Normal and Special Models of Neutrino Masses and Mixings

CERN Document Server

Altarelli, Guido

2005-01-01

One can make a distinction between "normal" and "special" models. For normal models $\\theta_{23}$ is not too close to maximal and $\\theta_{13}$ is not too small, typically a small power of the self-suggesting order parameter $\\sqrt{r}$, with $r=\\Delta m_{sol}^2/\\Delta m_{atm}^2 \\sim 1/35$. Special models are those where some symmetry or dynamical feature assures in a natural way the near vanishing of $\\theta_{13}$ and/or of $\\theta_{23}- \\pi/4$. Normal models are conceptually more economical and much simpler to construct. Here we focus on special models, in particular a recent one based on A4 discrete symmetry and extra dimensions that leads in a natural way to a Harrison-Perkins-Scott mixing matrix.

A numerical insight into elastomer normally closed micro valve actuation with cohesive interfacial cracking modelling

Science.gov (United States)

Wang, Dongyang; Ba, Dechun; Hao, Ming; Duan, Qihui; Liu, Kun; Mei, Qi

2018-05-01

Pneumatic NC (normally closed) valves are widely used in high density microfluidics systems. To improve actuation reliability, the actuation pressure needs to be reduced. In this work, we utilize 3D FEM (finite element method) modelling to get an insight into the valve actuation process numerically. Specifically, the progressive debonding process at the elastomer interface is simulated with CZM (cohesive zone model) method. To minimize the actuation pressure, the V-shape design has been investigated and compared with a normal straight design. The geometrical effects of valve shape has been elaborated, in terms of valve actuation pressure. Based on our simulated results, we formulate the main concerns for micro valve design and fabrication, which is significant for minimizing actuation pressures and ensuring reliable operation.

Hydrodynamic Cucker-Smale model with normalized communication weights and time delay

KAUST Repository

Choi, Young-Pil

2017-07-17

We study a hydrodynamic Cucker-Smale-type model with time delay in communication and information processing, in which agents interact with each other through normalized communication weights. The model consists of a pressureless Euler system with time delayed non-local alignment forces. We resort to its Lagrangian formulation and prove the existence of its global in time classical solutions. Moreover, we derive a sufficient condition for the asymptotic flocking behavior of the solutions. Finally, we show the presence of a critical phenomenon for the Eulerian system posed in the spatially one-dimensional setting.

Modeling and simulation of normal and hemiparetic gait

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Luengas, Lely A.; Camargo, Esperanza; Sanchez, Giovanni

2015-09-01

Gait is the collective term for the two types of bipedal locomotion, walking and running. This paper is focused on walking. The analysis of human gait is of interest to many different disciplines, including biomechanics, human-movement science, rehabilitation and medicine in general. Here we present a new model that is capable of reproducing the properties of walking, normal and pathological. The aim of this paper is to establish the biomechanical principles that underlie human walking by using Lagrange method. The constraint forces of Rayleigh dissipation function, through which to consider the effect on the tissues in the gait, are included. Depending on the value of the factor present in the Rayleigh dissipation function, both normal and pathological gait can be simulated. First of all, we apply it in the normal gait and then in the permanent hemiparetic gait. Anthropometric data of adult person are used by simulation, and it is possible to use anthropometric data for children but is necessary to consider existing table of anthropometric data. Validation of these models includes simulations of passive dynamic gait that walk on level ground. The dynamic walking approach provides a new perspective of gait analysis, focusing on the kinematics and kinetics of gait. There have been studies and simulations to show normal human gait, but few of them have focused on abnormal, especially hemiparetic gait. Quantitative comparisons of the model predictions with gait measurements show that the model can reproduce the significant characteristics of normal gait.

Unit Root Testing and Estimation in Nonlinear ESTAR Models with Normal and Non-Normal Errors.

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Umair Khalil

Full Text Available Exponential Smooth Transition Autoregressive (ESTAR models can capture non-linear adjustment of the deviations from equilibrium conditions which may explain the economic behavior of many variables that appear non stationary from a linear viewpoint. Many researchers employ the Kapetanios test which has a unit root as the null and a stationary nonlinear model as the alternative. However this test statistics is based on the assumption of normally distributed errors in the DGP. Cook has analyzed the size of the nonlinear unit root of this test in the presence of heavy-tailed innovation process and obtained the critical values for both finite variance and infinite variance cases. However the test statistics of Cook are oversized. It has been found by researchers that using conventional tests is dangerous though the best performance among these is a HCCME. The over sizing for LM tests can be reduced by employing fixed design wild bootstrap remedies which provide a valuable alternative to the conventional tests. In this paper the size of the Kapetanios test statistic employing hetroscedastic consistent covariance matrices has been derived and the results are reported for various sample sizes in which size distortion is reduced. The properties for estimates of ESTAR models have been investigated when errors are assumed non-normal. We compare the results obtained through the fitting of nonlinear least square with that of the quantile regression fitting in the presence of outliers and the error distribution was considered to be from t-distribution for various sample sizes.

A neural network model of normal and abnormal auditory information processing.

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Du, X; Jansen, B H

2011-08-01

The ability of the brain to attenuate the response to irrelevant sensory stimulation is referred to as sensory gating. A gating deficiency has been reported in schizophrenia. To study the neural mechanisms underlying sensory gating, a neuroanatomically inspired model of auditory information processing has been developed. The mathematical model consists of lumped parameter modules representing the thalamus (TH), the thalamic reticular nucleus (TRN), auditory cortex (AC), and prefrontal cortex (PC). It was found that the membrane potential of the pyramidal cells in the PC module replicated auditory evoked potentials, recorded from the scalp of healthy individuals, in response to pure tones. Also, the model produced substantial attenuation of the response to the second of a pair of identical stimuli, just as seen in actual human experiments. We also tested the viewpoint that schizophrenia is associated with a deficit in prefrontal dopamine (DA) activity, which would lower the excitatory and inhibitory feedback gains in the AC and PC modules. Lowering these gains by less than 10% resulted in model behavior resembling the brain activity seen in schizophrenia patients, and replicated the reported gating deficits. The model suggests that the TRN plays a critical role in sensory gating, with the smaller response to a second tone arising from a reduction in inhibition of TH by the TRN. Copyright © 2011 Elsevier Ltd. All rights reserved.

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.

New Riemannian Priors on the Univariate Normal Model

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Salem Said

2014-07-01

Full Text Available The current paper introduces new prior distributions on the univariate normal model, with the aim of applying them to the classification of univariate normal populations. These new prior distributions are entirely based on the Riemannian geometry of the univariate normal model, so that they can be thought of as “Riemannian priors”. Precisely, if {pθ ; θ ∈ Θ} is any parametrization of the univariate normal model, the paper considers prior distributions G( θ - , γ with hyperparameters θ - ∈ Θ and γ > 0, whose density with respect to Riemannian volume is proportional to exp(−d2(θ, θ - /2γ2, where d2(θ, θ - is the square of Rao’s Riemannian distance. The distributions G( θ - , γ are termed Gaussian distributions on the univariate normal model. The motivation for considering a distribution G( θ - , γ is that this distribution gives a geometric representation of a class or cluster of univariate normal populations. Indeed, G( θ - , γ has a unique mode θ - (precisely, θ - is the unique Riemannian center of mass of G( θ - , γ, as shown in the paper, and its dispersion away from θ - is given by γ.  Therefore, one thinks of members of the class represented by G( θ - , γ as being centered around θ - and  lying within a typical  distance determined by γ. The paper defines rigorously the Gaussian distributions G( θ - , γ and describes an algorithm for computing maximum likelihood estimates of their hyperparameters. Based on this algorithm and on the Laplace approximation, it describes how the distributions G( θ - , γ can be used as prior distributions for Bayesian classification of large univariate normal populations. In a concrete application to texture image classification, it is shown that  this  leads  to  an  improvement  in  performance  over  the  use  of  conjugate  priors.

Process evaluation of discharge planning implementation in healthcare using normalization process theory.

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Nordmark, Sofi; Zingmark, Karin; Lindberg, Inger

2016-04-27

Discharge planning is a care process that aims to secure the transfer of care for the patient at transition from home to the hospital and back home. Information exchange and collaboration between care providers are essential, but deficits are common. A wide range of initiatives to improve the discharge planning process have been developed and implemented for the past three decades. However, there are still high rates of reported medical errors and adverse events related to failures in the discharge planning. Using theoretical frameworks such as Normalization Process Theory (NPT) can support evaluations of complex interventions and processes in healthcare. The aim of this study was to explore the embedding and integration of the DPP from the perspective of registered nurses, district nurses and homecare organizers. The study design was explorative, using the NPT as a framework to explore the embedding and integration of the DPP. Data consisted of written documentation from; workshops with staff, registered adverse events and system failures, web based survey and individual interviews with staff. Using the NPT as a framework to explore the embedding and integration of discharge planning after 10 years in use showed that the staff had reached a consensus of opinion of what the process was (coherence) and how they evaluated the process (reflexive monitoring). However, they had not reached a consensus of opinion of who performed the process (cognitive participation) and how it was performed (collective action). This could be interpreted as the process had not become normalized in daily practice. The result shows necessity to observe the implementation of old practices to better understand the needs of new ones before developing and implementing new practices or supportive tools within healthcare to reach the aim of development and to accomplish sustainable implementation. The NPT offers a generalizable framework for analysis, which can explain and shape the

Model-based normalization for iterative 3D PET image

International Nuclear Information System (INIS)

Bai, B.; Li, Q.; Asma, E.; Leahy, R.M.; Holdsworth, C.H.; Chatziioannou, A.; Tai, Y.C.

2002-01-01

We describe a method for normalization in 3D PET for use with maximum a posteriori (MAP) or other iterative model-based image reconstruction methods. This approach is an extension of previous factored normalization methods in which we include separate factors for detector sensitivity, geometric response, block effects and deadtime. Since our MAP reconstruction approach already models some of the geometric factors in the forward projection, the normalization factors must be modified to account only for effects not already included in the model. We describe a maximum likelihood approach to joint estimation of the count-rate independent normalization factors, which we apply to data from a uniform cylindrical source. We then compute block-wise and block-profile deadtime correction factors using singles and coincidence data, respectively, from a multiframe cylindrical source. We have applied this method for reconstruction of data from the Concorde microPET P4 scanner. Quantitative evaluation of this method using well-counter measurements of activity in a multicompartment phantom compares favourably with normalization based directly on cylindrical source measurements. (author)

A framework for analysis of abortive colony size distributions using a model of branching processes in irradiated normal human fibroblasts.

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Sakashita, Tetsuya; Hamada, Nobuyuki; Kawaguchi, Isao; Ouchi, Noriyuki B; Hara, Takamitsu; Kobayashi, Yasuhiko; Saito, Kimiaki

2013-01-01

Clonogenicity gives important information about the cellular reproductive potential following ionizing irradiation, but an abortive colony that fails to continue to grow remains poorly characterized. It was recently reported that the fraction of abortive colonies increases with increasing dose. Thus, we set out to investigate the production kinetics of abortive colonies using a model of branching processes. We firstly plotted the experimentally determined colony size distribution of abortive colonies in irradiated normal human fibroblasts, and found the linear relationship on the log-linear or log-log plot. By applying the simple model of branching processes to the linear relationship, we found the persistent reproductive cell death (RCD) over several generations following irradiation. To verify the estimated probability of RCD, abortive colony size distribution (≤ 15 cells) and the surviving fraction were simulated by the Monte Carlo computational approach for colony expansion. Parameters estimated from the log-log fit demonstrated the good performance in both simulations than those from the log-linear fit. Radiation-induced RCD, i.e. excess probability, lasted over 16 generations and mainly consisted of two components in the early (probability over 5 generations, whereas abortive colony size distribution was robust against it. These results suggest that, whereas short-term RCD is critical to the abortive colony size distribution, long-lasting RCD is important for the dose response of the surviving fraction. Our present model provides a single framework for understanding the behavior of primary cell colonies in culture following irradiation.

Software reliability growth models with normal failure time distributions

International Nuclear Information System (INIS)

Okamura, Hiroyuki; Dohi, Tadashi; Osaki, Shunji

2013-01-01

This paper proposes software reliability growth models (SRGM) where the software failure time follows a normal distribution. The proposed model is mathematically tractable and has sufficient ability of fitting to the software failure data. In particular, we consider the parameter estimation algorithm for the SRGM with normal distribution. The developed algorithm is based on an EM (expectation-maximization) algorithm and is quite simple for implementation as software application. Numerical experiment is devoted to investigating the fitting ability of the SRGMs with normal distribution through 16 types of failure time data collected in real software projects

American Option Pricing using GARCH models and the Normal Inverse Gaussian distribution

DEFF Research Database (Denmark)

Stentoft, Lars Peter

In this paper we propose a feasible way to price American options in a model with time varying volatility and conditional skewness and leptokurtosis using GARCH processes and the Normal Inverse Gaussian distribution. We show how the risk neutral dynamics can be obtained in this model, we interpret...... properties shows that there are important option pricing differences compared to the Gaussian case as well as to the symmetric special case. A large scale empirical examination shows that our model outperforms the Gaussian case for pricing options on three large US stocks as well as a major index...

A Box-Cox normal model for response times.

Science.gov (United States)

Klein Entink, R H; van der Linden, W J; Fox, J-P

2009-11-01

The log-transform has been a convenient choice in response time modelling on test items. However, motivated by a dataset of the Medical College Admission Test where the lognormal model violated the normality assumption, the possibilities of the broader class of Box-Cox transformations for response time modelling are investigated. After an introduction and an outline of a broader framework for analysing responses and response times simultaneously, the performance of a Box-Cox normal model for describing response times is investigated using simulation studies and a real data example. A transformation-invariant implementation of the deviance information criterium (DIC) is developed that allows for comparing model fit between models with different transformation parameters. Showing an enhanced description of the shape of the response time distributions, its application in an educational measurement context is discussed at length.

Normal tissue dose-effect models in biological dose optimisation

International Nuclear Information System (INIS)

Alber, M.

2008-01-01

Sophisticated radiotherapy techniques like intensity modulated radiotherapy with photons and protons rely on numerical dose optimisation. The evaluation of normal tissue dose distributions that deviate significantly from the common clinical routine and also the mathematical expression of desirable properties of a dose distribution is difficult. In essence, a dose evaluation model for normal tissues has to express the tissue specific volume effect. A formalism of local dose effect measures is presented, which can be applied to serial and parallel responding tissues as well as target volumes and physical dose penalties. These models allow a transparent description of the volume effect and an efficient control over the optimum dose distribution. They can be linked to normal tissue complication probability models and the equivalent uniform dose concept. In clinical applications, they provide a means to standardize normal tissue doses in the face of inevitable anatomical differences between patients and a vastly increased freedom to shape the dose, without being overly limiting like sets of dose-volume constraints. (orig.)

On a Robust MaxEnt Process Regression Model with Sample-Selection

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Hea-Jung Kim

2018-04-01

Full Text Available In a regression analysis, a sample-selection bias arises when a dependent variable is partially observed as a result of the sample selection. This study introduces a Maximum Entropy (MaxEnt process regression model that assumes a MaxEnt prior distribution for its nonparametric regression function and finds that the MaxEnt process regression model includes the well-known Gaussian process regression (GPR model as a special case. Then, this special MaxEnt process regression model, i.e., the GPR model, is generalized to obtain a robust sample-selection Gaussian process regression (RSGPR model that deals with non-normal data in the sample selection. Various properties of the RSGPR model are established, including the stochastic representation, distributional hierarchy, and magnitude of the sample-selection bias. These properties are used in the paper to develop a hierarchical Bayesian methodology to estimate the model. This involves a simple and computationally feasible Markov chain Monte Carlo algorithm that avoids analytical or numerical derivatives of the log-likelihood function of the model. The performance of the RSGPR model in terms of the sample-selection bias correction, robustness to non-normality, and prediction, is demonstrated through results in simulations that attest to its good finite-sample performance.

Hierarchical Multinomial Processing Tree Models: A Latent-Trait Approach

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Klauer, Karl Christoph

2010-01-01

Multinomial processing tree models are widely used in many areas of psychology. A hierarchical extension of the model class is proposed, using a multivariate normal distribution of person-level parameters with the mean and covariance matrix to be estimated from the data. The hierarchical model allows one to take variability between persons into…

Continuation-like semantics for modeling structural process anomalies

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Grewe Niels

2012-09-01

Full Text Available Abstract Background Biomedical ontologies usually encode knowledge that applies always or at least most of the time, that is in normal circumstances. But for some applications like phenotype ontologies it is becoming increasingly important to represent information about aberrations from a norm. These aberrations may be modifications of physiological structures, but also modifications of biological processes. Methods To facilitate precise definitions of process-related phenotypes, such as delayed eruption of the primary teeth or disrupted ocular pursuit movements, I introduce a modeling approach that draws inspiration from the use of continuations in the analysis of programming languages and apply a similar idea to ontological modeling. This approach characterises processes by describing their outcome up to a certain point and the way they will continue in the canonical case. Definitions of process types are then given in terms of their continuations and anomalous phenotypes are defined by their differences to the canonical definitions. Results The resulting model is capable of accurately representing structural process anomalies. It allows distinguishing between different anomaly kinds (delays, interruptions, gives identity criteria for interrupted processes, and explains why normal and anomalous process instances can be subsumed under a common type, thus establishing the connection between canonical and anomalous process-related phenotypes. Conclusion This paper shows how to to give semantically rich definitions of process-related phenotypes. These allow to expand the application areas of phenotype ontologies beyond literature annotation and establishment of genotype-phenotype associations to the detection of anomalies in suitably encoded datasets.

New component-based normalization method to correct PET system models

International Nuclear Information System (INIS)

Kinouchi, Shoko; Miyoshi, Yuji; Suga, Mikio; Yamaya, Taiga; Yoshida, Eiji; Nishikido, Fumihiko; Tashima, Hideaki

2011-01-01

Normalization correction is necessary to obtain high-quality reconstructed images in positron emission tomography (PET). There are two basic types of normalization methods: the direct method and component-based methods. The former method suffers from the problem that a huge count number in the blank scan data is required. Therefore, the latter methods have been proposed to obtain high statistical accuracy normalization coefficients with a small count number in the blank scan data. In iterative image reconstruction methods, on the other hand, the quality of the obtained reconstructed images depends on the system modeling accuracy. Therefore, the normalization weighing approach, in which normalization coefficients are directly applied to the system matrix instead of a sinogram, has been proposed. In this paper, we propose a new component-based normalization method to correct system model accuracy. In the proposed method, two components are defined and are calculated iteratively in such a way as to minimize errors of system modeling. To compare the proposed method and the direct method, we applied both methods to our small OpenPET prototype system. We achieved acceptable statistical accuracy of normalization coefficients while reducing the count number of the blank scan data to one-fortieth that required in the direct method. (author)

IMPROVING QUALITY OF STATISTICAL PROCESS CONTROL BY DEALING WITH NON‐NORMAL DATA IN AUTOMOTIVE INDUSTRY

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Zuzana ANDRÁSSYOVÁ

2012-07-01

Full Text Available Study deals with an analysis of data to the effect that it improves the quality of statistical tools in processes of assembly of automobile seats. Normal distribution of variables is one of inevitable conditions for the analysis, examination, and improvement of the manufacturing processes (f. e.: manufacturing process capability although, there are constantly more approaches to non‐normal data handling. An appropriate probability distribution of measured data is firstly tested by the goodness of fit of empirical distribution with theoretical normal distribution on the basis of hypothesis testing using programme StatGraphics Centurion XV.II. Data are collected from the assembly process of 1st row automobile seats for each characteristic of quality (Safety Regulation ‐S/R individually. Study closely processes the measured data of an airbag´s assembly and it aims to accomplish the normal distributed data and apply it the statistical process control. Results of the contribution conclude in a statement of rejection of the null hypothesis (measured variables do not follow the normal distribution therefore it is necessary to begin to work on data transformation supported by Minitab15. Even this approach does not reach a normal distributed data and so should be proposed a procedure that leads to the quality output of whole statistical control of manufacturing processes.

Parser Adaptation for Social Media by Integrating Normalization

NARCIS (Netherlands)

van der Goot, Rob; van Noord, Gerardus

This work explores normalization for parser adaptation. Traditionally, normalization is used as separate pre-processing step. We show that integrating the normalization model into the parsing algorithm is beneficial. This way, multiple normalization candidates can be leveraged, which improves

The Influence of Normalization Weight in Population Pharmacokinetic Covariate Models.

Science.gov (United States)

Goulooze, Sebastiaan C; Völler, Swantje; Välitalo, Pyry A J; Calvier, Elisa A M; Aarons, Leon; Krekels, Elke H J; Knibbe, Catherijne A J

2018-03-23

In covariate (sub)models of population pharmacokinetic models, most covariates are normalized to the median value; however, for body weight, normalization to 70 kg or 1 kg is often applied. In this article, we illustrate the impact of normalization weight on the precision of population clearance (CL pop ) parameter estimates. The influence of normalization weight (70, 1 kg or median weight) on the precision of the CL pop estimate, expressed as relative standard error (RSE), was illustrated using data from a pharmacokinetic study in neonates with a median weight of 2.7 kg. In addition, a simulation study was performed to show the impact of normalization to 70 kg in pharmacokinetic studies with paediatric or obese patients. The RSE of the CL pop parameter estimate in the neonatal dataset was lowest with normalization to median weight (8.1%), compared with normalization to 1 kg (10.5%) or 70 kg (48.8%). Typical clearance (CL) predictions were independent of the normalization weight used. Simulations showed that the increase in RSE of the CL pop estimate with 70 kg normalization was highest in studies with a narrow weight range and a geometric mean weight away from 70 kg. When, instead of normalizing with median weight, a weight outside the observed range is used, the RSE of the CL pop estimate will be inflated, and should therefore not be used for model selection. Instead, established mathematical principles can be used to calculate the RSE of the typical CL (CL TV ) at a relevant weight to evaluate the precision of CL predictions.

Advection-diffusion model for normal grain growth and the stagnation of normal grain growth in thin films

International Nuclear Information System (INIS)

Lou, C.

2002-01-01

An advection-diffusion model has been set up to describe normal grain growth. In this model grains are divided into different groups according to their topological classes (number of sides of a grain). Topological transformations are modelled by advective and diffusive flows governed by advective and diffusive coefficients respectively, which are assumed to be proportional to topological classes. The ordinary differential equations governing self-similar time-independent grain size distribution can be derived analytically from continuity equations. It is proved that the time-independent distributions obtained by solving the ordinary differential equations have the same form as the time-dependent distributions obtained by solving the continuity equations. The advection-diffusion model is extended to describe the stagnation of normal grain growth in thin films. Grain boundary grooving prevents grain boundaries from moving, and the correlation between neighbouring grains accelerates the stagnation of normal grain growth. After introducing grain boundary grooving and the correlation between neighbouring grains into the model, the grain size distribution is close to a lognormal distribution, which is usually found in experiments. A vertex computer simulation of normal grain growth has also been carried out to make a cross comparison with the advection-diffusion model. The result from the simulation did not verify the assumption that the advective and diffusive coefficients are proportional to topological classes. Instead, we have observed that topological transformations usually occur on certain topological classes. This suggests that the advection-diffusion model can be improved by making a more realistic assumption on topological transformations. (author)

Process modeling study of the CIF incinerator

International Nuclear Information System (INIS)

Hang, T.

1995-01-01

The Savannah River Site (SRS) plans to begin operating the Consolidated Incineration Facility (CIF) in 1996. The CIF will treat liquid and solid low-level radioactive, mixed and RCRA hazardous wastes generated at SRS. In addition to experimental test programs, process modeling was applied to provide guidance in areas of safety, environmental regulation compliances, process improvement and optimization. A steady-state flowsheet model was used to calculate material/energy balances and to track key chemical constituents throughout the process units. Dynamic models were developed to predict the CIF transient characteristics in normal and abnormal operation scenarios. Predictions include the rotary kiln heat transfer, dynamic responses of the CIF to fluctuations in the solid waste feed or upsets in the system equipments, performance of the control system, air inleakage in the kiln, etc. This paper reviews the modeling study performed to assist in the deflagration risk assessment

Mathematical model and computer code for coated particles performance at normal operating conditions

International Nuclear Information System (INIS)

Golubev, I.; Kadarmetov, I.; Makarov, V.

2002-01-01

Computer modeling of thermo-mechanical behavior of coated particles during operating both at normal and off-normal conditions has a very significant role particularly on a stage of new reactors development. In Russia a big experience has been accumulated on fabrication and reactor tests of CP and fuel elements with UO 2 kernels. However, this experience cannot be using in full volume for development of a new reactor installation GT-MHR. This is due to very deep burn-up of the fuel based on plutonium oxide (up to 70% fima). Therefore the mathematical modeling of CP thermal-mechanical behavior and failure prediction becomes particularly important. The authors have a clean understanding that serviceability of fuel with high burn-ups are defined not only by thermo-mechanics, but also by structured changes in coating materials, thermodynamics of chemical processes, 'amoeba-effect', formation CO etc. In the report the first steps of development of integrate code for numerical modeling of coated particles behavior and some calculating results concerning the influence of various design parameters on fuel coated particles endurance for GT-MHR normal operating conditions are submitted. A failure model is developed to predict the fraction of TRISO-coated particles. In this model it is assumed that the failure of CP depends not only on probability of SiC-layer fracture but also on the PyC-layers damage. The coated particle is considered as a uniform design. (author)

A Box-Cox normal model for response times

NARCIS (Netherlands)

Klein Entink, R.H.; Fox, J.P.; Linden, W.J. van der

2009-01-01

The log-transform has been a convenient choice in response time modelling on test items. However, motivated by a dataset of the Medical College Admission Test where the lognormal model violated the normality assumption, the possibilities of the broader class of Box–Cox transformations for response

The Model of the Production Process for the Quality Management

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Alot Zbigniew

2017-02-01

Full Text Available This article is a result of the research on the models of the production processes for the quality management and their identification. It discusses the classical model and the indicators for evaluating the capabilities by taking as its starting point the assumption of the normal distribution of the process characteristics. The division of the process types proposed by ISO 21747:2006 standard introducing models for non-stationary processes is presented. A general process model that allows in any real case to precisely describe the statistical characteristics of the process is proposed. It gives the opportunity for more detailed description, in comparison to the model proposed by ISO 21747:2006 standard, of the process characteristics and determining its capability. This model contains the type of process, statistical distribution, and the method for determining the capability and performance (long-term capability of the process. One of the model elements is proposed, own classification and resulting set of process types. The classification follows the recommendations of ISO 21747:2006 introducing models for the non-stationary processes. However, the set of the process types allows, beyond a more precise description of the process characteristics, its usage to monitor the process.

Modified Normal Demand Distributions in (R,S)-Inventory Models

NARCIS (Netherlands)

Strijbosch, L.W.G.; Moors, J.J.A.

2003-01-01

To model demand, the normal distribution is by far the most popular; the disadvantage that it takes negative values is taken for granted.This paper proposes two modi.cations of the normal distribution, both taking non-negative values only.Safety factors and order-up-to-levels for the familiar (R,

Comparing Sensory Information Processing and Alexithymia between People with Substance Dependency and Normal.

Science.gov (United States)

Bashapoor, Sajjad; Hosseini-Kiasari, Seyyedeh Tayebeh; Daneshvar, Somayeh; Kazemi-Taskooh, Zeinab

2015-01-01

Sensory information processing and alexithymia are two important factors in determining behavioral reactions. Some studies explain the effect of the sensitivity of sensory processing and alexithymia in the tendency to substance abuse. Giving that, the aim of the current study was to compare the styles of sensory information processing and alexithymia between substance-dependent people and normal ones. The research method was cross-sectional and the statistical population of the current study comprised of all substance-dependent men who are present in substance quitting camps of Masal, Iran, in October 2013 (n = 78). 36 persons were selected randomly by simple randomly sampling method from this population as the study group, and 36 persons were also selected among the normal population in the same way as the comparison group. Both groups was evaluated by using Toronto alexithymia scale (TAS) and adult sensory profile, and the multivariate analysis of variance (MANOVA) test was applied to analyze data. The results showed that there are significance differences between two groups in low registration (P processing and difficulty in describing emotions (P process sensory information in a different way than normal people and show more alexithymia features than them.

Process-oriented dose assessment model for 14C due to releases during normal operation of a nuclear power plant

International Nuclear Information System (INIS)

Aquilonius, Karin; Hallberg, Bengt

2005-01-01

Swedish nuclear utility companies are required to assess doses due to releases of radionuclides during normal operation. In 2001, calculation methods used earlier were updated due to new authority regulations. The isotope 14 C is of special interest in dose assessments due to the role of carbon in the metabolism of all life forms. Earlier, factors expressing the ratio between concentration of 14 C in air and in various plants were used. In order to extend the possibility to take local conditions into account, a process-oriented assessment model for uptake of carbon and doses from releases of 14 C to air was developed (POM 14 C). The model uses part of Daisy which has been developed to model the turnover of carbon in crops. [Hansen, S., Jensen, H.E., Nielsen, N.E., Svendsen, H., 1993. Description of the Soil Plant System Model DAISY, Basic Principles and Modelling Approach. Simulation Model for Transformation and Transport of Energy and Matter in the Soil Plant Atmosphere System. Jordbruksfoerlaget, The Royal Veterianary and Agricultural University, Copenhagen, Denmark]. The main objectives were to test model performance of the former method, and to investigate if taking site specific parameters into account to a greater degree would lead to major differences in the results. Several exposure pathways were considered: direct consumption of locally grown cereals, vegetables, and root vegetables, as well as consumption of milk and meat from cows having eaten fodder cereals and green fodder from the area around the nuclear plant. The total dose of the earlier model was compared with that of POM 14 C. The result of the former was shown to be slightly higher than the latter, but POM 14 C confirmed that the earlier results were of a reasonable magnitude. When full account of local conditions was taken, e.g. as regards solar radiation, temperature, and concentration of 14 C in air at various places in the surroundings of each nuclear plant, a difference in dose between

Schema Design and Normalization Algorithm for XML Databases Model

Directory of Open Access Journals (Sweden)

Samir Abou El-Seoud

2009-06-01

Full Text Available In this paper we study the problem of schema design and normalization in XML databases model. We show that, like relational databases, XML documents may contain redundant information, and this redundancy may cause update anomalies. Furthermore, such problems are caused by certain functional dependencies among paths in the document. Based on our research works, in which we presented the functional dependencies and normal forms of XML Schema, we present the decomposition algorithm for converting any XML Schema into normalized one, that satisfies X-BCNF.

Notes on power of normality tests of error terms in regression models

International Nuclear Information System (INIS)

Střelec, Luboš

2015-01-01

Normality is one of the basic assumptions in applying statistical procedures. For example in linear regression most of the inferential procedures are based on the assumption of normality, i.e. the disturbance vector is assumed to be normally distributed. Failure to assess non-normality of the error terms may lead to incorrect results of usual statistical inference techniques such as t-test or F-test. Thus, error terms should be normally distributed in order to allow us to make exact inferences. As a consequence, normally distributed stochastic errors are necessary in order to make a not misleading inferences which explains a necessity and importance of robust tests of normality. Therefore, the aim of this contribution is to discuss normality testing of error terms in regression models. In this contribution, we introduce the general RT class of robust tests for normality, and present and discuss the trade-off between power and robustness of selected classical and robust normality tests of error terms in regression models

Notes on power of normality tests of error terms in regression models

Energy Technology Data Exchange (ETDEWEB)

Střelec, Luboš [Department of Statistics and Operation Analysis, Faculty of Business and Economics, Mendel University in Brno, Zemědělská 1, Brno, 61300 (Czech Republic)

2015-03-10

Normality is one of the basic assumptions in applying statistical procedures. For example in linear regression most of the inferential procedures are based on the assumption of normality, i.e. the disturbance vector is assumed to be normally distributed. Failure to assess non-normality of the error terms may lead to incorrect results of usual statistical inference techniques such as t-test or F-test. Thus, error terms should be normally distributed in order to allow us to make exact inferences. As a consequence, normally distributed stochastic errors are necessary in order to make a not misleading inferences which explains a necessity and importance of robust tests of normality. Therefore, the aim of this contribution is to discuss normality testing of error terms in regression models. In this contribution, we introduce the general RT class of robust tests for normality, and present and discuss the trade-off between power and robustness of selected classical and robust normality tests of error terms in regression models.

Evaluation of Two Absolute Radiometric Normalization Algorithms for Pre-processing of Landsat Imagery

Institute of Scientific and Technical Information of China (English)

Xu Hanqiu

2006-01-01

In order to evaluate radiometric normalization techniques, two image normalization algorithms for absolute radiometric correction of Landsat imagery were quantitatively compared in this paper, which are the Illumination Correction Model proposed by Markham and Irish and the Illumination and Atmospheric Correction Model developed by the Remote Sensing and GIS Laboratory of the Utah State University. Relative noise, correlation coefficient and slope value were used as the criteria for the evaluation and comparison, which were derived from pseudo-invariant features identified from multitemtween the normalized multitemporal images were significantly reduced when the seasons of multitemporal images were different. However, there was no significant difference between the normalized and unnormalized images with a similar seasonal condition. Furthermore, the correction results of two algorithms are similar when the images are relatively clear with a uniform atmospheric condition. Therefore, the radiometric normalization procedures should be carried out if the multitemporal images have a significant seasonal difference.

Log-normal distribution from a process that is not multiplicative but is additive.

Science.gov (United States)

Mouri, Hideaki

2013-10-01

The central limit theorem ensures that a sum of random variables tends to a Gaussian distribution as their total number tends to infinity. However, for a class of positive random variables, we find that the sum tends faster to a log-normal distribution. Although the sum tends eventually to a Gaussian distribution, the distribution of the sum is always close to a log-normal distribution rather than to any Gaussian distribution if the summands are numerous enough. This is in contrast to the current consensus that any log-normal distribution is due to a product of random variables, i.e., a multiplicative process, or equivalently to nonlinearity of the system. In fact, the log-normal distribution is also observable for a sum, i.e., an additive process that is typical of linear systems. We show conditions for such a sum, an analytical example, and an application to random scalar fields such as those of turbulence.

Nonparametric Bayesian models through probit stick-breaking processes.

Science.gov (United States)

Rodríguez, Abel; Dunson, David B

2011-03-01

We describe a novel class of Bayesian nonparametric priors based on stick-breaking constructions where the weights of the process are constructed as probit transformations of normal random variables. We show that these priors are extremely flexible, allowing us to generate a great variety of models while preserving computational simplicity. Particular emphasis is placed on the construction of rich temporal and spatial processes, which are applied to two problems in finance and ecology.

Mathematical model of normal tissue injury in telegammatherapy

International Nuclear Information System (INIS)

Belov, S.A.; Lyass, F.M.; Mamin, R.G.; Minakova, E.I.; Raevskaya, S.A.

1983-01-01

A model of normal tissue injury as a result of exposure to ionizing radiation is based on an assumption that the degree of tissue injury is determined by the degree of destruction by certain critical cells. The dependence of the number of lethal injuriies on a single dose is expressed by a trinomial - linear and quadratic parts and a constant, obtained as a result of the processing of experimental data. Quantitative correlations have been obtained for the skin and brain. They have been tested using clinical and experimental material. The results of the testing point out to the absence of time dependence on a single up to 6-week irradiation cources. Correlation with an irradiation field has been obtained for the skin. A conclusion has been made that the concept of isoefficacy of irradiation cources is conditional. Spatial-time fractionation is a promising direction in the development of radiation therapy

Exponential model normalization for electrical capacitance tomography with external electrodes under gap permittivity conditions

International Nuclear Information System (INIS)

Baidillah, Marlin R; Takei, Masahiro

2017-01-01

A nonlinear normalization model which is called exponential model for electrical capacitance tomography (ECT) with external electrodes under gap permittivity conditions has been developed. The exponential model normalization is proposed based on the inherently nonlinear relationship characteristic between the mixture permittivity and the measured capacitance due to the gap permittivity of inner wall. The parameters of exponential equation are derived by using an exponential fitting curve based on the simulation and a scaling function is added to adjust the experiment system condition. The exponential model normalization was applied to two dimensional low and high contrast dielectric distribution phantoms by using simulation and experimental studies. The proposed normalization model has been compared with other normalization models i.e. Parallel, Series, Maxwell and Böttcher models. Based on the comparison of image reconstruction results, the exponential model is reliable to predict the nonlinear normalization of measured capacitance in term of low and high contrast dielectric distribution. (paper)

Sildenafil normalizes bowel transit in preclinical models of constipation.

Directory of Open Access Journals (Sweden)

Sarah K Sharman

Full Text Available Guanylyl cyclase-C (GC-C agonists increase cGMP levels in the intestinal epithelium to promote secretion. This process underlies the utility of exogenous GC-C agonists such as linaclotide for the treatment of chronic idiopathic constipation (CIC and irritable bowel syndrome with constipation (IBS-C. Because GC-C agonists have limited use in pediatric patients, there is a need for alternative cGMP-elevating agents that are effective in the intestine. The present study aimed to determine whether the PDE-5 inhibitor sildenafil has similar effects as linaclotide on preclinical models of constipation. Oral administration of sildenafil caused increased cGMP levels in mouse intestinal epithelium demonstrating that blocking cGMP-breakdown is an alternative approach to increase cGMP in the gut. Both linaclotide and sildenafil reduced proliferation and increased differentiation in colon mucosa, indicating common target pathways. The homeostatic effects of cGMP required gut turnover since maximal effects were observed after 3 days of treatment. Neither linaclotide nor sildenafil treatment affected intestinal transit or water content of fecal pellets in healthy mice. To test the effectiveness of cGMP elevation in a functional motility disorder model, mice were treated with dextran sulfate sodium (DSS to induce colitis and were allowed to recover for several weeks. The recovered animals exhibited slower transit, but increased fecal water content. An acute dose of sildenafil was able to normalize transit and fecal water content in the DSS-recovery animal model, and also in loperamide-induced constipation. The higher fecal water content in the recovered animals was due to a compromised epithelial barrier, which was normalized by sildenafil treatment. Taken together our results show that sildenafil can have similar effects as linaclotide on the intestine, and may have therapeutic benefit to patients with CIC, IBS-C, and post-infectious IBS.

Log-normal frailty models fitted as Poisson generalized linear mixed models.

Science.gov (United States)

Hirsch, Katharina; Wienke, Andreas; Kuss, Oliver

2016-12-01

The equivalence of a survival model with a piecewise constant baseline hazard function and a Poisson regression model has been known since decades. As shown in recent studies, this equivalence carries over to clustered survival data: A frailty model with a log-normal frailty term can be interpreted and estimated as a generalized linear mixed model with a binary response, a Poisson likelihood, and a specific offset. Proceeding this way, statistical theory and software for generalized linear mixed models are readily available for fitting frailty models. This gain in flexibility comes at the small price of (1) having to fix the number of pieces for the baseline hazard in advance and (2) having to "explode" the data set by the number of pieces. In this paper we extend the simulations of former studies by using a more realistic baseline hazard (Gompertz) and by comparing the model under consideration with competing models. Furthermore, the SAS macro %PCFrailty is introduced to apply the Poisson generalized linear mixed approach to frailty models. The simulations show good results for the shared frailty model. Our new %PCFrailty macro provides proper estimates, especially in case of 4 events per piece. The suggested Poisson generalized linear mixed approach for log-normal frailty models based on the %PCFrailty macro provides several advantages in the analysis of clustered survival data with respect to more flexible modelling of fixed and random effects, exact (in the sense of non-approximate) maximum likelihood estimation, and standard errors and different types of confidence intervals for all variance parameters. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Normal Brain-Skull Development with Hybrid Deformable VR Models Simulation.

Science.gov (United States)

Jin, Jing; De Ribaupierre, Sandrine; Eagleson, Roy

2016-01-01

This paper describes a simulation framework for a clinical application involving skull-brain co-development in infants, leading to a platform for craniosynostosis modeling. Craniosynostosis occurs when one or more sutures are fused early in life, resulting in an abnormal skull shape. Surgery is required to reopen the suture and reduce intracranial pressure, but is difficult without any predictive model to assist surgical planning. We aim to study normal brain-skull growth by computer simulation, which requires a head model and appropriate mathematical methods for brain and skull growth respectively. On the basis of our previous model, we further specified suture model into fibrous and cartilaginous sutures and develop algorithm for skull extension. We evaluate the resulting simulation by comparison with datasets of cases and normal growth.

Bayesian Option Pricing Using Mixed Normal Heteroskedasticity Models

DEFF Research Database (Denmark)

Rombouts, Jeroen V.K.; Stentoft, Lars Peter

While stochastic volatility models improve on the option pricing error when compared to the Black-Scholes-Merton model, mispricings remain. This paper uses mixed normal heteroskedasticity models to price options. Our model allows for significant negative skewness and time varying higher order...... moments of the risk neutral distribution. Parameter inference using Gibbs sampling is explained and we detail how to compute risk neutral predictive densities taking into account parameter uncertainty. When forecasting out-of-sample options on the S&P 500 index, substantial improvements are found compared...

Normalization and gene p-value estimation: issues in microarray data processing.

Science.gov (United States)

Fundel, Katrin; Küffner, Robert; Aigner, Thomas; Zimmer, Ralf

2008-05-28

Numerous methods exist for basic processing, e.g. normalization, of microarray gene expression data. These methods have an important effect on the final analysis outcome. Therefore, it is crucial to select methods appropriate for a given dataset in order to assure the validity and reliability of expression data analysis. Furthermore, biological interpretation requires expression values for genes, which are often represented by several spots or probe sets on a microarray. How to best integrate spot/probe set values into gene values has so far been a somewhat neglected problem. We present a case study comparing different between-array normalization methods with respect to the identification of differentially expressed genes. Our results show that it is feasible and necessary to use prior knowledge on gene expression measurements to select an adequate normalization method for the given data. Furthermore, we provide evidence that combining spot/probe set p-values into gene p-values for detecting differentially expressed genes has advantages compared to combining expression values for spots/probe sets into gene expression values. The comparison of different methods suggests to use Stouffer's method for this purpose. The study has been conducted on gene expression experiments investigating human joint cartilage samples of osteoarthritis related groups: a cDNA microarray (83 samples, four groups) and an Affymetrix (26 samples, two groups) data set. The apparently straight forward steps of gene expression data analysis, e.g. between-array normalization and detection of differentially regulated genes, can be accomplished by numerous different methods. We analyzed multiple methods and the possible effects and thereby demonstrate the importance of the single decisions taken during data processing. We give guidelines for evaluating normalization outcomes. An overview of these effects via appropriate measures and plots compared to prior knowledge is essential for the biological

A new normalization method based on electrical field lines for electrical capacitance tomography

International Nuclear Information System (INIS)

Zhang, L F; Wang, H X

2009-01-01

Electrical capacitance tomography (ECT) is considered to be one of the most promising process tomography techniques. The image reconstruction for ECT is an inverse problem to find the spatially distributed permittivities in a pipe. Usually, the capacitance measurements obtained from the ECT system are normalized at the high and low permittivity for image reconstruction. The parallel normalization model is commonly used during the normalization process, which assumes the distribution of materials in parallel. Thus, the normalized capacitance is a linear function of measured capacitance. A recently used model is a series normalization model which results in the normalized capacitance as a nonlinear function of measured capacitance. The newest presented model is based on electrical field centre lines (EFCL), and is a mixture of two normalization models. The multi-threshold method of this model is presented in this paper. The sensitivity matrices based on different normalization models were obtained, and image reconstruction was carried out accordingly. Simulation results indicate that reconstructed images with higher quality can be obtained based on the presented model

Target normal sheath acceleration analytical modeling, comparative study and developments

International Nuclear Information System (INIS)

Perego, C.; Batani, D.; Zani, A.; Passoni, M.

2012-01-01

Ultra-intense laser interaction with solid targets appears to be an extremely promising technique to accelerate ions up to several MeV, producing beams that exhibit interesting properties for many foreseen applications. Nowadays, most of all the published experimental results can be theoretically explained in the framework of the target normal sheath acceleration (TNSA) mechanism proposed by Wilks et al. [Phys. Plasmas 8(2), 542 (2001)]. As an alternative to numerical simulation various analytical or semi-analytical TNSA models have been published in the latest years, each of them trying to provide predictions for some of the ion beam features, given the initial laser and target parameters. However, the problem of developing a reliable model for the TNSA process is still open, which is why the purpose of this work is to enlighten the present situation of TNSA modeling and experimental results, by means of a quantitative comparison between measurements and theoretical predictions of the maximum ion energy. Moreover, in the light of such an analysis, some indications for the future development of the model proposed by Passoni and Lontano [Phys. Plasmas 13(4), 042102 (2006)] are then presented.

Statistical validation of normal tissue complication probability models

NARCIS (Netherlands)

Xu, Cheng-Jian; van der Schaaf, Arjen; van t Veld, Aart; Langendijk, Johannes A.; Schilstra, Cornelis

2012-01-01

PURPOSE: To investigate the applicability and value of double cross-validation and permutation tests as established statistical approaches in the validation of normal tissue complication probability (NTCP) models. METHODS AND MATERIALS: A penalized regression method, LASSO (least absolute shrinkage

Options and pitfalls of normal tissues complication probability models

International Nuclear Information System (INIS)

Dorr, Wolfgang

2011-01-01

Full text: Technological improvements in the physical administration of radiotherapy have led to increasing conformation of the treatment volume (TV) with the planning target volume (PTV) and of the irradiated volume (IV) with the TV. In this process of improvement of the physical quality of radiotherapy, the total volumes of organs at risk exposed to significant doses have significantly decreased, resulting in increased inhomogeneities in the dose distributions within these organs. This has resulted in a need to identify and quantify volume effects in different normal tissues. Today, irradiated volume today must be considered a 6t h 'R' of radiotherapy, in addition to the 5 'Rs' defined by Withers and Steel in the mid/end 1980 s. The current status of knowledge of these volume effects has recently been summarized for many organs and tissues by the QUANTEC (Quantitative Analysis of Normal Tissue Effects in the Clinic) initiative [Int. J. Radiat. Oncol. BioI. Phys. 76 (3) Suppl., 2010]. However, the concept of using dose-volume histogram parameters as a basis for dose constraints, even without applying any models for normal tissue complication probabilities (NTCP), is based on (some) assumptions that are not met in clinical routine treatment planning. First, and most important, dose-volume histogram (DVH) parameters are usually derived from a single, 'snap-shot' CT-scan, without considering physiological (urinary bladder, intestine) or radiation induced (edema, patient weight loss) changes during radiotherapy. Also, individual variations, or different institutional strategies of delineating organs at risk are rarely considered. Moreover, the reduction of the 3-dimentional dose distribution into a '2dimensl' DVH parameter implies that the localization of the dose within an organ is irrelevant-there are ample examples that this assumption is not justified. Routinely used dose constraints also do not take into account that the residual function of an organ may be

Generalization of the normal-exponential model: exploration of a more accurate parametrisation for the signal distribution on Illumina BeadArrays.

Science.gov (United States)

Plancade, Sandra; Rozenholc, Yves; Lund, Eiliv

2012-12-11

in terms of bias, but at the cost of a loss in precision. This paper addresses the lack of fit of the usual normal-exponential model by proposing a more flexible parametrisation of the signal distribution as well as the associated background correction. This new model proves to be considerably more accurate for Illumina microarrays, but the improvement in terms of modeling does not lead to a higher sensitivity in differential analysis. Nevertheless, this realistic modeling makes way for future investigations, in particular to examine the characteristics of pre-processing strategies.

Log-Normal Turbulence Dissipation in Global Ocean Models

Science.gov (United States)

Pearson, Brodie; Fox-Kemper, Baylor

2018-03-01

Data from turbulent numerical simulations of the global ocean demonstrate that the dissipation of kinetic energy obeys a nearly log-normal distribution even at large horizontal scales O (10 km ) . As the horizontal scales of resolved turbulence are larger than the ocean is deep, the Kolmogorov-Yaglom theory for intermittency in 3D homogeneous, isotropic turbulence cannot apply; instead, the down-scale potential enstrophy cascade of quasigeostrophic turbulence should. Yet, energy dissipation obeys approximate log-normality—robustly across depths, seasons, regions, and subgrid schemes. The distribution parameters, skewness and kurtosis, show small systematic departures from log-normality with depth and subgrid friction schemes. Log-normality suggests that a few high-dissipation locations dominate the integrated energy and enstrophy budgets, which should be taken into account when making inferences from simplified models and inferring global energy budgets from sparse observations.

Normalization of time-series satellite reflectance data to a standard sun-target-sensor geometry using a semi-empirical model

Science.gov (United States)

Zhao, Yongguang; Li, Chuanrong; Ma, Lingling; Tang, Lingli; Wang, Ning; Zhou, Chuncheng; Qian, Yonggang

2017-10-01

Time series of satellite reflectance data have been widely used to characterize environmental phenomena, describe trends in vegetation dynamics and study climate change. However, several sensors with wide spatial coverage and high observation frequency are usually designed to have large field of view (FOV), which cause variations in the sun-targetsensor geometry in time-series reflectance data. In this study, on the basis of semiempirical kernel-driven BRDF model, a new semi-empirical model was proposed to normalize the sun-target-sensor geometry of remote sensing image. To evaluate the proposed model, bidirectional reflectance under different canopy growth conditions simulated by Discrete Anisotropic Radiative Transfer (DART) model were used. The semi-empirical model was first fitted by using all simulated bidirectional reflectance. Experimental result showed a good fit between the bidirectional reflectance estimated by the proposed model and the simulated value. Then, MODIS time-series reflectance data was normalized to a common sun-target-sensor geometry by the proposed model. The experimental results showed the proposed model yielded good fits between the observed and estimated values. The noise-like fluctuations in time-series reflectance data was also reduced after the sun-target-sensor normalization process.

Mathematical model with autoregressive process for electrocardiogram signals

Science.gov (United States)

Evaristo, Ronaldo M.; Batista, Antonio M.; Viana, Ricardo L.; Iarosz, Kelly C.; Szezech, José D., Jr.; Godoy, Moacir F. de

2018-04-01

The cardiovascular system is composed of the heart, blood and blood vessels. Regarding the heart, cardiac conditions are determined by the electrocardiogram, that is a noninvasive medical procedure. In this work, we propose autoregressive process in a mathematical model based on coupled differential equations in order to obtain the tachograms and the electrocardiogram signals of young adults with normal heartbeats. Our results are compared with experimental tachogram by means of Poincaré plot and dentrended fluctuation analysis. We verify that the results from the model with autoregressive process show good agreement with experimental measures from tachogram generated by electrical activity of the heartbeat. With the tachogram we build the electrocardiogram by means of coupled differential equations.

Estimation of value at risk and conditional value at risk using normal mixture distributions model

Science.gov (United States)

Kamaruzzaman, Zetty Ain; Isa, Zaidi

2013-04-01

Normal mixture distributions model has been successfully applied in financial time series analysis. In this paper, we estimate the return distribution, value at risk (VaR) and conditional value at risk (CVaR) for monthly and weekly rates of returns for FTSE Bursa Malaysia Kuala Lumpur Composite Index (FBMKLCI) from July 1990 until July 2010 using the two component univariate normal mixture distributions model. First, we present the application of normal mixture distributions model in empirical finance where we fit our real data. Second, we present the application of normal mixture distributions model in risk analysis where we apply the normal mixture distributions model to evaluate the value at risk (VaR) and conditional value at risk (CVaR) with model validation for both risk measures. The empirical results provide evidence that using the two components normal mixture distributions model can fit the data well and can perform better in estimating value at risk (VaR) and conditional value at risk (CVaR) where it can capture the stylized facts of non-normality and leptokurtosis in returns distribution.

The Advanced Data Acquisition Model (ADAM: A Process Model for Digital Forensic Practice

Directory of Open Access Journals (Sweden)

Richard Brian Adams

2013-12-01

Full Text Available As with other types of evidence, the courts make no presumption that digital evidence is reliable without some evidence of empirical testing in relation to the theories and techniques associated with its production. The issue of reliability means that courts pay close attention to the manner in which electronic evidence has been obtained and in particular the process in which the data is captured and stored. Previous process models have tended to focus on one particular area of digital forensic practice, such as law enforcement, and have not incorporated a formal description. We contend that this approach has prevented the establishment of generally accepted standards and processes that are urgently needed in the domain of digital forensics. This paper presents a generic process model as a step towards developing such a generally-accepted standard for a fundamental digital forensic activity – the acquisition of digital evidence. Normal 0 false false false EN-AU X-NONE X-NONE /* Style Definitions */ table.MsoNormalTable {mso-style-name:"Table Normal"; mso-tstyle-rowband-size:0; mso-tstyle-colband-size:0; mso-style-noshow:yes; mso-style-priority:99; mso-style-parent:""; mso-padding-alt:0cm 5.4pt 0cm 5.4pt; mso-para-margin-top:0cm; mso-para-margin-right:0cm; mso-para-margin-bottom:12.0pt; mso-para-margin-left:0cm; text-indent:18.0pt; line-height:200%; mso-pagination:widow-orphan; font-size:11.0pt; font-family:"Calibri","sans-serif"; mso-ascii-font-family:Calibri; mso-ascii-theme-font:minor-latin; mso-hansi-font-family:Calibri; mso-hansi-theme-font:minor-latin; mso-ansi-language:EN-US; mso-fareast-language:EN-US; mso-bidi-language:EN-US;}

Presenting Thin Media Models Affects Women's Choice of Diet or Normal Snacks

Science.gov (United States)

Krahe, Barbara; Krause, Christina

2010-01-01

Our study explored the influence of thin- versus normal-size media models and of self-reported restrained eating behavior on women's observed snacking behavior. Fifty female undergraduates saw a set of advertisements for beauty products showing either thin or computer-altered normal-size female models, allegedly as part of a study on effective…

Predicting consonant recognition and confusions in normal-hearing listeners

DEFF Research Database (Denmark)

Zaar, Johannes; Dau, Torsten

2017-01-01

, Kollmeier, and Kohlrausch [(1997). J. Acoust. Soc. Am. 102, 2892–2905]. The model was evaluated based on the extensive consonant perception data set provided by Zaar and Dau [(2015). J. Acoust. Soc. Am. 138, 1253–1267], which was obtained with normal-hearing listeners using 15 consonant-vowel combinations...... confusion groups. The large predictive power of the proposed model suggests that adaptive processes in the auditory preprocessing in combination with a cross-correlation based template-matching back end can account for some of the processes underlying consonant perception in normal-hearing listeners....... The proposed model may provide a valuable framework, e.g., for investigating the effects of hearing impairment and hearing-aid signal processing on phoneme recognition....

Option Pricing with Asymmetric Heteroskedastic Normal Mixture Models

DEFF Research Database (Denmark)

Rombouts, Jeroen V.K.; Stentoft, Lars

This paper uses asymmetric heteroskedastic normal mixture models to fit return data and to price options. The models can be estimated straightforwardly by maximum likelihood, have high statistical fit when used on S&P 500 index return data, and allow for substantial negative skewness and time...... varying higher order moments of the risk neutral distribution. When forecasting out-of-sample a large set of index options between 1996 and 2009, substantial improvements are found compared to several benchmark models in terms of dollar losses and the ability to explain the smirk in implied volatilities...

One Dimension Analytical Model of Normal Ballistic Impact on Ceramic/Metal Gradient Armor

International Nuclear Information System (INIS)

Liu Lisheng; Zhang Qingjie; Zhai Pengcheng; Cao Dongfeng

2008-01-01

An analytical model of normal ballistic impact on the ceramic/metal gradient armor, which is based on modified Alekseevskii-Tate equations, has been developed. The process of gradient armour impacted by the long rod can be divided into four stages in this model. First stage is projectile's mass erosion or flowing phase, mushrooming phase and rigid phase; second one is the formation of comminuted ceramic conoid; third one is the penetration of gradient layer and last one is the penetration of metal back-up plate. The equations of third stage have been advanced by assuming the behavior of gradient layer as rigid-plastic and considering the effect of strain rate on the dynamic yield strength

One Dimension Analytical Model of Normal Ballistic Impact on Ceramic/Metal Gradient Armor

Science.gov (United States)

Liu, Lisheng; Zhang, Qingjie; Zhai, Pengcheng; Cao, Dongfeng

2008-02-01

An analytical model of normal ballistic impact on the ceramic/metal gradient armor, which is based on modified Alekseevskii-Tate equations, has been developed. The process of gradient armour impacted by the long rod can be divided into four stages in this model. First stage is projectile's mass erosion or flowing phase, mushrooming phase and rigid phase; second one is the formation of comminuted ceramic conoid; third one is the penetration of gradient layer and last one is the penetration of metal back-up plate. The equations of third stage have been advanced by assuming the behavior of gradient layer as rigid-plastic and considering the effect of strain rate on the dynamic yield strength.

Attention and normalization circuits in macaque V1

Science.gov (United States)

Sanayei, M; Herrero, J L; Distler, C; Thiele, A

2015-01-01

Attention affects neuronal processing and improves behavioural performance. In extrastriate visual cortex these effects have been explained by normalization models, which assume that attention influences the circuit that mediates surround suppression. While normalization models have been able to explain attentional effects, their validity has rarely been tested against alternative models. Here we investigate how attention and surround/mask stimuli affect neuronal firing rates and orientation tuning in macaque V1. Surround/mask stimuli provide an estimate to what extent V1 neurons are affected by normalization, which was compared against effects of spatial top down attention. For some attention/surround effect comparisons, the strength of attentional modulation was correlated with the strength of surround modulation, suggesting that attention and surround/mask stimulation (i.e. normalization) might use a common mechanism. To explore this in detail, we fitted multiplicative and additive models of attention to our data. In one class of models, attention contributed to normalization mechanisms, whereas in a different class of models it did not. Model selection based on Akaike's and on Bayesian information criteria demonstrated that in most cells the effects of attention were best described by models where attention did not contribute to normalization mechanisms. This demonstrates that attentional influences on neuronal responses in primary visual cortex often bypass normalization mechanisms. PMID:25757941

The gamma model : a new neural network for temporal processing

NARCIS (Netherlands)

Vries, de B.

1992-01-01

In this paper we develop the gamma neural model, a new neural net architecture for processing of temporal patterns. Time varying patterns are normally segmented into a sequence of static patterns that are successively presented to a neural net. In the approach presented here segmentation is avoided.

Perhitungan Iuran Normal Program Pensiun dengan Asumsi Suku Bunga Mengikuti Model Vasicek

Directory of Open Access Journals (Sweden)

I Nyoman Widana

2017-12-01

Full Text Available Labor has a very important role for national development. One way to optimize their productivity is to guarantee a certainty to earn income after retirement. Therefore the government and the private sector must have a program that can ensure the sustainability of this financial support. One option is a pension plan. The purpose of this study is to calculate the  normal cost  with the interest rate assumed to follow the Vasicek model and analyze the normal contribution of the pension program participants. Vasicek model is used to match with  the actual conditions. The method used in this research is the Projected Unit Credit Method and the Entry Age Normal method. The data source of this research is lecturers of FMIPA Unud. In addition, secondary data is also used in the form of the interest  rate of Bank Indonesia for the period of January 2006-December 2015. The results of this study indicate that  the older the age of the participants, when starting the pension program, the greater the first year normal cost  and the smaller the benefit which he or she  will get. Then, normal cost with constant interest rate  greater than normal cost with Vasicek interest rate. This occurs because the Vasicek model predicts interest between 4.8879%, up to 6.8384%. While constant interest is only 4.25%.  In addition, using normal cost that proportional to salary, it is found that the older the age of the participants the greater the proportion of the salary for normal cost.

Postmortem abdominal CT: Assessing normal cadaveric modifications and pathological processes

International Nuclear Information System (INIS)

Charlier, P.; Carlier, R.; Roffi, F.; Ezra, J.; Chaillot, P.F.; Duchat, F.; Huynh-Charlier, I.; Lorin de la Grandmaison, G.

2012-01-01

Purpose: To investigate the interest of postmortem non-enhanced computer tomography (CT) for abdominal lesions in a forensic context of suspicions death and to list the different radiological cadaveric modifications occurring normally at abdominal stage, which must be known by non forensic radiologists in case of any postmortem exam. Materials and methods: 30 cadavers have been submitted to a body CT-scan without injection of contrast material. CT exams were reviewed by two independent radiologists and radiological findings were compared with forensic autopsy data. Results: False positive CT findings included physiological postmortem transudates misdiagnosed with intra-abdominal bleedings, and putrefaction gas misdiagnosed with gas embolism, aeroporty, aerobily, digestive parietal pneumatosis. Incidentalomas without any role in death process were also reported. False negative CT findings included small contusions, vascular thromboses, acute infarcts foci, non radio-opaque foreign bodies. Normal cadaveric modifications were due to livor mortis and putrefaction, and are seen quickly (some hours) after death. Conclusion: The non forensic radiologist should be familiar with the normal abdominal postmortem features in order to avoid misdiagnoses, and detect informative lesions which can help and guide the forensic practitioner or the clinical physician.

Statistical validation of normal tissue complication probability models.

Science.gov (United States)

Xu, Cheng-Jian; van der Schaaf, Arjen; Van't Veld, Aart A; Langendijk, Johannes A; Schilstra, Cornelis

2012-09-01

To investigate the applicability and value of double cross-validation and permutation tests as established statistical approaches in the validation of normal tissue complication probability (NTCP) models. A penalized regression method, LASSO (least absolute shrinkage and selection operator), was used to build NTCP models for xerostomia after radiation therapy treatment of head-and-neck cancer. Model assessment was based on the likelihood function and the area under the receiver operating characteristic curve. Repeated double cross-validation showed the uncertainty and instability of the NTCP models and indicated that the statistical significance of model performance can be obtained by permutation testing. Repeated double cross-validation and permutation tests are recommended to validate NTCP models before clinical use. Copyright © 2012 Elsevier Inc. All rights reserved.

Statistical Validation of Normal Tissue Complication Probability Models

Energy Technology Data Exchange (ETDEWEB)

Xu Chengjian, E-mail: c.j.xu@umcg.nl [Department of Radiation Oncology, University of Groningen, University Medical Center Groningen, Groningen (Netherlands); Schaaf, Arjen van der; Veld, Aart A. van' t; Langendijk, Johannes A. [Department of Radiation Oncology, University of Groningen, University Medical Center Groningen, Groningen (Netherlands); Schilstra, Cornelis [Department of Radiation Oncology, University of Groningen, University Medical Center Groningen, Groningen (Netherlands); Radiotherapy Institute Friesland, Leeuwarden (Netherlands)

2012-09-01

Purpose: To investigate the applicability and value of double cross-validation and permutation tests as established statistical approaches in the validation of normal tissue complication probability (NTCP) models. Methods and Materials: A penalized regression method, LASSO (least absolute shrinkage and selection operator), was used to build NTCP models for xerostomia after radiation therapy treatment of head-and-neck cancer. Model assessment was based on the likelihood function and the area under the receiver operating characteristic curve. Results: Repeated double cross-validation showed the uncertainty and instability of the NTCP models and indicated that the statistical significance of model performance can be obtained by permutation testing. Conclusion: Repeated double cross-validation and permutation tests are recommended to validate NTCP models before clinical use.

Process modelling on a canonical basis[Process modelling; Canonical modelling

Energy Technology Data Exchange (ETDEWEB)

Siepmann, Volker

2006-12-20

Based on an equation oriented solving strategy, this thesis investigates a new approach to process modelling. Homogeneous thermodynamic state functions represent consistent mathematical models of thermodynamic properties. Such state functions of solely extensive canonical state variables are the basis of this work, as they are natural objective functions in optimisation nodes to calculate thermodynamic equilibrium regarding phase-interaction and chemical reactions. Analytical state function derivatives are utilised within the solution process as well as interpreted as physical properties. By this approach, only a limited range of imaginable process constraints are considered, namely linear balance equations of state variables. A second-order update of source contributions to these balance equations is obtained by an additional constitutive equation system. These equations are general dependent on state variables and first-order sensitivities, and cover therefore practically all potential process constraints. Symbolic computation technology efficiently provides sparsity and derivative information of active equations to avoid performance problems regarding robustness and computational effort. A benefit of detaching the constitutive equation system is that the structure of the main equation system remains unaffected by these constraints, and a priori information allows to implement an efficient solving strategy and a concise error diagnosis. A tailor-made linear algebra library handles the sparse recursive block structures efficiently. The optimisation principle for single modules of thermodynamic equilibrium is extended to host entire process models. State variables of different modules interact through balance equations, representing material flows from one module to the other. To account for reusability and encapsulation of process module details, modular process modelling is supported by a recursive module structure. The second-order solving algorithm makes it

Monte Carlo modeling of Standard Model multi-boson production processes for √s = 13 TeV ATLAS analyses

CERN Document Server

Li, Shu; The ATLAS collaboration

2017-01-01

We present the Monte Carlo(MC) setup used by ATLAS to model multi-boson processes in √s = 13 TeV proton-proton collisions. The baseline Monte Carlo generators are compared with each other in key kinematic distributions of the processes under study. Sample normalization and systematic uncertainties are discussed.

Bladder cancer mapping in Libya based on standardized morbidity ratio and log-normal model

Science.gov (United States)

Alhdiri, Maryam Ahmed; Samat, Nor Azah; Mohamed, Zulkifley

2017-05-01

Disease mapping contains a set of statistical techniques that detail maps of rates based on estimated mortality, morbidity, and prevalence. A traditional approach to measure the relative risk of the disease is called Standardized Morbidity Ratio (SMR). It is the ratio of an observed and expected number of accounts in an area, which has the greatest uncertainty if the disease is rare or if geographical area is small. Therefore, Bayesian models or statistical smoothing based on Log-normal model are introduced which might solve SMR problem. This study estimates the relative risk for bladder cancer incidence in Libya from 2006 to 2007 based on the SMR and log-normal model, which were fitted to data using WinBUGS software. This study starts with a brief review of these models, starting with the SMR method and followed by the log-normal model, which is then applied to bladder cancer incidence in Libya. All results are compared using maps and tables. The study concludes that the log-normal model gives better relative risk estimates compared to the classical method. The log-normal model has can overcome the SMR problem when there is no observed bladder cancer in an area.

Accident and Off-Normal Response and Recovery from Multi-Canister Overpack (MCO) Processing Events

International Nuclear Information System (INIS)

ALDERMAN, C.A.

2000-01-01

In the process of removing spent nuclear fuel (SNF) from the K Basins through its subsequent packaging, drymg, transportation and storage steps, the SNF Project must be able to respond to all anticipated or foreseeable off-normal and accident events that may occur. Response procedures and recovery plans need to be in place, personnel training established and implemented to ensure the project will be capable of appropriate actions. To establish suitable project planning, these events must first be identified and analyzed for their expected impact to the project. This document assesses all off-normal and accident events for their potential cross-facility or Multi-Canister Overpack (MCO) process reversal impact. Table 1 provides the methodology for establishing the event planning level and these events are provided in Table 2 along with the general response and recovery planning. Accidents and off-normal events of the SNF Project have been evaluated and are identified in the appropriate facility Safety Analysis Report (SAR) or in the transportation Safety Analysis Report for Packaging (SARP). Hazards and accidents are summarized from these safety analyses and listed in separate tables for each facility and the transportation system in Appendix A, along with identified off-normal events. The tables identify the general response time required to ensure a stable state after the event, governing response documents, and the events with potential cross-facility or SNF process reversal impacts. The event closure is predicated on stable state response time, impact to operations and the mitigated annual occurrence frequency of the event as developed in the hazard analysis process

Modelling growth curves of Nigerian indigenous normal feather ...

African Journals Online (AJOL)

This study was conducted to predict the growth curve parameters using Bayesian Gompertz and logistic models and also to compare the two growth function in describing the body weight changes across age in Nigerian indigenous normal feather chicken. Each chick was wing-tagged at day old and body weights were ...

Elevated intrabolus pressure identifies obstructive processes when integrated relaxation pressure is normal on esophageal high-resolution manometry.

Science.gov (United States)

Quader, Farhan; Reddy, Chanakyaram; Patel, Amit; Gyawali, C Prakash

2017-07-01

Elevated integrated relaxation pressure (IRP) on esophageal high-resolution manometry (HRM) identifies obstructive processes at the esophagogastric junction (EGJ). Our aim was to determine whether intrabolus pressure (IBP) can identify structural EGJ processes when IRP is normal. In this observational cohort study, adult patients with dysphagia and undergoing HRM were evaluated for endoscopic evidence of structural EGJ processes (strictures, rings, hiatus hernia) in the setting of normal IRP. HRM metrics [IRP, distal contractile integral (DCI), distal latency (DL), IBP, and EGJ contractile integral (EGJ-CI)] were compared among 74 patients with structural EGJ findings (62.8 ± 1.6 yr, 67.6% women), 27 patients with normal EGD (52.9 ± 3.2 yr, 70.3% women), and 21 healthy controls (27.6 ± 0.6 yr, 52.4% women). Findings were validated in 85 consecutive symptomatic patients to address clinical utility. In the primary cohort, mean IBP (18.4 ± 0.9 mmHg) was higher with structural EGJ findings compared with dysphagia with normal EGD (13.5 ± 1.1 mmHg, P = 0.002) and healthy controls (10.9 ± 0.9 mmHg, P 0.05 for each comparison). During multiple rapid swallows, IBP remained higher in the structural findings group compared with controls ( P = 0.02). Similar analysis of the prospective validation cohort confirmed IBP elevation in structural EGJ processes, but correlation with dysphagia could not be demonstrated. We conclude that elevated IBP predicts the presence of structural EGJ processes even when IRP is normal, but correlation with dysphagia is suboptimal. NEW & NOTEWORTHY Integrated relaxation pressure (IRP) above the upper limit of normal defines esophageal outflow obstruction using high-resolution manometry. In patients with normal IRP, elevated intrabolus pressure (IBP) can be a surrogate marker for a structural restrictive or obstructive process at the esophagogastric junction (EGJ). This has the potential to augment the clinical value of

Investigation of cold extrusion process using coupled thermo-mechanical FEM analysis and adaptive friction modeling

Science.gov (United States)

Görtan, Mehmet Okan

2017-10-01

Cold extrusion processes are known for their excellent material usage as well as high efficiency in the production of large batches. Although the process starts at room temperature, workpiece temperatures may rise above 200°C. Moreover, contact normal stresses can exceed 2500 MPa, whereas surface enlargement values can reach up to 30. These changes affects friction coefficients in cold extrusion processes. In the current study, friction coefficients between a plain carbon steel C4C (1.0303) and a tool steel (1.2379) are determined dependent on temperature and contact pressure using the sliding compression test (SCT). In order to represent contact normal stress and temperature effects on friction coefficients, an empirical adaptive friction model has been proposed. The validity of the model has been tested with experiments and finite element simulations for a cold forward extrusion process. By using the proposed adaptive friction model together with thermo-mechanical analysis, the deviation in the process loads between numerical simulations and model experiments could be reduced from 18.6% to 3.3%.

Mitochondrial base excision repair in mouse synaptosomes during normal aging and in a model of Alzheimer's disease

DEFF Research Database (Denmark)

Diaz, Ricardo Gredilla; Weissman, Lior; Yang, JL

2012-01-01

Brain aging is associated with synaptic decline and synaptic function is highly dependent on mitochondria. Increased levels of oxidative DNA base damage and accumulation of mitochondrial DNA (mtDNA) mutations or deletions lead to mitochondrial dysfunction, playing an important role in the aging...... process and the pathogenesis of several neurodegenerative diseases. Here we have investigated the repair of oxidative base damage, in synaptosomes of mouse brain during normal aging and in an AD model. During normal aging, a reduction in the base excision repair (BER) capacity was observed...... suggest that the age-related reduction in BER capacity in the synaptosomal fraction might contribute to mitochondrial and synaptic dysfunction during aging. The development of AD-like pathology in the 3xTgAD mouse model was, however, not associated with deficiencies of the BER mechanisms...

Attention and normalization circuits in macaque V1.

Science.gov (United States)

Sanayei, M; Herrero, J L; Distler, C; Thiele, A

2015-04-01

Attention affects neuronal processing and improves behavioural performance. In extrastriate visual cortex these effects have been explained by normalization models, which assume that attention influences the circuit that mediates surround suppression. While normalization models have been able to explain attentional effects, their validity has rarely been tested against alternative models. Here we investigate how attention and surround/mask stimuli affect neuronal firing rates and orientation tuning in macaque V1. Surround/mask stimuli provide an estimate to what extent V1 neurons are affected by normalization, which was compared against effects of spatial top down attention. For some attention/surround effect comparisons, the strength of attentional modulation was correlated with the strength of surround modulation, suggesting that attention and surround/mask stimulation (i.e. normalization) might use a common mechanism. To explore this in detail, we fitted multiplicative and additive models of attention to our data. In one class of models, attention contributed to normalization mechanisms, whereas in a different class of models it did not. Model selection based on Akaike's and on Bayesian information criteria demonstrated that in most cells the effects of attention were best described by models where attention did not contribute to normalization mechanisms. This demonstrates that attentional influences on neuronal responses in primary visual cortex often bypass normalization mechanisms. © 2015 The Authors. European Journal of Neuroscience published by Federation of European Neuroscience Societies and John Wiley & Sons Ltd.

Information Theory Analysis of Cascading Process in a Synthetic Model of Fluid Turbulence

Directory of Open Access Journals (Sweden)

Massimo Materassi

2014-02-01

Full Text Available The use of transfer entropy has proven to be helpful in detecting which is the verse of dynamical driving in the interaction of two processes, X and Y . In this paper, we present a different normalization for the transfer entropy, which is capable of better detecting the information transfer direction. This new normalized transfer entropy is applied to the detection of the verse of energy flux transfer in a synthetic model of fluid turbulence, namely the Gledzer–Ohkitana–Yamada shell model. Indeed, this is a fully well-known model able to model the fully developed turbulence in the Fourier space, which is characterized by an energy cascade towards the small scales (large wavenumbers k, so that the application of the information-theory analysis to its outcome tests the reliability of the analysis tool rather than exploring the model physics. As a result, the presence of a direct cascade along the scales in the shell model and the locality of the interactions in the space of wavenumbers come out as expected, indicating the validity of this data analysis tool. In this context, the use of a normalized version of transfer entropy, able to account for the difference of the intrinsic randomness of the interacting processes, appears to perform better, being able to discriminate the wrong conclusions to which the “traditional” transfer entropy would drive.

A GMM-Based Test for Normal Disturbances of the Heckman Sample Selection Model

Directory of Open Access Journals (Sweden)

Michael Pfaffermayr

2014-10-01

Full Text Available The Heckman sample selection model relies on the assumption of normal and homoskedastic disturbances. However, before considering more general, alternative semiparametric models that do not need the normality assumption, it seems useful to test this assumption. Following Meijer and Wansbeek (2007, the present contribution derives a GMM-based pseudo-score LM test on whether the third and fourth moments of the disturbances of the outcome equation of the Heckman model conform to those implied by the truncated normal distribution. The test is easy to calculate and in Monte Carlo simulations it shows good performance for sample sizes of 1000 or larger.

Reflectance spectrometry of normal and bruised human skins: experiments and modeling

International Nuclear Information System (INIS)

Kim, Oleg; Alber, Mark; McMurdy, John; Lines, Collin; Crawford, Gregory; Duffy, Susan

2012-01-01

A stochastic photon transport model in multilayer skin tissue combined with reflectance spectroscopy measurements is used to study normal and bruised skins. The model is shown to provide a very good approximation to both normal and bruised real skin tissues by comparing experimental and simulated reflectance spectra. The sensitivity analysis of the skin reflectance spectrum to variations of skin layer thicknesses, blood oxygenation parameter and concentrations of main chromophores is performed to optimize model parameters. The reflectance spectrum of a developed bruise in a healthy adult is simulated, and the concentrations of bilirubin, blood volume fraction and blood oxygenation parameter are determined for different times as the bruise progresses. It is shown that bilirubin and blood volume fraction reach their peak values at 80 and 55 h after contusion, respectively, and the oxygenation parameter is lower than its normal value during 80 h after contusion occurred. The obtained time correlations of chromophore concentrations in developing contusions are shown to be consistent with previous studies. The developed model uses a detailed seven-layer skin approximation for contusion and allows one to obtain more biologically relevant results than those obtained with previous models using one- to three-layer skin approximations. A combination of modeling with spectroscopy measurements provides a new tool for detailed biomedical studies of human skin tissue and for age determination of contusions. (paper)

Quasi-normal modes from non-commutative matrix dynamics

Science.gov (United States)

Aprile, Francesco; Sanfilippo, Francesco

2017-09-01

We explore similarities between the process of relaxation in the BMN matrix model and the physics of black holes in AdS/CFT. Focusing on Dyson-fluid solutions of the matrix model, we perform numerical simulations of the real time dynamics of the system. By quenching the equilibrium distribution we study quasi-normal oscillations of scalar single trace observables, we isolate the lowest quasi-normal mode, and we determine its frequencies as function of the energy. Considering the BMN matrix model as a truncation of N=4 SYM, we also compute the frequencies of the quasi-normal modes of the dual scalar fields in the AdS5-Schwarzschild background. We compare the results, and we finda surprising similarity.

Process for preparing a normal lighting and heating gas etc

Energy Technology Data Exchange (ETDEWEB)

Becker, J

1910-12-11

A process for preparing a normal lighting and heating gas from Australian bituminous shale by distillation and decomposition in the presence of water vapor is characterized by the fact that the gasification is suitably undertaken with gradual filling of a retort and with simultaneous introduction of water vapor at a temperature not exceeding 1,000/sup 0/ C. The resulting amount of gas is heated in the same or a second heated retort with freshly supplied vapor.

A heteroscedastic generalized linear model with a non-normal speed factor for responses and response times.

Science.gov (United States)

Molenaar, Dylan; Bolsinova, Maria

2017-05-01

In generalized linear modelling of responses and response times, the observed response time variables are commonly transformed to make their distribution approximately normal. A normal distribution for the transformed response times is desirable as it justifies the linearity and homoscedasticity assumptions in the underlying linear model. Past research has, however, shown that the transformed response times are not always normal. Models have been developed to accommodate this violation. In the present study, we propose a modelling approach for responses and response times to test and model non-normality in the transformed response times. Most importantly, we distinguish between non-normality due to heteroscedastic residual variances, and non-normality due to a skewed speed factor. In a simulation study, we establish parameter recovery and the power to separate both effects. In addition, we apply the model to a real data set. © 2017 The Authors. British Journal of Mathematical and Statistical Psychology published by John Wiley & Sons Ltd on behalf of British Psychological Society.

From explicit to implicit normal mode initialization of a limited-area model

Energy Technology Data Exchange (ETDEWEB)

Bijlsma, S.J.

2013-02-15

In this note the implicit normal mode initialization of a limited-area model is discussed from a different point of view. To that end it is shown that the equations describing the explicit normal mode initialization applied to the shallow water equations in differentiated form on the sphere can readily be derived in normal mode space if the model equations are separable, but only in the case of stationary Rossby modes can be transformed into the implicit equations in physical space. This is a consequence of the simple relations between the components of the different modes in that case. In addition a simple eigenvalue problem is given for the frequencies of the gravity waves. (orig.)

Deconstructing Interocular Suppression: Attention and Divisive Normalization.

Directory of Open Access Journals (Sweden)

Hsin-Hung Li

2015-10-01

Full Text Available In interocular suppression, a suprathreshold monocular target can be rendered invisible by a salient competitor stimulus presented in the other eye. Despite decades of research on interocular suppression and related phenomena (e.g., binocular rivalry, flash suppression, continuous flash suppression, the neural processing underlying interocular suppression is still unknown. We developed and tested a computational model of interocular suppression. The model included two processes that contributed to the strength of interocular suppression: divisive normalization and attentional modulation. According to the model, the salient competitor induced a stimulus-driven attentional modulation selective for the location and orientation of the competitor, thereby increasing the gain of neural responses to the competitor and reducing the gain of neural responses to the target. Additional suppression was induced by divisive normalization in the model, similar to other forms of visual masking. To test the model, we conducted psychophysics experiments in which both the size and the eye-of-origin of the competitor were manipulated. For small and medium competitors, behavioral performance was consonant with a change in the response gain of neurons that responded to the target. But large competitors induced a contrast-gain change, even when the competitor was split between the two eyes. The model correctly predicted these results and outperformed an alternative model in which the attentional modulation was eye specific. We conclude that both stimulus-driven attention (selective for location and feature and divisive normalization contribute to interocular suppression.

Deconstructing Interocular Suppression: Attention and Divisive Normalization.

Science.gov (United States)

Li, Hsin-Hung; Carrasco, Marisa; Heeger, David J

2015-10-01

In interocular suppression, a suprathreshold monocular target can be rendered invisible by a salient competitor stimulus presented in the other eye. Despite decades of research on interocular suppression and related phenomena (e.g., binocular rivalry, flash suppression, continuous flash suppression), the neural processing underlying interocular suppression is still unknown. We developed and tested a computational model of interocular suppression. The model included two processes that contributed to the strength of interocular suppression: divisive normalization and attentional modulation. According to the model, the salient competitor induced a stimulus-driven attentional modulation selective for the location and orientation of the competitor, thereby increasing the gain of neural responses to the competitor and reducing the gain of neural responses to the target. Additional suppression was induced by divisive normalization in the model, similar to other forms of visual masking. To test the model, we conducted psychophysics experiments in which both the size and the eye-of-origin of the competitor were manipulated. For small and medium competitors, behavioral performance was consonant with a change in the response gain of neurons that responded to the target. But large competitors induced a contrast-gain change, even when the competitor was split between the two eyes. The model correctly predicted these results and outperformed an alternative model in which the attentional modulation was eye specific. We conclude that both stimulus-driven attention (selective for location and feature) and divisive normalization contribute to interocular suppression.

Microscopic prediction of speech recognition for listeners with normal hearing in noise using an auditory model.

Science.gov (United States)

Jürgens, Tim; Brand, Thomas

2009-11-01

This study compares the phoneme recognition performance in speech-shaped noise of a microscopic model for speech recognition with the performance of normal-hearing listeners. "Microscopic" is defined in terms of this model twofold. First, the speech recognition rate is predicted on a phoneme-by-phoneme basis. Second, microscopic modeling means that the signal waveforms to be recognized are processed by mimicking elementary parts of human's auditory processing. The model is based on an approach by Holube and Kollmeier [J. Acoust. Soc. Am. 100, 1703-1716 (1996)] and consists of a psychoacoustically and physiologically motivated preprocessing and a simple dynamic-time-warp speech recognizer. The model is evaluated while presenting nonsense speech in a closed-set paradigm. Averaged phoneme recognition rates, specific phoneme recognition rates, and phoneme confusions are analyzed. The influence of different perceptual distance measures and of the model's a-priori knowledge is investigated. The results show that human performance can be predicted by this model using an optimal detector, i.e., identical speech waveforms for both training of the recognizer and testing. The best model performance is yielded by distance measures which focus mainly on small perceptual distances and neglect outliers.

Colorimetric determination of reducing normality in the Purex process

International Nuclear Information System (INIS)

Baumann, E.W.

1983-07-01

Adjustment of the valence state of plutonium from extractable Pu(IV) to nonextractable Pu(III) in the Purex process is accomplished by addition of reductants such as Fe(II), hydroxylamine nitrate (HAN), or U(IV). To implement on-line monitoring of this reduction step for improved process control at the Savannah River Plant, a simple colorimetric method for determining excess reductant (reducing normality) was developed. The method is based on formation of a colored complex of Fe(II) with FerroZine (Hach Chemical Company). The concentration of Fe(II) is determined directly. The concentration of HAN or U(IV), in addition to Fe(II), is determined indirectly as Fe(II), produced through reduction of Fe(III). Experimental conditions for a HAN-Fe(III) reaction of known stoichiometry were established. The effect of hydrazine, which stabilizes U(IV), was also determined. Real-time measurements of color development were made that simulated on-line performance. A laboratory analytical procedure is included. 5 references, 8 figures

A Dirichlet process mixture model for brain MRI tissue classification.

Science.gov (United States)

Ferreira da Silva, Adelino R

2007-04-01

Accurate classification of magnetic resonance images according to tissue type or region of interest has become a critical requirement in diagnosis, treatment planning, and cognitive neuroscience. Several authors have shown that finite mixture models give excellent results in the automated segmentation of MR images of the human normal brain. However, performance and robustness of finite mixture models deteriorate when the models have to deal with a variety of anatomical structures. In this paper, we propose a nonparametric Bayesian model for tissue classification of MR images of the brain. The model, known as Dirichlet process mixture model, uses Dirichlet process priors to overcome the limitations of current parametric finite mixture models. To validate the accuracy and robustness of our method we present the results of experiments carried out on simulated MR brain scans, as well as on real MR image data. The results are compared with similar results from other well-known MRI segmentation methods.

A speech processing study using an acoustic model of a multiple-channel cochlear implant

Science.gov (United States)

Xu, Ying

1998-10-01

A cochlear implant is an electronic device designed to provide sound information for adults and children who have bilateral profound hearing loss. The task of representing speech signals as electrical stimuli is central to the design and performance of cochlear implants. Studies have shown that the current speech- processing strategies provide significant benefits to cochlear implant users. However, the evaluation and development of speech-processing strategies have been complicated by hardware limitations and large variability in user performance. To alleviate these problems, an acoustic model of a cochlear implant with the SPEAK strategy is implemented in this study, in which a set of acoustic stimuli whose psychophysical characteristics are as close as possible to those produced by a cochlear implant are presented on normal-hearing subjects. To test the effectiveness and feasibility of this acoustic model, a psychophysical experiment was conducted to match the performance of a normal-hearing listener using model- processed signals to that of a cochlear implant user. Good agreement was found between an implanted patient and an age-matched normal-hearing subject in a dynamic signal discrimination experiment, indicating that this acoustic model is a reasonably good approximation of a cochlear implant with the SPEAK strategy. The acoustic model was then used to examine the potential of the SPEAK strategy in terms of its temporal and frequency encoding of speech. It was hypothesized that better temporal and frequency encoding of speech can be accomplished by higher stimulation rates and a larger number of activated channels. Vowel and consonant recognition tests were conducted on normal-hearing subjects using speech tokens processed by the acoustic model, with different combinations of stimulation rate and number of activated channels. The results showed that vowel recognition was best at 600 pps and 8 activated channels, but further increases in stimulation rate and

Developing Visualization Support System for Teaching/Learning Database Normalization

Science.gov (United States)

Folorunso, Olusegun; Akinwale, AdioTaofeek

2010-01-01

Purpose: In tertiary institution, some students find it hard to learn database design theory, in particular, database normalization. The purpose of this paper is to develop a visualization tool to give students an interactive hands-on experience in database normalization process. Design/methodology/approach: The model-view-controller architecture…

Aggregate and Individual Replication Probability within an Explicit Model of the Research Process

Science.gov (United States)

Miller, Jeff; Schwarz, Wolf

2011-01-01

We study a model of the research process in which the true effect size, the replication jitter due to changes in experimental procedure, and the statistical error of effect size measurement are all normally distributed random variables. Within this model, we analyze the probability of successfully replicating an initial experimental result by…

Modeling styles in business process modeling

NARCIS (Netherlands)

Pinggera, J.; Soffer, P.; Zugal, S.; Weber, B.; Weidlich, M.; Fahland, D.; Reijers, H.A.; Mendling, J.; Bider, I.; Halpin, T.; Krogstie, J.; Nurcan, S.; Proper, E.; Schmidt, R.; Soffer, P.; Wrycza, S.

2012-01-01

Research on quality issues of business process models has recently begun to explore the process of creating process models. As a consequence, the question arises whether different ways of creating process models exist. In this vein, we observed 115 students engaged in the act of modeling, recording

Dynamic divisive normalization predicts time-varying value coding in decision-related circuits.

Science.gov (United States)

Louie, Kenway; LoFaro, Thomas; Webb, Ryan; Glimcher, Paul W

2014-11-26

Normalization is a widespread neural computation, mediating divisive gain control in sensory processing and implementing a context-dependent value code in decision-related frontal and parietal cortices. Although decision-making is a dynamic process with complex temporal characteristics, most models of normalization are time-independent and little is known about the dynamic interaction of normalization and choice. Here, we show that a simple differential equation model of normalization explains the characteristic phasic-sustained pattern of cortical decision activity and predicts specific normalization dynamics: value coding during initial transients, time-varying value modulation, and delayed onset of contextual information. Empirically, we observe these predicted dynamics in saccade-related neurons in monkey lateral intraparietal cortex. Furthermore, such models naturally incorporate a time-weighted average of past activity, implementing an intrinsic reference-dependence in value coding. These results suggest that a single network mechanism can explain both transient and sustained decision activity, emphasizing the importance of a dynamic view of normalization in neural coding. Copyright © 2014 the authors 0270-6474/14/3416046-12$15.00/0.

Computer modeling the boron compound factor in normal brain tissue

International Nuclear Information System (INIS)

Gavin, P.R.; Huiskamp, R.; Wheeler, F.J.; Griebenow, M.L.

1993-01-01

The macroscopic distribution of borocaptate sodium (Na 2 B 12 H 11 SH or BSH) in normal tissues has been determined and can be accurately predicted from the blood concentration. The compound para-borono-phenylalanine (p-BPA) has also been studied in dogs and normal tissue distribution has been determined. The total physical dose required to reach a biological isoeffect appears to increase directly as the proportion of boron capture dose increases. This effect, together with knowledge of the macrodistribution, led to estimates of the influence of the microdistribution of the BSH compound. This paper reports a computer model that was used to predict the compound factor for BSH and p-BPA and, hence, the equivalent radiation in normal tissues. The compound factor would need to be calculated for other compounds with different distributions. This information is needed to design appropriate normal tissue tolerance studies for different organ systems and/or different boron compounds

Currents, HF Radio-derived, Monterey Bay, Normal Model, Zonal, EXPERIMENTAL

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — The data is the zonal component of ocean surface currents derived from High Frequency Radio-derived measurements, with missing values filled in by a normal model....

Estimating structural equation models with non-normal variables by using transformations

NARCIS (Netherlands)

Montfort, van K.; Mooijaart, A.; Meijerink, F.

2009-01-01

We discuss structural equation models for non-normal variables. In this situation the maximum likelihood and the generalized least-squares estimates of the model parameters can give incorrect estimates of the standard errors and the associated goodness-of-fit chi-squared statistics. If the sample

Process modeling style

CERN Document Server

Long, John

2014-01-01

Process Modeling Style focuses on other aspects of process modeling beyond notation that are very important to practitioners. Many people who model processes focus on the specific notation used to create their drawings. While that is important, there are many other aspects to modeling, such as naming, creating identifiers, descriptions, interfaces, patterns, and creating useful process documentation. Experience author John Long focuses on those non-notational aspects of modeling, which practitioners will find invaluable. Gives solid advice for creating roles, work produ

Modeling operators' emergency response time for chemical processing operations.

Science.gov (United States)

Murray, Susan L; Harputlu, Emrah; Mentzer, Ray A; Mannan, M Sam

2014-01-01

Operators have a crucial role during emergencies at a variety of facilities such as chemical processing plants. When an abnormality occurs in the production process, the operator often has limited time to either take corrective actions or evacuate before the situation becomes deadly. It is crucial that system designers and safety professionals can estimate the time required for a response before procedures and facilities are designed and operations are initiated. There are existing industrial engineering techniques to establish time standards for tasks performed at a normal working pace. However, it is reasonable to expect the time required to take action in emergency situations will be different than working at a normal production pace. It is possible that in an emergency, operators will act faster compared to a normal pace. It would be useful for system designers to be able to establish a time range for operators' response times for emergency situations. This article develops a modeling approach to estimate the time standard range for operators taking corrective actions or following evacuation procedures in emergency situations. This will aid engineers and managers in establishing time requirements for operators in emergency situations. The methodology used for this study combines a well-established industrial engineering technique for determining time requirements (predetermined time standard system) and adjustment coefficients for emergency situations developed by the authors. Numerous videos of workers performing well-established tasks at a maximum pace were studied. As an example, one of the tasks analyzed was pit crew workers changing tires as quickly as they could during a race. The operations in these videos were decomposed into basic, fundamental motions (such as walking, reaching for a tool, and bending over) by studying the videos frame by frame. A comparison analysis was then performed between the emergency pace and the normal working pace operations

Challenges in clinical natural language processing for automated disorder normalization.

Science.gov (United States)

Leaman, Robert; Khare, Ritu; Lu, Zhiyong

2015-10-01

to be frequent causes of error, in addition to the mentions the annotators were not able to identify within the scope of the controlled vocabulary. Disorder mentions in text from clinical narratives use a rich vocabulary that results in high term variation, which we believe to be one of the primary causes of reduced performance in clinical narrative. We show that pairwise learning to rank offers high performance in this context, and introduce several lexical enhancements - generalizable to other clinical NER tasks - that improve the ability of the NER system to handle this variation. DNorm-C is a high performing, open source system for disorders in clinical text, and a promising step toward NER and normalization methods that are trainable to a wide variety of domains and entities. (DNorm-C is open source software, and is available with a trained model at the DNorm demonstration website: http://www.ncbi.nlm.nih.gov/CBBresearch/Lu/Demo/tmTools/#DNorm.). Published by Elsevier Inc.

Researches Concerning to Minimize Vibrations when Processing Normal Lathe

Directory of Open Access Journals (Sweden)

Lenuța Cîndea

2015-09-01

Full Text Available In the cutting process, vibration is inevitable appearance, and in situations where the amplitude exceeds the limits of precision dimensional and shape of the surfaces generated vibrator phenomenon is detrimental.Field vibration is an issue of increasingly developed, so the futures will a better understanding of them and their use even in other sectors.The paper developed experimental measurement of vibrations at the lathe machining normal. The scheme described kinematical machine tool, cutting tool, cutting conditions, presenting experimental facility for measuring vibration occurring at turning. Experimental results have followed measurement of amplitude, which occurs during interior turning the knife without silencer incorporated. The tests were performed continuously for different speed, feed and depth of cut.

Continuum modeling of ion-beam eroded surfaces under normal incidence: Impact of stochastic fluctuations

International Nuclear Information System (INIS)

Dreimann, Karsten; Linz, Stefan J.

2010-01-01

Graphical abstract: Deterministic surface pattern (left) and its stochastic counterpart (right) arising in a stochastic damped Kuramoto-Sivashinsky equation that serves as a model equation for ion-beam eroded surfaces and is systematically investigated. - Abstract: Using a recently proposed field equation for the surface evolution of ion-beam eroded semiconductor target materials under normal incidence, we systematically explore the impact of additive stochastic fluctuations that are permanently present during the erosion process. Specifically, we investigate the dependence of the surface roughness, the underlying pattern forming properties and the bifurcation behavior on the strength of the fluctuations.

Modulation of the inter-hemispheric processing of semantic information during normal aging. A divided visual field experiment.

Science.gov (United States)

Hoyau, E; Cousin, E; Jaillard, A; Baciu, M

2016-12-01

We evaluated the effect of normal aging on the inter-hemispheric processing of semantic information by using the divided visual field (DVF) method, with words and pictures. Two main theoretical models have been considered, (a) the HAROLD model which posits that aging is associated with supplementary recruitment of the right hemisphere (RH) and decreased hemispheric specialization, and (b) the RH decline theory, which assumes that the RH becomes less efficient with aging, associated with increased LH specialization. Two groups of subjects were examined, a Young Group (YG) and an Old Group (OG), while participants performed a semantic categorization task (living vs. non-living) in words and pictures. The DVF was realized in two steps: (a) unilateral DVF presentation with stimuli presented separately in each visual field, left or right, allowing for their initial processing by only one hemisphere, right or left, respectively; (b) bilateral DVF presentation (BVF) with stimuli presented simultaneously in both visual fields, followed by their processing by both hemispheres. These two types of presentation permitted the evaluation of two main characteristics of the inter-hemispheric processing of information, the hemispheric specialization (HS) and the inter-hemispheric cooperation (IHC). Moreover, the BVF allowed determining the driver-hemisphere for processing information presented in BVF. Results obtained in OG indicated that: (a) semantic categorization was performed as accurately as YG, even if more slowly, (b) a non-semantic RH decline was observed, and (c) the LH controls the semantic processing during the BVF, suggesting an increased role of the LH in aging. However, despite the stronger involvement of the LH in OG, the RH is not completely devoid of semantic abilities. As discussed in the paper, neither the HAROLD nor the RH decline does fully explain this pattern of results. We rather suggest that the effect of aging on the hemispheric specialization and inter

Condition monitoring with wind turbine SCADA data using Neuro-Fuzzy normal behavior models

DEFF Research Database (Denmark)

Schlechtingen, Meik; Santos, Ilmar

2012-01-01

System (ANFIS) models are employed to learn the normal behavior in a training phase, where the component condition can be considered healthy. In the application phase the trained models are applied to predict the target signals, e.g. temperatures, pressures, currents, power output, etc. The behavior......This paper presents the latest research results of a project that focuses on normal behavior models for condition monitoring of wind turbines and their components, via ordinary Supervisory Control And Data Acquisition (SCADA) data. In this machine learning approach Adaptive Neuro-Fuzzy Interference...... of the prediction error is used as an indicator for normal and abnormal behavior, with respect to the learned behavior. The advantage of this approach is that the prediction error is widely decoupled from the typical fluctuations of the SCADA data caused by the different turbine operational modes. To classify...

Normality of raw data in general linear models: The most widespread myth in statistics

Science.gov (United States)

Kery, Marc; Hatfield, Jeff S.

2003-01-01

In years of statistical consulting for ecologists and wildlife biologists, by far the most common misconception we have come across has been the one about normality in general linear models. These comprise a very large part of the statistical models used in ecology and include t tests, simple and multiple linear regression, polynomial regression, and analysis of variance (ANOVA) and covariance (ANCOVA). There is a widely held belief that the normality assumption pertains to the raw data rather than to the model residuals. We suspect that this error may also occur in countless published studies, whenever the normality assumption is tested prior to analysis. This may lead to the use of nonparametric alternatives (if there are any), when parametric tests would indeed be appropriate, or to use of transformations of raw data, which may introduce hidden assumptions such as multiplicative effects on the natural scale in the case of log-transformed data. Our aim here is to dispel this myth. We very briefly describe relevant theory for two cases of general linear models to show that the residuals need to be normally distributed if tests requiring normality are to be used, such as t and F tests. We then give two examples demonstrating that the distribution of the response variable may be nonnormal, and yet the residuals are well behaved. We do not go into the issue of how to test normality; instead we display the distributions of response variables and residuals graphically.

An Integrated Numerical Model of the Spray Forming Process

DEFF Research Database (Denmark)

Pryds, Nini; Hattel, Jesper; Pedersen, Trine Bjerre

2002-01-01

of the deposition model is accomplished using a 2D cylindrical heat flow model. This model is now coupled with an atomization model via a log-normal droplet size distribution. The coupling between the atomization and the deposition is accomplished by ensuring that the total droplet size distribution of the spray......In this paper, an integrated approach for modelling the entire spray forming process is presented. The basis for the analysis is a recently developed model which extents previous studies and includes the interaction between an array of droplets and the enveloping gas. The formulation...... is in fact the summation of 'local' droplet size distributions along the r-axis. A key parameter, which determines the yield and the shape of the deposit material, is the sticking efficiency. The sticking phenomenon is therefore incorporated into the deposition model. (C) 2002 Acta Materialia Inc. Published...

Mathematical modeling of a convective textile drying process

Directory of Open Access Journals (Sweden)

G. Johann

2014-12-01

Full Text Available This study aims to develop a model that accurately represents the convective drying process of textile materials. The mathematical modeling was developed from energy and mass balances and, for the solution of the mathematical model, the technique of finite differences, in Cartesian coordinates, was used. It transforms the system of partial differential equations into a system of ordinary equations, with the unknowns, the temperature and humidity of both the air and the textile material. The simulation results were compared with experimental data obtained from the literature. In the statistical analysis the Shapiro-Wilk test was used to validate the model and, in all cases simulated, the results were p-values greater than 5 %, indicating normality of the data. The R-squared values were above 0.997 and the ratios Fcalculated/Fsimulated, at the 95 % confidence level, higher than five, indicating that the modeling was predictive in all simulations.

Transforming Collaborative Process Models into Interface Process Models by Applying an MDA Approach

Science.gov (United States)

Lazarte, Ivanna M.; Chiotti, Omar; Villarreal, Pablo D.

Collaborative business models among enterprises require defining collaborative business processes. Enterprises implement B2B collaborations to execute these processes. In B2B collaborations the integration and interoperability of processes and systems of the enterprises are required to support the execution of collaborative processes. From a collaborative process model, which describes the global view of the enterprise interactions, each enterprise must define the interface process that represents the role it performs in the collaborative process in order to implement the process in a Business Process Management System. Hence, in this work we propose a method for the automatic generation of the interface process model of each enterprise from a collaborative process model. This method is based on a Model-Driven Architecture to transform collaborative process models into interface process models. By applying this method, interface processes are guaranteed to be interoperable and defined according to a collaborative process.

Modeling auditory processing and speech perception in hearing-impaired listeners

DEFF Research Database (Denmark)

Jepsen, Morten Løve

in a diagnostic rhyme test. The framework was constructed such that discrimination errors originating from the front-end and the back-end were separated. The front-end was fitted to individual listeners with cochlear hearing loss according to non-speech data, and speech data were obtained in the same listeners......A better understanding of how the human auditory system represents and analyzes sounds and how hearing impairment affects such processing is of great interest for researchers in the fields of auditory neuroscience, audiology, and speech communication as well as for applications in hearing......-instrument and speech technology. In this thesis, the primary focus was on the development and evaluation of a computational model of human auditory signal-processing and perception. The model was initially designed to simulate the normal-hearing auditory system with particular focus on the nonlinear processing...

Numerical modeling of optical coherent transient processes with complex configurations-III: Noisy laser source

International Nuclear Information System (INIS)

Chang Tiejun; Tian Mingzhen

2007-01-01

A previously developed numerical model based on Maxwell-Bloch equations was modified to simulate optical coherent transient and spectral hole burning processes with noisy laser sources. Random walk phase noise was simulated using laser-phase sequences generated numerically according to the normal distribution of the phase shift. The noise model was tested by comparing the simulated spectral hole burning effect with the analytical solution. The noise effects on a few typical optical coherence transient processes were investigated using this numerical tool. Flicker and random walk frequency noises were considered in accumulation process

Applying normalization process theory to understand implementation of a family violence screening and care model in maternal and child health nursing practice: a mixed method process evaluation of a randomised controlled trial.

Science.gov (United States)

Hooker, Leesa; Small, Rhonda; Humphreys, Cathy; Hegarty, Kelsey; Taft, Angela

2015-03-28

In Victoria, Australia, Maternal and Child Health (MCH) services deliver primary health care to families with children 0-6 years, focusing on health promotion, parenting support and early intervention. Family violence (FV) has been identified as a major public health concern, with increased prevalence in the child-bearing years. Victorian Government policy recommends routine FV screening of all women attending MCH services. Using Normalization Process Theory (NPT), we aimed to understand the barriers and facilitators of implementing an enhanced screening model into MCH nurse clinical practice. NPT informed the process evaluation of a pragmatic, cluster randomised controlled trial in eight MCH nurse teams in metropolitan Melbourne, Victoria, Australia. Using mixed methods (surveys and interviews), we explored the views of MCH nurses, MCH nurse team leaders, FV liaison workers and FV managers on implementation of the model. Quantitative data were analysed by comparing proportionate group differences and change within trial arm over time between interim and impact nurse surveys. Qualitative data were inductively coded, thematically analysed and mapped to NPT constructs (coherence, cognitive participation, collective action and reflexive monitoring) to enhance our understanding of the outcome evaluation. MCH nurse participation rates for interim and impact surveys were 79% (127/160) and 71% (114/160), respectively. Twenty-three key stakeholder interviews were completed. FV screening work was meaningful and valued by participants; however, the implementation coincided with a significant (government directed) change in clinical practice which impacted on full engagement with the model (coherence and cognitive participation). The use of MCH nurse-designed FV screening/management tools in focussed women's health consultations and links with FV services enhanced the participants' work (collective action). Monitoring of FV work (reflexive monitoring) was limited. The use of

Interpretation of metabolic memory phenomenon using a physiological systems model: What drives oxidative stress following glucose normalization?

Science.gov (United States)

Voronova, Veronika; Zhudenkov, Kirill; Helmlinger, Gabriel; Peskov, Kirill

2017-01-01

Hyperglycemia is generally associated with oxidative stress, which plays a key role in diabetes-related complications. A complex, quantitative relationship has been established between glucose levels and oxidative stress, both in vitro and in vivo. For example, oxidative stress is known to persist after glucose normalization, a phenomenon described as metabolic memory. Also, uncontrolled glucose levels appear to be more detrimental to patients with diabetes (non-constant glucose levels) vs. patients with high, constant glucose levels. The objective of the current study was to delineate the mechanisms underlying such behaviors, using a mechanistic physiological systems modeling approach that captures and integrates essential underlying pathophysiological processes. The proposed model was based on a system of ordinary differential equations. It describes the interplay between reactive oxygen species production potential (ROS), ROS-induced cell alterations, and subsequent adaptation mechanisms. Model parameters were calibrated using different sources of experimental information, including ROS production in cell cultures exposed to various concentration profiles of constant and oscillating glucose levels. The model adequately reproduced the ROS excess generation after glucose normalization. Such behavior appeared to be driven by positive feedback regulations between ROS and ROS-induced cell alterations. The further oxidative stress-related detrimental effect as induced by unstable glucose levels can be explained by inability of cells to adapt to dynamic environment. Cell adaptation to instable high glucose declines during glucose normalization phases, and further glucose increase promotes similar or higher oxidative stress. In contrast, gradual ROS production potential decrease, driven by adaptation, is observed in cells exposed to constant high glucose.

An inexact log-normal distribution-based stochastic chance-constrained model for agricultural water quality management

Science.gov (United States)

Wang, Yu; Fan, Jie; Xu, Ye; Sun, Wei; Chen, Dong

2018-05-01

In this study, an inexact log-normal-based stochastic chance-constrained programming model was developed for solving the non-point source pollution issues caused by agricultural activities. Compared to the general stochastic chance-constrained programming model, the main advantage of the proposed model is that it allows random variables to be expressed as a log-normal distribution, rather than a general normal distribution. Possible deviations in solutions caused by irrational parameter assumptions were avoided. The agricultural system management in the Erhai Lake watershed was used as a case study, where critical system factors, including rainfall and runoff amounts, show characteristics of a log-normal distribution. Several interval solutions were obtained under different constraint-satisfaction levels, which were useful in evaluating the trade-off between system economy and reliability. The applied results show that the proposed model could help decision makers to design optimal production patterns under complex uncertainties. The successful application of this model is expected to provide a good example for agricultural management in many other watersheds.

Overcoming the Problem of Embedding Change in Educational Organizations: A Perspective from Normalization Process Theory

Science.gov (United States)

Wood, Phil

2017-01-01

In this article, I begin by outlining some of the barriers which constrain sustainable organizational change in schools and universities. I then go on to introduce a theory which has already started to help explain complex change and innovation processes in health and care contexts, Normalization Process Theory. Finally, I consider what this…

What work has to be done to implement collaborative care for depression? Process evaluation of a trial utilizing the Normalization Process Model

Directory of Open Access Journals (Sweden)

Lankshear Annette J

2010-02-01

Full Text Available Abstract Background There is a considerable evidence base for 'collaborative care' as a method to improve quality of care for depression, but an acknowledged gap between efficacy and implementation. This study utilises the Normalisation Process Model (NPM to inform the process of implementation of collaborative care in both a future full-scale trial, and the wider health economy. Methods Application of the NPM to qualitative data collected in both focus groups and one-to-one interviews before and after an exploratory randomised controlled trial of a collaborative model of care for depression. Results Findings are presented as they relate to the four factors of the NPM (interactional workability, relational integration, skill-set workability, and contextual integration and a number of necessary tasks are identified. Using the model, it was possible to observe that predictions about necessary work to implement collaborative care that could be made from analysis of the pre-trial data relating to the four different factors of the NPM were indeed borne out in the post-trial data. However, additional insights were gained from the post-trial interview participants who, unlike those interviewed before the trial, had direct experience of a novel intervention. The professional freedom enjoyed by more senior mental health workers may work both for and against normalisation of collaborative care as those who wish to adopt new ways of working have the freedom to change their practice but are not obliged to do so. Conclusions The NPM provides a useful structure for both guiding and analysing the process by which an intervention is optimized for testing in a larger scale trial or for subsequent full-scale implementation.

What work has to be done to implement collaborative care for depression? Process evaluation of a trial utilizing the Normalization Process Model.

Science.gov (United States)

Gask, Linda; Bower, Peter; Lovell, Karina; Escott, Diane; Archer, Janine; Gilbody, Simon; Lankshear, Annette J; Simpson, Angela E; Richards, David A

2010-02-10

There is a considerable evidence base for 'collaborative care' as a method to improve quality of care for depression, but an acknowledged gap between efficacy and implementation. This study utilises the Normalisation Process Model (NPM) to inform the process of implementation of collaborative care in both a future full-scale trial, and the wider health economy. Application of the NPM to qualitative data collected in both focus groups and one-to-one interviews before and after an exploratory randomised controlled trial of a collaborative model of care for depression. Findings are presented as they relate to the four factors of the NPM (interactional workability, relational integration, skill-set workability, and contextual integration) and a number of necessary tasks are identified. Using the model, it was possible to observe that predictions about necessary work to implement collaborative care that could be made from analysis of the pre-trial data relating to the four different factors of the NPM were indeed borne out in the post-trial data. However, additional insights were gained from the post-trial interview participants who, unlike those interviewed before the trial, had direct experience of a novel intervention. The professional freedom enjoyed by more senior mental health workers may work both for and against normalisation of collaborative care as those who wish to adopt new ways of working have the freedom to change their practice but are not obliged to do so. The NPM provides a useful structure for both guiding and analysing the process by which an intervention is optimized for testing in a larger scale trial or for subsequent full-scale implementation.

Verbal Processing Reaction Times in "Normal" and "Poor" Readers.

Science.gov (United States)

Culbertson, Jack; And Others

After it had been determined that reaction time (RT) was a sensitive measure of hemispheric dominance in a verbal task performed by normal adult readers, the reaction times of three groups of subjects (20 normal reading college students, 12 normal reading third graders and 11 poor reading grade school students) were compared. Ss were exposed to…

Toward a normalized clinical drug knowledge base in China-applying the RxNorm model to Chinese clinical drugs.

Science.gov (United States)

Wang, Li; Zhang, Yaoyun; Jiang, Min; Wang, Jingqi; Dong, Jiancheng; Liu, Yun; Tao, Cui; Jiang, Guoqian; Zhou, Yi; Xu, Hua

2018-04-04

In recent years, electronic health record systems have been widely implemented in China, making clinical data available electronically. However, little effort has been devoted to making drug information exchangeable among these systems. This study aimed to build a Normalized Chinese Clinical Drug (NCCD) knowledge base, by applying and extending the information model of RxNorm to Chinese clinical drugs. Chinese drugs were collected from 4 major resources-China Food and Drug Administration, China Health Insurance Systems, Hospital Pharmacy Systems, and China Pharmacopoeia-for integration and normalization in NCCD. Chemical drugs were normalized using the information model in RxNorm without much change. Chinese patent drugs (i.e., Chinese herbal extracts), however, were represented using an expanded RxNorm model to incorporate the unique characteristics of these drugs. A hybrid approach combining automated natural language processing technologies and manual review by domain experts was then applied to drug attribute extraction, normalization, and further generation of drug names at different specification levels. Lastly, we reported the statistics of NCCD, as well as the evaluation results using several sets of randomly selected Chinese drugs. The current version of NCCD contains 16 976 chemical drugs and 2663 Chinese patent medicines, resulting in 19 639 clinical drugs, 250 267 unique concepts, and 2 602 760 relations. By manual review of 1700 chemical drugs and 250 Chinese patent drugs randomly selected from NCCD (about 10%), we showed that the hybrid approach could achieve an accuracy of 98.60% for drug name extraction and normalization. Using a collection of 500 chemical drugs and 500 Chinese patent drugs from other resources, we showed that NCCD achieved coverages of 97.0% and 90.0% for chemical drugs and Chinese patent drugs, respectively. Evaluation results demonstrated the potential to improve interoperability across various electronic drug systems

Testing the normality assumption in the sample selection model with an application to travel demand

NARCIS (Netherlands)

van der Klaauw, B.; Koning, R.H.

2003-01-01

In this article we introduce a test for the normality assumption in the sample selection model. The test is based on a flexible parametric specification of the density function of the error terms in the model. This specification follows a Hermite series with bivariate normality as a special case.

Testing the normality assumption in the sample selection model with an application to travel demand

NARCIS (Netherlands)

van der Klauw, B.; Koning, R.H.

In this article we introduce a test for the normality assumption in the sample selection model. The test is based on a flexible parametric specification of the density function of the error terms in the model. This specification follows a Hermite series with bivariate normality as a special case.

Normal and Abnormal Scenario Modeling with GoldSim for Radioactive Waste Disposal System

International Nuclear Information System (INIS)

Lee, Youn Myoung; Jeong, Jong Tae

2010-08-01

A modeling study and development of a total system performance assessment (TSPA) template program, by which an assessment of safety and performance for the radioactive waste repository with normal and/or abnormal nuclide release cases could be assessed has been carried out by utilizing a commercial development tool program, GoldSim. Scenarios associated with the various FEPs and involved in the performance of the proposed repository in view of nuclide transport and transfer both in the geosphere and biosphere has been also carried out. Selected normal and abnormal scenarios that could alter groundwater flow scheme and then nuclide transport are modeled with the template program. To this end in-depth system models for the normal and abnormal well and earthquake scenarios that are conceptually and rather practically described and then ready for implementing into a GoldSim TSPA template program are introduced with conceptual schemes for each repository system. Illustrative evaluations with data currently available are also shown

Normal processes of phonon-phonon scattering and thermal conductivity of germanium crystals with isotopic disorder

CERN Document Server

Kuleev, I G

2001-01-01

The effect of normal processes of the phonon-phonon scattering on the thermal conductivity of the germanium crystals with various isotopic disorder degrees is considered. The phonon pulse redistribution in the normal scattering processes both inside each oscillatory branch (the Simons mechanism) and between various phonon oscillatory branches (the Herring mechanism) is accounted for. The contributions of the longitudinal and cross-sectional phonons drift motion into the thermal conductivity are analyzed. It is shown that the pulse redistribution in the Herring relaxation mechanism leads to essential suppression of the longitudinal phonons drift motion in the isotopically pure germanium crystals. The calculations results of thermal conductivity for the Herring relaxation mechanism agree well with experimental data on the germanium crystals with various isotopic disorder degrees

Fuzzy Pruning Based LS-SVM Modeling Development for a Fermentation Process

Directory of Open Access Journals (Sweden)

Weili Xiong

2014-01-01

Full Text Available Due to the complexity and uncertainty of microbial fermentation processes, data coming from the plants often contain some outliers. However, these data may be treated as the normal support vectors, which always deteriorate the performance of soft sensor modeling. Since the outliers also contaminate the correlation structure of the least square support vector machine (LS-SVM, the fuzzy pruning method is provided to deal with the problem. Furthermore, by assigning different fuzzy membership scores to data samples, the sensitivity of the model to the outliers can be reduced greatly. The effectiveness and efficiency of the proposed approach are demonstrated through two numerical examples as well as a simulator case of penicillin fermentation process.

Working Memory Processing In Normal Subjects and Subjects with Dyslexia

Science.gov (United States)

Bowyer, S. M.; Lajiness-O'Neill, R.; Weiland, B. J.; Mason, K.; Tepley, N.

2004-10-01

Magnetoencephalography (MEG) was used to determine the neuroanatomical location of working memory (WM) processes. Differences between subjects with dyslexia (SD; n=5) and normal readers (NR; n=5) were studied during two WM tasks. A spatial WM task (SMW) consisted of blocks visually presented in one of 12 positions for 2 s each. Subjects were to determine if the current position matched the position presented 2 slides earlier (N-Back Test). The verbal task (VMW) consisted of presentation of a single letter. The location of cortical activity during SWM in NR (determined with MR-FOCUSS analysis) was in the right superior temporal gyrus (STG) and right angular gyrus (AG). Similar activation was seen in SD with a slight delay of approximately 20 ms. During VWM activity was seen in LEFT STG and LEFT AG in NR. In contrast for SD, activation was in the RIGHT STG and RIGHT AG. This study demonstrates the possibility to differentiate WM processing in subjects with and without learning disorders.

Model-Based Normalization of a Fractional-Crystal Collimator for Small-Animal PET Imaging.

Science.gov (United States)

Li, Yusheng; Matej, Samuel; Karp, Joel S; Metzler, Scott D

2017-05-01

Previously, we proposed to use a coincidence collimator to achieve fractional-crystal resolution in PET imaging. We have designed and fabricated a collimator prototype for a small-animal PET scanner, A-PET. To compensate for imperfections in the fabricated collimator prototype, collimator normalization, as well as scanner normalization, is required to reconstruct quantitative and artifact-free images. In this study, we develop a normalization method for the collimator prototype based on the A-PET normalization using a uniform cylinder phantom. We performed data acquisition without the collimator for scanner normalization first, and then with the collimator from eight different rotation views for collimator normalization. After a reconstruction without correction, we extracted the cylinder parameters from which we generated expected emission sinograms. Single scatter simulation was used to generate the scattered sinograms. We used the least-squares method to generate the normalization coefficient for each LOR based on measured, expected and scattered sinograms. The scanner and collimator normalization coefficients were factorized by performing two normalizations separately. The normalization methods were also verified using experimental data acquired from A-PET with and without the collimator. In summary, we developed a model-base collimator normalization that can significantly reduce variance and produce collimator normalization with adequate statistical quality within feasible scan time.

Standard Model processes

CERN Document Server

Mangano, M.L.; Aguilar-Saavedra, Juan Antonio; Alekhin, S.; Badger, S.; Bauer, C.W.; Becher, T.; Bertone, V.; Bonvini, M.; Boselli, S.; Bothmann, E.; Boughezal, R.; Cacciari, M.; Carloni Calame, C.M.; Caola, F.; Campbell, J.M.; Carrazza, S.; Chiesa, M.; Cieri, L.; Cimaglia, F.; Febres Cordero, F.; Ferrarese, P.; D'Enterria, D.; Ferrera, G.; Garcia i Tormo, X.; Garzelli, M.V.; Germann, E.; Hirschi, V.; Han, T.; Ita, H.; Jäger, B.; Kallweit, S.; Karlberg, A.; Kuttimalai, S.; Krauss, F.; Larkoski, A.J.; Lindert, J.; Luisoni, G.; Maierhöfer, P.; Mattelaer, O.; Martinez, H.; Moch, S.; Montagna, G.; Moretti, M.; Nason, P.; Nicrosini, O.; Oleari, C.; Pagani, D.; Papaefstathiou, A.; Petriello, F.; Piccinini, F.; Pierini, M.; Pierog, T.; Pozzorini, S.; Re, E.; Robens, T.; Rojo, J.; Ruiz, R.; Sakurai, K.; Salam, G.P.; Salfelder, L.; Schönherr, M.; Schulze, M.; Schumann, S.; Selvaggi, M.; Shivaji, A.; Siodmok, A.; Skands, P.; Torrielli, P.; Tramontano, F.; Tsinikos, I.; Tweedie, B.; Vicini, A.; Westhoff, S.; Zaro, M.; Zeppenfeld, D.; CERN. Geneva. ATS Department

2017-06-22

This report summarises the properties of Standard Model processes at the 100 TeV pp collider. We document the production rates and typical distributions for a number of benchmark Standard Model processes, and discuss new dynamical phenomena arising at the highest energies available at this collider. We discuss the intrinsic physics interest in the measurement of these Standard Model processes, as well as their role as backgrounds for New Physics searches.

Normalization of Gravitational Acceleration Models

Science.gov (United States)

Eckman, Randy A.; Brown, Aaron J.; Adamo, Daniel R.

2011-01-01

Unlike the uniform density spherical shell approximations of Newton, the con- sequence of spaceflight in the real universe is that gravitational fields are sensitive to the nonsphericity of their generating central bodies. The gravitational potential of a nonspherical central body is typically resolved using spherical harmonic approximations. However, attempting to directly calculate the spherical harmonic approximations results in at least two singularities which must be removed in order to generalize the method and solve for any possible orbit, including polar orbits. Three unique algorithms have been developed to eliminate these singularities by Samuel Pines [1], Bill Lear [2], and Robert Gottlieb [3]. This paper documents the methodical normalization of two1 of the three known formulations for singularity-free gravitational acceleration (namely, the Lear [2] and Gottlieb [3] algorithms) and formulates a general method for defining normalization parameters used to generate normalized Legendre Polynomials and ALFs for any algorithm. A treatment of the conventional formulation of the gravitational potential and acceleration is also provided, in addition to a brief overview of the philosophical differences between the three known singularity-free algorithms.

Visualizing the process of process modeling with PPMCharts

NARCIS (Netherlands)

Claes, J.; Vanderfeesten, I.T.P.; Pinggera, J.; Reijers, H.A.; Weber, B.; Poels, G.; La Rosa, M.; Soffer, P.

2013-01-01

In the quest for knowledge about how to make good process models, recent research focus is shifting from studying the quality of process models to studying the process of process modeling (often abbreviated as PPM) itself. This paper reports on our efforts to visualize this specific process in such

Simulation of reactive nanolaminates using reduced models: II. Normal propagation

Energy Technology Data Exchange (ETDEWEB)

Salloum, Maher; Knio, Omar M. [Department of Mechanical Engineering, The Johns Hopkins University, Baltimore, MD 21218-2686 (United States)

2010-03-15

Transient normal flame propagation in reactive Ni/Al multilayers is analyzed computationally. Two approaches are implemented, based on generalization of earlier methodology developed for axial propagation, and on extension of the model reduction formalism introduced in Part I. In both cases, the formulation accommodates non-uniform layering as well as the presence of inert layers. The equations of motion for the reactive system are integrated using a specially-tailored integration scheme, that combines extended-stability, Runge-Kutta-Chebychev (RKC) integration of diffusion terms with exact treatment of the chemical source term. The detailed and reduced models are first applied to the analysis of self-propagating fronts in uniformly-layered materials. Results indicate that both the front velocities and the ignition threshold are comparable for normal and axial propagation. Attention is then focused on analyzing the effect of a gap composed of inert material on reaction propagation. In particular, the impacts of gap width and thermal conductivity are briefly addressed. Finally, an example is considered illustrating reaction propagation in reactive composites combining regions corresponding to two bilayer widths. This setup is used to analyze the effect of the layering frequency on the velocity of the corresponding reaction fronts. In all cases considered, good agreement is observed between the predictions of the detailed model and the reduced model, which provides further support for adoption of the latter. (author)

Modelling of tension stiffening for normal and high strength concrete

DEFF Research Database (Denmark)

Christiansen, Morten Bo; Nielsen, Mogens Peter

1998-01-01

form the model is extended to apply to biaxial stress fields as well. To determine the biaxial stress field, the theorem of minimum complementary elastic energy is used. The theory has been compared with tests on rods, disks, and beams of both normal and high strength concrete, and very good results...

Black-Litterman model on non-normal stock return (Case study four banks at LQ-45 stock index)

Science.gov (United States)

Mahrivandi, Rizki; Noviyanti, Lienda; Setyanto, Gatot Riwi

2017-03-01

The formation of the optimal portfolio is a method that can help investors to minimize risks and optimize profitability. One model for the optimal portfolio is a Black-Litterman (BL) model. BL model can incorporate an element of historical data and the views of investors to form a new prediction about the return of the portfolio as a basis for preparing the asset weighting models. BL model has two fundamental problems, the assumption of normality and estimation parameters on the market Bayesian prior framework that does not from a normal distribution. This study provides an alternative solution where the modelling of the BL model stock returns and investor views from non-normal distribution.

Crack growth resistance for anisotropic plasticity with non-normality effects

DEFF Research Database (Denmark)

Tvergaard, Viggo; Legarth, Brian Nyvang

2006-01-01

For a plastically anisotropic solid a plasticity model using a plastic flow rule with non-normality is applied to predict crack growth. The fracture process is modelled in terms of a traction–separation law specified on the crack plane. A phenomenological elastic–viscoplastic material model...... is applied, using one of two different anisotropic yield criteria to account for the plastic anisotropy, and in each case the effect of the normality flow rule is compared with the effect of non-normality. Conditions of small scale yielding are assumed, with mode I loading conditions far from the crack......-tip, and various directions of the crack plane relative to the principal axes of the anisotropy are considered. It is found that the steady-state fracture toughness is significantly reduced when the non-normality flow rule is used. Furthermore, it is shown that the predictions are quite sensitive to the value...

Normalization: A Preprocessing Stage

OpenAIRE

Patro, S. Gopal Krishna; Sahu, Kishore Kumar

2015-01-01

As we know that the normalization is a pre-processing stage of any type problem statement. Especially normalization takes important role in the field of soft computing, cloud computing etc. for manipulation of data like scale down or scale up the range of data before it becomes used for further stage. There are so many normalization techniques are there namely Min-Max normalization, Z-score normalization and Decimal scaling normalization. So by referring these normalization techniques we are ...

Evaluation of subject contrast and normalized average glandular dose by semi-analytical models

International Nuclear Information System (INIS)

Tomal, A.; Poletti, M.E.; Caldas, L.V.E.

2010-01-01

In this work, two semi-analytical models are described to evaluate the subject contrast of nodules and the normalized average glandular dose in mammography. Both models were used to study the influence of some parameters, such as breast characteristics (thickness and composition) and incident spectra (kVp and target-filter combination) on the subject contrast of a nodule and on the normalized average glandular dose. From the subject contrast results, detection limits of nodules were also determined. Our results are in good agreement with those reported by other authors, who had used Monte Carlo simulation, showing the robustness of our semi-analytical method.

Pattern Matching Framework to Estimate the Urgency of Off-Normal Situations in NPPs

Energy Technology Data Exchange (ETDEWEB)

Shin, Jin Soo; Park, Sang Jun; Heo, Gyun Young [Kyung Hee University, Yongin (Korea, Republic of); Park, Jin Kyun [Korea Atomic Energy Research Institute, Daejeon (Korea, Republic of); Kim, Hyo Jin; Park, Soon Yeol [Korea Hydro and Nuclear Power, Yeonggwang (Korea, Republic of)

2010-10-15

According to power plant operators, it was said that they could quite well recognize off-normal situations from an incipient stage and also anticipate the possibility of upcoming trips in case of skilled operators, even though it is difficult to clarify the cause of the off-normal situation. From the interview, we could assure the feasibility of two assumptions for the diagnosis of off-normal conditions: One is that we can predict whether an accidental shutdown happens or not if we observe the early stage when an off-normal starts to grow. The other is the observation at the early stage can provide the remaining time to a trip as well as the cause of such an off-normal situation. For this purpose, the development of on-line monitoring systems using various data processing techniques in nuclear power plants (NPPs) has been the subject of increasing attention and becomes important contributor to improve performance and economics. Many of studies have suggested the diagnostic methodologies. One of representative methods was to use the distance discrimination as a similarity measure, for example, such as the Euclidean distance. A variety of artificial intelligence techniques such as a neural network have been developed as well. In addition, some of these methodologies were to reduce the data dimensions for more effectively work. While sharing the same motivation with the previous achievements, this study proposed non-parametric pattern matching techniques to reduce the uncertainty in pursuance of selection of models and modeling processes. This could be characterized by the following two aspects: First, for overcoming considering only a few typical scenarios in the most of the studies, this study is getting the entire sets of off-normal situations which are anticipated in NPPs, which are created by a full-scope simulator. Second, many of the existing researches adopted the process of forming a diagnosis model which is so-called a training technique or a parametric

Pattern Matching Framework to Estimate the Urgency of Off-Normal Situations in NPPs

International Nuclear Information System (INIS)

Shin, Jin Soo; Park, Sang Jun; Heo, Gyun Young; Park, Jin Kyun; Kim, Hyo Jin; Park, Soon Yeol

2010-01-01

According to power plant operators, it was said that they could quite well recognize off-normal situations from an incipient stage and also anticipate the possibility of upcoming trips in case of skilled operators, even though it is difficult to clarify the cause of the off-normal situation. From the interview, we could assure the feasibility of two assumptions for the diagnosis of off-normal conditions: One is that we can predict whether an accidental shutdown happens or not if we observe the early stage when an off-normal starts to grow. The other is the observation at the early stage can provide the remaining time to a trip as well as the cause of such an off-normal situation. For this purpose, the development of on-line monitoring systems using various data processing techniques in nuclear power plants (NPPs) has been the subject of increasing attention and becomes important contributor to improve performance and economics. Many of studies have suggested the diagnostic methodologies. One of representative methods was to use the distance discrimination as a similarity measure, for example, such as the Euclidean distance. A variety of artificial intelligence techniques such as a neural network have been developed as well. In addition, some of these methodologies were to reduce the data dimensions for more effectively work. While sharing the same motivation with the previous achievements, this study proposed non-parametric pattern matching techniques to reduce the uncertainty in pursuance of selection of models and modeling processes. This could be characterized by the following two aspects: First, for overcoming considering only a few typical scenarios in the most of the studies, this study is getting the entire sets of off-normal situations which are anticipated in NPPs, which are created by a full-scope simulator. Second, many of the existing researches adopted the process of forming a diagnosis model which is so-called a training technique or a parametric

Review of friction modeling in metal forming processes

DEFF Research Database (Denmark)

Nielsen, C.V.; Bay, N.

2018-01-01

Abstract In metal forming processes, friction between tool and workpiece is an important parameter influencing the material flow, surface quality and tool life. Theoretical models of friction in metal forming are based on analysis of the real contact area in tool-workpiece interfaces. Several...... research groups have studied and modeled the asperity flattening of workpiece material against tool surface in dry contact or in contact interfaces with only thin layers of lubrication with the aim to improve understanding of friction in metal forming. This paper aims at giving a review of the most...... conditions, normal pressure, sliding length and speed, temperature changes, friction on the flattened plateaus and deformation of the underlying material. The review illustrates the development in the understanding of asperity flattening and the methods of analysis....

Business process model repositories : efficient process retrieval

NARCIS (Netherlands)

Yan, Z.

2012-01-01

As organizations increasingly work in process-oriented manner, the number of business process models that they develop and have to maintain increases. As a consequence, it has become common for organizations to have collections of hundreds or even thousands of business process models. When a

Post-processing scheme for modelling the lithospheric magnetic field

Directory of Open Access Journals (Sweden)

V. Lesur

2013-03-01

Full Text Available We investigated how the noise in satellite magnetic data affects magnetic lithospheric field models derived from these data in the special case where this noise is correlated along satellite orbit tracks. For this we describe the satellite data noise as a perturbation magnetic field scaled independently for each orbit, where the scaling factor is a random variable, normally distributed with zero mean. Under this assumption, we have been able to derive a model for errors in lithospheric models generated by the correlated satellite data noise. Unless the perturbation field is known, estimating the noise in the lithospheric field model is a non-linear inverse problem. We therefore proposed an iterative post-processing technique to estimate both the lithospheric field model and its associated noise model. The technique has been successfully applied to derive a lithospheric field model from CHAMP satellite data up to spherical harmonic degree 120. The model is in agreement with other existing models. The technique can, in principle, be extended to all sorts of potential field data with "along-track" correlated errors.

Blood Vessel Normalization in the Hamster Oral Cancer Model for Experimental Cancer Therapy Studies

Energy Technology Data Exchange (ETDEWEB)

Ana J. Molinari; Romina F. Aromando; Maria E. Itoiz; Marcela A. Garabalino; Andrea Monti Hughes; Elisa M. Heber; Emiliano C. C. Pozzi; David W. Nigg; Veronica A. Trivillin; Amanda E. Schwint

2012-07-01

Normalization of tumor blood vessels improves drug and oxygen delivery to cancer cells. The aim of this study was to develop a technique to normalize blood vessels in the hamster cheek pouch model of oral cancer. Materials and Methods: Tumor-bearing hamsters were treated with thalidomide and were compared with controls. Results: Twenty eight hours after treatment with thalidomide, the blood vessels of premalignant tissue observable in vivo became narrower and less tortuous than those of controls; Evans Blue Dye extravasation in tumor was significantly reduced (indicating a reduction in aberrant tumor vascular hyperpermeability that compromises blood flow), and tumor blood vessel morphology in histological sections, labeled for Factor VIII, revealed a significant reduction in compressive forces. These findings indicated blood vessel normalization with a window of 48 h. Conclusion: The technique developed herein has rendered the hamster oral cancer model amenable to research, with the potential benefit of vascular normalization in head and neck cancer therapy.

Modeling Aspects of Activated Sludge Processes Part l l: Mathematical Process Modeling and Biokinetics of Activated Sludge Processes

Energy Technology Data Exchange (ETDEWEB)

AbdElHaleem, H S [Cairo Univ.-CivlI Eng. Dept., Giza (Egypt); EI-Ahwany, A H [CairoUlmrsity- Faculty ofEngincering - Chemical Engineering Department, Giza (Egypt); Ibrahim, H I [Helwan University- Faculty of Engineering - Biomedical Engineering Department, Helwan (Egypt); Ibrahim, G [Menofia University- Faculty of Engineering Sbebin EI Kom- Basic Eng. Sc. Dept., Menofia (Egypt)

2004-07-01

Mathematical process modeling and biokinetics of activated sludge process were reviewed considering different types of models. It has been evaluated the task group models of ASMI. and 2, and 3 versioned by Henze et al considering the conditions of each model and the different processes of which every model consists. It is revealed that ASMI contains some defects avoided in ASM3. Relied on homogeneity, Models can be classified into homogenous models characterized by taking the activated sludge process as one phase. In this type of models, the internal mass transfer inside the floes was neglected.. Hence, the kinetic parameter produces can be considered inaccurate. The other type of models is the heterogeneous model This type considers the mass transfer operations in addition to the biochemical reaction processes; hence, the resulted kinetic parameters can be considered more accurate than that of homogenous type.

Modeling Aspects of Activated Sludge Processes Part l l: Mathematical Process Modeling and Biokinetics of Activated Sludge Processes

International Nuclear Information System (INIS)

AbdElHaleem, H.S.; EI-Ahwany, A. H.; Ibrahim, H.I.; Ibrahim, G.

2004-01-01

Mathematical process modeling and biokinetics of activated sludge process were reviewed considering different types of models. It has been evaluated the task group models of ASMI. and 2, and 3 versioned by Henze et al considering the conditions of each model and the different processes of which every model consists. It is revealed that ASMI contains some defects avoided in ASM3. Relied on homogeneity, Models can be classified into homogenous models characterized by taking the activated sludge process as one phase. In this type of models, the internal mass transfer inside the floes was neglected.. Hence, the kinetic parameter produces can be considered inaccurate. The other type of models is the heterogeneous model This type considers the mass transfer operations in addition to the biochemical reaction processes; hence, the resulted kinetic parameters can be considered more accurate than that of homogenous type

Process correlation analysis model for process improvement identification.

Science.gov (United States)

Choi, Su-jin; Kim, Dae-Kyoo; Park, Sooyong

2014-01-01

Software process improvement aims at improving the development process of software systems. It is initiated by process assessment identifying strengths and weaknesses and based on the findings, improvement plans are developed. In general, a process reference model (e.g., CMMI) is used throughout the process of software process improvement as the base. CMMI defines a set of process areas involved in software development and what to be carried out in process areas in terms of goals and practices. Process areas and their elements (goals and practices) are often correlated due to the iterative nature of software development process. However, in the current practice, correlations of process elements are often overlooked in the development of an improvement plan, which diminishes the efficiency of the plan. This is mainly attributed to significant efforts and the lack of required expertise. In this paper, we present a process correlation analysis model that helps identify correlations of process elements from the results of process assessment. This model is defined based on CMMI and empirical data of improvement practices. We evaluate the model using industrial data.

The impact of working memory and the "process of process modelling" on model quality: Investigating experienced versus inexperienced modellers

DEFF Research Database (Denmark)

Martini, Markus; Pinggera, Jakob; Neurauter, Manuel

2016-01-01

of reconciliation phases was positively related to PM quality in experienced modellers. Our research reveals central cognitive mechanisms in process modelling and has potential practical implications for the development of modelling software and teaching the craft of process modelling....... the role of cognitive processes as well as modelling processes in creating a PM in experienced and inexperienced modellers. Specifically, two working memory (WM) functions (holding and processing of information and relational integration) and three process of process modelling phases (comprehension...

Bayesian Option Pricing using Mixed Normal Heteroskedasticity Models

DEFF Research Database (Denmark)

Rombouts, Jeroen; Stentoft, Lars

2014-01-01

Option pricing using mixed normal heteroscedasticity models is considered. It is explained how to perform inference and price options in a Bayesian framework. The approach allows to easily compute risk neutral predictive price densities which take into account parameter uncertainty....... In an application to the S&P 500 index, classical and Bayesian inference is performed on the mixture model using the available return data. Comparing the ML estimates and posterior moments small differences are found. When pricing a rich sample of options on the index, both methods yield similar pricing errors...... measured in dollar and implied standard deviation losses, and it turns out that the impact of parameter uncertainty is minor. Therefore, when it comes to option pricing where large amounts of data are available, the choice of the inference method is unimportant. The results are robust to different...

Product and Process Modelling

DEFF Research Database (Denmark)

Cameron, Ian T.; Gani, Rafiqul

. These approaches are put into the context of life cycle modelling, where multiscale and multiform modelling is increasingly prevalent in the 21st century. The book commences with a discussion of modern product and process modelling theory and practice followed by a series of case studies drawn from a variety......This book covers the area of product and process modelling via a case study approach. It addresses a wide range of modelling applications with emphasis on modelling methodology and the subsequent in-depth analysis of mathematical models to gain insight via structural aspects of the models...... to biotechnology applications, food, polymer and human health application areas. The book highlights to important nature of modern product and process modelling in the decision making processes across the life cycle. As such it provides an important resource for students, researchers and industrial practitioners....

Modelling of real area of contact between tool and workpiece in metal forming processes including the influence of subsurface deformation

DEFF Research Database (Denmark)

Nielsen, Chris Valentin; Martins, Paulo A. F.; Bay, Niels Oluf

2016-01-01

New equipment for testing asperity deformation at various normal loads and subsurface elongations is presented. Resulting real contact area ratios increase heavily with increasing subsurface expansion due to lowered yield pressure on the asperities when imposing subsurface normal stress parallel ...... for estimating friction in the numerical modelling of metal forming processes.......New equipment for testing asperity deformation at various normal loads and subsurface elongations is presented. Resulting real contact area ratios increase heavily with increasing subsurface expansion due to lowered yield pressure on the asperities when imposing subsurface normal stress parallel...... to the surface. Finite element modelling supports the presentation and contributes by extrapolation of results to complete the mapping of contact area as function of normal pressure and one-directional subsurface strain parallel to the surface. Improved modelling of the real contact area is the basis...

Modeling of biopharmaceutical processes. Part 2: Process chromatography unit operation

DEFF Research Database (Denmark)

Kaltenbrunner, Oliver; McCue, Justin; Engel, Philip

2008-01-01

Process modeling can be a useful tool to aid in process development, process optimization, and process scale-up. When modeling a chromatography process, one must first select the appropriate models that describe the mass transfer and adsorption that occurs within the porous adsorbent. The theoret......Process modeling can be a useful tool to aid in process development, process optimization, and process scale-up. When modeling a chromatography process, one must first select the appropriate models that describe the mass transfer and adsorption that occurs within the porous adsorbent...

Development and Implementation of Mechanistic Terry Turbine Models in RELAP-7 to Simulate RCIC Normal Operation Conditions

Energy Technology Data Exchange (ETDEWEB)

Zhao, Haihua [Idaho National Lab. (INL), Idaho Falls, ID (United States); Zou, Ling [Idaho National Lab. (INL), Idaho Falls, ID (United States); Zhang, Hongbin [Idaho National Lab. (INL), Idaho Falls, ID (United States); O' Brien, James Edward [Idaho National Lab. (INL), Idaho Falls, ID (United States)

2016-09-01

As part of the efforts to understand the unexpected “self-regulating” mode of the RCIC (Reactor Core Isolation Cooling) systems in Fukushima accidents and extend BWR RCIC and PWR AFW (Auxiliary Feed Water) operational range and flexibility, mechanistic models for the Terry turbine, based on Sandia’s original work [1], have been developed and implemented in the RELAP-7 code to simulate the RCIC system. In 2016, our effort has been focused on normal working conditions of the RCIC system. More complex off-design conditions will be pursued in later years when more data are available. In the Sandia model, the turbine stator inlet velocity is provided according to a reduced-order model which was obtained from a large number of CFD (computational fluid dynamics) simulations. In this work, we propose an alternative method, using an under-expanded jet model to obtain the velocity and thermodynamic conditions for the turbine stator inlet. The models include both an adiabatic expansion process inside the nozzle and a free expansion process outside of the nozzle to ambient pressure. The combined models are able to predict the steam mass flow rate and supersonic velocity to the Terry turbine bucket entrance, which are the necessary input information for the Terry turbine rotor model. The analytical models for the nozzle were validated with experimental data and benchmarked with CFD simulations. The analytical models generally agree well with the experimental data and CFD simulations. The analytical models are suitable for implementation into a reactor system analysis code or severe accident code as part of mechanistic and dynamical models to understand the RCIC behaviors. The newly developed nozzle models and modified turbine rotor model according to the Sandia’s original work have been implemented into RELAP-7, along with the original Sandia Terry turbine model. A new pump model has also been developed and implemented to couple with the Terry turbine model. An input

Deformation associated with continental normal faults

Science.gov (United States)

Resor, Phillip G.

Deformation associated with normal fault earthquakes and geologic structures provide insights into the seismic cycle as it unfolds over time scales from seconds to millions of years. Improved understanding of normal faulting will lead to more accurate seismic hazard assessments and prediction of associated structures. High-precision aftershock locations for the 1995 Kozani-Grevena earthquake (Mw 6.5), Greece image a segmented master fault and antithetic faults. This three-dimensional fault geometry is typical of normal fault systems mapped from outcrop or interpreted from reflection seismic data and illustrates the importance of incorporating three-dimensional fault geometry in mechanical models. Subsurface fault slip associated with the Kozani-Grevena and 1999 Hector Mine (Mw 7.1) earthquakes is modeled using a new method for slip inversion on three-dimensional fault surfaces. Incorporation of three-dimensional fault geometry improves the fit to the geodetic data while honoring aftershock distributions and surface ruptures. GPS Surveying of deformed bedding surfaces associated with normal faulting in the western Grand Canyon reveals patterns of deformation that are similar to those observed by interferometric satellite radar interferometry (InSAR) for the Kozani Grevena earthquake with a prominent down-warp in the hanging wall and a lesser up-warp in the footwall. However, deformation associated with the Kozani-Grevena earthquake extends ˜20 km from the fault surface trace, while the folds in the western Grand Canyon only extend 500 m into the footwall and 1500 m into the hanging wall. A comparison of mechanical and kinematic models illustrates advantages of mechanical models in exploring normal faulting processes including incorporation of both deformation and causative forces, and the opportunity to incorporate more complex fault geometry and constitutive properties. Elastic models with antithetic or synthetic faults or joints in association with a master

The impact of working memory and the "process of process modelling" on model quality: Investigating experienced versus inexperienced modellers.

Science.gov (United States)

Martini, Markus; Pinggera, Jakob; Neurauter, Manuel; Sachse, Pierre; Furtner, Marco R; Weber, Barbara

2016-05-09

A process model (PM) represents the graphical depiction of a business process, for instance, the entire process from online ordering a book until the parcel is delivered to the customer. Knowledge about relevant factors for creating PMs of high quality is lacking. The present study investigated the role of cognitive processes as well as modelling processes in creating a PM in experienced and inexperienced modellers. Specifically, two working memory (WM) functions (holding and processing of information and relational integration) and three process of process modelling phases (comprehension, modelling, and reconciliation) were related to PM quality. Our results show that the WM function of relational integration was positively related to PM quality in both modelling groups. The ratio of comprehension phases was negatively related to PM quality in inexperienced modellers and the ratio of reconciliation phases was positively related to PM quality in experienced modellers. Our research reveals central cognitive mechanisms in process modelling and has potential practical implications for the development of modelling software and teaching the craft of process modelling.

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

Directory of Open Access Journals (Sweden)

Ventura Martins Paula

2017-03-01

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

A model of synovial fluid lubricant composition in normal and injured joints

Directory of Open Access Journals (Sweden)

M E Blewis

2007-03-01

Full Text Available The synovial fluid (SF of joints normally functions as a biological lubricant, providing low-friction and low-wear properties to articulating cartilage surfaces through the putative contributions of proteoglycan 4 (PRG4, hyaluronic acid (HA, and surface active phospholipids (SAPL. These lubricants are secreted by chondrocytes in articular cartilage and synoviocytes in synovium, and concentrated in the synovial space by the semi-permeable synovial lining. A deficiency in this lubricating system may contribute to the erosion of articulating cartilage surfaces in conditions of arthritis. A quantitative intercompartmental model was developed to predict in vivo SF lubricant concentration in the human knee joint. The model consists of a SF compartment that (a is lined by cells of appropriate types, (b is bound by a semi-permeable membrane, and (c contains factors that regulate lubricant secretion. Lubricant concentration was predicted with different chemical regulators of chondrocyte and synoviocyte secretion, and also with therapeutic interventions of joint lavage and HA injection. The model predicted steady-state lubricant concentrations that were within physiologically observed ranges, and which were markedly altered with chemical regulation. The model also predicted that when starting from a zero lubricant concentration after joint lavage, PRG4 reaches steady-state concentration ~10-40 times faster than HA. Additionally, analysis of the clearance rate of HA after therapeutic injection into SF predicted that the majority of HA leaves the joint after ~1-2 days. This quantitative intercompartmental model allows integration of biophysical processes to identify both environmental factors and clinical therapies that affect SF lubricant composition in whole joints.

Publicly available models to predict normal boiling point of organic compounds

International Nuclear Information System (INIS)

Oprisiu, Ioana; Marcou, Gilles; Horvath, Dragos; Brunel, Damien Bernard; Rivollet, Fabien; Varnek, Alexandre

2013-01-01

Quantitative structure–property models to predict the normal boiling point (T b ) of organic compounds were developed using non-linear ASNNs (associative neural networks) as well as multiple linear regression – ISIDA-MLR and SQS (stochastic QSAR sampler). Models were built on a diverse set of 2098 organic compounds with T b varying in the range of 185–491 K. In ISIDA-MLR and ASNN calculations, fragment descriptors were used, whereas fragment, FPTs (fuzzy pharmacophore triplets), and ChemAxon descriptors were employed in SQS models. Prediction quality of the models has been assessed in 5-fold cross validation. Obtained models were implemented in the on-line ISIDA predictor at (http://infochim.u-strasbg.fr/webserv/VSEngine.html)

Normal Mode Derived Models of the Physical Properties of Earth's Outer Core

Science.gov (United States)

Irving, J. C. E.; Cottaar, S.; Lekic, V.; Wu, W.

2017-12-01

Earth's outer core, the largest reservoir of metal in our planet, is comprised of an iron alloy of an uncertain composition. Its dynamical behaviour is responsible for the generation of Earth's magnetic field, with convection driven both by thermal and chemical buoyancy fluxes. Existing models of the seismic velocity and density of the outer core exhibit some variation, and there are only a small number of models which aim to represent the outer core's density.It is therefore important that we develop a better understanding of the physical properties of the outer core. Though most of the outer core is likely to be well mixed, it is possible that the uppermost outer core is stably stratified: it may be enriched in light elements released during the growth of the solid, iron enriched, inner core; by elements dissolved from the mantle into the outer core; or by exsolution of compounds previously dissolved in the liquid metal which will eventually be swept into the mantle. The stratified layer may host MAC or Rossby waves and it could impede communication between the chemically differentiated mantle and outer core, including screening out some of the geodynamo's signal. We use normal mode center frequencies to estimate the physical properties of the outer core in a Bayesian framework. We estimate the mineral physical parameters needed to best produce velocity and density models of the outer core which are consistent with the normal mode observations. We require that our models satisfy realistic physical constraints. We create models of the outer core with and without a distinct uppermost layer and assess the importance of this region.Our normal mode-derived models are compared with observations of body waves which travel through the outer core. In particular, we consider SmKS waves which are especially sensitive to the uppermost outer core and are therefore an important way to understand the robustness of our models.

Optimum parameters in a model for tumour control probability, including interpatient heterogeneity: evaluation of the log-normal distribution

International Nuclear Information System (INIS)

Keall, P J; Webb, S

2007-01-01

The heterogeneity of human tumour radiation response is well known. Researchers have used the normal distribution to describe interpatient tumour radiosensitivity. However, many natural phenomena show a log-normal distribution. Log-normal distributions are common when mean values are low, variances are large and values cannot be negative. These conditions apply to radiosensitivity. The aim of this work was to evaluate the log-normal distribution to predict clinical tumour control probability (TCP) data and to compare the results with the homogeneous (δ-function with single α-value) and normal distributions. The clinically derived TCP data for four tumour types-melanoma, breast, squamous cell carcinoma and nodes-were used to fit the TCP models. Three forms of interpatient tumour radiosensitivity were considered: the log-normal, normal and δ-function. The free parameters in the models were the radiosensitivity mean, standard deviation and clonogenic cell density. The evaluation metric was the deviance of the maximum likelihood estimation of the fit of the TCP calculated using the predicted parameters to the clinical data. We conclude that (1) the log-normal and normal distributions of interpatient tumour radiosensitivity heterogeneity more closely describe clinical TCP data than a single radiosensitivity value and (2) the log-normal distribution has some theoretical and practical advantages over the normal distribution. Further work is needed to test these models on higher quality clinical outcome datasets

Modeling multiphase materials processes

CERN Document Server

Iguchi, Manabu

2010-01-01

""Modeling Multiphase Materials Processes: Gas-Liquid Systems"" describes the methodology and application of physical and mathematical modeling to multi-phase flow phenomena in materials processing. The book focuses on systems involving gas-liquid interaction, the most prevalent in current metallurgical processes. The performance characteristics of these processes are largely dependent on transport phenomena. This volume covers the inherent characteristics that complicate the modeling of transport phenomena in such systems, including complex multiphase structure, intense turbulence, opacity of

Statistical Theory of Normal Grain Growth Revisited

International Nuclear Information System (INIS)

Gadomski, A.; Luczka, J.

2002-01-01

In this paper, we discuss three physically relevant problems concerning the normal grain growth process. These are: Infinite vs finite size of the system under study (a step towards more realistic modeling); conditions of fine-grained structure formation, with possible applications to thin films and biomembranes, and interesting relations to superplasticity of materials; approach to log-normality, an ubiquitous natural phenomenon, frequently reported in literature. It turns out that all three important points mentioned are possible to be included in a Mulheran-Harding type behavior of evolving grains-containing systems that we have studied previously. (author)

Application of a Brittle Damage Model to Normal Plate-on-Plate Impact

National Research Council Canada - National Science Library

Raftenberg, Martin N

2005-01-01

A brittle damage model presented by Grinfeld and Wright of the U.S. Army Research Laboratory was implemented in the LS-DYNA finite element code and applied to the simulation of normal plate-on-plate impact...

An MCNP model of glove boxes in a plutonium processing facility

International Nuclear Information System (INIS)

Dooley, D.E.; Kornreich, D.E.

1998-01-01

Nuclear material processing usually occurs simultaneously in several glove boxes whose primary purpose is to contain radioactive materials and prevent inhalation or ingestion of radioactive materials by workers. A room in the plutonium facility at Los Alamos National Laboratory has been slated for installation of a glove box for storing plutonium metal in various shapes during processing. This storage glove box will be located in a room containing other glove boxes used daily by workers processing plutonium parts. An MCNP model of the room and glove boxes has been constructed to estimate the neutron flux at various locations in the room for two different locations of the storage glove box and to determine the effect of placing polyethylene shielding around the storage glove box. A neutron dose survey of the room with sources dispersed as during normal production operations was used as a benchmark to compare the neutron dose equivalent rates calculated by the MCNP model

A Note on the Equivalence between the Normal and the Lognormal Implied Volatility : A Model Free Approach

OpenAIRE

Grunspan, Cyril

2011-01-01

First, we show that implied normal volatility is intimately linked with the incomplete Gamma function. Then, we deduce an expansion on implied normal volatility in terms of the time-value of a European call option. Then, we formulate an equivalence between the implied normal volatility and the lognormal implied volatility with any strike and any model. This generalizes a known result for the SABR model. Finally, we adress the issue of the "breakeven move" of a delta-hedged portfolio.

Wind turbine condition monitoring based on SCADA data using normal behavior models

DEFF Research Database (Denmark)

Schlechtingen, Meik; Santos, Ilmar; Achiche, Sofiane

2013-01-01

This paper proposes a system for wind turbine condition monitoring using Adaptive Neuro-Fuzzy Interference Systems (ANFIS). For this purpose: (1) ANFIS normal behavior models for common Supervisory Control And Data Acquisition (SCADA) data are developed in order to detect abnormal behavior...... the applicability of ANFIS models for monitoring wind turbine SCADA signals. The computational time needed for model training is compared to Neural Network (NN) models showing the strength of ANFIS in training speed. (2) For automation of fault diagnosis Fuzzy Interference Systems (FIS) are used to analyze...

Method for Automatic Selection of Parameters in Normal Tissue Complication Probability Modeling.

Science.gov (United States)

Christophides, Damianos; Appelt, Ane L; Gusnanto, Arief; Lilley, John; Sebag-Montefiore, David

2018-07-01

To present a fully automatic method to generate multiparameter normal tissue complication probability (NTCP) models and compare its results with those of a published model, using the same patient cohort. Data were analyzed from 345 rectal cancer patients treated with external radiation therapy to predict the risk of patients developing grade 1 or ≥2 cystitis. In total, 23 clinical factors were included in the analysis as candidate predictors of cystitis. Principal component analysis was used to decompose the bladder dose-volume histogram into 8 principal components, explaining more than 95% of the variance. The data set of clinical factors and principal components was divided into training (70%) and test (30%) data sets, with the training data set used by the algorithm to compute an NTCP model. The first step of the algorithm was to obtain a bootstrap sample, followed by multicollinearity reduction using the variance inflation factor and genetic algorithm optimization to determine an ordinal logistic regression model that minimizes the Bayesian information criterion. The process was repeated 100 times, and the model with the minimum Bayesian information criterion was recorded on each iteration. The most frequent model was selected as the final "automatically generated model" (AGM). The published model and AGM were fitted on the training data sets, and the risk of cystitis was calculated. The 2 models had no significant differences in predictive performance, both for the training and test data sets (P value > .05) and found similar clinical and dosimetric factors as predictors. Both models exhibited good explanatory performance on the training data set (P values > .44), which was reduced on the test data sets (P values < .05). The predictive value of the AGM is equivalent to that of the expert-derived published model. It demonstrates potential in saving time, tackling problems with a large number of parameters, and standardizing variable selection in NTCP

Semantic Business Process Modeling

OpenAIRE

Markovic, Ivan

2010-01-01

This book presents a process-oriented business modeling framework based on semantic technologies. The framework consists of modeling languages, methods, and tools that allow for semantic modeling of business motivation, business policies and rules, and business processes. Quality of the proposed modeling framework is evaluated based on the modeling content of SAP Solution Composer and several real-world business scenarios.

Nitroglycerin provocation in normal subjects is not a useful human migraine model?

DEFF Research Database (Denmark)

Tvedskov, J F; Iversen, Helle Klingenberg; Olesen, J

2010-01-01

Provoking delayed migraine with nitroglycerin in migraine sufferers is a cumbersome model. Patients are difficult to recruit, migraine comes on late and variably and only 50-80% of patients develop an attack. A model using normal volunteers would be much more useful, but it should be validated...... aspirin 1000 mg, zolmitriptan 5 mg or placebo to normal healthy volunteers. The design was double-blind, placebo-controlled three-way crossover. Our hypothesis was that these drugs would be effective in the treatment of the mild constant headache induced by long-lasting GTN infusion. The headaches did...... experiment suggests that headache caused by direct nitric oxide (NO) action in the continued presence of NO is very resistance to analgesics and to specific acute migraine treatments. This suggests that NO works very deep in the cascade of events associated with vascular headache, whereas tested drugs work...

Nonepileptic seizures under levetiracetam therapy: a case report of forced normalization process

Directory of Open Access Journals (Sweden)

Anzellotti F

2014-05-01

Full Text Available Francesca Anzellotti, Raffaella Franciotti, Holta Zhuzhuni, Aurelio D'Amico, Astrid Thomas, Marco Onofrj Department of Neuroscience and Imaging, Aging Research Centre, Gabriele d'Annunzio University Foundation, Gabriele d'Annunzio University, Chieti, Italy Abstract: Nonepileptic seizures (NES apparently look like epileptic seizures, but are not associated with ictal electrical discharges in the brain. NES constitute one of the most important differential diagnoses of epilepsy. They have been recognized as a distinctive clinical phenomenon for centuries, and video/electroencephalogram monitoring has allowed clinicians to make near-certain diagnoses. NES are supposedly unrelated to organic brain lesions, and despite the preponderance of a psychiatric/psychological context, they may have an iatrogenic origin. We report a patient with NES precipitated by levetiracetam therapy; in this case, NES was observed during the disappearance of epileptiform discharges from the routine video/electroencephalogram. We discuss the possible mechanisms underlying NES with regard to alternative psychoses associated with the phenomenon of the forced normalization process. Keywords: nonepileptic seizures, forced normalization, levetiracetam, behavioral side effects

Business Process Modeling: Perceived Benefits

Science.gov (United States)

Indulska, Marta; Green, Peter; Recker, Jan; Rosemann, Michael

The process-centered design of organizations and information systems is globally seen as an appropriate response to the increased economic pressure on organizations. At the methodological core of process-centered management is process modeling. However, business process modeling in large initiatives can be a time-consuming and costly exercise, making it potentially difficult to convince executive management of its benefits. To date, and despite substantial interest and research in the area of process modeling, the understanding of the actual benefits of process modeling in academia and practice is limited. To address this gap, this paper explores the perception of benefits derived from process modeling initiatives, as reported through a global Delphi study. The study incorporates the views of three groups of stakeholders - academics, practitioners and vendors. Our findings lead to the first identification and ranking of 19 unique benefits associated with process modeling. The study in particular found that process modeling benefits vary significantly between practitioners and academics. We argue that the variations may point to a disconnect between research projects and practical demands.

Normal and abnormal neuronal migration in the developing cerebral cortex.

Science.gov (United States)

Sun, Xue-Zhi; Takahashi, Sentaro; Cui, Chun; Zhang, Rui; Sakata-Haga, Hiromi; Sawada, Kazuhiko; Fukui, Yoshihiro

2002-08-01

Neuronal migration is the critical cellular process which initiates histogenesis of cerebral cortex. Migration involves a series of complex cell interactions and transformation. After completing their final mitosis, neurons migrate from the ventricular zone into the cortical plate, and then establish neuronal lamina and settle onto the outermost layer, forming an "inside-out" gradient of maturation. This process is guided by radial glial fibers, requires proper receptors, ligands, other unknown extracellular factors, and local signaling to stop neuronal migration. This process is also highly sensitive to various physical, chemical and biological agents as well as to genetic mutations. Any disturbance of the normal process may result in neuronal migration disorder. Such neuronal migration disorder is believed as major cause of both gross brain malformation and more special cerebral structural and functional abnormalities in experimental animals and in humans. An increasing number of instructive studies on experimental models and several genetic model systems of neuronal migration disorder have established the foundation of cortex formation and provided deeper insights into the genetic and molecular mechanisms underlying normal and abnormal neuronal migration.

Relating normalization to neuronal populations across cortical areas.

Science.gov (United States)

Ruff, Douglas A; Alberts, Joshua J; Cohen, Marlene R

2016-09-01

Normalization, which divisively scales neuronal responses to multiple stimuli, is thought to underlie many sensory, motor, and cognitive processes. In every study where it has been investigated, neurons measured in the same brain area under identical conditions exhibit a range of normalization, ranging from suppression by nonpreferred stimuli (strong normalization) to additive responses to combinations of stimuli (no normalization). Normalization has been hypothesized to arise from interactions between neuronal populations, either in the same or different brain areas, but current models of normalization are not mechanistic and focus on trial-averaged responses. To gain insight into the mechanisms underlying normalization, we examined interactions between neurons that exhibit different degrees of normalization. We recorded from multiple neurons in three cortical areas while rhesus monkeys viewed superimposed drifting gratings. We found that neurons showing strong normalization shared less trial-to-trial variability with other neurons in the same cortical area and more variability with neurons in other cortical areas than did units with weak normalization. Furthermore, the cortical organization of normalization was not random: neurons recorded on nearby electrodes tended to exhibit similar amounts of normalization. Together, our results suggest that normalization reflects a neuron's role in its local network and that modulatory factors like normalization share the topographic organization typical of sensory tuning properties. Copyright © 2016 the American Physiological Society.

Improved Discovery of Molecular Interactions in Genome-Scale Data with Adaptive Model-Based Normalization

Science.gov (United States)

Brown, Patrick O.

2013-01-01

Background High throughput molecular-interaction studies using immunoprecipitations (IP) or affinity purifications are powerful and widely used in biology research. One of many important applications of this method is to identify the set of RNAs that interact with a particular RNA-binding protein (RBP). Here, the unique statistical challenge presented is to delineate a specific set of RNAs that are enriched in one sample relative to another, typically a specific IP compared to a non-specific control to model background. The choice of normalization procedure critically impacts the number of RNAs that will be identified as interacting with an RBP at a given significance threshold – yet existing normalization methods make assumptions that are often fundamentally inaccurate when applied to IP enrichment data. Methods In this paper, we present a new normalization methodology that is specifically designed for identifying enriched RNA or DNA sequences in an IP. The normalization (called adaptive or AD normalization) uses a basic model of the IP experiment and is not a variant of mean, quantile, or other methodology previously proposed. The approach is evaluated statistically and tested with simulated and empirical data. Results and Conclusions The adaptive (AD) normalization method results in a greatly increased range in the number of enriched RNAs identified, fewer false positives, and overall better concordance with independent biological evidence, for the RBPs we analyzed, compared to median normalization. The approach is also applicable to the study of pairwise RNA, DNA and protein interactions such as the analysis of transcription factors via chromatin immunoprecipitation (ChIP) or any other experiments where samples from two conditions, one of which contains an enriched subset of the other, are studied. PMID:23349766

A model for the analysis of a normal evolution scenarios for a deep geological granite repository for high-level radioactive waste

International Nuclear Information System (INIS)

Cormenzana Lopez, J.L.; Cunado, M.A.; Lopez, M.T.

1996-01-01

The methodology usually used to evaluate the behaviour of deep geological repositories for high-level radioactive wastes comprises three phases: Identification of factors (processes, characteristics and events) that can affect the repository. Generation of scenarios. In general, a normal evolution scenario (Reference Scenario) and various disruptive scenarios (earthquake, human intrusion, etc) are considered. Evaluation of the behaviour of the repository in each scenario. The normal evolution scenario taking into account all factors with a high probability of occurrence is the first to be analysed. The performance assessment of behaviour being carried out by ENRESA for the AGP Granite has led to the identification of 63 of these factors. To analyse repository behaviour in the normal evolution scenario, it is necessary to first of all create an integrated model of the global system. This is a qualitative model including the 63 factors identified. For a global view of a such a complex system, it is very useful to graphically display the relationship between factors in an Influence Diagram. This paper shows the Influence Diagram used in the analysis of the AGP Granite Reference Scenario. (Author)

Thermal modelling of normal distributed nanoparticles through thickness in an inorganic material matrix

Science.gov (United States)

Latré, S.; Desplentere, F.; De Pooter, S.; Seveno, D.

2017-10-01

Nanoscale materials showing superior thermal properties have raised the interest of the building industry. By adding these materials to conventional construction materials, it is possible to decrease the total thermal conductivity by almost one order of magnitude. This conductivity is mainly influenced by the dispersion quality within the matrix material. At the industrial scale, the main challenge is to control this dispersion to reduce or even eliminate thermal bridges. This allows to reach an industrially relevant process to balance out the high material cost and their superior thermal insulation properties. Therefore, a methodology is required to measure and describe these nanoscale distributions within the inorganic matrix material. These distributions are either random or normally distributed through thickness within the matrix material. We show that the influence of these distributions is meaningful and modifies the thermal conductivity of the building material. Hence, this strategy will generate a thermal model allowing to predict the thermal behavior of the nanoscale particles and their distributions. This thermal model will be validated by the hot wire technique. For the moment, a good correlation is found between the numerical results and experimental data for a randomly distributed form of nanoparticles in all directions.

Process Cost Modeling for Multi-Disciplinary Design Optimization

Science.gov (United States)

Bao, Han P.; Freeman, William (Technical Monitor)

2002-01-01

For early design concepts, the conventional approach to cost is normally some kind of parametric weight-based cost model. There is now ample evidence that this approach can be misleading and inaccurate. By the nature of its development, a parametric cost model requires historical data and is valid only if the new design is analogous to those for which the model was derived. Advanced aerospace vehicles have no historical production data and are nowhere near the vehicles of the past. Using an existing weight-based cost model would only lead to errors and distortions of the true production cost. This report outlines the development of a process-based cost model in which the physical elements of the vehicle are costed according to a first-order dynamics model. This theoretical cost model, first advocated by early work at MIT, has been expanded to cover the basic structures of an advanced aerospace vehicle. Elemental costs based on the geometry of the design can be summed up to provide an overall estimation of the total production cost for a design configuration. This capability to directly link any design configuration to realistic cost estimation is a key requirement for high payoff MDO problems. Another important consideration in this report is the handling of part or product complexity. Here the concept of cost modulus is introduced to take into account variability due to different materials, sizes, shapes, precision of fabrication, and equipment requirements. The most important implication of the development of the proposed process-based cost model is that different design configurations can now be quickly related to their cost estimates in a seamless calculation process easily implemented on any spreadsheet tool. In successive sections, the report addresses the issues of cost modeling as follows. First, an introduction is presented to provide the background for the research work. Next, a quick review of cost estimation techniques is made with the intention to

Strength of Gamma Rhythm Depends on Normalization

Science.gov (United States)

Ray, Supratim; Ni, Amy M.; Maunsell, John H. R.

2013-01-01

Neuronal assemblies often exhibit stimulus-induced rhythmic activity in the gamma range (30–80 Hz), whose magnitude depends on the attentional load. This has led to the suggestion that gamma rhythms form dynamic communication channels across cortical areas processing the features of behaviorally relevant stimuli. Recently, attention has been linked to a normalization mechanism, in which the response of a neuron is suppressed (normalized) by the overall activity of a large pool of neighboring neurons. In this model, attention increases the excitatory drive received by the neuron, which in turn also increases the strength of normalization, thereby changing the balance of excitation and inhibition. Recent studies have shown that gamma power also depends on such excitatory–inhibitory interactions. Could modulation in gamma power during an attention task be a reflection of the changes in the underlying excitation–inhibition interactions? By manipulating the normalization strength independent of attentional load in macaque monkeys, we show that gamma power increases with increasing normalization, even when the attentional load is fixed. Further, manipulations of attention that increase normalization increase gamma power, even when they decrease the firing rate. Thus, gamma rhythms could be a reflection of changes in the relative strengths of excitation and normalization rather than playing a functional role in communication or control. PMID:23393427

Changes of regional cerebral glucose metabolism in normal aging process : A study with FDG PET

Energy Technology Data Exchange (ETDEWEB)

Yoon, Joon Kee; Kim, Sang Eun; Lee, Kyung Han; Choi, Yong; Choe, Yearn Seong; Kim, Byung Tae [Sungkyunkwan Univ., School of Medicine, Seoul (Korea, Republic of)

2001-08-01

Normal aging results in detectable changes in the brain structure and function. We evaluated the changes of regional cerebral glucose metabolism in the normal aging process with FDG PET. Brain PET images were obtained in 44 healthy volunteers (age range 20-69'y'; M:F = 29:15) who had no history of neuropsychiatric disorders. On 6 representative transaxial images, ROls were drawn in the cortical and subcortical areas. Regional FDG uptake was normalized using whole brain uptake to adjust for the injection dose and correct for nonspecific declines of glucose metabolism affecting all brain areas equally. In the prefrontal, temporoparietal and primary sensorimotor cortex, the normalized FDG uptake (NFU) reached a peak In subjects in their 30s. The NFU in the prefrontal and primary sensorimotor cortex declined with age after 30s at a rate of 3.15%/decade and 1.93%/decade, respectively. However, the NFU in the lernporoparietal cortex did not change significantly with age after 30s. The anterior (prefrontal) posterior (temporoparietal) gradient peaked in subjects in their 30s and declined with age the reafter at a rate of 35%/decade. The NFU in the caudate nucleus was decreased with age after 20s at a rate of 2.39%/decade. In the primary visual cortex, putamen, and thalamus, the NFU values did not change significantly throughout the ages covered. These patterns were not significantly different between right and left cerebral hemispheres. Of interest was that the NFU in the left cerebellar cortex was increased with age after 20s at a rate of 2.86%/decade. These data demonstrate regional variation of the age-related changes in the cerebral glucose metabolism, with the most prominent age-related decline of metabolism in the prefrontal cortex. The increase in the cerebellar metabolism with age might reflect a process of neuronal plasticity associated with aging.

Changes of regional cerebral glucose metabolism in normal aging process : A study with FDG PET

International Nuclear Information System (INIS)

Yoon, Joon Kee; Kim, Sang Eun; Lee, Kyung Han; Choi, Yong; Choe, Yearn Seong; Kim, Byung Tae

2001-01-01

Normal aging results in detectable changes in the brain structure and function. We evaluated the changes of regional cerebral glucose metabolism in the normal aging process with FDG PET. Brain PET images were obtained in 44 healthy volunteers (age range 20-69'y'; M:F = 29:15) who had no history of neuropsychiatric disorders. On 6 representative transaxial images, ROls were drawn in the cortical and subcortical areas. Regional FDG uptake was normalized using whole brain uptake to adjust for the injection dose and correct for nonspecific declines of glucose metabolism affecting all brain areas equally. In the prefrontal, temporoparietal and primary sensorimotor cortex, the normalized FDG uptake (NFU) reached a peak In subjects in their 30s. The NFU in the prefrontal and primary sensorimotor cortex declined with age after 30s at a rate of 3.15%/decade and 1.93%/decade, respectively. However, the NFU in the lernporoparietal cortex did not change significantly with age after 30s. The anterior (prefrontal) posterior (temporoparietal) gradient peaked in subjects in their 30s and declined with age the reafter at a rate of 35%/decade. The NFU in the caudate nucleus was decreased with age after 20s at a rate of 2.39%/decade. In the primary visual cortex, putamen, and thalamus, the NFU values did not change significantly throughout the ages covered. These patterns were not significantly different between right and left cerebral hemispheres. Of interest was that the NFU in the left cerebellar cortex was increased with age after 20s at a rate of 2.86%/decade. These data demonstrate regional variation of the age-related changes in the cerebral glucose metabolism, with the most prominent age-related decline of metabolism in the prefrontal cortex. The increase in the cerebellar metabolism with age might reflect a process of neuronal plasticity associated with aging

Effect of care management program structure on implementation: a normalization process theory analysis.

Science.gov (United States)

Holtrop, Jodi Summers; Potworowski, Georges; Fitzpatrick, Laurie; Kowalk, Amy; Green, Lee A

2016-08-15

Care management in primary care can be effective in helping patients with chronic disease improve their health status, however, primary care practices are often challenged with implementation. Further, there are different ways to structure care management that may make implementation more or less successful. Normalization process theory (NPT) provides a means of understanding how a new complex intervention can become routine (normalized) in practice. In this study, we used NPT to understand how care management structure affected how well care management became routine in practice. Data collection involved semi-structured interviews and observations conducted at 25 practices in five physician organizations in Michigan, USA. Practices were selected to reflect variation in physician organizations, type of care management program, and degree of normalization. Data were transcribed, qualitatively coded and analyzed, initially using an editing approach and then a template approach with NPT as a guiding framework. Seventy interviews and 25 observations were completed. Two key structures for care management organization emerged: practice-based care management where the care managers were embedded in the practice as part of the practice team; and centralized care management where the care managers worked independently of the practice work flow and was located outside the practice. There were differences in normalization of care management across practices. Practice-based care management was generally better normalized as compared to centralized care management. Differences in normalization were well explained by the NPT, and in particular the collective action construct. When care managers had multiple and flexible opportunities for communication (interactional workability), had the requisite knowledge, skills, and personal characteristics (skill set workability), and the organizational support and resources (contextual integration), a trusting professional relationship

WWTP Process Tank Modelling

DEFF Research Database (Denmark)

Laursen, Jesper

The present thesis considers numerical modeling of activated sludge tanks on municipal wastewater treatment plants. Focus is aimed at integrated modeling where the detailed microbiological model the Activated Sludge Model 3 (ASM3) is combined with a detailed hydrodynamic model based on a numerical...... solution of the Navier-Stokes equations in a multiphase scheme. After a general introduction to the activated sludge tank as a system, the activated sludge tank model is gradually setup in separate stages. The individual sub-processes that are often occurring in activated sludge tanks are initially...... hydrofoil shaped propellers. These two sub-processes deliver the main part of the supplied energy to the activated sludge tank, and for this reason they are important for the mixing conditions in the tank. For other important processes occurring in the activated sludge tank, existing models and measurements...

Semi-empirical models for the estimation of clear sky solar global and direct normal irradiances in the tropics

International Nuclear Information System (INIS)

Janjai, S.; Sricharoen, K.; Pattarapanitchai, S.

2011-01-01

Highlights: → New semi-empirical models for predicting clear sky irradiance were developed. → The proposed models compare favorably with other empirical models. → Performance of proposed models is comparable with that of widely used physical models. → The proposed models have advantage over the physical models in terms of simplicity. -- Abstract: This paper presents semi-empirical models for estimating global and direct normal solar irradiances under clear sky conditions in the tropics. The models are based on a one-year period of clear sky global and direct normal irradiances data collected at three solar radiation monitoring stations in Thailand: Chiang Mai (18.78 o N, 98.98 o E) located in the North of the country, Nakhon Pathom (13.82 o N, 100.04 o E) in the Centre and Songkhla (7.20 o N, 100.60 o E) in the South. The models describe global and direct normal irradiances as functions of the Angstrom turbidity coefficient, the Angstrom wavelength exponent, precipitable water and total column ozone. The data of Angstrom turbidity coefficient, wavelength exponent and precipitable water were obtained from AERONET sunphotometers, and column ozone was retrieved from the OMI/AURA satellite. Model validation was accomplished using data from these three stations for the data periods which were not included in the model formulation. The models were also validated against an independent data set collected at Ubon Ratchathani (15.25 o N, 104.87 o E) in the Northeast. The global and direct normal irradiances calculated from the models and those obtained from measurements are in good agreement, with the root mean square difference (RMSD) of 7.5% for both global and direct normal irradiances. The performance of the models was also compared with that of other models. The performance of the models compared favorably with that of empirical models. Additionally, the accuracy of irradiances predicted from the proposed model are comparable with that obtained from some

Implementation of the Business Process Modelling Notation (BPMN) in the modelling of anatomic pathology processes.

Science.gov (United States)

Rojo, Marcial García; Rolón, Elvira; Calahorra, Luis; García, Felix Oscar; Sánchez, Rosario Paloma; Ruiz, Francisco; Ballester, Nieves; Armenteros, María; Rodríguez, Teresa; Espartero, Rafael Martín

2008-07-15

Process orientation is one of the essential elements of quality management systems, including those in use in healthcare. Business processes in hospitals are very complex and variable. BPMN (Business Process Modelling Notation) is a user-oriented language specifically designed for the modelling of business (organizational) processes. Previous experiences of the use of this notation in the processes modelling within the Pathology in Spain or another country are not known. We present our experience in the elaboration of the conceptual models of Pathology processes, as part of a global programmed surgical patient process, using BPMN. With the objective of analyzing the use of BPMN notation in real cases, a multidisciplinary work group was created, including software engineers from the Dep. of Technologies and Information Systems from the University of Castilla-La Mancha and health professionals and administrative staff from the Hospital General de Ciudad Real. The work in collaboration was carried out in six phases: informative meetings, intensive training, process selection, definition of the work method, process describing by hospital experts, and process modelling. The modelling of the processes of Anatomic Pathology is presented using BPMN. The presented subprocesses are those corresponding to the surgical pathology examination of the samples coming from operating theatre, including the planning and realization of frozen studies. The modelling of Anatomic Pathology subprocesses has allowed the creation of an understandable graphical model, where management and improvements are more easily implemented by health professionals.

Experimental Modeling of VHTR Plenum Flows during Normal Operation and Pressurized Conduction Cooldown

Energy Technology Data Exchange (ETDEWEB)

Glenn E McCreery; Keith G Condie

2006-09-01

The Very High Temperature Reactor (VHTR) is the leading candidate for the Next Generation Nuclear Power (NGNP) Project in the U.S. which has the goal of demonstrating the production of emissions free electricity and hydrogen by 2015. The present document addresses experimental modeling of flow and thermal mixing phenomena of importance during normal or reduced power operation and during a loss of forced reactor cooling (pressurized conduction cooldown) scenario. The objectives of the experiments are, 1), provide benchmark data for assessment and improvement of codes proposed for NGNP designs and safety studies, and, 2), obtain a better understanding of related phenomena, behavior and needs. Physical models of VHTR vessel upper and lower plenums which use various working fluids to scale phenomena of interest are described. The models may be used to both simulate natural convection conditions during pressurized conduction cooldown and turbulent lower plenum flow during normal or reduced power operation.

modeling grinding modeling grinding processes as micro processes

African Journals Online (AJOL)

eobe

industrial precision grinding processes are cylindrical, center less and ... Several model shave been proposed and used to study grinding ..... grinding force for the two cases were 9.07237N/mm ..... International Journal of Machine Tools &.

Proteolytic processing of connective tissue growth factor in normal ocular tissues and during corneal wound healing.

Science.gov (United States)

Robinson, Paulette M; Smith, Tyler S; Patel, Dilan; Dave, Meera; Lewin, Alfred S; Pi, Liya; Scott, Edward W; Tuli, Sonal S; Schultz, Gregory S

2012-12-13

Connective tissue growth factor (CTGF) is a fibrogenic cytokine that is up-regulated by TGF-β and mediates most key fibrotic actions of TGF-β, including stimulation of synthesis of extracellular matrix and differentiation of fibroblasts into myofibroblasts. This study addresses the role of proteolytic processing of CTGF in human corneal fibroblasts (HCF) stimulated with TGF-β, normal ocular tissues and wounded corneas. Proteolytic processing of CTGF in HCF cultures, normal animal eyes, and excimer laser wounded rat corneas were examined by Western blot. The identity of a 21-kDa band was determined by tandem mass spectrometry, and possible alternative splice variants of CTGF were assessed by 5' Rapid Amplification of cDNA Ends (RACE). HCF stimulated by TGF-β contained full length 38-kDa CTGF and fragments of 25, 21, 18, and 13 kDa, while conditioned medium contained full length 38- and a 21-kDa fragment of CTGF that contained the middle "hinge" region of CTGF. Fragmentation of recombinant CTGF incubated in HCF extracts was blocked by the aspartate protease inhibitor, pepstatin. Normal mouse, rat, and rabbit whole eyes and rabbit ocular tissues contained abundant amounts of C-terminal 25- and 21-kDa fragments and trace amounts of 38-kDa CTGF, although no alternative transcripts were detected. All forms of CTGF (38, 25, and 21 kDa) were detected during healing of excimer ablated rat corneas, peaking on day 11. Proteolytic processing of 38-kDa CTGF occurs during corneal wound healing, which may have important implications in regulation of corneal scar formation.

Arrays of surface-normal electroabsorption modulators for the generation and signal processing of microwave photonics signals

NARCIS (Netherlands)

Noharet, Bertrand; Wang, Qin; Platt, Duncan; Junique, Stéphane; Marpaung, D.A.I.; Roeloffzen, C.G.H.

2011-01-01

The development of an array of 16 surface-normal electroabsorption modulators operating at 1550nm is presented. The modulator array is dedicated to the generation and processing of microwave photonics signals, targeting a modulation bandwidth in excess of 5GHz. The hybrid integration of the

Modeling the Circle of Willis Using Electrical Analogy Method under both Normal and Pathological Circumstances

Science.gov (United States)

Abdi, Mohsen; Karimi, Alireza; Navidbakhsh, Mahdi; Rahmati, Mohammadali; Hassani, Kamran; Razmkon, Ali

2013-01-01

Background and objective: The circle of Willis (COW) supports adequate blood supply to the brain. The cardiovascular system, in the current study, is modeled using an equivalent electronic system focusing on the COW. Methods: In our previous study we used 42 compartments to model whole cardiovascular system. In the current study, nevertheless, we extended our model by using 63 compartments to model whole CS. Each cardiovascular artery is modeled using electrical elements, including resistor, capacitor, and inductor. The MATLAB Simulink software is used to obtain the left and right ventricles pressure as well as pressure distribution at efferent arteries of the circle of Willis. Firstly, the normal operation of the system is shown and then the stenosis of cerebral arteries is induced in the circuit and, consequently, the effects are studied. Results: In the normal condition, the difference between pressure distribution of right and left efferent arteries (left and right ACA–A2, left and right MCA, left and right PCA–P2) is calculated to indicate the effect of anatomical difference between left and right sides of supplying arteries of the COW. In stenosis cases, the effect of internal carotid artery occlusion on efferent arteries pressure is investigated. The modeling results are verified by comparing to the clinical observation reported in the literature. Conclusion: We believe the presented model is a useful tool for representing the normal operation of the cardiovascular system and study of the pathologies. PMID:25505747

Modeling of column apparatus processes

CERN Document Server

Boyadjiev, Christo; Boyadjiev, Boyan; Popova-Krumova, Petya

2016-01-01

This book presents a new approach for the modeling of chemical and interphase mass transfer processes in industrial column apparatuses, using convection-diffusion and average-concentration models. The convection-diffusion type models are used for a qualitative analysis of the processes and to assess the main, small and slight physical effects, and then reject the slight effects. As a result, the process mechanism can be identified. It also introduces average concentration models for quantitative analysis, which use the average values of the velocity and concentration over the cross-sectional area of the column. The new models are used to analyze different processes (simple and complex chemical reactions, absorption, adsorption and catalytic reactions), and make it possible to model the processes of gas purification with sulfur dioxide, which form the basis of several patents.

Wavefield extrapolation in caustic-free normal ray coordinates

KAUST Repository

Ma, Xuxin

2012-11-04

Normal ray coordinates are conventionally constructed from ray tracing, which inherently requires smooth velocity profiles. To use rays as coordinates, the velocities have to be smoothed further to avoid caustics, which is detrimental to the mapping process. Solving the eikonal equation numerically for a line source at the surface provides a platform to map normal rays in complex unsmoothed velocity models and avoid caustics. We implement reverse-time migration (RTM) and downward continuation in the new ray coordinate system, which allows us to obtain efficient images and avoid some of the dip limitations of downward continuation.

Construction and updating of event models in auditory event processing.

Science.gov (United States)

Huff, Markus; Maurer, Annika E; Brich, Irina; Pagenkopf, Anne; Wickelmaier, Florian; Papenmeier, Frank

2018-02-01

Humans segment the continuous stream of sensory information into distinct events at points of change. Between 2 events, humans perceive an event boundary. Present theories propose changes in the sensory information to trigger updating processes of the present event model. Increased encoding effort finally leads to a memory benefit at event boundaries. Evidence from reading time studies (increased reading times with increasing amount of change) suggest that updating of event models is incremental. We present results from 5 experiments that studied event processing (including memory formation processes and reading times) using an audio drama as well as a transcript thereof as stimulus material. Experiments 1a and 1b replicated the event boundary advantage effect for memory. In contrast to recent evidence from studies using visual stimulus material, Experiments 2a and 2b found no support for incremental updating with normally sighted and blind participants for recognition memory. In Experiment 3, we replicated Experiment 2a using a written transcript of the audio drama as stimulus material, allowing us to disentangle encoding and retrieval processes. Our results indicate incremental updating processes at encoding (as measured with reading times). At the same time, we again found recognition performance to be unaffected by the amount of change. We discuss these findings in light of current event cognition theories. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

Use of SAMC for Bayesian analysis of statistical models with intractable normalizing constants

KAUST Repository

Jin, Ick Hoon; Liang, Faming

2014-01-01

Statistical inference for the models with intractable normalizing constants has attracted much attention. During the past two decades, various approximation- or simulation-based methods have been proposed for the problem, such as the Monte Carlo

Investigating the Process of Process Modeling with Eye Movement Analysis

OpenAIRE

Pinggera, Jakob; Furtner, Marco; Martini, Markus; Sachse, Pierre; Reiter, Katharina; Zugal, Stefan; Weber, Barbara

2015-01-01

Research on quality issues of business process models has recently begun to explore the process of creating process models by analyzing the modeler's interactions with the modeling environment. In this paper we aim to complement previous insights on the modeler's modeling behavior with data gathered by tracking the modeler's eye movements when engaged in the act of modeling. We present preliminary results and outline directions for future research to triangulate toward a more comprehensive un...

Physics of collisionless scrape-off-layer plasma during normal and off-normal Tokamak operating conditions

International Nuclear Information System (INIS)

Hassanein, A.; Konkashbaev, I.

1999-01-01

The structure of a collisionless scrape-off-layer (SOL) plasma in tokamak reactors is being studied to define the electron distribution function and the corresponding sheath potential between the divertor plate and the edge plasma. The collisionless model is shown to be valid during the thermal phase of a plasma disruption, as well as during the newly desired low-recycling normal phase of operation with low-density, high-temperature, edge plasma conditions. An analytical solution is developed by solving the Fokker-Planck equation for electron distribution and balance in the SOL. The solution is in good agreement with numerical studies using Monte-Carlo methods. The analytical solutions provide an insight to the role of different physical and geometrical processes in a collisionless SOL during disruptions and during the enhanced phase of normal operation over a wide range of parameters

What makes process models understandable?

NARCIS (Netherlands)

Mendling, J.; Reijers, H.A.; Cardoso, J.; Alonso, G.; Dadam, P.; Rosemann, M.

2007-01-01

Despite that formal and informal quality aspects are of significant importance to business process modeling, there is only little empirical work reported on process model quality and its impact factors. In this paper we investigate understandability as a proxy for quality of process models and focus

Modeling the Object-Oriented Software Process: OPEN and the Unified Process

NARCIS (Netherlands)

van den Berg, Klaas; Aksit, Mehmet; van den Broek, P.M.

A short introduction to software process modeling is presented, particularly object-oriented modeling. Two major industrial process models are discussed: the OPEN model and the Unified Process model. In more detail, the quality assurance in the Unified Process tool (formally called Objectory) is

Modeling and stress analyses of a normal foot-ankle and a prosthetic foot-ankle complex.

Science.gov (United States)

Ozen, Mustafa; Sayman, Onur; Havitcioglu, Hasan

2013-01-01

Total ankle replacement (TAR) is a relatively new concept and is becoming more popular for treatment of ankle arthritis and fractures. Because of the high costs and difficulties of experimental studies, the developments of TAR prostheses are progressing very slowly. For this reason, the medical imaging techniques such as CT, and MR have become more and more useful. The finite element method (FEM) is a widely used technique to estimate the mechanical behaviors of materials and structures in engineering applications. FEM has also been increasingly applied to biomechanical analyses of human bones, tissues and organs, thanks to the development of both the computing capabilities and the medical imaging techniques. 3-D finite element models of the human foot and ankle from reconstruction of MR and CT images have been investigated by some authors. In this study, data of geometries (used in modeling) of a normal and a prosthetic foot and ankle were obtained from a 3D reconstruction of CT images. The segmentation software, MIMICS was used to generate the 3D images of the bony structures, soft tissues and components of prosthesis of normal and prosthetic ankle-foot complex. Except the spaces between the adjacent surface of the phalanges fused, metatarsals, cuneiforms, cuboid, navicular, talus and calcaneus bones, soft tissues and components of prosthesis were independently developed to form foot and ankle complex. SOLIDWORKS program was used to form the boundary surfaces of all model components and then the solid models were obtained from these boundary surfaces. Finite element analyses software, ABAQUS was used to perform the numerical stress analyses of these models for balanced standing position. Plantar pressure and von Mises stress distributions of the normal and prosthetic ankles were compared with each other. There was a peak pressure increase at the 4th metatarsal, first metatarsal and talus bones and a decrease at the intermediate cuneiform and calcaneus bones, in

Migration using a transversely isotropic medium with symmetry normal to the reflector dip

KAUST Repository

Alkhalifah, Tariq Ali; Sava, P.

2011-01-01

A transversely isotropic (TI) model in which the tilt is constrained to be normal to the dip (DTI model) allows for simplifications in the imaging and velocity model building efforts as compared to a general TI (TTI) model. Although this model cannot be represented physically in all situations, for example, in the case of conflicting dips, it handles arbitrary reflector orientations under the assumption of symmetry axis normal to the dip. Using this assumption, we obtain efficient downward continuation algorithms compared to the general TTI ones, by utilizing the reflection features of such a model. Phase-shift migration can be easily extended to approximately handle lateral inhomogeneity using, for example, the split-step approach. This is possible because, unlike the general TTI case, the DTI model reduces to VTI for zero dip. These features enable a process in which we can extract velocity information by including tools that expose inaccuracies in the velocity model in the downward continuation process. We test this model on synthetic data corresponding to a general TTI medium and show its resilience. 2011 Tariq Alkhalifah and Paul Sava.

Modeling the Object-Oriented Software Process: OPEN and the Unified Process

OpenAIRE

van den Berg, Klaas; Aksit, Mehmet; van den Broek, P.M.

1999-01-01

A short introduction to software process modeling is presented, particularly object-oriented modeling. Two major industrial process models are discussed: the OPEN model and the Unified Process model. In more detail, the quality assurance in the Unified Process tool (formally called Objectory) is reviewed.

Local stem cell depletion model for normal tissue damage

International Nuclear Information System (INIS)

Yaes, R.J.; Keland, A.

1987-01-01

The hypothesis that radiation causes normal tissue damage by completely depleting local regions of tissue of viable stem cells leads to a simple mathematical model for such damage. In organs like skin and spinal cord where destruction of a small volume of tissue leads to a clinically apparent complication, the complication probability is expressed as a function of dose, volume and stem cell number by a simple triple negative exponential function analogous to the double exponential function of Munro and Gilbert for tumor control. The steep dose response curves for radiation myelitis that are obtained with our model are compared with the experimental data for radiation myelitis in laboratory rats. The model can be generalized to include other types or organs, high LET radiation, fractionated courses of radiation, and cases where an organ with a heterogeneous stem cell population receives an inhomogeneous dose of radiation. In principle it would thus be possible to determine the probability of tumor control and of damage to any organ within the radiation field if the dose distribution in three dimensional space within a patient is known

Dissolution process analysis using model-free Noyes-Whitney integral equation.

Science.gov (United States)

Hattori, Yusuke; Haruna, Yoshimasa; Otsuka, Makoto

2013-02-01

Drug dissolution process of solid dosages is theoretically described by Noyes-Whitney-Nernst equation. However, the analysis of the process is demonstrated assuming some models. Normally, the model-dependent methods are idealized and require some limitations. In this study, Noyes-Whitney integral equation was proposed and applied to represent the drug dissolution profiles of a solid formulation via the non-linear least squares (NLLS) method. The integral equation is a model-free formula involving the dissolution rate constant as a parameter. In the present study, several solid formulations were prepared via changing the blending time of magnesium stearate (MgSt) with theophylline monohydrate, α-lactose monohydrate, and crystalline cellulose. The formula could excellently represent the dissolution profile, and thereby the rate constant and specific surface area could be obtained by NLLS method. Since the long time blending coated the particle surface with MgSt, it was found that the water permeation was disturbed by its layer dissociating into disintegrant particles. In the end, the solid formulations were not disintegrated; however, the specific surface area gradually increased during the process of dissolution. The X-ray CT observation supported this result and demonstrated that the rough surface was dominant as compared to dissolution, and thus, specific surface area of the solid formulation gradually increased. Copyright © 2012 Elsevier B.V. All rights reserved.

Multi-enzyme Process Modeling

DEFF Research Database (Denmark)

Andrade Santacoloma, Paloma de Gracia

are affected (in a positive or negative way) by the presence of the other enzymes and compounds in the media. In this thesis the concept of multi-enzyme in-pot term is adopted for processes that are carried out by the combination of enzymes in a single reactor and implemented at pilot or industrial scale...... features of the process and provides the information required to structure the process model by using a step-by-step procedure with the required tools and methods. In this way, this framework increases efficiency of the model development process with respect to time and resources needed (fast and effective....... In this way the model parameters that drives the main dynamic behavior can be identified and thus a better understanding of this type of processes. In order to develop, test and verify the methodology, three case studies were selected, specifically the bi-enzyme process for the production of lactobionic acid...

Process model repositories and PNML

NARCIS (Netherlands)

Hee, van K.M.; Post, R.D.J.; Somers, L.J.A.M.; Werf, van der J.M.E.M.; Kindler, E.

2004-01-01

Bringing system and process models together in repositories facilitates the interchange of model information between modelling tools, and allows the combination and interlinking of complementary models. Petriweb is a web application for managing such repositories. It supports hierarchical process

Model-based software process improvement

Science.gov (United States)

Zettervall, Brenda T.

1994-01-01

The activities of a field test site for the Software Engineering Institute's software process definition project are discussed. Products tested included the improvement model itself, descriptive modeling techniques, the CMM level 2 framework document, and the use of process definition guidelines and templates. The software process improvement model represents a five stage cyclic approach for organizational process improvement. The cycles consist of the initiating, diagnosing, establishing, acting, and leveraging phases.

Using Unified Modelling Language (UML) as a process-modelling technique for clinical-research process improvement.

Science.gov (United States)

Kumarapeli, P; De Lusignan, S; Ellis, T; Jones, B

2007-03-01

The Primary Care Data Quality programme (PCDQ) is a quality-improvement programme which processes routinely collected general practice computer data. Patient data collected from a wide range of different brands of clinical computer systems are aggregated, processed, and fed back to practices in an educational context to improve the quality of care. Process modelling is a well-established approach used to gain understanding and systematic appraisal, and identify areas of improvement of a business process. Unified modelling language (UML) is a general purpose modelling technique used for this purpose. We used UML to appraise the PCDQ process to see if the efficiency and predictability of the process could be improved. Activity analysis and thinking-aloud sessions were used to collect data to generate UML diagrams. The UML model highlighted the sequential nature of the current process as a barrier for efficiency gains. It also identified the uneven distribution of process controls, lack of symmetric communication channels, critical dependencies among processing stages, and failure to implement all the lessons learned in the piloting phase. It also suggested that improved structured reporting at each stage - especially from the pilot phase, parallel processing of data and correctly positioned process controls - should improve the efficiency and predictability of research projects. Process modelling provided a rational basis for the critical appraisal of a clinical data processing system; its potential maybe underutilized within health care.

Understanding the challenges to implementing case management for people with dementia in primary care in England: a qualitative study using Normalization Process Theory.

Science.gov (United States)

Bamford, Claire; Poole, Marie; Brittain, Katie; Chew-Graham, Carolyn; Fox, Chris; Iliffe, Steve; Manthorpe, Jill; Robinson, Louise

2014-11-08

Case management has been suggested as a way of improving the quality and cost-effectiveness of support for people with dementia. In this study we adapted and implemented a successful United States' model of case management in primary care in England. The results are reported elsewhere, but a key finding was that little case management took place. This paper reports the findings of the process evaluation which used Normalization Process Theory to understand the barriers to implementation. Ethnographic methods were used to explore the views and experiences of case management. Interviews with 49 stakeholders (patients, carers, case managers, health and social care professionals) were supplemented with observation of case managers during meetings and initial assessments with patients. Transcripts and field notes were analysed initially using the constant comparative approach and emerging themes were then mapped onto the framework of Normalization Process Theory. The primary focus during implementation was on the case managers as isolated individuals, with little attention being paid to the social or organizational context within which they worked. Barriers relating to each of the four main constructs of Normalization Process Theory were identified, with a lack of clarity over the scope and boundaries of the intervention (coherence); variable investment in the intervention (cognitive participation); a lack of resources, skills and training to deliver case management (collective action); and limited reflection and feedback on the case manager role (reflexive monitoring). Despite the intuitive appeal of case management to all stakeholders, there were multiple barriers to implementation in primary care in England including: difficulties in embedding case managers within existing well-established community networks; the challenges of protecting time for case management; and case managers' inability to identify, and act on, emerging patient and carer needs (an essential, but

Bayesian Hierarchical Scale Mixtures of Log-Normal Models for Inference in Reliability with Stochastic Constraint

Directory of Open Access Journals (Sweden)

Hea-Jung Kim

2017-06-01

Full Text Available This paper develops Bayesian inference in reliability of a class of scale mixtures of log-normal failure time (SMLNFT models with stochastic (or uncertain constraint in their reliability measures. The class is comprehensive and includes existing failure time (FT models (such as log-normal, log-Cauchy, and log-logistic FT models as well as new models that are robust in terms of heavy-tailed FT observations. Since classical frequency approaches to reliability analysis based on the SMLNFT model with stochastic constraint are intractable, the Bayesian method is pursued utilizing a Markov chain Monte Carlo (MCMC sampling based approach. This paper introduces a two-stage maximum entropy (MaxEnt prior, which elicits a priori uncertain constraint and develops Bayesian hierarchical SMLNFT model by using the prior. The paper also proposes an MCMC method for Bayesian inference in the SMLNFT model reliability and calls attention to properties of the MaxEnt prior that are useful for method development. Finally, two data sets are used to illustrate how the proposed methodology works.

Developing engineering processes through integrated modelling of product and process

DEFF Research Database (Denmark)

Nielsen, Jeppe Bjerrum; Hvam, Lars

2012-01-01

This article aims at developing an operational tool for integrated modelling of product assortments and engineering processes in companies making customer specific products. Integrating a product model in the design of engineering processes will provide a deeper understanding of the engineering...... activities as well as insight into how product features affect the engineering processes. The article suggests possible ways of integrating models of products with models of engineering processes. The models have been tested and further developed in an action research study carried out in collaboration...... with a major international engineering company....

UML in business process modeling

Directory of Open Access Journals (Sweden)

Bartosz Marcinkowski

2013-03-01

Full Text Available Selection and proper application of business process modeling methods and techniques have a significant impact on organizational improvement capabilities as well as proper understanding of functionality of information systems that shall support activity of the organization. A number of business process modeling notations were popularized in practice in recent decades. Most significant of the notations include Business Process Modeling Notation (OMG BPMN and several Unified Modeling Language (OMG UML extensions. In this paper, the assessment whether one of the most flexible and strictly standardized contemporary business process modeling notations, i.e. Rational UML Profile for Business Modeling, enable business analysts to prepare business models that are all-embracing and understandable by all the stakeholders. After the introduction, methodology of research is discussed. Section 2 presents selected case study results. The paper is concluded with a summary.

Normalized value coding explains dynamic adaptation in the human valuation process.

Science.gov (United States)

Khaw, Mel W; Glimcher, Paul W; Louie, Kenway

2017-11-28

The notion of subjective value is central to choice theories in ecology, economics, and psychology, serving as an integrated decision variable by which options are compared. Subjective value is often assumed to be an absolute quantity, determined in a static manner by the properties of an individual option. Recent neurobiological studies, however, have shown that neural value coding dynamically adapts to the statistics of the recent reward environment, introducing an intrinsic temporal context dependence into the neural representation of value. Whether valuation exhibits this kind of dynamic adaptation at the behavioral level is unknown. Here, we show that the valuation process in human subjects adapts to the history of previous values, with current valuations varying inversely with the average value of recently observed items. The dynamics of this adaptive valuation are captured by divisive normalization, linking these temporal context effects to spatial context effects in decision making as well as spatial and temporal context effects in perception. These findings suggest that adaptation is a universal feature of neural information processing and offer a unifying explanation for contextual phenomena in fields ranging from visual psychophysics to economic choice.

Automatic extraction of process categories from process model collections

NARCIS (Netherlands)

Malinova, M.; Dijkman, R.M.; Mendling, J.; Lohmann, N.; Song, M.; Wohed, P.

2014-01-01

Many organizations build up their business process management activities in an incremental way. As a result, there is no overarching structure defined at the beginning. However, as business process modeling initiatives often yield hundreds to thousands of process models, there is a growing need for

Biosphere Process Model Report

Energy Technology Data Exchange (ETDEWEB)

J. Schmitt

2000-05-25

To evaluate the postclosure performance of a potential monitored geologic repository at Yucca Mountain, a Total System Performance Assessment (TSPA) will be conducted. Nine Process Model Reports (PMRs), including this document, are being developed to summarize the technical basis for each of the process models supporting the TSPA model. These reports cover the following areas: (1) Integrated Site Model; (2) Unsaturated Zone Flow and Transport; (3) Near Field Environment; (4) Engineered Barrier System Degradation, Flow, and Transport; (5) Waste Package Degradation; (6) Waste Form Degradation; (7) Saturated Zone Flow and Transport; (8) Biosphere; and (9) Disruptive Events. Analysis/Model Reports (AMRs) contain the more detailed technical information used to support TSPA and the PMRs. The AMRs consists of data, analyses, models, software, and supporting documentation that will be used to defend the applicability of each process model for evaluating the postclosure performance of the potential Yucca Mountain repository system. This documentation will ensure the traceability of information from its source through its ultimate use in the TSPA-Site Recommendation (SR) and in the National Environmental Policy Act (NEPA) analysis processes. The objective of the Biosphere PMR is to summarize (1) the development of the biosphere model, and (2) the Biosphere Dose Conversion Factors (BDCFs) developed for use in TSPA. The Biosphere PMR does not present or summarize estimates of potential radiation doses to human receptors. Dose calculations are performed as part of TSPA and will be presented in the TSPA documentation. The biosphere model is a component of the process to evaluate postclosure repository performance and regulatory compliance for a potential monitored geologic repository at Yucca Mountain, Nevada. The biosphere model describes those exposure pathways in the biosphere by which radionuclides released from a potential repository could reach a human receptor

Biosphere Process Model Report

International Nuclear Information System (INIS)

Schmitt, J.

2000-01-01

To evaluate the postclosure performance of a potential monitored geologic repository at Yucca Mountain, a Total System Performance Assessment (TSPA) will be conducted. Nine Process Model Reports (PMRs), including this document, are being developed to summarize the technical basis for each of the process models supporting the TSPA model. These reports cover the following areas: (1) Integrated Site Model; (2) Unsaturated Zone Flow and Transport; (3) Near Field Environment; (4) Engineered Barrier System Degradation, Flow, and Transport; (5) Waste Package Degradation; (6) Waste Form Degradation; (7) Saturated Zone Flow and Transport; (8) Biosphere; and (9) Disruptive Events. Analysis/Model Reports (AMRs) contain the more detailed technical information used to support TSPA and the PMRs. The AMRs consists of data, analyses, models, software, and supporting documentation that will be used to defend the applicability of each process model for evaluating the postclosure performance of the potential Yucca Mountain repository system. This documentation will ensure the traceability of information from its source through its ultimate use in the TSPA-Site Recommendation (SR) and in the National Environmental Policy Act (NEPA) analysis processes. The objective of the Biosphere PMR is to summarize (1) the development of the biosphere model, and (2) the Biosphere Dose Conversion Factors (BDCFs) developed for use in TSPA. The Biosphere PMR does not present or summarize estimates of potential radiation doses to human receptors. Dose calculations are performed as part of TSPA and will be presented in the TSPA documentation. The biosphere model is a component of the process to evaluate postclosure repository performance and regulatory compliance for a potential monitored geologic repository at Yucca Mountain, Nevada. The biosphere model describes those exposure pathways in the biosphere by which radionuclides released from a potential repository could reach a human receptor

Conceptual models of information processing

Science.gov (United States)

Stewart, L. J.

1983-01-01

The conceptual information processing issues are examined. Human information processing is defined as an active cognitive process that is analogous to a system. It is the flow and transformation of information within a human. The human is viewed as an active information seeker who is constantly receiving, processing, and acting upon the surrounding environmental stimuli. Human information processing models are conceptual representations of cognitive behaviors. Models of information processing are useful in representing the different theoretical positions and in attempting to define the limits and capabilities of human memory. It is concluded that an understanding of conceptual human information processing models and their applications to systems design leads to a better human factors approach.

Normality in Analytical Psychology

Science.gov (United States)

Myers, Steve

2013-01-01

Although C.G. Jung’s interest in normality wavered throughout his career, it was one of the areas he identified in later life as worthy of further research. He began his career using a definition of normality which would have been the target of Foucault’s criticism, had Foucault chosen to review Jung’s work. However, Jung then evolved his thinking to a standpoint that was more aligned to Foucault’s own. Thereafter, the post Jungian concept of normality has remained relatively undeveloped by comparison with psychoanalysis and mainstream psychology. Jung’s disjecta membra on the subject suggest that, in contemporary analytical psychology, too much focus is placed on the process of individuation to the neglect of applications that consider collective processes. Also, there is potential for useful research and development into the nature of conflict between individuals and societies, and how normal people typically develop in relation to the spectrum between individuation and collectivity. PMID:25379262

Normality in Analytical Psychology

Directory of Open Access Journals (Sweden)

Steve Myers

2013-11-01

Full Text Available Although C.G. Jung’s interest in normality wavered throughout his career, it was one of the areas he identified in later life as worthy of further research. He began his career using a definition of normality which would have been the target of Foucault’s criticism, had Foucault chosen to review Jung’s work. However, Jung then evolved his thinking to a standpoint that was more aligned to Foucault’s own. Thereafter, the post Jungian concept of normality has remained relatively undeveloped by comparison with psychoanalysis and mainstream psychology. Jung’s disjecta membra on the subject suggest that, in contemporary analytical psychology, too much focus is placed on the process of individuation to the neglect of applications that consider collective processes. Also, there is potential for useful research and development into the nature of conflict between individuals and societies, and how normal people typically develop in relation to the spectrum between individuation and collectivity.

Subsequent development of the normal temperature fusion reaction. Joon kakuyugo sonogo no shinten

Energy Technology Data Exchange (ETDEWEB)

Matsumoto, T. (Hokkaido University, Sapporo (Japan). Faculty of Engineering)

1991-04-24

This paper reports on a NATTOH model made public in May 1989 by T. Matsumoto who took notice of abnormality of the normal temperature fusion reaction. The NATTO model is based on a chain reaction by hydrogen with a hydrogen-catalyzed fusion reaction which is the normal temperature fusion reaction as an elementary process. If a high temperature fusion reaction is a small-size simulation of the fusion reaction rising on the surface of the sparkling star like the sun, the normal temperature fusion reaction can be a small-size simulation of the phenomena in the last years of the star in the far distance of the space. This gives reality to the normal temperature fusion reaction. The reaction mechanism of the normal temperature fusion reaction is almost being clarified by a NATTOH model. There remain problems on a possibility of generation of unknown radioactive rays and identification of radioactive wastes, but it seems that a prospect of commercialization can be talked about now. As for the utilization as energy, sea water may be used as it is. 10 ref., 5 figs.

Improved model management with aggregated business process models

NARCIS (Netherlands)

Reijers, H.A.; Mans, R.S.; Toorn, van der R.A.

2009-01-01

Contemporary organizations invest much efforts in creating models of their business processes. This raises the issue of how to deal with large sets of process models that become available over time. This paper proposes an extension of Event-driven Process Chains, called the aggregate EPC (aEPC),

Business process modeling in healthcare.

Science.gov (United States)

Ruiz, Francisco; Garcia, Felix; Calahorra, Luis; Llorente, César; Gonçalves, Luis; Daniel, Christel; Blobel, Bernd

2012-01-01

The importance of the process point of view is not restricted to a specific enterprise sector. In the field of health, as a result of the nature of the service offered, health institutions' processes are also the basis for decision making which is focused on achieving their objective of providing quality medical assistance. In this chapter the application of business process modelling - using the Business Process Modelling Notation (BPMN) standard is described. Main challenges of business process modelling in healthcare are the definition of healthcare processes, the multi-disciplinary nature of healthcare, the flexibility and variability of the activities involved in health care processes, the need of interoperability between multiple information systems, and the continuous updating of scientific knowledge in healthcare.

Pharmacokinetic-pharmacodynamic modeling of diclofenac in normal and Freund's complete adjuvant-induced arthritic rats

Science.gov (United States)

Zhang, Jing; Li, Pei; Guo, Hai-fang; Liu, Li; Liu, Xiao-dong

2012-01-01

Aim: To characterize pharmacokinetic-pharmacodynamic modeling of diclofenac in Freund's complete adjuvant (FCA)-induced arthritic rats using prostaglandin E2 (PGE2) as a biomarker. Methods: The pharmacokinetics of diclofenac was investigated using 20-day-old arthritic rats. PGE2 level in the rats was measured using an enzyme immunoassay. A pharmacokinetic-pharmacodynamic (PK-PD) model was developed to illustrate the relationship between the plasma concentration of diclofenac and the inhibition of PGE2 production. The inhibition of diclofenac on lipopolysaccharide (LPS)-induced PGE2 production in blood cells was investigated in vitro. Results: Similar pharmacokinetic behavior of diclofenac was found both in normal and FCA-induced arthritic rats. Diclofenac significantly decreased the plasma levels of PGE2 in both normal and arthritic rats. The inhibitory effect on PGE2 levels in the plasma was in proportion to the plasma concentration of diclofenac. No delay in the onset of inhibition was observed, suggesting that the effect compartment was located in the central compartment. An inhibitory effect sigmoid Imax model was selected to characterize the relationship between the plasma concentration of diclofenac and the inhibition of PGE2 production in vivo. The Imax model was also used to illustrate the inhibition of diclofenac on LPS-induced PGE2 production in blood cells in vitro. Conclusion: Arthritis induced by FCA does not alter the pharmacokinetic behaviors of diclofenac in rats, but the pharmacodynamics of diclofenac is slightly affected. A PK-PD model characterizing an inhibitory effect sigmoid Imax can be used to fit the relationship between the plasma PGE2 and diclofenac levels in both normal rats and FCA-induced arthritic rats. PMID:22842736

Integrating textual and model-based process descriptions for comprehensive process search

NARCIS (Netherlands)

Leopold, Henrik; van der Aa, Han; Pittke, Fabian; Raffel, Manuel; Mendling, Jan; Reijers, Hajo A.

2016-01-01

Documenting business processes using process models is common practice in many organizations. However, not all process information is best captured in process models. Hence, many organizations complement these models with textual descriptions that specify additional details. The problem with this

On generalisations of the log-Normal distribution by means of a new product definition in the Kapteyn process

Science.gov (United States)

Duarte Queirós, Sílvio M.

2012-07-01

We discuss the modification of the Kapteyn multiplicative process using the q-product of Borges [E.P. Borges, A possible deformed algebra and calculus inspired in nonextensive thermostatistics, Physica A 340 (2004) 95]. Depending on the value of the index q a generalisation of the log-Normal distribution is yielded. Namely, the distribution increases the tail for small (when q1) values of the variable upon analysis. The usual log-Normal distribution is retrieved when q=1, which corresponds to the traditional Kapteyn multiplicative process. The main statistical features of this distribution as well as related random number generators and tables of quantiles of the Kolmogorov-Smirnov distance are presented. Finally, we illustrate the validity of this scenario by describing a set of variables of biological and financial origin.

Genetic Analysis of Somatic Cell Score in Danish Holsteins Using a Liability-Normal Mixture Model

DEFF Research Database (Denmark)

Madsen, P; Shariati, M M; Ødegård, J

2008-01-01

Mixture models are appealing for identifying hidden structures affecting somatic cell score (SCS) data, such as unrecorded cases of subclinical mastitis. Thus, liability-normal mixture (LNM) models were used for genetic analysis of SCS data, with the aim of predicting breeding values for such cas...

Mathematical modeling of compression processes in air-driven boosters

International Nuclear Information System (INIS)

Li Zeyu; Zhao Yuanyang; Li Liansheng; Shu Pengcheng

2007-01-01

The compressed air in normal pressure is used as the source of power of the air-driven booster. The continuous working of air-driven boosters relies on the difference of surface area between driven piston and driving piston, i.e., the different forces acting on the pistons. When the working surface area of the driving piston for providing power is greater than that of the driven piston for compressing gas, the gas in compression chamber will be compressed. On the basis of the first law of thermodynamics, the motion regulation of piston is analyzed and the mathematical model of compression processes is set up. Giving a calculating example, the vary trends of gas pressure and pistons' move in working process of booster have been gotten. The change of parameters at different working conditions is also calculated and compared. And the corresponding results can be referred in the design of air-driven boosters

Process modeling for Humanities: tracing and analyzing scientific processes

OpenAIRE

Hug , Charlotte; Salinesi , Camille; Deneckere , Rebecca; Lamasse , Stéphane

2011-01-01

International audience; This paper concerns epistemology and the understanding of research processes in Humanities, such as Archaeology. We believe that to properly understand research processes, it is essential to trace them. The collected traces depend on the process model established, which has to be as accurate as possible to exhaustively record the traces. In this paper, we briefly explain why the existing process models for Humanities are not sufficient to represent traces. We then pres...

Quench pressure, thermal expulsion, and normal zone propagation in internally cooled superconductors

International Nuclear Information System (INIS)

Dresner, L.

1988-01-01

When a nonrecovering normal zone appears in an internally cooled superconductor, the pressure in the conductor rises, helium is expelled from its ends, and the normal zone grows in size. This paper presents a model of these processes that allows calculation of the pressure, the expulsion velocity, and the propagation velocity with simple formulas. The model is intended to apply to conductors such as the cable-in-conduit conductor of the Westinghouse LCT (WH-LCT) coil, the helium volumes of which have very large length-to-diameter ratios (3 /times/ 10 5 ). The predictions of the model agree with the rather limited data available from propagation experiments carried out on the WH-LCT coil. 3 refs., 1 fig

Modeling nuclear processes by Simulink

Energy Technology Data Exchange (ETDEWEB)

Rashid, Nahrul Khair Alang Md, E-mail: nahrul@iium.edu.my [Faculty of Engineering, International Islamic University Malaysia, Jalan Gombak, Selangor (Malaysia)

2015-04-29

Modelling and simulation are essential parts in the study of dynamic systems behaviours. In nuclear engineering, modelling and simulation are important to assess the expected results of an experiment before the actual experiment is conducted or in the design of nuclear facilities. In education, modelling can give insight into the dynamic of systems and processes. Most nuclear processes can be described by ordinary or partial differential equations. Efforts expended to solve the equations using analytical or numerical solutions consume time and distract attention from the objectives of modelling itself. This paper presents the use of Simulink, a MATLAB toolbox software that is widely used in control engineering, as a modelling platform for the study of nuclear processes including nuclear reactor behaviours. Starting from the describing equations, Simulink models for heat transfer, radionuclide decay process, delayed neutrons effect, reactor point kinetic equations with delayed neutron groups, and the effect of temperature feedback are used as examples.

Modeling nuclear processes by Simulink

International Nuclear Information System (INIS)

Rashid, Nahrul Khair Alang Md

2015-01-01

Modelling and simulation are essential parts in the study of dynamic systems behaviours. In nuclear engineering, modelling and simulation are important to assess the expected results of an experiment before the actual experiment is conducted or in the design of nuclear facilities. In education, modelling can give insight into the dynamic of systems and processes. Most nuclear processes can be described by ordinary or partial differential equations. Efforts expended to solve the equations using analytical or numerical solutions consume time and distract attention from the objectives of modelling itself. This paper presents the use of Simulink, a MATLAB toolbox software that is widely used in control engineering, as a modelling platform for the study of nuclear processes including nuclear reactor behaviours. Starting from the describing equations, Simulink models for heat transfer, radionuclide decay process, delayed neutrons effect, reactor point kinetic equations with delayed neutron groups, and the effect of temperature feedback are used as examples

A qualitative systematic review of studies using the normalization process theory to research implementation processes.

Science.gov (United States)

McEvoy, Rachel; Ballini, Luciana; Maltoni, Susanna; O'Donnell, Catherine A; Mair, Frances S; Macfarlane, Anne

2014-01-02

There is a well-recognized need for greater use of theory to address research translational gaps. Normalization Process Theory (NPT) provides a set of sociological tools to understand and explain the social processes through which new or modified practices of thinking, enacting, and organizing work are implemented, embedded, and integrated in healthcare and other organizational settings. This review of NPT offers readers the opportunity to observe how, and in what areas, a particular theoretical approach to implementation is being used. In this article we review the literature on NPT in order to understand what interventions NPT is being used to analyze, how NPT is being operationalized, and the reported benefits, if any, of using NPT. Using a framework analysis approach, we conducted a qualitative systematic review of peer-reviewed literature using NPT. We searched 12 electronic databases and all citations linked to six key NPT development papers. Grey literature/unpublished studies were not sought. Limitations of English language, healthcare setting and year of publication 2006 to June 2012 were set. Twenty-nine articles met the inclusion criteria; in the main, NPT is being applied to qualitatively analyze a diverse range of complex interventions, many beyond its original field of e-health and telehealth. The NPT constructs have high stability across settings and, notwithstanding challenges in applying NPT in terms of managing overlaps between constructs, there is evidence that it is a beneficial heuristic device to explain and guide implementation processes. NPT offers a generalizable framework that can be applied across contexts with opportunities for incremental knowledge gain over time and an explicit framework for analysis, which can explain and potentially shape implementation processes. This is the first review of NPT in use and it generates an impetus for further and extended use of NPT. We recommend that in future NPT research, authors should explicate

Process simulation and statistical approaches for validating waste form qualification models

International Nuclear Information System (INIS)

Kuhn, W.L.; Toland, M.R.; Pulsipher, B.A.

1989-05-01

This report describes recent progress toward one of the principal objectives of the Nuclear Waste Treatment Program (NWTP) at the Pacific Northwest Laboratory (PNL): to establish relationships between vitrification process control and glass product quality. during testing of a vitrification system, it is important to show that departures affecting the product quality can be sufficiently detected through process measurements to prevent an unacceptable canister from being produced. Meeting this goal is a practical definition of a successful sampling, data analysis, and process control strategy. A simulation model has been developed and preliminarily tested by applying it to approximate operation of the West Valley Demonstration Project (WVDP) vitrification system at West Valley, New York. Multivariate statistical techniques have been identified and described that can be applied to analyze large sets of process measurements. Information on components, tanks, and time is then combined to create a single statistic through which all of the information can be used at once to determine whether the process has shifted away from a normal condition

Tuned with a tune: Talker normalization via general auditory processes

Directory of Open Access Journals (Sweden)

Erika J C Laing

2012-06-01

Full Text Available Voices have unique acoustic signatures, contributing to the acoustic variability listeners must contend with in perceiving speech, and it has long been proposed that listeners normalize speech perception to information extracted from a talker’s speech. Initial attempts to explain talker normalization relied on extraction of articulatory referents, but recent studies of context-dependent auditory perception suggest that general auditory referents such as the long-term average spectrum (LTAS of a talker’s speech similarly affect speech perception. The present study aimed to differentiate the contributions of articulatory/linguistic versus auditory referents for context-driven talker normalization effects and, more specifically, to identify the specific constraints under which such contexts impact speech perception. Synthesized sentences manipulated to sound like different talkers influenced categorization of a subsequent speech target only when differences in the sentences’ LTAS were in the frequency range of the acoustic cues relevant for the target phonemic contrast. This effect was true both for speech targets preceded by spoken sentence contexts and for targets preceded by nonspeech tone sequences that were LTAS-matched to the spoken sentence contexts. Specific LTAS characteristics, rather than perceived talker, predicted the results suggesting that general auditory mechanisms play an important role in effects considered to be instances of perceptual talker normalization.

Sato Processes in Default Modeling

DEFF Research Database (Denmark)

Kokholm, Thomas; Nicolato, Elisa

-change of a homogeneous Levy process. While the processes in these two classes share the same average behavior over time, the associated intensities exhibit very different properties. Concrete specifications are calibrated to data on the single names included in the iTraxx Europe index. The performances are compared......In reduced form default models, the instantaneous default intensity is classically the modeling object. Survival probabilities are then given by the Laplace transform of the cumulative hazard defined as the integrated intensity process. Instead, recent literature has shown a tendency towards...... specifying the cumulative hazard process directly. Within this framework we present a new model class where cumulative hazards are described by self-similar additive processes, also known as Sato processes. Furthermore we also analyze specifications obtained via a simple deterministic time...

Quasi-particle lifetime broadening in normal-superconductor junctions with UPt3

NARCIS (Netherlands)

deWilde, Y; Klapwijk, TM; Jansen, AGM; Heil, J; Wyder, P

For the Andreev-reflection process of quasi-particles at a normal-metal-superconductor interface the influence of lifetime broadening of the quasi-particles on the current-voltage characteristics of NS point contacts is analyzed along the lines of the Blonder-Tinkham-Klapwijk model. The anomalous

Numerical modeling of normal turbulent plane jet impingement on solid wall

Energy Technology Data Exchange (ETDEWEB)

Guo, C.Y.; Maxwell, W.H.C.

1984-10-01

Attention is given to a numerical turbulence model for the impingement of a well developed normal plane jet on a solid wall, by means of which it is possible to express different jet impingement geometries in terms of different boundary conditions. Examples of these jets include those issuing from VTOL aircraft, chemical combustors, etc. The two-equation, turbulent kinetic energy-turbulent dissipation rate model is combined with the continuity equation and the transport equation of vorticity, using an iterative finite difference technique in the computations. Peak levels of turbulent kinetic energy occur not only in the impingement zone, but also in the intermingling zone between the edges of the free jet and the wall jet. 20 references.

Nonepileptic seizures under levetiracetam therapy: a case report of forced normalization process.

Science.gov (United States)

Anzellotti, Francesca; Franciotti, Raffaella; Zhuzhuni, Holta; D'Amico, Aurelio; Thomas, Astrid; Onofrj, Marco

2014-01-01

Nonepileptic seizures (NES) apparently look like epileptic seizures, but are not associated with ictal electrical discharges in the brain. NES constitute one of the most important differential diagnoses of epilepsy. They have been recognized as a distinctive clinical phenomenon for centuries, and video/electroencephalogram monitoring has allowed clinicians to make near-certain diagnoses. NES are supposedly unrelated to organic brain lesions, and despite the preponderance of a psychiatric/psychological context, they may have an iatrogenic origin. We report a patient with NES precipitated by levetiracetam therapy; in this case, NES was observed during the disappearance of epileptiform discharges from the routine video/electroencephalogram. We discuss the possible mechanisms underlying NES with regard to alternative psychoses associated with the phenomenon of the forced normalization process.

Visual attention and flexible normalization pools

Science.gov (United States)

Schwartz, Odelia; Coen-Cagli, Ruben

2013-01-01

Attention to a spatial location or feature in a visual scene can modulate the responses of cortical neurons and affect perceptual biases in illusions. We add attention to a cortical model of spatial context based on a well-founded account of natural scene statistics. The cortical model amounts to a generalized form of divisive normalization, in which the surround is in the normalization pool of the center target only if they are considered statistically dependent. Here we propose that attention influences this computation by accentuating the neural unit activations at the attended location, and that the amount of attentional influence of the surround on the center thus depends on whether center and surround are deemed in the same normalization pool. The resulting form of model extends a recent divisive normalization model of attention (Reynolds & Heeger, 2009). We simulate cortical surround orientation experiments with attention and show that the flexible model is suitable for capturing additional data and makes nontrivial testable predictions. PMID:23345413

Comparison of spectrum normalization techniques for univariate ...

Indian Academy of Sciences (India)

Laser-induced breakdown spectroscopy; univariate study; normalization models; stainless steel; standard error of prediction. Abstract. Analytical performance of six different spectrum normalization techniques, namelyinternal normalization, normalization with total light, normalization with background along with their ...

Multiphysics modelling of manufacturing processes: A review

DEFF Research Database (Denmark)

Jabbari, Masoud; Baran, Ismet; Mohanty, Sankhya

2018-01-01

Numerical modelling is increasingly supporting the analysis and optimization of manufacturing processes in the production industry. Even if being mostly applied to multistep processes, single process steps may be so complex by nature that the needed models to describe them must include multiphysics...... the diversity in the field of modelling of manufacturing processes as regards process, materials, generic disciplines as well as length scales: (1) modelling of tape casting for thin ceramic layers, (2) modelling the flow of polymers in extrusion, (3) modelling the deformation process of flexible stamps...... for nanoimprint lithography, (4) modelling manufacturing of composite parts and (5) modelling the selective laser melting process. For all five examples, the emphasis is on modelling results as well as describing the models in brief mathematical details. Alongside with relevant references to the original work...

Process convergence of self-normalized sums of i.i.d. random ...

Indian Academy of Sciences (India)

The study of the asymptotics of the self-normalized sums are also interesting. Logan ... if the constituent random variables are from the domain of attraction of a normal dis- tribution ... index of stability α which equals 2 (for definition, see §2).

Configurable multi-perspective business process models

NARCIS (Netherlands)

La Rosa, M.; Dumas, M.; Hofstede, ter A.H.M.; Mendling, J.

2011-01-01

A configurable process model provides a consolidated view of a family of business processes. It promotes the reuse of proven practices by providing analysts with a generic modeling artifact from which to derive individual process models. Unfortunately, the scope of existing notations for

Probabilistic evaluation of process model matching techniques

NARCIS (Netherlands)

Kuss, Elena; Leopold, Henrik; van der Aa, Han; Stuckenschmidt, Heiner; Reijers, Hajo A.

2016-01-01

Process model matching refers to the automatic identification of corresponding activities between two process models. It represents the basis for many advanced process model analysis techniques such as the identification of similar process parts or process model search. A central problem is how to

Normal and Pathological NCAT Image and PhantomData Based onPhysiologically Realistic Left Ventricle Finite-Element Models

Energy Technology Data Exchange (ETDEWEB)

Veress, Alexander I.; Segars, W. Paul; Weiss, Jeffrey A.; Tsui,Benjamin M.W.; Gullberg, Grant T.

2006-08-02

The 4D NURBS-based Cardiac-Torso (NCAT) phantom, whichprovides a realistic model of the normal human anatomy and cardiac andrespiratory motions, is used in medical imaging research to evaluate andimprove imaging devices and techniques, especially dynamic cardiacapplications. One limitation of the phantom is that it lacks the abilityto accurately simulate altered functions of the heart that result fromcardiac pathologies such as coronary artery disease (CAD). The goal ofthis work was to enhance the 4D NCAT phantom by incorporating aphysiologically based, finite-element (FE) mechanical model of the leftventricle (LV) to simulate both normal and abnormal cardiac motions. Thegeometry of the FE mechanical model was based on gated high-resolutionx-ray multi-slice computed tomography (MSCT) data of a healthy malesubject. The myocardial wall was represented as transversely isotropichyperelastic material, with the fiber angle varying from -90 degrees atthe epicardial surface, through 0 degreesat the mid-wall, to 90 degreesat the endocardial surface. A time varying elastance model was used tosimulate fiber contraction, and physiological intraventricular systolicpressure-time curves were applied to simulate the cardiac motion over theentire cardiac cycle. To demonstrate the ability of the FE mechanicalmodel to accurately simulate the normal cardiac motion as well abnormalmotions indicative of CAD, a normal case and two pathologic cases weresimulated and analyzed. In the first pathologic model, a subendocardialanterior ischemic region was defined. A second model was created with atransmural ischemic region defined in the same location. The FE baseddeformations were incorporated into the 4D NCAT cardiac model through thecontrol points that define the cardiac structures in the phantom whichwere set to move according to the predictions of the mechanical model. Asimulation study was performed using the FE-NCAT combination toinvestigate how the differences in contractile function

Syntax highlighting in business process models

NARCIS (Netherlands)

Reijers, H.A.; Freytag, T.; Mendling, J.; Eckleder, A.

2011-01-01

Sense-making of process models is an important task in various phases of business process management initiatives. Despite this, there is currently hardly any support in business process modeling tools to adequately support model comprehension. In this paper we adapt the concept of syntax

Genetic Process Mining: Alignment-based Process Model Mutation

NARCIS (Netherlands)

Eck, van M.L.; Buijs, J.C.A.M.; Dongen, van B.F.; Fournier, F.; Mendling, J.

2015-01-01

The Evolutionary Tree Miner (ETM) is a genetic process discovery algorithm that enables the user to guide the discovery process based on preferences with respect to four process model quality dimensions: replay fitness, precision, generalization and simplicity. Traditionally, the ETM algorithm uses

Mutual-friction induced instability of normal-fluid vortex tubes in superfluid helium-4

Science.gov (United States)

Kivotides, Demosthenes

2018-06-01

It is shown that, as a result of its interactions with superfluid vorticity, a normal-fluid vortex tube in helium-4 becomes unstable and disintegrates. The superfluid vorticity acquires only a small (few percents of normal-fluid tube strength) polarization, whilst expanding in a front-like manner in the intervortex space of the normal-fluid, forming a dense, unstructured tangle in the process. The accompanied energy spectra scalings offer a structural explanation of analogous scalings in fully developed finite-temperature superfluid turbulence. A macroscopic mutual-friction model incorporating these findings is proposed.

The effects of limited bandwidth and noise on verbal processing time and word recall in normal-hearing children.

Science.gov (United States)

McCreery, Ryan W; Stelmachowicz, Patricia G

2013-09-01

Understanding speech in acoustically degraded environments can place significant cognitive demands on school-age children who are developing the cognitive and linguistic skills needed to support this process. Previous studies suggest the speech understanding, word learning, and academic performance can be negatively impacted by background noise, but the effect of limited audibility on cognitive processes in children has not been directly studied. The aim of the present study was to evaluate the impact of limited audibility on speech understanding and working memory tasks in school-age children with normal hearing. Seventeen children with normal hearing between 6 and 12 years of age participated in the present study. Repetition of nonword consonant-vowel-consonant stimuli was measured under conditions with combinations of two different signal to noise ratios (SNRs; 3 and 9 dB) and two low-pass filter settings (3.2 and 5.6 kHz). Verbal processing time was calculated based on the time from the onset of the stimulus to the onset of the child's response. Monosyllabic word repetition and recall were also measured in conditions with a full bandwidth and 5.6 kHz low-pass cutoff. Nonword repetition scores decreased as audibility decreased. Verbal processing time increased as audibility decreased, consistent with predictions based on increased listening effort. Although monosyllabic word repetition did not vary between the full bandwidth and 5.6 kHz low-pass filter condition, recall was significantly poorer in the condition with limited bandwidth (low pass at 5.6 kHz). Age and expressive language scores predicted performance on word recall tasks, but did not predict nonword repetition accuracy or verbal processing time. Decreased audibility was associated with reduced accuracy for nonword repetition and increased verbal processing time in children with normal hearing. Deficits in free recall were observed even under conditions where word repetition was not affected

Corticocortical feedback increases the spatial extent of normalization.

Science.gov (United States)

Nassi, Jonathan J; Gómez-Laberge, Camille; Kreiman, Gabriel; Born, Richard T

2014-01-01

Normalization has been proposed as a canonical computation operating across different brain regions, sensory modalities, and species. It provides a good phenomenological description of non-linear response properties in primary visual cortex (V1), including the contrast response function and surround suppression. Despite its widespread application throughout the visual system, the underlying neural mechanisms remain largely unknown. We recently observed that corticocortical feedback contributes to surround suppression in V1, raising the possibility that feedback acts through normalization. To test this idea, we characterized area summation and contrast response properties in V1 with and without feedback from V2 and V3 in alert macaques and applied a standard normalization model to the data. Area summation properties were well explained by a form of divisive normalization, which computes the ratio between a neuron's driving input and the spatially integrated activity of a "normalization pool." Feedback inactivation reduced surround suppression by shrinking the spatial extent of the normalization pool. This effect was independent of the gain modulation thought to mediate the influence of contrast on area summation, which remained intact during feedback inactivation. Contrast sensitivity within the receptive field center was also unaffected by feedback inactivation, providing further evidence that feedback participates in normalization independent of the circuit mechanisms involved in modulating contrast gain and saturation. These results suggest that corticocortical feedback contributes to surround suppression by increasing the visuotopic extent of normalization and, via this mechanism, feedback can play a critical role in contextual information processing.

76 FR 36864 - Special Conditions: Gulfstream Model GVI Airplane; Operation Without Normal Electric Power

Science.gov (United States)

2011-06-23

... Normal Electric Power AGENCY: Federal Aviation Administration (FAA), DOT. ACTION: Final special... Interface Branch, ANM-111, Transport Standards Staff, Transport Airplane Directorate, Aircraft Certification... Model GVI airplane will be an all-new, two- engine jet transport airplane. The maximum takeoff weight...

The triconnected abstraction of process models

OpenAIRE

Polyvyanyy, Artem; Smirnov, Sergey; Weske, Mathias

2009-01-01

Contents: Artem Polyvanny, Sergey Smirnow, and Mathias Weske The Triconnected Abstraction of Process Models 1 Introduction 2 Business Process Model Abstraction 3 Preliminaries 4 Triconnected Decomposition 4.1 Basic Approach for Process Component Discovery 4.2 SPQR-Tree Decomposition 4.3 SPQR-Tree Fragments in the Context of Process Models 5 Triconnected Abstraction 5.1 Abstraction Rules 5.2 Abstraction Algorithm 6 Related Work and Conclusions

Modeling Suspension and Continuation of a Process

Directory of Open Access Journals (Sweden)

Oleg Svatos

2012-04-01

Full Text Available This work focuses on difficulties an analyst encounters when modeling suspension and continuation of a process in contemporary process modeling languages. As a basis there is introduced general lifecycle of an activity which is then compared to activity lifecycles supported by individual process modeling languages. The comparison shows that the contemporary process modeling languages cover the defined general lifecycle of an activity only partially. There are picked two popular process modeling languages and there is modeled real example, which reviews how the modeling languages can get along with their lack of native support of suspension and continuation of an activity. Upon the unsatisfying results of the contemporary process modeling languages in the modeled example, there is presented a new process modeling language which, as demonstrated, is capable of capturing suspension and continuation of an activity in much simpler and precise way.

Improving historical spelling normalization with bi-directional LSTMs and multi-task learning

OpenAIRE

Bollmann, Marcel; Søgaard, Anders

2016-01-01

Natural-language processing of historical documents is complicated by the abundance of variant spellings and lack of annotated data. A common approach is to normalize the spelling of historical words to modern forms. We explore the suitability of a deep neural network architecture for this task, particularly a deep bi-LSTM network applied on a character level. Our model compares well to previously established normalization algorithms when evaluated on a diverse set of texts from Early New Hig...

Higher Fasting Plasma Glucose Levels, within the Normal Range, are Associated with Decreased Processing Speed in High Functioning Young Elderly

OpenAIRE

Raizes, Meytal; Elkana, Odelia; Franko, Motty; Springer, Ramit Ravona; Segev, Shlomo; Beeri, Michal Schnaider

2016-01-01

We explored the association of plasma glucose levels within the normal range with processing speed in high functioning young elderly, free of type 2 diabetes mellitus (T2DM). A sample of 41 participants (mean age = 64.7, SD = 10; glucose 94.5 mg/dL, SD = 9.3), were examined with a computerized cognitive battery. Hierarchical linear regression analysis showed that higher plasma glucose levels, albeit within the normal range (

Declarative modeling for process supervision

International Nuclear Information System (INIS)

Leyval, L.

1989-01-01

Our work is a contribution to computer aided supervision of continuous processes. It is inspired by an area of Artificial Intelligence: qualitative physics. Here, supervision is based on a model which continuously provides operators with a synthetic view of the process; but this model is founded on general principles of control theory rather than on physics. It involves concepts such as high gain or small time response. It helps in linking temporally the evolution of various variables. Moreover, the model provides predictions of the future behaviour of the process, which allows action advice and alarm filtering. This should greatly reduce the famous cognitive overload associated to any complex and dangerous evolution of the process

ECONOMIC MODELING PROCESSES USING MATLAB

Directory of Open Access Journals (Sweden)

Anamaria G. MACOVEI

2008-06-01

Full Text Available To study economic phenomena and processes using mathem atical modeling, and to determine the approximatesolution to a problem we need to choose a method of calculation and a numerical computer program, namely thepackage of programs MatLab. Any economic process or phenomenon is a mathematical description of h is behavior,and thus draw up an economic and mathematical model that has the following stages: formulation of the problem, theanalysis process modeling, the production model and design verification, validation and implementation of the model.This article is presented an economic model and its modeling is using mathematical equations and software packageMatLab, which helps us approximation effective solution. As data entry is considered the net cost, the cost of direct andtotal cost and the link between them. I presented the basic formula for determining the total cost. Economic modelcalculations were made in MatLab software package and with graphic representation of its interpretation of the resultsachieved in terms of our specific problem.

Normal and Pathological NCAT Image and Phantom Data Based on Physiologically Realistic Left Ventricle Finite-Element Models

International Nuclear Information System (INIS)

Veress, Alexander I.; Segars, W. Paul; Weiss, Jeffrey A.; Tsui, Benjamin M.W.; Gullberg, Grant T.

2006-01-01

The 4D NURBS-based Cardiac-Torso (NCAT) phantom, which provides a realistic model of the normal human anatomy and cardiac and respiratory motions, is used in medical imaging research to evaluate and improve imaging devices and techniques, especially dynamic cardiac applications. One limitation of the phantom is that it lacks the ability to accurately simulate altered functions of the heart that result from cardiac pathologies such as coronary artery disease (CAD). The goal of this work was to enhance the 4D NCAT phantom by incorporating a physiologically based, finite-element (FE) mechanical model of the left ventricle (LV) to simulate both normal and abnormal cardiac motions. The geometry of the FE mechanical model was based on gated high-resolution x-ray multi-slice computed tomography (MSCT) data of a healthy male subject. The myocardial wall was represented as transversely isotropichyperelastic material, with the fiber angle varying from -90 degrees at the epicardial surface, through 0 degrees at the mid-wall, to 90 degrees at the endocardial surface. A time varying elastance model was used to simulate fiber contraction, and physiological intraventricular systolic pressure-time curves were applied to simulate the cardiac motion over the entire cardiac cycle. To demonstrate the ability of the FE mechanical model to accurately simulate the normal cardiac motion as well abnormal motions indicative of CAD, a normal case and two pathologic cases were simulated and analyzed. In the first pathologic model, a subendocardial anterior ischemic region was defined. A second model was created with a transmural ischemic region defined in the same location. The FE based deformations were incorporated into the 4D NCAT cardiac model through the control points that define the cardiac structures in the phantom which were set to move according to the predictions of the mechanical model. A simulation study was performed using the FE-NCAT combination to investigate how the

Styles in business process modeling: an exploration and a model

NARCIS (Netherlands)

Pinggera, J.; Soffer, P.; Fahland, D.; Weidlich, M.; Zugal, S.; Weber, B.; Reijers, H.A.; Mendling, J.

2015-01-01

Business process models are an important means to design, analyze, implement, and control business processes. As with every type of conceptual model, a business process model has to meet certain syntactic, semantic, and pragmatic quality requirements to be of value. For many years, such quality

Composing Models of Geographic Physical Processes

Science.gov (United States)

Hofer, Barbara; Frank, Andrew U.

Processes are central for geographic information science; yet geographic information systems (GIS) lack capabilities to represent process related information. A prerequisite to including processes in GIS software is a general method to describe geographic processes independently of application disciplines. This paper presents such a method, namely a process description language. The vocabulary of the process description language is derived formally from mathematical models. Physical processes in geography can be described in two equivalent languages: partial differential equations or partial difference equations, where the latter can be shown graphically and used as a method for application specialists to enter their process models. The vocabulary of the process description language comprises components for describing the general behavior of prototypical geographic physical processes. These process components can be composed by basic models of geographic physical processes, which is shown by means of an example.

Cue acquisition: A feature of Malawian midwives decision making process to support normality during the first stage of labour.

Science.gov (United States)

Chodzaza, Elizabeth; Haycock-Stuart, Elaine; Holloway, Aisha; Mander, Rosemary

2018-03-01

to explore Malawian midwives decision making when caring for women during the first stage of labour in the hospital setting. this focused ethnographic study examined the decision making process of 9 nurse-midwives with varying years of clinical experience in the real world setting of an urban and semi urban hospital from October 2013 to May 2014.This was done using 27 participant observations and 27 post-observation in-depth interviews over a period of six months. Qualitative data analysis software, NVivo 10, was used to assist with data management for the analysis. All data was analysed using the principle of theme and category formation. analysis revealed a six-stage process of decision making that include a baseline for labour, deciding to admit a woman to labour ward, ascertaining the normal physiological progress of labour, supporting the normal physiological progress of labour, embracing uncertainty: the midwives' construction of unusual labour as normal, dealing with uncertainty and deciding to intervene in unusual labour. This six-stage process of decision making is conceptualised as the 'role of cue acquisition', illustrating the ways in which midwives utilise their assessment of labouring women to reason and make decisions on how to care for them in labour. Cue acquisition involved the midwives piecing together segments of information they obtained from the women to formulate an understanding of the woman's birthing progress and inform the midwives decision making process. This understanding of cue acquisition by midwives is significant for supporting safe care in the labour setting. When there was uncertainty in a woman's progress of labour, midwives used deductive reasoning, for example, by cross-checking and analysing the information obtained during the span of labour. Supporting normal labour physiological processes was identified as an underlying principle that shaped the midwives clinical judgement and decision making when they cared for women in

Normal stresses in semiflexible polymer hydrogels

Science.gov (United States)

Vahabi, M.; Vos, Bart E.; de Cagny, Henri C. G.; Bonn, Daniel; Koenderink, Gijsje H.; MacKintosh, F. C.

2018-03-01

Biopolymer gels such as fibrin and collagen networks are known to develop tensile axial stress when subject to torsion. This negative normal stress is opposite to the classical Poynting effect observed for most elastic solids including synthetic polymer gels, where torsion provokes a positive normal stress. As shown recently, this anomalous behavior in fibrin gels depends on the open, porous network structure of biopolymer gels, which facilitates interstitial fluid flow during shear and can be described by a phenomenological two-fluid model with viscous coupling between network and solvent. Here we extend this model and develop a microscopic model for the individual diagonal components of the stress tensor that determine the axial response of semiflexible polymer hydrogels. This microscopic model predicts that the magnitude of these stress components depends inversely on the characteristic strain for the onset of nonlinear shear stress, which we confirm experimentally by shear rheometry on fibrin gels. Moreover, our model predicts a transient behavior of the normal stress, which is in excellent agreement with the full time-dependent normal stress we measure.

A Look at the Memory Performance of Retarded and Normal Children Utilizing the Levels of Processing Framework.

Science.gov (United States)

Lupart, Judy L.; Mulcahy, Robert F.

Memory performance differences of mental age matched (9-12 years) educable mentally retarded (EMR) (n=56) and normal (n=56) children were examined in two experiments using the F. Craik and R. Lockhart levels of processing framework. In experiment 1, Ss were randomly assigned to an incidental, intentional, or planned intentional learning condition,…

The Structured Process Modeling Theory (SPMT) : a cognitive view on why and how modelers benefit from structuring the process of process modeling

NARCIS (Netherlands)

Claes, J.; Vanderfeesten, I.T.P.; Gailly, F.; Grefen, P.W.P.J.; Poels, G.

2015-01-01

After observing various inexperienced modelers constructing a business process model based on the same textual case description, it was noted that great differences existed in the quality of the produced models. The impression arose that certain quality issues originated from cognitive failures

Integrated modelling in materials and process technology

DEFF Research Database (Denmark)

Hattel, Jesper Henri

2008-01-01

Integrated modelling of entire process sequences and the subsequent in-service conditions, and multiphysics modelling of the single process steps are areas that increasingly support optimisation of manufactured parts. In the present paper, three different examples of modelling manufacturing...... processes from the viewpoint of combined materials and process modelling are presented: solidification of thin walled ductile cast iron, integrated modelling of spray forming and multiphysics modelling of friction stir welding. The fourth example describes integrated modelling applied to a failure analysis...

A probabilistic approach using deformable organ models for automatic definition of normal anatomical structures for 3D treatment planning

International Nuclear Information System (INIS)

Fritsch, Daniel; Yu Liyun; Johnson, Valen; McAuliffe, Matthew; Pizer, Stephen; Chaney, Edward

1996-01-01

Purpose/Objective : Current clinical methods for defining normal anatomical structures on tomographic images are time consuming and subject to intra- and inter-user variability. With the widespread implementation of 3D RTP, conformal radiotherapy, and dose escalation the implications of imprecise object definition have assumed a much higher level of importance. Object definition and volume-weighted metrics for normal anatomy, such as DVHs and NTCPs, play critical roles in aiming, shaping, and weighting beams. Improvements in object definition, including computer automation, are essential to yield reliable volume-weighted metrics and gains in human efficiency. The purpose of this study was to investigate a probabilistic approach using deformable models to automatically recognize and extract normal anatomy in tomographic images. Materials and Methods: Object models were created from normal organs that were segmented by an interactive method which involved placing a cursor near the center of the object on a slice and clicking a mouse button to initiate computation of structures called cores. Cores describe the skeletal and boundary shape of image objects in a manner that, in 2D, associates a location on the skeleton with the width of the object at that location. A significant advantage of cores is stability against image disturbances such as noise and blur. The model was composed of a relatively small set of extracted points on the skeleton and boundary. The points were carefully chosen to summarize the shape information captured by the cores. Neighborhood relationships between points were represented mathematically by energy functions that penalize, due to warping of the model, the ''goodness'' of match between the model and the image data at any stage during the segmentation process. The model was matched against the image data using a probabilistic approach based on Bayes theorem, which provides a means for computing a posteriori (posterior) probability from 1) a

The impact of working memory and the “process of process modelling” on model quality: Investigating experienced versus inexperienced modellers

Science.gov (United States)

Martini, Markus; Pinggera, Jakob; Neurauter, Manuel; Sachse, Pierre; Furtner, Marco R.; Weber, Barbara

2016-01-01

A process model (PM) represents the graphical depiction of a business process, for instance, the entire process from online ordering a book until the parcel is delivered to the customer. Knowledge about relevant factors for creating PMs of high quality is lacking. The present study investigated the role of cognitive processes as well as modelling processes in creating a PM in experienced and inexperienced modellers. Specifically, two working memory (WM) functions (holding and processing of information and relational integration) and three process of process modelling phases (comprehension, modelling, and reconciliation) were related to PM quality. Our results show that the WM function of relational integration was positively related to PM quality in both modelling groups. The ratio of comprehension phases was negatively related to PM quality in inexperienced modellers and the ratio of reconciliation phases was positively related to PM quality in experienced modellers. Our research reveals central cognitive mechanisms in process modelling and has potential practical implications for the development of modelling software and teaching the craft of process modelling. PMID:27157858

Des proprietes de l'etat normal du modele de Hubbard bidimensionnel

Science.gov (United States)

Lemay, Francois

Depuis leur decouverte, les etudes experimentales ont demontre que les supra-conducteurs a haute temperature ont une phase normale tres etrange. Les proprietes de ces materiaux ne sont pas bien decrites par la theorie du liquide de Fermi. Le modele de Hubbard bidimensionnel, bien qu'il ne soit pas encore resolu, est toujours considere comme un candidat pour expliquer la physique de ces composes. Dans cet ouvrage, nous mettons en evidence plusieurs proprietes electroniques du modele qui sont incompatibles avec l'existence de quasi-particules. Nous montrons notamment que la susceptibilite des electrons libres sur reseau contient des singularites logarithmiques qui influencent de facon determinante les proprietes de la self-energie a basse frequence. Ces singularites sont responsables de la destruction des quasi-particules. En l'absence de fluctuations antiferromagnetiques, elles sont aussi responsables de l'existence d'un petit pseudogap dans le poids spectral au niveau de Fermi. Les proprietes du modele sont egalement etudiees pour une surface de Fermi similaire a celle des supraconducteurs a haute temperature. Un parallele est etabli entre certaines caracteristiques du modele et celles de ces materiaux.

Detecting Difference between Process Models Based on the Refined Process Structure Tree

Directory of Open Access Journals (Sweden)

Jing Fan

2017-01-01

Full Text Available The development of mobile workflow management systems (mWfMS leads to large number of business process models. In the meantime, the location restriction embedded in mWfMS may result in different process models for a single business process. In order to help users quickly locate the difference and rebuild the process model, detecting the difference between different process models is needed. Existing detection methods either provide a dissimilarity value to represent the difference or use predefined difference template to generate the result, which cannot reflect the entire composition of the difference. Hence, in this paper, we present a new approach to solve this problem. Firstly, we parse the process models to their corresponding refined process structure trees (PSTs, that is, decomposing a process model into a hierarchy of subprocess models. Then we design a method to convert the PST to its corresponding task based process structure tree (TPST. As a consequence, the problem of detecting difference between two process models is transformed to detect difference between their corresponding TPSTs. Finally, we obtain the difference between two TPSTs based on the divide and conquer strategy, where the difference is described by an edit script and we make the cost of the edit script close to minimum. The extensive experimental evaluation shows that our method can meet the real requirements in terms of precision and efficiency.

Strategies to Automatically Derive a Process Model from a Configurable Process Model Based on Event Data

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Mauricio Arriagada-Benítez

2017-10-01

Full Text Available Configurable process models are frequently used to represent business workflows and other discrete event systems among different branches of large organizations: they unify commonalities shared by all branches and describe their differences, at the same time. The configuration of such models is usually done manually, which is challenging. On the one hand, when the number of configurable nodes in the configurable process model grows, the size of the search space increases exponentially. On the other hand, the person performing the configuration may lack the holistic perspective to make the right choice for all configurable nodes at the same time, since choices influence each other. Nowadays, information systems that support the execution of business processes create event data reflecting how processes are performed. In this article, we propose three strategies (based on exhaustive search, genetic algorithms and a greedy heuristic that use event data to automatically derive a process model from a configurable process model that better represents the characteristics of the process in a specific branch. These strategies have been implemented in our proposed framework and tested in both business-like event logs as recorded in a higher educational enterprise resource planning system and a real case scenario involving a set of Dutch municipalities.

Repairing process models to reflect reality

NARCIS (Netherlands)

Fahland, D.; Aalst, van der W.M.P.; Barros, A.; Gal, A.; Kindler, E.

2012-01-01

Process mining techniques relate observed behavior (i.e., event logs) to modeled behavior (e.g., a BPMN model or a Petri net). Processes models can be discovered from event logs and conformance checking techniques can be used to detect and diagnose differences between observed and modeled behavior.

Análise dos processos fonológicos em crianças com desenvolvimento fonológico normal Phonological processes analysis in children with normal phonological development

Directory of Open Access Journals (Sweden)

Carla Ferrante

2009-01-01

Full Text Available OBJETIVO: O presente estudo teve como objetivo verificar o uso dos processos fonológicos em uma população de crianças com desenvolvimento fonológico normal. MÉTODOS: Fizeram parte da pesquisa 240 crianças, de ambos os sexos, com idades entre três e oito anos. Foram realizadas análises relativas aos processos fonológicos e os dados foram comparados em relação à faixa etária e sexo. RESULTADOS: A análise dos resultados permitiu concluir que aos três, quatro e cinco anos os processos de redução de encontro consonantal, lateralização e apagamento de consoante final foram os mais utilizados. A metátese foi o segundo processo mais utilizado na faixa etária de seis anos, aparecendo em terceiro lugar na faixa etária de sete anos. Em relação ao número de processos fonológicos utilizados por faixa etária, aos três anos de idade as crianças utilizaram um mínimo de dois processos e a partir da faixa etária de quatro anos o número mínimo de processos fonológicos utilizados foi zero e o número máximo diminuiu gradativamente de acordo com o aumento da faixa etária, assim como a média. Em relação à variável sexo, não foi observada nenhuma diferença estatisticamente significante em nenhuma das análises realizadas nesta pesquisa. CONCLUSÕES: Os dados encontrados nesta pesquisa evidenciam a dificuldade encontrada pelas crianças na produção das líquidas e nas estruturas silábicas mais complexas.PURPOSE: The aim of this study was to verify the use of phonological processes in a group of children with normal phonological development. METHODS: The participants were 240 children of both genders, aged between three and eight years. Analyses regarding phonological processes were carried out, and the data were compared considering age and gender. RESULTS: The results allowed the conclusion that at the ages of three, four and five years the most frequently used processes were cluster reduction, lateralization, and final

Business process modeling for processing classified documents using RFID technology

Directory of Open Access Journals (Sweden)

Koszela Jarosław

2016-01-01

Full Text Available The article outlines the application of the processing approach to the functional description of the designed IT system supporting the operations of the secret office, which processes classified documents. The article describes the application of the method of incremental modeling of business processes according to the BPMN model to the description of the processes currently implemented (“as is” in a manual manner and target processes (“to be”, using the RFID technology for the purpose of their automation. Additionally, the examples of applying the method of structural and dynamic analysis of the processes (process simulation to verify their correctness and efficiency were presented. The extension of the process analysis method is a possibility of applying the warehouse of processes and process mining methods.

Trade off between variable and fixed size normalization in orthogonal polynomials based iris recognition system.

Science.gov (United States)

Krishnamoorthi, R; Anna Poorani, G

2016-01-01

Iris normalization is an important stage in any iris biometric, as it has a propensity to trim down the consequences of iris distortion. To indemnify the variation in size of the iris owing to the action of stretching or enlarging the pupil in iris acquisition process and camera to eyeball distance, two normalization schemes has been proposed in this work. In the first method, the iris region of interest is normalized by converting the iris into the variable size rectangular model in order to avoid the under samples near the limbus border. In the second method, the iris region of interest is normalized by converting the iris region into a fixed size rectangular model in order to avoid the dimensional discrepancies between the eye images. The performance of the proposed normalization methods is evaluated with orthogonal polynomials based iris recognition in terms of FAR, FRR, GAR, CRR and EER.

Business Process Modelling for Measuring Quality

NARCIS (Netherlands)

Heidari, F.; Loucopoulos, P.; Brazier, F.M.

2013-01-01

Business process modelling languages facilitate presentation, communication and analysis of business processes with different stakeholders. This paper proposes an approach that drives specification and measurement of quality requirements and in doing so relies on business process models as

Investigation of Mediational Processes Using Parallel Process Latent Growth Curve Modeling

Science.gov (United States)

Cheong, JeeWon; MacKinnon, David P.; Khoo, Siek Toon

2010-01-01

This study investigated a method to evaluate mediational processes using latent growth curve modeling. The mediator and the outcome measured across multiple time points were viewed as 2 separate parallel processes. The mediational process was defined as the independent variable influencing the growth of the mediator, which, in turn, affected the growth of the outcome. To illustrate modeling procedures, empirical data from a longitudinal drug prevention program, Adolescents Training and Learning to Avoid Steroids, were used. The program effects on the growth of the mediator and the growth of the outcome were examined first in a 2-group structural equation model. The mediational process was then modeled and tested in a parallel process latent growth curve model by relating the prevention program condition, the growth rate factor of the mediator, and the growth rate factor of the outcome. PMID:20157639

Behavioral conformance of artifact-centric process models

NARCIS (Netherlands)

Fahland, D.; Leoni, de M.; Dongen, van B.F.; Aalst, van der W.M.P.; Abramowicz, W.

2011-01-01

The use of process models in business information systems for analysis, execution, and improvement of processes assumes that the models describe reality. Conformance checking is a technique to validate how good a given process model describes recorded executions of the actual process. Recently,

Pseudo SU(3) shell model: Normal parity bands in odd-mass nuclei

International Nuclear Information System (INIS)

Vargas, C.E.; Hirsch, J.G.; Draayer, J.P.

2000-01-01

A pseudo shell SU(3) model description of normal parity bands in 159 Tb is presented. The Hamiltonian includes spherical Nilsson single-particle energies, the quadrupole-quadrupole and pairing interactions, as well as three rotor terms. A systematic parametrization is introduced, accompanied by a detailed discussion of the effect each term in the Hamiltonian has on the energy spectrum. Yrast and excited band wavefunctions are analyzed together with their B(E2) values

Corticocortical feedback increases the spatial extent of normalization

Science.gov (United States)

Nassi, Jonathan J.; Gómez-Laberge, Camille; Kreiman, Gabriel; Born, Richard T.

2014-01-01

Normalization has been proposed as a canonical computation operating across different brain regions, sensory modalities, and species. It provides a good phenomenological description of non-linear response properties in primary visual cortex (V1), including the contrast response function and surround suppression. Despite its widespread application throughout the visual system, the underlying neural mechanisms remain largely unknown. We recently observed that corticocortical feedback contributes to surround suppression in V1, raising the possibility that feedback acts through normalization. To test this idea, we characterized area summation and contrast response properties in V1 with and without feedback from V2 and V3 in alert macaques and applied a standard normalization model to the data. Area summation properties were well explained by a form of divisive normalization, which computes the ratio between a neuron's driving input and the spatially integrated activity of a “normalization pool.” Feedback inactivation reduced surround suppression by shrinking the spatial extent of the normalization pool. This effect was independent of the gain modulation thought to mediate the influence of contrast on area summation, which remained intact during feedback inactivation. Contrast sensitivity within the receptive field center was also unaffected by feedback inactivation, providing further evidence that feedback participates in normalization independent of the circuit mechanisms involved in modulating contrast gain and saturation. These results suggest that corticocortical feedback contributes to surround suppression by increasing the visuotopic extent of normalization and, via this mechanism, feedback can play a critical role in contextual information processing. PMID:24910596

Cost Models for MMC Manufacturing Processes

Science.gov (United States)

Elzey, Dana M.; Wadley, Haydn N. G.

1996-01-01

Processes for the manufacture of advanced metal matrix composites are rapidly approaching maturity in the research laboratory and there is growing interest in their transition to industrial production. However, research conducted to date has almost exclusively focused on overcoming the technical barriers to producing high-quality material and little attention has been given to the economical feasibility of these laboratory approaches and process cost issues. A quantitative cost modeling (QCM) approach was developed to address these issues. QCM are cost analysis tools based on predictive process models relating process conditions to the attributes of the final product. An important attribute, of the QCM approach is the ability to predict the sensitivity of material production costs to product quality and to quantitatively explore trade-offs between cost and quality. Applications of the cost models allow more efficient direction of future MMC process technology development and a more accurate assessment of MMC market potential. Cost models were developed for two state-of-the art metal matrix composite (MMC) manufacturing processes: tape casting and plasma spray deposition. Quality and Cost models are presented for both processes and the resulting predicted quality-cost curves are presented and discussed.

Conceptual modelling of human resource evaluation process

Directory of Open Access Journals (Sweden)

Negoiţă Doina Olivia

2017-01-01

Full Text Available Taking into account the highly diverse tasks which employees have to fulfil due to complex requirements of nowadays consumers, the human resource within an enterprise has become a strategic element for developing and exploiting products which meet the market expectations. Therefore, organizations encounter difficulties when approaching the human resource evaluation process. Hence, the aim of the current paper is to design a conceptual model of the aforementioned process, which allows the enterprises to develop a specific methodology. In order to design the conceptual model, Business Process Modelling instruments were employed - Adonis Community Edition Business Process Management Toolkit using the ADONIS BPMS Notation. The conceptual model was developed based on an in-depth secondary research regarding the human resource evaluation process. The proposed conceptual model represents a generic workflow (sequential and/ or simultaneously activities, which can be extended considering the enterprise’s needs regarding their requirements when conducting a human resource evaluation process. Enterprises can benefit from using software instruments for business process modelling as they enable process analysis and evaluation (predefined / specific queries and also model optimization (simulations.

Modeling Dynamic Systems with Efficient Ensembles of Process-Based Models.

Directory of Open Access Journals (Sweden)

Nikola Simidjievski

Full Text Available Ensembles are a well established machine learning paradigm, leading to accurate and robust models, predominantly applied to predictive modeling tasks. Ensemble models comprise a finite set of diverse predictive models whose combined output is expected to yield an improved predictive performance as compared to an individual model. In this paper, we propose a new method for learning ensembles of process-based models of dynamic systems. The process-based modeling paradigm employs domain-specific knowledge to automatically learn models of dynamic systems from time-series observational data. Previous work has shown that ensembles based on sampling observational data (i.e., bagging and boosting, significantly improve predictive performance of process-based models. However, this improvement comes at the cost of a substantial increase of the computational time needed for learning. To address this problem, the paper proposes a method that aims at efficiently learning ensembles of process-based models, while maintaining their accurate long-term predictive performance. This is achieved by constructing ensembles with sampling domain-specific knowledge instead of sampling data. We apply the proposed method to and evaluate its performance on a set of problems of automated predictive modeling in three lake ecosystems using a library of process-based knowledge for modeling population dynamics. The experimental results identify the optimal design decisions regarding the learning algorithm. The results also show that the proposed ensembles yield significantly more accurate predictions of population dynamics as compared to individual process-based models. Finally, while their predictive performance is comparable to the one of ensembles obtained with the state-of-the-art methods of bagging and boosting, they are substantially more efficient.

A combined approach of generalized additive model and bootstrap with small sample sets for fault diagnosis in fermentation process of glutamate.

Science.gov (United States)

Liu, Chunbo; Pan, Feng; Li, Yun

2016-07-29

Glutamate is of great importance in food and pharmaceutical industries. There is still lack of effective statistical approaches for fault diagnosis in the fermentation process of glutamate. To date, the statistical approach based on generalized additive model (GAM) and bootstrap has not been used for fault diagnosis in fermentation processes, much less the fermentation process of glutamate with small samples sets. A combined approach of GAM and bootstrap was developed for the online fault diagnosis in the fermentation process of glutamate with small sample sets. GAM was first used to model the relationship between glutamate production and different fermentation parameters using online data from four normal fermentation experiments of glutamate. The fitted GAM with fermentation time, dissolved oxygen, oxygen uptake rate and carbon dioxide evolution rate captured 99.6 % variance of glutamate production during fermentation process. Bootstrap was then used to quantify the uncertainty of the estimated production of glutamate from the fitted GAM using 95 % confidence interval. The proposed approach was then used for the online fault diagnosis in the abnormal fermentation processes of glutamate, and a fault was defined as the estimated production of glutamate fell outside the 95 % confidence interval. The online fault diagnosis based on the proposed approach identified not only the start of the fault in the fermentation process, but also the end of the fault when the fermentation conditions were back to normal. The proposed approach only used a small sample sets from normal fermentations excitements to establish the approach, and then only required online recorded data on fermentation parameters for fault diagnosis in the fermentation process of glutamate. The proposed approach based on GAM and bootstrap provides a new and effective way for the fault diagnosis in the fermentation process of glutamate with small sample sets.

Statistical mechanics of normal grain growth in one dimension: A partial integro-differential equation model

International Nuclear Information System (INIS)

Ng, Felix S.L.

2016-01-01

We develop a statistical-mechanical model of one-dimensional normal grain growth that does not require any drift-velocity parameterization for grain size, such as used in the continuity equation of traditional mean-field theories. The model tracks the population by considering grain sizes in neighbour pairs; the probability of a pair having neighbours of certain sizes is determined by the size-frequency distribution of all pairs. Accordingly, the evolution obeys a partial integro-differential equation (PIDE) over ‘grain size versus neighbour grain size’ space, so that the grain-size distribution is a projection of the PIDE's solution. This model, which is applicable before as well as after statistically self-similar grain growth has been reached, shows that the traditional continuity equation is invalid outside this state. During statistically self-similar growth, the PIDE correctly predicts the coarsening rate, invariant grain-size distribution and spatial grain size correlations observed in direct simulations. The PIDE is then reducible to the standard continuity equation, and we derive an explicit expression for the drift velocity. It should be possible to formulate similar parameterization-free models of normal grain growth in two and three dimensions.

Information-Processing Models and Curriculum Design

Science.gov (United States)

Calfee, Robert C.

1970-01-01

"This paper consists of three sections--(a) the relation of theoretical analyses of learning to curriculum design, (b) the role of information-processing models in analyses of learning processes, and (c) selected examples of the application of information-processing models to curriculum design problems." (Author)

Large-scale grain growth in the solid-state process: From "Abnormal" to "Normal"

Science.gov (United States)

Jiang, Minhong; Han, Shengnan; Zhang, Jingwei; Song, Jiageng; Hao, Chongyan; Deng, Manjiao; Ge, Lingjing; Gu, Zhengfei; Liu, Xinyu

2018-02-01

Abnormal grain growth (AGG) has been a common phenomenon during the ceramic or metallurgy processing since prehistoric times. However, usually it had been very difficult to grow big single crystal (centimeter scale over) by using the AGG method due to its so-called occasionality. Based on the AGG, a solid-state crystal growth (SSCG) method was developed. The greatest advantages of the SSCG technology are the simplicity and cost-effectiveness of the technique. But the traditional SSCG technology is still uncontrollable. This article first summarizes the history and current status of AGG, and then reports recent technical developments from AGG to SSCG, and further introduces a new seed-free, solid-state crystal growth (SFSSCG) technology. This SFSSCG method allows us to repeatedly and controllably fabricate large-scale single crystals with appreciable high quality and relatively stable chemical composition at a relatively low temperature, at least in (K0.5Na0.5)NbO3(KNN) and Cu-Al-Mn systems. In this sense, the exaggerated grain growth is no longer 'Abnormal' but 'Normal' since it is able to be artificially controllable and repeated now. This article also provides a crystal growth model to qualitatively explain the mechanism of SFSSCG for KNN system. Compared with the traditional melt and high temperature solution growth methods, the SFSSCG method has the advantages of low energy consumption, low investment, simple technique, composition homogeneity overcoming the issues with incongruent melting and high volatility. This SFSSCG could be helpful for improving the mechanical and physical properties of single crystals, which should be promising for industrial applications.

Parametric estimation of covariance function in Gaussian-process based Kriging models. Application to uncertainty quantification for computer experiments

International Nuclear Information System (INIS)

Bachoc, F.

2013-01-01

The parametric estimation of the covariance function of a Gaussian process is studied, in the framework of the Kriging model. Maximum Likelihood and Cross Validation estimators are considered. The correctly specified case, in which the covariance function of the Gaussian process does belong to the parametric set used for estimation, is first studied in an increasing-domain asymptotic framework. The sampling considered is a randomly perturbed multidimensional regular grid. Consistency and asymptotic normality are proved for the two estimators. It is then put into evidence that strong perturbations of the regular grid are always beneficial to Maximum Likelihood estimation. The incorrectly specified case, in which the covariance function of the Gaussian process does not belong to the parametric set used for estimation, is then studied. It is shown that Cross Validation is more robust than Maximum Likelihood in this case. Finally, two applications of the Kriging model with Gaussian processes are carried out on industrial data. For a validation problem of the friction model of the thermal-hydraulic code FLICA 4, where experimental results are available, it is shown that Gaussian process modeling of the FLICA 4 code model error enables to considerably improve its predictions. Finally, for a meta modeling problem of the GERMINAL thermal-mechanical code, the interest of the Kriging model with Gaussian processes, compared to neural network methods, is shown. (author) [fr

NORMAL PRESSURE AND FRICTION STRESS MEASUREMENT IN ROLLING PROCESSES

DEFF Research Database (Denmark)

Henningsen, Poul; Arentoft, Mogens; Lagergren, Jonas

2005-01-01

the output from the transducer, the friction stress and normal pressure in the contact zone can be determined. The new concept differs from existing pin designs by a lower disturbance of lubricant film and material flow and limited penetration of material between transducer and roll. Aluminum, cupper...

STOCHASTIC PRICING MODEL FOR THE REAL ESTATE MARKET: FORMATION OF LOG-NORMAL GENERAL POPULATION

Directory of Open Access Journals (Sweden)

Oleg V. Rusakov

2015-01-01

Full Text Available We construct a stochastic model of real estate pricing. The method of the pricing construction is based on a sequential comparison of the supply prices. We proof that under standard assumptions imposed upon the comparison coefficients there exists an unique non-degenerated limit in distribution and this limit has the lognormal law of distribution. The accordance of empirical distributions of prices to thetheoretically obtained log-normal distribution we verify by numerous statistical data of real estate prices from Saint-Petersburg (Russia. For establishing this accordance we essentially apply the efficient and sensitive test of fit of Kolmogorov-Smirnov. Basing on “The Russian Federal Estimation Standard N2”, we conclude that the most probable price, i.e. mode of distribution, is correctly and uniquely defined under the log-normal approximation. Since the mean value of log-normal distribution exceeds the mode - most probable value, it follows that the prices valued by the mathematical expectation are systematically overstated.

Measuring similarity between business process models

NARCIS (Netherlands)

Dongen, van B.F.; Dijkman, R.M.; Mendling, J.

2007-01-01

Quality aspects become increasingly important when business process modeling is used in a large-scale enterprise setting. In order to facilitate a storage without redundancy and an efficient retrieval of relevant process models in model databases it is required to develop a theoretical understanding

Quantum transport in graphene normal-metal superconductor- normal-metal structures

Directory of Open Access Journals (Sweden)

H. Mohammadpour

2008-06-01

Full Text Available  We study the transport of electrons in a graphene NSN structure in which two normal regions are connected by a superconducting strip of thickness d. Within Dirac-Bogoliubov-de Gennes equations we describe the transmission through the contact in terms of different scattering processes consisting of quasiparticle cotunneling, local and crossed Andreev reflections. Compared to a fully normal structure we show that the angular dependence of the transmission probability is significantly modified by the presence of superconducting correlations. This modifation can be explained in terms of the interplay between Andreev reflection and Klein tunneling of chiral quasiparticles. We further analyze the energy dependence of the resulting differential conductance of the structure. The subgap differential conductance shows features of Andreev reflection and cotunelling processes, which tends to the values of an NS structure for large ds. Above the gap, the differential conductance shows an oscillatory behavior with energy even at very large ds.

Model medication management process in Australian nursing homes using business process modeling.

Science.gov (United States)

Qian, Siyu; Yu, Ping

2013-01-01

One of the reasons for end user avoidance or rejection to use health information systems is poor alignment of the system with healthcare workflow, likely causing by system designers' lack of thorough understanding about healthcare process. Therefore, understanding the healthcare workflow is the essential first step for the design of optimal technologies that will enable care staff to complete the intended tasks faster and better. The often use of multiple or "high risk" medicines by older people in nursing homes has the potential to increase medication error rate. To facilitate the design of information systems with most potential to improve patient safety, this study aims to understand medication management process in nursing homes using business process modeling method. The paper presents study design and preliminary findings from interviewing two registered nurses, who were team leaders in two nursing homes. Although there were subtle differences in medication management between the two homes, major medication management activities were similar. Further field observation will be conducted. Based on the data collected from observations, an as-is process model for medication management will be developed.

Higher Fasting Plasma Glucose Levels, within the Normal Range, are Associated with Decreased Processing Speed in High Functioning Young Elderly.

Science.gov (United States)

Raizes, Meytal; Elkana, Odelia; Franko, Motty; Ravona Springer, Ramit; Segev, Shlomo; Beeri, Michal Schnaider

2016-01-01

We explored the association of plasma glucose levels within the normal range with processing speed in high functioning young elderly, free of type 2 diabetes mellitus (T2DM). A sample of 41 participants (mean age = 64.7, SD = 10; glucose 94.5 mg/dL, SD = 9.3), were examined with a computerized cognitive battery. Hierarchical linear regression analysis showed that higher plasma glucose levels, albeit within the normal range (levels may have an impact on cognitive function.

Feature scale modeling for etching and deposition processes in semiconductor manufacturing

International Nuclear Information System (INIS)

Pyka, W.

2000-04-01

Simulation of etching and deposition processes as well as three-dimensional geometry generation are important issues in state of the art TCAD applications. Three-dimensional effects are gaining importance for semiconductor devices and for their interconnects. Therefore a strictly physically based simulation of their topography is required. Accurate investigation of single etching and deposition processes has become equally important as process integration. Within this context several aspects of three-dimensional topography simulation have been covered by this thesis and new and interesting results have been achieved in various areas. The algorithmic core of the cell-based structuring element surface propagation method has been optimized and has been eliminated from its position as factor which predominantly determines the required CPU time. In parallel with investigated optimization techniques and required by various process models, the implementation of the surface normal calculation and the special handling of voids and unconnected parts of the geometry has been completed in three dimensions. A process-step-based solid modeling tool which incorporates layout data as well as aerial image simulation has been supplied. It can be coupled with the topography simulation and includes simple geometrically based models for CMP and oxidation. In the presented combination, the tool makes use of the design information stored in the layout file, combines it with the manufacturing recipe, and hence is extremely helpful for the automatic generation of three-dimensional structures. Its usefulness has been proven with several interconnect examples. Regarding topography models, resist development not only turned out to be very helpful for predicting exposed and etched resist profiles within a rigorous lithography simulation, but, by means of benchmark examples, also demonstrated the extraordinary stability of the proposed cellular surface movement algorithm. With respect to

Simulation Modeling of Software Development Processes

Science.gov (United States)

Calavaro, G. F.; Basili, V. R.; Iazeolla, G.

1996-01-01

A simulation modeling approach is proposed for the prediction of software process productivity indices, such as cost and time-to-market, and the sensitivity analysis of such indices to changes in the organization parameters and user requirements. The approach uses a timed Petri Net and Object Oriented top-down model specification. Results demonstrate the model representativeness, and its usefulness in verifying process conformance to expectations, and in performing continuous process improvement and optimization.

Social software for business process modeling

NARCIS (Netherlands)

Koschmider, A.; Song, M.S.; Reijers, H.A.

2010-01-01

Formal models of business processes are used for a variety of purposes. But where the elicitation of the characteristics of a business process usually takes place in a collaborative fashion, the building of the final, formal process model is done mostly by a single person. This article presents the

Temporal and speech processing skills in normal hearing individuals exposed to occupational noise.

Science.gov (United States)

Kumar, U Ajith; Ameenudin, Syed; Sangamanatha, A V

2012-01-01

Prolonged exposure to high levels of occupational noise can cause damage to hair cells in the cochlea and result in permanent noise-induced cochlear hearing loss. Consequences of cochlear hearing loss on speech perception and psychophysical abilities have been well documented. Primary goal of this research was to explore temporal processing and speech perception Skills in individuals who are exposed to occupational noise of more than 80 dBA and not yet incurred clinically significant threshold shifts. Contribution of temporal processing skills to speech perception in adverse listening situation was also evaluated. A total of 118 participants took part in this research. Participants comprised three groups of train drivers in the age range of 30-40 (n= 13), 41 50 ( = 13), 41-50 (n = 9), and 51-60 (n = 6) years and their non-noise-exposed counterparts (n = 30 in each age group). Participants of all the groups including the train drivers had hearing sensitivity within 25 dB HL in the octave frequencies between 250 and 8 kHz. Temporal processing was evaluated using gap detection, modulation detection, and duration pattern tests. Speech recognition was tested in presence multi-talker babble at -5dB SNR. Differences between experimental and control groups were analyzed using ANOVA and independent sample t-tests. Results showed a trend of reduced temporal processing skills in individuals with noise exposure. These deficits were observed despite normal peripheral hearing sensitivity. Speech recognition scores in the presence of noise were also significantly poor in noise-exposed group. Furthermore, poor temporal processing skills partially accounted for the speech recognition difficulties exhibited by the noise-exposed individuals. These results suggest that noise can cause significant distortions in the processing of suprathreshold temporal cues which may add to difficulties in hearing in adverse listening conditions.

Temporal and speech processing skills in normal hearing individuals exposed to occupational noise

Directory of Open Access Journals (Sweden)

U Ajith Kumar

2012-01-01

Full Text Available Prolonged exposure to high levels of occupational noise can cause damage to hair cells in the cochlea and result in permanent noise-induced cochlear hearing loss. Consequences of cochlear hearing loss on speech perception and psychophysical abilities have been well documented. Primary goal of this research was to explore temporal processing and speech perception Skills in individuals who are exposed to occupational noise of more than 80 dBA and not yet incurred clinically significant threshold shifts. Contribution of temporal processing skills to speech perception in adverse listening situation was also evaluated. A total of 118 participants took part in this research. Participants comprised three groups of train drivers in the age range of 30-40 (n= 13, 41 50 ( = 13, 41-50 (n = 9, and 51-60 (n = 6 years and their non-noise-exposed counterparts (n = 30 in each age group. Participants of all the groups including the train drivers had hearing sensitivity within 25 dB HL in the octave frequencies between 250 and 8 kHz. Temporal processing was evaluated using gap detection, modulation detection, and duration pattern tests. Speech recognition was tested in presence multi-talker babble at -5dB SNR. Differences between experimental and control groups were analyzed using ANOVA and independent sample t-tests. Results showed a trend of reduced temporal processing skills in individuals with noise exposure. These deficits were observed despite normal peripheral hearing sensitivity. Speech recognition scores in the presence of noise were also significantly poor in noise-exposed group. Furthermore, poor temporal processing skills partially accounted for the speech recognition difficulties exhibited by the noise-exposed individuals. These results suggest that noise can cause significant distortions in the processing of suprathreshold temporal cues which may add to difficulties in hearing in adverse listening conditions.

Modal analysis of inter-area oscillations using the theory of normal modes

Energy Technology Data Exchange (ETDEWEB)

Betancourt, R.J. [School of Electromechanical Engineering, University of Colima, Manzanillo, Col. 28860 (Mexico); Barocio, E. [CUCEI, University of Guadalajara, Guadalajara, Jal. 44480 (Mexico); Messina, A.R. [Graduate Program in Electrical Engineering, Cinvestav, Guadalajara, Jal. 45015 (Mexico); Martinez, I. [State Autonomous University of Mexico, Toluca, Edo. Mex. 50110 (Mexico)

2009-04-15

Based on the notion of normal modes in mechanical systems, a method is proposed for the analysis and characterization of oscillatory processes in power systems. The method is based on the property of invariance of modal subspaces and can be used to represent complex power system modal behavior by a set of decoupled, two-degree-of-freedom nonlinear oscillator equations. Using techniques from nonlinear mechanics, a new approach is outlined, for determining the normal modes (NMs) of motion of a general n-degree-of-freedom nonlinear system. Equations relating the normal modes and the physical velocities and displacements are developed from the linearized system model and numerical issues associated with the application of the technique are discussed. In addition to qualitative insight, this method can be utilized in the study of nonlinear behavior and bifurcation analyses. The application of these procedures is illustrated on a planning model of the Mexican interconnected system using a quadratic nonlinear model. Specifically, the use of normal mode analysis as a basis for identifying modal parameters, including natural frequencies and damping ratios of general, linear systems with n degrees of freedom is discussed. Comparisons to conventional linear analysis techniques demonstrate the ability of the proposed technique to extract the different oscillation modes embedded in the oscillation. (author)

Modeling business processes: theoretical and practical aspects

Directory of Open Access Journals (Sweden)

V.V. Dubininа

2015-06-01

Full Text Available The essence of process-oriented enterprise management has been examined in the article. The content and types of information technology have been analyzed in the article, due to the complexity and differentiation of existing methods, as well as the specificity of language, terminology of the enterprise business processes modeling. The theoretical aspects of business processes modeling have been reviewed and the modern traditional modeling techniques received practical application in the visualization model of retailers activity have been studied in the article. In the process of theoretical analysis of the modeling methods found that UFO-toolkit method that has been developed by Ukrainian scientists due to it systemology integrated opportunities, is the most suitable for structural and object analysis of retailers business processes. It was designed visualized simulation model of the business process "sales" as is" of retailers using a combination UFO-elements with the aim of the further practical formalization and optimization of a given business process.

Qualitative simulation in formal process modelling

International Nuclear Information System (INIS)

Sivertsen, Elin R.

1999-01-01

In relation to several different research activities at the OECD Halden Reactor Project, the usefulness of formal process models has been identified. Being represented in some appropriate representation language, the purpose of these models is to model process plants and plant automatics in a unified way to allow verification and computer aided design of control strategies. The present report discusses qualitative simulation and the tool QSIM as one approach to formal process models. In particular, the report aims at investigating how recent improvements of the tool facilitate the use of the approach in areas like process system analysis, procedure verification, and control software safety analysis. An important long term goal is to provide a basis for using qualitative reasoning in combination with other techniques to facilitate the treatment of embedded programmable systems in Probabilistic Safety Analysis (PSA). This is motivated from the potential of such a combination in safety analysis based on models comprising both software, hardware, and operator. It is anticipated that the research results from this activity will benefit V and V in a wide variety of applications where formal process models can be utilized. Examples are operator procedures, intelligent decision support systems, and common model repositories (author) (ml)

IBUPROFEN AS A MEDICATION FOR A CORRECTION OF SYMPTOMS OF NORMAL VACCINAL PROCESS IN CHILDREN

Directory of Open Access Journals (Sweden)

T.A. Chebotareva

2008-01-01

Full Text Available The pathogenetic approach to treatment of symptoms of normal vaccinal process in children after standard vaccination, based on the results of application of anti9inflammatory medications — ibuprofen (nurofen for children and paracetamol is presented in this article. Clinical activity of ibuprofen was established on the basis of clinica catamnestic observation of 856 vaccinated children aged from 3 months to 3 years. recommendations for application of these medications as a treatment for a correction of vaccinal reactions are given.Key words: children, ibuprofen, paracetamol, vaccination.

Information processing in micro and meso-scale neural circuits during normal and disease states

Science.gov (United States)

Luongo, Francisco

Neural computation can occur at multiple spatial and temporal timescales. The sum total of all of these processes is to guide optimal behaviors within the context of the constraints imposed by the physical world. How the circuits of the brain achieves this goal represents a central question in systems neuroscience. Here I explore the many ways in which the circuits of the brain can process information at both the micro and meso scale. Understanding the way information is represented and processed in the brain could shed light on the neuropathology underlying complex neuropsychiatric diseases such as autism and schizophrenia. Chapter 2 establishes an experimental paradigm for assaying patterns of microcircuit activity and examines the role of dopaminergic modulation on prefrontal microcircuits. We find that dopamine type 2 (D2) receptor activation results in an increase in spontaneous activity while dopamine type 1 (D1) activation does not. Chapter 3 of this dissertation presents a study that illustrates how cholingergic activation normally produces what has been suggested as a neural substrate of attention; pairwise decorrelation in microcircuit activity. This study also shows that in two etiologicall distinct mouse models of autism, FMR1 knockout mice and Valproic Acid exposed mice, this ability to decorrelate in the presence of cholinergic activation is lost. This represents a putative microcircuit level biomarker of autism. Chapter 4 examines the structure/function relationship within the prefrontal microcircuit. Spontaneous activity in prefrontal microcircuits is shown to be organized according to a small world architecture. Interestingly, this architecture is important for one concrete function of neuronal microcircuits; the ability to produce temporally stereotyped patterns of activation. In the final chapter, we identify subnetworks in chronic intracranial electrocorticographic (ECoG) recordings using pairwise electrode coherence and dimensionality reduction

Modeling closed nuclear fuel cycles processes

Energy Technology Data Exchange (ETDEWEB)

Shmidt, O.V. [A.A. Bochvar All-Russian Scientific Research Institute for Inorganic Materials, Rogova, 5a street, Moscow, 123098 (Russian Federation); Makeeva, I.R. [Zababakhin All-Russian Scientific Research Institute of Technical Physics, Vasiliev street 13, Snezhinsk, Chelyabinsk region, 456770 (Russian Federation); Liventsov, S.N. [Tomsk Polytechnic University, Tomsk, Lenin Avenue, 30, 634050 (Russian Federation)

2016-07-01

Computer models of processes are necessary for determination of optimal operating conditions for closed nuclear fuel cycle (NFC) processes. Computer models can be quickly changed in accordance with new and fresh data from experimental research. 3 kinds of process simulation are necessary. First, the VIZART software package is a balance model development used for calculating the material flow in technological processes. VIZART involves taking into account of equipment capacity, transport lines and storage volumes. Secondly, it is necessary to simulate the physico-chemical processes that are involved in the closure of NFC. The third kind of simulation is the development of software that allows the optimization, diagnostics and control of the processes which implies real-time simulation of product flows on the whole plant or on separate lines of the plant. (A.C.)

Eye Tracking Meets the Process of Process Modeling: a Visual Analytic Approach

DEFF Research Database (Denmark)

Burattin, Andrea; Kaiser, M.; Neurauter, Manuel

2017-01-01

Research on the process of process modeling (PPM) studies how process models are created. It typically uses the logs of the interactions with the modeling tool to assess the modeler’s behavior. In this paper we suggest to introduce an additional stream of data (i.e., eye tracking) to improve the ...

Modeling biochemical transformation processes and information processing with Narrator.

Science.gov (United States)

Mandel, Johannes J; Fuss, Hendrik; Palfreyman, Niall M; Dubitzky, Werner

2007-03-27

Software tools that model and simulate the dynamics of biological processes and systems are becoming increasingly important. Some of these tools offer sophisticated graphical user interfaces (GUIs), which greatly enhance their acceptance by users. Such GUIs are based on symbolic or graphical notations used to describe, interact and communicate the developed models. Typically, these graphical notations are geared towards conventional biochemical pathway diagrams. They permit the user to represent the transport and transformation of chemical species and to define inhibitory and stimulatory dependencies. A critical weakness of existing tools is their lack of supporting an integrative representation of transport, transformation as well as biological information processing. Narrator is a software tool facilitating the development and simulation of biological systems as Co-dependence models. The Co-dependence Methodology complements the representation of species transport and transformation together with an explicit mechanism to express biological information processing. Thus, Co-dependence models explicitly capture, for instance, signal processing structures and the influence of exogenous factors or events affecting certain parts of a biological system or process. This combined set of features provides the system biologist with a powerful tool to describe and explore the dynamics of life phenomena. Narrator's GUI is based on an expressive graphical notation which forms an integral part of the Co-dependence Methodology. Behind the user-friendly GUI, Narrator hides a flexible feature which makes it relatively easy to map models defined via the graphical notation to mathematical formalisms and languages such as ordinary differential equations, the Systems Biology Markup Language or Gillespie's direct method. This powerful feature facilitates reuse, interoperability and conceptual model development. Narrator is a flexible and intuitive systems biology tool. It is

The Formalization of the Business Process Modeling Goals

Directory of Open Access Journals (Sweden)

Ligita Bušinska

2016-10-01

Full Text Available In business process modeling the de facto standard BPMN has emerged. However, the applications of this notation have many subsets of elements and various extensions. Also, BPMN still coincides with many other modeling languages, forming a large set of available options for business process modeling languages and dialects. While, in general, the goal of modelers is a central notion in the choice of modeling languages and notations, in most researches that propose guidelines, techniques, and methods for business process modeling language evaluation and/or selection, the business process modeling goal is not formalized and not transparently taken into account. To overcome this gap, and to explicate and help to handle business process modeling complexity, the approach to formalize the business process modeling goal, and the supporting three dimensional business process modeling framework, are proposed.

Non-homogeneous Markov process models with informative observations with an application to Alzheimer's disease.

Science.gov (United States)

Chen, Baojiang; Zhou, Xiao-Hua

2011-05-01

Identifying risk factors for transition rates among normal cognition, mildly cognitive impairment, dementia and death in an Alzheimer's disease study is very important. It is known that transition rates among these states are strongly time dependent. While Markov process models are often used to describe these disease progressions, the literature mainly focuses on time homogeneous processes, and limited tools are available for dealing with non-homogeneity. Further, patients may choose when they want to visit the clinics, which creates informative observations. In this paper, we develop methods to deal with non-homogeneous Markov processes through time scale transformation when observation times are pre-planned with some observations missing. Maximum likelihood estimation via the EM algorithm is derived for parameter estimation. Simulation studies demonstrate that the proposed method works well under a variety of situations. An application to the Alzheimer's disease study identifies that there is a significant increase in transition rates as a function of time. Furthermore, our models reveal that the non-ignorable missing mechanism is perhaps reasonable. Copyright © 2011 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Objective classification of latent behavioral states in bio-logging data using multivariate-normal hidden Markov models.

Science.gov (United States)

Phillips, Joe Scutt; Patterson, Toby A; Leroy, Bruno; Pilling, Graham M; Nicol, Simon J

2015-07-01

Analysis of complex time-series data from ecological system study requires quantitative tools for objective description and classification. These tools must take into account largely ignored problems of bias in manual classification, autocorrelation, and noise. Here we describe a method using existing estimation techniques for multivariate-normal hidden Markov models (HMMs) to develop such a classification. We use high-resolution behavioral data from bio-loggers attached to free-roaming pelagic tuna as an example. Observed patterns are assumed to be generated by an unseen Markov process that switches between several multivariate-normal distributions. Our approach is assessed in two parts. The first uses simulation experiments, from which the ability of the HMM to estimate known parameter values is examined using artificial time series of data consistent with hypotheses about pelagic predator foraging ecology. The second is the application to time series of continuous vertical movement data from yellowfin and bigeye tuna taken from tuna tagging experiments. These data were compressed into summary metrics capturing the variation of patterns in diving behavior and formed into a multivariate time series used to estimate a HMM. Each observation was associated with covariate information incorporating the effect of day and night on behavioral switching. Known parameter values were well recovered by the HMMs in our simulation experiments, resulting in mean correct classification rates of 90-97%, although some variance-covariance parameters were estimated less accurately. HMMs with two distinct behavioral states were selected for every time series of real tuna data, predicting a shallow warm state, which was similar across all individuals, and a deep colder state, which was more variable. Marked diurnal behavioral switching was predicted, consistent with many previous empirical studies on tuna. HMMs provide easily interpretable models for the objective classification of

Pre-Processing and Modeling Tools for Bigdata

Directory of Open Access Journals (Sweden)

Hashem Hadi

2016-09-01

Full Text Available Modeling tools and operators help the user / developer to identify the processing field on the top of the sequence and to send into the computing module only the data related to the requested result. The remaining data is not relevant and it will slow down the processing. The biggest challenge nowadays is to get high quality processing results with a reduced computing time and costs. To do so, we must review the processing sequence, by adding several modeling tools. The existing processing models do not take in consideration this aspect and focus on getting high calculation performances which will increase the computing time and costs. In this paper we provide a study of the main modeling tools for BigData and a new model based on pre-processing.

Kopernik : modeling business processes for digital customers

OpenAIRE

Estañol Lamarca, Montserrat; Castro, Manuel; Díaz-Montenegro, Sylvia; Teniente López, Ernest

2016-01-01

This paper presents the Kopernik methodology for modeling business processes for digital customers. These processes require a high degree of flexibility in the execution of their tasks or actions. We achieve this by using the artifact-centric approach to process modeling and the use of condition-action rules. The processes modeled following Kopernik can then be implemented in an existing commercial tool, Balandra.

Normalization and Implementation of Three Gravitational Acceleration Models

Science.gov (United States)

Eckman, Randy A.; Brown, Aaron J.; Adamo, Daniel R.; Gottlieb, Robert G.

2016-01-01

Unlike the uniform density spherical shell approximations of Newton, the consequence of spaceflight in the real universe is that gravitational fields are sensitive to the asphericity of their generating central bodies. The gravitational potential of an aspherical central body is typically resolved using spherical harmonic approximations. However, attempting to directly calculate the spherical harmonic approximations results in at least two singularities that must be removed to generalize the method and solve for any possible orbit, including polar orbits. Samuel Pines, Bill Lear, and Robert Gottlieb developed three unique algorithms to eliminate these singularities. This paper documents the methodical normalization of two of the three known formulations for singularity-free gravitational acceleration (namely, the Lear and Gottlieb algorithms) and formulates a general method for defining normalization parameters used to generate normalized Legendre polynomials and Associated Legendre Functions (ALFs) for any algorithm. A treatment of the conventional formulation of the gravitational potential and acceleration is also provided, in addition to a brief overview of the philosophical differences between the three known singularity-free algorithms.

Specification of e-business process model for PayPal online payment process using Reo

OpenAIRE

Xie, M.

2005-01-01

textabstractE-business process modeling allows business analysts to better understand and analyze the business processes, and eventually to use software systems to automate (parts of) these business processes to achieve higher profit. To support e-business process modeling, many business process modeling languages have been used as tools. However, many existing business process modeling languages lack (a) formal semantics, (b) formal computational model, and (c) an integrated view of the busi...

Assessment of ANN and SVM models for estimating normal direct irradiation (H_b)

International Nuclear Information System (INIS)

Santos, Cícero Manoel dos; Escobedo, João Francisco; Teramoto, Érico Tadao; Modenese Gorla da Silva, Silvia Helena

2016-01-01

Highlights: • The performance of SVM and ANN in estimating Normal Direct Irradiation (H_b) was evaluated. • 12 models using different input variables are developed (hourly and daily partitions). • The most relevant input variables for DNI are kt, H_s_c and insolation ratio (r′ = n/N). • Support Vector Machine (SVM) provides accurate estimates and outperforms the Artificial Neural Network (ANN). - Abstract: This study evaluates the estimation of hourly and daily normal direct irradiation (H_b) using machine learning techniques (ML): Artificial Neural Network (ANN) and Support Vector Machine (SVM). Time series of different meteorological variables measured over thirteen years in Botucatu were used for training and validating ANN and SVM. Seven different sets of input variables were tested and evaluated, which were chosen based on statistical models reported in the literature. Relative Mean Bias Error (rMBE), Relative Root Mean Square Error (rRMSE), determination coefficient (R"2) and “d” Willmott index were used to evaluate ANN and SVM models. When compared to statistical models which use the same set of input variables (R"2 between 0.22 and 0.78), ANN and SVM show higher values of R"2 (hourly models between 0.52 and 0.88; daily models between 0.42 and 0.91). Considering the input variables, atmospheric transmissivity of global radiation (kt), integrated solar constant (H_s_c) and insolation ratio (n/N, n is sunshine duration and N is photoperiod) were the most relevant in ANN and SVM models. The rMBE and rRMSE values in the two time partitions of SVM models are lower than those obtained with ANN. Hourly ANN and SVM models have higher rRMSE values than daily models. Optimal performance with hourly models was obtained with ANN4"h (rMBE = 12.24%, rRMSE = 23.99% and “d” = 0.96) and SVM4"h (rMBE = 1.75%, rRMSE = 20.10% and “d” = 0.96). Optimal performance with daily models was obtained with ANN2"d (rMBE = −3.09%, rRMSE = 18.95% and “d” = 0

Process mining using BPMN: relating event logs and process models

NARCIS (Netherlands)

Kalenkova, A.A.; van der Aalst, W.M.P.; Lomazova, I.A.; Rubin, V.A.

2017-01-01

Process-aware information systems (PAIS) are systems relying on processes, which involve human and software resources to achieve concrete goals. There is a need to develop approaches for modeling, analysis, improvement and monitoring processes within PAIS. These approaches include process mining

Process mining using BPMN : relating event logs and process models

NARCIS (Netherlands)

Kalenkova, A.A.; Aalst, van der W.M.P.; Lomazova, I.A.; Rubin, V.A.

2015-01-01

Process-aware information systems (PAIS) are systems relying on processes, which involve human and software resources to achieve concrete goals. There is a need to develop approaches for modeling, analysis, improvement and monitoring processes within PAIS. These approaches include process mining

A Comparative of business process modelling techniques

Science.gov (United States)

Tangkawarow, I. R. H. T.; Waworuntu, J.

2016-04-01

In this era, there is a lot of business process modeling techniques. This article is the research about differences of business process modeling techniques. For each technique will explain about the definition and the structure. This paper presents a comparative analysis of some popular business process modelling techniques. The comparative framework is based on 2 criteria: notation and how it works when implemented in Somerleyton Animal Park. Each technique will end with the advantages and disadvantages. The final conclusion will give recommend of business process modeling techniques that easy to use and serve the basis for evaluating further modelling techniques.

Piecewise deterministic processes in biological models

CERN Document Server

Rudnicki, Ryszard

2017-01-01

This book presents a concise introduction to piecewise deterministic Markov processes (PDMPs), with particular emphasis on their applications to biological models. Further, it presents examples of biological phenomena, such as gene activity and population growth, where different types of PDMPs appear: continuous time Markov chains, deterministic processes with jumps, processes with switching dynamics, and point processes. Subsequent chapters present the necessary tools from the theory of stochastic processes and semigroups of linear operators, as well as theoretical results concerning the long-time behaviour of stochastic semigroups induced by PDMPs and their applications to biological models. As such, the book offers a valuable resource for mathematicians and biologists alike. The first group will find new biological models that lead to interesting and often new mathematical questions, while the second can observe how to include seemingly disparate biological processes into a unified mathematical theory, and...

Computer Aided Continuous Time Stochastic Process Modelling

DEFF Research Database (Denmark)

Kristensen, N.R.; Madsen, Henrik; Jørgensen, Sten Bay

2001-01-01

A grey-box approach to process modelling that combines deterministic and stochastic modelling is advocated for identification of models for model-based control of batch and semi-batch processes. A computer-aided tool designed for supporting decision-making within the corresponding modelling cycle...

Individual loss reserving with the Multivariate Skew Normal model

NARCIS (Netherlands)

Pigeon, M.; Antonio, K.; Denuit, M.

2011-01-01

In general insurance, the evaluation of future cash ows and solvency capital has become increasingly important. To assist in this process, the present paper proposes an individual discrete-time loss re- serving model describing the occurrence, the reporting delay, the timeto the first payment, and

Neuroscientific Model of Motivational Process

OpenAIRE

Kim, Sung-il

2013-01-01

Considering the neuroscientific findings on reward, learning, value, decision-making, and cognitive control, motivation can be parsed into three sub processes, a process of generating motivation, a process of maintaining motivation, and a process of regulating motivation. I propose a tentative neuroscientific model of motivational processes which consists of three distinct but continuous sub processes, namely reward-driven approach, value-based decision-making, and goal-directed control. Rewa...

Measures of Quality in Business Process Modelling

Directory of Open Access Journals (Sweden)

Radek Hronza

2015-06-01

Full Text Available Business process modelling and analysing is undoubtedly one of the most important parts of Applied (Business Informatics. Quality of business process models (diagrams is crucial for any purpose in this area. The goal of a process analyst’s work is to create generally understandable, explicit and error free models. If a process is properly described, created models can be used as an input into deep analysis and optimization. It can be assumed that properly designed business process models (similarly as in the case of correctly written algorithms contain characteristics that can be mathematically described. Besides it will be possible to create a tool that will help process analysts to design proper models. As part of this review will be conducted systematic literature review in order to find and analyse business process model’s design and business process model’s quality measures. It was found that mentioned area had already been the subject of research investigation in the past. Thirty-three suitable scietific publications and twenty-two quality measures were found. Analysed scientific publications and existing quality measures do not reflect all important attributes of business process model’s clarity, simplicity and completeness. Therefore it would be appropriate to add new measures of quality.

Hypothyroidism after primary radiotherapy for head and neck squamous cell carcinoma: Normal tissue complication probability modeling with latent time correction

DEFF Research Database (Denmark)

Rønjom, Marianne Feen; Brink, Carsten; Bentzen, Søren

2013-01-01

To develop a normal tissue complication probability (NTCP) model of radiation-induced biochemical hypothyroidism (HT) after primary radiotherapy for head and neck squamous cell carcinoma (HNSCC) with adjustment for latency and clinical risk factors.......To develop a normal tissue complication probability (NTCP) model of radiation-induced biochemical hypothyroidism (HT) after primary radiotherapy for head and neck squamous cell carcinoma (HNSCC) with adjustment for latency and clinical risk factors....

Modeling of ETL-Processes and Processed Information in Clinical Data Warehousing.

Science.gov (United States)

Tute, Erik; Steiner, Jochen

2018-01-01

Literature describes a big potential for reuse of clinical patient data. A clinical data warehouse (CDWH) is a means for that. To support management and maintenance of processes extracting, transforming and loading (ETL) data into CDWHs as well as to ease reuse of metadata between regular IT-management, CDWH and secondary data users by providing a modeling approach. Expert survey and literature review to find requirements and existing modeling techniques. An ETL-modeling-technique was developed extending existing modeling techniques. Evaluation by exemplarily modeling existing ETL-process and a second expert survey. Nine experts participated in the first survey. Literature review yielded 15 included publications. Six existing modeling techniques were identified. A modeling technique extending 3LGM2 and combining it with openEHR information models was developed and evaluated. Seven experts participated in the evaluation. The developed approach can help in management and maintenance of ETL-processes and could serve as interface between regular IT-management, CDWH and secondary data users.

Simulation Models of Human Decision-Making Processes

Directory of Open Access Journals (Sweden)

Nina RIZUN

2014-10-01

Full Text Available The main purpose of the paper is presentation of the new concept of human decision-making process modeling via using the analogy with Automatic Control Theory. From the author's point of view this concept allows to develop and improve the theory of decision-making in terms of the study and classification of specificity of the human intellectual processes in different conditions. It was proved that the main distinguishing feature between the Heuristic / Intuitive and Rational Decision-Making Models is the presence of so-called phenomenon of "enrichment" of the input information with human propensity, hobbies, tendencies, expectations, axioms and judgments, presumptions or bias and their justification. In order to obtain additional knowledge about the basic intellectual processes as well as the possibility of modeling the decision results in various parameters characterizing the decision-maker, the complex of the simulation models was developed. These models are based on the assumptions that:  basic intellectual processes of the Rational Decision-Making Model can be adequately simulated and identified by the transient processes of the proportional-integral-derivative controller; basic intellectual processes of the Bounded Rationality and Intuitive Models can be adequately simulated and identified by the transient processes of the nonlinear elements.The taxonomy of the most typical automatic control theory elements and their compliance with certain decision-making models with a point of view of decision-making process specificity and decision-maker behavior during a certain time of professional activity was obtained.

User-guided discovery of declarative process models

NARCIS (Netherlands)

Maggi, F.M.; Mooij, A.J.; Aalst, van der W.M.P.; Chawla, N.; King, I.; Sperduti, A.

2011-01-01

Process mining techniques can be used to effectively discover process models from logs with example behaviour. Cross-correlating a discovered model with information in the log can be used to improve the underlying process. However, existing process discovery techniques have two important drawbacks.

A Hierarchical Poisson Log-Normal Model for Network Inference from RNA Sequencing Data

Science.gov (United States)

Gallopin, Mélina; Rau, Andrea; Jaffrézic, Florence

2013-01-01

Gene network inference from transcriptomic data is an important methodological challenge and a key aspect of systems biology. Although several methods have been proposed to infer networks from microarray data, there is a need for inference methods able to model RNA-seq data, which are count-based and highly variable. In this work we propose a hierarchical Poisson log-normal model with a Lasso penalty to infer gene networks from RNA-seq data; this model has the advantage of directly modelling discrete data and accounting for inter-sample variance larger than the sample mean. Using real microRNA-seq data from breast cancer tumors and simulations, we compare this method to a regularized Gaussian graphical model on log-transformed data, and a Poisson log-linear graphical model with a Lasso penalty on power-transformed data. For data simulated with large inter-sample dispersion, the proposed model performs better than the other methods in terms of sensitivity, specificity and area under the ROC curve. These results show the necessity of methods specifically designed for gene network inference from RNA-seq data. PMID:24147011

Deferred Action: Theoretical model of process architecture design for emergent business processes

Directory of Open Access Journals (Sweden)

Patel, N.V.

2007-01-01

Full Text Available E-Business modelling and ebusiness systems development assumes fixed company resources, structures, and business processes. Empirical and theoretical evidence suggests that company resources and structures are emergent rather than fixed. Planning business activity in emergent contexts requires flexible ebusiness models based on better management theories and models . This paper builds and proposes a theoretical model of ebusiness systems capable of catering for emergent factors that affect business processes. Drawing on development of theories of the ‘action and design’class the Theory of Deferred Action is invoked as the base theory for the theoretical model. A theoretical model of flexible process architecture is presented by identifying its core components and their relationships, and then illustrated with exemplar flexible process architectures capable of responding to emergent factors. Managerial implications of the model are considered and the model’s generic applicability is discussed.

Differentiation of prostate cancer from normal prostate tissue in an animal model: conventional MRI and dynamic contrast-enhanced MRI

International Nuclear Information System (INIS)

Gemeinhardt, O.; Prochnow, D.; Taupitz, M.; Hamm, B.; Beyersdorff, D.; Luedemann, L.; Abramjuk, C.

2005-01-01

Purpose: to differentiate orthotopically implanted prostate cancer from normal prostate tissue using magnetic resonance imaging (MRI) and Gd-DTPA-BMA-enhanced dynamic MRI in the rat model. Material and methods: tumors were induced in 15 rats by orthotopic implantation of G subline Dunning rat prostatic tumor cells. MRI was performed 56 to 60 days after tumor cell implantation using T1-weighted spin-echo, T2-weighted turbo SE sequences, and a 2D FLASH sequence for the contrast medium based dynamic study. The interstitial leakage volume, normalized permeability and the permeability surface area product of tumor and healthy prostate were determined quantitatively using a pharmacokinetic model. The results were confirmed by histologic examination. Results: axial T2-weighted TSE images depicted low-intensity areas suspicious for tumor in all 15 animals. The mean tumor volume was 46.5 mm3. In the dynamic study, the suspicious areas in all animals displayed faster and more pronounced signal enhancement than surrounding prostate tissue. The interstitial volume and the permeability surface area product of the tumors increased significantly by 420% (p<0.001) and 424% (p<0.001), respectively, compared to normal prostate tissue, while no significant difference was seen for normalized permeability alone. Conclusion: the results of the present study demonstrate that quantitative analysis of contrast-enhanced dynamic MRI data enables differentiation of small, slowly growing orthotopic prostate cancer from normal prostate tissue in the rat model. (orig.)

Surface morphology of active normal faults in hard rock: Implications for the mechanics of the Asal Rift, Djibouti

Science.gov (United States)

Pinzuti, Paul; Mignan, Arnaud; King, Geoffrey C. P.

2010-10-01

Tectonic-stretching models have been previously proposed to explain the process of continental break-up through the example of the Asal Rift, Djibouti, one of the few places where the early stages of seafloor spreading can be observed. In these models, deformation is distributed starting at the base of a shallow seismogenic zone, in which sub-vertical normal faults are responsible for subsidence whereas cracks accommodate extension. Alternative models suggest that extension results from localised magma intrusion, with normal faults accommodating extension and subsidence only above the maximum reach of the magma column. In these magmatic rifting models, or so-called magmatic intrusion models, normal faults have dips of 45-55° and root into dikes. Vertical profiles of normal fault scarps from levelling campaign in the Asal Rift, where normal faults seem sub-vertical at surface level, have been analysed to discuss the creation and evolution of normal faults in massive fractured rocks (basalt lava flows), using mechanical and kinematics concepts. We show that the studied normal fault planes actually have an average dip ranging between 45° and 65° and are characterised by an irregular stepped form. We suggest that these normal fault scarps correspond to sub-vertical en echelon structures, and that, at greater depth, these scarps combine and give birth to dipping normal faults. The results of our analysis are compatible with the magmatic intrusion models instead of tectonic-stretching models. The geometry of faulting between the Fieale volcano and Lake Asal in the Asal Rift can be simply related to the depth of diking, which in turn can be related to magma supply. This new view supports the magmatic intrusion model of early stages of continental breaking.

Differential expression and processing of transforming growth factor beta induced protein (TGFBIp) in the normal human cornea during postnatal development and aging

DEFF Research Database (Denmark)

Karring, Henrik; Runager, Kasper; Valnickova, Zuzana

2010-01-01

Transforming growth factor beta induced protein (TGFBIp, also named keratoepithelin) is an extracellular matrix protein abundant in the cornea. The purpose of this study was to determine the expression and processing of TGFBIp in the normal human cornea during postnatal development and aging...... trimming events from the N-terminus of mature TGFBIp generate TGFBIp isoforms which form a similar "zig-zag" pattern when separated by 2-D polyacrylamide gel electrophoresis (PAGE). This study shows that in humans TGFBIp is more abundant in mature corneas than in the developing cornea...... and that the processing of TGFBIp changes during postnatal development of the cornea. In addition, TGFBIp appears to be degraded in a highly orchestrated manner in the normal human cornea with the resulting C-terminal fragments being retained in the cornea. The age-related changes in the expression and processing...

A review of shear strength models for rock joints subjected to constant normal stiffness

Directory of Open Access Journals (Sweden)

Sivanathan Thirukumaran

2016-06-01

Full Text Available The typical shear behaviour of rough joints has been studied under constant normal load/stress (CNL boundary conditions, but recent studies have shown that this boundary condition may not replicate true practical situations. Constant normal stiffness (CNS is more appropriate to describe the stress–strain response of field joints since the CNS boundary condition is more realistic than CNL. The practical implications of CNS are movements of unstable blocks in the roof or walls of an underground excavation, reinforced rock wedges sliding in a rock slope or foundation, and the vertical movement of rock-socketed concrete piles. In this paper, the highlights and limitations of the existing models used to predict the shear strength/behaviour of joints under CNS conditions are discussed in depth.

Modelling Hospital Materials Management Processes

Directory of Open Access Journals (Sweden)

Raffaele Iannone

2013-06-01

integrated and detailed analysis and description model for hospital materials management data and tasks, which is able to tackle information from patient requirements to usage, from replenishment requests to supplying and handling activities. The model takes account of medical risk reduction, traceability and streamlined processes perspectives. Second, the paper translates this information into a business process model and mathematical formalization.The study provides a useful guide to the various relevant technology‐related, management and business issues, laying the foundations of an efficient reengineering of the supply chain to reduce healthcare costs and improve the quality of care.

Regime-switching models to study psychological process

NARCIS (Netherlands)

Hamaker, E.L.; Grasman, R.P.P.P.; Kamphuis, J.H.

2010-01-01

Many psychological processes are characterized by recurrent shifts between different states. To model these processes at the level of the individual, regime-switching models may prove useful. In this chapter we discuss two of these models: the threshold autoregressive model and the Markov

Modeling biochemical transformation processes and information processing with Narrator

Directory of Open Access Journals (Sweden)

Palfreyman Niall M

2007-03-01

Full Text Available Abstract Background Software tools that model and simulate the dynamics of biological processes and systems are becoming increasingly important. Some of these tools offer sophisticated graphical user interfaces (GUIs, which greatly enhance their acceptance by users. Such GUIs are based on symbolic or graphical notations used to describe, interact and communicate the developed models. Typically, these graphical notations are geared towards conventional biochemical pathway diagrams. They permit the user to represent the transport and transformation of chemical species and to define inhibitory and stimulatory dependencies. A critical weakness of existing tools is their lack of supporting an integrative representation of transport, transformation as well as biological information processing. Results Narrator is a software tool facilitating the development and simulation of biological systems as Co-dependence models. The Co-dependence Methodology complements the representation of species transport and transformation together with an explicit mechanism to express biological information processing. Thus, Co-dependence models explicitly capture, for instance, signal processing structures and the influence of exogenous factors or events affecting certain parts of a biological system or process. This combined set of features provides the system biologist with a powerful tool to describe and explore the dynamics of life phenomena. Narrator's GUI is based on an expressive graphical notation which forms an integral part of the Co-dependence Methodology. Behind the user-friendly GUI, Narrator hides a flexible feature which makes it relatively easy to map models defined via the graphical notation to mathematical formalisms and languages such as ordinary differential equations, the Systems Biology Markup Language or Gillespie's direct method. This powerful feature facilitates reuse, interoperability and conceptual model development. Conclusion Narrator is a

A finite element propagation model for extracting normal incidence impedance in nonprogressive acoustic wave fields

Science.gov (United States)

Watson, Willie R.; Jones, Michael G.; Tanner, Sharon E.; Parrott, Tony L.

1995-01-01

A propagation model method for extracting the normal incidence impedance of an acoustic material installed as a finite length segment in a wall of a duct carrying a nonprogressive wave field is presented. The method recasts the determination of the unknown impedance as the minimization of the normalized wall pressure error function. A finite element propagation model is combined with a coarse/fine grid impedance plane search technique to extract the impedance of the material. Results are presented for three different materials for which the impedance is known. For each material, the input data required for the prediction scheme was computed from modal theory and then contaminated by random error. The finite element method reproduces the known impedance of each material almost exactly for random errors typical of those found in many measurement environments. Thus, the method developed here provides a means for determining the impedance of materials in a nonprogressirve wave environment such as that usually encountered in a commercial aircraft engine and most laboratory settings.

Linear regression and the normality assumption.

Science.gov (United States)

Schmidt, Amand F; Finan, Chris

2017-12-16

Researchers often perform arbitrary outcome transformations to fulfill the normality assumption of a linear regression model. This commentary explains and illustrates that in large data settings, such transformations are often unnecessary, and worse may bias model estimates. Linear regression assumptions are illustrated using simulated data and an empirical example on the relation between time since type 2 diabetes diagnosis and glycated hemoglobin levels. Simulation results were evaluated on coverage; i.e., the number of times the 95% confidence interval included the true slope coefficient. Although outcome transformations bias point estimates, violations of the normality assumption in linear regression analyses do not. The normality assumption is necessary to unbiasedly estimate standard errors, and hence confidence intervals and P-values. However, in large sample sizes (e.g., where the number of observations per variable is >10) violations of this normality assumption often do not noticeably impact results. Contrary to this, assumptions on, the parametric model, absence of extreme observations, homoscedasticity, and independency of the errors, remain influential even in large sample size settings. Given that modern healthcare research typically includes thousands of subjects focusing on the normality assumption is often unnecessary, does not guarantee valid results, and worse may bias estimates due to the practice of outcome transformations. Copyright © 2017 Elsevier Inc. All rights reserved.

Probabilistic modeling of discourse-aware sentence processing.

Science.gov (United States)

Dubey, Amit; Keller, Frank; Sturt, Patrick

2013-07-01

Probabilistic models of sentence comprehension are increasingly relevant to questions concerning human language processing. However, such models are often limited to syntactic factors. This restriction is unrealistic in light of experimental results suggesting interactions between syntax and other forms of linguistic information in human sentence processing. To address this limitation, this article introduces two sentence processing models that augment a syntactic component with information about discourse co-reference. The novel combination of probabilistic syntactic components with co-reference classifiers permits them to more closely mimic human behavior than existing models. The first model uses a deep model of linguistics, based in part on probabilistic logic, allowing it to make qualitative predictions on experimental data; the second model uses shallow processing to make quantitative predictions on a broad-coverage reading-time corpus. Copyright © 2013 Cognitive Science Society, Inc.

The (Mathematical) Modeling Process in Biosciences.

Science.gov (United States)

Torres, Nestor V; Santos, Guido

2015-01-01

In this communication, we introduce a general framework and discussion on the role of models and the modeling process in the field of biosciences. The objective is to sum up the common procedures during the formalization and analysis of a biological problem from the perspective of Systems Biology, which approaches the study of biological systems as a whole. We begin by presenting the definitions of (biological) system and model. Particular attention is given to the meaning of mathematical model within the context of biology. Then, we present the process of modeling and analysis of biological systems. Three stages are described in detail: conceptualization of the biological system into a model, mathematical formalization of the previous conceptual model and optimization and system management derived from the analysis of the mathematical model. All along this work the main features and shortcomings of the process are analyzed and a set of rules that could help in the task of modeling any biological system are presented. Special regard is given to the formative requirements and the interdisciplinary nature of this approach. We conclude with some general considerations on the challenges that modeling is posing to current biology.

Prediction of failure in tube hydrofonning process using a damage model

International Nuclear Information System (INIS)

Majzoobi, G. H.; Saniee, F. Freshteh; Shirazi, A.

2007-01-01

In tube hydroforming process (THP), two types of loading, internal pressure and axial feeding and in particular the combination of them, are needed to feed the material into the cavities of the die to form the workpiece into the desired shape. If the variation of pressure versus axial feeding is not determined properly, the workpiece may be buckled, wrinkled or burst during THP. The appropriate variation is normally determined by experiment which is expensive and time-consuming. In this work, numerical simulation using Johnson-Cook models for predicting the elasto-plastic response and the failure of the material are employed to obtain the best combination of internal pressure and axial feeding. The numerical simulations are examined by a number of experiments conducted in the present investigation. The results show very close agreement between the numerical simulations and the experiments, suggesting that the numerical simulations using Johnson-Cook material and failure models provide a valuable tool to examine the different parameters involved in THP

Model for Simulating a Spiral Software-Development Process

Science.gov (United States)

Mizell, Carolyn; Curley, Charles; Nayak, Umanath

2010-01-01

A discrete-event simulation model, and a computer program that implements the model, have been developed as means of analyzing a spiral software-development process. This model can be tailored to specific development environments for use by software project managers in making quantitative cases for deciding among different software-development processes, courses of action, and cost estimates. A spiral process can be contrasted with a waterfall process, which is a traditional process that consists of a sequence of activities that include analysis of requirements, design, coding, testing, and support. A spiral process is an iterative process that can be regarded as a repeating modified waterfall process. Each iteration includes assessment of risk, analysis of requirements, design, coding, testing, delivery, and evaluation. A key difference between a spiral and a waterfall process is that a spiral process can accommodate changes in requirements at each iteration, whereas in a waterfall process, requirements are considered to be fixed from the beginning and, therefore, a waterfall process is not flexible enough for some projects, especially those in which requirements are not known at the beginning or may change during development. For a given project, a spiral process may cost more and take more time than does a waterfall process, but may better satisfy a customer's expectations and needs. Models for simulating various waterfall processes have been developed previously, but until now, there have been no models for simulating spiral processes. The present spiral-process-simulating model and the software that implements it were developed by extending a discrete-event simulation process model of the IEEE 12207 Software Development Process, which was built using commercially available software known as the Process Analysis Tradeoff Tool (PATT). Typical inputs to PATT models include industry-average values of product size (expressed as number of lines of code

Software-Engineering Process Simulation (SEPS) model

Science.gov (United States)

Lin, C. Y.; Abdel-Hamid, T.; Sherif, J. S.

1992-01-01

The Software Engineering Process Simulation (SEPS) model is described which was developed at JPL. SEPS is a dynamic simulation model of the software project development process. It uses the feedback principles of system dynamics to simulate the dynamic interactions among various software life cycle development activities and management decision making processes. The model is designed to be a planning tool to examine tradeoffs of cost, schedule, and functionality, and to test the implications of different managerial policies on a project's outcome. Furthermore, SEPS will enable software managers to gain a better understanding of the dynamics of software project development and perform postmodern assessments.

Normal tissue complication probability modeling of radiation-induced hypothyroidism after head-and-neck radiation therapy.

Science.gov (United States)

Bakhshandeh, Mohsen; Hashemi, Bijan; Mahdavi, Seied Rabi Mehdi; Nikoofar, Alireza; Vasheghani, Maryam; Kazemnejad, Anoshirvan

2013-02-01

To determine the dose-response relationship of the thyroid for radiation-induced hypothyroidism in head-and-neck radiation therapy, according to 6 normal tissue complication probability models, and to find the best-fit parameters of the models. Sixty-five patients treated with primary or postoperative radiation therapy for various cancers in the head-and-neck region were prospectively evaluated. Patient serum samples (tri-iodothyronine, thyroxine, thyroid-stimulating hormone [TSH], free tri-iodothyronine, and free thyroxine) were measured before and at regular time intervals until 1 year after the completion of radiation therapy. Dose-volume histograms (DVHs) of the patients' thyroid gland were derived from their computed tomography (CT)-based treatment planning data. Hypothyroidism was defined as increased TSH (subclinical hypothyroidism) or increased TSH in combination with decreased free thyroxine and thyroxine (clinical hypothyroidism). Thyroid DVHs were converted to 2 Gy/fraction equivalent doses using the linear-quadratic formula with α/β = 3 Gy. The evaluated models included the following: Lyman with the DVH reduced to the equivalent uniform dose (EUD), known as LEUD; Logit-EUD; mean dose; relative seriality; individual critical volume; and population critical volume models. The parameters of the models were obtained by fitting the patients' data using a maximum likelihood analysis method. The goodness of fit of the models was determined by the 2-sample Kolmogorov-Smirnov test. Ranking of the models was made according to Akaike's information criterion. Twenty-nine patients (44.6%) experienced hypothyroidism. None of the models was rejected according to the evaluation of the goodness of fit. The mean dose model was ranked as the best model on the basis of its Akaike's information criterion value. The D(50) estimated from the models was approximately 44 Gy. The implemented normal tissue complication probability models showed a parallel architecture for the

Normal Tissue Complication Probability Modeling of Radiation-Induced Hypothyroidism After Head-and-Neck Radiation Therapy

Energy Technology Data Exchange (ETDEWEB)

Bakhshandeh, Mohsen [Department of Medical Physics, Faculty of Medical Sciences, Tarbiat Modares University, Tehran (Iran, Islamic Republic of); Hashemi, Bijan, E-mail: bhashemi@modares.ac.ir [Department of Medical Physics, Faculty of Medical Sciences, Tarbiat Modares University, Tehran (Iran, Islamic Republic of); Mahdavi, Seied Rabi Mehdi [Department of Medical Physics, Faculty of Medical Sciences, Tehran University of Medical Sciences, Tehran (Iran, Islamic Republic of); Nikoofar, Alireza; Vasheghani, Maryam [Department of Radiation Oncology, Hafte-Tir Hospital, Tehran University of Medical Sciences, Tehran (Iran, Islamic Republic of); Kazemnejad, Anoshirvan [Department of Biostatistics, Faculty of Medical Sciences, Tarbiat Modares University, Tehran (Iran, Islamic Republic of)

2013-02-01

Purpose: To determine the dose-response relationship of the thyroid for radiation-induced hypothyroidism in head-and-neck radiation therapy, according to 6 normal tissue complication probability models, and to find the best-fit parameters of the models. Methods and Materials: Sixty-five patients treated with primary or postoperative radiation therapy for various cancers in the head-and-neck region were prospectively evaluated. Patient serum samples (tri-iodothyronine, thyroxine, thyroid-stimulating hormone [TSH], free tri-iodothyronine, and free thyroxine) were measured before and at regular time intervals until 1 year after the completion of radiation therapy. Dose-volume histograms (DVHs) of the patients' thyroid gland were derived from their computed tomography (CT)-based treatment planning data. Hypothyroidism was defined as increased TSH (subclinical hypothyroidism) or increased TSH in combination with decreased free thyroxine and thyroxine (clinical hypothyroidism). Thyroid DVHs were converted to 2 Gy/fraction equivalent doses using the linear-quadratic formula with {alpha}/{beta} = 3 Gy. The evaluated models included the following: Lyman with the DVH reduced to the equivalent uniform dose (EUD), known as LEUD; Logit-EUD; mean dose; relative seriality; individual critical volume; and population critical volume models. The parameters of the models were obtained by fitting the patients' data using a maximum likelihood analysis method. The goodness of fit of the models was determined by the 2-sample Kolmogorov-Smirnov test. Ranking of the models was made according to Akaike's information criterion. Results: Twenty-nine patients (44.6%) experienced hypothyroidism. None of the models was rejected according to the evaluation of the goodness of fit. The mean dose model was ranked as the best model on the basis of its Akaike's information criterion value. The D{sub 50} estimated from the models was approximately 44 Gy. Conclusions: The implemented

Prediction of normalized biodiesel properties by simulation of multiple feedstock blends.

Science.gov (United States)

García, Manuel; Gonzalo, Alberto; Sánchez, José Luis; Arauzo, Jesús; Peña, José Angel

2010-06-01

A continuous process for biodiesel production has been simulated using Aspen HYSYS V7.0 software. As fresh feed, feedstocks with a mild acid content have been used. The process flowsheet follows a traditional alkaline transesterification scheme constituted by esterification, transesterification and purification stages. Kinetic models taking into account the concentration of the different species have been employed in order to simulate the behavior of the CSTR reactors and the product distribution within the process. The comparison between experimental data found in literature and the predicted normalized properties, has been discussed. Additionally, a comparison between different thermodynamic packages has been performed. NRTL activity model has been selected as the most reliable of them. The combination of these models allows the prediction of 13 out of 25 parameters included in standard EN-14214:2003, and confers simulators a great value as predictive as well as optimization tool. (c) 2010 Elsevier Ltd. All rights reserved.

Metrics for Business Process Models

Science.gov (United States)

Mendling, Jan

Up until now, there has been little research on why people introduce errors in real-world business process models. In a more general context, Simon [404] points to the limitations of cognitive capabilities and concludes that humans act rationally only to a certain extent. Concerning modeling errors, this argument would imply that human modelers lose track of the interrelations of large and complex models due to their limited cognitive capabilities and introduce errors that they would not insert in a small model. A recent study by Mendling et al. [275] explores in how far certain complexity metrics of business process models have the potential to serve as error determinants. The authors conclude that complexity indeed appears to have an impact on error probability. Before we can test such a hypothesis in a more general setting, we have to establish an understanding of how we can define determinants that drive error probability and how we can measure them.

Impact of statistical learning methods on the predictive power of multivariate normal tissue complication probability models

NARCIS (Netherlands)

Xu, Cheng-Jian; van der Schaaf, Arjen; Schilstra, Cornelis; Langendijk, Johannes A.; van t Veld, Aart A.

2012-01-01

PURPOSE: To study the impact of different statistical learning methods on the prediction performance of multivariate normal tissue complication probability (NTCP) models. METHODS AND MATERIALS: In this study, three learning methods, stepwise selection, least absolute shrinkage and selection operator

Revising process models through inductive learning

NARCIS (Netherlands)

Maggi, F.M.; Corapi, D.; Russo, A.; Lupu, E.; Visaggio, G.; Muehlen, zur M.; Su, J.

2011-01-01

Discovering the Business Process (BP) model underpinning existing practices through analysis of event logs, allows users to understand, analyse and modify the process. But, to be useful, the BP model must be kept in line with practice throughout its lifetime, as changes occur to the business

Diagnosing differences between business process models

NARCIS (Netherlands)

Dijkman, R.M.; Dumas, M.; Reichert, M.; Shan, M.-C.

2008-01-01

This paper presents a technique to diagnose differences between business process models in the EPC notation. The diagnosis returns the exact position of a difference in the business process models and diagnoses the type of a difference, using a typology of differences developed in previous work.

Group normalization for genomic data.

Science.gov (United States)

Ghandi, Mahmoud; Beer, Michael A

2012-01-01

Data normalization is a crucial preliminary step in analyzing genomic datasets. The goal of normalization is to remove global variation to make readings across different experiments comparable. In addition, most genomic loci have non-uniform sensitivity to any given assay because of variation in local sequence properties. In microarray experiments, this non-uniform sensitivity is due to different DNA hybridization and cross-hybridization efficiencies, known as the probe effect. In this paper we introduce a new scheme, called Group Normalization (GN), to remove both global and local biases in one integrated step, whereby we determine the normalized probe signal by finding a set of reference probes with similar responses. Compared to conventional normalization methods such as Quantile normalization and physically motivated probe effect models, our proposed method is general in the sense that it does not require the assumption that the underlying signal distribution be identical for the treatment and control, and is flexible enough to correct for nonlinear and higher order probe effects. The Group Normalization algorithm is computationally efficient and easy to implement. We also describe a variant of the Group Normalization algorithm, called Cross Normalization, which efficiently amplifies biologically relevant differences between any two genomic datasets.

AMFIBIA: A Meta-Model for the Integration of Business Process Modelling Aspects

DEFF Research Database (Denmark)

Axenath, Björn; Kindler, Ekkart; Rubin, Vladimir

2007-01-01

AMFIBIA is a meta-model that formalises the essential aspects and concepts of business processes. Though AMFIBIA is not the first approach to formalising the aspects and concepts of business processes, it is more ambitious in the following respects: Firstly, it is independent from particular...... modelling formalisms of business processes and it is designed in such a way that any formalism for modelling some aspect of a business process can be plugged into AMFIBIA. Therefore, AMFIBIA is formalism-independent. Secondly, it is not biased toward any aspect of business processes; the different aspects...... can be considered and modelled independently of each other. Moreover, AMFIBIA is not restricted to a fixed set of aspects; new aspects of business processes can be easily integrated. Thirdly, AMFIBIA does not only name and relate the concepts of business process modelling, as it is typically done...

Spin-filtering effect and proximity effect in normal metal/ferromagnetic insulator/normal metal/superconductor junctions

International Nuclear Information System (INIS)

Li Hong; Yang Wei; Yang Xinjian; Qin Minghui; Xu Yihong

2007-01-01

Taking into account the thickness of the ferromagnetic insulator (FI), the spin-filtering effect and proximity effect in normal metal/ferromagnetic insulator/normal metal/superconductor (NM/FI/NM/SC) junctions are studied based on an extended Blonder-Tinkham-Klapwijk (BTK) theory. It is shown that a spin-dependent energy shift during the tunneling process induces splitting of the sub-energy gap conductance peaks and the spin polarization in the ferromagnetic insulator causes an imbalance of the peak heights. Different from the ferromagnet the spin-filtering effect of the FI cannot cause the reversion of the normalized conductance in NM/FI/NM/SC junctions

Model based process-product design and analysis

DEFF Research Database (Denmark)

Gani, Rafiqul

This paper gives a perspective on modelling and the important role it has within product-process design and analysis. Different modelling issues related to development and application of systematic model-based solution approaches for product-process design is discussed and the need for a hybrid...... model-based framework is highlighted. This framework should be able to manage knowledge-data, models, and associated methods and tools integrated with design work-flows and data-flows for specific product-process design problems. In particular, the framework needs to manage models of different types......, forms and complexity, together with their associated parameters. An example of a model-based system for design of chemicals based formulated products is also given....

Understanding Quality in Process Modelling: Towards a Holistic Perspective

Directory of Open Access Journals (Sweden)

Jan Recker

2007-09-01

Full Text Available Quality is one of the main topics in current conceptual modelling research, as is the field of business process modelling. Yet, widely acknowledged academic contributions towards an understanding or measurement of business process model quality are limited at best. In this paper I argue that the development of methodical theories concerning the measurement or establishment of process model quality must be preceded by methodological elaborations on business process modelling. I further argue that existing epistemological foundations of process modelling are insufficient for describing all extrinsic and intrinsic traits of model quality. This in turn has led to a lack of holistic understanding of process modelling. Taking into account the inherent social and purpose-oriented character of process modelling in contemporary organizations I present a socio-pragmatic constructionist methodology of business process modelling and sketch out implications of this perspective towards an understanding of process model quality. I anticipate that, based on this research, theories can be developed that facilitate the evaluation of the ’goodness’ of a business process model.

Animated-simulation modeling facilitates clinical-process costing.

Science.gov (United States)

Zelman, W N; Glick, N D; Blackmore, C C

2001-09-01

Traditionally, the finance department has assumed responsibility for assessing process costs in healthcare organizations. To enhance process-improvement efforts, however, many healthcare providers need to include clinical staff in process cost analysis. Although clinical staff often use electronic spreadsheets to model the cost of specific processes, PC-based animated-simulation tools offer two major advantages over spreadsheets: they allow clinicians to interact more easily with the costing model so that it more closely represents the process being modeled, and they represent cost output as a cost range rather than as a single cost estimate, thereby providing more useful information for decision making.

Normal Inverse Gaussian Model-Based Image Denoising in the NSCT Domain

Directory of Open Access Journals (Sweden)

Jian Jia

2015-01-01

Full Text Available The objective of image denoising is to retain useful details while removing as much noise as possible to recover an original image from its noisy version. This paper proposes a novel normal inverse Gaussian (NIG model-based method that uses a Bayesian estimator to carry out image denoising in the nonsubsampled contourlet transform (NSCT domain. In the proposed method, the NIG model is first used to describe the distributions of the image transform coefficients of each subband in the NSCT domain. Then, the corresponding threshold function is derived from the model using Bayesian maximum a posteriori probability estimation theory. Finally, optimal linear interpolation thresholding algorithm (OLI-Shrink is employed to guarantee a gentler thresholding effect. The results of comparative experiments conducted indicate that the denoising performance of our proposed method in terms of peak signal-to-noise ratio is superior to that of several state-of-the-art methods, including BLS-GSM, K-SVD, BivShrink, and BM3D. Further, the proposed method achieves structural similarity (SSIM index values that are comparable to those of the block-matching 3D transformation (BM3D method.

How visual cognition influences process model comprehension

NARCIS (Netherlands)

Petrusel, Razvan; Mendling, Jan; Reijers, Hajo A.

2017-01-01

Process analysts and other professionals extensively use process models to analyze business processes and identify performance improvement opportunities. Therefore, it is important that such models can be easily and properly understood. Previous research has mainly focused on two types of factors

A general model for membrane-based separation processes

DEFF Research Database (Denmark)

Soni, Vipasha; Abildskov, Jens; Jonsson, Gunnar Eigil

2009-01-01

behaviour will play an important role. In this paper, modelling of membrane-based processes for separation of gas and liquid mixtures are considered. Two general models, one for membrane-based liquid separation processes (with phase change) and another for membrane-based gas separation are presented....... The separation processes covered are: membrane-based gas separation processes, pervaporation and various types of membrane distillation processes. The specific model for each type of membrane-based process is generated from the two general models by applying the specific system descriptions and the corresponding...

Modelling binaural processes involved in simultaneous reflection masking: limitations of current models

DEFF Research Database (Denmark)

Buchholz, Jörg

2007-01-01

Masked thresholds were measured for a single test reflection, masked by the direct sound, as a function of the reflection delay. This was done for diotic as well as for dichotic stimulus presentations and all stimuli were presented via headphones. The input signal was a 200-ms long broadband noise......, such as normalized cross-correlation models (e.g., Bernstein et al., 1999, JASA, pp. 870-876), the power-addition model (Zurek, 1979, JASA, pp. 1750-1757), or Equalization-Cancellation-based models (e.g., Breebaart et al., 2001, JASA, pp. 1074-1088), cannot account for the psychoacoustical data. The present talk...

Elastoplastical Analysis of the Interface between Clay and Concrete Incorporating the Effect of the Normal Stress History

Directory of Open Access Journals (Sweden)

Zhao Cheng

2013-01-01

Full Text Available The behaviour of the soil-structure interface is crucial to the design of a pile foundation. Radial unloading occurs during the process of hole boring and concrete curing, which will affect the load transfer rule of the pile-soil interface. Through large shear tests on the interface between clay and concrete, it can be concluded that the normal stress history significantly influences the shear behaviour of the interface. The numerical simulation of the bored shaft-soil interaction problem requires proper modelling of the interface. By taking the energy accumulated on the interface as a hardening parameter and viewing the shearing process of the interface as the process of the energy dissipated to do work, considering the influence of the normal stress history on the shearing rigidity, a mechanical model of the interface between clay and concrete is proposed. The methods to define the model parameters are also introduced. The model is based on a legible mathematical theory, and all its parameters have definite physical meaning. The model was validated using data from a direct shear test; the validation results indicated that the model can reproduce and predict the mechanical behaviour of the interface between clay and concrete under an arbitrary stress history.

APROMORE : an advanced process model repository

NARCIS (Netherlands)

La Rosa, M.; Reijers, H.A.; Aalst, van der W.M.P.; Dijkman, R.M.; Mendling, J.; Dumas, M.; García-Bañuelos, L.

2011-01-01

Business process models are becoming available in large numbers due to their widespread use in many industrial applications such as enterprise and quality engineering projects. On the one hand, this raises a challenge as to their proper management: how can it be ensured that the proper process model

Making nuclear 'normal'

International Nuclear Information System (INIS)

Haehlen, Peter; Elmiger, Bruno

2000-01-01

The mechanics of the Swiss NPPs' 'come and see' programme 1995-1999 were illustrated in our contributions to all PIME workshops since 1996. Now, after four annual 'waves', all the country has been covered by the NPPs' invitation to dialogue. This makes PIME 2000 the right time to shed some light on one particular objective of this initiative: making nuclear 'normal'. The principal aim of the 'come and see' programme, namely to give the Swiss NPPs 'a voice of their own' by the end of the nuclear moratorium 1990-2000, has clearly been attained and was commented on during earlier PIMEs. It is, however, equally important that Swiss nuclear energy not only made progress in terms of public 'presence', but also in terms of being perceived as a normal part of industry, as a normal branch of the economy. The message that Swiss nuclear energy is nothing but a normal business involving normal people, was stressed by several components of the multi-prong campaign: - The speakers in the TV ads were real - 'normal' - visitors' guides and not actors; - The testimonials in the print ads were all real NPP visitors - 'normal' people - and not models; - The mailings inviting a very large number of associations to 'come and see' activated a typical channel of 'normal' Swiss social life; - Spending money on ads (a new activity for Swiss NPPs) appears to have resulted in being perceived by the media as a normal branch of the economy. Today we feel that the 'normality' message has well been received by the media. In the controversy dealing with antinuclear arguments brought forward by environmental organisations journalists nowadays as a rule give nuclear energy a voice - a normal right to be heard. As in a 'normal' controversy, the media again actively ask themselves questions about specific antinuclear claims, much more than before 1990 when the moratorium started. The result is that in many cases such arguments are discarded by journalists, because they are, e.g., found to be

Improving normal tissue complication probability models: the need to adopt a "data-pooling" culture.

Science.gov (United States)

Deasy, Joseph O; Bentzen, Søren M; Jackson, Andrew; Ten Haken, Randall K; Yorke, Ellen D; Constine, Louis S; Sharma, Ashish; Marks, Lawrence B

2010-03-01

Clinical studies of the dependence of normal tissue response on dose-volume factors are often confusingly inconsistent, as the QUANTEC reviews demonstrate. A key opportunity to accelerate progress is to begin storing high-quality datasets in repositories. Using available technology, multiple repositories could be conveniently queried, without divulging protected health information, to identify relevant sources of data for further analysis. After obtaining institutional approvals, data could then be pooled, greatly enhancing the capability to construct predictive models that are more widely applicable and better powered to accurately identify key predictive factors (whether dosimetric, image-based, clinical, socioeconomic, or biological). Data pooling has already been carried out effectively in a few normal tissue complication probability studies and should become a common strategy. Copyright 2010 Elsevier Inc. All rights reserved.

A model evaluation checklist for process-based environmental models

Science.gov (United States)

Jackson-Blake, Leah

2015-04-01

Mechanistic catchment-scale phosphorus models appear to perform poorly where diffuse sources dominate. The reasons for this were investigated for one commonly-applied model, the INtegrated model of CAtchment Phosphorus (INCA-P). Model output was compared to 18 months of daily water quality monitoring data in a small agricultural catchment in Scotland, and model structure, key model processes and internal model responses were examined. Although the model broadly reproduced dissolved phosphorus dynamics, it struggled with particulates. The reasons for poor performance were explored, together with ways in which improvements could be made. The process of critiquing and assessing model performance was then generalised to provide a broadly-applicable model evaluation checklist, incorporating: (1) Calibration challenges, relating to difficulties in thoroughly searching a high-dimensional parameter space and in selecting appropriate means of evaluating model performance. In this study, for example, model simplification was identified as a necessary improvement to reduce the number of parameters requiring calibration, whilst the traditionally-used Nash Sutcliffe model performance statistic was not able to discriminate between realistic and unrealistic model simulations, and alternative statistics were needed. (2) Data limitations, relating to a lack of (or uncertainty in) input data, data to constrain model parameters, data for model calibration and testing, and data to test internal model processes. In this study, model reliability could be improved by addressing all four kinds of data limitation. For example, there was insufficient surface water monitoring data for model testing against an independent dataset to that used in calibration, whilst additional monitoring of groundwater and effluent phosphorus inputs would help distinguish between alternative plausible model parameterisations. (3) Model structural inadequacies, whereby model structure may inadequately represent

The evolution of process-based hydrologic models

NARCIS (Netherlands)

Clark, Martyn P.; Bierkens, Marc F.P.; Samaniego, Luis; Woods, Ross A.; Uijlenhoet, Remko; Bennett, Katrina E.; Pauwels, Valentijn R.N.; Cai, Xitian; Wood, Andrew W.; Peters-Lidard, Christa D.

2017-01-01

The diversity in hydrologic models has historically led to great controversy on the "correct" approach to process-based hydrologic modeling, with debates centered on the adequacy of process parameterizations, data limitations and uncertainty, and computational constraints on model analysis. In this

Food addiction spectrum: a theoretical model from normality to eating and overeating disorders.

Science.gov (United States)

Piccinni, Armando; Marazziti, Donatella; Vanelli, Federica; Franceschini, Caterina; Baroni, Stefano; Costanzo, Davide; Cremone, Ivan Mirko; Veltri, Antonello; Dell'Osso, Liliana

2015-01-01

The authors comment on the recently proposed food addiction spectrum that represents a theoretical model to understand the continuum between several conditions ranging from normality to pathological states, including eating disorders and obesity, as well as why some individuals show a peculiar attachment to food that can become an addiction. Further, they review the possible neurobiological underpinnings of these conditions that include dopaminergic neurotransmission and circuits that have long been implicated in drug addiction. The aim of this article is also that at stimulating a debate regarding the possible model of a food (or eating) addiction spectrum that may be helpful towards the search of novel therapeutic approaches to different pathological states related to disturbed feeding or overeating.

Software Process Validation: Quantitatively Measuring the Correspondence of a Process to a Model

National Research Council Canada - National Science Library

Cook, Jonathan E; Wolf, Alexander L

1997-01-01

.... When process models and process executions diverge, something significant is happening. The authors have developed techniques for uncovering and measuring the discrepancies between models and executions, which they call process validation...

Distillation modeling for a uranium refining process

Energy Technology Data Exchange (ETDEWEB)

Westphal, B.R.