IV in all examined variables. The IV is much smaller than the inter-annual variability at seasonal scales for regionally averaged temperature and precipitation. The IV is also smaller than the projected changes in air-temperature for the mid- and late twenty-first century. However, the IV is larger than the projected changes in precipitation for the mid- and late twenty-first century.

Internal and forced eddy variability in the Labrador Sea

Science.gov (United States)

Bracco, A.; Luo, H.; Zhong, Y.; Lilly, J.

2009-04-01

Water mass transformation in the Labrador Sea, widely believed to be one of the key regions in the Atlantic Meridional Overturning Circulation (AMOC), now appears to be strongly impacted by vortex dynamics of the unstable boundary current. Large interannual variations in both eddy shedding and buoyancy transport from the boundary current have been observed but not explained, and are apparently sensitive to the state of the inflowing current. Heat and salinity fluxes associated with the eddies drive ventilation changes not accounted for by changes in local surface forcing, particularly during occasional years of extreme eddy activity, and constitute a predominant source of "internal" oceanic variability. The nature of this variable eddy-driven restratification is one of the outstanding questions along the northern transformation pathway. Here we investigate the eddy generation mechanism and the associated buoyancy fluxes by combining realistic and idealized numerical modeling, data analysis, and theory. Theory, supported by idealized experiments, provides criteria to test hypotheses as to the vortex formation process (by baroclinic instability linked to the bottom topography). Ensembles of numerical experiments with a high-resolution regional model (ROMS) allow for quantifying the sensitivity of eddy generation and property transport to variations in local and external forcing parameters. For the first time, we reproduce with a numerical simulation the observed interannual variability in the eddy kinetic energy in the convective region of the Labrador Basin and along the West Greenland Current.

Internal state variable plasticity-damage modeling of AISI 4140 steel including microstructure-property relations: temperature and strain rate effects

Science.gov (United States)

Nacif el Alaoui, Reda

Mechanical structure-property relations have been quantified for AISI 4140 steel. under different strain rates and temperatures. The structure-property relations were used. to calibrate a microstructure-based internal state variable plasticity-damage model for. monotonic tension, compression and torsion plasticity, as well as damage evolution. Strong stress state and temperature dependences were observed for the AISI 4140 steel. Tension tests on three different notched Bridgman specimens were undertaken to study. the damage-triaxiality dependence for model validation purposes. Fracture surface. analysis was performed using Scanning Electron Microscopy (SEM) to quantify the void. nucleation and void sizes in the different specimens. The stress-strain behavior exhibited. a fairly large applied stress state (tension, compression dependence, and torsion), a. moderate temperature dependence, and a relatively small strain rate dependence.

Variable importance in latent variable regression models

NARCIS (Netherlands)

Kvalheim, O.M.; Arneberg, R.; Bleie, O.; Rajalahti, T.; Smilde, A.K.; Westerhuis, J.A.

2014-01-01

The quality and practical usefulness of a regression model are a function of both interpretability and prediction performance. This work presents some new graphical tools for improved interpretation of latent variable regression models that can also assist in improved algorithms for variable

On the Temporal Variability of Low-Mode Internal Tides in the Deep Ocean

Science.gov (United States)

Ray, Richard D.; Zaron, E. D.

2010-01-01

In situ measurements of internal tides are typically characterized by high temporal variability, with strong dependence on stratification, mesoscale eddies, and background currents commonly observed. Thus, it is surprising to find phase-locked internal tides detectable by satellite altimetry. An important question is how much tidal variability is missed by altimetry. We address this question in several ways. We subset the altimetry by season and find only very small changes -- an important exception being internal tides in the South China Sea where we observe strong seasonal dependence. A wavenumber-domain analysis confirms that throughout most of the global ocean there is little temporal variability in altimetric internal-tide signals, at least in the first baroclinic mode, which is the mode that dominates surface elevation. The analysis shows higher order modes to be significantly more variable. The results of this study have important practical implications for the anticipated SWOT wide-swath altimeter mission, for which removal of internal tide signals is critical for observing non-tidal submesoscale phenomena.

Oscillating shells: A model for a variable cosmic object

OpenAIRE

Nunez, Dario

1997-01-01

A model for a possible variable cosmic object is presented. The model consists of a massive shell surrounding a compact object. The gravitational and self-gravitational forces tend to collapse the shell, but the internal tangential stresses oppose the collapse. The combined action of the two types of forces is studied and several cases are presented. In particular, we investigate the spherically symmetric case in which the shell oscillates radially around a central compact object.

The Matrix model, a driven state variables approach to non-equilibrium thermodynamics

NARCIS (Netherlands)

Jongschaap, R.J.J.

2001-01-01

One of the new approaches in non-equilibrium thermodynamics is the so-called matrix model of Jongschaap. In this paper some features of this model are discussed. We indicate the differences with the more common approach based upon internal variables and the more sophisticated Hamiltonian and GENERIC

Changes in Southern Hemisphere circulation variability in climate change modelling experiments

International Nuclear Information System (INIS)

Grainger, Simon; Frederiksen, Carsten; Zheng, Xiaogu

2007-01-01

Full text: The seasonal mean of a climate variable can be considered as a statistical random variable, consisting of a signal and noise components (Madden 1976). The noise component consists of internal intraseasonal variability, and is not predictable on time-scales of a season or more ahead. The signal consists of slowly varying external and internal variability, and is potentially predictable on seasonal time-scales. The method of Zheng and Frederiksen (2004) has been applied to monthly time series of 500hPa Geopotential height from models submitted to the Coupled Model Intercomparison Project (CMIP3) experiment to obtain covariance matrices of the intraseasonal and slow components of covariability for summer and winter. The Empirical Orthogonal Functions (EOFs) of the intraseasonal and slow covariance matrices for the second half of the 20th century are compared with those observed by Frederiksen and Zheng (2007). The leading EOF in summer and winter for both the intraseasonal and slow components of covariability is the Southern Annular Mode (see, e.g. Kiladis and Mo 1998). This is generally reproduced by the CMIP3 models, although with different variance amounts. The observed secondary intraseasonal covariability modes of wave 4 patterns in summer and wave 3 or blocking in winter are also generally seen in the models, although the actual spatial pattern is different. For the slow covariabilty, the models are less successful in reproducing the two observed ENSO modes, with generally only one of them being represented among the leading EOFs. However, most models reproduce the observed South Pacific wave pattern. The intraseasonal and slow covariances matrices of 500hPa geopotential height under three climate change scenarios are also analysed and compared with those found for the second half of the 20th century. Through aggregating the results from a number of CMIP3 models, a consensus estimate of the changes in Southern Hemisphere variability, and their

Does internal climate variability overwhelm climate change signals in streamflow? The upper Po and Rhone basin case studies

International Nuclear Information System (INIS)

Fatichi, S.; Rimkus, S.; Burlando, P.; Bordoy, R.

2014-01-01

Projections of climate change effects in streamflow are increasingly required to plan water management strategies. These projections are however largely uncertain due to the spread among climate model realizations, internal climate variability, and difficulties in transferring climate model results at the spatial and temporal scales required by catchment hydrology. A combination of a stochastic downscaling methodology and distributed hydrological modeling was used in the ACQWA project to provide projections of future streamflow (up to year 2050) for the upper Po and Rhone basins, respectively located in northern Italy and south-western Switzerland. Results suggest that internal (stochastic) climate variability is a fundamental source of uncertainty, typically comparable or larger than the projected climate change signal. Therefore, climate change effects in streamflow mean, frequency, and seasonality can be masked by natural climatic fluctuations in large parts of the analyzed regions. An exception to the overwhelming role of stochastic variability is represented by high elevation catchments fed by glaciers where streamflow is expected to be considerably reduced due to glacier retreat, with consequences appreciable in the main downstream rivers in August and September. Simulations also identify regions (west upper Rhone and Toce, Ticino river basins) where a strong precipitation increase in the February to April period projects streamflow beyond the range of natural climate variability during the melting season. This study emphasizes the importance of including internal climate variability in climate change analyses, especially when compared to the limited uncertainty that would be accounted for by few deterministic projections. The presented results could be useful in guiding more specific impact studies, although design or management decisions should be better based on reliability and vulnerability criteria as suggested by recent literature. - Highlights: �

Does internal climate variability overwhelm climate change signals in streamflow? The upper Po and Rhone basin case studies

Energy Technology Data Exchange (ETDEWEB)

Fatichi, S., E-mail: simone.fatichi@ifu.baug.ethz.ch; Rimkus, S.; Burlando, P.; Bordoy, R.

2014-09-15

Projections of climate change effects in streamflow are increasingly required to plan water management strategies. These projections are however largely uncertain due to the spread among climate model realizations, internal climate variability, and difficulties in transferring climate model results at the spatial and temporal scales required by catchment hydrology. A combination of a stochastic downscaling methodology and distributed hydrological modeling was used in the ACQWA project to provide projections of future streamflow (up to year 2050) for the upper Po and Rhone basins, respectively located in northern Italy and south-western Switzerland. Results suggest that internal (stochastic) climate variability is a fundamental source of uncertainty, typically comparable or larger than the projected climate change signal. Therefore, climate change effects in streamflow mean, frequency, and seasonality can be masked by natural climatic fluctuations in large parts of the analyzed regions. An exception to the overwhelming role of stochastic variability is represented by high elevation catchments fed by glaciers where streamflow is expected to be considerably reduced due to glacier retreat, with consequences appreciable in the main downstream rivers in August and September. Simulations also identify regions (west upper Rhone and Toce, Ticino river basins) where a strong precipitation increase in the February to April period projects streamflow beyond the range of natural climate variability during the melting season. This study emphasizes the importance of including internal climate variability in climate change analyses, especially when compared to the limited uncertainty that would be accounted for by few deterministic projections. The presented results could be useful in guiding more specific impact studies, although design or management decisions should be better based on reliability and vulnerability criteria as suggested by recent literature. - Highlights: �

Singular vector decomposition of the internal variability of the Canadian Regional Climate Model

Energy Technology Data Exchange (ETDEWEB)

Diaconescu, Emilia Paula; Laprise, Rene [University of Quebec at Montreal (UQAM), Department of Earth and Atmospheric Sciences, Canadian Network for Regional Climate Modelling and Diagnostics, P.O. Box 8888, Montreal, QC (Canada); Centre ESCER (Etude et Simulation du Climat a l' Echelle Regionale), Montreal, QC (Canada); Zadra, Ayrton [University of Quebec at Montreal (UQAM), Department of Earth and Atmospheric Sciences, Canadian Network for Regional Climate Modelling and Diagnostics, P.O. Box 8888, Montreal, QC (Canada); Environment Canada, Meteorological Research Division, Montreal, QC (Canada); Centre ESCER (Etude et Simulation du Climat a l' Echelle Regionale), Montreal, QC (Canada)

2012-03-15

Previous studies have shown that Regional Climate Models (RCM) internal variability (IV) fluctuates in time depending on synoptic events. This study focuses on the physical understanding of episodes with rapid growth of IV. An ensemble of 21 simulations, differing only in their initial conditions, was run over North America using version 5 of the Canadian RCM (CRCM). The IV is quantified in terms of energy of CRCM perturbations with respect to a reference simulation. The working hypothesis is that IV is arising through rapidly growing perturbations developed in dynamically unstable regions. If indeed IV is triggered by the growth of unstable perturbations, a large proportion of the CRCM perturbations must project onto the most unstable singular vectors (SVs). A set of ten SVs was computed to identify the orthogonal set of perturbations that provide the maximum growth with respect to the dry total-energy norm during the course of the CRCM ensemble of simulations. CRCM perturbations were then projected onto the subspace of SVs. The analysis of one episode of rapid growth of IV is presented in detail. It is shown that a large part of the IV growth is explained by initially small-amplitude unstable perturbations represented by the ten leading SVs, the SV subspace accounting for over 70% of the CRCM IV growth in 36 h. The projection on the leading SV at final time is greater than the projection on the remaining SVs and there is a high similarity between the CRCM perturbations and the leading SV after 24-36 h tangent-linear model integration. The vertical structure of perturbations revealed that the baroclinic conversion is the dominant process in IV growth for this particular episode. (orig.)

Does internal climate variability overwhelm climate change signals in streamflow? The upper Po and Rhone basin case studies.

Science.gov (United States)

Fatichi, S; Rimkus, S; Burlando, P; Bordoy, R

2014-09-15

Projections of climate change effects in streamflow are increasingly required to plan water management strategies. These projections are however largely uncertain due to the spread among climate model realizations, internal climate variability, and difficulties in transferring climate model results at the spatial and temporal scales required by catchment hydrology. A combination of a stochastic downscaling methodology and distributed hydrological modeling was used in the ACQWA project to provide projections of future streamflow (up to year 2050) for the upper Po and Rhone basins, respectively located in northern Italy and south-western Switzerland. Results suggest that internal (stochastic) climate variability is a fundamental source of uncertainty, typically comparable or larger than the projected climate change signal. Therefore, climate change effects in streamflow mean, frequency, and seasonality can be masked by natural climatic fluctuations in large parts of the analyzed regions. An exception to the overwhelming role of stochastic variability is represented by high elevation catchments fed by glaciers where streamflow is expected to be considerably reduced due to glacier retreat, with consequences appreciable in the main downstream rivers in August and September. Simulations also identify regions (west upper Rhone and Toce, Ticino river basins) where a strong precipitation increase in the February to April period projects streamflow beyond the range of natural climate variability during the melting season. This study emphasizes the importance of including internal climate variability in climate change analyses, especially when compared to the limited uncertainty that would be accounted for by few deterministic projections. The presented results could be useful in guiding more specific impact studies, although design or management decisions should be better based on reliability and vulnerability criteria as suggested by recent literature. Copyright © 2013

Hidden Markov latent variable models with multivariate longitudinal data.

Science.gov (United States)

Song, Xinyuan; Xia, Yemao; Zhu, Hongtu

2017-03-01

Cocaine addiction is chronic and persistent, and has become a major social and health problem in many countries. Existing studies have shown that cocaine addicts often undergo episodic periods of addiction to, moderate dependence on, or swearing off cocaine. Given its reversible feature, cocaine use can be formulated as a stochastic process that transits from one state to another, while the impacts of various factors, such as treatment received and individuals' psychological problems on cocaine use, may vary across states. This article develops a hidden Markov latent variable model to study multivariate longitudinal data concerning cocaine use from a California Civil Addict Program. The proposed model generalizes conventional latent variable models to allow bidirectional transition between cocaine-addiction states and conventional hidden Markov models to allow latent variables and their dynamic interrelationship. We develop a maximum-likelihood approach, along with a Monte Carlo expectation conditional maximization (MCECM) algorithm, to conduct parameter estimation. The asymptotic properties of the parameter estimates and statistics for testing the heterogeneity of model parameters are investigated. The finite sample performance of the proposed methodology is demonstrated by simulation studies. The application to cocaine use study provides insights into the prevention of cocaine use. © 2016, The International Biometric Society.

A thermomechanical constitutive model for cemented granular materials with quantifiable internal variables. Part II - Validation and localization analysis

Science.gov (United States)

Das, Arghya; Tengattini, Alessandro; Nguyen, Giang D.; Viggiani, Gioacchino; Hall, Stephen A.; Einav, Itai

2014-10-01

We study the mechanical failure of cemented granular materials (e.g., sandstones) using a constitutive model based on breakage mechanics for grain crushing and damage mechanics for cement fracture. The theoretical aspects of this model are presented in Part I: Tengattini et al. (2014), A thermomechanical constitutive model for cemented granular materials with quantifiable internal variables, Part I - Theory (Journal of the Mechanics and Physics of Solids, 10.1016/j.jmps.2014.05.021). In this Part II we investigate the constitutive and structural responses of cemented granular materials through analyses of Boundary Value Problems (BVPs). The multiple failure mechanisms captured by the proposed model enable the behavior of cemented granular rocks to be well reproduced for a wide range of confining pressures. Furthermore, through comparison of the model predictions and experimental data, the micromechanical basis of the model provides improved understanding of failure mechanisms of cemented granular materials. In particular, we show that grain crushing is the predominant inelastic deformation mechanism under high pressures while cement failure is the relevant mechanism at low pressures. Over an intermediate pressure regime a mixed mode of failure mechanisms is observed. Furthermore, the micromechanical roots of the model allow the effects on localized deformation modes of various initial microstructures to be studied. The results obtained from both the constitutive responses and BVP solutions indicate that the proposed approach and model provide a promising basis for future theoretical studies on cemented granular materials.

A class of constitutive relations with internal variable derivatives. Derivation from homogenization and initial value problem

International Nuclear Information System (INIS)

Andrieux, S.; Joussemet, M.; Lorentz, E.

1996-01-01

A general framework for deriving and using a class of constitutive laws incorporating spatial gradients of internal variables is presented. It uses two basic ingredients: a derivation of such models by homogenization techniques and a reformulation of the evolution equation at the scale of the whole structure. (orig.)

A Model of International Communication Media Appraisal and Exposure: A Comprehensive Test in Belize.

Science.gov (United States)

Johnson, J. David; Oliveira, Omar Souki

A study constituted the fifth phase of a programmatic research effort designed to develop and test a model of international communications media exposure and appraisal. The model posits that three variables--editorial tone, communication potential, and utility--have positive determinant effects on these dependent variables. Research was carried…

A Thermodynamical Theory with Internal Variables Describing Thermal Effects in Viscous Fluids

Science.gov (United States)

Ciancio, Vincenzo; Palumbo, Annunziata

2018-04-01

In this paper the heat conduction in viscous fluids is described by using the theory of classical irreversible thermodynamics with internal variables. In this theory, the deviation from the local equilibrium is characterized by vectorial internal variables and a generalized entropy current density expressed in terms of so-called current multipliers. Cross effects between heat conduction and viscosity are also considered and some phenomenological generalizations of Fourier's and Newton's laws are obtained.

Sparse modeling of spatial environmental variables associated with asthma.

Science.gov (United States)

Chang, Timothy S; Gangnon, Ronald E; David Page, C; Buckingham, William R; Tandias, Aman; Cowan, Kelly J; Tomasallo, Carrie D; Arndt, Brian G; Hanrahan, Lawrence P; Guilbert, Theresa W

2015-02-01

Geographically distributed environmental factors influence the burden of diseases such as asthma. Our objective was to identify sparse environmental variables associated with asthma diagnosis gathered from a large electronic health record (EHR) dataset while controlling for spatial variation. An EHR dataset from the University of Wisconsin's Family Medicine, Internal Medicine and Pediatrics Departments was obtained for 199,220 patients aged 5-50years over a three-year period. Each patient's home address was geocoded to one of 3456 geographic census block groups. Over one thousand block group variables were obtained from a commercial database. We developed a Sparse Spatial Environmental Analysis (SASEA). Using this method, the environmental variables were first dimensionally reduced with sparse principal component analysis. Logistic thin plate regression spline modeling was then used to identify block group variables associated with asthma from sparse principal components. The addresses of patients from the EHR dataset were distributed throughout the majority of Wisconsin's geography. Logistic thin plate regression spline modeling captured spatial variation of asthma. Four sparse principal components identified via model selection consisted of food at home, dog ownership, household size, and disposable income variables. In rural areas, dog ownership and renter occupied housing units from significant sparse principal components were associated with asthma. Our main contribution is the incorporation of sparsity in spatial modeling. SASEA sequentially added sparse principal components to Logistic thin plate regression spline modeling. This method allowed association of geographically distributed environmental factors with asthma using EHR and environmental datasets. SASEA can be applied to other diseases with environmental risk factors. Copyright © 2014 Elsevier Inc. All rights reserved.

Internal variability of fine-scale components of meteorological fields in extended-range limited-area model simulations with atmospheric and surface nudging

Science.gov (United States)

Separovic, Leo; Husain, Syed Zahid; Yu, Wei

2015-09-01

Internal variability (IV) in dynamical downscaling with limited-area models (LAMs) represents a source of error inherent to the downscaled fields, which originates from the sensitive dependence of the models to arbitrarily small modifications. If IV is large it may impose the need for probabilistic verification of the downscaled information. Atmospheric spectral nudging (ASN) can reduce IV in LAMs as it constrains the large-scale components of LAM fields in the interior of the computational domain and thus prevents any considerable penetration of sensitively dependent deviations into the range of large scales. Using initial condition ensembles, the present study quantifies the impact of ASN on IV in LAM simulations in the range of fine scales that are not controlled by spectral nudging. Four simulation configurations that all include strong ASN but differ in the nudging settings are considered. In the fifth configuration, grid nudging of land surface variables toward high-resolution surface analyses is applied. The results show that the IV at scales larger than 300 km can be suppressed by selecting an appropriate ASN setup. At scales between 300 and 30 km, however, in all configurations, the hourly near-surface temperature, humidity, and winds are only partly reproducible. Nudging the land surface variables is found to have the potential to significantly reduce IV, particularly for fine-scale temperature and humidity. On the other hand, hourly precipitation accumulations at these scales are generally irreproducible in all configurations, and probabilistic approach to downscaling is therefore recommended.

Seasonal variability of Internal tide energetics in the western Bay of Bengal

Science.gov (United States)

Mohanty, S.; Rao, A. D.

2017-12-01

The Internal Waves (IWs) are generated by the flow of barotropic tide over the rapidly varying and steep topographic features like continental shelf slope, seamounts, etc. These waves are an important phenomena in the ocean due to their influence on the density structure and energy transfer into the region. Such waves are also important in submarine acoustics, underwater navigation, offshore structures, ocean mixing and biogeochemical processes, etc. over the shelf-slope region. The seasonal variability of internal tides in the western Bay of Bengal is examined by using three-dimensional MITgcm model. The numerical simulations are performed for different periods covering August-September, 2013; November-December, 2013 and March-April, 2014 representing monsoon, post-monsoon and pre-monsoon seasons respectively during which high temporal resolution observed data sets are available. The model is initially validated through the spectral estimate of density and the baroclinic velocities. From the estimate, it is found that its peak is associated with the semi-diurnal frequency at all the depths in both observations and model simulations for November-December and March-April. However in August, the estimate is found to be maximum near the inertial frequency at all available depths. EOF analysis suggests that about 70-80% of the total variance comes from Mode-1 semi-diurnal internal tide in both observations as well as in the model simulations. The phase speed, group speed and wavelength are found to be maximum for post-monsoon season compared to other two seasons. To understand the generation and propagation of internal tides over this region, barotropic-to-baroclinic M2 tidal energy conversion and energy flux are examined. The barotropic-to-baroclinic conversion occurs intensively along the shelf-slope regions and propagate towards the coast. The model simulated energy dissipation rate infers that its maximum occurs at the generation sites and hence the local mixing

Model Pengendalian Internal Berbasis Sarbanes-Oxley Act dan Keandalan Pelaporan Keuangan (Studi Internal Audit Pada Perusahaan Publik di Indonesia

Directory of Open Access Journals (Sweden)

Syahril Djaddang

2016-06-01

Full Text Available This study focus on internal control application based on the Sarbanes-Oxley Act. The research objective is to examine the impact of Sarbanes-Oxley Act implementation and the financial reporting reliability toward audit quality and audit opinion. The research is conducted on public companies implementing Sarbanes- Oxley Act in Indonesia. The internal audit section in the companies are used as respondents. Based on questionnaires distributed, there were 35 samples of public companies used in this research. This study employs WarpPLS to handle the SEM model in testing the hypotheses and multigroup analysis to conduct the sensitivity analysis. The research’s results showed that application of Sarbanes-Oxley Act based internal control and financial reporting reliability are positively affect the audit opinions and directly influence the audit quality. However, the independent auditor's opinion is not a moderating variables between other variables. The research results are expected to be used as considerations by the companies in implementation of Sarbanes-Oxley Act based internal control.

Models of international entrepreneurship

DEFF Research Database (Denmark)

Rask, Morten; Servais, Per

2012-01-01

on International Entrepreneurship, and specifically but not exclusively, International New Ventures (INVs). The three resulting ‘meta-models’ depict the activities and loci of such firms (Figure 1), the motivating factors that give rise to such firms (Figure 2) and their growth modalities and strategies (Figure 3......). These models reflect the merger of entrepreneurship and international business into the field of international entrepreneurship. Managers in international entrepreneurial firms and students in international business and entrepreneurship can use the models as framework for understanding international...... entrepreneurship....

Modelling and prediction of pig iron variables in the blast furnace

Energy Technology Data Exchange (ETDEWEB)

Saxen, H.; Laaksonen, M.; Waller, M. [Aabo Akademi, Turku (Finland). Heat Engineering Lab.

1996-12-31

The blast furnace, where pig iron for steelmaking is produced, is an extremely complicated process, with heat and mass transfer and chemical reactions between several phases. Very few direct measurements on the internal state are available in the operation of the process. A main problem in on-line analysis and modelling is that the state of the furnace may undergo spontaneous changes, which alter the dynamic behaviour of the process. Moreover, large internal disturbances frequently occur, which affect the product quality. The work in this research project focuses on a central problem in the control of the blast furnace process, i.e., short-term prediction of pig iron variables. The problem is of considerable importance for fuel economy, product quality, and for an optimal decision making in integrated steel plants. The operation of the blast furnace aims at producing a product (hot metal) with variables maintained on a stable level (close to their setpoints) without waste of expensive fuel (metallurgical coke). The hot metal temperature and composition affect the downstream (steelmaking) processes, so fluctuations in the pig iron quality must be `corrected` in the steel plant. The goal is to develop a system which predicts the evolution of the hot metal variables (temperature, chemical composition) during the next few taps, and that can be used for decision-making in the operation of the blast furnace. Because of the complicated behaviour of the process, it is considered important to include both deterministic and stochastic components in the modelling: Mathematical models, which on the basis of measurements describe the physical state of the process, and statistical (black-box) models will be combined in the system. Moreover, different models will be applied in different domains in order to capture structural changes in the dynamics of the process SULA 2 Research Programme; 17 refs.

Modelling and prediction of pig iron variables in the blast furnace

Energy Technology Data Exchange (ETDEWEB)

Saxen, H; Laaksonen, M; Waller, M [Aabo Akademi, Turku (Finland). Heat Engineering Lab.

1997-12-31

The blast furnace, where pig iron for steelmaking is produced, is an extremely complicated process, with heat and mass transfer and chemical reactions between several phases. Very few direct measurements on the internal state are available in the operation of the process. A main problem in on-line analysis and modelling is that the state of the furnace may undergo spontaneous changes, which alter the dynamic behaviour of the process. Moreover, large internal disturbances frequently occur, which affect the product quality. The work in this research project focuses on a central problem in the control of the blast furnace process, i.e., short-term prediction of pig iron variables. The problem is of considerable importance for fuel economy, product quality, and for an optimal decision making in integrated steel plants. The operation of the blast furnace aims at producing a product (hot metal) with variables maintained on a stable level (close to their setpoints) without waste of expensive fuel (metallurgical coke). The hot metal temperature and composition affect the downstream (steelmaking) processes, so fluctuations in the pig iron quality must be `corrected` in the steel plant. The goal is to develop a system which predicts the evolution of the hot metal variables (temperature, chemical composition) during the next few taps, and that can be used for decision-making in the operation of the blast furnace. Because of the complicated behaviour of the process, it is considered important to include both deterministic and stochastic components in the modelling: Mathematical models, which on the basis of measurements describe the physical state of the process, and statistical (black-box) models will be combined in the system. Moreover, different models will be applied in different domains in order to capture structural changes in the dynamics of the process SULA 2 Research Programme; 17 refs.

Adding thin-ideal internalization and impulsiveness to the cognitive-behavioral model of bulimic symptoms.

Science.gov (United States)

Schnitzler, Caroline E; von Ranson, Kristin M; Wallace, Laurel M

2012-08-01

This study evaluated the cognitive-behavioral (CB) model of bulimia nervosa and an extension that included two additional maintaining factors - thin-ideal internalization and impulsiveness - in 327 undergraduate women. Participants completed measures of demographics, self-esteem, concern about shape and weight, dieting, bulimic symptoms, thin-ideal internalization, and impulsiveness. Both the original CB model and the extended model provided good fits to the data. Although structural equation modeling analyses suggested that the original CB model was most parsimonious, hierarchical regression analyses indicated that the additional variables accounted for significantly more variance. Additional analyses showed that the model fit could be improved by adding a path from concern about shape and weight, and deleting the path from dieting, to bulimic symptoms. Expanding upon the factors considered in the model may better capture the scope of variables maintaining bulimic symptoms in young women with a range of severity of bulimic symptoms. Copyright © 2012 Elsevier Ltd. All rights reserved.

Confounding of three binary-variables counterfactual model

OpenAIRE

Liu, Jingwei; Hu, Shuang

2011-01-01

Confounding of three binary-variables counterfactual model is discussed in this paper. According to the effect between the control variable and the covariate variable, we investigate three counterfactual models: the control variable is independent of the covariate variable, the control variable has the effect on the covariate variable and the covariate variable affects the control variable. Using the ancillary information based on conditional independence hypotheses, the sufficient conditions...

SME International Business Models

DEFF Research Database (Denmark)

Child, John; Hsieh, Linda; Elbanna, Said

2017-01-01

This paper addresses two questions through a study of 180 SMEs located in contrasting industry and home country contexts. First, which business models for international markets prevail among SMEs and do they configure into different types? Second, which factors predict the international business...... models that SMEs follow? Three distinct international business models (traditional market-adaptive, technology exploiter, and ambidextrous explorer) are found among the SMEs studied. The likelihood of SMEs adopting one business model rather than another is to a high degree predictable with reference...

Two-Layer Variable Infiltration Capacity Land Surface Representation for General Circulation Models

Science.gov (United States)

Xu, L.

1994-01-01

A simple two-layer variable infiltration capacity (VIC-2L) land surface model suitable for incorporation in general circulation models (GCMs) is described. The model consists of a two-layer characterization of the soil within a GCM grid cell, and uses an aerodynamic representation of latent and sensible heat fluxes at the land surface. The effects of GCM spatial subgrid variability of soil moisture and a hydrologically realistic runoff mechanism are represented in the soil layers. The model was tested using long-term hydrologic and climatalogical data for Kings Creek, Kansas to estimate and validate the hydrological parameters. Surface flux data from three First International Satellite Land Surface Climatology Project Field Experiments (FIFE) intensive field compaigns in the summer and fall of 1987 in central Kansas, and from the Anglo-Brazilian Amazonian Climate Observation Study (ABRACOS) in Brazil were used to validate the mode-simulated surface energy fluxes and surface temperature.

Spatio-temporal variability of internal waves in the northern Gulf of Mexico studied with the Navy Coastal Ocean Model, NCOM

Science.gov (United States)

Cambazoglu, M. K.; Jacobs, G. A.; Howden, S. D.; Book, J. W.; Arnone, R.; Soto Ramos, I. M.; Vandermeulen, R. A.; Greer, A. T.; Miles, T. N.

2016-02-01

Internal waves enhance mixing in the upper ocean, transport nutrients and plankton over the water column and across the shelf from deeper waters to shallower coastal areas, and could also transport pollutants such as hydrocarbons onshore during an oil spill event. This study aims to characterize internal waves in the northern Gulf of Mexico (nGoM) and investigate the possible generation and dissipation mechanisms using a high-resolution (1-km) application of the Navy Coastal Ocean Model (NCOM). Three dimensional model products are used to detect the propagation patterns of internal waves. The vertical structure of internal waves is studied and the role of stratification is analyzed by looking at the temperature, salinity and velocity variations along the water column. The model predictions suggest the generation of internal waves on the continental shelf, therefore the role of ocean bottom topography interacting with tides and general circulation features such as the Loop Current Eddy front, on the internal wave generation will be discussed. The time periods of internal wave occurrences are identified from model predictions and compared to satellite ocean color imagery. Further data analysis, e.g. Fourier analysis, is implemented to determine internal wavelengths and frequencies and to determine if the response of internal waves are at tidal periods or at different frequencies. The atmospheric forcing provided to NCOM and meteorological data records are analyzed to define the interaction between wind forcing and internal wave generation. Wavelet analysis characterizes the ocean response to atmospheric events with periodic frequencies. Ocean color satellite imagery was used to visualize the location of the Mississippi river plume (and other oceanic features) and compared to the model predictions because the enhanced stratification from freshwater plumes which propagate across the Mississippi Bight can provide favorable conditions in coastal waters for internal wave

Sources and Impacts of Modeled and Observed Low-Frequency Climate Variability

Science.gov (United States)

Parsons, Luke Alexander

Here we analyze climate variability using instrumental, paleoclimate (proxy), and the latest climate model data to understand more about the sources and impacts of low-frequency climate variability. Understanding the drivers of climate variability at interannual to century timescales is important for studies of climate change, including analyses of detection and attribution of climate change impacts. Additionally, correctly modeling the sources and impacts of variability is key to the simulation of abrupt change (Alley et al., 2003) and extended drought (Seager et al., 2005; Pelletier and Turcotte, 1997; Ault et al., 2014). In Appendix A, we employ an Earth system model (GFDL-ESM2M) simulation to study the impacts of a weakening of the Atlantic meridional overturning circulation (AMOC) on the climate of the American Tropics. The AMOC drives some degree of local and global internal low-frequency climate variability (Manabe and Stouffer, 1995; Thornalley et al., 2009) and helps control the position of the tropical rainfall belt (Zhang and Delworth, 2005). We find that a major weakening of the AMOC can cause large-scale temperature, precipitation, and carbon storage changes in Central and South America. Our results suggest that possible future changes in AMOC strength alone will not be sufficient to drive a large-scale dieback of the Amazonian forest, but this key natural ecosystem is sensitive to dry-season length and timing of rainfall (Parsons et al., 2014). In Appendix B, we compare a paleoclimate record of precipitation variability in the Peruvian Amazon to climate model precipitation variability. The paleoclimate (Lake Limon) record indicates that precipitation variability in western Amazonia is 'red' (i.e., increasing variability with timescale). By contrast, most state-of-the-art climate models indicate precipitation variability in this region is nearly 'white' (i.e., equally variability across timescales). This paleo-model disagreement in the overall

Using an Altimeter-Derived Internal Tide Model to Remove Tides from in Situ Data

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Zaron, Edward D.; Ray, Richard D.

2017-01-01

Internal waves at tidal frequencies, i.e., the internal tides, are a prominent source of variability in the ocean associated with significant vertical isopycnal displacements and currents. Because the isopycnal displacements are caused by ageostrophic dynamics, they contribute uncertainty to geostrophic transport inferred from vertical profiles in the ocean. Here it is demonstrated that a newly developed model of the main semidiurnal (M2) internal tide derived from satellite altimetry may be used to partially remove the tide from vertical profile data, as measured by the reduction of steric height variance inferred from the profiles. It is further demonstrated that the internal tide model can account for a component of the near-surface velocity as measured by drogued drifters. These comparisons represent a validation of the internal tide model using independent data and highlight its potential use in removing internal tide signals from in situ observations.

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.

Materials with memory initial-boundary value problems for constitutive equations with internal variables

CERN Document Server

Alber, Hans-Dieter

1998-01-01

This book contributes to the mathematical theory of systems of differential equations consisting of the partial differential equations resulting from conservation of mass and momentum, and of constitutive equations with internal variables. The investigations are guided by the objective of proving existence and uniqueness, and are based on the idea of transforming the internal variables and the constitutive equations. A larger number of constitutive equations from the engineering sciences are presented. The book is therefore suitable not only for specialists, but also for mathematicians seeking for an introduction in the field, and for engineers with a sound mathematical background.

Can oceanic reanalyses be used to assess recent anthropogenic changes and low-frequency internal variability of upper ocean temperature?

Energy Technology Data Exchange (ETDEWEB)

Corre, L.; Terray, L.; Weaver, A. [Cerfacs-CNRS, Toulouse (France); Balmaseda, M. [E.C.M.W.F, Reading (United Kingdom); Ribes, A. [CNRM-GAME, Meteo France-CNRS, Toulouse (France)

2012-03-15

A multivariate analysis of the upper ocean thermal structure is used to examine the recent long-term changes and decadal variability in the upper ocean heat content as represented by model-based ocean reanalyses and a model-independent objective analysis. The three variables used are the mean temperature above the 14 C isotherm, its depth and a fixed depth mean temperature (250 m mean temperature). The mean temperature above the 14 C isotherm is a convenient, albeit simple, way to isolate thermodynamical changes by filtering out dynamical changes related to thermocline vertical displacements. The global upper ocean observations and reanalyses exhibit very similar warming trends (0.045 C per decade) over the period 1965-2005, superimposed with marked decadal variability in the 1970s and 1980s. The spatial patterns of the regression between indices (representative of anthropogenic changes and known modes of internal decadal variability), and the three variables associated with the ocean heat content are used as fingerprint to separate out the different contributions. The choice of variables provides information about the local heat absorption, vertical distribution and horizontal redistribution of heat, this latter being suggestive of changes in ocean circulation. The discrepancy between the objective analysis and the reanalyses, as well as the spread among the different reanalyses, are used as a simple estimate of ocean state uncertainties. Two robust findings result from this analysis: (1) the signature of anthropogenic changes is qualitatively different from those of the internal decadal variability associated to the Pacific Interdecadal Oscillation and the Atlantic Meridional Oscillation, and (2) the anthropogenic changes in ocean heat content do not only consist of local heat absorption, but are likely related with changes in the ocean circulation, with a clear shallowing of the tropical thermocline in the Pacific and Indian oceans. (orig.)

Internal versus external controls on age variability: Definitions, origins and implications in a changing climate

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Harman, C. J.

2015-12-01

The unsteadiness of stream water age is now well established, but the controls on the age dynamics, and the adequate representation and prediction of those dynamics, are not. A basic distinction can be made between internal variability that arises from changes in the proportions of flow moving through the diverse flow pathways of a hydrologic system, and external variability that arises from the stochasticity of inputs and outputs (such as precipitation and streamflow). In this talk I will show how these two types of age variability can be formally defined and distinguished within the framework of rank StorAge Selection (rSAS) functions. Internal variability implies variations in time in the rSAS function, while external variability does not. This leads naturally to the definition of several modes of internal variability, reflecting generic ways that system flowpaths may be rearranged. This rearrangement may be induced by fluctuations in the system state (such as catchment wetness), or by longer-term changes in catchment structure (such as land use change). One type of change, the 'inverse storage effect' is characterized by an increase in the release of young water from the system in response to an increase in overall system storage. This effect can be seen in many hydrologic settings, and has important implications for the effect of altered hydroclimatic conditions on solute transport through a landscape. External variability, such as increased precipitation, can induce a decrease in mean transit time (and vice versa), but this effect is greatly enhanced if accompanied by an internal shift in flow pathways that increases the relative importance of younger water. These effects will be illustrated using data from field and experimental studies.

Variable selection and model choice in geoadditive regression models.

Science.gov (United States)

Kneib, Thomas; Hothorn, Torsten; Tutz, Gerhard

2009-06-01

Model choice and variable selection are issues of major concern in practical regression analyses, arising in many biometric applications such as habitat suitability analyses, where the aim is to identify the influence of potentially many environmental conditions on certain species. We describe regression models for breeding bird communities that facilitate both model choice and variable selection, by a boosting algorithm that works within a class of geoadditive regression models comprising spatial effects, nonparametric effects of continuous covariates, interaction surfaces, and varying coefficients. The major modeling components are penalized splines and their bivariate tensor product extensions. All smooth model terms are represented as the sum of a parametric component and a smooth component with one degree of freedom to obtain a fair comparison between the model terms. A generic representation of the geoadditive model allows us to devise a general boosting algorithm that automatically performs model choice and variable selection.

Are Simulated and Observed Twentieth Century Tropical Pacific Sea Surface Temperature Trends Significant Relative to Internal Variability?

Science.gov (United States)

Coats, S.; Karnauskas, K. B.

2017-10-01

Historical trends in the tropical Pacific zonal sea surface temperature gradient (SST gradient) are analyzed herein using 41 climate models (83 simulations) and 5 observational data sets. A linear inverse model is trained on each simulation and observational data set to assess if trends in the SST gradient are significant relative to the stationary statistics of internal variability, as would suggest an important role for external forcings such as anthropogenic greenhouse gasses. None of the 83 simulations have a positive trend in the SST gradient, a strengthening of the climatological SST gradient with more warming in the western than eastern tropical Pacific, as large as the mean trend across the five observational data sets. If the observed trends are anthropogenically forced, this discrepancy suggests that state-of-the-art climate models are not capturing the observed response of the tropical Pacific to anthropogenic forcing, with serious implications for confidence in future climate projections. There are caveats to this interpretation, however, as some climate models have a significant strengthening of the SST gradient between 1900 and 2013 Common Era, though smaller in magnitude than the observational data sets, and the strengthening in three out of five observational data sets is insignificant. When combined with observational uncertainties and the possibility of centennial time scale internal variability not sampled by the linear inverse model, this suggests that confident validation of anthropogenic SST gradient trends in climate models will require further emergence of anthropogenic trends. Regardless, the differences in SST gradient trends between climate models and observational data sets are concerning and motivate the need for process-level validation of the atmosphere-ocean dynamics relevant to climate change in the tropical Pacific.

Hydration level is an internal variable for computing motivation to obtain water rewards in monkeys.

Science.gov (United States)

Minamimoto, Takafumi; Yamada, Hiroshi; Hori, Yukiko; Suhara, Tetsuya

2012-05-01

In the process of motivation to engage in a behavior, valuation of the expected outcome is comprised of not only external variables (i.e., incentives) but also internal variables (i.e., drive). However, the exact neural mechanism that integrates these variables for the computation of motivational value remains unclear. Besides, the signal of physiological needs, which serves as the primary internal variable for this computation, remains to be identified. Concerning fluid rewards, the osmolality level, one of the physiological indices for the level of thirst, may be an internal variable for valuation, since an increase in the osmolality level induces drinking behavior. Here, to examine the relationship between osmolality and the motivational value of a water reward, we repeatedly measured the blood osmolality level, while 2 monkeys continuously performed an instrumental task until they spontaneously stopped. We found that, as the total amount of water earned increased, the osmolality level progressively decreased (i.e., the hydration level increased) in an individual-dependent manner. There was a significant negative correlation between the error rate of the task (the proportion of trials with low motivation) and the osmolality level. We also found that the increase in the error rate with reward accumulation can be well explained by a formula describing the changes in the osmolality level. These results provide a biologically supported computational formula for the motivational value of a water reward that depends on the hydration level, enabling us to identify the neural mechanism that integrates internal and external variables.

Modelling the internal boundary layer over the lower fraser valley, British Columbia

Energy Technology Data Exchange (ETDEWEB)

Batchvarova, E. [National Inst. of Meteorology and Hydrology, Sofia (Bulgaria); Steyn, D. [Univ. of British Columbia, Dept. of Geography, Vancouver (Canada); Cai, X. [Univ. of Birmingham, School of Geography, Edgbaston (United Kingdom); Gryning, S.E. [Risoe National Lab., Roskilde (Denmark); Baldi, M. [Inst. for Atmospheric Physics, IFA-CNR, Rome (Italy)

1997-10-01

In this study we use the very extensive data-set on temporal and spatial structure of the internal boundary layer on the Lower Faser Valley, Canada, collected during the so-called Pacific `93 field campaign, to study the ability of the simple applied model by Gryning and Batchvarova (1996) and the CSU-RAMS meso-scale model summarised in Pielke et al. (1992) to describe the development and variability of the internal boundary layer depth during the course of a day. Given the complexity of topography, coastline and land-use in the Lower Fraser Valley region, both models perform remarkably well. The simple applied model performs extremely well, given its simplicity. It is clear that correct specification of spatially resolved surface sensible heat flux and wind field are crucial to the success of this model which can be operated at very fine spatial resolution. The 3D model performs extremely well, though it too must capture the local wind field correctly for complete success. Its limited horizontal resolution results in strongly smoothed internal boundary layer height fields. (LN)

THE INTERNAL CONTROL MODELS IN ROMANIA

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TEODORESCU CRISTIAN DRAGOȘ

2015-06-01

Full Text Available Internal control is indissolubly linked to business and accounting. Throughout history, domestic and international trade has grown exponentially, which has led to an increasing complexity of internal control, to new methods and techniques to control the business. The literature has presented the first models of internal control in the Sumerian period (3600 - 3200 BC, and the emergence and development of internal control in Egypt, Persia, Greek and Roman Empire, in the Middle Ages till modern times. The purpose of this article is to present the models of internal control in Romania, starting from the principles of the classical model of internal control (COSO model. For a better understanding of the implication of internal control in terms of public and private sector, I have structured the article in the following parts: (a the definition of internal control in the literature; (b the presentation of the COSO model; (c internal control and internal audit in public institutions; (d internal control issues in accounting regulations on the individual and consolidated annual financial statements; (e internal / managerial control; (f conclusions.

Assessing the accuracy and stability of variable selection methods for random forest modeling in ecology.

Science.gov (United States)

Fox, Eric W; Hill, Ryan A; Leibowitz, Scott G; Olsen, Anthony R; Thornbrugh, Darren J; Weber, Marc H

2017-07-01

Random forest (RF) modeling has emerged as an important statistical learning method in ecology due to its exceptional predictive performance. However, for large and complex ecological data sets, there is limited guidance on variable selection methods for RF modeling. Typically, either a preselected set of predictor variables are used or stepwise procedures are employed which iteratively remove variables according to their importance measures. This paper investigates the application of variable selection methods to RF models for predicting probable biological stream condition. Our motivating data set consists of the good/poor condition of n = 1365 stream survey sites from the 2008/2009 National Rivers and Stream Assessment, and a large set (p = 212) of landscape features from the StreamCat data set as potential predictors. We compare two types of RF models: a full variable set model with all 212 predictors and a reduced variable set model selected using a backward elimination approach. We assess model accuracy using RF's internal out-of-bag estimate, and a cross-validation procedure with validation folds external to the variable selection process. We also assess the stability of the spatial predictions generated by the RF models to changes in the number of predictors and argue that model selection needs to consider both accuracy and stability. The results suggest that RF modeling is robust to the inclusion of many variables of moderate to low importance. We found no substantial improvement in cross-validated accuracy as a result of variable reduction. Moreover, the backward elimination procedure tended to select too few variables and exhibited numerous issues such as upwardly biased out-of-bag accuracy estimates and instabilities in the spatial predictions. We use simulations to further support and generalize results from the analysis of real data. A main purpose of this work is to elucidate issues of model selection bias and instability to ecologists interested in

Processes of Internal and International Migration from Chitwan, Nepal.

Science.gov (United States)

Bohra, Pratikshya; Massey, Douglas S

2009-01-01

In this study we examine which factors predict internal and international migration from Chitwan, a flat valley located in the South-Central region of Nepal, seeking to measure the effect of theoretically specified variables such as human capital, social capital, physical capital, and neighborhood socioeconomic conditions while controlling for demographic variables. We use data from the Chitwan Valley Family Study (CVFS) to estimate a series of discrete time event history models of first and repeat migration to three competing destinations: other locations within Chitwan, other districts within Nepal, and places outside of Nepal. Results support hypotheses derived from neoclassical economics, the theory of new economics of migration, social capital theory, and cumulative causation theory. Our results underscore the need for a synthetic theoretical model that incorporates factors operating at the individual, household, and community levels. The use of multiple explanatory models yields a clearer picture of the forces driving internal and international migration from rural districts in developing nations such as Nepal.

On a model of mixtures with internal variables: Extended Liu procedure for the exploitation of the entropy principle

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Francesco Oliveri

2016-01-01

Full Text Available The exploitation of second law of thermodynamics for a mixture of two fluids with a scalar internal variable and a first order nonlocal state space is achieved by using the extended Liu approach. This method requires to insert as constraints in the entropy inequality either the field equations or their gradient extensions. Consequently, the thermodynamic restrictions imposed by the entropy principle are derived without introducing extra terms neither in the energy balance equation nor in the entropy inequality.

Modeling key processes causing climate change and variability

Energy Technology Data Exchange (ETDEWEB)

Henriksson, S.

2013-09-01

Greenhouse gas warming, internal climate variability and aerosol climate effects are studied and the importance to understand these key processes and being able to separate their influence on the climate is discussed. Aerosol-climate model ECHAM5-HAM and the COSMOS millennium model consisting of atmospheric, ocean and carbon cycle and land-use models are applied and results compared to measurements. Topics at focus are climate sensitivity, quasiperiodic variability with a period of 50-80 years and variability at other timescales, climate effects due to aerosols over India and climate effects of northern hemisphere mid- and high-latitude volcanic eruptions. The main findings of this work are (1) pointing out the remaining challenges in reducing climate sensitivity uncertainty from observational evidence, (2) estimates for the amplitude of a 50-80 year quasiperiodic oscillation in global mean temperature ranging from 0.03 K to 0.17 K and for its phase progression as well as the synchronising effect of external forcing, (3) identifying a power law shape S(f) {proportional_to} f-{alpha} for the spectrum of global mean temperature with {alpha} {approx} 0.8 between multidecadal and El Nino timescales with a smaller exponent in modelled climate without external forcing, (4) separating aerosol properties and climate effects in India by season and location (5) the more efficient dispersion of secondary sulfate aerosols than primary carbonaceous aerosols in the simulations, (6) an increase in monsoon rainfall in northern India due to aerosol light absorption and a probably larger decrease due to aerosol dimming effects and (7) an estimate of mean maximum cooling of 0.19 K due to larger northern hemisphere mid- and high-latitude volcanic eruptions. The results could be applied or useful in better isolating the human-caused climate change signal, in studying the processes further and in more detail, in decadal climate prediction, in model evaluation and in emission policy

Brain signal variability is modulated as a function of internal and external demand in younger and older adults.

Science.gov (United States)

Grady, Cheryl L; Garrett, Douglas D

2018-04-01

Variability in the Blood Oxygen-Level Dependent (BOLD) signal from fMRI is often associated with better cognitive performance and younger age. It has been proposed that neural variability enables flexible responding to uncertainty in a changing environment. However, signal variability reflecting environmental uncertainty may reduce to the extent that a task depends on internally-directed attention and is supported by neural "solutions" that are schematic and relatively stable within each individual. Accordingly, we examined the hypothesis that BOLD variability will be low at rest, higher during internally-directed tasks, and higher still during externally-directed tasks, and that this effect will be reduced with aging. Modulation of BOLD variability across conditions was consistent with these hypotheses, and was associated with faster and more stable behavioral performance in both young and older adults. These data support the idea that brain signal variability may modulate in response to environmental uncertainty, which is presumed to be greater in the external environment than in the internal milieu. Reduced flexibility of signal variability with age may indicate less ability to switch between internal and external brain states. Copyright © 2017 Elsevier Inc. All rights reserved.

A Core Language for Separate Variability Modeling

DEFF Research Database (Denmark)

Iosif-Lazăr, Alexandru Florin; Wasowski, Andrzej; Schaefer, Ina

2014-01-01

Separate variability modeling adds variability to a modeling language without requiring modifications of the language or the supporting tools. We define a core language for separate variability modeling using a single kind of variation point to define transformations of software artifacts in object...... hierarchical dependencies between variation points via copying and flattening. Thus, we reduce a model with intricate dependencies to a flat executable model transformation consisting of simple unconditional local variation points. The core semantics is extremely concise: it boils down to two operational rules...

Comparison of elastic--plastic and variable modulus-cracking constitutive models for prestressed concrete reactor vessels

International Nuclear Information System (INIS)

Anderson, C.A.; Smith, P.D.

1978-01-01

The variable modulus-cracking model is capable of predicting the behavior of reinforced concrete structures (such as the reinforced plate under transverse pressure described previously) well into the range of nonlinear behavior including the prediction of the ultimate load. For unreinforced thick-walled concrete vessels under internal pressure the use of elastic--plastic concrete models in finite element codes enhances the apparent ductility of the vessels in contrast to variable modulus-cracking models that predict nearly instantaneous rupture whenever the tensile strength at the inner wall is exceeded. For unreinforced thick-walled end slabs representative of PCRV heads, the behavior predicted by finite element codes using variable modulus-cracking models is much stiffer in the nonlinear range than that observed experimentally. Although the shear type failures and crack patterns that are observed experimentally are predicted by such concrete models, the ultimate load carrying capacity and vessel-ductility are significantly underestimated. It appears that such models do not adequately model such features as aggregate interlock that could lead to an enhanced vessel reserve strength and ductility

Macroeconomic modelling of international carbon tax regimes

International Nuclear Information System (INIS)

Hall, S.; Mabey, N.; Smith, Clare

1994-01-01

An econometric model of fossil fuel demand has been estimated for eight OECD countries, relating coal, oil and gas demands to GDP and prices. In addition, for five of these countries, a model of endogenous technical progress has been estimated, representing the decline in energy intensity as a function of price and macroeconomic variables. This aims to include both price induced innovation in energy and structural change in the economy as long term determinants of energy consumption. A number of possible international carbon/energy tax agreements are simulated, showing the impacts on carbon dioxide emissions and comparing the two models. It is shown that the endogenous technical change model does include an important element that is missed in the more conventional approach. However in the long run the magnitude of taxes required to stabilise or reduce emissions would be large, and it is suggested that other non-price policies will become more important. (Author)

The role of individual and social variables in predicting body dissatisfaction and eating disorder symptoms among Iranian adolescent girls: an expanding of the tripartite influence model

Directory of Open Access Journals (Sweden)

Shima Shahyad

2018-03-01

Full Text Available The aim of the present study was to examine the causal relationships between psychological and social factors, being independent variables and body image dissatisfaction plus symptoms of eating disorders as dependent variables through the mediation of social comparison and thin-ideal internalization. To conduct the study, 477 high-school students from Tehran were recruited by method of cluster sampling. Next, they filled out Rosenberg Self-esteem Scale (RSES, Physical Appearance Comparison Scale (PACS, Self-Concept Clarity Scale (SCCS, Appearance Perfectionism Scale (APS, Eating Disorder Inventory (EDI, Multidimensional Body Self Relations Questionnaire (MBSRQ and Sociocultural Attitudes towards Appearance Questionnaire (SATAQ-4. In the end, collected data were analyzed using structural equation modeling. Findings showed that the assumed model perfectly fitted the data after modification and as a result, all the path-coefficients of latent variables (except for the path between self-esteem and thin-ideal internalization were statistically significant (p<0.05. Also, in this model, 75% of scores' distribution of body dissatisfaction was explained through psychological variables, socio-cultural variables, social comparison and internalization of the thin ideal. The results of the present study provid experimental basis for the confirmation of proposed causal model. The combination of psychological, social and cultural variables could efficiently predict body image dissatisfaction of young girls in Iran. Key Words: Thin-ideal Internalization, Social comparison, Body image dissatisfaction, mediating effects model, eating disorder symptoms, psychological factors.

Models og International Entrepreneurship

DEFF Research Database (Denmark)

Rask, Morten; Servais, Per

2015-01-01

on International Entrepreneurship, and specifically but not exclusively, International New Ventures (INVs). The three resulting ‘meta-models’ depict the activities and loci of such firms, the motivating factors that give rise to such firms and their growth modalities and strategies. These models reflect the merger...... of entrepreneurship and international business into the field of international entrepreneurship....

Contributions of internal climate variability to mitigation of projected future regional sea level rise

Science.gov (United States)

Hu, A.; Bates, S. C.

2017-12-01

Observations indicate that the global mean surface temperature is rising, so does the global mean sea level. Sea level rise (SLR) can impose significant impacts on island and coastal communities, especially when SLR is compounded with storm surges. Here, via analyzing results from two sets of ensemble simulations from the Community Earth System Model version 1, we investigate how the potential SLR benefits through mitigating the future emission scenarios from business as usual to a mild-mitigation over the 21st Century would be affected by internal climate variability. Results show that there is almost no SLR benefit in the near term due to the large SLR variability due to the internal ocean dynamics. However, toward the end of the 21st century, the SLR benefit can be as much as a 26±1% reduction of the global mean SLR due to seawater thermal expansion. Regionally, the benefits from this mitigation for both near and long terms are heterogeneous. They vary from just a 11±5% SLR reduction in Melbourne, Australia to a 35±6% reduction in London. The processes contributing to these regional differences are the coupling of the wind-driven ocean circulation with the decadal scale sea surface temperature mode in the Pacific and Southern Oceans, and the changes of the thermohaline circulation and the mid-latitude air-sea coupling in the Atlantic.

Internal variability in a 1000-yr control simulation with the coupled climate model ECHO-G - II. El Nino Southern Oscillation and North Atlantic Oscillation

Energy Technology Data Exchange (ETDEWEB)

Min, Seung-Ki; Hense, Andreas [Univ. of Bonn (Germany). Meteorological Inst.; Legutke, Stephanie [Max Planck Inst. for Meteorology, Hamburg (Germany); Kwon, Won-Tae [Meteorological Research Inst., Seoul (Korea, Republic of)

2005-08-01

A 1000-yr control simulation (CTL) performed with the atmosphere-ocean global climate model ECHO-G is analysed with regard to the El Nino Southern Oscillation (ENSO) and North Atlantic Oscillation (NAO), the two major natural climatic variabilities, in comparison with observations and other model simulations. The ENSO-related sea surface temperature climate and its seasonal cycle in the tropical Pacific and a single Intertropical Convergence Zone in the eastern tropical Pacific are simulated reasonably, and the ENSO phase-locking to the annual cycle and the subsurface ocean behaviour related to equatorial wave dynamics are also reproduced well. The simulated amplitude of the ENSO signal is however too large and its occurrence is too regular and frequent. Also, the observed westward propagation of zonal wind stress over the equatorial Pacific is not captured by the model. Nevertheless, the ENSO-related teleconnection patterns of near-surface temperature (T2m), precipitation (PCP) and mean sea level pressure (MSLP) are reproduced realistically. The NAO index, defined as the MSLP difference between Gibraltar and Iceland, has a 'white' noise spectrum similar to that of the detrended index obtained from observed data. The correlation and regression patterns of T2m, PCP and MSLP with the NAO index are also successfully simulated. However, the model overestimates the warming over the North Pacific in the high index phase of the NAO, a feature it shares with other coupled models. This might be associated with an enhanced Atlantic/Pacific teleconnection, which is hardly seen in the observations. A detection analysis of the NAO index shows that the observed recent 4060 yr trend cannot be explained by the model's internal variability while the recent 2030 yr trend occurs with a more than 1% chance in ECHO-G CTL.

Bayesian modeling of measurement error in predictor variables

NARCIS (Netherlands)

Fox, Gerardus J.A.; Glas, Cornelis A.W.

2003-01-01

It is shown that measurement error in predictor variables can be modeled using item response theory (IRT). The predictor variables, that may be defined at any level of an hierarchical regression model, are treated as latent variables. The normal ogive model is used to describe the relation between

Non-linear Heart Rate Variability as a Discriminator of Internalizing Psychopathology and Negative Affect in Children With Internalizing Problems and Healthy Controls

Directory of Open Access Journals (Sweden)

Charlotte Fiskum

2018-05-01

Full Text Available Background: Internalizing psychopathology and dysregulated negative affect are characterized by dysregulation in the autonomic nervous system and reduced heart rate variability (HRV due to increases in sympathetic activity alongside reduced vagal tone. The neurovisceral system is however, a complex nonlinear system, and nonlinear indices related to psychopathology are so far less studied in children. Essential nonlinear properties of a system can be found in two main domains: the informational domain and the invariant domain. sample entropy (SampEn is a much-used method from the informational domain, while detrended fluctuation analysis (DFA represents a widely-used method from the invariant domain. To see if nonlinear HRV can provide information beyond linear indices of autonomic activation, this study investigated SampEn and DFA as discriminators of internalizing psychopathology and negative affect alongside measures of vagally-mediated HRV and sympathetic activation.Material and Methods: Thirty-Two children with internalizing difficulties and 25 healthy controls (aged 9–13 were assessed with the Child Behavior Checklist and the Early Adolescent Temperament Questionnaire, Revised, giving an estimate of internalizing psychopathology, negative affect and effortful control, a protective factor against psychopathology. Five minute electrocardiogram and impedance cardiography recordings were collected during a resting baseline, giving estimates of SampEn, DFA short-term scaling exponent α1, root mean square of successive differences (RMSSD, and pre-ejection period (PEP. Between-group differences and correlations were assessed with parametric and non-parametric tests, and the relationships between cardiac variables, psychopathology and negative affect were assessed using generalized linear modeling.Results: SampEn and DFA were not significantly different between the groups. SampEn was weakly negatively related to heart rate (HR in the controls

Design strategies for the International Space University's variable gravity research facility

Science.gov (United States)

Bailey, Sheila G.; Chiaramonte, Francis P.; Davidian, Kenneth J.

1990-01-01

A variable gravity research facility named 'Newton' was designed by 58 students from 13 countries at the International Space University's 1989 summer session at the Universite Louis Pasteur, Strasbourge, France. The project was comprehensive in scope, including a political and legal foundation for international cooperation, development and financing; technical, science and engineering issues; architectural design; plausible schedules; and operations, crew issues and maintenance. Since log-term exposure to zero gravity is known to be harmful to the human body, the main goal was to design a unique variable gravity research facility which would find a practical solution to this problem, permitting a manned mission to Mars. The facility would not duplicate other space-based facilities and would provide the flexibility for examining a number of gravity levels, including lunar and Martian gravities. Major design alternatives included a truss versus a tether based system which also involved the question of docking while spinning or despinning to dock. These design issues are described. The relative advantages or disadvantages are discussed, including comments on the necessary research and technology development required for each.

VizieR Online Data Catalog: AAVSO International Variable Star Index VSX (Watson+, 2006-2014)

Science.gov (United States)

Watson, C.; Henden, A. A.; Price, A.

2018-05-01

This file contains Galactic stars known or suspected to be variable. It lists all stars that have an entry in the AAVSO International Variable Star Index (VSX; http://www.aavso.org/vsx). The database consisted initially of the General Catalogue of Variable Stars (GCVS) and the New Catalogue of Suspected Variables (NSV) and was then supplemented with a large number of variable star catalogues, as well as individual variable star discoveries or variables found in the literature. Effort has also been invested to update the entries with the latest information regarding position, type and period and to remove duplicates. The VSX database is being continually updated and maintained. For historical reasons some objects outside of the Galaxy have been included. (3 data files).

Modeling variability in dendritic ice crystal backscattering cross sections at millimeter wavelengths using a modified Rayleigh–Gans theory

International Nuclear Information System (INIS)

Lu, Yinghui; Clothiaux, Eugene E.; Aydin, Kültegin; Botta, Giovanni; Verlinde, Johannes

2013-01-01

Using the Generalized Multi-particle Mie-method (GMM), Botta et al. (in this issue) [7] created a database of backscattering cross sections for 412 different ice crystal dendrites at X-, Ka- and W-band wavelengths for different incident angles. The Rayleigh–Gans theory, which accounts for interference effects but ignores interactions between different parts of an ice crystal, explains much, but not all, of the variability in the database of backscattering cross sections. Differences between it and the GMM range from −3.5 dB to +2.5 dB and are highly dependent on the incident angle. To explain the residual variability a physically intuitive iterative method was developed to estimate the internal electric field within an ice crystal that accounts for interactions between the neighboring regions within it. After modifying the Rayleigh–Gans theory using this estimated internal electric field, the difference between the estimated backscattering cross sections and those from the GMM method decreased to within 0.5 dB for most of the ice crystals. The largest percentage differences occur when the form factor from the Rayleigh–Gans theory is close to zero. Both interference effects and neighbor interactions are sensitive to the morphology of ice crystals. Improvements in ice-microphysical models are necessary to predict or diagnose internal structures within ice crystals to aid in more accurate interpretation of radar returns. Observations of the morphology of ice crystals are, in turn, necessary to guide the development of such ice-microphysical models and to better understand the statistical properties of ice crystal morphologies in different environmental conditions. -- Highlights: • Significant variability exists in radar backscattering cross sections of dendrites. • Source of variability depends upon detailed distribution of mass within dendrites. • The Rayleigh–Gans theory (RG) captures most of the variability. • Improving RG by estimating dendrite

Modelling the Growth and Volatility in Daily International Mass Tourism to Peru

OpenAIRE

Jose Angelo Divino; Michael McAleer

2009-01-01

Peru is a South American country that is divided into two parts by the Andes Mountains. The rich historical, cultural and geographic diversity has led to the inclusion of ten Peruvian sites on UNESCO’s World Heritage List. For the potential negative impacts of mass tourism on the environment, and hence on future international tourism demand, to be managed appropriately require modelling growth rates and volatility adequately. The paper models the growth rate and volatility (or the variability...

Handbook of latent variable and related models

CERN Document Server

Lee, Sik-Yum

2011-01-01

This Handbook covers latent variable models, which are a flexible class of models for modeling multivariate data to explore relationships among observed and latent variables.- Covers a wide class of important models- Models and statistical methods described provide tools for analyzing a wide spectrum of complicated data- Includes illustrative examples with real data sets from business, education, medicine, public health and sociology.- Demonstrates the use of a wide variety of statistical, computational, and mathematical techniques.

Editorial: Papers from the 7th International Conference on Dendrochronology - Cultural Diversity, Environmental Variability

Science.gov (United States)

Margaret S. Devall; Elaine K. Sutherland

2008-01-01

The 7th International Conference on Dendrochronology - Cultural Diversity, Environmental Variability was held in Beijing, China from 11 to 17 June 2006. The conference was organized and hosted by the Institute of Botany, Chinese Academy of Sciences (IB_CAS) in conjunction with the International Union of Forest Research Organizations (IUFRO) Working Group 5.01.07 (Tree-...

Modeling of a Pouch Lithium Ion Battery Using a Distributed Parameter Equivalent Circuit for Internal Non-Uniformity Analysis

Directory of Open Access Journals (Sweden)

Dafen Chen

2016-10-01

Full Text Available A battery model that has the capability of analyzing the internal non-uniformity of local state variables, including the state of charge (SOC, temperature and current density, is proposed in this paper. The model is built using a set of distributed parameter equivalent circuits. In order to validate the accuracy of the model, a customized battery with embedded T-type thermocouple sensors inside the battery is tested. The simulated temperature conforms well with the measured temperature at each test point, and the maximum difference is less than 1 °C. Then, the model is applied to analyze the evolution processes of local state variables’ distribution inside the battery during the discharge process. The simulation results demonstrate drastic distribution changes of the local state variables inside the battery during the discharge process. The internal non-uniformity is originally caused by the resistance of positive and negative foils, while also influenced by the change rate of open circuit voltage and the total resistance of the battery. Hence, the factors that affect the distribution of the local state variables are addressed.

A comparison of elastic-plastic and variable modulus-cracking constitutive models for prestressed concrete reactor vessels

International Nuclear Information System (INIS)

Anderson, C.A.; Smith, P.D.

1979-01-01

Numerical prediction of the behavior of prestressed concrete reactor vessels (PCRVs) under static, dynamic and long term loadings is complicated by the currently ill-defined behavior of concrete under stress and the three-dimensional nature of PCRVs. Which constitutive model most closely approximates the behavior of concrete in PCRVs under load has not yet been decided. Many equations for accurately modeling the three-dimensional behavior of PCRVs tax the capability of a most up-to-date computing system. The main purpose of this paper is to compare the characteristics of two constitutive models which have been proposed for concrete, variable modulus cracking model and elastic-plastic model. Moreover, the behavior of typical concrete structures was compared, the materials of which obey these constitutive laws. The response to internal pressure of PCRV structure, the constitutive models for concrete, the test problems using a thick-walled concrete ring and a rectangular concrete plate, and the analysis of an axisymmetric concrete pressure vessel PV-26 using the variable modulus cracking model of the ADINA code are explained. The variable modulus cracking model can predict the behavior of reinforced concrete structures well into the range of nonlinear behavior. (Kako, I.)

Variable Selection for Regression Models of Percentile Flows

Science.gov (United States)

Fouad, G.

2017-12-01

Percentile flows describe the flow magnitude equaled or exceeded for a given percent of time, and are widely used in water resource management. However, these statistics are normally unavailable since most basins are ungauged. Percentile flows of ungauged basins are often predicted using regression models based on readily observable basin characteristics, such as mean elevation. The number of these independent variables is too large to evaluate all possible models. A subset of models is typically evaluated using automatic procedures, like stepwise regression. This ignores a large variety of methods from the field of feature (variable) selection and physical understanding of percentile flows. A study of 918 basins in the United States was conducted to compare an automatic regression procedure to the following variable selection methods: (1) principal component analysis, (2) correlation analysis, (3) random forests, (4) genetic programming, (5) Bayesian networks, and (6) physical understanding. The automatic regression procedure only performed better than principal component analysis. Poor performance of the regression procedure was due to a commonly used filter for multicollinearity, which rejected the strongest models because they had cross-correlated independent variables. Multicollinearity did not decrease model performance in validation because of a representative set of calibration basins. Variable selection methods based strictly on predictive power (numbers 2-5 from above) performed similarly, likely indicating a limit to the predictive power of the variables. Similar performance was also reached using variables selected based on physical understanding, a finding that substantiates recent calls to emphasize physical understanding in modeling for predictions in ungauged basins. The strongest variables highlighted the importance of geology and land cover, whereas widely used topographic variables were the weakest predictors. Variables suffered from a high

Interannual Tropical Rainfall Variability in General Circulation Model Simulations Associated with the Atmospheric Model Intercomparison Project.

Science.gov (United States)

Sperber, K. R.; Palmer, T. N.

1996-11-01

The interannual variability of rainfall over the Indian subcontinent, the African Sahel, and the Nordeste region of Brazil have been evaluated in 32 models for the period 1979-88 as part of the Atmospheric Model Intercomparison Project (AMIP). The interannual variations of Nordeste rainfall are the most readily captured, owing to the intimate link with Pacific and Atlantic sea surface temperatures. The precipitation variations over India and the Sahel are less well simulated. Additionally, an Indian monsoon wind shear index was calculated for each model. Evaluation of the interannual variability of a wind shear index over the summer monsoon region indicates that the models exhibit greater fidelity in capturing the large-scale dynamic fluctuations than the regional-scale rainfall variations. A rainfall/SST teleconnection quality control was used to objectively stratify model performance. Skill scores improved for those models that qualitatively simulated the observed rainfall/El Niño- Southern Oscillation SST correlation pattern. This subset of models also had a rainfall climatology that was in better agreement with observations, indicating a link between systematic model error and the ability to simulate interannual variations.A suite of six European Centre for Medium-Range Weather Forecasts (ECMWF) AMIP runs (differing only in their initial conditions) have also been examined. As observed, all-India rainfall was enhanced in 1988 relative to 1987 in each of these realizations. All-India rainfall variability during other years showed little or no predictability, possibly due to internal chaotic dynamics associated with intraseasonal monsoon fluctuations and/or unpredictable land surface process interactions. The interannual variations of Nordeste rainfall were best represented. The State University of New York at Albany/National Center for Atmospheric Research Genesis model was run in five initial condition realizations. In this model, the Nordeste rainfall

TEDS-M 2008 User Guide for the International Database. Supplement 3: Variables Derived from the Educator and Future Teacher Data

Science.gov (United States)

Brese, Falk, Ed.

2012-01-01

This supplement contains documentation on all the derived variables contained in the TEDS-M educator and future teacher data files. These derived variables were used to report data in the TEDS-M international reports. The variables that constitute the scales and indices are made available as part of the TEDS-M International Database to be used in…

Variability of the ocean heat content during the last millennium – an assessment with the ECHO-g Model

Directory of Open Access Journals (Sweden)

P. Ortega

2013-03-01

Full Text Available Studies addressing climate variability during the last millennium generally focus on variables with a direct influence on climate variability, like the fast thermal response to varying radiative forcing, or the large-scale changes in atmospheric dynamics (e.g. North Atlantic Oscillation. The ocean responds to these variations by slowly integrating in depth the upper heat flux changes, thus producing a delayed influence on ocean heat content (OHC that can later impact low frequency SST (sea surface temperature variability through reemergence processes. In this study, both the externally and internally driven variations of the OHC during the last millennium are investigated using a set of fully coupled simulations with the ECHO-G (coupled climate model ECHAMA4 and ocean model HOPE-G atmosphere–ocean general circulation model (AOGCM. When compared to observations for the last 55 yr, the model tends to overestimate the global trends and underestimate the decadal OHC variability. Extending the analysis back to the last one thousand years, the main impact of the radiative forcing is an OHC increase at high latitudes, explained to some extent by a reduction in cloud cover and the subsequent increase of short-wave radiation at the surface. This OHC response is dominated by the effect of volcanism in the preindustrial era, and by the fast increase of GHGs during the last 150 yr. Likewise, salient impacts from internal climate variability are observed at regional scales. For instance, upper temperature in the equatorial Pacific is controlled by ENSO (El Niño Southern Oscillation variability from interannual to multidecadal timescales. Also, both the Pacific Decadal Oscillation (PDO and the Atlantic Multidecadal Oscillation (AMO modulate intermittently the interdecadal OHC variability in the North Pacific and Mid Atlantic, respectively. The NAO, through its influence on North Atlantic surface heat fluxes and convection, also plays an important role on

Preliminary Multi-Variable Parametric Cost Model for Space Telescopes

Science.gov (United States)

Stahl, H. Philip; Hendrichs, Todd

2010-01-01

This slide presentation reviews creating a preliminary multi-variable cost model for the contract costs of making a space telescope. There is discussion of the methodology for collecting the data, definition of the statistical analysis methodology, single variable model results, testing of historical models and an introduction of the multi variable models.

How to get rid of W: a latent variables approach to modelling spatially lagged variables

NARCIS (Netherlands)

Folmer, H.; Oud, J.

2008-01-01

In this paper we propose a structural equation model (SEM) with latent variables to model spatial dependence. Rather than using the spatial weights matrix W, we propose to use latent variables to represent spatial dependence and spillover effects, of which the observed spatially lagged variables are

How to get rid of W : a latent variables approach to modelling spatially lagged variables

NARCIS (Netherlands)

Folmer, Henk; Oud, Johan

2008-01-01

In this paper we propose a structural equation model (SEM) with latent variables to model spatial dependence. Rather than using the spatial weights matrix W, we propose to use latent variables to represent spatial dependence and spillover effects, of which the observed spatially lagged variables are

Investigation on the Effects of Internal EGR by Variable Exhaust Valve Actuation with Post Injection on Auto-ignited Combustion and Emission Performance

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Insu Cho

2018-04-01

Full Text Available Variable valve mechanisms are usually applied to a gasoline combustion engine to improve its power performance by controlling the amount of intake air according to the operating load. These mechanisms offer one possibility of resolving the conflict of objectives between a further reduction of raw emissions and an improvement in fuel efficiency. In recent years, variable valve control systems have become extremely important in the diesel combustion engine. Importantly, it has been shown that there are several potential benefits of applying variable valve timing (VVT to a compression ignition engine. Valve train variability could offer one option to achieve the reduction goals of engine-out emissions and fuel consumption. The aim of this study was to investigate the effects on part load combustion and emission performance of internal exhaust gas recirculation (EGR by variable exhaust valve lift actuation using a cam-in-cam system, which is an electronically variable valve device with a variable inside cam retarded to about 30 degrees. Numerical simulation based on GT-POWER has been performed to predict the NOx reduction strategy at the part load operating point of 1200 rpm in a four-valve diesel engine. A GT-POWER model of a common-rail direct injection engine with internal EGR was built and verified with experimental data. As a result, large potential for reducing NOx emissions through the use of exhaust valve control has been identified. Namely, it is possible to utilize heat efficiently as recompression of retarded post injection with downscaled specification of the exhaust valve rather than the intake valve, even if the CIC V1 condition with a reduction of the exhaust valve has a higher internal EGR rate of about 2% compared to that of the CIC V2 condition.

Effective model development of internal auditors in the village financial institution

Science.gov (United States)

Arsana, I. M. M.; Sugiarta, I. N.

2018-01-01

Designing an effective audit system is complex and challenging, and a focus on examining how internal audit drive improvement in three core performance dimensions ethicality, efficiency, and effectiveness in organization is needed. The problem of research is how the desain model and peripheral of supporter of effective supervation Village Credit Institution? Research of objectives is yielding the desain model and peripheral of supporter of effective supervation Village Credit Institution. Method Research use data collecting technique interview, observation and enquette. Data analysis, data qualitative before analysed to be turned into quantitative data in the form of scale. Each variable made to become five classificat pursuant to scale of likert. Data analysed descriptively to find supervation level, Structural Equation Model (SEM) to find internal and eksternal factor. So that desain model supervation with descriptive analysis. Result of research desain model and peripheral of supporter of effective supervation Village Credit Institution. The conclusion desain model supported by three sub system: sub system institute yield body supervisor of Village Credit Institution, sub system standardization and working procedure yield standard operating procedure supervisor of Village Credit Institution, sub system education and training yield supervisor professional of Village Credit Institution.

Generalized latent variable modeling multilevel, longitudinal, and structural equation models

CERN Document Server

Skrondal, Anders; Rabe-Hesketh, Sophia

2004-01-01

This book unifies and extends latent variable models, including multilevel or generalized linear mixed models, longitudinal or panel models, item response or factor models, latent class or finite mixture models, and structural equation models.

Variable-angle total internal reflection fluorescence microscopy of intact cells of Arabidopsis thaliana

Directory of Open Access Journals (Sweden)

Kim Myung K

2011-09-01

Full Text Available Abstract Background Total internal reflection fluorescence microscopy (TIRFM is a powerful tool for observing fluorescently labeled molecules on the plasma membrane surface of animal cells. However, the utility of TIRFM in plant cell studies has been limited by the fact that plants have cell walls, thick peripheral layers surrounding the plasma membrane. Recently, a new technique known as variable-angle epifluorescence microscopy (VAEM was developed to circumvent this problem. However, the lack of a detailed analysis of the optical principles underlying VAEM has limited its applications in plant-cell biology. Results Here, we present theoretical and experimental evidence supporting the use of variable-angle TIRFM in observations of intact plant cells. We show that when total internal reflection occurs at the cell wall/cytosol interface with an appropriate angle of incidence, an evanescent wave field of constant depth is produced inside the cytosol. Results of experimental TIRFM observations of the dynamic behaviors of phototropin 1 (a membrane receptor protein and clathrin light chain (a vesicle coat protein support our theoretical analysis. Conclusions These findings demonstrate that variable-angle TIRFM is appropriate for quantitative live imaging of cells in intact tissues of Arabidopsis thaliana.

Modeling Internal Radiation Therapy

NARCIS (Netherlands)

van den Broek, Egon; Schouten, Theo E.; Pellegrini, M.; Fred, A.; Filipe, J.; Gamboa, H.

2011-01-01

A new technique is described to model (internal) radiation therapy. It is founded on morphological processing, in particular distance transforms. Its formal basis is presented as well as its implementation via the Fast Exact Euclidean Distance (FEED) transform. Its use for all variations of internal

TIMSS 2011 User Guide for the International Database. Supplement 3: Variables Derived from the Student, Home, Teacher, and School Questionnaire Data

Science.gov (United States)

Foy, Pierre, Ed.; Arora, Alka, Ed.; Stanco, Gabrielle M., Ed.

2013-01-01

This supplement contains documentation on all the derived variables contained in the TIMSS 2011 data files that are based on background questionnaire variables. These variables were used to report background data in the TIMSS 2011 International Results in Mathematics and TIMSS 2011 International Results in Science reports, and are made available…

Predicting Internalizing and Externalizing Symptoms in Children with ASD: Evaluation of a Contextual Model of Parental Factors

Science.gov (United States)

McRae, Elizabeth M.; Stoppelbein, Laura; O'Kelley, Sarah E.; Fite, Paula; Greening, Leilani

2018-01-01

Parental adjustment, parenting behaviors, and child routines have been linked to internalizing and externalizing child behavior. The purpose of the present study was to evaluate a comprehensive model examining relations among these variables in children with ASD and their parents. Based on Sameroff's Transactional Model of Development (Sameroff…

Diagnostic budget study of the internal variability in ensemble simulations of the Canadian RCM

Energy Technology Data Exchange (ETDEWEB)

Nikiema, Oumarou; Laprise, Rene [UQAM, Canadian Network for Regional Climate Modelling and Diagnostics, Centre ESCER, Departement des Sciences de la Terre et de l' Atmosphere, B.P. 8888, Montreal, QC (Canada)

2011-06-15

Due to the chaotic and nonlinear nature of the atmospheric dynamics, it is known that small differences in the initial conditions (IC) of models can grow and affect the simulation evolution. In this study, we perform a quantitative diagnostic budget calculation of the various diabatic and dynamical contributions to the time evolution and spatial distribution of internal variability (IV) in simulations with the nested Canadian Regional Climate Model. We establish prognostic budget equations of the IV for the potential temperature and the relative vorticity fields. For both of these variables, the IV equations present similar terms, notably terms relating to the transport of IV by ensemble-mean flow and to the covariance of fluctuations acting on the gradient of the ensemble-mean state. We show the skill of these equations to diagnose the IV that took place in an ensemble of 20 3-month (summer season) simulations that differed only in their IC. Our study suggests that the dominant terms responsible for the large increase of IV are either the covariance term involving the potential temperature fluctuations and diabatic heating fluctuations, or the covariance of inter-member fluctuations acting upon ensemble-mean gradients. Our results also show that, on average, the third-order terms are negligible, but they can become important when the IV is large. (orig.)

Modelling Inter-relationships among water, governance, human development variables in developing countries with Bayesian networks.

Science.gov (United States)

Dondeynaz, C.; Lopez-Puga, J.; Carmona-Moreno, C.

2012-04-01

Improving Water and Sanitation Services (WSS), being a complex and interdisciplinary issue, passes through collaboration and coordination of different sectors (environment, health, economic activities, governance, and international cooperation). This inter-dependency has been recognised with the adoption of the "Integrated Water Resources Management" principles that push for the integration of these various dimensions involved in WSS delivery to ensure an efficient and sustainable management. The understanding of these interrelations appears as crucial for decision makers in the water sector in particular in developing countries where WSS still represent an important leverage for livelihood improvement. In this framework, the Joint Research Centre of the European Commission has developed a coherent database (WatSan4Dev database) containing 29 indicators from environmental, socio-economic, governance and financial aid flows data focusing on developing countries (Celine et al, 2011 under publication). The aim of this work is to model the WatSan4Dev dataset using probabilistic models to identify the key variables influencing or being influenced by the water supply and sanitation access levels. Bayesian Network Models are suitable to map the conditional dependencies between variables and also allows ordering variables by level of influence on the dependent variable. Separated models have been built for water supply and for sanitation because of different behaviour. The models are validated if complying with statistical criteria but either with scientific knowledge and literature. A two steps approach has been adopted to build the structure of the model; Bayesian network is first built for each thematic cluster of variables (e.g governance, agricultural pressure, or human development) keeping a detailed level for interpretation later one. A global model is then built based on significant indicators of each cluster being previously modelled. The structure of the

Defining a Family of Cognitive Diagnosis Models Using Log-Linear Models with Latent Variables

Science.gov (United States)

Henson, Robert A.; Templin, Jonathan L.; Willse, John T.

2009-01-01

This paper uses log-linear models with latent variables (Hagenaars, in "Loglinear Models with Latent Variables," 1993) to define a family of cognitive diagnosis models. In doing so, the relationship between many common models is explicitly defined and discussed. In addition, because the log-linear model with latent variables is a general model for…

On the explaining-away phenomenon in multivariate latent variable models.

Science.gov (United States)

van Rijn, Peter; Rijmen, Frank

2015-02-01

Many probabilistic models for psychological and educational measurements contain latent variables. Well-known examples are factor analysis, item response theory, and latent class model families. We discuss what is referred to as the 'explaining-away' phenomenon in the context of such latent variable models. This phenomenon can occur when multiple latent variables are related to the same observed variable, and can elicit seemingly counterintuitive conditional dependencies between latent variables given observed variables. We illustrate the implications of explaining away for a number of well-known latent variable models by using both theoretical and real data examples. © 2014 The British Psychological Society.

Obligations, internalization, and excuse making: integrating the triangle model and self-determination theory.

Science.gov (United States)

Sheldon, Kennon M; Schachtman, Todd R

2007-04-01

Schlenker's triangle model (Schlenker, Britt, Pennington, Murphy, & Doherty, 1994, Schlenker, Pontari, & Christopher, 2001) identifies three excuses people use to avoid taking responsibility after failure: that one had no control in the situation, that the obligation was unclear, and that it was not really one's obligation. Three retrospective studies tested the presumed negative association between excuse making and responsibility taking. The studies also examined the effects of self-determination theory's concept of motivational internalization (Deci & Ryan, 2000) upon these variables. A complex but replicable pattern emerged, such that responsibility taking and motivational internalization correlated with adaptive outcomes such as future commitment and positive expectancy and excuse making did not. Of particular interest, perceiving that the person levying the obligation internalized motivation predicted responsibility taking, in all three studies. Implications for the triangle model, as well as for theories of maturity and personality development, are considered.

The practical engineer-fine-tuning memory macros using variable internal delays

CERN Document Server

Gray, K

1999-01-01

Embedded memory blocks are extremely common in application-specific IC (ASIC) chips. In this era of design reuse, it is critical that these memory macros, as they are also called, should be as versatile as possible. Their $9 performance should be optimal, with adequate sense amplifier signal over the full manufacturing process range of the chip. Fortunately, several simple techniques exist for adapting memory macros to different applications running at $9 different speeds. The key is to design in delays that are variable and/or programmable. The approach is also helpful in debugging initial hardware where a memory macro is refusing to function because its timing is too fast and there $9 is insufficient internal delay for proper circuit operation. The techniques can also eliminate the process of redesigning and refabricating the initial hardware just to characterize it. A memory macro is made to function by internal $9 pulses, generated in the correct number, sequence and relationship by the internal timing ch...

International energy market dynamics: a modelling approach. Tome 1

International Nuclear Information System (INIS)

Nachet, S.

1996-01-01

This work is an attempt to model international energy market and reproduce the behaviour of both energy demand and supply. Energy demand was represented using sector versus source approach. For developing countries, existing link between economic and energy sectors were analysed. Energy supply is exogenous for energy sources other than oil and natural gas. For hydrocarbons, exploration-production process was modelled and produced figures as production yield, exploration effort index, etc. The model built is econometric and is solved using a software that was constructed for this purpose. We explore the energy market future using three scenarios and obtain projections by 2010 for energy demand per source and oil natural gas supply per region. Economic variables are used to produce different indicators as energy intensity, energy per capita, etc. (author). 378 refs., 26 figs., 35 tabs., 11 appends

International energy market dynamics: a modelling approach. Tome 2

International Nuclear Information System (INIS)

Nachet, S.

1996-01-01

This work is an attempt to model international energy market and reproduce the behaviour of both energy demand and supply. Energy demand was represented using sector versus source approach. For developing countries, existing link between economic and energy sectors were analysed. Energy supply is exogenous for energy sources other than oil and natural gas. For hydrocarbons, exploration-production process was modelled and produced figures as production yield, exploration effort index, ect. The model build is econometric and is solved using a software that was constructed for this purpose. We explore the energy market future using three scenarios and obtain projections by 2010 for energy demand per source and oil and natural gas supply per region. Economic variables are used to produce different indicators as energy intensity, energy per capita, etc. (author). 378 refs., 26 figs., 35 tabs., 11 appends

Proposal of a socio-cognitive-behavioral structural equation model of internalized stigma in people with severe and persistent mental illness.

Science.gov (United States)

Muñoz, Manuel; Sanz, María; Pérez-Santos, Eloísa; Quiroga, María de Los Ángeles

2011-04-30

The social stigma of mental illness has received much attention in recent years and its effects on diverse variables such as psychiatric symptoms, social functioning, self-esteem, self-efficacy, quality of life, and social integration are well established. However, internalized stigma in people with severe and persistent mental illness has not received the same attention. The aim of the present work was to study the relationships between the principal variables involved in the functioning of internalized stigma (sociodemographic and clinical variables, social stigma, psychosocial functioning, recovery expectations, empowerment, and discrimination experiences) in a sample of people with severe and persistent mental illness (N=108). The main characteristics of the sample and the differences between groups with high and low internalized stigma were analyzed, a correlation analysis of the variables was performed, and a structural equation model, integrating variables of social, cognitive, and behavioral content, was proposed and tested. The results indicate the relationships among social stigma, discrimination experiences, recovery expectation, and internalized stigma and their role in the psychosocial and behavioral outcomes in schizophrenia spectrum disorders. Copyright © 2010 Elsevier Ireland Ltd. All rights reserved.

Linear latent variable models: the lava-package

DEFF Research Database (Denmark)

Holst, Klaus Kähler; Budtz-Jørgensen, Esben

2013-01-01

are implemented including robust standard errors for clustered correlated data, multigroup analyses, non-linear parameter constraints, inference with incomplete data, maximum likelihood estimation with censored and binary observations, and instrumental variable estimators. In addition an extensive simulation......An R package for specifying and estimating linear latent variable models is presented. The philosophy of the implementation is to separate the model specification from the actual data, which leads to a dynamic and easy way of modeling complex hierarchical structures. Several advanced features...

Gait variability: methods, modeling and meaning

Directory of Open Access Journals (Sweden)

Hausdorff Jeffrey M

2005-07-01

Full Text Available Abstract The study of gait variability, the stride-to-stride fluctuations in walking, offers a complementary way of quantifying locomotion and its changes with aging and disease as well as a means of monitoring the effects of therapeutic interventions and rehabilitation. Previous work has suggested that measures of gait variability may be more closely related to falls, a serious consequence of many gait disorders, than are measures based on the mean values of other walking parameters. The Current JNER series presents nine reports on the results of recent investigations into gait variability. One novel method for collecting unconstrained, ambulatory data is reviewed, and a primer on analysis methods is presented along with a heuristic approach to summarizing variability measures. In addition, the first studies of gait variability in animal models of neurodegenerative disease are described, as is a mathematical model of human walking that characterizes certain complex (multifractal features of the motor control's pattern generator. Another investigation demonstrates that, whereas both healthy older controls and patients with a higher-level gait disorder walk more slowly in reduced lighting, only the latter's stride variability increases. Studies of the effects of dual tasks suggest that the regulation of the stride-to-stride fluctuations in stride width and stride time may be influenced by attention loading and may require cognitive input. Finally, a report of gait variability in over 500 subjects, probably the largest study of this kind, suggests how step width variability may relate to fall risk. Together, these studies provide new insights into the factors that regulate the stride-to-stride fluctuations in walking and pave the way for expanded research into the control of gait and the practical application of measures of gait variability in the clinical setting.

Multi-wheat-model ensemble responses to interannual climatic variability

DEFF Research Database (Denmark)

Ruane, A C; Hudson, N I; Asseng, S

2016-01-01

We compare 27 wheat models' yield responses to interannual climate variability, analyzed at locations in Argentina, Australia, India, and The Netherlands as part of the Agricultural Model Intercomparison and Improvement Project (AgMIP) Wheat Pilot. Each model simulated 1981–2010 grain yield, and ......-term warming, suggesting that additional processes differentiate climate change impacts from observed climate variability analogs and motivating continuing analysis and model development efforts.......We compare 27 wheat models' yield responses to interannual climate variability, analyzed at locations in Argentina, Australia, India, and The Netherlands as part of the Agricultural Model Intercomparison and Improvement Project (AgMIP) Wheat Pilot. Each model simulated 1981–2010 grain yield, and we...... evaluate results against the interannual variability of growing season temperature, precipitation, and solar radiation. The amount of information used for calibration has only a minor effect on most models' climate response, and even small multi-model ensembles prove beneficial. Wheat model clusters reveal...

Multi-Wheat-Model Ensemble Responses to Interannual Climate Variability

Science.gov (United States)

Ruane, Alex C.; Hudson, Nicholas I.; Asseng, Senthold; Camarrano, Davide; Ewert, Frank; Martre, Pierre; Boote, Kenneth J.; Thorburn, Peter J.; Aggarwal, Pramod K.; Angulo, Carlos

2016-01-01

We compare 27 wheat models' yield responses to interannual climate variability, analyzed at locations in Argentina, Australia, India, and The Netherlands as part of the Agricultural Model Intercomparison and Improvement Project (AgMIP) Wheat Pilot. Each model simulated 1981e2010 grain yield, and we evaluate results against the interannual variability of growing season temperature, precipitation, and solar radiation. The amount of information used for calibration has only a minor effect on most models' climate response, and even small multi-model ensembles prove beneficial. Wheat model clusters reveal common characteristics of yield response to climate; however models rarely share the same cluster at all four sites indicating substantial independence. Only a weak relationship (R2 0.24) was found between the models' sensitivities to interannual temperature variability and their response to long-termwarming, suggesting that additional processes differentiate climate change impacts from observed climate variability analogs and motivating continuing analysis and model development efforts.

Are revised models better models? A skill score assessment of regional interannual variability

Science.gov (United States)

Sperber, Kenneth R.; Participating AMIP Modelling Groups

1999-05-01

Various skill scores are used to assess the performance of revised models relative to their original configurations. The interannual variability of all-India, Sahel and Nordeste rainfall and summer monsoon windshear is examined in integrations performed under the experimental design of the Atmospheric Model Intercomparison Project. For the indices considered, the revised models exhibit greater fidelity at simulating the observed interannual variability. Interannual variability of all-India rainfall is better simulated by models that have a more realistic rainfall climatology in the vicinity of India, indicating the beneficial effect of reducing systematic model error.

Coevolution of variability models and related software artifacts

DEFF Research Database (Denmark)

Passos, Leonardo; Teixeira, Leopoldo; Dinztner, Nicolas

2015-01-01

models coevolve with other artifact types, we study a large and complex real-world variant-rich software system: the Linux kernel. Specifically, we extract variability-coevolution patterns capturing changes in the variability model of the Linux kernel with subsequent changes in Makefiles and C source...

Variable selection in Logistic regression model with genetic algorithm.

Science.gov (United States)

Zhang, Zhongheng; Trevino, Victor; Hoseini, Sayed Shahabuddin; Belciug, Smaranda; Boopathi, Arumugam Manivanna; Zhang, Ping; Gorunescu, Florin; Subha, Velappan; Dai, Songshi

2018-02-01

Variable or feature selection is one of the most important steps in model specification. Especially in the case of medical-decision making, the direct use of a medical database, without a previous analysis and preprocessing step, is often counterproductive. In this way, the variable selection represents the method of choosing the most relevant attributes from the database in order to build a robust learning models and, thus, to improve the performance of the models used in the decision process. In biomedical research, the purpose of variable selection is to select clinically important and statistically significant variables, while excluding unrelated or noise variables. A variety of methods exist for variable selection, but none of them is without limitations. For example, the stepwise approach, which is highly used, adds the best variable in each cycle generally producing an acceptable set of variables. Nevertheless, it is limited by the fact that it commonly trapped in local optima. The best subset approach can systematically search the entire covariate pattern space, but the solution pool can be extremely large with tens to hundreds of variables, which is the case in nowadays clinical data. Genetic algorithms (GA) are heuristic optimization approaches and can be used for variable selection in multivariable regression models. This tutorial paper aims to provide a step-by-step approach to the use of GA in variable selection. The R code provided in the text can be extended and adapted to other data analysis needs.

TEC variability near northern EIA crest and comparison with IRI model

Science.gov (United States)

Aggarwal, Malini

2011-10-01

Monthly median values of hourly total electron content (TEC) is obtained with GPS at a station near northern anomaly crest, Rajkot (geog. 22.29°N, 70.74°E; geomag. 14.21°N, 144.9°E) to study the variability of low latitude ionospheric behavior during low solar activity period (April 2005 to March 2006). The TEC exhibit characteristic features like day-to-day variability, semiannual anomaly and noon bite out. The observed TEC is compared with latest International Reference Ionosphere (IRI) - 2007 model using options of topside electron density, NeQuick, IRI01-corr and IRI-2001 by using both URSI and CCIR coefficients. A good agreement of observed and predicted TEC is found during the daytime with underestimation at other times. The predicted TEC by NeQuick and IRI01-corr is closer to the observed TEC during the daytime whereas during nighttime and morning hours, IRI-2001 shows lesser discrepancy in all seasons by both URSI and CCIR coefficients.

Improved variable reduction in partial least squares modelling by Global-Minimum Error Uninformative-Variable Elimination.

Science.gov (United States)

Andries, Jan P M; Vander Heyden, Yvan; Buydens, Lutgarde M C

2017-08-22

The calibration performance of Partial Least Squares regression (PLS) can be improved by eliminating uninformative variables. For PLS, many variable elimination methods have been developed. One is the Uninformative-Variable Elimination for PLS (UVE-PLS). However, the number of variables retained by UVE-PLS is usually still large. In UVE-PLS, variable elimination is repeated as long as the root mean squared error of cross validation (RMSECV) is decreasing. The set of variables in this first local minimum is retained. In this paper, a modification of UVE-PLS is proposed and investigated, in which UVE is repeated until no further reduction in variables is possible, followed by a search for the global RMSECV minimum. The method is called Global-Minimum Error Uninformative-Variable Elimination for PLS, denoted as GME-UVE-PLS or simply GME-UVE. After each iteration, the predictive ability of the PLS model, built with the remaining variable set, is assessed by RMSECV. The variable set with the global RMSECV minimum is then finally selected. The goal is to obtain smaller sets of variables with similar or improved predictability than those from the classical UVE-PLS method. The performance of the GME-UVE-PLS method is investigated using four data sets, i.e. a simulated set, NIR and NMR spectra, and a theoretical molecular descriptors set, resulting in twelve profile-response (X-y) calibrations. The selective and predictive performances of the models resulting from GME-UVE-PLS are statistically compared to those from UVE-PLS and 1-step UVE, one-sided paired t-tests. The results demonstrate that variable reduction with the proposed GME-UVE-PLS method, usually eliminates significantly more variables than the classical UVE-PLS, while the predictive abilities of the resulting models are better. With GME-UVE-PLS, a lower number of uninformative variables, without a chemical meaning for the response, may be retained than with UVE-PLS. The selectivity of the classical UVE method

From Transition Systems to Variability Models and from Lifted Model Checking Back to UPPAAL

DEFF Research Database (Denmark)

Dimovski, Aleksandar; Wasowski, Andrzej

2017-01-01

efficient lifted (family-based) model checking for real-time variability models. This reduces the cost of maintaining specialized family-based real-time model checkers. Real-time variability models can be model checked using the standard UPPAAL. We have implemented abstractions as syntactic source...

Robust control of chaos in Chua's circuit based on internal model principle

International Nuclear Information System (INIS)

Lee, Keum W.; Singh, Sahjendra N.

2007-01-01

The paper treats the question of robust control of chaos in Chua's circuit based on the internal model principle. The Chua's diode has polynomial non-linearity and it is assumed that the parameters of the circuit are not known. A robust control law for the asymptotic regulation of the output (node voltage) along constant and sinusoidal reference trajectories is derived. For the derivation of the control law, the non-linear regulator equations are solved to obtain a manifold in the state space on which the output error is zero and an internal model of the k-fold exosystem (k = 3 here) is constructed. Then a feedback control law using the optimal control theory or pole placement technique for the stabilization of the augmented system including the Chua's circuit and the internal model is derived. In the closed-loop system, robust output node voltage trajectory tracking of sinusoidal and constant reference trajectories are accomplished and in the steady state, the remaining state variables converge to periodic and constant trajectories, respectively. Simulation results are presented which show that in the closed-loop system, asymptotic trajectory control, disturbance rejection and suppression of chaotic motion in spite of uncertainties in the system are accomplished

Model-based internal wave processing

Energy Technology Data Exchange (ETDEWEB)

Candy, J.V.; Chambers, D.H.

1995-06-09

A model-based approach is proposed to solve the oceanic internal wave signal processing problem that is based on state-space representations of the normal-mode vertical velocity and plane wave horizontal velocity propagation models. It is shown that these representations can be utilized to spatially propagate the modal (dept) vertical velocity functions given the basic parameters (wave numbers, Brunt-Vaisala frequency profile etc.) developed from the solution of the associated boundary value problem as well as the horizontal velocity components. Based on this framework, investigations are made of model-based solutions to the signal enhancement problem for internal waves.

The meganism behind internally generated centennial-to-millennial scale climate variability in an earth system model of intermediate complexity

NARCIS (Netherlands)

Friedrich, T.; Timmermann, A.; Menviel, L.; Elison Timm, O.; Mouchet, A.; Roche, D.M.V.A.P.

2010-01-01

The mechanism triggering centennial-to-millennial-scale variability of the Atlantic Meridional Overturning Circulation (AMOC) in the earth system model of intermediate complexity LOVECLIM is investigated. It is found that for several climate boundary conditions such as low obliquity values (∼22.1 )

Spatial variability and parametric uncertainty in performance assessment models

International Nuclear Information System (INIS)

Pensado, Osvaldo; Mancillas, James; Painter, Scott; Tomishima, Yasuo

2011-01-01

The problem of defining an appropriate treatment of distribution functions (which could represent spatial variability or parametric uncertainty) is examined based on a generic performance assessment model for a high-level waste repository. The generic model incorporated source term models available in GoldSim ® , the TDRW code for contaminant transport in sparse fracture networks with a complex fracture-matrix interaction process, and a biosphere dose model known as BDOSE TM . Using the GoldSim framework, several Monte Carlo sampling approaches and transport conceptualizations were evaluated to explore the effect of various treatments of spatial variability and parametric uncertainty on dose estimates. Results from a model employing a representative source and ensemble-averaged pathway properties were compared to results from a model allowing for stochastic variation of transport properties along streamline segments (i.e., explicit representation of spatial variability within a Monte Carlo realization). We concluded that the sampling approach and the definition of an ensemble representative do influence consequence estimates. In the examples analyzed in this paper, approaches considering limited variability of a transport resistance parameter along a streamline increased the frequency of fast pathways resulting in relatively high dose estimates, while those allowing for broad variability along streamlines increased the frequency of 'bottlenecks' reducing dose estimates. On this basis, simplified approaches with limited consideration of variability may suffice for intended uses of the performance assessment model, such as evaluation of site safety. (author)

Model Parameter Variability for Enhanced Anaerobic Bioremediation of DNAPL Source Zones

Science.gov (United States)

Mao, X.; Gerhard, J. I.; Barry, D. A.

2005-12-01

The objective of the Source Area Bioremediation (SABRE) project, an international collaboration of twelve companies, two government agencies and three research institutions, is to evaluate the performance of enhanced anaerobic bioremediation for the treatment of chlorinated ethene source areas containing dense, non-aqueous phase liquids (DNAPL). This 4-year, 5.7 million dollars research effort focuses on a pilot-scale demonstration of enhanced bioremediation at a trichloroethene (TCE) DNAPL field site in the United Kingdom, and includes a significant program of laboratory and modelling studies. Prior to field implementation, a large-scale, multi-laboratory microcosm study was performed to determine the optimal system properties to support dehalogenation of TCE in site soil and groundwater. This statistically-based suite of experiments measured the influence of key variables (electron donor, nutrient addition, bioaugmentation, TCE concentration and sulphate concentration) in promoting the reductive dechlorination of TCE to ethene. As well, a comprehensive biogeochemical numerical model was developed for simulating the anaerobic dehalogenation of chlorinated ethenes. An appropriate (reduced) version of this model was combined with a parameter estimation method based on fitting of the experimental results. Each of over 150 individual microcosm calibrations involved matching predicted and observed time-varying concentrations of all chlorinated compounds. This study focuses on an analysis of this suite of fitted model parameter values. This includes determining the statistical correlation between parameters typically employed in standard Michaelis-Menten type rate descriptions (e.g., maximum dechlorination rates, half-saturation constants) and the key experimental variables. The analysis provides insight into the degree to which aqueous phase TCE and cis-DCE inhibit dechlorination of less-chlorinated compounds. Overall, this work provides a database of the numerical

Preliminary Multi-Variable Cost Model for Space Telescopes

Science.gov (United States)

Stahl, H. Philip; Hendrichs, Todd

2010-01-01

Parametric cost models are routinely used to plan missions, compare concepts and justify technology investments. This paper reviews the methodology used to develop space telescope cost models; summarizes recently published single variable models; and presents preliminary results for two and three variable cost models. Some of the findings are that increasing mass reduces cost; it costs less per square meter of collecting aperture to build a large telescope than a small telescope; and technology development as a function of time reduces cost at the rate of 50% per 17 years.

Internal Universes in Models of Homotopy Type Theory

DEFF Research Database (Denmark)

Licata, Daniel R.; Orton, Ian; Pitts, Andrew M.

2018-01-01

We show that universes of fibrations in various models of homotopy type theory have an essentially global character: they cannot be described in the internal language of the presheaf topos from which the model is constructed. We get around this problem by extending the internal language with a mo...... that the interval in cubical sets does indeed have. This leads to a completely internal development of models of homotopy type theory within what we call crisp type theory.......We show that universes of fibrations in various models of homotopy type theory have an essentially global character: they cannot be described in the internal language of the presheaf topos from which the model is constructed. We get around this problem by extending the internal language...

A holistic model of behavioural branding: The role of employee behaviours and internal branding

DEFF Research Database (Denmark)

Mazzei, Alessandra; Ravazzani, Silvia

2015-01-01

consistent meaning during the interaction with customers. It reviews the literature about behavioural branding and its antecedents, mediating variables and consequences in order to develop a holistic model of the inside-out brand building process, rooted in the theoretical perspectives of proactive...... behaviours, hierarchy of effects and planned behaviour. The paper concludes with a reflection on the role of internal branding in eliciting and managing employee brand consistent behaviours, and with avenues for future empirical research aimed to verify the model, its constructs and related measures....

The International Reference Ionosphere 2012 – a model of international collaboration☆

Directory of Open Access Journals (Sweden)

Bilitza Dieter

2014-02-01

Full Text Available The International Reference Ionosphere (IRI project was established jointly by the Committee on Space Research (COSPAR and the International Union of Radio Science (URSI in the late sixties with the goal to develop an international standard for the specification of plasma parameters in the Earth’s ionosphere. COSPAR needed such a specification for the evaluation of environmental effects on spacecraft and experiments in space, and URSI for radiowave propagation studies and applications. At the request of COSPAR and URSI, IRI was developed as a data-based model to avoid the uncertainty of theory-based models which are only as good as the evolving theoretical understanding. Being based on most of the available and reliable observations of the ionospheric plasma from the ground and from space, IRI describes monthly averages of electron density, electron temperature, ion temperature, ion composition, and several additional parameters in the altitude range from 60 km to 2000 km. A working group of about 50 international ionospheric experts is in charge of developing and improving the IRI model. Over time as new data became available and new modeling techniques emerged, steadily improved editions of the IRI model have been published. This paper gives a brief history of the IRI project and describes the latest version of the model, IRI-2012. It also briefly discusses efforts to develop a real-time IRI model. The IRI homepage is at http://IRImodel.org.

Research on climate change and variability at the Ab dus Salam International Centre for Theoretical Physics

International Nuclear Information System (INIS)

Giorgi, F.; Molteni, F.

2002-01-01

The Physics of Weather and Climate Section at the Abdus Salam International Centre for Theoretical Physics, established in 1998, is currently performing research on different aspects of climate variability, dealing with both natural and anthropogenic aspects of climate changes. In addition to performing diagnostic work on multi-decadal observational datasets and climate simulations carried out in major research centres, the PWC section has been developing its own climate modeling capability, which is focused on three main areas: a) modeling of regional climate change; b) seasonal forecasting at global and regional scale; c) development of simplified models of the general circulation. On topic a), research on different aspects of anthropogenic climate change is being carried out using the Regional Climate (RegCM) developed by Giorgi and collaborators at the National Centre for Atmospheric Research. Time-slice experiments with a high-resolution atmospheric GCM, comparing current climate conditions with future climate scenarios in selected decades, are also planned for the near future. On topic b), a strategy based on ensembles of high-resolution simulations with atmospheric GCM's, using sea surface temperature anomalies predicted by lower-resolution coupled models from other institutions, is currently under experimentation. A one-way nesting of RegCM into the GCM simulations will also be tested. On item c), a 5-layer atmospheric GCM with simplified physical parameterizations has been developed. This model has a very small computational cost compared with state-of-the-art GCMs, and is suitable for studies of natural climate variability on inter-decadal and intercentennial time scales. It is planned to couple this model to simplified ocean models of different complexity, from a simple, static mixed layer model, to simplified models of the tropical Pacific circulation suited to the simulation of the El Nino phenomenon. A joint project with the IAEA-MEL Laboratory in

Analysis models for variables associated with breastfeeding duration

Directory of Open Access Journals (Sweden)

Edson Theodoro dos S. Neto

2013-09-01

Full Text Available OBJECTIVE To analyze the factors associated with breastfeeding duration by two statistical models. METHODS A population-based cohort study was conducted with 86 mothers and newborns from two areas primary covered by the National Health System, with high rates of infant mortality in Vitória, Espírito Santo, Brazil. During 30 months, 67 (78% children and mothers were visited seven times at home by trained interviewers, who filled out survey forms. Data on food and sucking habits, socioeconomic and maternal characteristics were collected. Variables were analyzed by Cox regression models, considering duration of breastfeeding as the dependent variable, and logistic regression (dependent variables, was the presence of a breastfeeding child in different post-natal ages. RESULTS In the logistic regression model, the pacifier sucking (adjusted Odds Ratio: 3.4; 95%CI 1.2-9.55 and bottle feeding (adjusted Odds Ratio: 4.4; 95%CI 1.6-12.1 increased the chance of weaning a child before one year of age. Variables associated to breastfeeding duration in the Cox regression model were: pacifier sucking (adjusted Hazard Ratio 2.0; 95%CI 1.2-3.3 and bottle feeding (adjusted Hazard Ratio 2.0; 95%CI 1.2-3.5. However, protective factors (maternal age and family income differed between both models. CONCLUSIONS Risk and protective factors associated with cessation of breastfeeding may be analyzed by different models of statistical regression. Cox Regression Models are adequate to analyze such factors in longitudinal studies.

In search of control variables : A systems approach

NARCIS (Netherlands)

Dalenoort, GJ

1997-01-01

Motor processes cannot be modeled by a single (unified) model. Instead, a number of models at different levels of description are needed. The concepts of control and control variable only make sense at the functional level. A clear distinction must be made between external models and internal

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.

Understanding and forecasting polar stratospheric variability with statistical models

Directory of Open Access Journals (Sweden)

C. Blume

2012-07-01

Full Text Available The variability of the north-polar stratospheric vortex is a prominent aspect of the middle atmosphere. This work investigates a wide class of statistical models with respect to their ability to model geopotential and temperature anomalies, representing variability in the polar stratosphere. Four partly nonstationary, nonlinear models are assessed: linear discriminant analysis (LDA; a cluster method based on finite elements (FEM-VARX; a neural network, namely the multi-layer perceptron (MLP; and support vector regression (SVR. These methods model time series by incorporating all significant external factors simultaneously, including ENSO, QBO, the solar cycle, volcanoes, to then quantify their statistical importance. We show that variability in reanalysis data from 1980 to 2005 is successfully modeled. The period from 2005 to 2011 can be hindcasted to a certain extent, where MLP performs significantly better than the remaining models. However, variability remains that cannot be statistically hindcasted within the current framework, such as the unexpected major warming in January 2009. Finally, the statistical model with the best generalization performance is used to predict a winter 2011/12 with warm and weak vortex conditions. A vortex breakdown is predicted for late January, early February 2012.

Gaussian Mixture Model of Heart Rate Variability

Science.gov (United States)

Costa, Tommaso; Boccignone, Giuseppe; Ferraro, Mario

2012-01-01

Heart rate variability (HRV) is an important measure of sympathetic and parasympathetic functions of the autonomic nervous system and a key indicator of cardiovascular condition. This paper proposes a novel method to investigate HRV, namely by modelling it as a linear combination of Gaussians. Results show that three Gaussians are enough to describe the stationary statistics of heart variability and to provide a straightforward interpretation of the HRV power spectrum. Comparisons have been made also with synthetic data generated from different physiologically based models showing the plausibility of the Gaussian mixture parameters. PMID:22666386

Modern Gravity Models of Internal Migration. The Case of Romania

Directory of Open Access Journals (Sweden)

Daniela BUNEA

2012-04-01

Full Text Available Internal migration, although less investigated than international migration, is a key mechanism for adjustment to regional economic shocks, especially when other tools prove useless. But this process has very complex factors of determination which can be economic, social, demographic, environmental, etc. Based on previous international studies, in the case of Romania the robust variables proved to be the population size, the per capita gross domestic product, the road density, an amenity index and the crime rate from a static perspective, and the previous migration, the population size and the amenity index from a dynamic perspective. The techniques I have employed in making this study are the Least Square Dummy Variables (LSDV, or the fixed effects method and the Generalized Method of Moments (GMM, or the dynamic method both applied to panel data.

Verification of models for ballistic movement time and endpoint variability.

Science.gov (United States)

Lin, Ray F; Drury, Colin G

2013-01-01

A hand control movement is composed of several ballistic movements. The time required in performing a ballistic movement and its endpoint variability are two important properties in developing movement models. The purpose of this study was to test potential models for predicting these two properties. Twelve participants conducted ballistic movements of specific amplitudes using a drawing tablet. The measured data of movement time and endpoint variability were then used to verify the models. This study was successful with Hoffmann and Gan's movement time model (Hoffmann, 1981; Gan and Hoffmann 1988) predicting more than 90.7% data variance for 84 individual measurements. A new theoretically developed ballistic movement variability model, proved to be better than Howarth, Beggs, and Bowden's (1971) model, predicting on average 84.8% of stopping-variable error and 88.3% of aiming-variable errors. These two validated models will help build solid theoretical movement models and evaluate input devices. This article provides better models for predicting end accuracy and movement time of ballistic movements that are desirable in rapid aiming tasks, such as keying in numbers on a smart phone. The models allow better design of aiming tasks, for example button sizes on mobile phones for different user populations.

Parents' attachment histories and children's externalizing and internalizing behaviors: exploring family systems models of linkage.

Science.gov (United States)

Cowan, P A; Cowan, C P; Cohn, D A; Pearson, J L

1996-02-01

Twenty-seven mothers and 27 fathers were given the Adult Attachment Interview (M. Main & R. Goldwyn, in press) when their children were 3.5 years old. Continuous ratings of narrative coherence, probable experience quality (parents perceived as loving), and state of mind (current anger at parents) were entered as latent variables in partial least squares structural equation models that included observational measures of marital quality and parenting style. Models that include fathers' attachment histories predicted more variance in kindergarten teachers' descriptions of children's externalizing behavior, whereas models that include mothers' attachment histories predicted more variance in children's internalizing behavior. Marital data added predictive power to the equations. Discussion is focused on the importance of integrating attachment and family systems approaches, and of parents' gender and marital quality, in understanding specific links between parents' attachment histories and their young children's externalizing and internalizing behaviors.

Latent variable modeling%建立隐性变量模型

Institute of Scientific and Technical Information of China (English)

蔡力

2012-01-01

@@ A latent variable model, as the name suggests,is a statistical model that contains latent, that is, unobserved, variables.Their roots go back to Spearman's 1904 seminal work[1] on factor analysis,which is arguably the first well-articulated latent variable model to be widely used in psychology, mental health research, and allied disciplines.Because of the association of factor analysis with early studies of human intelligence, the fact that key variables in a statistical model are, on occasion, unobserved has been a point of lingering contention and controversy.The reader is assured, however, that a latent variable,defined in the broadest manner, is no more mysterious than an error term in a normal theory linear regression model or a random effect in a mixed model.

Galactic models with variable spiral structure

International Nuclear Information System (INIS)

James, R.A.; Sellwood, J.A.

1978-01-01

A series of three-dimensional computer simulations of disc galaxies has been run in which the self-consistent potential of the disc stars is supplemented by that arising from a small uniform Population II sphere. The models show variable spiral structure, which is more pronounced for thin discs. In addition, the thin discs form weak bars. In one case variable spiral structure associated with this bar has been seen. The relaxed discs are cool outside resonance regions. (author)

A variable-order fractal derivative model for anomalous diffusion

Directory of Open Access Journals (Sweden)

Liu Xiaoting

2017-01-01

Full Text Available This paper pays attention to develop a variable-order fractal derivative model for anomalous diffusion. Previous investigations have indicated that the medium structure, fractal dimension or porosity may change with time or space during solute transport processes, results in time or spatial dependent anomalous diffusion phenomena. Hereby, this study makes an attempt to introduce a variable-order fractal derivative diffusion model, in which the index of fractal derivative depends on temporal moment or spatial position, to characterize the above mentioned anomalous diffusion (or transport processes. Compared with other models, the main advantages in description and the physical explanation of new model are explored by numerical simulation. Further discussions on the dissimilitude such as computational efficiency, diffusion behavior and heavy tail phenomena of the new model and variable-order fractional derivative model are also offered.

Using internal discharge data in a distributed conceptual model to reduce uncertainty in streamflow simulations

Science.gov (United States)

Guerrero, J.; Halldin, S.; Xu, C.; Lundin, L.

2011-12-01

Distributed hydrological models are important tools in water management as they account for the spatial variability of the hydrological data, as well as being able to produce spatially distributed outputs. They can directly incorporate and assess potential changes in the characteristics of our basins. A recognized problem for models in general is equifinality, which is only exacerbated for distributed models who tend to have a large number of parameters. We need to deal with the fundamentally ill-posed nature of the problem that such models force us to face, i.e. a large number of parameters and very few variables that can be used to constrain them, often only the catchment discharge. There is a growing but yet limited literature showing how the internal states of a distributed model can be used to calibrate/validate its predictions. In this paper, a distributed version of WASMOD, a conceptual rainfall runoff model with only three parameters, combined with a routing algorithm based on the high-resolution HydroSHEDS data was used to simulate the discharge in the Paso La Ceiba basin in Honduras. The parameter space was explored using Monte-Carlo simulations and the region of space containing the parameter-sets that were considered behavioral according to two different criteria was delimited using the geometric concept of alpha-shapes. The discharge data from five internal sub-basins was used to aid in the calibration of the model and to answer the following questions: Can this information improve the simulations at the outlet of the catchment, or decrease their uncertainty? Also, after reducing the number of model parameters needing calibration through sensitivity analysis: Is it possible to relate them to basin characteristics? The analysis revealed that in most cases the internal discharge data can be used to reduce the uncertainty in the discharge at the outlet, albeit with little improvement in the overall simulation results.

Higher-dimensional cosmological model with variable gravitational ...

Indian Academy of Sciences (India)

We have studied five-dimensional homogeneous cosmological models with variable and bulk viscosity in Lyra geometry. Exact solutions for the field equations have been obtained and physical properties of the models are discussed. It has been observed that the results of new models are well within the observational ...

Multi-scale climate modelling over Southern Africa using a variable-resolution global model

CSIR Research Space (South Africa)

Engelbrecht, FA

2011-12-01

Full Text Available -mail: fengelbrecht@csir.co.za Multi-scale climate modelling over Southern Africa using a variable-resolution global model FA Engelbrecht1, 2*, WA Landman1, 3, CJ Engelbrecht4, S Landman5, MM Bopape1, B Roux6, JL McGregor7 and M Thatcher7 1 CSIR Natural... improvement. Keywords: multi-scale climate modelling, variable-resolution atmospheric model Introduction Dynamic climate models have become the primary tools for the projection of future climate change, at both the global and regional scales. Dynamic...

Modelling the co-evolution of indirect genetic effects and inherited variability.

Science.gov (United States)

Marjanovic, Jovana; Mulder, Han A; Rönnegård, Lars; Bijma, Piter

2018-03-28

When individuals interact, their phenotypes may be affected not only by their own genes but also by genes in their social partners. This phenomenon is known as Indirect Genetic Effects (IGEs). In aquaculture species and some plants, however, competition not only affects trait levels of individuals, but also inflates variability of trait values among individuals. In the field of quantitative genetics, the variability of trait values has been studied as a quantitative trait in itself, and is often referred to as inherited variability. Such studies, however, consider only the genetic effect of the focal individual on trait variability and do not make a connection to competition. Although the observed phenotypic relationship between competition and variability suggests an underlying genetic relationship, the current quantitative genetic models of IGE and inherited variability do not allow for such a relationship. The lack of quantitative genetic models that connect IGEs to inherited variability limits our understanding of the potential of variability to respond to selection, both in nature and agriculture. Models of trait levels, for example, show that IGEs may considerably change heritable variation in trait values. Currently, we lack the tools to investigate whether this result extends to variability of trait values. Here we present a model that integrates IGEs and inherited variability. In this model, the target phenotype, say growth rate, is a function of the genetic and environmental effects of the focal individual and of the difference in trait value between the social partner and the focal individual, multiplied by a regression coefficient. The regression coefficient is a genetic trait, which is a measure of cooperation; a negative value indicates competition, a positive value cooperation, and an increasing value due to selection indicates the evolution of cooperation. In contrast to the existing quantitative genetic models, our model allows for co-evolution of

MODEL EVALUASI INTERNAL KOMPETENSI GURU BAHASA INGGRIS (MODEL_EIKGBI SMA

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Sahraini Sahraini

2015-10-01

Full Text Available Studi ini bertujuan untuk: (1 mengembangkan model evaluasi kompetensi guru bahasa Inggris SMA yang dapat digunakan untuk mengidentifikasi kelebihan dan kekurangan guru dalam proses pemelajaran dan (2 mengetahui efektivitas implementasi evaluasi internal kompetensi guru bahasa Inggris SMA. Studi ini menggunakan metode penelitian dan pengembangan yang dikembangkan oleh Borg & Gall (1983, p.775. Subjek penelitian berjumlah 17 guru yang berasal dari 7 SMA di Sulawesi Selatan. Konstruk instrumen terdiri atas instrumen untuk mengevaluasi kompetensi guru bahasa Inggris dalam merencanakan pemelajaran, instrumen untuk mengevaluasi kompetensi guru dalam melaksanaan proses pemelajaran, dan instrumen untuk mengevaluai kompetensi guru dalam mengevaluasi hasil proses pemelajaran. Hasil penelitian menunjukkan bahwa instrumen yang dikembangkan dapat digunakan untuk mengevaluasi kompetensi guru bahasa Inggris. Untuk mengetahui sejauh mana tingkat efektivitas Model Evaluasi Internal Kompetensi Guru Bahasa Inggris SMA, model ini kemudian dievaluasi oleh teman sejawat guru bahasa Inggris dan guru bahasa Inggris itu sendiri. Mereka menyimpulkan bahwa komponen dari model tersebut adalah komprehensip, praktis, ekonomis, dan telah didukung oleh instrumen yang valid dan reliabel. Kata kunci: evaluasi internal, model evaluasi, kompetensi guru   INTERNAL EVALUATION MODEL OF ENGLISH TEACHERS’ COMPETENCY (IEMET FOR SENIOR HIGH SCHOOL Abstract High School that can be used to identify the teacher’s strengths and weaknesses in learning and teaching processes and (2 find out the implementation effectiveness of the Internal Evaluation Model of English Teachers’ Competency for Senior High School. This study used research & development methods by following the pattern of phases developed by Borg & Gall (1983, p.775.  The subjects of this study were seventeen English teachers from seven Senior High Schools in South Sulawesi. The constructs of instruments consist of the

Variable Renewable Energy in Long-Term Planning Models: A Multi-Model Perspective

Energy Technology Data Exchange (ETDEWEB)

Cole, Wesley [National Renewable Energy Lab. (NREL), Golden, CO (United States); Frew, Bethany [National Renewable Energy Lab. (NREL), Golden, CO (United States); Mai, Trieu [National Renewable Energy Lab. (NREL), Golden, CO (United States); Sun, Yinong [National Renewable Energy Lab. (NREL), Golden, CO (United States); Bistline, John [Electric Power Research Inst. (EPRI), Knoxville, TN (United States); Blanford, Geoffrey [Electric Power Research Inst. (EPRI), Knoxville, TN (United States); Young, David [Electric Power Research Inst. (EPRI), Knoxville, TN (United States); Marcy, Cara [U.S. Energy Information Administration, Washington, DC (United States); Namovicz, Chris [U.S. Energy Information Administration, Washington, DC (United States); Edelman, Risa [US Environmental Protection Agency (EPA), Washington, DC (United States); Meroney, Bill [US Environmental Protection Agency (EPA), Washington, DC (United States); Sims, Ryan [US Environmental Protection Agency (EPA), Washington, DC (United States); Stenhouse, Jeb [US Environmental Protection Agency (EPA), Washington, DC (United States); Donohoo-Vallett, Paul [Dept. of Energy (DOE), Washington DC (United States)

2017-11-01

Long-term capacity expansion models of the U.S. electricity sector have long been used to inform electric sector stakeholders and decision-makers. With the recent surge in variable renewable energy (VRE) generators — primarily wind and solar photovoltaics — the need to appropriately represent VRE generators in these long-term models has increased. VRE generators are especially difficult to represent for a variety of reasons, including their variability, uncertainty, and spatial diversity. This report summarizes the analyses and model experiments that were conducted as part of two workshops on modeling VRE for national-scale capacity expansion models. It discusses the various methods for treating VRE among four modeling teams from the Electric Power Research Institute (EPRI), the U.S. Energy Information Administration (EIA), the U.S. Environmental Protection Agency (EPA), and the National Renewable Energy Laboratory (NREL). The report reviews the findings from the two workshops and emphasizes the areas where there is still need for additional research and development on analysis tools to incorporate VRE into long-term planning and decision-making. This research is intended to inform the energy modeling community on the modeling of variable renewable resources, and is not intended to advocate for or against any particular energy technologies, resources, or policies.

Modelling and Internal Fuzzy Model Power Control of a Francis Water Turbine

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Klemen Nagode

2014-02-01

Full Text Available This paper presents dynamic modelling of a Francis turbine with a surge tank and the control of a hydro power plant (HPP. Non-linear and linear models include technical parameters and show high similarity to measurement data. Turbine power control with an internal model control (IMC is proposed, based on a turbine fuzzy model. Considering appropriate control responses in the entire area of turbine power, the model parameters of the process are determined from a fuzzy model, which are further included in the internal model controller. The results are compared to a proportional-integral (PI controller tuned with an integral absolute error (IAE objective function, and show an improved response of internal model control.

The Theory of Thermodynamic Systems with Internal Variables of State: Necessary and Sufficient Conditions for Compliance with the Second Law of Thermodynamics

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Shnip, A. I.

2018-01-01

Based on the entropy-free thermodynamic approach, a generalized theory of thermodynamic systems with internal variables of state is being developed. For the case of nonlinear thermodynamic systems with internal variables of state and linear relaxation, the necessary and sufficient conditions have been proved for fulfillment of the second law of thermodynamics in entropy-free formulation which, according to the basic theorem of the theory, are also necessary and sufficient for the existence of a thermodynamic potential. Moreover, relations of correspondence between thermodynamic systems with memory and systems with internal variables of state have been established, as well as some useful relations in the spaces of states of both types of systems.

The necessity of connection structures in neural models of variable binding.

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van der Velde, Frank; de Kamps, Marc

2015-08-01

In his review of neural binding problems, Feldman (Cogn Neurodyn 7:1-11, 2013) addressed two types of models as solutions of (novel) variable binding. The one type uses labels such as phase synchrony of activation. The other ('connectivity based') type uses dedicated connections structures to achieve novel variable binding. Feldman argued that label (synchrony) based models are the only possible candidates to handle novel variable binding, whereas connectivity based models lack the flexibility required for that. We argue and illustrate that Feldman's analysis is incorrect. Contrary to his conclusion, connectivity based models are the only viable candidates for models of novel variable binding because they are the only type of models that can produce behavior. We will show that the label (synchrony) based models analyzed by Feldman are in fact examples of connectivity based models. Feldman's analysis that novel variable binding can be achieved without existing connection structures seems to result from analyzing the binding problem in a wrong frame of reference, in particular in an outside instead of the required inside frame of reference. Connectivity based models can be models of novel variable binding when they possess a connection structure that resembles a small-world network, as found in the brain. We will illustrate binding with this type of model with episode binding and the binding of words, including novel words, in sentence structures.

Towards an integrated model of international migration

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Douglas S. MASSEY

2012-12-01

Full Text Available Demographers have yet to develop a suitable integrated model of international migration and consequently have been very poor at forecasting immigration. This paper outlines the basic elements of an integrated model and surveys recent history to suggest the key challenges to model construction. A comprehensive theory must explain the structural forces that create a supply of people prone to migrate internationally, the structural origins of labour demand in receiving countries, the motivations of those who respond to these forces by choosing to migrate internationally, the growth and structure of transnational networks that arise to support international movement, the behaviour states in response to immigrant flows, and the influence of state actions on the behaviour of migrants. Recent history suggests that a good model needs to respect the salience of markets, recognize the circularity of migrant flows, appreciate the power of feedback effects, and be alert unanticipated consequences of policy actions.

Instrumental variables estimation of exposure effects on a time-to-event endpoint using structural cumulative survival models.

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Martinussen, Torben; Vansteelandt, Stijn; Tchetgen Tchetgen, Eric J; Zucker, David M

2017-12-01

The use of instrumental variables for estimating the effect of an exposure on an outcome is popular in econometrics, and increasingly so in epidemiology. This increasing popularity may be attributed to the natural occurrence of instrumental variables in observational studies that incorporate elements of randomization, either by design or by nature (e.g., random inheritance of genes). Instrumental variables estimation of exposure effects is well established for continuous outcomes and to some extent for binary outcomes. It is, however, largely lacking for time-to-event outcomes because of complications due to censoring and survivorship bias. In this article, we make a novel proposal under a class of structural cumulative survival models which parameterize time-varying effects of a point exposure directly on the scale of the survival function; these models are essentially equivalent with a semi-parametric variant of the instrumental variables additive hazards model. We propose a class of recursive instrumental variable estimators for these exposure effects, and derive their large sample properties along with inferential tools. We examine the performance of the proposed method in simulation studies and illustrate it in a Mendelian randomization study to evaluate the effect of diabetes on mortality using data from the Health and Retirement Study. We further use the proposed method to investigate potential benefit from breast cancer screening on subsequent breast cancer mortality based on the HIP-study. © 2017, The International Biometric Society.

Effective properties of linear viscoelastic heterogeneous media: Internal variables formulation and extension to ageing behaviours

International Nuclear Information System (INIS)

Ricaud, J.M.; Masson, R.; Masson, R.

2009-01-01

The Laplace-Carson transform classically used for homogenization of linear viscoelastic heterogeneous media yields integral formulations of effective behaviours. These are far less convenient than internal variables formulations with respect to computational aspects as well as to theoretical extensions to closely related problems such as ageing viscoelasticity. Noticing that the collocation method is usually adopted to invert the Laplace-Carson transforms, we first remark that this approximation is equivalent to an internal variables formulation which is exact in some specific situations. This result is illustrated for a two-phase composite with phases obeying a compressible Maxwellian behaviour. Next, an incremental formulation allows to extend at each time step the previous general framework to ageing viscoelasticity. Finally, with the help of a creep test of a porous viscoelastic matrix reinforced with elastic inclusions, it is shown that the method yields accurate predictions (comparing to reference results provided by periodic cell finite element computations). (authors)

Internal Motion Estimation by Internal-external Motion Modeling for Lung Cancer Radiotherapy.

Science.gov (United States)

Chen, Haibin; Zhong, Zichun; Yang, Yiwei; Chen, Jiawei; Zhou, Linghong; Zhen, Xin; Gu, Xuejun

2018-02-27

The aim of this study is to develop an internal-external correlation model for internal motion estimation for lung cancer radiotherapy. Deformation vector fields that characterize the internal-external motion are obtained by respectively registering the internal organ meshes and external surface meshes from the 4DCT images via a recently developed local topology preserved non-rigid point matching algorithm. A composite matrix is constructed by combing the estimated internal phasic DVFs with external phasic and directional DVFs. Principle component analysis is then applied to the composite matrix to extract principal motion characteristics, and generate model parameters to correlate the internal-external motion. The proposed model is evaluated on a 4D NURBS-based cardiac-torso (NCAT) synthetic phantom and 4DCT images from five lung cancer patients. For tumor tracking, the center of mass errors of the tracked tumor are 0.8(±0.5)mm/0.8(±0.4)mm for synthetic data, and 1.3(±1.0)mm/1.2(±1.2)mm for patient data in the intra-fraction/inter-fraction tracking, respectively. For lung tracking, the percent errors of the tracked contours are 0.06(±0.02)/0.07(±0.03) for synthetic data, and 0.06(±0.02)/0.06(±0.02) for patient data in the intra-fraction/inter-fraction tracking, respectively. The extensive validations have demonstrated the effectiveness and reliability of the proposed model in motion tracking for both the tumor and the lung in lung cancer radiotherapy.

The relative contributions of tropical Pacific sea surface temperatures and atmospheric internal variability to the recent global warming hiatus

Science.gov (United States)

Deser, Clara; Guo, Ruixia; Lehner, Flavio

2017-08-01

The recent slowdown in global mean surface temperature (GMST) warming during boreal winter is examined from a regional perspective using 10-member initial-condition ensembles with two global coupled climate models in which observed tropical Pacific sea surface temperature anomalies (TPAC SSTAs) and radiative forcings are specified. Both models show considerable diversity in their surface air temperature (SAT) trend patterns across the members, attesting to the importance of internal variability beyond the tropical Pacific that is superimposed upon the response to TPAC SSTA and radiative forcing. Only one model shows a close relationship between the realism of its simulated GMST trends and SAT trend patterns. In this model, Eurasian cooling plays a dominant role in determining the GMST trend amplitude, just as in nature. In the most realistic member, intrinsic atmospheric dynamics and teleconnections forced by TPAC SSTA cause cooling over Eurasia (and North America), and contribute equally to its GMST trend.

Modes of interannual variability in northern hemisphere winter atmospheric circulation in CMIP5 models: evaluation, projection and role of external forcing

Science.gov (United States)

Frederiksen, Carsten S.; Ying, Kairan; Grainger, Simon; Zheng, Xiaogu

2018-04-01

Models from the coupled model intercomparison project phase 5 (CMIP5) dataset are evaluated for their ability to simulate the dominant slow modes of interannual variability in the Northern Hemisphere atmospheric circulation 500 hPa geopotential height in the twentieth century. A multi-model ensemble of the best 13 models has then been used to identify the leading modes of interannual variability in components related to (1) intraseasonal processes; (2) slowly-varying internal dynamics; and (3) the slowly-varying response to external changes in radiative forcing. Modes in the intraseasonal component are related to intraseasonal variability in the North Atlantic, North Pacific and North American, and Eurasian regions and are little affected by the larger radiative forcing of the Representative Concentration Pathways 8.5 (RCP8.5) scenario. The leading modes in the slow-internal component are related to the El Niño-Southern Oscillation, Pacific North American or Tropical Northern Hemisphere teleconnection, the North Atlantic Oscillation, and the Western Pacific teleconnection pattern. While the structure of these slow-internal modes is little affected by the larger radiative forcing of the RCP8.5 scenario, their explained variance increases in the warmer climate. The leading mode in the slow-external component has a significant trend and is shown to be related predominantly to the climate change trend in the well mixed greenhouse gas concentration during the historical period. This mode is associated with increasing height in the 500 hPa pressure level. A secondary influence on this mode is the radiative forcing due to stratospheric aerosols associated with volcanic eruptions. The second slow-external mode is shown to be also related to radiative forcing due to stratospheric aerosols. Under RCP8.5 there is only one slow-external mode related to greenhouse gas forcing with a trend over four times the historical trend.

Meteorological and small scale internal ecosystem variability characterize the uncertainty of ecosystem level responses to elevated CO2. Insights from the Duke Forest FACE experiment

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Paschalis, A.; Katul, G. G.; Fatichi, S.; Palmroth, S.; Way, D.

2017-12-01

One of the open questions in climate change research is the pathway by which elevated atmospheric CO2 concentration impacts the biogeochemical and hydrological cycles at the ecosystem scale. This impact leads to significant changes in long-term carbon stocks and the potential of ecosystems to sequester CO2, partially mitigating anthropogenic emissions. While the significance of elevated atmospheric CO2 concentration on instantaneous leaf-level processes such as photosynthesis and transpiration is rarely disputed, its integrated effect at the ecosystem level and at long-time scales remains a subject of debate. This debate has taken on some urgency as illustrated by differences arising between ecosystem modelling studies, and data-model comparisons using Free Air CO2 Enrichment (FACE) sites around the world. Inherent leaf-to-leaf variability in gas exchange rates can generate such inconsistencies. This inherent variability arises from the combined effect of meteorological "temporal" variability and the "spatial" variability of the biochemical parameters regulating vegetation carbon uptake. This combined variability leads to a non-straightforward scaling of ecosystem fluxes from the leaf to ecosystems. To illustrate this scaling behaviour, we used 10 years of leaf gas exchange measurements collected at the Duke Forest FACE experiment. The internal variability of the ecosystem parameters are first quantified and then combined with three different leaf-scale stomatal conductance models and an ecosystem model. The main results are: (a) Variability of the leaf level fluxes is dependent on both the meteorological drivers and differences in leaf age, position within the canopy, nitrogen and CO2 fertilization, which can be accommodated in model parameters; (b) Meteorological variability plays the dominant role at short temporal scales while parameter variability is significant at longer temporal scales. (c) Leaf level results do not necessarily translate to similar ecosystem

Improved variable reduction in partial least squares modelling based on predictive-property-ranked variables and adaptation of partial least squares complexity.

Science.gov (United States)

Andries, Jan P M; Vander Heyden, Yvan; Buydens, Lutgarde M C

2011-10-31

The calibration performance of partial least squares for one response variable (PLS1) can be improved by elimination of uninformative variables. Many methods are based on so-called predictive variable properties, which are functions of various PLS-model parameters, and which may change during the variable reduction process. In these methods variable reduction is made on the variables ranked in descending order for a given variable property. The methods start with full spectrum modelling. Iteratively, until a specified number of remaining variables is reached, the variable with the smallest property value is eliminated; a new PLS model is calculated, followed by a renewed ranking of the variables. The Stepwise Variable Reduction methods using Predictive-Property-Ranked Variables are denoted as SVR-PPRV. In the existing SVR-PPRV methods the PLS model complexity is kept constant during the variable reduction process. In this study, three new SVR-PPRV methods are proposed, in which a possibility for decreasing the PLS model complexity during the variable reduction process is build in. Therefore we denote our methods as PPRVR-CAM methods (Predictive-Property-Ranked Variable Reduction with Complexity Adapted Models). The selective and predictive abilities of the new methods are investigated and tested, using the absolute PLS regression coefficients as predictive property. They were compared with two modifications of existing SVR-PPRV methods (with constant PLS model complexity) and with two reference methods: uninformative variable elimination followed by either a genetic algorithm for PLS (UVE-GA-PLS) or an interval PLS (UVE-iPLS). The performance of the methods is investigated in conjunction with two data sets from near-infrared sources (NIR) and one simulated set. The selective and predictive performances of the variable reduction methods are compared statistically using the Wilcoxon signed rank test. The three newly developed PPRVR-CAM methods were able to retain

The Role of Information Technology as Moderating Variable and Internal Control Effectiveness as intervening in the Relationship between Human Resource Competency and Internal Auditor Service Quality on of Report

OpenAIRE

Haliah, Hamid,Irdam

2015-01-01

in general, this research is intended to investigate factors that effect quality of report of local government in west Sulawesi province, Indonesia. Human resource competence and quality of services of internal auditor have indirect effect through the effectiveness of internal control to the quality of the report. These results indicate that the effectiveness of internal control serves as an intervening variable on the relationship of competence of human resources and internal auditor service...

Modeling of carbon sequestration in coal-beds: A variable saturated simulation

International Nuclear Information System (INIS)

Liu Guoxiang; Smirnov, Andrei V.

2008-01-01

Storage of carbon dioxide in deep coal seams is a profitable method to reduce the concentration of green house gases in the atmosphere while the methane as a byproduct can be extracted during carbon dioxide injection into the coal seam. In this procedure, the key element is to keep carbon dioxide in the coal seam without escaping for a long term. It is depended on many factors such as properties of coal basin, fracture state, phase equilibrium, etc., especially the porosity, permeability and saturation of the coal seam. In this paper, a variable saturation model was developed to predict the capacity of carbon dioxide sequestration and coal-bed methane recovery. This variable saturation model can be used to track the saturation variability with the partial pressures change caused by carbon dioxide injection. Saturation variability is a key factor to predict the capacity of carbon dioxide storage and methane recovery. Based on this variable saturation model, a set of related variables including capillary pressure, relative permeability, porosity, coupled adsorption model, concentration and temperature equations were solved. From results of the simulation, historical data agree with the variable saturation model as well as the adsorption model constructed by Langmuir equations. The Appalachian basin, as an example, modeled the carbon dioxide sequestration in this paper. The results of the study and the developed models can provide the projections for the CO 2 sequestration and methane recovery in coal-beds within different regional specifics

Mediterranean climate modelling: variability and climate change scenarios

International Nuclear Information System (INIS)

Somot, S.

2005-12-01

Air-sea fluxes, open-sea deep convection and cyclo-genesis are studied in the Mediterranean with the development of a regional coupled model (AORCM). It accurately simulates these processes and their climate variabilities are quantified and studied. The regional coupling shows a significant impact on the number of winter intense cyclo-genesis as well as on associated air-sea fluxes and precipitation. A lower inter-annual variability than in non-coupled models is simulated for fluxes and deep convection. The feedbacks driving this variability are understood. The climate change response is then analysed for the 21. century with the non-coupled models: cyclo-genesis decreases, associated precipitation increases in spring and autumn and decreases in summer. Moreover, a warming and salting of the Mediterranean as well as a strong weakening of its thermohaline circulation occur. This study also concludes with the necessity of using AORCMs to assess climate change impacts on the Mediterranean. (author)

Investigations on the acoustic optimisation of a variable displacement pump using virtual prototyping

Directory of Open Access Journals (Sweden)

Thomas NIED-MENNINGER

2009-01-01

Full Text Available In modern vehicles the steering systems are still widely equipped with power-assisted steering pumps. In most cases vane pumps are used which limit the fluid volume flow in dependence of required pressure and running speed by a special design of the internal control valve. This control valve internally redirects the volume flow inside the pump leading still to unnecessary fluid circulation. Variable displacement pumps now offer an additional opportunity to eliminate the internal volume flow in dependence of the required load with reduced losses and hence increased efficiency. This is realized by a variable adjustment of the displacement cells, but simultaneously the variable force and load distributions inside the pump make the acoustic optimization even more difficult. In this paper the kinematics of the vane pump are modelled with a combined analytical and numerical approach. The data out of this model are used as input data for the hydraulic model of the variable displacement vane pump with a commercial tool. Both models are validated with data from test rig investigations. With this validated virtual prototype different design options are developed and finally successfully investigated on a test rig and in a passenger vehicle.

Predictive and Descriptive CoMFA Models: The Effect of Variable Selection.

Science.gov (United States)

Sepehri, Bakhtyar; Omidikia, Nematollah; Kompany-Zareh, Mohsen; Ghavami, Raouf

2018-01-01

Aims & Scope: In this research, 8 variable selection approaches were used to investigate the effect of variable selection on the predictive power and stability of CoMFA models. Three data sets including 36 EPAC antagonists, 79 CD38 inhibitors and 57 ATAD2 bromodomain inhibitors were modelled by CoMFA. First of all, for all three data sets, CoMFA models with all CoMFA descriptors were created then by applying each variable selection method a new CoMFA model was developed so for each data set, 9 CoMFA models were built. Obtained results show noisy and uninformative variables affect CoMFA results. Based on created models, applying 5 variable selection approaches including FFD, SRD-FFD, IVE-PLS, SRD-UVEPLS and SPA-jackknife increases the predictive power and stability of CoMFA models significantly. Among them, SPA-jackknife removes most of the variables while FFD retains most of them. FFD and IVE-PLS are time consuming process while SRD-FFD and SRD-UVE-PLS run need to few seconds. Also applying FFD, SRD-FFD, IVE-PLS, SRD-UVE-PLS protect CoMFA countor maps information for both fields. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

Prediction of Placental Barrier Permeability: A Model Based on Partial Least Squares Variable Selection Procedure

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Yong-Hong Zhang

2015-05-01

Full Text Available Assessing the human placental barrier permeability of drugs is very important to guarantee drug safety during pregnancy. Quantitative structure–activity relationship (QSAR method was used as an effective assessing tool for the placental transfer study of drugs, while in vitro human placental perfusion is the most widely used method. In this study, the partial least squares (PLS variable selection and modeling procedure was used to pick out optimal descriptors from a pool of 620 descriptors of 65 compounds and to simultaneously develop a QSAR model between the descriptors and the placental barrier permeability expressed by the clearance indices (CI. The model was subjected to internal validation by cross-validation and y-randomization and to external validation by predicting CI values of 19 compounds. It was shown that the model developed is robust and has a good predictive potential (r2 = 0.9064, RMSE = 0.09, q2 = 0.7323, rp2 = 0.7656, RMSP = 0.14. The mechanistic interpretation of the final model was given by the high variable importance in projection values of descriptors. Using PLS procedure, we can rapidly and effectively select optimal descriptors and thus construct a model with good stability and predictability. This analysis can provide an effective tool for the high-throughput screening of the placental barrier permeability of drugs.

Simulation-Based Internal Models for Safer Robots

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Christian Blum

2018-01-01

Full Text Available In this paper, we explore the potential of mobile robots with simulation-based internal models for safety in highly dynamic environments. We propose a robot with a simulation of itself, other dynamic actors and its environment, inside itself. Operating in real time, this simulation-based internal model is able to look ahead and predict the consequences of both the robot’s own actions and those of the other dynamic actors in its vicinity. Hence, the robot continuously modifies its own actions in order to actively maintain its own safety while also achieving its goal. Inspired by the problem of how mobile robots could move quickly and safely through crowds of moving humans, we present experimental results which compare the performance of our internal simulation-based controller with a purely reactive approach as a proof-of-concept study for the practical use of simulation-based internal models.

Robust control of chaos in Chua's circuit based on internal model principle

Energy Technology Data Exchange (ETDEWEB)

Lee, Keum W. [Department of Electrical and Computer Engineering, University of Nevada Las Vegas, 4505 Maryland Parkway, Las Vegas, NV, 89154-4026 (United States); Singh, Sahjendra N. [Department of Electrical and Computer Engineering, University of Nevada Las Vegas, 4505 Maryland Parkway, Las Vegas, NV, 89154-4026 (United States)]. E-mail: sahaj@ee.unlv.edu

2007-03-15

The paper treats the question of robust control of chaos in Chua's circuit based on the internal model principle. The Chua's diode has polynomial non-linearity and it is assumed that the parameters of the circuit are not known. A robust control law for the asymptotic regulation of the output (node voltage) along constant and sinusoidal reference trajectories is derived. For the derivation of the control law, the non-linear regulator equations are solved to obtain a manifold in the state space on which the output error is zero and an internal model of the k-fold exosystem (k = 3 here) is constructed. Then a feedback control law using the optimal control theory or pole placement technique for the stabilization of the augmented system including the Chua's circuit and the internal model is derived. In the closed-loop system, robust output node voltage trajectory tracking of sinusoidal and constant reference trajectories are accomplished and in the steady state, the remaining state variables converge to periodic and constant trajectories, respectively. Simulation results are presented which show that in the closed-loop system, asymptotic trajectory control, disturbance rejection and suppression of chaotic motion in spite of uncertainties in the system are accomplished.

Variable-Structure Control of a Model Glider Airplane

Science.gov (United States)

Waszak, Martin R.; Anderson, Mark R.

2008-01-01

A variable-structure control system designed to enable a fuselage-heavy airplane to recover from spin has been demonstrated in a hand-launched, instrumented model glider airplane. Variable-structure control is a high-speed switching feedback control technique that has been developed for control of nonlinear dynamic systems.

The Selection, Use, and Reporting of Control Variables in International Business Research

DEFF Research Database (Denmark)

Nielsen, Bo Bernhard; Raswant, Arpit

2018-01-01

This study explores the selection, use, and reporting of control variables in studies published in the leading international business (IB) research journals. We review a sample of 246 empirical studies published in the top five IB journals over the period 2012–2015 with particular emphasis...... on selection, use, and reporting of controls. Approximately 83% of studies included only half of what we consider Minimum Standard of Practice with regards to controls, whereas only 38% of the studies met the 75% threshold. We provide recommendations on how to effectively identify, use and report controls...

Motor skills in kindergarten: Internal structure, cognitive correlates and relationships to background variables.

Science.gov (United States)

Oberer, Nicole; Gashaj, Venera; Roebers, Claudia M

2017-04-01

The present study aimed to contribute to the discussion about the relation between motor coordination and executive functions in preschool children. Specifically, the relation between gross and fine motor skills and executive functions as well as the relation to possible background variables (SES, physical activity) were investigated. Based on the data of N=156 kindergarten children the internal structure of motor skills was investigated and confirmed the theoretically assumed subdivision of gross and fine motor skills. Both, gross and fine motor skills correlated significantly with executive functions, whereas the background variables seemed to have no significant impact on the executive functions and motor skills. Higher order control processes are discussed as an explanation of the relation between executive functions and motor skills. Copyright © 2017 Elsevier B.V. All rights reserved.

Theory and simulations for hard-disk models of binary mixtures of molecules with internal degrees of freedom

DEFF Research Database (Denmark)

Fraser, Diane P.; Zuckermann, Martin J.; Mouritsen, Ole G.

1991-01-01

A two-dimensional Monte Carlo simulation method based on the NpT ensemble and the Voronoi tesselation, which was previously developed for single-species hard-disk systems, is extended, along with a version of scaled-particle theory, to many-component mixtures. These systems are unusual in the sense...... and internal degrees of freedom leads to a rich phase structure that includes solid-liquid transitions (governed by the translational variables) as well as transitions involving changes in average disk size (governed by the internal variables). The relationship between these two types of transitions is studied...... by the method in the case of a binary mixture, and results are presented for varying disk-size ratios and degeneracies. The results are also compared with the predictions of the extended scaled-particle theory. Applications of the model are discussed in relation to lipid monolayers spread on air...

The use of a xylosylated plant glycoprotein as an internal standard accounting for N-linked glycan cleavage and sample preparation variability.

Science.gov (United States)

Walker, S Hunter; Taylor, Amber D; Muddiman, David C

2013-06-30

Traditionally, free oligosaccharide internal standards are used to account for variability in glycan relative quantification experiments by mass spectrometry. However, a more suitable internal standard would be a glycoprotein, which could also control for enzymatic cleavage efficiency, allowing for more accurate quantitative experiments. Hydrophobic, hydrazide N-linked glycan reagents (both native and stable-isotope labeled) are used to derivatize and differentially label N-linked glycan samples for relative quantification, and the samples are analyzed by a reversed-phase liquid chromatography chip system coupled online to a Q-Exactive mass spectrometer. The inclusion of two internal standards, maltoheptaose (previously used) and horseradish peroxidase (HRP) (novel), is studied to demonstrate the effectiveness of using a glycoprotein as an internal standard in glycan relative quantification experiments. HRP is a glycoprotein containing a xylosylated N-linked glycan, which is unique from mammalian N-linked glycans. Thus, the internal standard xylosylated glycan could be detected without interference to the sample. Additionally, it was shown that differences in cleavage efficiency can be detected by monitoring the HRP glycan. In a sample where cleavage efficiency variation is minimal, the HRP glycan performs as well as maltoheptaose. Because the HRP glycan performs as well as maltoheptaose but is also capable of correcting and accounting for cleavage variability, it is a more versatile internal standard and will be used in all subsequent biological studies. Because of the possible lot-to-lot variation of an enzyme, differences in biological matrix, and variable enzyme activity over time, it is a necessity to account for glycan cleavage variability in glycan relative quantification experiments. Copyright © 2013 John Wiley & Sons, Ltd.

Computational Fluid Dynamics Modeling of a Supersonic Nozzle and Integration into a Variable Cycle Engine Model

Science.gov (United States)

Connolly, Joseph W.; Friedlander, David; Kopasakis, George

2015-01-01

This paper covers the development of an integrated nonlinear dynamic simulation for a variable cycle turbofan engine and nozzle that can be integrated with an overall vehicle Aero-Propulso-Servo-Elastic (APSE) model. A previously developed variable cycle turbofan engine model is used for this study and is enhanced here to include variable guide vanes allowing for operation across the supersonic flight regime. The primary focus of this study is to improve the fidelity of the model's thrust response by replacing the simple choked flow equation convergent-divergent nozzle model with a MacCormack method based quasi-1D model. The dynamic response of the nozzle model using the MacCormack method is verified by comparing it against a model of the nozzle using the conservation element/solution element method. A methodology is also presented for the integration of the MacCormack nozzle model with the variable cycle engine.

Analytical Model for LLC Resonant Converter With Variable Duty-Cycle Control

DEFF Research Database (Denmark)

Shen, Yanfeng; Wang, Huai; Blaabjerg, Frede

2016-01-01

are identified and discussed. The proposed model enables a better understanding of the operation characteristics and fast parameter design of the LLC converter, which otherwise cannot be achieved by the existing simulation based methods and numerical models. The results obtained from the proposed model......In LLC resonant converters, the variable duty-cycle control is usually combined with a variable frequency control to widen the gain range, improve the light-load efficiency, or suppress the inrush current during start-up. However, a proper analytical model for the variable duty-cycle controlled LLC...... converter is still not available due to the complexity of operation modes and the nonlinearity of steady-state equations. This paper makes the efforts to develop an analytical model for the LLC converter with variable duty-cycle control. All possible operation models and critical operation characteristics...

A model for AGN variability on multiple time-scales

Science.gov (United States)

Sartori, Lia F.; Schawinski, Kevin; Trakhtenbrot, Benny; Caplar, Neven; Treister, Ezequiel; Koss, Michael J.; Urry, C. Megan; Zhang, C. E.

2018-05-01

We present a framework to link and describe active galactic nuclei (AGN) variability on a wide range of time-scales, from days to billions of years. In particular, we concentrate on the AGN variability features related to changes in black hole fuelling and accretion rate. In our framework, the variability features observed in different AGN at different time-scales may be explained as realisations of the same underlying statistical properties. In this context, we propose a model to simulate the evolution of AGN light curves with time based on the probability density function (PDF) and power spectral density (PSD) of the Eddington ratio (L/LEdd) distribution. Motivated by general galaxy population properties, we propose that the PDF may be inspired by the L/LEdd distribution function (ERDF), and that a single (or limited number of) ERDF+PSD set may explain all observed variability features. After outlining the framework and the model, we compile a set of variability measurements in terms of structure function (SF) and magnitude difference. We then combine the variability measurements on a SF plot ranging from days to Gyr. The proposed framework enables constraints on the underlying PSD and the ability to link AGN variability on different time-scales, therefore providing new insights into AGN variability and black hole growth phenomena.

Valsalva and gravitational variability of the internal jugular vein and common femoral vein: Ultrasound assessment

Energy Technology Data Exchange (ETDEWEB)

Beddy, P. [Department of Radiology, The Adelaide and Meath Hospital, Tallaght, Dublin 24 (Ireland)]. E-mail: pbeddy@eircom.net; Geoghegan, T. [Department of Radiology, The Adelaide and Meath Hospital, Tallaght, Dublin 24 (Ireland); Ramesh, N. [Department of Radiology, The Adelaide and Meath Hospital, Tallaght, Dublin 24 (Ireland); Buckley, O. [Department of Radiology, The Adelaide and Meath Hospital, Tallaght, Dublin 24 (Ireland); O' Brien, J. [Department of Radiology, The Adelaide and Meath Hospital, Tallaght, Dublin 24 (Ireland); Colville, J. [Department of Radiology, The Adelaide and Meath Hospital, Tallaght, Dublin 24 (Ireland); Torreggiani, W.C. [Department of Radiology, The Adelaide and Meath Hospital, Tallaght, Dublin 24 (Ireland)

2006-05-15

Purpose: Central venous cannulation via the common femoral vein is an important starting point for many interventions. The purpose of this study was to determine the optimum conditions for cannulation of the femoral vein and to compare these with the relative changes in the internal jugular vein. Methods: High-resolution 2D ultrasound was utilised to determine variability of the calibre of the femoral and internal jugular veins in 10 healthy subjects. Venous diameter was assessed during the Valsalva manoeuvre and in different degrees of the Trendelenburg position. Results: The Valsalva manoeuvre significantly increased the size of the femoral and internal jugular veins. There was a relatively greater increase in femoral vein diameter when compared with the internal jugular vein of 40 and 29%, respectively. Changes in body inclination (Trendelenburg position) did not significantly alter the luminal diameter of the femoral vein. However, it significantly increased internal jugular vein diameter. Conclusions: Femoral vein cannulation is augmented by the Valsalva manoeuvre but not significantly altered by the gravitational position of the subject.

External and internal limitations in amplitude-modulation processing

DEFF Research Database (Denmark)

Ewert, Stephan; Dau, Torsten

2004-01-01

Three experiments are presented to explore the relative role of "external" signal variability and "internal" resolution limitations of the auditory system in the detection and discrimination of amplitude modulations (AM). In the first experiment, AM-depth discrimination performance was determined......-filterbank models. The predictions revealed that AM-depth discrimination and AM detection are limited by a combination of the external signal variability and an internal "Weber-fraction" noise process....

International Space Station Model Correlation Analysis

Science.gov (United States)

Laible, Michael R.; Fitzpatrick, Kristin; Hodge, Jennifer; Grygier, Michael

2018-01-01

This paper summarizes the on-orbit structural dynamic data and the related modal analysis, model validation and correlation performed for the International Space Station (ISS) configuration ISS Stage ULF7, 2015 Dedicated Thruster Firing (DTF). The objective of this analysis is to validate and correlate the analytical models used to calculate the ISS internal dynamic loads and compare the 2015 DTF with previous tests. During the ISS configurations under consideration, on-orbit dynamic measurements were collected using the three main ISS instrumentation systems; Internal Wireless Instrumentation System (IWIS), External Wireless Instrumentation System (EWIS) and the Structural Dynamic Measurement System (SDMS). The measurements were recorded during several nominal on-orbit DTF tests on August 18, 2015. Experimental modal analyses were performed on the measured data to extract modal parameters including frequency, damping, and mode shape information. Correlation and comparisons between test and analytical frequencies and mode shapes were performed to assess the accuracy of the analytical models for the configurations under consideration. These mode shapes were also compared to earlier tests. Based on the frequency comparisons, the accuracy of the mathematical models is assessed and model refinement recommendations are given. In particular, results of the first fundamental mode will be discussed, nonlinear results will be shown, and accelerometer placement will be assessed.

Classification criteria of syndromes by latent variable models

DEFF Research Database (Denmark)

Petersen, Janne

2010-01-01

patient's characteristics. These methods may erroneously reduce multiplicity either by combining markers of different phenotypes or by mixing HALS with other processes such as aging. Latent class models identify homogenous groups of patients based on sets of variables, for example symptoms. As no gold......The thesis has two parts; one clinical part: studying the dimensions of human immunodeficiency virus associated lipodystrophy syndrome (HALS) by latent class models, and a more statistical part: investigating how to predict scores of latent variables so these can be used in subsequent regression...... standard exists for diagnosing HALS the normally applied diagnostic models cannot be used. Latent class models, which have never before been used to diagnose HALS, make it possible, under certain assumptions, to: statistically evaluate the number of phenotypes, test for mixing of HALS with other processes...

Using structural equation modeling to investigate relationships among ecological variables

Science.gov (United States)

Malaeb, Z.A.; Kevin, Summers J.; Pugesek, B.H.

2000-01-01

Structural equation modeling is an advanced multivariate statistical process with which a researcher can construct theoretical concepts, test their measurement reliability, hypothesize and test a theory about their relationships, take into account measurement errors, and consider both direct and indirect effects of variables on one another. Latent variables are theoretical concepts that unite phenomena under a single term, e.g., ecosystem health, environmental condition, and pollution (Bollen, 1989). Latent variables are not measured directly but can be expressed in terms of one or more directly measurable variables called indicators. For some researchers, defining, constructing, and examining the validity of latent variables may be the end task of itself. For others, testing hypothesized relationships of latent variables may be of interest. We analyzed the correlation matrix of eleven environmental variables from the U.S. Environmental Protection Agency's (USEPA) Environmental Monitoring and Assessment Program for Estuaries (EMAP-E) using methods of structural equation modeling. We hypothesized and tested a conceptual model to characterize the interdependencies between four latent variables-sediment contamination, natural variability, biodiversity, and growth potential. In particular, we were interested in measuring the direct, indirect, and total effects of sediment contamination and natural variability on biodiversity and growth potential. The model fit the data well and accounted for 81% of the variability in biodiversity and 69% of the variability in growth potential. It revealed a positive total effect of natural variability on growth potential that otherwise would have been judged negative had we not considered indirect effects. That is, natural variability had a negative direct effect on growth potential of magnitude -0.3251 and a positive indirect effect mediated through biodiversity of magnitude 0.4509, yielding a net positive total effect of 0

A bivariate measurement error model for semicontinuous and continuous variables: Application to nutritional epidemiology.

Science.gov (United States)

Kipnis, Victor; Freedman, Laurence S; Carroll, Raymond J; Midthune, Douglas

2016-03-01

Semicontinuous data in the form of a mixture of a large portion of zero values and continuously distributed positive values frequently arise in many areas of biostatistics. This article is motivated by the analysis of relationships between disease outcomes and intakes of episodically consumed dietary components. An important aspect of studies in nutritional epidemiology is that true diet is unobservable and commonly evaluated by food frequency questionnaires with substantial measurement error. Following the regression calibration approach for measurement error correction, unknown individual intakes in the risk model are replaced by their conditional expectations given mismeasured intakes and other model covariates. Those regression calibration predictors are estimated using short-term unbiased reference measurements in a calibration substudy. Since dietary intakes are often "energy-adjusted," e.g., by using ratios of the intake of interest to total energy intake, the correct estimation of the regression calibration predictor for each energy-adjusted episodically consumed dietary component requires modeling short-term reference measurements of the component (a semicontinuous variable), and energy (a continuous variable) simultaneously in a bivariate model. In this article, we develop such a bivariate model, together with its application to regression calibration. We illustrate the new methodology using data from the NIH-AARP Diet and Health Study (Schatzkin et al., 2001, American Journal of Epidemiology 154, 1119-1125), and also evaluate its performance in a simulation study. © 2015, The International Biometric Society.

The use of Chernobyl data to test model predictions for interindividual variability of 137Cs concentrations in humans

International Nuclear Information System (INIS)

Hoffman, F. Owen; Thiessen, Kathleen M.

1996-01-01

Data sets assembled in the aftermath of the Chernobyl accident as a part of the International Atomic Energy Agency's model testing program (VAMP) have provided a rare opportunity for 'blind-testing' predictions made with exposure assessment models. Measurements of Chernobyl-derived 137 Cs in Central Bohemia (Czech Republic) and southern Finland were used to test model predictions for a number of endpoints, including the distribution of whole-body concentrations of 137 Cs in adults in these regions at specified time points. This test endpoint required separation of uncertainty due to stochastic variability (aleatoric uncertainty) and uncertainty due to lack of knowledge about fixed but unknown values (epistemic uncertainty). Predictions of the distribution of whole-body 137 Cs concentrations were made by a minority of the participants in these model-testing exercises. Major reasons for misprediction included bias in the bioavailability of 137 Cs in soil and misestimation of the total intake of 137 Cs in the diet. Overestimation of the amount of interindividual variability often resulted from confusion of uncertainty with variability. The spreads of the distributions for parameters describing interindividual variability were frequently increased to compensate for lack of knowledge about the uptake and metabolism of 137 Cs in the population. Accurate results produced by participants are attributable both to a participant's access to additional site-specific data or choice of appropriate site-specific assumptions and to the effects of compensatory errors

Fixed transaction costs and modelling limited dependent variables

NARCIS (Netherlands)

Hempenius, A.L.

1994-01-01

As an alternative to the Tobit model, for vectors of limited dependent variables, I suggest a model, which follows from explicitly using fixed costs, if appropriate of course, in the utility function of the decision-maker.

Evaluating two model reduction approaches for large scale hedonic models sensitive to omitted variables and multicollinearity

DEFF Research Database (Denmark)

Panduro, Toke Emil; Thorsen, Bo Jellesmark

2014-01-01

Hedonic models in environmental valuation studies have grown in terms of number of transactions and number of explanatory variables. We focus on the practical challenge of model reduction, when aiming for reliable parsimonious models, sensitive to omitted variable bias and multicollinearity. We...

Quasilinear Extreme Learning Machine Model Based Internal Model Control for Nonlinear Process

Directory of Open Access Journals (Sweden)

Dazi Li

2015-01-01

Full Text Available A new strategy for internal model control (IMC is proposed using a regression algorithm of quasilinear model with extreme learning machine (QL-ELM. Aimed at the chemical process with nonlinearity, the learning process of the internal model and inverse model is derived. The proposed QL-ELM is constructed as a linear ARX model with a complicated nonlinear coefficient. It shows some good approximation ability and fast convergence. The complicated coefficients are separated into two parts. The linear part is determined by recursive least square (RLS, while the nonlinear part is identified through extreme learning machine. The parameters of linear part and the output weights of ELM are estimated iteratively. The proposed internal model control is applied to CSTR process. The effectiveness and accuracy of the proposed method are extensively verified through numerical results.

Can co-activation reduce kinematic variability? A simulation study.

NARCIS (Netherlands)

Selen, L.P.J.; Beek, P.J.; van Dieen, J.H.

2005-01-01

Impedance modulation has been suggested as a means to suppress the effects of internal 'noise' on movement kinematics. We investigated this hypothesis in a neuro-musculo-skeletal model. A prerequisite is that the muscle model produces realistic force variability. We found that standard Hill-type

Variability of the internal tide on the southern Monterey Bay continental shelf and associated bottom boundary layer sediment transport

Science.gov (United States)

Rosenberger, Kurt; Storlazzi, Curt; Cheriton, Olivia

2016-01-01

A 6-month deployment of instrumentation from April to October 2012 in 90 m water depth near the outer edge of the mid-shelf mud belt in southern Monterey Bay, California, reveals the importance regional upwelling on water column density structure, potentially accounting for the majority of the variability in internal tidal energy flux across the shelf. Observations consisted of time-series measurements of water-column currents, temperature and salinity, and near-bed currents and suspended matter. The internal tide accounted for 15–25% of the water-column current variance and the barotropic tide accounted for up to 35%. The subtidal flow showed remarkably little shear and was dominated by the 7–14 day band, which is associated with relaxations in the dominant equatorward winds typical of coastal California in the spring and summer. Upwelling and relaxation events resulted in strong near-bed flows and accounted for almost half of the current stress on the seafloor (not accounting for wave orbital velocities), and may have driven along-shelf geostrophic flow during steady state conditions. Several elevated suspended particulate matter (SPM) events occurred within 3 m of the bed and were generally associated with higher, long-period surface waves. However, these peaks in SPM did not coincide with the predicted resuspension events from the modeled combined wave–current shear stress, indicating that the observed SPM at our site was most likely resuspended elsewhere and advected along-isobath. Sediment flux was almost equal in magnitude in the alongshore and cross-shore directions. Instances of wave–current shear stress that exceeded the threshold of resuspension for the silty-clays common at these water depths only occurred when near-bed orbital velocities due to long-period surface waves coincided with vigorous near-bed currents associated with the internal tide or upwelling/relaxation events. Thus upwelling/relaxation dynamics are primarily responsible for

Stochastically-forced Decadal Variability in Australian Rainfall

Science.gov (United States)

Taschetto, A.

2015-12-01

Iconic Australian dry and wet periods were driven by anomalous conditions in the tropical oceans, such as the worst short-term drought in the southeast in 1982 associated with the strong El Niño and the widespread "Big Wet" in 1974 linked with a La Niña event. The association with oceanic conditions makes droughts predictable to some extent. However, prediction can be difficult when there is no clear external forcing such as El Niños. Can dry spells be triggered and maintained with no ocean memory? In this study, we investigate the potential role of internal multi-century atmospheric variability in controlling the frequency, duration and intensity of long-term dry and wet spells over Australia. Two multi-century-scale simulations were performed with the NCAR CESM: (1) a fully-coupled simulation (CPLD) and (2) an atmospheric simulation forced by a seasonal SST climatology derived from the coupled experiment (ACGM). Results reveal that droughts and wet spells can indeed be generated by internal variability of the atmosphere. Those internally generated events are less severe than those forced by oceanic variability, however the duration of dry and wet spells longer than 3 years is comparable with and without the ocean memory. Large-scale ocean modes of variability seem to play an important role in producing continental-scale rainfall impacts over Australia. While the Pacific Decadal Oscillation plays an important role in generating droughts in the fully coupled model, perturbations of monsoonal winds seem to be the main trigger of dry spells in the AGCM case. Droughts in the mid-latitude regions such as Tasmania can be driven by perturbations in the Southern Annular Mode, not necessarily linked to oceanic conditions even in the fully-coupled model. The mechanisms behind internally-driven mega-droughts and mega-wets will be discussed.

International Nuclear Model. Volume 3. Program description

International Nuclear Information System (INIS)

Andress, D.

1985-01-01

This is Volume 3 of three volumes of documentation of the International Nuclear Model (INM). This volume presents the Program Description of the International Nuclear Model, which was developed for the Nuclear and Alternate Fuels Division (NAFD), Office of Coal, Nuclear, Electric and Alternate Fuels, Energy Information Administration (EIA), US Department of Energy (DOE). The International Nuclear Model (INM) is a comprehensive model of the commercial nuclear power industry. It simulates economic decisions for reactor deployment and fuel management decision based on an input set of technical economic and scenario parameters. The technical parameters include reactor operating characteristics, fuel cycle timing and mass loss factors, and enrichment tails assays. Economic parameters include fuel cycle costs, financial data, and tax alternatives. INM has a broad range of scenario options covering, for example, process constraints, interregional activities, reprocessing, and fuel management selection. INM reports reactor deployment schedules, electricity generation, and fuel cycle requirements and costs. It also has specialized reports for extended burnup and permanent disposal. Companion volumes to Volume 3 are: Volume 1 - Model Overview, and Volume 2 - Data Base Relationships

Hydrologic scales, cloud variability, remote sensing, and models: Implications for forecasting snowmelt and streamflow

Science.gov (United States)

Simpson, James J.; Dettinger, M.D.; Gehrke, F.; McIntire, T.J.; Hufford, Gary L.

2004-01-01

Accurate prediction of available water supply from snowmelt is needed if the myriad of human, environmental, agricultural, and industrial demands for water are to be satisfied, especially given legislatively imposed conditions on its allocation. Robust retrievals of hydrologic basin model variables (e.g., insolation or areal extent of snow cover) provide several advantages over the current operational use of either point measurements or parameterizations to help to meet this requirement. Insolation can be provided at hourly time scales (or better if needed during rapid melt events associated with flooding) and at 1-km spatial resolution. These satellite-based retrievals incorporate the effects of highly variable (both in space and time) and unpredictable cloud cover on estimates of insolation. The insolation estimates are further adjusted for the effects of basin topography using a high-resolution digital elevation model prior to model input. Simulations of two Sierra Nevada rivers in the snowmelt seasons of 1998 and 1999 indicate that even the simplest improvements in modeled insolation can improve snowmelt simulations, with 10%-20% reductions in root-mean-square errors. Direct retrieval of the areal extent of snow cover may mitigate the need to rely entirely on internal calculations of this variable, a reliance that can yield large errors that are difficult to correct until long after the season is complete and that often leads to persistent underestimates or overestimates of the volumes of the water to operational reservoirs. Agencies responsible for accurately predicting available water resources from the melt of snowpack [e.g., both federal (the National Weather Service River Forecast Centers) and state (the California Department of Water Resources)] can benefit by incorporating concepts developed herein into their operational forecasting procedures. ?? 2004 American Meteorological Society.

Variability aware compact model characterization for statistical circuit design optimization

Science.gov (United States)

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

2012-03-01

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

Interannual modes of variability of Southern Hemisphere atmospheric circulation in CMIP3 models

International Nuclear Information System (INIS)

Grainger, S; Frederiksen, C S; Zheng, X

2010-01-01

The atmospheric circulation acts as a bridge between large-scale sources of climate variability, and climate variability on regional scales. Here a statistical method is applied to monthly mean Southern Hemisphere 500hPa geopotential height to separate the interannual variability of the seasonal mean into intraseasonal and slowly varying (time scales of a season or longer) components. Intraseasonal and slow modes of variability are estimated from realisations of models from the Coupled Model Intercomparison Project Phase 3 (CMIP3) twentieth century coupled climate simulation (20c3m) and are evaluated against those estimated from reanalysis data. The intraseasonal modes of variability are generally well reproduced across all CMIP3 20c3m models for both Southern Hemisphere summer and winter. The slow modes are in general less well reproduced than the intraseasonal modes, and there are larger differences between realisations than for the intraseasonal modes. New diagnostics are proposed to evaluate model variability. It is found that differences between realisations from each model are generally less than inter-model differences. Differences between model-mean diagnostics are found. The results obtained are applicable to assessing the reliability of changes in atmospheric circulation variability in CMIP3 models and for their suitability for further studies of regional climate variability.

A novel methodology improves reservoir characterization models using geologic fuzzy variables

Energy Technology Data Exchange (ETDEWEB)

Soto B, Rodolfo [DIGITOIL, Maracaibo (Venezuela); Soto O, David A. [Texas A and M University, College Station, TX (United States)

2004-07-01

One of the research projects carried out in Cusiana field to explain its rapid decline during the last years was to get better permeability models. The reservoir of this field has a complex layered system that it is not easy to model using conventional methods. The new technique included the development of porosity and permeability maps from cored wells following the same trend of the sand depositions for each facie or layer according to the sedimentary facie and the depositional system models. Then, we used fuzzy logic to reproduce those maps in three dimensions as geologic fuzzy variables. After multivariate statistical and factor analyses, we found independence and a good correlation coefficient between the geologic fuzzy variables and core permeability and porosity. This means, the geologic fuzzy variable could explain the fabric, the grain size and the pore geometry of the reservoir rock trough the field. Finally, we developed a neural network permeability model using porosity, gamma ray and the geologic fuzzy variable as input variables. This model has a cross-correlation coefficient of 0.873 and average absolute error of 33% compared with the actual model with a correlation coefficient of 0.511 and absolute error greater than 250%. We tested different methodologies, but this new one showed dramatically be a promiser way to get better permeability models. The use of the models have had a high impact in the explanation of well performance and workovers, and reservoir simulation models. (author)

Plasticity models of material variability based on uncertainty quantification techniques

Energy Technology Data Exchange (ETDEWEB)

Jones, Reese E. [Sandia National Lab. (SNL-CA), Livermore, CA (United States); Rizzi, Francesco [Sandia National Lab. (SNL-CA), Livermore, CA (United States); Boyce, Brad [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Templeton, Jeremy Alan [Sandia National Lab. (SNL-CA), Livermore, CA (United States); Ostien, Jakob [Sandia National Lab. (SNL-CA), Livermore, CA (United States)

2017-11-01

The advent of fabrication techniques like additive manufacturing has focused attention on the considerable variability of material response due to defects and other micro-structural aspects. This variability motivates the development of an enhanced design methodology that incorporates inherent material variability to provide robust predictions of performance. In this work, we develop plasticity models capable of representing the distribution of mechanical responses observed in experiments using traditional plasticity models of the mean response and recently developed uncertainty quantification (UQ) techniques. Lastly, we demonstrate that the new method provides predictive realizations that are superior to more traditional ones, and how these UQ techniques can be used in model selection and assessing the quality of calibrated physical parameters.

Efficient Business Service Consumption by Customization with Variability Modelling

Directory of Open Access Journals (Sweden)

Michael Stollberg

2010-07-01

Full Text Available The establishment of service orientation in industry determines the need for efficient engineering technologies that properly support the whole life cycle of service provision and consumption. A central challenge is adequate support for the efficient employment of komplex services in their individual application context. This becomes particularly important for large-scale enterprise technologies where generic services are designed for reuse in several business scenarios. In this article we complement our work regarding Service Variability Modelling presented in a previous publication. There we presented an approach for the customization of services for individual application contexts by creating simplified variants, based on model-driven variability management. That work presents our revised service variability metamodel, new features of the variability tools and an applicability study, which reveals that substantial improvements on the efficiency of standard business service consumption under both usability and economic aspects can be achieved.

Internal Stress in a Model Elasto-Plastic Fluid

OpenAIRE

Ooshida, Takeshi; Sekimoto, Ken

2004-01-01

Plastic materials can carry memory of past mechanical treatment in the form of internal stress. We introduce a natural definition of the vorticity of internal stress in a simple two-dimensional model of elasto-plastic fluids, which generates the internal stress. We demonstrate how the internal stress is induced under external loading, and how the presence of the internal stress modifies the plastic behavior.

Multi-messenger Light Curves from Gamma-Ray Bursts in the Internal Shock Model

Energy Technology Data Exchange (ETDEWEB)

Bustamante, Mauricio [Center for Cosmology and AstroParticle Physics (CCAPP), The Ohio State University, Columbus, OH 43210 (United States); Heinze, Jonas; Winter, Walter [Deutsches Elektronen-Synchrotron (DESY), Platanenallee 6, D-15738 Zeuthen (Germany); Murase, Kohta, E-mail: bustamanteramirez.1@osu.edu, E-mail: walter.winter@desy.de, E-mail: jonas.heinze@desy.de, E-mail: murase@psu.edu [Center for Particle and Gravitational Astrophysics, The Pennsylvania State University, University Park, PA16802 (United States)

2017-03-01

Gamma-ray bursts (GRBs) are promising as sources of neutrinos and cosmic rays. In the internal shock scenario, blobs of plasma emitted from a central engine collide within a relativistic jet and form shocks, leading to particle acceleration and emission. Motivated by present experimental constraints and sensitivities, we improve the predictions of particle emission by investigating time-dependent effects from multiple shocks. We produce synthetic light curves with different variability timescales that stem from properties of the central engine. For individual GRBs, qualitative conclusions about model parameters, neutrino production efficiency, and delays in high-energy gamma-rays can be deduced from inspection of the gamma-ray light curves. GRBs with fast time variability without additional prominent pulse structure tend to be efficient neutrino emitters, whereas GRBs with fast variability modulated by a broad pulse structure can be inefficient neutrino emitters and produce delayed high-energy gamma-ray signals. Our results can be applied to quantitative tests of the GRB origin of ultra-high-energy cosmic rays, and have the potential to impact current and future multi-messenger searches.

Multi-messenger light curves from gamma-ray bursts in the internal shock model

Energy Technology Data Exchange (ETDEWEB)

Bustamante, Mauricio [Ohio State Univ., Columbus, OH (United States). Center for Cosmology and AstroParticle Physics (CCAPP); Ohio State Univ., Columbus, OH (United States). Dept. of Physics; Murase, Kohta [Pennsylvania State Univ., University Park, PA (United States). Center for Particle and Gravitational Astrophysics; Pennsylvania State Univ., University Park, PA (United States). Dept. of Astronomy and Astrophysics; Winter, Walter [Deutsches Elektronen-Synchrotron (DESY), Zeuthen (Germany)

2016-06-15

Gamma-ray bursts (GRBs) are promising as sources of neutrinos and cosmic rays. In the internal shock scenario, blobs of plasma emitted from a central engine collide within a relativistic jet and form shocks, leading to particle acceleration and emission. Motivated by present experimental constraints and sensitivities, we improve the predictions of particle emission by investigating time-dependent effects from multiple shocks. We produce synthetic light curves with different variability timescales that stem from properties of the central engine. For individual GRBs, qualitative conclusions about model parameters, neutrino production efficiency, and delays in high-energy gamma rays can be deduced from inspection of the gamma-ray light curves. GRBs with fast time variability without additional prominent pulse structure tend to be efficient neutrino emitters, whereas GRBs with fast variability modulated by a broad pulse structure tend to be inefficient neutrino emitters and produce delayed high-energy gamma-ray signals. Our results can be applied to quantitative tests of the GRB origin of ultra-high-energy cosmic rays, and have the potential to impact current and future multi-messenger searches.

Prognostic importance of glycaemic variability on hospital mortality in patients hospitalised in Internal Medicine Departments.

Science.gov (United States)

Sáenz-Abad, D; Gimeno-Orna, J A; Pérez-Calvo, J I

2015-12-01

The objective was to assess the prognostic importance of various glycaemic control measures on hospital mortality. Retrospective, analytical cohort study that included patients hospitalised in internal medicine departments with a diagnosis related to diabetes mellitus (DM), excluding acute decompensations. The clinical endpoint was hospital mortality. We recorded clinical, analytical and glycaemic control-related variables (scheduled insulin administration, plasma glycaemia at admission, HbA1c, mean glycaemia (MG) and in-hospital glycaemic variability and hypoglycaemia). The measurement of hospital mortality predictors was performed using univariate and multivariate logistic regression. A total of 384 patients (50.3% men) were included. The mean age was 78.5 (SD, 10.3) years. The DM-related diagnoses were type 2 diabetes (83.6%) and stress hyperglycaemia (6.8%). Thirty-one (8.1%) patients died while in hospital. In the multivariate analysis, the best model for predicting mortality (R(2)=0.326; P<.0001) consisted, in order of importance, of age (χ(2)=8.19; OR=1.094; 95% CI 1.020-1.174; P=.004), Charlson index (χ(2)=7.28; OR=1.48; 95% CI 1.11-1.99; P=.007), initial glycaemia (χ(2)=6.05; OR=1.007; 95% CI 1.001-1.014; P=.014), HbA1c (χ(2)=5.76; OR=0.59; 95% CI 0.33-1; P=.016), glycaemic variability (χ(2)=4.41; OR=1.031; 95% CI 1-1.062; P=.036), need for corticosteroid treatment (χ(2)=4.03; OR=3.1; 95% CI 1-9.64; P=.045), administration of scheduled insulin (χ(2)=3.98; OR=0.26; 95% CI 0.066-1; P=.046) and systolic blood pressure (χ(2)=2.92; OR=0.985; 95% CI 0.97-1.003; P=.088). An increase in initial glycaemia and in-hospital glycaemic variability predict the risk of mortality for hospitalised patients with DM. Copyright © 2015 Elsevier España, S.L.U. y Sociedad Española de Medicina Interna (SEMI). All rights reserved.

Combustion modeling in internal combustion engines

Science.gov (United States)

Zeleznik, F. J.

1976-01-01

The fundamental assumptions of the Blizard and Keck combustion model for internal combustion engines are examined and a generalization of that model is derived. The most significant feature of the model is that it permits the occurrence of unburned hydrocarbons in the thermodynamic-kinetic modeling of exhaust gases. The general formulas are evaluated in two specific cases that are likely to be significant in the applications of the model.

Analytical model of cracking due to rebar corrosion expansion in concrete considering the structure internal force

Science.gov (United States)

Lin, Xiangyue; Peng, Minli; Lei, Fengming; Tan, Jiangxian; Shi, Huacheng

2017-12-01

Based on the assumptions of uniform corrosion and linear elastic expansion, an analytical model of cracking due to rebar corrosion expansion in concrete was established, which is able to consider the structure internal force. And then, by means of the complex variable function theory and series expansion technology established by Muskhelishvili, the corresponding stress component functions of concrete around the reinforcement were obtained. Also, a comparative analysis was conducted between the numerical simulation model and present model in this paper. The results show that the calculation results of both methods were consistent with each other, and the numerical deviation was less than 10%, proving that the analytical model established in this paper is reliable.

Generalized Network Psychometrics : Combining Network and Latent Variable Models

NARCIS (Netherlands)

Epskamp, S.; Rhemtulla, M.; Borsboom, D.

2017-01-01

We introduce the network model as a formal psychometric model, conceptualizing the covariance between psychometric indicators as resulting from pairwise interactions between observable variables in a network structure. This contrasts with standard psychometric models, in which the covariance between

Can Geostatistical Models Represent Nature's Variability? An Analysis Using Flume Experiments

Science.gov (United States)

Scheidt, C.; Fernandes, A. M.; Paola, C.; Caers, J.

2015-12-01

The lack of understanding in the Earth's geological and physical processes governing sediment deposition render subsurface modeling subject to large uncertainty. Geostatistics is often used to model uncertainty because of its capability to stochastically generate spatially varying realizations of the subsurface. These methods can generate a range of realizations of a given pattern - but how representative are these of the full natural variability? And how can we identify the minimum set of images that represent this natural variability? Here we use this minimum set to define the geostatistical prior model: a set of training images that represent the range of patterns generated by autogenic variability in the sedimentary environment under study. The proper definition of the prior model is essential in capturing the variability of the depositional patterns. This work starts with a set of overhead images from an experimental basin that showed ongoing autogenic variability. We use the images to analyze the essential characteristics of this suite of patterns. In particular, our goal is to define a prior model (a minimal set of selected training images) such that geostatistical algorithms, when applied to this set, can reproduce the full measured variability. A necessary prerequisite is to define a measure of variability. In this study, we measure variability using a dissimilarity distance between the images. The distance indicates whether two snapshots contain similar depositional patterns. To reproduce the variability in the images, we apply an MPS algorithm to the set of selected snapshots of the sedimentary basin that serve as training images. The training images are chosen from among the initial set by using the distance measure to ensure that only dissimilar images are chosen. Preliminary investigations show that MPS can reproduce fairly accurately the natural variability of the experimental depositional system. Furthermore, the selected training images provide

High performance continuously variable transmission control through robust-control-relevant model validation

NARCIS (Netherlands)

Oomen, T.A.E.; Meulen, van der S.H.

2013-01-01

Optimal operation of continuously variable transmissions (CVTs) is essential to meet tightening emission and fuel consumption requirements. This is achieved by accurately tracking a prescribed transmission ratio reference and simultaneously optimizing the internal efficiency of the CVT. To reduce

Internal Representational Models of Attachment Relationships.

Science.gov (United States)

Crittenden, Patricia M.

This paper outlines several properties of internal representational models (IRMs) and offers terminology that may help to differentiate the models. Properties of IRMs include focus, memory systems, content, cognitive function, "metastructure," quality of attachment, behavioral strategies, and attitude toward attachment. An IRM focuses on…

A model of turbocharger radial turbines appropriate to be used in zero- and one-dimensional gas dynamics codes for internal combustion engines modelling

Energy Technology Data Exchange (ETDEWEB)

Serrano, J.R.; Arnau, F.J.; Dolz, V.; Tiseira, A. [CMT-Motores Termicos, Universidad Politecnica de Valencia, Camino de Vera s/n, 46022 Valencia (Spain); Cervello, C. [Conselleria de Cultura, Educacion y Deporte, Generalitat Valenciana (Spain)

2008-12-15

The paper presents a model of fixed and variable geometry turbines. The aim of this model is to provide an efficient boundary condition to model turbocharged internal combustion engines with zero- and one-dimensional gas dynamic codes. The model is based from its very conception on the measured characteristics of the turbine. Nevertheless, it is capable of extrapolating operating conditions that differ from those included in the turbine maps, since the engines usually work within these zones. The presented model has been implemented in a one-dimensional gas dynamic code and has been used to calculate unsteady operating conditions for several turbines. The results obtained have been compared with success against pressure-time histories measured upstream and downstream of the turbine during on-engine operation. (author)

A model of turbocharger radial turbines appropriate to be used in zero- and one-dimensional gas dynamics codes for internal combustion engines modelling

International Nuclear Information System (INIS)

Serrano, J.R.; Arnau, F.J.; Dolz, V.; Tiseira, A.; Cervello, C.

2008-01-01

The paper presents a model of fixed and variable geometry turbines. The aim of this model is to provide an efficient boundary condition to model turbocharged internal combustion engines with zero- and one-dimensional gas dynamic codes. The model is based from its very conception on the measured characteristics of the turbine. Nevertheless, it is capable of extrapolating operating conditions that differ from those included in the turbine maps, since the engines usually work within these zones. The presented model has been implemented in a one-dimensional gas dynamic code and has been used to calculate unsteady operating conditions for several turbines. The results obtained have been compared with success against pressure-time histories measured upstream and downstream of the turbine during on-engine operation

Pengaruh Pemasaran Internal dan Kualitas Layanan Internal Terhadap Kepuasan Pelanggan Internal (Studi Pada Industri Kepariwisataan di Daerah Istimewa Yogyakarta

Directory of Open Access Journals (Sweden)

Jumadi Jumadi

2016-06-01

Full Text Available The aim of this research is to investigate the implication of internal marketing and internal service quality effectivity towards internal customer satisfaction in Tourism Industry in Yogyakarta Special Territory. This internal marketing studyinvolves variables of motivation and reward system, effective communication, effective employee's selection, effective recruitment, effective development, effective support system, and healthy work environment. While the internal quality service aspects that will be examined in this study are: tangible, emphaty, responsiveness, reliability and assurance, and then their influences on internal customer satisfaction would be analyzed.The sample size is 210 respondents,which is determined using purposive sampling method. The main instrument for data collection in this study is through questionnaire. The analysis tool used to examine the hypothesis of the study is Structural Equation Modeling using AMOS Version 20.0 Software. The result of the study shows that: Internal marketing and internal quality service significantly influence internal customers satisfation. However, the internal quality service influence the internal customers satisfaction more significantly. Therefore the managers in tourism industry should improve the internal marketing more than the internal quality service.

Impulsive synchronization and parameter mismatch of the three-variable autocatalator model

International Nuclear Information System (INIS)

Li, Yang; Liao, Xiaofeng; Li, Chuandong; Huang, Tingwen; Yang, Degang

2007-01-01

The synchronization problems of the three-variable autocatalator model via impulsive control approach are investigated; several theorems on the stability of impulsive control systems are also investigated. These theorems are then used to find the conditions under which the three-variable autocatalator model can be asymptotically controlled to the equilibrium point. This Letter derives some sufficient conditions for the stabilization and synchronization of a three-variable autocatalator model via impulsive control with varying impulsive intervals. Furthermore, we address the chaos quasi-synchronization in the presence of single-parameter mismatch. To illustrate the effectiveness of the new scheme, several numerical examples are given

Constraint-Led Changes in Internal Variability in Running

OpenAIRE

Haudum, Anita; Birklbauer, Jürgen; Kröll, Josef; Müller, Erich

2012-01-01

We investigated the effect of a one-time application of elastic constraints on movement-inherent variability during treadmill running. Eleven males ran two 35-min intervals while surface EMG was measured. In one of two 35-min intervals, after 10 min of running without tubes, elastic tubes (between hip and heels) were attached, followed by another 5 min of running without tubes. To assess variability, stride-to-stride iEMG variability was calculated. Significant increases in variability (36 % ...

Variable cycle control model for intersection based on multi-source information

Science.gov (United States)

Sun, Zhi-Yuan; Li, Yue; Qu, Wen-Cong; Chen, Yan-Yan

2018-05-01

In order to improve the efficiency of traffic control system in the era of big data, a new variable cycle control model based on multi-source information is presented for intersection in this paper. Firstly, with consideration of multi-source information, a unified framework based on cyber-physical system is proposed. Secondly, taking into account the variable length of cell, hysteresis phenomenon of traffic flow and the characteristics of lane group, a Lane group-based Cell Transmission Model is established to describe the physical properties of traffic flow under different traffic signal control schemes. Thirdly, the variable cycle control problem is abstracted into a bi-level programming model. The upper level model is put forward for cycle length optimization considering traffic capacity and delay. The lower level model is a dynamic signal control decision model based on fairness analysis. Then, a Hybrid Intelligent Optimization Algorithm is raised to solve the proposed model. Finally, a case study shows the efficiency and applicability of the proposed model and algorithm.

Influence of an Internally-Generated QBO on Modeled Stratospheric Dynamics and Ozone

Science.gov (United States)

Hurwitz, M. M.; Newman, P. A.; Song, I. S.

2011-01-01

A GEOS V2 CCM simulation with an internally generated quasi-biennial oscillation (QBO) signal is compared to an otherwise identical simulation without a QBO. In a present-day climate, inclusion of the modeled QBO makes a significant difference to stratospheric dynamics and ozone throughout the year. The QBO enhances variability in the tropics, as expected, but also in the polar stratosphere in some seasons. The modeled QBO also affects the mean stratospheric climate. Because tropical zonal winds in the baseline simulation are generally easterly, there is a relative increase in zonal wind magnitudes in tropical lower and middle stratosphere in the QBO simulation. Extra-tropical differences between the QBO and 'no QBO' simulations thus reflect a bias toward the westerly phase of the QBO: a relative strengthening and poleward shifting the polar stratospheric jets, and a reduction in Arctic lower stratospheric ozone.

A variable resolution nonhydrostatic global atmospheric semi-implicit semi-Lagrangian model

Science.gov (United States)

Pouliot, George Antoine

2000-10-01

The objective of this project is to develop a variable-resolution finite difference adiabatic global nonhydrostatic semi-implicit semi-Lagrangian (SISL) model based on the fully compressible nonhydrostatic atmospheric equations. To achieve this goal, a three-dimensional variable resolution dynamical core was developed and tested. The main characteristics of the dynamical core can be summarized as follows: Spherical coordinates were used in a global domain. A hydrostatic/nonhydrostatic switch was incorporated into the dynamical equations to use the fully compressible atmospheric equations. A generalized horizontal variable resolution grid was developed and incorporated into the model. For a variable resolution grid, in contrast to a uniform resolution grid, the order of accuracy of finite difference approximations is formally lost but remains close to the order of accuracy associated with the uniform resolution grid provided the grid stretching is not too significant. The SISL numerical scheme was implemented for the fully compressible set of equations. In addition, the generalized minimum residual (GMRES) method with restart and preconditioner was used to solve the three-dimensional elliptic equation derived from the discretized system of equations. The three-dimensional momentum equation was integrated in vector-form to incorporate the metric terms in the calculations of the trajectories. Using global re-analysis data for a specific test case, the model was compared to similar SISL models previously developed. Reasonable agreement between the model and the other independently developed models was obtained. The Held-Suarez test for dynamical cores was used for a long integration and the model was successfully integrated for up to 1200 days. Idealized topography was used to test the variable resolution component of the model. Nonhydrostatic effects were simulated at grid spacings of 400 meters with idealized topography and uniform flow. Using a high

Disentangling Global Warming, Multidecadal Variability, and El Niño in Pacific Temperatures

Science.gov (United States)

Wills, Robert C.; Schneider, Tapio; Wallace, John M.; Battisti, David S.; Hartmann, Dennis L.

2018-03-01

A key challenge in climate science is to separate observed temperature changes into components due to internal variability and responses to external forcing. Extended integrations of forced and unforced climate models are often used for this purpose. Here we demonstrate a novel method to separate modes of internal variability from global warming based on differences in time scale and spatial pattern, without relying on climate models. We identify uncorrelated components of Pacific sea surface temperature variability due to global warming, the Pacific Decadal Oscillation (PDO), and the El Niño-Southern Oscillation (ENSO). Our results give statistical representations of PDO and ENSO that are consistent with their being separate processes, operating on different time scales, but are otherwise consistent with canonical definitions. We isolate the multidecadal variability of the PDO and find that it is confined to midlatitudes; tropical sea surface temperatures and their teleconnections mix in higher-frequency variability. This implies that midlatitude PDO anomalies are more persistent than previously thought.

Variable Fidelity Aeroelastic Toolkit - Structural Model, Phase I

Data.gov (United States)

National Aeronautics and Space Administration — The proposed innovation is a methodology to incorporate variable fidelity structural models into steady and unsteady aeroelastic and aeroservoelastic analyses in...

The Properties of Model Selection when Retaining Theory Variables

DEFF Research Database (Denmark)

Hendry, David F.; Johansen, Søren

Economic theories are often fitted directly to data to avoid possible model selection biases. We show that embedding a theory model that specifies the correct set of m relevant exogenous variables, x{t}, within the larger set of m+k candidate variables, (x{t},w{t}), then selection over the second...... set by their statistical significance can be undertaken without affecting the estimator distribution of the theory parameters. This strategy returns the theory-parameter estimates when the theory is correct, yet protects against the theory being under-specified because some w{t} are relevant....

Anticommuting variables, internal degrees of freedom, and the Wilson loop

International Nuclear Information System (INIS)

Barducci, A.; Casalbuoni, R.; Lusanna, L.

1981-01-01

In this paper we show that is possible to give a real physical meaning to theories in which internal degrees of freedom are described by Grassmann variables. The physical theory is defined by means of an averaging procedure in terms of a distribution function in the Grassmann restricted space satisfying all the physical requirements. If we use this result for a scalar particle with inner degrees of freedom (electric charge, colour, ...) interacting with Yang-Mills gauge fields, it turns out that we can define two different classical theories. Taking the average of the coupled particle-field equations of motion, we recover the usual classical theory. Taking instead the average of the solution of such equations we get a theory which is free from all the classical infinities (and so of the causal defects, like runaway solution or pre-acceleration) but also of all the effects of the same order in the charges (like radiation). The main point is that the processes of averaging and integrating the equations of motion do not commute. Then for the case of colour degrees of freedom we study the quantization of the theory by the path-integral method and we show that the functional integration can be done for an arbitrary gluon field simply by using the classical solution. As a result we obtain an expression for the Wilson loop as a functional integral for the internal fermionic degrees of freedom. (orig.)

Present and Future Modes of Low Frequency Climate Variability

Energy Technology Data Exchange (ETDEWEB)

Cane, Mark A.

2014-02-20

This project addressed area (1) of the FOA, “Interaction of Climate Change and Low Frequency Modes of Natural Climate Variability”. Our overarching objective is to detect, describe and understand the changes in low frequency variability between model simulations of the preindustrial climate and simulations of a doubled CO2 climate. The deliverables are a set of papers providing a dynamical characterization of interannual, decadal, and multidecadal variability in coupled models with attention to the changes in this low frequency variability between pre-industrial concentrations of greenhouse gases and a doubling of atmospheric concentrations of CO2. The principle mode of analysis, singular vector decomposition, is designed to advance our physical, mechanistic understanding. This study will include external natural variability due to solar and volcanic aerosol variations as well as variability internal to the climate system. An important byproduct is a set of analysis tools for estimating global singular vector structures from the archived output of model simulations.

One-Dimensional Modelling of Internal Ballistics

Science.gov (United States)

Monreal-González, G.; Otón-Martínez, R. A.; Velasco, F. J. S.; García-Cascáles, J. R.; Ramírez-Fernández, F. J.

2017-10-01

A one-dimensional model is introduced in this paper for problems of internal ballistics involving solid propellant combustion. First, the work presents the physical approach and equations adopted. Closure relationships accounting for the physical phenomena taking place during combustion (interfacial friction, interfacial heat transfer, combustion) are deeply discussed. Secondly, the numerical method proposed is presented. Finally, numerical results provided by this code (UXGun) are compared with results of experimental tests and with the outcome from a well-known zero-dimensional code. The model provides successful results in firing tests of artillery guns, predicting with good accuracy the maximum pressure in the chamber and muzzle velocity what highlights its capabilities as prediction/design tool for internal ballistics.

Constraint-led changes in internal variability in running.

Science.gov (United States)

Haudum, Anita; Birklbauer, Jürgen; Kröll, Josef; Müller, Erich

2012-01-01

We investigated the effect of a one-time application of elastic constraints on movement-inherent variability during treadmill running. Eleven males ran two 35-min intervals while surface EMG was measured. In one of two 35-min intervals, after 10 min of running without tubes, elastic tubes (between hip and heels) were attached, followed by another 5 min of running without tubes. To assess variability, stride-to-stride iEMG variability was calculated. Significant increases in variability (36 % to 74 %) were observed during tube running, whereas running without tubes after the tube running block showed no significant differences. Results show that elastic tubes affect variability on a muscular level despite the constant environmental conditions and underline the nervous system's adaptability to cope with somehow unpredictable constraints since stride duration was unaltered.

A review of a method for dynamic load distribution, dynamical modeling, and explicit internal force control when two manipulators mutually lift and transport a rigid body object

International Nuclear Information System (INIS)

Unseren, M.A.

1997-01-01

The paper reviews a method for modeling and controlling two serial link manipulators which mutually lift and transport a rigid body object in a three dimensional workspace. A new vector variable is introduced which parameterizes the internal contact force controlled degrees of freedom. A technique for dynamically distributing the payload between the manipulators is suggested which yields a family of solutions for the contact forces and torques the manipulators impart to the object. A set of rigid body kinematic constraints which restrict the values of the joint velocities of both manipulators is derived. A rigid body dynamical model for the closed chain system is first developed in the joint space. The model is obtained by generalizing the previous methods for deriving the model. The joint velocity and acceleration variables in the model are expressed in terms of independent pseudovariables. The pseudospace model is transformed to obtain reduced order equations of motion and a separate set of equations governing the internal components of the contact forces and torques. A theoretic control architecture is suggested which explicitly decouples the two sets of equations comprising the model. The controller enables the designer to develop independent, non-interacting control laws for the position control and internal force control of the system

A review of a method for dynamic load distribution, dynamical modeling, and explicit internal force control when two manipulators mutually lift and transport a rigid body object

Energy Technology Data Exchange (ETDEWEB)

Unseren, M.A.

1997-04-20

The paper reviews a method for modeling and controlling two serial link manipulators which mutually lift and transport a rigid body object in a three dimensional workspace. A new vector variable is introduced which parameterizes the internal contact force controlled degrees of freedom. A technique for dynamically distributing the payload between the manipulators is suggested which yields a family of solutions for the contact forces and torques the manipulators impart to the object. A set of rigid body kinematic constraints which restrict the values of the joint velocities of both manipulators is derived. A rigid body dynamical model for the closed chain system is first developed in the joint space. The model is obtained by generalizing the previous methods for deriving the model. The joint velocity and acceleration variables in the model are expressed in terms of independent pseudovariables. The pseudospace model is transformed to obtain reduced order equations of motion and a separate set of equations governing the internal components of the contact forces and torques. A theoretic control architecture is suggested which explicitly decouples the two sets of equations comprising the model. The controller enables the designer to develop independent, non-interacting control laws for the position control and internal force control of the system.

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.

Influences of variables on ship collision probability in a Bayesian belief network model

International Nuclear Information System (INIS)

Hänninen, Maria; Kujala, Pentti

2012-01-01

The influences of the variables in a Bayesian belief network model for estimating the role of human factors on ship collision probability in the Gulf of Finland are studied for discovering the variables with the largest influences and for examining the validity of the network. The change in the so-called causation probability is examined while observing each state of the network variables and by utilizing sensitivity and mutual information analyses. Changing course in an encounter situation is the most influential variable in the model, followed by variables such as the Officer of the Watch's action, situation assessment, danger detection, personal condition and incapacitation. The least influential variables are the other distractions on bridge, the bridge view, maintenance routines and the officer's fatigue. In general, the methods are found to agree on the order of the model variables although some disagreements arise due to slightly dissimilar approaches to the concept of variable influence. The relative values and the ranking of variables based on the values are discovered to be more valuable than the actual numerical values themselves. Although the most influential variables seem to be plausible, there are some discrepancies between the indicated influences in the model and literature. Thus, improvements are suggested to the network.

A margin model to account for respiration-induced tumour motion and its variability

International Nuclear Information System (INIS)

Coolens, Catherine; Webb, Steve; Evans, Phil M; Shirato, H; Nishioka, K

2008-01-01

In order to reduce the sensitivity of radiotherapy treatments to organ motion, compensation methods are being investigated such as gating of treatment delivery, tracking of tumour position, 4D scanning and planning of the treatment, etc. An outstanding problem that would occur with all these methods is the assumption that breathing motion is reproducible throughout the planning and delivery process of treatment. This is obviously not a realistic assumption and is one that will introduce errors. A dynamic internal margin model (DIM) is presented that is designed to follow the tumour trajectory and account for the variability in respiratory motion. The model statistically describes the variation of the breathing cycle over time, i.e. the uncertainty in motion amplitude and phase reproducibility, in a polar coordinate system from which margins can be derived. This allows accounting for an additional gating window parameter for gated treatment delivery as well as minimizing the area of normal tissue irradiated. The model was illustrated with abdominal motion for a patient with liver cancer and tested with internal 3D lung tumour trajectories. The results confirm that the respiratory phases around exhale are most reproducible and have the smallest variation in motion amplitude and phase (approximately 2 mm). More importantly, the margin area covering normal tissue is significantly reduced by using trajectory-specific margins (as opposed to conventional margins) as the angular component is by far the largest contributor to the margin area. The statistical approach to margin calculation, in addition, offers the possibility for advanced online verification and updating of breathing variation as more data become available

Uncertainty and variability in computational and mathematical models of cardiac physiology.

Science.gov (United States)

Mirams, Gary R; Pathmanathan, Pras; Gray, Richard A; Challenor, Peter; Clayton, Richard H

2016-12-01

Mathematical and computational models of cardiac physiology have been an integral component of cardiac electrophysiology since its inception, and are collectively known as the Cardiac Physiome. We identify and classify the numerous sources of variability and uncertainty in model formulation, parameters and other inputs that arise from both natural variation in experimental data and lack of knowledge. The impact of uncertainty on the outputs of Cardiac Physiome models is not well understood, and this limits their utility as clinical tools. We argue that incorporating variability and uncertainty should be a high priority for the future of the Cardiac Physiome. We suggest investigating the adoption of approaches developed in other areas of science and engineering while recognising unique challenges for the Cardiac Physiome; it is likely that novel methods will be necessary that require engagement with the mathematics and statistics community. The Cardiac Physiome effort is one of the most mature and successful applications of mathematical and computational modelling for describing and advancing the understanding of physiology. After five decades of development, physiological cardiac models are poised to realise the promise of translational research via clinical applications such as drug development and patient-specific approaches as well as ablation, cardiac resynchronisation and contractility modulation therapies. For models to be included as a vital component of the decision process in safety-critical applications, rigorous assessment of model credibility will be required. This White Paper describes one aspect of this process by identifying and classifying sources of variability and uncertainty in models as well as their implications for the application and development of cardiac models. We stress the need to understand and quantify the sources of variability and uncertainty in model inputs, and the impact of model structure and complexity and their consequences for

Natural climate variability in a coupled model

International Nuclear Information System (INIS)

Zebiak, S.E.; Cane, M.A.

1990-01-01

Multi-century simulations with a simplified coupled ocean-atmosphere model are described. These simulations reveal an impressive range of variability on decadal and longer time scales, in addition to the dominant interannual el Nino/Southern Oscillation signal that the model originally was designed to simulate. Based on a very large sample of century-long simulations, it is nonetheless possible to identify distinct model parameter sensitivities that are described here in terms of selected indices. Preliminary experiments motivated by general circulation model results for increasing greenhouse gases suggest a definite sensitivity to model global warming. While these results are not definitive, they strongly suggest that coupled air-sea dynamics figure prominently in global change and must be included in models for reliable predictions

Thermomechanical and calorimetric behaviours of supported glass-forming films: A study based on thermodynamics with internal variables

International Nuclear Information System (INIS)

Lion, Alexander; Engelhard, Marco; Johlitz, Michael

2012-01-01

In order to understand the temperature-dependent response behaviour of thin thermoviscoelastic films which are deposited on relative stiff but thermally deformable substrates it is important to consider the lateral geometric constraints. They are generated by differences in the thermal expansion properties between the substrate and the film and provoke internal stresses. Since glass-forming materials exhibit distinct temperature history-dependent thermal expansion and calorimetric properties, primarily in the vicinity of the glass transition, the situation is rather complicated. In this article, a recently developed three-dimensional model of thermodynamics with internal variables is applied and adapted to simulate this type of behaviour. Explicit relations are obtained for the specific heat of the film, the normal strain and the lateral stresses. Numerical simulations demonstrate that the magnitude of the internal stress at temperatures below the glass transition depends strongly on the cooling rate. It is also shown that the specific heat of the supported film is principally different from the isobaric specific heat of the bulk material: the glassy limit of the specific heat of the film is reduced but the glass transition temperature is almost uninfluenced. The simulated behaviour is in accordance with experimental observations from literature. - Highlights: ► For the specific heat, stress and strain of the film, explicit equations were derived. ► The constraints of the substrate reduce the glassy limit of specific heat of the film. ► Glass transition temperatures of free bulk material and supported film are equal. ► Simulations are in good agreement with experimental observations from literature.

SME International Business Models: The Role of Context and Experience

DEFF Research Database (Denmark)

Child, John; Hsieh, Linda; Elbanna, Said

2017-01-01

This paper addresses two questions through a study of 180 SMEs located in contrasting industry and home country contexts. First, which business models for international markets prevail among SMEs and do they configure into different types? Second, which factors predict the international business...... models that SMEs follow? Three distinct international business models (traditional market-adaptive, technology exploiter, and ambidextrous explorer) are found among the SMEs studied. The likelihood of SMEs adopting one business model rather than another is to a high degree predictable with reference...

AMOC decadal variability in Earth system models: Mechanisms and climate impacts

Energy Technology Data Exchange (ETDEWEB)

Fedorov, Alexey [Yale Univ., New Haven, CT (United States)

2017-09-06

This is the final report for the project titled "AMOC decadal variability in Earth system models: Mechanisms and climate impacts". The central goal of this one-year research project was to understand the mechanisms of decadal and multi-decadal variability of the Atlantic Meridional Overturning Circulation (AMOC) within a hierarchy of climate models ranging from realistic ocean GCMs to Earth system models. The AMOC is a key element of ocean circulation responsible for oceanic transport of heat from low to high latitudes and controlling, to a large extent, climate variations in the North Atlantic. The questions of the AMOC stability, variability and predictability, directly relevant to the questions of climate predictability, were at the center of the research work.

Higher-dimensional cosmological model with variable gravitational ...

Indian Academy of Sciences (India)

variable G and bulk viscosity in Lyra geometry. Exact solutions for ... a comparative study of Robertson–Walker models with a constant deceleration .... where H is defined as H =(˙A/A)+(1/3)( ˙B/B) and β0,H0 are representing present values of β ...

Tropospheric Ozone Assessment Report: Assessment of global-scale model performance for global and regional ozone distributions, variability, and trends

Directory of Open Access Journals (Sweden)

P. J. Young

2018-01-01

Full Text Available The goal of the Tropospheric Ozone Assessment Report (TOAR is to provide the research community with an up-to-date scientific assessment of tropospheric ozone, from the surface to the tropopause. While a suite of observations provides significant information on the spatial and temporal distribution of tropospheric ozone, observational gaps make it necessary to use global atmospheric chemistry models to synthesize our understanding of the processes and variables that control tropospheric ozone abundance and its variability. Models facilitate the interpretation of the observations and allow us to make projections of future tropospheric ozone and trace gas distributions for different anthropogenic or natural perturbations. This paper assesses the skill of current-generation global atmospheric chemistry models in simulating the observed present-day tropospheric ozone distribution, variability, and trends. Drawing upon the results of recent international multi-model intercomparisons and using a range of model evaluation techniques, we demonstrate that global chemistry models are broadly skillful in capturing the spatio-temporal variations of tropospheric ozone over the seasonal cycle, for extreme pollution episodes, and changes over interannual to decadal periods. However, models are consistently biased high in the northern hemisphere and biased low in the southern hemisphere, throughout the depth of the troposphere, and are unable to replicate particular metrics that define the longer term trends in tropospheric ozone as derived from some background sites. When the models compare unfavorably against observations, we discuss the potential causes of model biases and propose directions for future developments, including improved evaluations that may be able to better diagnose the root cause of the model-observation disparity. Overall, model results should be approached critically, including determining whether the model performance is acceptable for

Modeling temporal and spatial variability of traffic-related air pollution: Hourly land use regression models for black carbon

Science.gov (United States)

Dons, Evi; Van Poppel, Martine; Kochan, Bruno; Wets, Geert; Int Panis, Luc

2013-08-01

Land use regression (LUR) modeling is a statistical technique used to determine exposure to air pollutants in epidemiological studies. Time-activity diaries can be combined with LUR models, enabling detailed exposure estimation and limiting exposure misclassification, both in shorter and longer time lags. In this study, the traffic related air pollutant black carbon was measured with μ-aethalometers on a 5-min time base at 63 locations in Flanders, Belgium. The measurements show that hourly concentrations vary between different locations, but also over the day. Furthermore the diurnal pattern is different for street and background locations. This suggests that annual LUR models are not sufficient to capture all the variation. Hourly LUR models for black carbon are developed using different strategies: by means of dummy variables, with dynamic dependent variables and/or with dynamic and static independent variables. The LUR model with 48 dummies (weekday hours and weekend hours) performs not as good as the annual model (explained variance of 0.44 compared to 0.77 in the annual model). The dataset with hourly concentrations of black carbon can be used to recalibrate the annual model, resulting in many of the original explaining variables losing their statistical significance, and certain variables having the wrong direction of effect. Building new independent hourly models, with static or dynamic covariates, is proposed as the best solution to solve these issues. R2 values for hourly LUR models are mostly smaller than the R2 of the annual model, ranging from 0.07 to 0.8. Between 6 a.m. and 10 p.m. on weekdays the R2 approximates the annual model R2. Even though models of consecutive hours are developed independently, similar variables turn out to be significant. Using dynamic covariates instead of static covariates, i.e. hourly traffic intensities and hourly population densities, did not significantly improve the models' performance.

BIOMOVS: an international model validation study

International Nuclear Information System (INIS)

Haegg, C.; Johansson, G.

1988-01-01

BIOMOVS (BIOspheric MOdel Validation Study) is an international study where models used for describing the distribution of radioactive and nonradioactive trace substances in terrestrial and aquatic environments are compared and tested. The main objectives of the study are to compare and test the accuracy of predictions between such models, explain differences in these predictions, recommend priorities for future research concerning the improvement of the accuracy of model predictions and act as a forum for the exchange of ideas, experience and information. (author)

BIOMOVS: An international model validation study

International Nuclear Information System (INIS)

Haegg, C.; Johansson, G.

1987-01-01

BIOMOVS (BIOspheric MOdel Validation Study) is an international study where models used for describing the distribution of radioactive and nonradioactive trace substances in terrestrial and aquatic environments are compared and tested. The main objectives of the study are to compare and test the accuracy of predictions between such models, explain differences in these predictions, recommend priorities for future research concerning the improvement of the accuracy of model predictions and act as a forum for the exchange of ideas, experience and information. (orig.)

Variable selection for mixture and promotion time cure rate models.

Science.gov (United States)

Masud, Abdullah; Tu, Wanzhu; Yu, Zhangsheng

2016-11-16

Failure-time data with cured patients are common in clinical studies. Data from these studies are typically analyzed with cure rate models. Variable selection methods have not been well developed for cure rate models. In this research, we propose two least absolute shrinkage and selection operators based methods, for variable selection in mixture and promotion time cure models with parametric or nonparametric baseline hazards. We conduct an extensive simulation study to assess the operating characteristics of the proposed methods. We illustrate the use of the methods using data from a study of childhood wheezing. © The Author(s) 2016.

Application of soft computing based hybrid models in hydrological variables modeling: a comprehensive review

Science.gov (United States)

Fahimi, Farzad; Yaseen, Zaher Mundher; El-shafie, Ahmed

2017-05-01

Since the middle of the twentieth century, artificial intelligence (AI) models have been used widely in engineering and science problems. Water resource variable modeling and prediction are the most challenging issues in water engineering. Artificial neural network (ANN) is a common approach used to tackle this problem by using viable and efficient models. Numerous ANN models have been successfully developed to achieve more accurate results. In the current review, different ANN models in water resource applications and hydrological variable predictions are reviewed and outlined. In addition, recent hybrid models and their structures, input preprocessing, and optimization techniques are discussed and the results are compared with similar previous studies. Moreover, to achieve a comprehensive view of the literature, many articles that applied ANN models together with other techniques are included. Consequently, coupling procedure, model evaluation, and performance comparison of hybrid models with conventional ANN models are assessed, as well as, taxonomy and hybrid ANN models structures. Finally, current challenges and recommendations for future researches are indicated and new hybrid approaches are proposed.

Model Predictive Control of a Nonlinear System with Known Scheduling Variable

DEFF Research Database (Denmark)

Mirzaei, Mahmood; Poulsen, Niels Kjølstad; Niemann, Hans Henrik

2012-01-01

Model predictive control (MPC) of a class of nonlinear systems is considered in this paper. We will use Linear Parameter Varying (LPV) model of the nonlinear system. By taking the advantage of having future values of the scheduling variable, we will simplify state prediction. Consequently...... the control problem of the nonlinear system is simplied into a quadratic programming. Wind turbine is chosen as the case study and we choose wind speed as the scheduling variable. Wind speed is measurable ahead of the turbine, therefore the scheduling variable is known for the entire prediction horizon....

Self-organized Criticality Model for Ocean Internal Waves

International Nuclear Information System (INIS)

Wang Gang; Hou Yijun; Lin Min; Qiao Fangli

2009-01-01

In this paper, we present a simple spring-block model for ocean internal waves based on the self-organized criticality (SOC). The oscillations of the water blocks in the model display power-law behavior with an exponent of -2 in the frequency domain, which is similar to the current and sea water temperature spectra in the actual ocean and the universal Garrett and Munk deep ocean internal wave model [Geophysical Fluid Dynamics 2 (1972) 225; J. Geophys. Res. 80 (1975) 291]. The influence of the ratio of the driving force to the spring coefficient to SOC behaviors in the model is also discussed. (general)

Examples of EOS Variables as compared to the UMM-Var Data Model

Science.gov (United States)

Cantrell, Simon; Lynnes, Chris

2016-01-01

In effort to provide EOSDIS clients a way to discover and use variable data from different providers, a Unified Metadata Model for Variables is being created. This presentation gives an overview of the model and use cases we are handling.

Predicting Teacher Retention Using Stress and Support Variables

Science.gov (United States)

Sass, Daniel A.; Seal, Andrea K.; Martin, Nancy K.

2011-01-01

Purpose: Teacher attrition is a significant international concern facing administrators. Although a considerable amount of literature exists related to the causes of job dissatisfaction and teachers leaving the profession, relatively few theoretical models test the complex interrelationships between these variables. The goal of this paper is to…

Testing and analysis of internal hardwood log defect prediction models

Science.gov (United States)

R. Edward Thomas

2011-01-01

The severity and location of internal defects determine the quality and value of lumber sawn from hardwood logs. Models have been developed to predict the size and position of internal defects based on external defect indicator measurements. These models were shown to predict approximately 80% of all internal knots based on external knot indicators. However, the size...

Speech-discrimination scores modeled as a binomial variable.

Science.gov (United States)

Thornton, A R; Raffin, M J

1978-09-01

Many studies have reported variability data for tests of speech discrimination, and the disparate results of these studies have not been given a simple explanation. Arguments over the relative merits of 25- vs 50-word tests have ignored the basic mathematical properties inherent in the use of percentage scores. The present study models performance on clinical tests of speech discrimination as a binomial variable. A binomial model was developed, and some of its characteristics were tested against data from 4120 scores obtained on the CID Auditory Test W-22. A table for determining significant deviations between scores was generated and compared to observed differences in half-list scores for the W-22 tests. Good agreement was found between predicted and observed values. Implications of the binomial characteristics of speech-discrimination scores are discussed.

Optimal variable-grid finite-difference modeling for porous media

International Nuclear Information System (INIS)

Liu, Xinxin; Yin, Xingyao; Li, Haishan

2014-01-01

Numerical modeling of poroelastic waves by the finite-difference (FD) method is more expensive than that of acoustic or elastic waves. To improve the accuracy and computational efficiency of seismic modeling, variable-grid FD methods have been developed. In this paper, we derived optimal staggered-grid finite difference schemes with variable grid-spacing and time-step for seismic modeling in porous media. FD operators with small grid-spacing and time-step are adopted for low-velocity or small-scale geological bodies, while FD operators with big grid-spacing and time-step are adopted for high-velocity or large-scale regions. The dispersion relations of FD schemes were derived based on the plane wave theory, then the FD coefficients were obtained using the Taylor expansion. Dispersion analysis and modeling results demonstrated that the proposed method has higher accuracy with lower computational cost for poroelastic wave simulation in heterogeneous reservoirs. (paper)

Comparison of climate envelope models developed using expert-selected variables versus statistical selection

Science.gov (United States)

Brandt, Laura A.; Benscoter, Allison; Harvey, Rebecca G.; Speroterra, Carolina; Bucklin, David N.; Romañach, Stephanie; Watling, James I.; Mazzotti, Frank J.

2017-01-01

Climate envelope models are widely used to describe potential future distribution of species under different climate change scenarios. It is broadly recognized that there are both strengths and limitations to using climate envelope models and that outcomes are sensitive to initial assumptions, inputs, and modeling methods Selection of predictor variables, a central step in modeling, is one of the areas where different techniques can yield varying results. Selection of climate variables to use as predictors is often done using statistical approaches that develop correlations between occurrences and climate data. These approaches have received criticism in that they rely on the statistical properties of the data rather than directly incorporating biological information about species responses to temperature and precipitation. We evaluated and compared models and prediction maps for 15 threatened or endangered species in Florida based on two variable selection techniques: expert opinion and a statistical method. We compared model performance between these two approaches for contemporary predictions, and the spatial correlation, spatial overlap and area predicted for contemporary and future climate predictions. In general, experts identified more variables as being important than the statistical method and there was low overlap in the variable sets (0.9 for area under the curve (AUC) and >0.7 for true skill statistic (TSS). Spatial overlap, which compares the spatial configuration between maps constructed using the different variable selection techniques, was only moderate overall (about 60%), with a great deal of variability across species. Difference in spatial overlap was even greater under future climate projections, indicating additional divergence of model outputs from different variable selection techniques. Our work is in agreement with other studies which have found that for broad-scale species distribution modeling, using statistical methods of variable

Parameter estimation of variable-parameter nonlinear Muskingum model using excel solver

Science.gov (United States)

Kang, Ling; Zhou, Liwei

2018-02-01

Abstract . The Muskingum model is an effective flood routing technology in hydrology and water resources Engineering. With the development of optimization technology, more and more variable-parameter Muskingum models were presented to improve effectiveness of the Muskingum model in recent decades. A variable-parameter nonlinear Muskingum model (NVPNLMM) was proposed in this paper. According to the results of two real and frequently-used case studies by various models, the NVPNLMM could obtain better values of evaluation criteria, which are used to describe the superiority of the estimated outflows and compare the accuracies of flood routing using various models, and the optimal estimated outflows by the NVPNLMM were closer to the observed outflows than the ones by other models.

BehavePlus fire modeling system, version 5.0: Variables

Science.gov (United States)

Patricia L. Andrews

2009-01-01

This publication has been revised to reflect updates to version 4.0 of the BehavePlus software. It was originally published as the BehavePlus fire modeling system, version 4.0: Variables in July, 2008.The BehavePlus fire modeling system is a computer program based on mathematical models that describe wildland fire behavior and effects and the...

Internal cycle modeling and environmental assessment of multiple cycle consumer products

International Nuclear Information System (INIS)

Tsiliyannis, C.A.

2012-01-01

Highlights: ► Dynamic flow models are presented for remanufactured, reused or recycled products. ► Early loss and stochastic return are included for fast and slow cycling products. ► The reuse-to-input flow ratio (Internal Cycle Factor, ICF) is determined. ► The cycle rate, which is increasing with the ICF, monitors eco-performance. ► Early internal cycle losses diminish the ICF, the cycle rate and performance. - Abstract: Dynamic annual flow models incorporating consumer discard and usage loss and featuring deterministic and stochastic end-of-cycle (EOC) return by the consumer are developed for reused or remanufactured products (multiple cycle products, MCPs), including fast and slow cycling, short and long-lived products. It is shown that internal flows (reuse and overall consumption) increase proportionally to the dimensionless internal cycle factor (ICF) which is related to environmental impact reduction factors. The combined reuse/recycle (or cycle) rate is shown capable for shortcut, albeit effective, monitoring of environmental performance in terms of waste production, virgin material extraction and manufacturing impacts of all MCPs, a task, which physical variables (lifetime, cycling frequency, mean or total number of return trips) and conventional rates, via which environmental policy has been officially implemented (e.g. recycling rate) cannot accomplish. The cycle rate is shown to be an increasing (hyperbolic) function of ICF. The impact of the stochastic EOC return characteristics on total reuse and consumption flows, as well as on eco-performance, is assessed: symmetric EOC return has a small, positive effect on performance compared to deterministic, while early shifted EOC return is more beneficial. In order to be efficient, environmental policy should set higher minimum reuse targets for higher trippage MCPs. The results may serve for monitoring, flow accounting and comparative eco-assessment of MCPs. They may be useful in identifying

Partitioning the impacts of spatial and climatological rainfall variability in urban drainage modeling

Science.gov (United States)

Peleg, Nadav; Blumensaat, Frank; Molnar, Peter; Fatichi, Simone; Burlando, Paolo

2017-03-01

The performance of urban drainage systems is typically examined using hydrological and hydrodynamic models where rainfall input is uniformly distributed, i.e., derived from a single or very few rain gauges. When models are fed with a single uniformly distributed rainfall realization, the response of the urban drainage system to the rainfall variability remains unexplored. The goal of this study was to understand how climate variability and spatial rainfall variability, jointly or individually considered, affect the response of a calibrated hydrodynamic urban drainage model. A stochastic spatially distributed rainfall generator (STREAP - Space-Time Realizations of Areal Precipitation) was used to simulate many realizations of rainfall for a 30-year period, accounting for both climate variability and spatial rainfall variability. The generated rainfall ensemble was used as input into a calibrated hydrodynamic model (EPA SWMM - the US EPA's Storm Water Management Model) to simulate surface runoff and channel flow in a small urban catchment in the city of Lucerne, Switzerland. The variability of peak flows in response to rainfall of different return periods was evaluated at three different locations in the urban drainage network and partitioned among its sources. The main contribution to the total flow variability was found to originate from the natural climate variability (on average over 74 %). In addition, the relative contribution of the spatial rainfall variability to the total flow variability was found to increase with longer return periods. This suggests that while the use of spatially distributed rainfall data can supply valuable information for sewer network design (typically based on rainfall with return periods from 5 to 15 years), there is a more pronounced relevance when conducting flood risk assessments for larger return periods. The results show the importance of using multiple distributed rainfall realizations in urban hydrology studies to capture the

INTERNAL REGULATIONS OF INTERNATIONAL COMPANIES OPERATING IN POLAND AND TRADITIONAL FAMILY MODEL

Directory of Open Access Journals (Sweden)

Chojara-Sobiecka Małgorzata

2017-12-01

Full Text Available Most of the big companies have the internal regulations about human resources management. The bylaws in question are usually created in the reality of a particular legal system. When a company expands abroad, it starts operating in a different legal system than its own. As a result, the bylaws are not always compatible neither with laws nor the legal culture of the state of a new market. The paper touches upon the problem of the cohesion of internal regulations of some of the international companies operating in Poland with the traditional family model established in Polish law analyzing three areas such as: supporting parenting, family business, and preference for non-heterosexual persons. The conclusions are that some of the internal regulations are not coherent with Polish law, and some of the bylaws regarding, e.g., daycare or flexible working hours, can be adapted to Polish legal system. It (unclear what “it” is referring to would benefit traditional model of the family. The paper contains also the excursus about some legis-lative phenomenon regarding the reception of state law regulations issues by private companies and pos-tulates that the Polish legislator shall be open to new ideas in this matter and search for the well-tried regulations.

Modeling Turbulent Combustion for Variable Prandtl and Schmidt Number

Science.gov (United States)

Hassan, H. A.

2004-01-01

This report consists of two abstracts submitted for possible presentation at the AIAA Aerospace Science Meeting to be held in January 2005. Since the submittal of these abstracts we are continuing refinement of the model coefficients derived for the case of a variable Turbulent Prandtl number. The test cases being investigated are a Mach 9.2 flow over a degree ramp and a Mach 8.2 3-D calculation of crossing shocks. We have developed an axisymmetric code for treating axisymmetric flows. In addition the variable Schmidt number formulation was incorporated in the code and we are in the process of determining the model constants.

Impacts of correcting the inter-variable correlation of climate model outputs on hydrological modeling

Science.gov (United States)

Chen, Jie; Li, Chao; Brissette, François P.; Chen, Hua; Wang, Mingna; Essou, Gilles R. C.

2018-05-01

Bias correction is usually implemented prior to using climate model outputs for impact studies. However, bias correction methods that are commonly used treat climate variables independently and often ignore inter-variable dependencies. The effects of ignoring such dependencies on impact studies need to be investigated. This study aims to assess the impacts of correcting the inter-variable correlation of climate model outputs on hydrological modeling. To this end, a joint bias correction (JBC) method which corrects the joint distribution of two variables as a whole is compared with an independent bias correction (IBC) method; this is considered in terms of correcting simulations of precipitation and temperature from 26 climate models for hydrological modeling over 12 watersheds located in various climate regimes. The results show that the simulated precipitation and temperature are considerably biased not only in the individual distributions, but also in their correlations, which in turn result in biased hydrological simulations. In addition to reducing the biases of the individual characteristics of precipitation and temperature, the JBC method can also reduce the bias in precipitation-temperature (P-T) correlations. In terms of hydrological modeling, the JBC method performs significantly better than the IBC method for 11 out of the 12 watersheds over the calibration period. For the validation period, the advantages of the JBC method are greatly reduced as the performance becomes dependent on the watershed, GCM and hydrological metric considered. For arid/tropical and snowfall-rainfall-mixed watersheds, JBC performs better than IBC. For snowfall- or rainfall-dominated watersheds, however, the two methods behave similarly, with IBC performing somewhat better than JBC. Overall, the results emphasize the advantages of correcting the P-T correlation when using climate model-simulated precipitation and temperature to assess the impact of climate change on watershed

A Time-Series Water Level Forecasting Model Based on Imputation and Variable Selection Method.

Science.gov (United States)

Yang, Jun-He; Cheng, Ching-Hsue; Chan, Chia-Pan

2017-01-01

Reservoirs are important for households and impact the national economy. This paper proposed a time-series forecasting model based on estimating a missing value followed by variable selection to forecast the reservoir's water level. This study collected data from the Taiwan Shimen Reservoir as well as daily atmospheric data from 2008 to 2015. The two datasets are concatenated into an integrated dataset based on ordering of the data as a research dataset. The proposed time-series forecasting model summarily has three foci. First, this study uses five imputation methods to directly delete the missing value. Second, we identified the key variable via factor analysis and then deleted the unimportant variables sequentially via the variable selection method. Finally, the proposed model uses a Random Forest to build the forecasting model of the reservoir's water level. This was done to compare with the listing method under the forecasting error. These experimental results indicate that the Random Forest forecasting model when applied to variable selection with full variables has better forecasting performance than the listing model. In addition, this experiment shows that the proposed variable selection can help determine five forecast methods used here to improve the forecasting capability.

A Model for Positively Correlated Count Variables

DEFF Research Database (Denmark)

Møller, Jesper; Rubak, Ege Holger

2010-01-01

An α-permanental random field is briefly speaking a model for a collection of non-negative integer valued random variables with positive associations. Though such models possess many appealing probabilistic properties, many statisticians seem unaware of α-permanental random fields...... and their potential applications. The purpose of this paper is to summarize useful probabilistic results, study stochastic constructions and simulation techniques, and discuss some examples of α-permanental random fields. This should provide a useful basis for discussing the statistical aspects in future work....

Interacting ghost dark energy models with variable G and Λ

Science.gov (United States)

Sadeghi, J.; Khurshudyan, M.; Movsisyan, A.; Farahani, H.

2013-12-01

In this paper we consider several phenomenological models of variable Λ. Model of a flat Universe with variable Λ and G is accepted. It is well known, that varying G and Λ gives rise to modified field equations and modified conservation laws, which gives rise to many different manipulations and assumptions in literature. We will consider two component fluid, which parameters will enter to Λ. Interaction between fluids with energy densities ρ1 and ρ2 assumed as Q = 3Hb(ρ1+ρ2). We have numerical analyze of important cosmological parameters like EoS parameter of the composed fluid and deceleration parameter q of the model.

Single cell adhesion strength assessed with variable-angle total internal reflection fluorescence microscopy

Directory of Open Access Journals (Sweden)

Marcelina Cardoso Dos Santos

2017-06-01

Full Text Available We propose a new strategy to evaluate adhesion strength at the single cell level. This approach involves variable-angle total internal reflection fluorescence microscopy to monitor in real time the topography of cell membranes, i.e. a map of the membrane/substrate separation distance. According to the Boltzmann distribution, both potential energy profile and dissociation energy related to the interactions between the cell membrane and the substrate were determined from the membrane topography. We have highlighted on glass substrates coated with poly-L-lysine and fibronectin, that the dissociation energy is a reliable parameter to quantify the adhesion strength of MDA-MB-231 motile cells.

Representing general theoretical concepts in structural equation models: The role of composite variables

Science.gov (United States)

Grace, J.B.; Bollen, K.A.

2008-01-01

Structural equation modeling (SEM) holds the promise of providing natural scientists the capacity to evaluate complex multivariate hypotheses about ecological systems. Building on its predecessors, path analysis and factor analysis, SEM allows for the incorporation of both observed and unobserved (latent) variables into theoretically-based probabilistic models. In this paper we discuss the interface between theory and data in SEM and the use of an additional variable type, the composite. In simple terms, composite variables specify the influences of collections of other variables and can be helpful in modeling heterogeneous concepts of the sort commonly of interest to ecologists. While long recognized as a potentially important element of SEM, composite variables have received very limited use, in part because of a lack of theoretical consideration, but also because of difficulties that arise in parameter estimation when using conventional solution procedures. In this paper we present a framework for discussing composites and demonstrate how the use of partially-reduced-form models can help to overcome some of the parameter estimation and evaluation problems associated with models containing composites. Diagnostic procedures for evaluating the most appropriate and effective use of composites are illustrated with an example from the ecological literature. It is argued that an ability to incorporate composite variables into structural equation models may be particularly valuable in the study of natural systems, where concepts are frequently multifaceted and the influence of suites of variables are often of interest. ?? Springer Science+Business Media, LLC 2007.

Inter-model variability and biases of the global water cycle in CMIP3 coupled climate models

International Nuclear Information System (INIS)

Liepert, Beate G; Previdi, Michael

2012-01-01

Observed changes such as increasing global temperatures and the intensification of the global water cycle in the 20th century are robust results of coupled general circulation models (CGCMs). In spite of these successes, model-to-model variability and biases that are small in first order climate responses, however, have considerable implications for climate predictability especially when multi-model means are used. We show that most climate simulations of the 20th and 21st century A2 scenario performed with CMIP3 (Coupled Model Inter-comparison Project Phase 3) models have deficiencies in simulating the global atmospheric moisture balance. Large biases of only a few models (some biases reach the simulated global precipitation changes in the 20th and 21st centuries) affect the multi-model mean global moisture budget. An imbalanced flux of −0.14 Sv exists while the multi-model median imbalance is only −0.02 Sv. Moreover, for most models the detected imbalance changes over time. As a consequence, in 13 of the 18 CMIP3 models examined, global annual mean precipitation exceeds global evaporation, indicating that there should be a ‘leaking’ of moisture from the atmosphere whereas for the remaining five models a ‘flooding’ is implied. Nonetheless, in all models, the actual atmospheric moisture content and its variability correctly increases during the course of the 20th and 21st centuries. These discrepancies therefore imply an unphysical and hence ‘ghost’ sink/source of atmospheric moisture in the models whose atmospheres flood/leak. The ghost source/sink of moisture can also be regarded as atmospheric latent heating/cooling and hence as positive/negative perturbation of the atmospheric energy budget or non-radiative forcing in the range of −1 to +6 W m −2 (median +0.1 W m −2 ). The inter-model variability of the global atmospheric moisture transport from oceans to land areas, which impacts the terrestrial water cycle, is also quite high and ranges

How ocean lateral mixing changes Southern Ocean variability in coupled climate models

Science.gov (United States)

Pradal, M. A. S.; Gnanadesikan, A.; Thomas, J. L.

2016-02-01

The lateral mixing of tracers represents a major uncertainty in the formulation of coupled climate models. The mixing of tracers along density surfaces in the interior and horizontally within the mixed layer is often parameterized using a mixing coefficient ARedi. The models used in the Coupled Model Intercomparison Project 5 exhibit more than an order of magnitude range in the values of this coefficient used within the Southern Ocean. The impacts of such uncertainty on Southern Ocean variability have remained unclear, even as recent work has shown that this variability differs between different models. In this poster, we change the lateral mixing coefficient within GFDL ESM2Mc, a coarse-resolution Earth System model that nonetheless has a reasonable circulation within the Southern Ocean. As the coefficient varies from 400 to 2400 m2/s the amplitude of the variability varies significantly. The low-mixing case shows strong decadal variability with an annual mean RMS temperature variability exceeding 1C in the Circumpolar Current. The highest-mixing case shows a very similar spatial pattern of variability, but with amplitudes only about 60% as large. The suppression of mixing is larger in the Atlantic Sector of the Southern Ocean relatively to the Pacific sector. We examine the salinity budgets of convective regions, paying particular attention to the extent to which high mixing prevents the buildup of low-saline waters that are capable of shutting off deep convection entirely.

Investigation of a rotary valving system with variable valve timing for internal combustion engines

Science.gov (United States)

Cross, Paul C.; Hansen, Craig N.

1994-11-01

The objective of the program was to provide a functional demonstration of the Hansen Rotary Valving System with Variable Valve Timing (HRVS/VVT), capable of throttleless inlet charge control, as an alternative to conventional poppet-valves for use in spark ignited internal combustion engines. The goal of this new technology is to secure benefits in fuel economy, broadened torque band, vibration reduction, and overhaul accessibility. Additionally, use of the variable valve timing capability to vary the effective compression ratio is expected to improve multifuel tolerance and efficiency. Efforts directed at the design of HRVS components proved to be far more extensive than had been anticipated, ultimately requiring that proof-trial design/development work be performed. Although both time and funds were exhausted before optical or ion-probe types of in-cylinder investigation could be undertaken, a great deal of laboratory data was acquired during the course of the design/development work. This laboratory data is the basis for the information presented in this final report.

A Composite Likelihood Inference in Latent Variable Models for Ordinal Longitudinal Responses

Science.gov (United States)

Vasdekis, Vassilis G. S.; Cagnone, Silvia; Moustaki, Irini

2012-01-01

The paper proposes a composite likelihood estimation approach that uses bivariate instead of multivariate marginal probabilities for ordinal longitudinal responses using a latent variable model. The model considers time-dependent latent variables and item-specific random effects to be accountable for the interdependencies of the multivariate…

Modeling the internal combustion engine

Science.gov (United States)

Zeleznik, F. J.; Mcbride, B. J.

1985-01-01

A flexible and computationally economical model of the internal combustion engine was developed for use on large digital computer systems. It is based on a system of ordinary differential equations for cylinder-averaged properties. The computer program is capable of multicycle calculations, with some parameters varying from cycle to cycle, and has restart capabilities. It can accommodate a broad spectrum of reactants, permits changes in physical properties, and offers a wide selection of alternative modeling functions without any reprogramming. It readily adapts to the amount of information available in a particular case because the model is in fact a hierarchy of five models. The models range from a simple model requiring only thermodynamic properties to a complex model demanding full combustion kinetics, transport properties, and poppet valve flow characteristics. Among its many features the model includes heat transfer, valve timing, supercharging, motoring, finite burning rates, cycle-to-cycle variations in air-fuel ratio, humid air, residual and recirculated exhaust gas, and full combustion kinetics.

A review of a method for dynamic load distribution, dynamic modeling, and explicit internal force control when two serial link manipulators mutually lift and transport a rigid body object

International Nuclear Information System (INIS)

Unseren, M.A.

1997-09-01

The report reviews a method for modeling and controlling two serial link manipulators which mutually lift and transport a rigid body object in a three dimensional workspace. A new vector variable is introduced which parameterizes the internal contact force controlled degrees of freedom. A technique for dynamically distributing the payload between the manipulators is suggested which yields a family of solutions for the contact forces and torques the manipulators impart to the object. A set of rigid body kinematic constraints which restricts the values of the joint velocities of both manipulators is derived. A rigid body dynamical model for the closed chain system is first developed in the joint space. The model is obtained by generalizing the previous methods for deriving the model. The joint velocity and acceleration variables in the model are expressed in terms of independent pseudovariables. The pseudospace model is transformed to obtain reduced order equations of motion and a separate set of equations governing the internal components of the contact forces and torques. A theoretic control architecture is suggested which explicitly decouples the two sets of equations comprising the model. The controller enables the designer to develop independent, non-interacting control laws for the position control and internal force control of the system

A review of a method for dynamic load distribution, dynamic modeling, and explicit internal force control when two serial link manipulators mutually lift and transport a rigid body object

Energy Technology Data Exchange (ETDEWEB)

Unseren, M.A.

1997-09-01

The report reviews a method for modeling and controlling two serial link manipulators which mutually lift and transport a rigid body object in a three dimensional workspace. A new vector variable is introduced which parameterizes the internal contact force controlled degrees of freedom. A technique for dynamically distributing the payload between the manipulators is suggested which yields a family of solutions for the contact forces and torques the manipulators impart to the object. A set of rigid body kinematic constraints which restricts the values of the joint velocities of both manipulators is derived. A rigid body dynamical model for the closed chain system is first developed in the joint space. The model is obtained by generalizing the previous methods for deriving the model. The joint velocity and acceleration variables in the model are expressed in terms of independent pseudovariables. The pseudospace model is transformed to obtain reduced order equations of motion and a separate set of equations governing the internal components of the contact forces and torques. A theoretic control architecture is suggested which explicitly decouples the two sets of equations comprising the model. The controller enables the designer to develop independent, non-interacting control laws for the position control and internal force control of the system.

Input variable selection for data-driven models of Coriolis flowmeters for two-phase flow measurement

International Nuclear Information System (INIS)

Wang, Lijuan; Yan, Yong; Wang, Xue; Wang, Tao

2017-01-01

Input variable selection is an essential step in the development of data-driven models for environmental, biological and industrial applications. Through input variable selection to eliminate the irrelevant or redundant variables, a suitable subset of variables is identified as the input of a model. Meanwhile, through input variable selection the complexity of the model structure is simplified and the computational efficiency is improved. This paper describes the procedures of the input variable selection for the data-driven models for the measurement of liquid mass flowrate and gas volume fraction under two-phase flow conditions using Coriolis flowmeters. Three advanced input variable selection methods, including partial mutual information (PMI), genetic algorithm-artificial neural network (GA-ANN) and tree-based iterative input selection (IIS) are applied in this study. Typical data-driven models incorporating support vector machine (SVM) are established individually based on the input candidates resulting from the selection methods. The validity of the selection outcomes is assessed through an output performance comparison of the SVM based data-driven models and sensitivity analysis. The validation and analysis results suggest that the input variables selected from the PMI algorithm provide more effective information for the models to measure liquid mass flowrate while the IIS algorithm provides a fewer but more effective variables for the models to predict gas volume fraction. (paper)

A Model of Internal Communication in Adaptive Communication Systems.

Science.gov (United States)

Williams, M. Lee

A study identified and categorized different types of internal communication systems and developed an applied model of internal communication in adaptive organizational systems. Twenty-one large organizations were selected for their varied missions and diverse approaches to managing internal communication. Individual face-to-face or telephone…

The test of variables of attention (TOVA): Internal consistency (Q1 vs. Q2 and Q3 vs. Q4) in children with Attention Deficit/Hyperactivity Disorder (ADHD)

Science.gov (United States)

The internal consistency of the Test of Variables of Attention (TOVA) was examined in a cohort of 6- to 12-year-old children (N = 63) strictly diagnosed with ADHD. The internal consistency of errors of omission (OMM), errors of commission (COM), response time (RT), and response time variability (RTV...

Thermomechanical and calorimetric behaviours of supported glass-forming films: A study based on thermodynamics with internal variables

Energy Technology Data Exchange (ETDEWEB)

Lion, Alexander, E-mail: alexander.lion@unibw.de; Engelhard, Marco; Johlitz, Michael

2012-11-01

In order to understand the temperature-dependent response behaviour of thin thermoviscoelastic films which are deposited on relative stiff but thermally deformable substrates it is important to consider the lateral geometric constraints. They are generated by differences in the thermal expansion properties between the substrate and the film and provoke internal stresses. Since glass-forming materials exhibit distinct temperature history-dependent thermal expansion and calorimetric properties, primarily in the vicinity of the glass transition, the situation is rather complicated. In this article, a recently developed three-dimensional model of thermodynamics with internal variables is applied and adapted to simulate this type of behaviour. Explicit relations are obtained for the specific heat of the film, the normal strain and the lateral stresses. Numerical simulations demonstrate that the magnitude of the internal stress at temperatures below the glass transition depends strongly on the cooling rate. It is also shown that the specific heat of the supported film is principally different from the isobaric specific heat of the bulk material: the glassy limit of the specific heat of the film is reduced but the glass transition temperature is almost uninfluenced. The simulated behaviour is in accordance with experimental observations from literature. - Highlights: Black-Right-Pointing-Pointer For the specific heat, stress and strain of the film, explicit equations were derived. Black-Right-Pointing-Pointer The constraints of the substrate reduce the glassy limit of specific heat of the film. Black-Right-Pointing-Pointer Glass transition temperatures of free bulk material and supported film are equal. Black-Right-Pointing-Pointer Simulations are in good agreement with experimental observations from literature.

Ensembling Variable Selectors by Stability Selection for the Cox Model

Directory of Open Access Journals (Sweden)

Qing-Yan Yin

2017-01-01

Full Text Available As a pivotal tool to build interpretive models, variable selection plays an increasingly important role in high-dimensional data analysis. In recent years, variable selection ensembles (VSEs have gained much interest due to their many advantages. Stability selection (Meinshausen and Bühlmann, 2010, a VSE technique based on subsampling in combination with a base algorithm like lasso, is an effective method to control false discovery rate (FDR and to improve selection accuracy in linear regression models. By adopting lasso as a base learner, we attempt to extend stability selection to handle variable selection problems in a Cox model. According to our experience, it is crucial to set the regularization region Λ in lasso and the parameter λmin properly so that stability selection can work well. To the best of our knowledge, however, there is no literature addressing this problem in an explicit way. Therefore, we first provide a detailed procedure to specify Λ and λmin. Then, some simulated and real-world data with various censoring rates are used to examine how well stability selection performs. It is also compared with several other variable selection approaches. Experimental results demonstrate that it achieves better or competitive performance in comparison with several other popular techniques.

International Business Models Developed Through Brokerage Knowledge and Value Creation

DEFF Research Database (Denmark)

Petersen, Nicolaj Hannesbo; Rasmussen, Erik Stavnsager

This paper highlights theoretically and empirically international business model decisions in networks with knowledge sharing and value creation. The paper expands the conceptual in-ternational business model framework for technology-oriented companies to include the focal firm’s network role...... and strategic fit in a global embeddedness. The brokerage role in the in-ternationalization of a network is discussed from both a theoretical and empirical point of view. From a business model and social network analysis perspective, this paper will show how firms and network grow internationally through two...

Multiscale thermohydrologic model: addressing variability and uncertainty at Yucca Mountain

International Nuclear Information System (INIS)

Buscheck, T; Rosenberg, N D; Gansemer, J D; Sun, Y

2000-01-01

Performance assessment and design evaluation require a modeling tool that simultaneously accounts for processes occurring at a scale of a few tens of centimeters around individual waste packages and emplacement drifts, and also on behavior at the scale of the mountain. Many processes and features must be considered, including non-isothermal, multiphase-flow in rock of variable saturation and thermal radiation in open cavities. Also, given the nature of the fractured rock at Yucca Mountain, a dual-permeability approach is needed to represent permeability. A monolithic numerical model with all these features requires too large a computational cost to be an effective simulation tool, one that is used to examine sensitivity to key model assumptions and parameters. We have developed a multi-scale modeling approach that effectively simulates 3D discrete-heat-source, mountain-scale thermohydrologic behavior at Yucca Mountain and captures the natural variability of the site consistent with what we know from site characterization and waste-package-to-waste-package variability in heat output. We describe this approach and present results examining the role of infiltration flux, the most important natural-system parameter with respect to how thermohydrologic behavior influences the performance of the repository

An Analysis of Basic Construction Variables of Racing Wheelchairs Used in the 1984 International Games for the Disabled.

Science.gov (United States)

York, Sherril L.; Kimura, Iris F.

1987-01-01

A photographic analysis of racing wheelchairs used by cerebral palsy class four athletes and amputee athletes at the 1984 International Games for the Disabled was undertaken in order to analyze seven wheelchair construction variables in relation to performance outcome, distance raced, and type of disability of the user. (Author/MT)

A Time-Series Water Level Forecasting Model Based on Imputation and Variable Selection Method

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Jun-He Yang

2017-01-01

Full Text Available Reservoirs are important for households and impact the national economy. This paper proposed a time-series forecasting model based on estimating a missing value followed by variable selection to forecast the reservoir’s water level. This study collected data from the Taiwan Shimen Reservoir as well as daily atmospheric data from 2008 to 2015. The two datasets are concatenated into an integrated dataset based on ordering of the data as a research dataset. The proposed time-series forecasting model summarily has three foci. First, this study uses five imputation methods to directly delete the missing value. Second, we identified the key variable via factor analysis and then deleted the unimportant variables sequentially via the variable selection method. Finally, the proposed model uses a Random Forest to build the forecasting model of the reservoir’s water level. This was done to compare with the listing method under the forecasting error. These experimental results indicate that the Random Forest forecasting model when applied to variable selection with full variables has better forecasting performance than the listing model. In addition, this experiment shows that the proposed variable selection can help determine five forecast methods used here to improve the forecasting capability.

Winter variability in the western Gulf of Maine: Part 1: Internal tides

Science.gov (United States)

Brown, W. S.

2011-09-01

During the winter 1997-1998, a field program was conducted in Wilkinson Basin-western Gulf of Maine-as part of a study of winter convective mixing. The field program consisted of (1) Wilkinson basin-scale hydrographic surveys, (2) a tight three-mooring array with ˜100 m separations measured temperature and conductivity at rates of 2-15 min and (3) a single pair of upward/downward-looking pair acoustic Doppler current profiling (ADCP) instruments measured currents with 8 m vertical resolution over the 270 m water column in north-central Wilkinson basin at a rate of 10 min. The moored array measurements below the mixed layer (˜100 m depth) between 11 January and 6 February 1998 were dominated by a combination of the relatively strong semidiurnal external (depth-independent or barotropic) tide; upon which were superposed a weaker phase-locked semidiurnal internal tide and a very weak water column mean currents of about 1 cm/s southward or approximately across the local isobaths. The harmonic analysis of a vertical average of the relatively uniform ADCP velocities in the well-mixed upper 123 m of the water column, defined the external tidal currents which were dominated by a nearly rectilinear, across-isobath (326°T) M 2 semidiurnal tidal current of about 15 cm/s. The depth-dependent residual current field, which was created by subtracting the external tidal current, consisted of (1) clockwise-rotating semidiurnal internal tidal currents of about 5 cm/s below the mixed layer; (2) clockwise-rotating inertial currents; and (3) a considerably less energetic subtidal current variability. The results from both frequency-domain empirical orthogonal function and tidal harmonic analyses of the of isotherm displacement series at each of the three moorings in the 100 m array mutually confirm an approximate east-northeastward phase propagation of the dominant M 2 semidiurnal internal tide across Wilkinson Basin. Further investigation supports the idea that this winter internal

Adaptation of endothelial cells to physiologically-modeled, variable shear stress.

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Joseph S Uzarski

Full Text Available Endothelial cell (EC function is mediated by variable hemodynamic shear stress patterns at the vascular wall, where complex shear stress profiles directly correlate with blood flow conditions that vary temporally based on metabolic demand. The interactions of these more complex and variable shear fields with EC have not been represented in hemodynamic flow models. We hypothesized that EC exposed to pulsatile shear stress that changes in magnitude and duration, modeled directly from real-time physiological variations in heart rate, would elicit phenotypic changes as relevant to their critical roles in thrombosis, hemostasis, and inflammation. Here we designed a physiological flow (PF model based on short-term temporal changes in blood flow observed in vivo and compared it to static culture and steady flow (SF at a fixed pulse frequency of 1.3 Hz. Results show significant changes in gene regulation as a function of temporally variable flow, indicating a reduced wound phenotype more representative of quiescence. EC cultured under PF exhibited significantly higher endothelial nitric oxide synthase (eNOS activity (PF: 176.0±11.9 nmol/10(5 EC; SF: 115.0±12.5 nmol/10(5 EC, p = 0.002 and lower TNF-a-induced HL-60 leukocyte adhesion (PF: 37±6 HL-60 cells/mm(2; SF: 111±18 HL-60/mm(2, p = 0.003 than cells cultured under SF which is consistent with a more quiescent anti-inflammatory and anti-thrombotic phenotype. In vitro models have become increasingly adept at mimicking natural physiology and in doing so have clarified the importance of both chemical and physical cues that drive cell function. These data illustrate that the variability in metabolic demand and subsequent changes in perfusion resulting in constantly variable shear stress plays a key role in EC function that has not previously been described.

Oracle Efficient Variable Selection in Random and Fixed Effects Panel Data Models

DEFF Research Database (Denmark)

Kock, Anders Bredahl

This paper generalizes the results for the Bridge estimator of Huang et al. (2008) to linear random and fixed effects panel data models which are allowed to grow in both dimensions. In particular we show that the Bridge estimator is oracle efficient. It can correctly distinguish between relevant...... and irrelevant variables and the asymptotic distribution of the estimators of the coefficients of the relevant variables is the same as if only these had been included in the model, i.e. as if an oracle had revealed the true model prior to estimation. In the case of more explanatory variables than observations......, we prove that the Marginal Bridge estimator can asymptotically correctly distinguish between relevant and irrelevant explanatory variables. We do this without restricting the dependence between covariates and without assuming sub Gaussianity of the error terms thereby generalizing the results...

Variable Renewable Energy in Long-Term Planning Models: A Multi-Model Perspective

Energy Technology Data Exchange (ETDEWEB)

Cole, Wesley J. [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Frew, Bethany A. [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Mai, Trieu T. [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Sun, Yinong [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Bistline, John [Electric Power Research Inst., Palo Alto, CA (United States); Blanford, Geoffrey [Electric Power Research Inst., Palo Alto, CA (United States); Young, David [Electric Power Research Inst., Palo Alto, CA (United States); Marcy, Cara [Energy Information Administration, Washington, DC (United States); Namovicz, Chris [Energy Information Administration, Washington, DC (United States); Edelman, Risa [Environmental Protection Agency, Washington, DC (United States); Meroney, Bill [Environmental Protection Agency; Sims, Ryan [Environmental Protection Agency; Stenhouse, Jeb [Environmental Protection Agency; Donohoo-Vallett, Paul [U.S. Department of Energy

2017-11-03

Long-term capacity expansion models of the U.S. electricity sector have long been used to inform electric sector stakeholders and decision makers. With the recent surge in variable renewable energy (VRE) generators - primarily wind and solar photovoltaics - the need to appropriately represent VRE generators in these long-term models has increased. VRE generators are especially difficult to represent for a variety of reasons, including their variability, uncertainty, and spatial diversity. To assess current best practices, share methods and data, and identify future research needs for VRE representation in capacity expansion models, four capacity expansion modeling teams from the Electric Power Research Institute, the U.S. Energy Information Administration, the U.S. Environmental Protection Agency, and the National Renewable Energy Laboratory conducted two workshops of VRE modeling for national-scale capacity expansion models. The workshops covered a wide range of VRE topics, including transmission and VRE resource data, VRE capacity value, dispatch and operational modeling, distributed generation, and temporal and spatial resolution. The objectives of the workshops were both to better understand these topics and to improve the representation of VRE across the suite of models. Given these goals, each team incorporated model updates and performed additional analyses between the first and second workshops. This report summarizes the analyses and model 'experiments' that were conducted as part of these workshops as well as the various methods for treating VRE among the four modeling teams. The report also reviews the findings and learnings from the two workshops. We emphasize the areas where there is still need for additional research and development on analysis tools to incorporate VRE into long-term planning and decision-making.

Separation of variables in anisotropic models: anisotropic Rabi and elliptic Gaudin model in an external magnetic field

Science.gov (United States)

Skrypnyk, T.

2017-08-01

We study the problem of separation of variables for classical integrable Hamiltonian systems governed by non-skew-symmetric non-dynamical so(3)\\otimes so(3) -valued elliptic r-matrices with spectral parameters. We consider several examples of such models, and perform separation of variables for classical anisotropic one- and two-spin Gaudin-type models in an external magnetic field, and for Jaynes-Cummings-Dicke-type models without the rotating wave approximation.

Modelling the effects of spatial variability on radionuclide migration

International Nuclear Information System (INIS)

1998-01-01

The NEA workshop reflect the present status in national waste management program, specifically in spatial variability and performance assessment of geologic disposal sites for deed repository system the four sessions were: Spatial Variability: Its Definition and Significance to Performance Assessment and Site Characterisation; Experience with the Modelling of Radionuclide Migration in the Presence of Spatial Variability in Various Geological Environments; New Areas for Investigation: Two Personal Views; What is Wanted and What is Feasible: Views and Future Plans in Selected Waste Management Organisations. The 26 papers presented on the four oral sessions and on the poster session have been abstracted and indexed individually for the INIS database. (R.P.)

International Summit on Integrated Environmental Modeling

Science.gov (United States)

This report describes the International Summit on Integrated Environmental Modeling (IEM), held in Washington, DC 7th-9th December 2010. The meeting brought together 57 scientists and managers from leading US and European government and non-governmental organizations, universitie...

EXPLANATORY MODEL OF SPOT PRICE OF IRON ORE

Directory of Open Access Journals (Sweden)

Juan Enrique Villalva A.

2015-11-01

Full Text Available The objective of this study was to construct an explanatory model of the spot price of iron ore in the international market. For this, the method of multiple linear regressions was used. As a dependent variable, the spot price of iron ore (62% Fe China Tianjin port was taken, between 2010 and 2013. As independents variables were taken seven variables of international iron ore market. The resulting model includes variables: Iron ore inventory in Chinese ports, Baltic Dry Index (BDI, Iron ore exports from Brazil & Australia and Chinese Rebar Steel Price, as explanatory variables of the behavior of the spot price of iron ore in the international market. The model has an adjusted coefficient of determination R2 of 0.90, and was validated by comparing its predictions vs. known values of 2014.

AeroPropulsoServoElasticity: Dynamic Modeling of the Variable Cycle Propulsion System

Science.gov (United States)

Kopasakis, George

2012-01-01

This presentation was made at the 2012 Fundamental Aeronautics Program Technical Conference and it covers research work for the Dynamic Modeling of the Variable cycle Propulsion System that was done under the Supersonics Project, in the area of AeroPropulsoServoElasticity. The presentation covers the objective for the propulsion system dynamic modeling work, followed by the work that has been done so far to model the variable Cycle Engine, modeling of the inlet, the nozzle, the modeling that has been done to model the affects of flow distortion, and finally presenting some concluding remarks and future plans.

Ocean carbon and heat variability in an Earth System Model

Science.gov (United States)

Thomas, J. L.; Waugh, D.; Gnanadesikan, A.

2016-12-01

Ocean carbon and heat content are very important for regulating global climate. Furthermore, due to lack of observations and dependence on parameterizations, there has been little consensus in the modeling community on the magnitude of realistic ocean carbon and heat content variability, particularly in the Southern Ocean. We assess the differences between global oceanic heat and carbon content variability in GFDL ESM2Mc using a 500-year, pre-industrial control simulation. The global carbon and heat content are directly out of phase with each other; however, in the Southern Ocean the heat and carbon content are in phase. The global heat mutli-decadal variability is primarily explained by variability in the tropics and mid-latitudes, while the variability in global carbon content is primarily explained by Southern Ocean variability. In order to test the robustness of this relationship, we use three additional pre-industrial control simulations using different mesoscale mixing parameterizations. Three pre-industrial control simulations are conducted with the along-isopycnal diffusion coefficient (Aredi) set to constant values of 400, 800 (control) and 2400 m2 s-1. These values for Aredi are within the range of parameter settings commonly used in modeling groups. Finally, one pre-industrial control simulation is conducted where the minimum in the Gent-McWilliams parameterization closure scheme (AGM) increased to 600 m2 s-1. We find that the different simulations have very different multi-decadal variability, especially in the Weddell Sea where the characteristics of deep convection are drastically changed. While the temporal frequency and amplitude global heat and carbon content changes significantly, the overall spatial pattern of variability remains unchanged between the simulations.

Predictive-property-ranked variable reduction in partial least squares modelling with final complexity adapted models: comparison of properties for ranking.

Science.gov (United States)

Andries, Jan P M; Vander Heyden, Yvan; Buydens, Lutgarde M C

2013-01-14

The calibration performance of partial least squares regression for one response (PLS1) can be improved by eliminating uninformative variables. Many variable-reduction methods are based on so-called predictor-variable properties or predictive properties, which are functions of various PLS-model parameters, and which may change during the steps of the variable-reduction process. Recently, a new predictive-property-ranked variable reduction method with final complexity adapted models, denoted as PPRVR-FCAM or simply FCAM, was introduced. It is a backward variable elimination method applied on the predictive-property-ranked variables. The variable number is first reduced, with constant PLS1 model complexity A, until A variables remain, followed by a further decrease in PLS complexity, allowing the final selection of small numbers of variables. In this study for three data sets the utility and effectiveness of six individual and nine combined predictor-variable properties are investigated, when used in the FCAM method. The individual properties include the absolute value of the PLS1 regression coefficient (REG), the significance of the PLS1 regression coefficient (SIG), the norm of the loading weight (NLW) vector, the variable importance in the projection (VIP), the selectivity ratio (SR), and the squared correlation coefficient of a predictor variable with the response y (COR). The selective and predictive performances of the models resulting from the use of these properties are statistically compared using the one-tailed Wilcoxon signed rank test. The results indicate that the models, resulting from variable reduction with the FCAM method, using individual or combined properties, have similar or better predictive abilities than the full spectrum models. After mean-centring of the data, REG and SIG, provide low numbers of informative variables, with a meaning relevant to the response, and lower than the other individual properties, while the predictive abilities are

Validation of Generic Models for Variable Speed Operation Wind Turbines Following the Recent Guidelines Issued by IEC 61400-27

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Andrés Honrubia-Escribano

2016-12-01

Full Text Available Considerable efforts are currently being made by several international working groups focused on the development of generic, also known as simplified or standard, wind turbine models for power system stability studies. In this sense, the first edition of International Electrotechnical Commission (IEC 61400-27-1, which defines generic dynamic simulation models for wind turbines, was published in February 2015. Nevertheless, the correlations of the IEC generic models with respect to specific wind turbine manufacturer models are required by the wind power industry to validate the accuracy and corresponding usability of these standard models. The present work conducts the validation of the two topologies of variable speed wind turbines that present not only the largest market share, but also the most technological advances. Specifically, the doubly-fed induction machine and the full-scale converter (FSC topology are modeled based on the IEC 61400-27-1 guidelines. The models are simulated for a wide range of voltage dips with different characteristics and wind turbine operating conditions. The simulated response of the IEC generic model is compared to the corresponding simplified model of a wind turbine manufacturer, showing a good correlation in most cases. Validation error sources are analyzed in detail, as well. In addition, this paper reviews in detail the previous work done in this field. Results suggest that wind turbine manufacturers are able to adjust the IEC generic models to represent the behavior of their specific wind turbines for power system stability analysis.

DAMPAK KINERJA INTERNAL DAN KONDISI MAKRO EKONOMI TERHADAP PROFITABILITAS PADA PERBANKAN

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Bayu Widokartiko

2016-05-01

Full Text Available The objectives of this study are 1 to analyze and measure the impacts of internal performance variables of the conventional and Islamic banking toward profitability; 2 to analyze and measure the impacts of macro-economic variables influencing the profitability of conventional and Islamic banking. This research used Granger causality and Vector Auto Regressive (VAR/Vector Error Correction Model (VECM as the data analysis tools. The results of this study confirm that Islamic banking has a more stable profitability in response to macroeconomic conditions as compared to the conventional banking system. The response of the profitability toward the influence of the movement of macroeconomic variables can conclude that the Islamic banking can be stable more quickly in CURRENCY and INFLATION. The influence of the performance variable of the internal banking toward macroeconomic occurs more frequently in conventional banks. CAR internal performance variable is influential on BI Rate, and LDR is influential on currencies. Key words: profitability, Islamic banking, granger causality, VAR, VECM

Effect of climate variables on cocoa black pod incidence in Sabah using ARIMAX model

Science.gov (United States)

Ling Sheng Chang, Albert; Ramba, Haya; Mohd. Jaaffar, Ahmad Kamil; Kim Phin, Chong; Chong Mun, Ho

2016-06-01

Cocoa black pod disease is one of the major diseases affecting the cocoa production in Malaysia and also around the world. Studies have shown that the climate variables have influenced the cocoa black pod disease incidence and it is important to quantify the black pod disease variation due to the effect of climate variables. Application of time series analysis especially auto-regressive moving average (ARIMA) model has been widely used in economics study and can be used to quantify the effect of climate variables on black pod incidence to forecast the right time to control the incidence. However, ARIMA model does not capture some turning points in cocoa black pod incidence. In order to improve forecasting performance, other explanatory variables such as climate variables should be included into ARIMA model as ARIMAX model. Therefore, this paper is to study the effect of climate variables on the cocoa black pod disease incidence using ARIMAX model. The findings of the study showed ARIMAX model using MA(1) and relative humidity at lag 7 days, RHt - 7 gave better R square value compared to ARIMA model using MA(1) which could be used to forecast the black pod incidence to assist the farmers determine timely application of fungicide spraying and culture practices to control the black pod incidence.

Incorporating Latent Variables into Discrete Choice Models - A Simultaneous Estimation Approach Using SEM Software

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Dirk Temme

2008-12-01

Full Text Available Integrated choice and latent variable (ICLV models represent a promising new class of models which merge classic choice models with the structural equation approach (SEM for latent variables. Despite their conceptual appeal, applications of ICLV models in marketing remain rare. We extend previous ICLV applications by first estimating a multinomial choice model and, second, by estimating hierarchical relations between latent variables. An empirical study on travel mode choice clearly demonstrates the value of ICLV models to enhance the understanding of choice processes. In addition to the usually studied directly observable variables such as travel time, we show how abstract motivations such as power and hedonism as well as attitudes such as a desire for flexibility impact on travel mode choice. Furthermore, we show that it is possible to estimate such a complex ICLV model with the widely available structural equation modeling package Mplus. This finding is likely to encourage more widespread application of this appealing model class in the marketing field.

a modified intervention model for gross domestic product variable

African Journals Online (AJOL)

observations on a variable that have been measured at ... assumption that successive values in the data file ... these interventions, one may try to evaluate the effect of ... generalized series by comparing the distinct periods. A ... the process of checking for adequacy of the model based .... As a result, the model's forecast will.

Occupant-vehicle dynamics and the role of the internal model

Science.gov (United States)

Cole, David J.

2018-05-01

With the increasing need to reduce time and cost of vehicle development there is increasing advantage in simulating mathematically the dynamic interaction of a vehicle and its occupant. The larger design space arising from the introduction of automated vehicles further increases the potential advantage. The aim of the paper is to outline the role of the internal model hypothesis in understanding and modelling occupant-vehicle dynamics, specifically the dynamics associated with direction and speed control of the vehicle. The internal model is the driver's or passenger's understanding of the vehicle dynamics and is thought to be employed in the perception, cognition and action processes of the brain. The internal model aids the estimation of the states of the vehicle from noisy sensory measurements. It can also be used to optimise cognitive control action by predicting the consequence of the action; thus model predictive control (MPC) theory provides a foundation for modelling the cognition process. The stretch reflex of the neuromuscular system also makes use of the prediction of the internal model. Extensions to the MPC approach are described which account for: interaction with an automated vehicle; robust control; intermittent control; and cognitive workload. Further work to extend understanding of occupant-vehicle dynamic interaction is outlined. This paper is based on a keynote presentation given by the author to the 13th International Symposium on Advanced Vehicle Control (AVEC) conference held in Munich, September 2016.

A self-organized internal models architecture for coding sensory-motor schemes

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Esaú eEscobar Juárez

2016-04-01

Full Text Available Cognitive robotics research draws inspiration from theories and models on cognition, as conceived by neuroscience or cognitive psychology, to investigate biologically plausible computational models in artificial agents. In this field, the theoretical framework of Grounded Cognition provides epistemological and methodological grounds for the computational modeling of cognition. It has been stressed in the literature that textit{simulation}, textit{prediction}, and textit{multi-modal integration} are key aspects of cognition and that computational architectures capable of putting them into play in a biologically plausible way are a necessity.Research in this direction has brought extensive empirical evidencesuggesting that textit{Internal Models} are suitable mechanisms forsensory-motor integration. However, current Internal Models architectures show several drawbacks, mainly due to the lack of a unified substrate allowing for a true sensory-motor integration space, enabling flexible and scalable ways to model cognition under the embodiment hypothesis constraints.We propose the Self-Organized Internal ModelsArchitecture (SOIMA, a computational cognitive architecture coded by means of a network of self-organized maps, implementing coupled internal models that allow modeling multi-modal sensory-motor schemes. Our approach addresses integrally the issues of current implementations of Internal Models.We discuss the design and features of the architecture, and provide empirical results on a humanoid robot that demonstrate the benefits and potentialities of the SOIMA concept for studying cognition in artificial agents.

Latent variable models are network models.

Science.gov (United States)

Molenaar, Peter C M

2010-06-01

Cramer et al. present an original and interesting network perspective on comorbidity and contrast this perspective with a more traditional interpretation of comorbidity in terms of latent variable theory. My commentary focuses on the relationship between the two perspectives; that is, it aims to qualify the presumed contrast between interpretations in terms of networks and latent variables.

a Latent Variable Path Analysis Model of Secondary Physics Enrollments in New York State.

Science.gov (United States)

Sobolewski, Stanley John

The Percentage of Enrollment in Physics (PEP) at the secondary level nationally has been approximately 20% for the past few decades. For a more scientifically literate citizenry as well as specialists to continue scientific research and development, it is desirable that more students enroll in physics. Some of the predictor variables for physics enrollment and physics achievement that have been identified previously includes a community's socioeconomic status, the availability of physics, the sex of the student, the curriculum, as well as teacher and student data. This study isolated and identified predictor variables for PEP of secondary schools in New York. Data gathered by the State Education Department for the 1990-1991 school year was used. The source of this data included surveys completed by teachers and administrators on student characteristics and school facilities. A data analysis similar to that done by Bryant (1974) was conducted to determine if the relationships between a set of predictor variables related to physics enrollment had changed in the past 20 years. Variables which were isolated included: community, facilities, teacher experience, number of type of science courses, school size and school science facilities. When these variables were isolated, latent variable path diagrams were proposed and verified by the Linear Structural Relations computer modeling program (LISREL). These diagrams differed from those developed by Bryant in that there were more manifest variables used which included achievement scores in the form of Regents exam results. Two criterion variables were used, percentage of students enrolled in physics (PEP) and percent of students enrolled passing the Regents physics exam (PPP). The first model treated school and community level variables as exogenous while the second model treated only the community level variables as exogenous. The goodness of fit indices for the models was 0.77 for the first model and 0.83 for the second

Stability of Intercellular Exchange of Biochemical Substances Affected by Variability of Environmental Parameters

Science.gov (United States)

Mihailović, Dragutin T.; Budinčević, Mirko; Balaž, Igor; Mihailović, Anja

Communication between cells is realized by exchange of biochemical substances. Due to internal organization of living systems and variability of external parameters, the exchange is heavily influenced by perturbations of various parameters at almost all stages of the process. Since communication is one of essential processes for functioning of living systems it is of interest to investigate conditions for its stability. Using previously developed simplified model of bacterial communication in a form of coupled difference logistic equations we investigate stability of exchange of signaling molecules under variability of internal and external parameters.

Variability of concrete properties: experimental characterisation and probabilistic modelling for calcium leaching

International Nuclear Information System (INIS)

De Larrard, Th.

2010-09-01

Evaluating structures durability requires taking into account the variability of material properties. The thesis has two main aspects: on the one hand, an experimental campaign aimed at quantifying the variability of many indicators of concrete behaviour; on the other hand, a simple numerical model for calcium leaching is developed in order to implement probabilistic methods so as to estimate the lifetime of structures such as those related to radioactive waste disposal. The experimental campaign consisted in following up two real building sites, and quantifying the variability of these indicators, studying their correlation, and characterising the random fields variability for the considered variables (especially the correlation length). To draw any conclusion from the accelerated leaching tests with ammonium nitrate by overcoming the effects of temperature, an inverse analysis tool based on the theory of artificial neural networks was developed. Simple numerical tools are presented to investigate the propagation of variability in durability issues, quantify the influence of this variability on the lifespan of structures and explain the variability of the input parameters of the numerical model and the physical measurable quantities of the material. (author)

The Integration of Continuous and Discrete Latent Variable Models: Potential Problems and Promising Opportunities

Science.gov (United States)

Bauer, Daniel J.; Curran, Patrick J.

2004-01-01

Structural equation mixture modeling (SEMM) integrates continuous and discrete latent variable models. Drawing on prior research on the relationships between continuous and discrete latent variable models, the authors identify 3 conditions that may lead to the estimation of spurious latent classes in SEMM: misspecification of the structural model,…

A general model for use in internal dosimetry

International Nuclear Information System (INIS)

Johnson, J.R.; Carver, M.B.

1981-01-01

A model is described that combines the International Commission on Radiological Protection's Task Group on Lung Dynamics' Model, Eve's model for transport of material through the gastro-intestinal tract and a compartment model for the organs. Differential equations for this model are given, which include urinary and fecal excretion rates, and the method used to obtain solutions to these equations is described. (author)

Thermomechanics of solid materials with application to the Gurson-Tvergaard material model

Energy Technology Data Exchange (ETDEWEB)

Santaoja, K. [VTT Manufacturing Technology, Espoo (Finland). Materials and Structural Integrity

1997-12-31

The elastic-plastic material model for porous material proposed by Gurson and Tvergaard is evaluated. First a general description is given of constitutive equations for solid materials by thermomechanics with internal variables. The role and definition of internal variables are briefly discussed and the following definition is given: The independent variables present (possibly hidden) in the basic laws for thermomechanics are called controllable variables. The other independent variables are called internal variables. An internal variable is shown always to be a state variable. This work shows that if the specific dissipation function is a homogeneous function of degree one in the fluxes, a description for a time-independent process is obtained. When damage to materials is evaluated, usually a scalar-valued or tensorial variable called damage is introduced in the set of internal variables. A problem arises when determining the relationship between physically observable weakening of the material and the value for damage. Here a more feasible approach is used. Instead of damage, the void volume fraction is inserted into the set of internal variables. This allows use of an analytical equation for description of the mechanical weakening of the material. An extension to the material model proposed by Gurson and modified by Tvergaard is derived. The derivation is based on results obtained by thermomechanics and damage mechanics. The main difference between the original Gurson-Tvergaard material model and the extended one lies in the definition of the internal variable `equivalent tensile flow stress in the matrix material` denoted by {sigma}{sup M}. Using classical plasticity theory, Tvergaard elegantly derived an evolution equation for {sigma}{sup M}. This is not necessary in the present model, since damage mechanics gives an analytical equation between the stress tensor {sigma} and {sigma}M. Investigation of the Clausius-Duhem inequality shows that in compression

Thermomechanics of solid materials with application to the Gurson-Tvergaard material model

International Nuclear Information System (INIS)

Santaoja, K.

1997-01-01

The elastic-plastic material model for porous material proposed by Gurson and Tvergaard is evaluated. First a general description is given of constitutive equations for solid materials by thermomechanics with internal variables. The role and definition of internal variables are briefly discussed and the following definition is given: The independent variables present (possibly hidden) in the basic laws for thermomechanics are called controllable variables. The other independent variables are called internal variables. An internal variable is shown always to be a state variable. This work shows that if the specific dissipation function is a homogeneous function of degree one in the fluxes, a description for a time-independent process is obtained. When damage to materials is evaluated, usually a scalar-valued or tensorial variable called damage is introduced in the set of internal variables. A problem arises when determining the relationship between physically observable weakening of the material and the value for damage. Here a more feasible approach is used. Instead of damage, the void volume fraction is inserted into the set of internal variables. This allows use of an analytical equation for description of the mechanical weakening of the material. An extension to the material model proposed by Gurson and modified by Tvergaard is derived. The derivation is based on results obtained by thermomechanics and damage mechanics. The main difference between the original Gurson-Tvergaard material model and the extended one lies in the definition of the internal variable 'equivalent tensile flow stress in the matrix material' denoted by σ M . Using classical plasticity theory, Tvergaard elegantly derived an evolution equation for σ M . This is not necessary in the present model, since damage mechanics gives an analytical equation between the stress tensor σ and σM. Investigation of the Clausius-Duhem inequality shows that in compression, states occur which are not

Modeling Source Water TOC Using Hydroclimate Variables and Local Polynomial Regression.

Science.gov (United States)

Samson, Carleigh C; Rajagopalan, Balaji; Summers, R Scott

2016-04-19

To control disinfection byproduct (DBP) formation in drinking water, an understanding of the source water total organic carbon (TOC) concentration variability can be critical. Previously, TOC concentrations in water treatment plant source waters have been modeled using streamflow data. However, the lack of streamflow data or unimpaired flow scenarios makes it difficult to model TOC. In addition, TOC variability under climate change further exacerbates the problem. Here we proposed a modeling approach based on local polynomial regression that uses climate, e.g. temperature, and land surface, e.g., soil moisture, variables as predictors of TOC concentration, obviating the need for streamflow. The local polynomial approach has the ability to capture non-Gaussian and nonlinear features that might be present in the relationships. The utility of the methodology is demonstrated using source water quality and climate data in three case study locations with surface source waters including river and reservoir sources. The models show good predictive skill in general at these locations, with lower skills at locations with the most anthropogenic influences in their streams. Source water TOC predictive models can provide water treatment utilities important information for making treatment decisions for DBP regulation compliance under future climate scenarios.

Modelling of internal structure in seismic analysis of a PHWR building

International Nuclear Information System (INIS)

Reddy, G.R.; Vaze, K.K.; Kushawaha, H.S.; Ingle, R.K.; Subramanian, K.V.

1991-01-01

Seismic analysis of complex and large structures, consisting of thick shear walls, such as Reactor Building is very involved and time consuming. It is a standard practice to model the structure as a stick model to predict reasonably the dynamic behaviour of the structure. It is required to determine approximate equivalent sectional properties of Internal Structure for representation in the stick model. The restraint to warping can change the stress distribution thus affecting the centre of rigidity and torsional inertia, Hence, standard formulae does not hold good for determination of sectional properties of the Internal Structure. In this case the equivalent sectional properties for the Internal Structure are calculated using a Finite Element Model (FEM) of the Internal Structure and applying unit horizontal forces in each direction. A 3-D stick model is developed using the guidelines. Using the properties calculated by FEM and also by standard formulae, the responses of the 3-D stick model are compared. (J.P.N.)

Linking Inflammation, Cardiorespiratory Variability, and Neural Control in Acute Inflammation via Computational Modeling.

Science.gov (United States)

Dick, Thomas E; Molkov, Yaroslav I; Nieman, Gary; Hsieh, Yee-Hsee; Jacono, Frank J; Doyle, John; Scheff, Jeremy D; Calvano, Steve E; Androulakis, Ioannis P; An, Gary; Vodovotz, Yoram

2012-01-01

Acute inflammation leads to organ failure by engaging catastrophic feedback loops in which stressed tissue evokes an inflammatory response and, in turn, inflammation damages tissue. Manifestations of this maladaptive inflammatory response include cardio-respiratory dysfunction that may be reflected in reduced heart rate and ventilatory pattern variabilities. We have developed signal-processing algorithms that quantify non-linear deterministic characteristics of variability in biologic signals. Now, coalescing under the aegis of the NIH Computational Biology Program and the Society for Complexity in Acute Illness, two research teams performed iterative experiments and computational modeling on inflammation and cardio-pulmonary dysfunction in sepsis as well as on neural control of respiration and ventilatory pattern variability. These teams, with additional collaborators, have recently formed a multi-institutional, interdisciplinary consortium, whose goal is to delineate the fundamental interrelationship between the inflammatory response and physiologic variability. Multi-scale mathematical modeling and complementary physiological experiments will provide insight into autonomic neural mechanisms that may modulate the inflammatory response to sepsis and simultaneously reduce heart rate and ventilatory pattern variabilities associated with sepsis. This approach integrates computational models of neural control of breathing and cardio-respiratory coupling with models that combine inflammation, cardiovascular function, and heart rate variability. The resulting integrated model will provide mechanistic explanations for the phenomena of respiratory sinus-arrhythmia and cardio-ventilatory coupling observed under normal conditions, and the loss of these properties during sepsis. This approach holds the potential of modeling cross-scale physiological interactions to improve both basic knowledge and clinical management of acute inflammatory diseases such as sepsis and trauma.

Modeling Complex Nesting Structures in International Business Research

DEFF Research Database (Denmark)

Nielsen, Bo Bernhard; Nielsen, Sabina

2013-01-01

hierarchical random coefficient models (RCM) are often used for the analysis of multilevel phenomena, IB issues often result in more complex nested structures. This paper illustrates how cross-nested multilevel modeling allowing for predictor variables and cross-level interactions at multiple (crossed) levels...

Resolving high-frequency internal waves generated at an isolated coral atoll using an unstructured grid ocean model

Science.gov (United States)

Rayson, Matthew D.; Ivey, Gregory N.; Jones, Nicole L.; Fringer, Oliver B.

2018-02-01

We apply the unstructured grid hydrodynamic model SUNTANS to investigate the internal wave dynamics around Scott Reef, Western Australia, an isolated coral reef atoll located on the edge of the continental shelf in water depths of 500,m and more. The atoll is subject to strong semi-diurnal tidal forcing and consists of two relatively shallow lagoons separated by a 500 m deep, 2 km wide and 15 km long channel. We focus on the dynamics in this channel as the internal tide-driven flow and resulting mixing is thought to be a key mechanism controlling heat and nutrient fluxes into the reef lagoons. We use an unstructured grid to discretise the domain and capture both the complex topography and the range of internal wave length scales in the channel flow. The model internal wave field shows super-tidal frequency lee waves generated by the combination of the steep channel topography and strong tidal flow. We evaluate the model performance using observations of velocity and temperature from two through water-column moorings in the channel separating the two reefs. Three different global ocean state estimate datasets (global HYCOM, CSIRO Bluelink, CSIRO climatology atlas) were used to provide the model initial and boundary conditions, and the model outputs from each were evaluated against the field observations. The scenario incorporating the CSIRO Bluelink data performed best in terms of through-water column Murphy skill scores of water temperature and eastward velocity variability in the channel. The model captures the observed vertical structure of the tidal (M2) and super-tidal (M4) frequency temperature and velocity oscillations. The model also predicts the direction and magnitude of the M2 internal tide energy flux. An energy analysis reveals a net convergence of the M2 energy flux and a divergence of the M4 energy flux in the channel, indicating the channel is a region of either energy transfer to higher frequencies or energy loss to dissipation. This conclusion is

An Atmospheric Variability Model for Venus Aerobraking Missions

Science.gov (United States)

Tolson, Robert T.; Prince, Jill L. H.; Konopliv, Alexander A.

2013-01-01

Aerobraking has proven to be an enabling technology for planetary missions to Mars and has been proposed to enable low cost missions to Venus. Aerobraking saves a significant amount of propulsion fuel mass by exploiting atmospheric drag to reduce the eccentricity of the initial orbit. The solar arrays have been used as the primary drag surface and only minor modifications have been made in the vehicle design to accommodate the relatively modest aerothermal loads. However, if atmospheric density is highly variable from orbit to orbit, the mission must either accept higher aerothermal risk, a slower pace for aerobraking, or a tighter corridor likely with increased propulsive cost. Hence, knowledge of atmospheric variability is of great interest for the design of aerobraking missions. The first planetary aerobraking was at Venus during the Magellan mission. After the primary Magellan science mission was completed, aerobraking was used to provide a more circular orbit to enhance gravity field recovery. Magellan aerobraking took place between local solar times of 1100 and 1800 hrs, and it was found that the Venusian atmospheric density during the aerobraking phase had less than 10% 1 sigma orbit to orbit variability. On the other hand, at some latitudes and seasons, Martian variability can be as high as 40% 1 sigmaFrom both the MGN and PVO mission it was known that the atmosphere, above aerobraking altitudes, showed greater variability at night, but this variability was never quantified in a systematic manner. This paper proposes a model for atmospheric variability that can be used for aerobraking mission design until more complete data sets become available.

Appraisal and Reliability of Variable Engagement Model Prediction ...

African Journals Online (AJOL)

The variable engagement model based on the stress - crack opening displacement relationship and, which describes the behaviour of randomly oriented steel fibres composite subjected to uniaxial tension has been evaluated so as to determine the safety indices associated when the fibres are subjected to pullout and with ...

Human Responses to Climate Variability: The Case of South Africa

Science.gov (United States)

Oppenheimer, M.; Licker, R.; Mastrorillo, M.; Bohra-Mishra, P.; Estes, L. D.; Cai, R.

2014-12-01

Climate variability has been associated with a range of societal and individual outcomes including migration, violent conflict, changes in labor productivity, and health impacts. Some of these may be direct responses to changes in mean temperature or precipitation or extreme events, such as displacement of human populations by tropical cyclones. Others may be mediated by a variety of biological, social, or ecological factors such as migration in response to long-term changes in crops yields. Research is beginning to elucidate and distinguish the many channels through which climate variability may influence human behavior (ranging from the individual to the collective, societal level) in order to better understand how to improve resilience in the face of current variability as well as future climate change. Using a variety of data sets from South Africa, we show how climate variability has influenced internal (within country) migration in recent history. We focus on South Africa as it is a country with high levels of internal migration and dramatic temperature and precipitation changes projected for the 21st century. High poverty rates and significant levels of rain-fed, smallholder agriculture leave large portions of South Africa's population base vulnerable to future climate change. In this study, we utilize two complementary statistical models - one micro-level model, driven by individual and household level survey data, and one macro-level model, driven by national census statistics. In both models, we consider the effect of climate on migration both directly (with gridded climate reanalysis data) and indirectly (with agricultural production statistics). With our historical analyses of climate variability, we gain insights into how the migration decisions of South Africans may be influenced by future climate change. We also offer perspective on the utility of micro and macro level approaches in the study of climate change and human migration.

STABILITY OF INTERNATIONAL ENVIRONMENTAL AGREEMENTS IN LEADERSHIP MODEL

Institute of Scientific and Technical Information of China (English)

Jin ZHANG; Shouyang WANG; Lei ZU

2008-01-01

International Environmental Agreements (IEAs) are a form of cooperation ratified by countries which can improve the management of shared environmental resources. The authors analyze the stability of International Environmental Agreements in leadership model. In 2006, Diamantoudi & Sartzetakis found that a stable coalition consists of either 2, 3, or 4 members if the number of countries is greater than 4. Their model is reconsidered. It is shown that the size of stable IEAs decreases from 3 to 2 when the total number of countries involved increases. However, a situation that can guarantee 4 to be the size of stable IEAs could not be found.

Role of environmental variables on radon concentration in soil

International Nuclear Information System (INIS)

Climent, H.; Bakalowicz, M.; Monnin, M.

1998-01-01

In the frame of an European project, radon concentrations in soil and measurements of environmental variables such as the nature of the soil or climatic variables were monitored. The data have been analysed by time-series analysis methods, i.e. Correlation and Spectrum Analysis, to point out relations between radon concentrations and some environmental variables. This approach is a compromise between direct observation and modelling. The observation of the rough time series is unable to point out the relation between radon concentrations and an environmental variable because of the overlapping of the influences of several variables, and the time delay induced by the medium. The Cross Spectrum function between the time series of radon and of an environmental variable describes the nature of the relation and gives the response time in the case of a cause to effect relation. It requires the only hypothesis that the environmental variable is the input function and radon concentration the output function. This analysis is an important preliminary study for modelling. By that way the importance of soil nature has been pointed out. The internal variables of the medium (permeability, porosity) appear to restrain the influence of the environmental variables such as humidity, temperature or atmospheric pressure. (author)

Viscous cosmological models with a variable cosmological term ...

African Journals Online (AJOL)

Einstein's field equations for a Friedmann-Lamaitre Robertson-Walker universe filled with a dissipative fluid with a variable cosmological term L described by full Israel-Stewart theory are considered. General solutions to the field equations for the flat case have been obtained. The solution corresponds to the dust free model ...

Automatic Welding Control Using a State Variable Model.

Science.gov (United States)

1979-06-01

A-A10 610 NAVEAL POSTGRADUATE SCH4O.M CEAY CA0/ 13/ SAUTOMATIC WELDING CONTROL USING A STATE VARIABLE MODEL.W()JUN 79 W V "my UNCLASSIFIED...taverse Drive Unit // Jbint Path /Fixed Track 34 (servomotor positioning). Additional controls of heave (vertical), roll (angular rotation about the

Robots with Internal Models: A Route to Self-Aware and Hence Safer Robots

Science.gov (United States)

Winfield, Alan F. T.

The following sections are included: * Introduction * Internal Models and Self-Awareness * Internal Model-Based Architecture for Robot Safety * The Internal Model * The Consequence Evaluator * The Object Tracker-Localizer * Towards an Ethical Robot * Challenges and Open Questions * Discussion: The Way Forward * Summary and Conclusions

Mathematical models in Slowpoke reactor internal irradiation site

International Nuclear Information System (INIS)

Raza, J.

2007-01-01

The main objective is to build representative mathematical models of neutron activation analysis in a Slowpoke internal irradiation site. Another significant objective is to correct various elements neutron activation analysis measured mass using these models. The neutron flux perturbation is responsible for the measured under-estimation of real masses. We supposed that neutron flux perturbation measurements taken during the Ecole Polytechnique de Montreal Slowpoke reactor first fuel loading were still valid after the second fuelling. .We also supposed that the thermal neutrons spatial and kinetic energies distributions as well as the absorption microscopic cross section dependence on the neutrons kinetic energies were important factors to satisfactorily represent neutron activation analysis results. In addition, we assumed that the neutron flux is isotropic in the laboratory system. We used experimental results from the Slowpoke reactor internal irradiation sites, in order to validate our mathematical models. Our models results are in close agreement with these experimental results..We established an accurate global mathematical correlation of the neutron flux perturbation in function of samples volumes and macroscopic neutron absorption cross sections. It is applicable to sample volumes ranging from 0,1 to 1,3 ml and macroscopic neutron absorption cross section up to 5 moles-b for seven (7) elements with atomic numbers (Z) ranging from 5 to 79. We first came up with a heuristic neutron transport mathematical semi-analytical model, in order to better understand neutrons behaviour in presence of one of several different nuclei samples volumes and mass. In order to well represent the neutron flux perturbation, we combined a neutron transport solution obtained from the spherical harmonics method of a finite cylinder and a mathematical expression combining two cylindrical harmonic functions..With the help of this model and the least squares method, we made extensive

On the ""early-time"" evolution of variables relevant to turbulence models for the Rayleigh-Taylor instability

Energy Technology Data Exchange (ETDEWEB)

Rollin, Bertrand [Los Alamos National Laboratory; Andrews, Malcolm J [Los Alamos National Laboratory

2010-01-01

We present our progress toward setting initial conditions in variable density turbulence models. In particular, we concentrate our efforts on the BHR turbulence model for turbulent Rayleigh-Taylor instability. Our approach is to predict profiles of relevant variables before fully turbulent regime and use them as initial conditions for the turbulence model. We use an idealized model of mixing between two interpenetrating fluids to define the initial profiles for the turbulence model variables. Velocities and volume fractions used in the idealized mixing model are obtained respectively from a set of ordinary differential equations modeling the growth of the Rayleigh-Taylor instability and from an idealization of the density profile in the mixing layer. A comparison between predicted profiles for the turbulence model variables and profiles of the variables obtained from low Atwood number three dimensional simulations show reasonable agreement.

Model tracking dual stochastic controller design under irregular internal noises

International Nuclear Information System (INIS)

Lee, Jong Bok; Heo, Hoon; Cho, Yun Hyun; Ji, Tae Young

2006-01-01

Although many methods about the control of irregular external noise have been introduced and implemented, it is still necessary to design a controller that will be more effective and efficient methods to exclude for various noises. Accumulation of errors due to model tracking, internal noises (thermal noise, shot noise and l/f noise) that come from elements such as resistor, diode and transistor etc. in the circuit system and numerical errors due to digital process often destabilize the system and reduce the system performance. New stochastic controller is adopted to remove those noises using conventional controller simultaneously. Design method of a model tracking dual controller is proposed to improve the stability of system while removing external and internal noises. In the study, design process of the model tracking dual stochastic controller is introduced that improves system performance and guarantees robustness under irregular internal noises which can be created internally. The model tracking dual stochastic controller utilizing F-P-K stochastic control technique developed earlier is implemented to reveal its performance via simulation

Internal controls and credit risk relationship among banks in Europe

Directory of Open Access Journals (Sweden)

Ellis Kofi Akwaa-Sekyi

2017-01-01

Full Text Available Purpose: The study purport to investigate the effectiveness of internal control mechanisms, investigate whether evidence of agency problem is found among banks in Europe and determine how internal controls affect credit risk. Design/methodology/approach: Panel data from 91 banks from 23 European Union countries were studied from 2008-2014. Hausman’s specification test suggest the use of fixed effects estimation technique of GLS. Quantitatively modelled data on 15 variables covering elements of internal controls, objectives of internal controls, agency problem, bank and country specific variables were used. Findings: There is still high credit risk in spite of measures being implemented by the European Central Bank. Banks have individual entity factors that increase or decrease credit risk. The study finds effective internal control systems because objectives of internal controls are achieved and significantly determine credit risk. Agency problem is confirmed due to significant positive relation with credit risk. There is significant effect of internal controls on credit risk with specific variables as risk assessment, return on average risk weighted assets, institutional ownership, bank size, inflation, interest rate and GDP. Research limitations/implications: Missing data prevented the use of strongly balanced panel. The lack of flexibility with using quantitative approach did not allow further scrutiny of the nature of variables. However, statistical tests were acceptable for the model used. The study has implications for management and owners of banks to be warry of agency problem because that provides incentive for reckless high risk transactions that may benefit the agent than the principal. Management must engage in actions that profile the company better and enhances value maximization. Rising default risk has tendency to impair corporate image leading to loss of reputational capital. Originality/value: The study provides the use of

Effect of process variables on the Drucker-Prager cap model and residual stress distribution of tablets estimated by the finite element method.

Science.gov (United States)

Hayashi, Yoshihiro; Otoguro, Saori; Miura, Takahiro; Onuki, Yoshinori; Obata, Yasuko; Takayama, Kozo

2014-01-01

A multivariate statistical technique was applied to clarify the causal correlation between variables in the manufacturing process and the residual stress distribution of tablets. Theophylline tablets were prepared according to a Box-Behnken design using the wet granulation method. Water amounts (X1), kneading time (X2), lubricant-mixing time (X3), and compression force (X4) were selected as design variables. The Drucker-Prager cap (DPC) model was selected as the method for modeling the mechanical behavior of pharmaceutical powders. Simulation parameters, such as Young's modulus, Poisson rate, internal friction angle, plastic deformation parameters, and initial density of the powder, were measured. Multiple regression analysis demonstrated that the simulation parameters were significantly affected by process variables. The constructed DPC models were fed into the analysis using the finite element method (FEM), and the mechanical behavior of pharmaceutical powders during the tableting process was analyzed using the FEM. The results of this analysis revealed that the residual stress distribution of tablets increased with increasing X4. Moreover, an interaction between X2 and X3 also had an effect on shear and the x-axial residual stress of tablets. Bayesian network analysis revealed causal relationships between the process variables, simulation parameters, residual stress distribution, and pharmaceutical responses of tablets. These results demonstrated the potential of the FEM as a tool to help improve our understanding of the residual stress of tablets and to optimize process variables, which not only affect tablet characteristics, but also are risks of causing tableting problems.

Sensitivity Modeling of On-chip Capacitances : Parasitics Extraction for Manufacturing Variability

NARCIS (Netherlands)

Bi, Y.

2012-01-01

With each new generation of IC process technologies, the impact of manufacturing variability is increasing. As such, design optimality is harder and harder to achieve and effective modeling tools and methods are needed to capture the effects of variability in such a way that it is understandable and

Effect of land model ensemble versus coupled model ensemble on the simulation of precipitation climatology and variability

Science.gov (United States)

Wei, Jiangfeng; Dirmeyer, Paul A.; Yang, Zong-Liang; Chen, Haishan

2017-10-01

Through a series of model simulations with an atmospheric general circulation model coupled to three different land surface models, this study investigates the impacts of land model ensembles and coupled model ensemble on precipitation simulation. It is found that coupling an ensemble of land models to an atmospheric model has a very minor impact on the improvement of precipitation climatology and variability, but a simple ensemble average of the precipitation from three individually coupled land-atmosphere models produces better results, especially for precipitation variability. The generally weak impact of land processes on precipitation should be the main reason that the land model ensembles do not improve precipitation simulation. However, if there are big biases in the land surface model or land surface data set, correcting them could improve the simulated climate, especially for well-constrained regional climate simulations.

On the Use of Variability Operations in the V-Modell XT Software Process Line

DEFF Research Database (Denmark)

Kuhrmann, Marco; Méndez Fernández, Daniel; Ternité, Thomas

2016-01-01

. In this article, we present a study on the feasibility of variability operations to support the development of software process lines in the context of the V-Modell XT. We analyze which variability operations are defined and practically used. We provide an initial catalog of variability operations...... as an improvement proposal for other process models. Our findings show that 69 variability operation types are defined across several metamodel versions of which, however, 25 remain unused. The found variability operations allow for systematically modifying the content of process model elements and the process......Software process lines provide a systematic approach to develop and manage software processes. It defines a reference process containing general process assets, whereas a well-defined customization approach allows process engineers to create new process variants, e.g., by extending or modifying...

A New Variable Selection Method Based on Mutual Information Maximization by Replacing Collinear Variables for Nonlinear Quantitative Structure-Property Relationship Models

Energy Technology Data Exchange (ETDEWEB)

Ghasemi, Jahan B.; Zolfonoun, Ehsan [Toosi University of Technology, Tehran (Korea, Republic of)

2012-05-15

Selection of the most informative molecular descriptors from the original data set is a key step for development of quantitative structure activity/property relationship models. Recently, mutual information (MI) has gained increasing attention in feature selection problems. This paper presents an effective mutual information-based feature selection approach, named mutual information maximization by replacing collinear variables (MIMRCV), for nonlinear quantitative structure-property relationship models. The proposed variable selection method was applied to three different QSPR datasets, soil degradation half-life of 47 organophosphorus pesticides, GC-MS retention times of 85 volatile organic compounds, and water-to-micellar cetyltrimethylammonium bromide partition coefficients of 62 organic compounds.The obtained results revealed that using MIMRCV as feature selection method improves the predictive quality of the developed models compared to conventional MI based variable selection algorithms.

A New Variable Selection Method Based on Mutual Information Maximization by Replacing Collinear Variables for Nonlinear Quantitative Structure-Property Relationship Models

International Nuclear Information System (INIS)

Ghasemi, Jahan B.; Zolfonoun, Ehsan

2012-01-01

Selection of the most informative molecular descriptors from the original data set is a key step for development of quantitative structure activity/property relationship models. Recently, mutual information (MI) has gained increasing attention in feature selection problems. This paper presents an effective mutual information-based feature selection approach, named mutual information maximization by replacing collinear variables (MIMRCV), for nonlinear quantitative structure-property relationship models. The proposed variable selection method was applied to three different QSPR datasets, soil degradation half-life of 47 organophosphorus pesticides, GC-MS retention times of 85 volatile organic compounds, and water-to-micellar cetyltrimethylammonium bromide partition coefficients of 62 organic compounds.The obtained results revealed that using MIMRCV as feature selection method improves the predictive quality of the developed models compared to conventional MI based variable selection algorithms

Modelling the Spatial Isotope Variability of Precipitation in Syria

Energy Technology Data Exchange (ETDEWEB)

Kattan, Z.; Kattaa, B. [Department of Geology, Atomic Energy Commission of Syria (AECS), Damascus (Syrian Arab Republic)

2013-07-15

Attempts were made to model the spatial variability of environmental isotope ({sup 18}O, {sup 2}H and {sup 3}H) compositions of precipitation in syria. Rainfall samples periodically collected on a monthly basis from 16 different stations were used for processing and demonstrating the spatial distributions of these isotopes, together with those of deuterium excess (d) values. Mathematically, the modelling process was based on applying simple polynomial models that take into consideration the effects of major geographic factors (Lon.E., Lat.N., and altitude). The modelling results of spatial distribution of stable isotopes ({sup 18}O and {sup 2}H) were generally good, as shown from the high correlation coefficients (R{sup 2} = 0.7-0.8), calculated between the observed and predicted values. In the case of deuterium excess and tritium distributions, the results were most likely approximates (R{sup 2} = 0.5-0.6). Improving the simulation of spatial isotope variability probably requires the incorporation of other local meteorological factors, such as relative air humidity, precipitation amount and vapour pressure, which are supposed to play an important role in such an arid country. (author)

Dynamical and biogeochemical control on the decadal variability of ocean carbon fluxes

Directory of Open Access Journals (Sweden)

R. Séférian

2013-04-01

Full Text Available Several recent observation-based studies suggest that ocean anthropogenic carbon uptake has slowed down due to the impact of anthropogenic forced climate change. However, it remains unclear whether detected changes over the recent time period can be attributed to anthropogenic climate change or rather to natural climate variability (internal plus naturally forced variability alone. One large uncertainty arises from the lack of knowledge on ocean carbon flux natural variability at the decadal time scales. To gain more insights into decadal time scales, we have examined the internal variability of ocean carbon fluxes in a 1000 yr long preindustrial simulation performed with the Earth System Model IPSL-CM5A-LR. Our analysis shows that ocean carbon fluxes exhibit low-frequency oscillations that emerge from their year-to-year variability in the North Atlantic, the North Pacific, and the Southern Ocean. In our model, a 20 yr mode of variability in the North Atlantic air-sea carbon flux is driven by sea surface temperature variability and accounts for ~40% of the interannual regional variance. The North Pacific and the Southern Ocean carbon fluxes are also characterised by decadal to multi-decadal modes of variability (10 to 50 yr that account for 20–40% of the interannual regional variance. These modes are driven by the vertical supply of dissolved inorganic carbon through the variability of Ekman-induced upwelling and deep-mixing events. Differences in drivers of regional modes of variability stem from the coupling between ocean dynamics variability and the ocean carbon distribution, which is set by large-scale secular ocean circulation.

Simple model for crop photosynthesis in terms of weather variables ...

African Journals Online (AJOL)

A theoretical mathematical model for describing crop photosynthetic rate in terms of the weather variables and crop characteristics is proposed. The model utilizes a series of efficiency parameters, each of which reflect the fraction of possible photosynthetic rate permitted by the different weather elements or crop architecture.

Model for expressing leaf photosynthesis in terms of weather variables

African Journals Online (AJOL)

A theoretical mathematical model for describing photosynthesis in individual leaves in terms of weather variables is proposed. The model utilizes a series of efficiency parameters, each of which reflect the fraction of potential photosynthetic rate permitted by the different environmental elements. These parameters are useful ...

Rate dependent inelastic behavior of polycrystalline solids using a dislocation model

International Nuclear Information System (INIS)

Werne, R.W.; Kelly, J.M.

1980-01-01

A rate dependent theory of polycrystalline plasticity is presented in which the solid is modeled as an isotropic continuum with internal variables. The rate of plastic deformation is shown to be a function of the deviatoric portion of the Cauchy stress tensor as well as two scalar internal variables. The scalar internal variables, which are the dislocation density and mobile fraction, are governed by rate equations which reflect the evolution of microstructural processes. The model has been incorporated into a two dimensional finite element code and several example multidimensional problems are presented which exhibit the rate dependence of the material model

High-resolution regional climate model evaluation using variable-resolution CESM over California

Science.gov (United States)

Huang, X.; Rhoades, A.; Ullrich, P. A.; Zarzycki, C. M.

2015-12-01

Understanding the effect of climate change at regional scales remains a topic of intensive research. Though computational constraints remain a problem, high horizontal resolution is needed to represent topographic forcing, which is a significant driver of local climate variability. Although regional climate models (RCMs) have traditionally been used at these scales, variable-resolution global climate models (VRGCMs) have recently arisen as an alternative for studying regional weather and climate allowing two-way interaction between these domains without the need for nudging. In this study, the recently developed variable-resolution option within the Community Earth System Model (CESM) is assessed for long-term regional climate modeling over California. Our variable-resolution simulations will focus on relatively high resolutions for climate assessment, namely 28km and 14km regional resolution, which are much more typical for dynamically downscaled studies. For comparison with the more widely used RCM method, the Weather Research and Forecasting (WRF) model will be used for simulations at 27km and 9km. All simulations use the AMIP (Atmospheric Model Intercomparison Project) protocols. The time period is from 1979-01-01 to 2005-12-31 (UTC), and year 1979 was discarded as spin up time. The mean climatology across California's diverse climate zones, including temperature and precipitation, is analyzed and contrasted with the Weather Research and Forcasting (WRF) model (as a traditional RCM), regional reanalysis, gridded observational datasets and uniform high-resolution CESM at 0.25 degree with the finite volume (FV) dynamical core. The results show that variable-resolution CESM is competitive in representing regional climatology on both annual and seasonal time scales. This assessment adds value to the use of VRGCMs for projecting climate change over the coming century and improve our understanding of both past and future regional climate related to fine

Modeling Psychological Attributes in Psychology – An Epistemological Discussion: Network Analysis vs. Latent Variables

Science.gov (United States)

Guyon, Hervé; Falissard, Bruno; Kop, Jean-Luc

2017-01-01

Network Analysis is considered as a new method that challenges Latent Variable models in inferring psychological attributes. With Network Analysis, psychological attributes are derived from a complex system of components without the need to call on any latent variables. But the ontological status of psychological attributes is not adequately defined with Network Analysis, because a psychological attribute is both a complex system and a property emerging from this complex system. The aim of this article is to reappraise the legitimacy of latent variable models by engaging in an ontological and epistemological discussion on psychological attributes. Psychological attributes relate to the mental equilibrium of individuals embedded in their social interactions, as robust attractors within complex dynamic processes with emergent properties, distinct from physical entities located in precise areas of the brain. Latent variables thus possess legitimacy, because the emergent properties can be conceptualized and analyzed on the sole basis of their manifestations, without exploring the upstream complex system. However, in opposition with the usual Latent Variable models, this article is in favor of the integration of a dynamic system of manifestations. Latent Variables models and Network Analysis thus appear as complementary approaches. New approaches combining Latent Network Models and Network Residuals are certainly a promising new way to infer psychological attributes, placing psychological attributes in an inter-subjective dynamic approach. Pragmatism-realism appears as the epistemological framework required if we are to use latent variables as representations of psychological attributes. PMID:28572780

A New Bi-Directional Projection Model Based on Pythagorean Uncertain Linguistic Variable

OpenAIRE

Huidong Wang; Shifan He; Xiaohong Pan

2018-01-01

To solve the multi-attribute decision making (MADM) problems with Pythagorean uncertain linguistic variable, an extended bi-directional projection method is proposed. First, we utilize the linguistic scale function to convert uncertain linguistic variable and provide a new projection model, subsequently. Then, to depict the bi-directional projection method, the formative vectors of alternatives and ideal alternatives are defined. Furthermore, a comparative analysis with projection model is co...

Internal and external influences on pro-environmental behavior: participation in a green electricity program

International Nuclear Information System (INIS)

Clark, C.F.; Moore, M.R.; Kotchen, M.J.; Michigan Univ., Ann Arbor, MI

2003-01-01

This paper integrates themes from psychology and economics to analyze pro-environmental behavior. Increasingly, both disciplines share an interest in understanding internal and external influences on behavior. In this study, we analyze data from a mail survey of participants and non-participants in a premium-priced, green electricity program. Internal variables consist of a newly developed scale for altruistic attitudes based on the Schwartz norm-activation model, and a modified version of the New Ecological Paradigm scale to measure environmental attitudes. External variables consist of household income and standard socio-demographic characteristics. The two internal variables and two external variables are significant in a logit model of the decision to participate in the program. We then focus on participants in the program and analyze their specific motives for participating. These include motives relating to several concerns: ecosystem health, personal health, environmental quality for residents in southeastern Michigan, global warming, and warm-glow (or intrinsic) satisfaction. In a statistical ranking of the importance of each motive, a biocentric motive ranks first, an altruistic motive ranks second, and an egoistic motive ranks third. (author)

Shared Variable Oriented Parallel Precompiler for SPMD Model

Institute of Scientific and Technical Information of China (English)

无

1995-01-01

For the moment,commercial parallel computer systems with distributed memory architecture are usually provided with parallel FORTRAN or parallel C compliers,which are just traditional sequential FORTRAN or C compilers expanded with communication statements.Programmers suffer from writing parallel programs with communication statements. The Shared Variable Oriented Parallel Precompiler (SVOPP) proposed in this paper can automatically generate appropriate communication statements based on shared variables for SPMD(Single Program Multiple Data) computation model and greatly ease the parallel programming with high communication efficiency.The core function of parallel C precompiler has been successfully verified on a transputer-based parallel computer.Its prominent performance shows that SVOPP is probably a break-through in parallel programming technique.

Efficient family-based model checking via variability abstractions

DEFF Research Database (Denmark)

Dimovski, Aleksandar; Al-Sibahi, Ahmad Salim; Brabrand, Claus

2016-01-01

with the abstract model checking of the concrete high-level variational model. This allows the use of Spin with all its accumulated optimizations for efficient verification of variational models without any knowledge about variability. We have implemented the transformations in a prototype tool, and we illustrate......Many software systems are variational: they can be configured to meet diverse sets of requirements. They can produce a (potentially huge) number of related systems, known as products or variants, by systematically reusing common parts. For variational models (variational systems or families...... of related systems), specialized family-based model checking algorithms allow efficient verification of multiple variants, simultaneously, in a single run. These algorithms, implemented in a tool Snip, scale much better than ``the brute force'' approach, where all individual systems are verified using...

Continuous-variable protocol for oblivious transfer in the noisy-storage model

DEFF Research Database (Denmark)

Furrer, Fabian; Gehring, Tobias; Schaffner, Christian

2018-01-01

for oblivious transfer for optical continuous-variable systems, and prove its security in the noisy-storage model. This model allows us to establish security by sending more quantum signals than an attacker can reliably store during the protocol. The security proof is based on uncertainty relations which we...... derive for continuous-variable systems, that differ from the ones used in quantum key distribution. We experimentally demonstrate in a proof-of-principle experiment the proposed oblivious transfer protocol for various channel losses by using entangled two-mode squeezed states measured with balanced...

Soil Cd, Cr, Cu, Ni, Pb and Zn sorption and retention models using SVM: Variable selection and competitive model.

Science.gov (United States)

González Costa, J J; Reigosa, M J; Matías, J M; Covelo, E F

2017-09-01

The aim of this study was to model the sorption and retention of Cd, Cu, Ni, Pb and Zn in soils. To that extent, the sorption and retention of these metals were studied and the soil characterization was performed separately. Multiple stepwise regression was used to produce multivariate models with linear techniques and with support vector machines, all of which included 15 explanatory variables characterizing soils. When the R-squared values are represented, two different groups are noticed. Cr, Cu and Pb sorption and retention show a higher R-squared; the most explanatory variables being humified organic matter, Al oxides and, in some cases, cation-exchange capacity (CEC). The other group of metals (Cd, Ni and Zn) shows a lower R-squared, and clays are the most explanatory variables, including a percentage of vermiculite and slime. In some cases, quartz, plagioclase or hematite percentages also show some explanatory capacity. Support Vector Machine (SVM) regression shows that the different models are not as regular as in multiple regression in terms of number of variables, the regression for nickel adsorption being the one with the highest number of variables in its optimal model. On the other hand, there are cases where the most explanatory variables are the same for two metals, as it happens with Cd and Cr adsorption. A similar adsorption mechanism is thus postulated. These patterns of the introduction of variables in the model allow us to create explainability sequences. Those which are the most similar to the selectivity sequences obtained by Covelo (2005) are Mn oxides in multiple regression and change capacity in SVM. Among all the variables, the only one that is explanatory for all the metals after applying the maximum parsimony principle is the percentage of sand in the retention process. In the competitive model arising from the aforementioned sequences, the most intense competitiveness for the adsorption and retention of different metals appears between

Variable-coefficient higher-order nonlinear Schroedinger model in optical fibers: Variable-coefficient bilinear form, Baecklund transformation, brightons and symbolic computation

International Nuclear Information System (INIS)

Tian Bo; Gao Yitian; Zhu Hongwu

2007-01-01

Symbolically investigated in this Letter is a variable-coefficient higher-order nonlinear Schroedinger (vcHNLS) model for ultrafast signal-routing, fiber laser systems and optical communication systems with distributed dispersion and nonlinearity management. Of physical and optical interests, with bilinear method extend, the vcHNLS model is transformed into a variable-coefficient bilinear form, and then an auto-Baecklund transformation is constructed. Constraints on coefficient functions are analyzed. Potentially observable with future optical-fiber experiments, variable-coefficient brightons are illustrated. Relevant properties and features are discussed as well. Baecklund transformation and other results of this Letter will be of certain value to the studies on inhomogeneous fiber media, core of dispersion-managed brightons, fiber amplifiers, laser systems and optical communication links with distributed dispersion and nonlinearity management

Preface: International Reference Ionosphere - Progress in Ionospheric Modelling

Science.gov (United States)

Bilitza Dieter; Reinisch, Bodo

2010-01-01

The international reference ionosphere (lRI) is the internationally recommended empirical model for the specification of ionospheric parameters supported by the Committee on Space Research (COSPAR) and the International Union of Radio Science (URSI) and recognized by the International Standardization Organization (ISO). IRI is being continually improved by a team of international experts as new data become available and better models are being developed. This issue chronicles the latest phase of model updates as reported during two IRI-related meetings. The first was a special session during the Scientific Assembly of the Committee of Space Research (COSPAR) in Montreal, Canada in July 2008 and the second was an IRI Task Force Activity at the US Air Force Academy in Colorado Springs in May 2009. This work led to several improvements and additions of the model which will be included in the next version, IRI-201O. The issue is divided into three sections focusing on the improvements made in the topside ionosphere, the F-peak, and the lower ionosphere, respectively. This issue would not have been possible without the reviewing efforts of many individuals. Each paper was reviewed by two referees. We thankfully acknowledge the contribution to this issue made by the following reviewers: Jacob Adeniyi, David Altadill, Eduardo Araujo, Feza Arikan, Dieter Bilitza, Jilijana Cander, Bela Fejer, Tamara Gulyaeva, Manuel Hermindez-Pajares, Ivan Kutiev, John MacDougal, Leo McNamara, Bruno Nava, Olivier Obrou, Elijah Oyeyemi, Vadym Paznukhov, Bodo Reinisch, John Retterer, Phil Richards, Gary Sales, J.H. Sastri, Ludger Scherliess, Iwona Stanislavska, Stamir Stankov, Shin-Yi Su, Manlian Zhang, Y ongliang Zhang, and Irina Zakharenkova. We are grateful to Peggy Ann Shea for her final review and guidance as the editor-in-chief for special issues of Advances in Space Research. We thank the authors for their timely submission and their quick response to the reviewer comments and humbly

Internal Physical Features of a Land Surface Model Employing a Tangent Linear Model

Science.gov (United States)

Yang, Runhua; Cohn, Stephen E.; daSilva, Arlindo; Joiner, Joanna; Houser, Paul R.

1997-01-01

The Earth's land surface, including its biomass, is an integral part of the Earth's weather and climate system. Land surface heterogeneity, such as the type and amount of vegetative covering., has a profound effect on local weather variability and therefore on regional variations of the global climate. Surface conditions affect local weather and climate through a number of mechanisms. First, they determine the re-distribution of the net radiative energy received at the surface, through the atmosphere, from the sun. A certain fraction of this energy increases the surface ground temperature, another warms the near-surface atmosphere, and the rest evaporates surface water, which in turn creates clouds and causes precipitation. Second, they determine how much rainfall and snowmelt can be stored in the soil and how much instead runs off into waterways. Finally, surface conditions influence the near-surface concentration and distribution of greenhouse gases such as carbon dioxide. The processes through which these mechanisms interact with the atmosphere can be modeled mathematically, to within some degree of uncertainty, on the basis of underlying physical principles. Such a land surface model provides predictive capability for surface variables including ground temperature, surface humidity, and soil moisture and temperature. This information is important for agriculture and industry, as well as for addressing fundamental scientific questions concerning global and local climate change. In this study we apply a methodology known as tangent linear modeling to help us understand more deeply, the behavior of the Mosaic land surface model, a model that has been developed over the past several years at NASA/GSFC. This methodology allows us to examine, directly and quantitatively, the dependence of prediction errors in land surface variables upon different vegetation conditions. The work also highlights the importance of accurate soil moisture information. Although surface

Two-step variable selection in quantile regression models

Directory of Open Access Journals (Sweden)

FAN Yali

2015-06-01

Full Text Available We propose a two-step variable selection procedure for high dimensional quantile regressions, in which the dimension of the covariates, pn is much larger than the sample size n. In the first step, we perform ℓ1 penalty, and we demonstrate that the first step penalized estimator with the LASSO penalty can reduce the model from an ultra-high dimensional to a model whose size has the same order as that of the true model, and the selected model can cover the true model. The second step excludes the remained irrelevant covariates by applying the adaptive LASSO penalty to the reduced model obtained from the first step. Under some regularity conditions, we show that our procedure enjoys the model selection consistency. We conduct a simulation study and a real data analysis to evaluate the finite sample performance of the proposed approach.

Corporate strategy and the organizational structure of companies in international business

Directory of Open Access Journals (Sweden)

Aleksić Ana

2004-01-01

Full Text Available The aim of this paper is to illuminate the importance of corporate strategy and organizational structure as crucial variables for successful international business. We wanted to point out that companies, in order to exploit opportunities in international environment, must develop a high level of consent between the applied strategy and the model of organizational structure. Today all organizations, no matter how big they are, are affected by the international environment and its management must consider very carefully the benefits and costs of alternative strategies and the corresponding models of organizational structure.

Internal cycling, not external loading, decides the nutrient limitation in eutrophic lake: A dynamic model with temporal Bayesian hierarchical inference.

Science.gov (United States)

Wu, Zhen; Liu, Yong; Liang, Zhongyao; Wu, Sifeng; Guo, Huaicheng

2017-06-01

Lake eutrophication is associated with excessive anthropogenic nutrients (mainly nitrogen (N) and phosphorus (P)) and unobserved internal nutrient cycling. Despite the advances in understanding the role of external loadings, the contribution of internal nutrient cycling is still an open question. A dynamic mass-balance model was developed to simulate and measure the contributions of internal cycling and external loading. It was based on the temporal Bayesian Hierarchical Framework (BHM), where we explored the seasonal patterns in the dynamics of nutrient cycling processes and the limitation of N and P on phytoplankton growth in hyper-eutrophic Lake Dianchi, China. The dynamic patterns of the five state variables (Chla, TP, ammonia, nitrate and organic N) were simulated based on the model. Five parameters (algae growth rate, sediment exchange rate of N and P, nitrification rate and denitrification rate) were estimated based on BHM. The model provided a good fit to observations. Our model results highlighted the role of internal cycling of N and P in Lake Dianchi. The internal cycling processes contributed more than external loading to the N and P changes in the water column. Further insights into the nutrient limitation analysis indicated that the sediment exchange of P determined the P limitation. Allowing for the contribution of denitrification to N removal, N was the more limiting nutrient in most of the time, however, P was the more important nutrient for eutrophication management. For Lake Dianchi, it would not be possible to recover solely by reducing the external watershed nutrient load; the mechanisms of internal cycling should also be considered as an approach to inhibit the release of sediments and to enhance denitrification. Copyright © 2017 Elsevier Ltd. All rights reserved.

Environmental versus demographic variability in stochastic predator–prey models

International Nuclear Information System (INIS)

Dobramysl, U; Täuber, U C

2013-01-01

In contrast to the neutral population cycles of the deterministic mean-field Lotka–Volterra rate equations, including spatial structure and stochastic noise in models for predator–prey interactions yields complex spatio-temporal structures associated with long-lived erratic population oscillations. Environmental variability in the form of quenched spatial randomness in the predation rates results in more localized activity patches. Our previous study showed that population fluctuations in rare favorable regions in turn cause a remarkable increase in the asymptotic densities of both predators and prey. Very intriguing features are found when variable interaction rates are affixed to individual particles rather than lattice sites. Stochastic dynamics with demographic variability in conjunction with inheritable predation efficiencies generate non-trivial time evolution for the predation rate distributions, yet with overall essentially neutral optimization. (paper)

Assessing geotechnical centrifuge modelling in addressing variably saturated flow in soil and fractured rock.

Science.gov (United States)

Jones, Brendon R; Brouwers, Luke B; Van Tonder, Warren D; Dippenaar, Matthys A

2017-05-01

The vadose zone typically comprises soil underlain by fractured rock. Often, surface water and groundwater parameters are readily available, but variably saturated flow through soil and rock are oversimplified or estimated as input for hydrological models. In this paper, a series of geotechnical centrifuge experiments are conducted to contribute to the knowledge gaps in: (i) variably saturated flow and dispersion in soil and (ii) variably saturated flow in discrete vertical and horizontal fractures. Findings from the research show that the hydraulic gradient, and not the hydraulic conductivity, is scaled for seepage flow in the geotechnical centrifuge. Furthermore, geotechnical centrifuge modelling has been proven as a viable experimental tool for the modelling of hydrodynamic dispersion as well as the replication of similar flow mechanisms for unsaturated fracture flow, as previously observed in literature. Despite the imminent challenges of modelling variable saturation in the vadose zone, the geotechnical centrifuge offers a powerful experimental tool to physically model and observe variably saturated flow. This can be used to give valuable insight into mechanisms associated with solid-fluid interaction problems under these conditions. Findings from future research can be used to validate current numerical modelling techniques and address the subsequent influence on aquifer recharge and vulnerability, contaminant transport, waste disposal, dam construction, slope stability and seepage into subsurface excavations.

Importance analysis for models with correlated variables and its sparse grid solution

International Nuclear Information System (INIS)

Li, Luyi; Lu, Zhenzhou

2013-01-01

For structural models involving correlated input variables, a novel interpretation for variance-based importance measures is proposed based on the contribution of the correlated input variables to the variance of the model output. After the novel interpretation of the variance-based importance measures is compared with the existing ones, two solutions of the variance-based importance measures of the correlated input variables are built on the sparse grid numerical integration (SGI): double-loop nested sparse grid integration (DSGI) method and single loop sparse grid integration (SSGI) method. The DSGI method solves the importance measure by decreasing the dimensionality of the input variables procedurally, while SSGI method performs importance analysis through extending the dimensionality of the inputs. Both of them can make full use of the advantages of the SGI, and are well tailored for different situations. By analyzing the results of several numerical and engineering examples, it is found that the novel proposed interpretation about the importance measures of the correlated input variables is reasonable, and the proposed methods for solving importance measures are efficient and accurate. -- Highlights: •The contribution of correlated variables to the variance of the output is analyzed. •A novel interpretation for variance-based indices of correlated variables is proposed. •Two solutions for variance-based importance measures of correlated variables are built

Multiple Imputation of Predictor Variables Using Generalized Additive Models

NARCIS (Netherlands)

de Jong, Roel; van Buuren, Stef; Spiess, Martin

2016-01-01

The sensitivity of multiple imputation methods to deviations from their distributional assumptions is investigated using simulations, where the parameters of scientific interest are the coefficients of a linear regression model, and values in predictor variables are missing at random. The

An agent-based model of cellular dynamics and circadian variability in human endotoxemia.

Directory of Open Access Journals (Sweden)

Tung T Nguyen

Full Text Available As cellular variability and circadian rhythmicity play critical roles in immune and inflammatory responses, we present in this study an agent-based model of human endotoxemia to examine the interplay between circadian controls, cellular variability and stochastic dynamics of inflammatory cytokines. The model is qualitatively validated by its ability to reproduce circadian dynamics of inflammatory mediators and critical inflammatory responses after endotoxin administration in vivo. Novel computational concepts are proposed to characterize the cellular variability and synchronization of inflammatory cytokines in a population of heterogeneous leukocytes. Our results suggest that there is a decrease in cell-to-cell variability of inflammatory cytokines while their synchronization is increased after endotoxin challenge. Model parameters that are responsible for IκB production stimulated by NFκB activation and for the production of anti-inflammatory cytokines have large impacts on system behaviors. Additionally, examining time-dependent systemic responses revealed that the system is least vulnerable to endotoxin in the early morning and most vulnerable around midnight. Although much remains to be explored, proposed computational concepts and the model we have pioneered will provide important insights for future investigations and extensions, especially for single-cell studies to discover how cellular variability contributes to clinical implications.

On the Internal Model Principle in the Coordination of Nonlinear Systems

NARCIS (Netherlands)

De Persis, C.; Jayawardhana, B.

2014-01-01

The role of the internal model principle is investigated in this paper for the coordination of relative-degree-one and relative-degree-two nonlinear systems. For relative-degree-one systems that are incrementally (output-feedback) passive, we propose internal-model-based distributed control laws

Econometric modelling of international carbon tax regimes

International Nuclear Information System (INIS)