WorldWideScience

Sample records for point process modeling

  1. Self-exciting point process in modeling earthquake occurrences

    International Nuclear Information System (INIS)

    Pratiwi, H.; Slamet, I.; Respatiwulan; Saputro, D. R. S.

    2017-01-01

    In this paper, we present a procedure for modeling earthquake based on spatial-temporal point process. The magnitude distribution is expressed as truncated exponential and the event frequency is modeled with a spatial-temporal point process that is characterized uniquely by its associated conditional intensity process. The earthquakes can be regarded as point patterns that have a temporal clustering feature so we use self-exciting point process for modeling the conditional intensity function. The choice of main shocks is conducted via window algorithm by Gardner and Knopoff and the model can be fitted by maximum likelihood method for three random variables. (paper)

  2. Determinantal point process models on the sphere

    DEFF Research Database (Denmark)

    Møller, Jesper; Nielsen, Morten; Porcu, Emilio

    defined on Sd × Sd . We review the appealing properties of such processes, including their specific moment properties, density expressions and simulation procedures. Particularly, we characterize and construct isotropic DPPs models on Sd , where it becomes essential to specify the eigenvalues......We consider determinantal point processes on the d-dimensional unit sphere Sd . These are finite point processes exhibiting repulsiveness and with moment properties determined by a certain determinant whose entries are specified by a so-called kernel which we assume is a complex covariance function...... and eigenfunctions in a spectral representation for the kernel, and we figure out how repulsive isotropic DPPs can be. Moreover, we discuss the shortcomings of adapting existing models for isotropic covariance functions and consider strategies for developing new models, including a useful spectral approach....

  3. Development and evaluation of spatial point process models for epidermal nerve fibers.

    Science.gov (United States)

    Olsbo, Viktor; Myllymäki, Mari; Waller, Lance A; Särkkä, Aila

    2013-06-01

    We propose two spatial point process models for the spatial structure of epidermal nerve fibers (ENFs) across human skin. The models derive from two point processes, Φb and Φe, describing the locations of the base and end points of the fibers. Each point of Φe (the end point process) is connected to a unique point in Φb (the base point process). In the first model, both Φe and Φb are Poisson processes, yielding a null model of uniform coverage of the skin by end points and general baseline results and reference values for moments of key physiologic indicators. The second model provides a mechanistic model to generate end points for each base, and we model the branching structure more directly by defining Φe as a cluster process conditioned on the realization of Φb as its parent points. In both cases, we derive distributional properties for observable quantities of direct interest to neurologists such as the number of fibers per base, and the direction and range of fibers on the skin. We contrast both models by fitting them to data from skin blister biopsy images of ENFs and provide inference regarding physiological properties of ENFs. Copyright © 2013 Elsevier Inc. All rights reserved.

  4. Mechanistic spatio-temporal point process models for marked point processes, with a view to forest stand data

    DEFF Research Database (Denmark)

    Møller, Jesper; Ghorbani, Mohammad; Rubak, Ege Holger

    We show how a spatial point process, where to each point there is associated a random quantitative mark, can be identified with a spatio-temporal point process specified by a conditional intensity function. For instance, the points can be tree locations, the marks can express the size of trees......, and the conditional intensity function can describe the distribution of a tree (i.e., its location and size) conditionally on the larger trees. This enable us to construct parametric statistical models which are easily interpretable and where likelihood-based inference is tractable. In particular, we consider maximum...

  5. Multivariate Product-Shot-noise Cox Point Process Models

    DEFF Research Database (Denmark)

    Jalilian, Abdollah; Guan, Yongtao; Mateu, Jorge

    We introduce a new multivariate product-shot-noise Cox process which is useful for model- ing multi-species spatial point patterns with clustering intra-specific interactions and neutral, negative or positive inter-specific interactions. The auto and cross pair correlation functions of the process...... can be obtained in closed analytical forms and approximate simulation of the process is straightforward. We use the proposed process to model interactions within and among five tree species in the Barro Colorado Island plot....

  6. A Bayesian MCMC method for point process models with intractable normalising constants

    DEFF Research Database (Denmark)

    Berthelsen, Kasper Klitgaard; Møller, Jesper

    2004-01-01

    to simulate from the "unknown distribution", perfect simulation algorithms become useful. We illustrate the method in cases whre the likelihood is given by a Markov point process model. Particularly, we consider semi-parametric Bayesian inference in connection to both inhomogeneous Markov point process models...... and pairwise interaction point processes....

  7. Statistical properties of several models of fractional random point processes

    Science.gov (United States)

    Bendjaballah, C.

    2011-08-01

    Statistical properties of several models of fractional random point processes have been analyzed from the counting and time interval statistics points of view. Based on the criterion of the reduced variance, it is seen that such processes exhibit nonclassical properties. The conditions for these processes to be treated as conditional Poisson processes are examined. Numerical simulations illustrate part of the theoretical calculations.

  8. Spatial Mixture Modelling for Unobserved Point Processes: Examples in Immunofluorescence Histology.

    Science.gov (United States)

    Ji, Chunlin; Merl, Daniel; Kepler, Thomas B; West, Mike

    2009-12-04

    We discuss Bayesian modelling and computational methods in analysis of indirectly observed spatial point processes. The context involves noisy measurements on an underlying point process that provide indirect and noisy data on locations of point outcomes. We are interested in problems in which the spatial intensity function may be highly heterogenous, and so is modelled via flexible nonparametric Bayesian mixture models. Analysis aims to estimate the underlying intensity function and the abundance of realized but unobserved points. Our motivating applications involve immunological studies of multiple fluorescent intensity images in sections of lymphatic tissue where the point processes represent geographical configurations of cells. We are interested in estimating intensity functions and cell abundance for each of a series of such data sets to facilitate comparisons of outcomes at different times and with respect to differing experimental conditions. The analysis is heavily computational, utilizing recently introduced MCMC approaches for spatial point process mixtures and extending them to the broader new context here of unobserved outcomes. Further, our example applications are problems in which the individual objects of interest are not simply points, but rather small groups of pixels; this implies a need to work at an aggregate pixel region level and we develop the resulting novel methodology for this. Two examples with with immunofluorescence histology data demonstrate the models and computational methodology.

  9. Marked point process for modelling seismic activity (case study in Sumatra and Java)

    Science.gov (United States)

    Pratiwi, Hasih; Sulistya Rini, Lia; Wayan Mangku, I.

    2018-05-01

    Earthquake is a natural phenomenon that is random, irregular in space and time. Until now the forecast of earthquake occurrence at a location is still difficult to be estimated so that the development of earthquake forecast methodology is still carried out both from seismology aspect and stochastic aspect. To explain the random nature phenomena, both in space and time, a point process approach can be used. There are two types of point processes: temporal point process and spatial point process. The temporal point process relates to events observed over time as a sequence of time, whereas the spatial point process describes the location of objects in two or three dimensional spaces. The points on the point process can be labelled with additional information called marks. A marked point process can be considered as a pair (x, m) where x is the point of location and m is the mark attached to the point of that location. This study aims to model marked point process indexed by time on earthquake data in Sumatra Island and Java Island. This model can be used to analyse seismic activity through its intensity function by considering the history process up to time before t. Based on data obtained from U.S. Geological Survey from 1973 to 2017 with magnitude threshold 5, we obtained maximum likelihood estimate for parameters of the intensity function. The estimation of model parameters shows that the seismic activity in Sumatra Island is greater than Java Island.

  10. Structured spatio-temporal shot-noise Cox point process models, with a view to modelling forest fires

    DEFF Research Database (Denmark)

    Møller, Jesper; Diaz-Avalos, Carlos

    Spatio-temporal Cox point process models with a multiplicative structure for the driving random intensity, incorporating covariate information into temporal and spatial components, and with a residual term modelled by a shot-noise process, are considered. Such models are flexible and tractable fo...... dataset consisting of 2796 days and 5834 spatial locations of fires. The model is compared with a spatio-temporal log-Gaussian Cox point process model, and likelihood-based methods are discussed to some extent....

  11. Structured Spatio-temporal shot-noise Cox point process models, with a view to modelling forest fires

    DEFF Research Database (Denmark)

    Møller, Jesper; Diaz-Avalos, Carlos

    2010-01-01

    Spatio-temporal Cox point process models with a multiplicative structure for the driving random intensity, incorporating covariate information into temporal and spatial components, and with a residual term modelled by a shot-noise process, are considered. Such models are flexible and tractable fo...... data set consisting of 2796 days and 5834 spatial locations of fires. The model is compared with a spatio-temporal log-Gaussian Cox point process model, and likelihood-based methods are discussed to some extent....

  12. Modeling fixation locations using spatial point processes.

    Science.gov (United States)

    Barthelmé, Simon; Trukenbrod, Hans; Engbert, Ralf; Wichmann, Felix

    2013-10-01

    Whenever eye movements are measured, a central part of the analysis has to do with where subjects fixate and why they fixated where they fixated. To a first approximation, a set of fixations can be viewed as a set of points in space; this implies that fixations are spatial data and that the analysis of fixation locations can be beneficially thought of as a spatial statistics problem. We argue that thinking of fixation locations as arising from point processes is a very fruitful framework for eye-movement data, helping turn qualitative questions into quantitative ones. We provide a tutorial introduction to some of the main ideas of the field of spatial statistics, focusing especially on spatial Poisson processes. We show how point processes help relate image properties to fixation locations. In particular we show how point processes naturally express the idea that image features' predictability for fixations may vary from one image to another. We review other methods of analysis used in the literature, show how they relate to point process theory, and argue that thinking in terms of point processes substantially extends the range of analyses that can be performed and clarify their interpretation.

  13. The importance of topographically corrected null models for analyzing ecological point processes.

    Science.gov (United States)

    McDowall, Philip; Lynch, Heather J

    2017-07-01

    Analyses of point process patterns and related techniques (e.g., MaxEnt) make use of the expected number of occurrences per unit area and second-order statistics based on the distance between occurrences. Ecologists working with point process data often assume that points exist on a two-dimensional x-y plane or within a three-dimensional volume, when in fact many observed point patterns are generated on a two-dimensional surface existing within three-dimensional space. For many surfaces, however, such as the topography of landscapes, the projection from the surface to the x-y plane preserves neither area nor distance. As such, when these point patterns are implicitly projected to and analyzed in the x-y plane, our expectations of the point pattern's statistical properties may not be met. When used in hypothesis testing, we find that the failure to account for the topography of the generating surface may bias statistical tests that incorrectly identify clustering and, furthermore, may bias coefficients in inhomogeneous point process models that incorporate slope as a covariate. We demonstrate the circumstances under which this bias is significant, and present simple methods that allow point processes to be simulated with corrections for topography. These point patterns can then be used to generate "topographically corrected" null models against which observed point processes can be compared. © 2017 by the Ecological Society of America.

  14. A MARKED POINT PROCESS MODEL FOR VEHICLE DETECTION IN AERIAL LIDAR POINT CLOUDS

    Directory of Open Access Journals (Sweden)

    A. Börcs

    2012-07-01

    Full Text Available In this paper we present an automated method for vehicle detection in LiDAR point clouds of crowded urban areas collected from an aerial platform. We assume that the input cloud is unordered, but it contains additional intensity and return number information which are jointly exploited by the proposed solution. Firstly, the 3-D point set is segmented into ground, vehicle, building roof, vegetation and clutter classes. Then the points with the corresponding class labels and intensity values are projected to the ground plane, where the optimal vehicle configuration is described by a Marked Point Process (MPP model of 2-D rectangles. Finally, the Multiple Birth and Death algorithm is utilized to find the configuration with the highest confidence.

  15. Thinning spatial point processes into Poisson processes

    DEFF Research Database (Denmark)

    Møller, Jesper; Schoenberg, Frederic Paik

    , and where one simulates backwards and forwards in order to obtain the thinned process. In the case of a Cox process, a simple independent thinning technique is proposed. In both cases, the thinning results in a Poisson process if and only if the true Papangelou conditional intensity is used, and thus can......This paper describes methods for randomly thinning certain classes of spatial point processes. In the case of a Markov point process, the proposed method involves a dependent thinning of a spatial birth-and-death process, where clans of ancestors associated with the original points are identified...... be used as a diagnostic for assessing the goodness-of-fit of a spatial point process model. Several examples, including clustered and inhibitive point processes, are considered....

  16. Inhomogeneous Markov point processes by transformation

    DEFF Research Database (Denmark)

    Jensen, Eva B. Vedel; Nielsen, Linda Stougaard

    2000-01-01

    We construct parametrized models for point processes, allowing for both inhomogeneity and interaction. The inhomogeneity is obtained by applying parametrized transformations to homogeneous Markov point processes. An interesting model class, which can be constructed by this transformation approach......, is that of exponential inhomogeneous Markov point processes. Statistical inference For such processes is discussed in some detail....

  17. Thinning spatial point processes into Poisson processes

    DEFF Research Database (Denmark)

    Møller, Jesper; Schoenberg, Frederic Paik

    2010-01-01

    are identified, and where we simulate backwards and forwards in order to obtain the thinned process. In the case of a Cox process, a simple independent thinning technique is proposed. In both cases, the thinning results in a Poisson process if and only if the true Papangelou conditional intensity is used, and......In this paper we describe methods for randomly thinning certain classes of spatial point processes. In the case of a Markov point process, the proposed method involves a dependent thinning of a spatial birth-and-death process, where clans of ancestors associated with the original points......, thus, can be used as a graphical exploratory tool for inspecting the goodness-of-fit of a spatial point process model. Several examples, including clustered and inhibitive point processes, are considered....

  18. MODELLING AND SIMULATION OF A NEUROPHYSIOLOGICAL EXPERIMENT BY SPATIO-TEMPORAL POINT PROCESSES

    Directory of Open Access Journals (Sweden)

    Viktor Beneš

    2011-05-01

    Full Text Available We present a stochastic model of an experimentmonitoring the spiking activity of a place cell of hippocampus of an experimental animal moving in an arena. Doubly stochastic spatio-temporal point process is used to model and quantify overdispersion. Stochastic intensity is modelled by a Lévy based random field while the animal path is simplified to a discrete random walk. In a simulation study first a method suggested previously is used. Then it is shown that a solution of the filtering problem yields the desired inference to the random intensity. Two approaches are suggested and the new one based on finite point process density is applied. Using Markov chain Monte Carlo we obtain numerical results from the simulated model. The methodology is discussed.

  19. A case study on point process modelling in disease mapping

    DEFF Research Database (Denmark)

    Møller, Jesper; Waagepetersen, Rasmus Plenge; Benes, Viktor

    2005-01-01

    of the risk on the covariates. Instead of using the common areal level approaches we base the analysis on a Bayesian approach for a log Gaussian Cox point process with covariates. Posterior characteristics for a discretized version of the log Gaussian Cox process are computed using Markov chain Monte Carlo...... methods. A particular problem which is thoroughly discussed is to determine a model for the background population density. The risk map shows a clear dependency with the population intensity models and the basic model which is adopted for the population intensity determines what covariates influence...... the risk of TBE. Model validation is based on the posterior predictive distribution of various summary statistics....

  20. Residual analysis for spatial point processes

    DEFF Research Database (Denmark)

    Baddeley, A.; Turner, R.; Møller, Jesper

    We define residuals for point process models fitted to spatial point pattern data, and propose diagnostic plots based on these residuals. The techniques apply to any Gibbs point process model, which may exhibit spatial heterogeneity, interpoint interaction and dependence on spatial covariates. Ou...... or covariate effects. Q-Q plots of the residuals are effective in diagnosing interpoint interaction. Some existing ad hoc statistics of point patterns (quadrat counts, scan statistic, kernel smoothed intensity, Berman's diagnostic) are recovered as special cases....

  1. Detecting determinism from point processes.

    Science.gov (United States)

    Andrzejak, Ralph G; Mormann, Florian; Kreuz, Thomas

    2014-12-01

    The detection of a nonrandom structure from experimental data can be crucial for the classification, understanding, and interpretation of the generating process. We here introduce a rank-based nonlinear predictability score to detect determinism from point process data. Thanks to its modular nature, this approach can be adapted to whatever signature in the data one considers indicative of deterministic structure. After validating our approach using point process signals from deterministic and stochastic model dynamics, we show an application to neuronal spike trains recorded in the brain of an epilepsy patient. While we illustrate our approach in the context of temporal point processes, it can be readily applied to spatial point processes as well.

  2. Self-Exciting Point Process Modeling of Conversation Event Sequences

    Science.gov (United States)

    Masuda, Naoki; Takaguchi, Taro; Sato, Nobuo; Yano, Kazuo

    Self-exciting processes of Hawkes type have been used to model various phenomena including earthquakes, neural activities, and views of online videos. Studies of temporal networks have revealed that sequences of social interevent times for individuals are highly bursty. We examine some basic properties of event sequences generated by the Hawkes self-exciting process to show that it generates bursty interevent times for a wide parameter range. Then, we fit the model to the data of conversation sequences recorded in company offices in Japan. In this way, we can estimate relative magnitudes of the self excitement, its temporal decay, and the base event rate independent of the self excitation. These variables highly depend on individuals. We also point out that the Hawkes model has an important limitation that the correlation in the interevent times and the burstiness cannot be independently modulated.

  3. State estimation for temporal point processes

    NARCIS (Netherlands)

    van Lieshout, Maria Nicolette Margaretha

    2015-01-01

    This paper is concerned with combined inference for point processes on the real line observed in a broken interval. For such processes, the classic history-based approach cannot be used. Instead, we adapt tools from sequential spatial point processes. For a range of models, the marginal and

  4. A random point process model for the score in sport matches

    Czech Academy of Sciences Publication Activity Database

    Volf, Petr

    2009-01-01

    Roč. 20, č. 2 (2009), s. 121-131 ISSN 1471-678X R&D Projects: GA AV ČR(CZ) IAA101120604 Institutional research plan: CEZ:AV0Z10750506 Keywords : sport statistics * scoring intensity * Cox’s regression model Subject RIV: BB - Applied Statistics, Operational Research http://library.utia.cas.cz/separaty/2009/SI/volf-a random point process model for the score in sport matches.pdf

  5. A CASE STUDY ON POINT PROCESS MODELLING IN DISEASE MAPPING

    Directory of Open Access Journals (Sweden)

    Viktor Beneš

    2011-05-01

    Full Text Available We consider a data set of locations where people in Central Bohemia have been infected by tick-borne encephalitis (TBE, and where population census data and covariates concerning vegetation and altitude are available. The aims are to estimate the risk map of the disease and to study the dependence of the risk on the covariates. Instead of using the common area level approaches we base the analysis on a Bayesian approach for a log Gaussian Cox point process with covariates. Posterior characteristics for a discretized version of the log Gaussian Cox process are computed using Markov chain Monte Carlo methods. A particular problem which is thoroughly discussed is to determine a model for the background population density. The risk map shows a clear dependency with the population intensity models and the basic model which is adopted for the population intensity determines what covariates influence the risk of TBE. Model validation is based on the posterior predictive distribution of various summary statistics.

  6. Transforming spatial point processes into Poisson processes using random superposition

    DEFF Research Database (Denmark)

    Møller, Jesper; Berthelsen, Kasper Klitgaaard

    with a complementary spatial point process Y  to obtain a Poisson process X∪Y  with intensity function β. Underlying this is a bivariate spatial birth-death process (Xt,Yt) which converges towards the distribution of (X,Y). We study the joint distribution of X and Y, and their marginal and conditional distributions....... In particular, we introduce a fast and easy simulation procedure for Y conditional on X. This may be used for model checking: given a model for the Papangelou intensity of the original spatial point process, this model is used to generate the complementary process, and the resulting superposition is a Poisson...... process with intensity function β if and only if the true Papangelou intensity is used. Whether the superposition is actually such a Poisson process can easily be examined using well known results and fast simulation procedures for Poisson processes. We illustrate this approach to model checking...

  7. Instantaneous nonlinear assessment of complex cardiovascular dynamics by Laguerre-Volterra point process models.

    Science.gov (United States)

    Valenza, Gaetano; Citi, Luca; Barbieri, Riccardo

    2013-01-01

    We report an exemplary study of instantaneous assessment of cardiovascular dynamics performed using point-process nonlinear models based on Laguerre expansion of the linear and nonlinear Wiener-Volterra kernels. As quantifiers, instantaneous measures such as high order spectral features and Lyapunov exponents can be estimated from a quadratic and cubic autoregressive formulation of the model first order moment, respectively. Here, these measures are evaluated on heartbeat series coming from 16 healthy subjects and 14 patients with Congestive Hearth Failure (CHF). Data were gathered from the on-line repository PhysioBank, which has been taken as landmark for testing nonlinear indices. Results show that the proposed nonlinear Laguerre-Volterra point-process methods are able to track the nonlinear and complex cardiovascular dynamics, distinguishing significantly between CHF and healthy heartbeat series.

  8. Estimating Function Approaches for Spatial Point Processes

    Science.gov (United States)

    Deng, Chong

    Spatial point pattern data consist of locations of events that are often of interest in biological and ecological studies. Such data are commonly viewed as a realization from a stochastic process called spatial point process. To fit a parametric spatial point process model to such data, likelihood-based methods have been widely studied. However, while maximum likelihood estimation is often too computationally intensive for Cox and cluster processes, pairwise likelihood methods such as composite likelihood, Palm likelihood usually suffer from the loss of information due to the ignorance of correlation among pairs. For many types of correlated data other than spatial point processes, when likelihood-based approaches are not desirable, estimating functions have been widely used for model fitting. In this dissertation, we explore the estimating function approaches for fitting spatial point process models. These approaches, which are based on the asymptotic optimal estimating function theories, can be used to incorporate the correlation among data and yield more efficient estimators. We conducted a series of studies to demonstrate that these estmating function approaches are good alternatives to balance the trade-off between computation complexity and estimating efficiency. First, we propose a new estimating procedure that improves the efficiency of pairwise composite likelihood method in estimating clustering parameters. Our approach combines estimating functions derived from pairwise composite likeli-hood estimation and estimating functions that account for correlations among the pairwise contributions. Our method can be used to fit a variety of parametric spatial point process models and can yield more efficient estimators for the clustering parameters than pairwise composite likelihood estimation. We demonstrate its efficacy through a simulation study and an application to the longleaf pine data. Second, we further explore the quasi-likelihood approach on fitting

  9. Modelling point patterns with linear structures

    DEFF Research Database (Denmark)

    Møller, Jesper; Rasmussen, Jakob Gulddahl

    2009-01-01

    processes whose realizations contain such linear structures. Such a point process is constructed sequentially by placing one point at a time. The points are placed in such a way that new points are often placed close to previously placed points, and the points form roughly line shaped structures. We...... consider simulations of this model and compare with real data....

  10. Modelling point patterns with linear structures

    DEFF Research Database (Denmark)

    Møller, Jesper; Rasmussen, Jakob Gulddahl

    processes whose realizations contain such linear structures. Such a point process is constructed sequentially by placing one point at a time. The points are placed in such a way that new points are often placed close to previously placed points, and the points form roughly line shaped structures. We...... consider simulations of this model and compare with real data....

  11. Multiplicative point process as a model of trading activity

    Science.gov (United States)

    Gontis, V.; Kaulakys, B.

    2004-11-01

    Signals consisting of a sequence of pulses show that inherent origin of the 1/ f noise is a Brownian fluctuation of the average interevent time between subsequent pulses of the pulse sequence. In this paper, we generalize the model of interevent time to reproduce a variety of self-affine time series exhibiting power spectral density S( f) scaling as a power of the frequency f. Furthermore, we analyze the relation between the power-law correlations and the origin of the power-law probability distribution of the signal intensity. We introduce a stochastic multiplicative model for the time intervals between point events and analyze the statistical properties of the signal analytically and numerically. Such model system exhibits power-law spectral density S( f)∼1/ fβ for various values of β, including β= {1}/{2}, 1 and {3}/{2}. Explicit expressions for the power spectra in the low-frequency limit and for the distribution density of the interevent time are obtained. The counting statistics of the events is analyzed analytically and numerically, as well. The specific interest of our analysis is related with the financial markets, where long-range correlations of price fluctuations largely depend on the number of transactions. We analyze the spectral density and counting statistics of the number of transactions. The model reproduces spectral properties of the real markets and explains the mechanism of power-law distribution of trading activity. The study provides evidence that the statistical properties of the financial markets are enclosed in the statistics of the time interval between trades. A multiplicative point process serves as a consistent model generating this statistics.

  12. SHAPE FROM TEXTURE USING LOCALLY SCALED POINT PROCESSES

    Directory of Open Access Journals (Sweden)

    Eva-Maria Didden

    2015-09-01

    Full Text Available Shape from texture refers to the extraction of 3D information from 2D images with irregular texture. This paper introduces a statistical framework to learn shape from texture where convex texture elements in a 2D image are represented through a point process. In a first step, the 2D image is preprocessed to generate a probability map corresponding to an estimate of the unnormalized intensity of the latent point process underlying the texture elements. The latent point process is subsequently inferred from the probability map in a non-parametric, model free manner. Finally, the 3D information is extracted from the point pattern by applying a locally scaled point process model where the local scaling function represents the deformation caused by the projection of a 3D surface onto a 2D image.

  13. Analysing the distribution of synaptic vesicles using a spatial point process model

    DEFF Research Database (Denmark)

    Khanmohammadi, Mahdieh; Waagepetersen, Rasmus; Nava, Nicoletta

    2014-01-01

    functionality by statistically modelling the distribution of the synaptic vesicles in two groups of rats: a control group subjected to sham stress and a stressed group subjected to a single acute foot-shock (FS)-stress episode. We hypothesize that the synaptic vesicles have different spatial distributions...... in the two groups. The spatial distributions are modelled using spatial point process models with an inhomogeneous conditional intensity and repulsive pairwise interactions. Our results verify the hypothesis that the two groups have different spatial distributions....

  14. Smooth random change point models.

    Science.gov (United States)

    van den Hout, Ardo; Muniz-Terrera, Graciela; Matthews, Fiona E

    2011-03-15

    Change point models are used to describe processes over time that show a change in direction. An example of such a process is cognitive ability, where a decline a few years before death is sometimes observed. A broken-stick model consists of two linear parts and a breakpoint where the two lines intersect. Alternatively, models can be formulated that imply a smooth change between the two linear parts. Change point models can be extended by adding random effects to account for variability between subjects. A new smooth change point model is introduced and examples are presented that show how change point models can be estimated using functions in R for mixed-effects models. The Bayesian inference using WinBUGS is also discussed. The methods are illustrated using data from a population-based longitudinal study of ageing, the Cambridge City over 75 Cohort Study. The aim is to identify how many years before death individuals experience a change in the rate of decline of their cognitive ability. Copyright © 2010 John Wiley & Sons, Ltd.

  15. Scattering analysis of point processes and random measures

    International Nuclear Information System (INIS)

    Hanisch, K.H.

    1984-01-01

    In the present paper scattering analysis of point processes and random measures is studied. Known formulae which connect the scattering intensity with the pair distribution function of the studied structures are proved in a rigorous manner with tools of the theory of point processes and random measures. For some special fibre processes the scattering intensity is computed. For a class of random measures, namely for 'grain-germ-models', a new formula is proved which yields the pair distribution function of the 'grain-germ-model' in terms of the pair distribution function of the underlying point process (the 'germs') and of the mean structure factor and the mean squared structure factor of the particles (the 'grains'). (author)

  16. Poisson branching point processes

    International Nuclear Information System (INIS)

    Matsuo, K.; Teich, M.C.; Saleh, B.E.A.

    1984-01-01

    We investigate the statistical properties of a special branching point process. The initial process is assumed to be a homogeneous Poisson point process (HPP). The initiating events at each branching stage are carried forward to the following stage. In addition, each initiating event independently contributes a nonstationary Poisson point process (whose rate is a specified function) located at that point. The additional contributions from all points of a given stage constitute a doubly stochastic Poisson point process (DSPP) whose rate is a filtered version of the initiating point process at that stage. The process studied is a generalization of a Poisson branching process in which random time delays are permitted in the generation of events. Particular attention is given to the limit in which the number of branching stages is infinite while the average number of added events per event of the previous stage is infinitesimal. In the special case when the branching is instantaneous this limit of continuous branching corresponds to the well-known Yule--Furry process with an initial Poisson population. The Poisson branching point process provides a useful description for many problems in various scientific disciplines, such as the behavior of electron multipliers, neutron chain reactions, and cosmic ray showers

  17. Linear and quadratic models of point process systems: contributions of patterned input to output.

    Science.gov (United States)

    Lindsay, K A; Rosenberg, J R

    2012-08-01

    In the 1880's Volterra characterised a nonlinear system using a functional series connecting continuous input and continuous output. Norbert Wiener, in the 1940's, circumvented problems associated with the application of Volterra series to physical problems by deriving from it a new series of terms that are mutually uncorrelated with respect to Gaussian processes. Subsequently, Brillinger, in the 1970's, introduced a point-process analogue of Volterra's series connecting point-process inputs to the instantaneous rate of point-process output. We derive here a new series from this analogue in which its terms are mutually uncorrelated with respect to Poisson processes. This new series expresses how patterned input in a spike train, represented by third-order cross-cumulants, is converted into the instantaneous rate of an output point-process. Given experimental records of suitable duration, the contribution of arbitrary patterned input to an output process can, in principle, be determined. Solutions for linear and quadratic point-process models with one and two inputs and a single output are investigated. Our theoretical results are applied to isolated muscle spindle data in which the spike trains from the primary and secondary endings from the same muscle spindle are recorded in response to stimulation of one and then two static fusimotor axons in the absence and presence of a random length change imposed on the parent muscle. For a fixed mean rate of input spikes, the analysis of the experimental data makes explicit which patterns of two input spikes contribute to an output spike. Copyright © 2012 Elsevier Ltd. All rights reserved.

  18. Modern Statistics for Spatial Point Processes

    DEFF Research Database (Denmark)

    Møller, Jesper; Waagepetersen, Rasmus

    2007-01-01

    We summarize and discuss the current state of spatial point process theory and directions for future research, making an analogy with generalized linear models and random effect models, and illustrating the theory with various examples of applications. In particular, we consider Poisson, Gibbs...

  19. Modern statistics for spatial point processes

    DEFF Research Database (Denmark)

    Møller, Jesper; Waagepetersen, Rasmus

    We summarize and discuss the current state of spatial point process theory and directions for future research, making an analogy with generalized linear models and random effect models, and illustrating the theory with various examples of applications. In particular, we consider Poisson, Gibbs...

  20. Weak convergence of marked point processes generated by crossings of multivariate jump processes

    DEFF Research Database (Denmark)

    Tamborrino, Massimiliano; Sacerdote, Laura; Jacobsen, Martin

    2014-01-01

    We consider the multivariate point process determined by the crossing times of the components of a multivariate jump process through a multivariate boundary, assuming to reset each component to an initial value after its boundary crossing. We prove that this point process converges weakly...... process converging to a multivariate Ornstein–Uhlenbeck process is discussed as a guideline for applying diffusion limits for jump processes. We apply our theoretical findings to neural network modeling. The proposed model gives a mathematical foundation to the generalization of the class of Leaky...

  1. Bubble point pressures of the selected model system for CatLiq® bio-oil process

    DEFF Research Database (Denmark)

    Toor, Saqib Sohail; Rosendahl, Lasse; Baig, Muhammad Noman

    2010-01-01

    . In this work, the bubble point pressures of a selected model mixture (CO2 + H2O + Ethanol + Acetic acid + Octanoic acid) were measured to investigate the phase boundaries of the CatLiq® process. The bubble points were measured in the JEFRI-DBR high pressure PVT phase behavior system. The experimental results......The CatLiq® process is a second generation catalytic liquefaction process for the production of bio-oil from WDGS (Wet Distillers Grains with Solubles) at subcritical conditions (280-350 oC and 225-250 bar) in the presence of a homogeneous alkaline and a heterogeneous Zirconia catalyst...

  2. A business process model as a starting point for tight cooperation among organizations

    Directory of Open Access Journals (Sweden)

    O. Mysliveček

    2006-01-01

    Full Text Available Outsourcing and other kinds of tight cooperation among organizations are more and more necessary for success on all markets (markets of high technology products are particularly influenced. Thus it is important for companies to be able to effectively set up all kinds of cooperation. A business process model (BPM is a suitable starting point for this future cooperation. In this paper the process of setting up such cooperation is outlined, as well as why it is important for business success. 

  3. Parametric methods for spatial point processes

    DEFF Research Database (Denmark)

    Møller, Jesper

    is studied in Section 4, and Bayesian inference in Section 5. On one hand, as the development in computer technology and computational statistics continues,computationally-intensive simulation-based methods for likelihood inference probably will play a increasing role for statistical analysis of spatial...... inference procedures for parametric spatial point process models. The widespread use of sensible but ad hoc methods based on summary statistics of the kind studied in Chapter 4.3 have through the last two decades been supplied by likelihood based methods for parametric spatial point process models......(This text is submitted for the volume ‘A Handbook of Spatial Statistics' edited by A.E. Gelfand, P. Diggle, M. Fuentes, and P. Guttorp, to be published by Chapmand and Hall/CRC Press, and planned to appear as Chapter 4.4 with the title ‘Parametric methods'.) 1 Introduction This chapter considers...

  4. Statistical aspects of determinantal point processes

    DEFF Research Database (Denmark)

    Lavancier, Frédéric; Møller, Jesper; Rubak, Ege

    The statistical aspects of determinantal point processes (DPPs) seem largely unexplored. We review the appealing properties of DDPs, demonstrate that they are useful models for repulsiveness, detail a simulation procedure, and provide freely available software for simulation and statistical infer...

  5. Post-Processing in the Material-Point Method

    DEFF Research Database (Denmark)

    Andersen, Søren; Andersen, Lars Vabbersgaard

    The material-point method (MPM) is a numerical method for dynamic or static analysis of solids using a discretization in time and space. The method has shown to be successful in modelling physical problems involving large deformations, which are difficult to model with traditional numerical tools...... such as the finite element method. In the material-point method, a set of material points is utilized to track the problem in time and space, while a computational background grid is utilized to obtain spatial derivatives relevant to the physical problem. Currently, the research within the material-point method......-point method. The first idea involves associating a volume with each material point and displaying the deformation of this volume. In the discretization process, the physical domain is divided into a number of smaller volumes each represented by a simple shape; here quadrilaterals are chosen for the presented...

  6. Fingerprint Analysis with Marked Point Processes

    DEFF Research Database (Denmark)

    Forbes, Peter G. M.; Lauritzen, Steffen; Møller, Jesper

    We present a framework for fingerprint matching based on marked point process models. An efficient Monte Carlo algorithm is developed to calculate the marginal likelihood ratio for the hypothesis that two observed prints originate from the same finger against the hypothesis that they originate from...... different fingers. Our model achieves good performance on an NIST-FBI fingerprint database of 258 matched fingerprint pairs....

  7. On the stability and dynamics of stochastic spiking neuron models: Nonlinear Hawkes process and point process GLMs.

    Science.gov (United States)

    Gerhard, Felipe; Deger, Moritz; Truccolo, Wilson

    2017-02-01

    Point process generalized linear models (PP-GLMs) provide an important statistical framework for modeling spiking activity in single-neurons and neuronal networks. Stochastic stability is essential when sampling from these models, as done in computational neuroscience to analyze statistical properties of neuronal dynamics and in neuro-engineering to implement closed-loop applications. Here we show, however, that despite passing common goodness-of-fit tests, PP-GLMs estimated from data are often unstable, leading to divergent firing rates. The inclusion of absolute refractory periods is not a satisfactory solution since the activity then typically settles into unphysiological rates. To address these issues, we derive a framework for determining the existence and stability of fixed points of the expected conditional intensity function (CIF) for general PP-GLMs. Specifically, in nonlinear Hawkes PP-GLMs, the CIF is expressed as a function of the previous spike history and exogenous inputs. We use a mean-field quasi-renewal (QR) approximation that decomposes spike history effects into the contribution of the last spike and an average of the CIF over all spike histories prior to the last spike. Fixed points for stationary rates are derived as self-consistent solutions of integral equations. Bifurcation analysis and the number of fixed points predict that the original models can show stable, divergent, and metastable (fragile) dynamics. For fragile models, fluctuations of the single-neuron dynamics predict expected divergence times after which rates approach unphysiologically high values. This metric can be used to estimate the probability of rates to remain physiological for given time periods, e.g., for simulation purposes. We demonstrate the use of the stability framework using simulated single-neuron examples and neurophysiological recordings. Finally, we show how to adapt PP-GLM estimation procedures to guarantee model stability. Overall, our results provide a

  8. INHOMOGENEITY IN SPATIAL COX POINT PROCESSES – LOCATION DEPENDENT THINNING IS NOT THE ONLY OPTION

    Directory of Open Access Journals (Sweden)

    Michaela Prokešová

    2010-11-01

    Full Text Available In the literature on point processes the by far most popular option for introducing inhomogeneity into a point process model is the location dependent thinning (resulting in a second-order intensity-reweighted stationary point process. This produces a very tractable model and there are several fast estimation procedures available. Nevertheless, this model dilutes the interaction (or the geometrical structure of the original homogeneous model in a special way. When concerning the Markov point processes several alternative inhomogeneous models were suggested and investigated in the literature. But it is not so for the Cox point processes, the canonical models for clustered point patterns. In the contribution we discuss several other options how to define inhomogeneous Cox point process models that result in point patterns with different types of geometric structure. We further investigate the possible parameter estimation procedures for such models.

  9. Non-parametric Bayesian inference for inhomogeneous Markov point processes

    DEFF Research Database (Denmark)

    Berthelsen, Kasper Klitgaard; Møller, Jesper; Johansen, Per Michael

    is a shot noise process, and the interaction function for a pair of points depends only on the distance between the two points and is a piecewise linear function modelled by a marked Poisson process. Simulation of the resulting posterior using a Metropolis-Hastings algorithm in the "conventional" way...

  10. Point process modeling and estimation: Advances in the analysis of dynamic neural spiking data

    Science.gov (United States)

    Deng, Xinyi

    2016-08-01

    A common interest of scientists in many fields is to understand the relationship between the dynamics of a physical system and the occurrences of discrete events within such physical system. Seismologists study the connection between mechanical vibrations of the Earth and the occurrences of earthquakes so that future earthquakes can be better predicted. Astrophysicists study the association between the oscillating energy of celestial regions and the emission of photons to learn the Universe's various objects and their interactions. Neuroscientists study the link between behavior and the millisecond-timescale spike patterns of neurons to understand higher brain functions. Such relationships can often be formulated within the framework of state-space models with point process observations. The basic idea is that the dynamics of the physical systems are driven by the dynamics of some stochastic state variables and the discrete events we observe in an interval are noisy observations with distributions determined by the state variables. This thesis proposes several new methodological developments that advance the framework of state-space models with point process observations at the intersection of statistics and neuroscience. In particular, we develop new methods 1) to characterize the rhythmic spiking activity using history-dependent structure, 2) to model population spike activity using marked point process models, 3) to allow for real-time decision making, and 4) to take into account the need for dimensionality reduction for high-dimensional state and observation processes. We applied these methods to a novel problem of tracking rhythmic dynamics in the spiking of neurons in the subthalamic nucleus of Parkinson's patients with the goal of optimizing placement of deep brain stimulation electrodes. We developed a decoding algorithm that can make decision in real-time (for example, to stimulate the neurons or not) based on various sources of information present in

  11. Detection of bursts in extracellular spike trains using hidden semi-Markov point process models.

    Science.gov (United States)

    Tokdar, Surya; Xi, Peiyi; Kelly, Ryan C; Kass, Robert E

    2010-08-01

    Neurons in vitro and in vivo have epochs of bursting or "up state" activity during which firing rates are dramatically elevated. Various methods of detecting bursts in extracellular spike trains have appeared in the literature, the most widely used apparently being Poisson Surprise (PS). A natural description of the phenomenon assumes (1) there are two hidden states, which we label "burst" and "non-burst," (2) the neuron evolves stochastically, switching at random between these two states, and (3) within each state the spike train follows a time-homogeneous point process. If in (2) the transitions from non-burst to burst and burst to non-burst states are memoryless, this becomes a hidden Markov model (HMM). For HMMs, the state transitions follow exponential distributions, and are highly irregular. Because observed bursting may in some cases be fairly regular-exhibiting inter-burst intervals with small variation-we relaxed this assumption. When more general probability distributions are used to describe the state transitions the two-state point process model becomes a hidden semi-Markov model (HSMM). We developed an efficient Bayesian computational scheme to fit HSMMs to spike train data. Numerical simulations indicate the method can perform well, sometimes yielding very different results than those based on PS.

  12. PROCESSING UAV AND LIDAR POINT CLOUDS IN GRASS GIS

    Directory of Open Access Journals (Sweden)

    V. Petras

    2016-06-01

    Full Text Available Today’s methods of acquiring Earth surface data, namely lidar and unmanned aerial vehicle (UAV imagery, non-selectively collect or generate large amounts of points. Point clouds from different sources vary in their properties such as number of returns, density, or quality. We present a set of tools with applications for different types of points clouds obtained by a lidar scanner, structure from motion technique (SfM, and a low-cost 3D scanner. To take advantage of the vertical structure of multiple return lidar point clouds, we demonstrate tools to process them using 3D raster techniques which allow, for example, the development of custom vegetation classification methods. Dense point clouds obtained from UAV imagery, often containing redundant points, can be decimated using various techniques before further processing. We implemented and compared several decimation techniques in regard to their performance and the final digital surface model (DSM. Finally, we will describe the processing of a point cloud from a low-cost 3D scanner, namely Microsoft Kinect, and its application for interaction with physical models. All the presented tools are open source and integrated in GRASS GIS, a multi-purpose open source GIS with remote sensing capabilities. The tools integrate with other open source projects, specifically Point Data Abstraction Library (PDAL, Point Cloud Library (PCL, and OpenKinect libfreenect2 library to benefit from the open source point cloud ecosystem. The implementation in GRASS GIS ensures long term maintenance and reproducibility by the scientific community but also by the original authors themselves.

  13. Pseudo-dynamic source modelling with 1-point and 2-point statistics of earthquake source parameters

    KAUST Repository

    Song, S. G.

    2013-12-24

    Ground motion prediction is an essential element in seismic hazard and risk analysis. Empirical ground motion prediction approaches have been widely used in the community, but efficient simulation-based ground motion prediction methods are needed to complement empirical approaches, especially in the regions with limited data constraints. Recently, dynamic rupture modelling has been successfully adopted in physics-based source and ground motion modelling, but it is still computationally demanding and many input parameters are not well constrained by observational data. Pseudo-dynamic source modelling keeps the form of kinematic modelling with its computational efficiency, but also tries to emulate the physics of source process. In this paper, we develop a statistical framework that governs the finite-fault rupture process with 1-point and 2-point statistics of source parameters in order to quantify the variability of finite source models for future scenario events. We test this method by extracting 1-point and 2-point statistics from dynamically derived source models and simulating a number of rupture scenarios, given target 1-point and 2-point statistics. We propose a new rupture model generator for stochastic source modelling with the covariance matrix constructed from target 2-point statistics, that is, auto- and cross-correlations. Our sensitivity analysis of near-source ground motions to 1-point and 2-point statistics of source parameters provides insights into relations between statistical rupture properties and ground motions. We observe that larger standard deviation and stronger correlation produce stronger peak ground motions in general. The proposed new source modelling approach will contribute to understanding the effect of earthquake source on near-source ground motion characteristics in a more quantitative and systematic way.

  14. From point process observations to collective neural dynamics: Nonlinear Hawkes process GLMs, low-dimensional dynamics and coarse graining.

    Science.gov (United States)

    Truccolo, Wilson

    2016-11-01

    This review presents a perspective on capturing collective dynamics in recorded neuronal ensembles based on multivariate point process models, inference of low-dimensional dynamics and coarse graining of spatiotemporal measurements. A general probabilistic framework for continuous time point processes reviewed, with an emphasis on multivariate nonlinear Hawkes processes with exogenous inputs. A point process generalized linear model (PP-GLM) framework for the estimation of discrete time multivariate nonlinear Hawkes processes is described. The approach is illustrated with the modeling of collective dynamics in neocortical neuronal ensembles recorded in human and non-human primates, and prediction of single-neuron spiking. A complementary approach to capture collective dynamics based on low-dimensional dynamics ("order parameters") inferred via latent state-space models with point process observations is presented. The approach is illustrated by inferring and decoding low-dimensional dynamics in primate motor cortex during naturalistic reach and grasp movements. Finally, we briefly review hypothesis tests based on conditional inference and spatiotemporal coarse graining for assessing collective dynamics in recorded neuronal ensembles. Published by Elsevier Ltd.

  15. Model for Semantically Rich Point Cloud Data

    Science.gov (United States)

    Poux, F.; Neuville, R.; Hallot, P.; Billen, R.

    2017-10-01

    This paper proposes an interoperable model for managing high dimensional point clouds while integrating semantics. Point clouds from sensors are a direct source of information physically describing a 3D state of the recorded environment. As such, they are an exhaustive representation of the real world at every scale: 3D reality-based spatial data. Their generation is increasingly fast but processing routines and data models lack of knowledge to reason from information extraction rather than interpretation. The enhanced smart point cloud developed model allows to bring intelligence to point clouds via 3 connected meta-models while linking available knowledge and classification procedures that permits semantic injection. Interoperability drives the model adaptation to potentially many applications through specialized domain ontologies. A first prototype is implemented in Python and PostgreSQL database and allows to combine semantic and spatial concepts for basic hybrid queries on different point clouds.

  16. MODEL FOR SEMANTICALLY RICH POINT CLOUD DATA

    Directory of Open Access Journals (Sweden)

    F. Poux

    2017-10-01

    Full Text Available This paper proposes an interoperable model for managing high dimensional point clouds while integrating semantics. Point clouds from sensors are a direct source of information physically describing a 3D state of the recorded environment. As such, they are an exhaustive representation of the real world at every scale: 3D reality-based spatial data. Their generation is increasingly fast but processing routines and data models lack of knowledge to reason from information extraction rather than interpretation. The enhanced smart point cloud developed model allows to bring intelligence to point clouds via 3 connected meta-models while linking available knowledge and classification procedures that permits semantic injection. Interoperability drives the model adaptation to potentially many applications through specialized domain ontologies. A first prototype is implemented in Python and PostgreSQL database and allows to combine semantic and spatial concepts for basic hybrid queries on different point clouds.

  17. Statistical aspects of determinantal point processes

    DEFF Research Database (Denmark)

    Lavancier, Frédéric; Møller, Jesper; Rubak, Ege Holger

    The statistical aspects of determinantal point processes (DPPs) seem largely unexplored. We review the appealing properties of DDPs, demonstrate that they are useful models for repulsiveness, detail a simulation procedure, and provide freely available software for simulation and statistical...... inference. We pay special attention to stationary DPPs, where we give a simple condition ensuring their existence, construct parametric models, describe how they can be well approximated so that the likelihood can be evaluated and realizations can be simulated, and discuss how statistical inference...

  18. Pseudo-dynamic source modelling with 1-point and 2-point statistics of earthquake source parameters

    KAUST Repository

    Song, S. G.; Dalguer, L. A.; Mai, Paul Martin

    2013-01-01

    statistical framework that governs the finite-fault rupture process with 1-point and 2-point statistics of source parameters in order to quantify the variability of finite source models for future scenario events. We test this method by extracting 1-point

  19. Hierarchical spatial point process analysis for a plant community with high biodiversity

    DEFF Research Database (Denmark)

    Illian, Janine B.; Møller, Jesper; Waagepetersen, Rasmus

    2009-01-01

    A complex multivariate spatial point pattern of a plant community with high biodiversity is modelled using a hierarchical multivariate point process model. In the model, interactions between plants with different post-fire regeneration strategies are of key interest. We consider initially a maxim...

  20. Lévy based Cox point processes

    DEFF Research Database (Denmark)

    Hellmund, Gunnar; Prokesová, Michaela; Jensen, Eva Bjørn Vedel

    2008-01-01

    In this paper we introduce Lévy-driven Cox point processes (LCPs) as Cox point processes with driving intensity function Λ defined by a kernel smoothing of a Lévy basis (an independently scattered, infinitely divisible random measure). We also consider log Lévy-driven Cox point processes (LLCPs......) with Λ equal to the exponential of such a kernel smoothing. Special cases are shot noise Cox processes, log Gaussian Cox processes, and log shot noise Cox processes. We study the theoretical properties of Lévy-based Cox processes, including moment properties described by nth-order product densities...

  1. A case study on point process modelling in disease mapping

    Czech Academy of Sciences Publication Activity Database

    Beneš, Viktor; Bodlák, M.; Moller, J.; Waagepetersen, R.

    2005-01-01

    Roč. 24, č. 3 (2005), s. 159-168 ISSN 1580-3139 R&D Projects: GA MŠk 0021620839; GA ČR GA201/03/0946 Institutional research plan: CEZ:AV0Z10750506 Keywords : log Gaussian Cox point process * Bayesian estimation Subject RIV: BB - Applied Statistics, Operational Research

  2. Plasmon point spread functions: How do we model plasmon-mediated emission processes?

    Science.gov (United States)

    Willets, Katherine A.

    2014-02-01

    A major challenge with studying plasmon-mediated emission events is the small size of plasmonic nanoparticles relative to the wavelength of light. Objects smaller than roughly half the wavelength of light will appear as diffraction-limited spots in far-field optical images, presenting a significant experimental challenge for studying plasmonic processes on the nanoscale. Super-resolution imaging has recently been applied to plasmonic nanosystems and allows plasmon-mediated emission to be resolved on the order of ˜5 nm. In super-resolution imaging, a diffraction-limited spot is fit to some model function in order to calculate the position of the emission centroid, which represents the location of the emitter. However, the accuracy of the centroid position strongly depends on how well the fitting function describes the data. This Perspective discusses the commonly used two-dimensional Gaussian fitting function applied to super-resolution imaging of plasmon-mediated emission, then introduces an alternative model based on dipole point spread functions. The two fitting models are compared and contrasted for super-resolution imaging of nanoparticle scattering/luminescence, surface-enhanced Raman scattering, and surface-enhanced fluorescence.

  3. Radial Basis Functional Model of Multi-Point Dieless Forming Process for Springback Reduction and Compensation

    Directory of Open Access Journals (Sweden)

    Misganaw Abebe

    2017-11-01

    Full Text Available Springback in multi-point dieless forming (MDF is a common problem because of the small deformation and blank holder free boundary condition. Numerical simulations are widely used in sheet metal forming to predict the springback. However, the computational time in using the numerical tools is time costly to find the optimal process parameters value. This study proposes radial basis function (RBF to replace the numerical simulation model by using statistical analyses that are based on a design of experiment (DOE. Punch holding time, blank thickness, and curvature radius are chosen as effective process parameters for determining the springback. The Latin hypercube DOE method facilitates statistical analyses and the extraction of a prediction model in the experimental process parameter domain. Finite element (FE simulation model is conducted in the ABAQUS commercial software to generate the springback responses of the training and testing samples. The genetic algorithm is applied to find the optimal value for reducing and compensating the induced springback for the different blank thicknesses using the developed RBF prediction model. Finally, the RBF numerical result is verified by comparing with the FE simulation result of the optimal process parameters and both results show that the springback is almost negligible from the target shape.

  4. The cylindrical K-function and Poisson line cluster point processes

    DEFF Research Database (Denmark)

    Møller, Jesper; Safavimanesh, Farzaneh; Rasmussen, Jakob G.

    Poisson line cluster point processes, is also introduced. Parameter estimation based on moment methods or Bayesian inference for this model is discussed when the underlying Poisson line process and the cluster memberships are treated as hidden processes. To illustrate the methodologies, we analyze two...

  5. Bayesian analysis of Markov point processes

    DEFF Research Database (Denmark)

    Berthelsen, Kasper Klitgaard; Møller, Jesper

    2006-01-01

    Recently Møller, Pettitt, Berthelsen and Reeves introduced a new MCMC methodology for drawing samples from a posterior distribution when the likelihood function is only specified up to a normalising constant. We illustrate the method in the setting of Bayesian inference for Markov point processes...... a partially ordered Markov point process as the auxiliary variable. As the method requires simulation from the "unknown" likelihood, perfect simulation algorithms for spatial point processes become useful....

  6. Point process models for localization and interdependence of punctate cellular structures.

    Science.gov (United States)

    Li, Ying; Majarian, Timothy D; Naik, Armaghan W; Johnson, Gregory R; Murphy, Robert F

    2016-07-01

    Accurate representations of cellular organization for multiple eukaryotic cell types are required for creating predictive models of dynamic cellular function. To this end, we have previously developed the CellOrganizer platform, an open source system for generative modeling of cellular components from microscopy images. CellOrganizer models capture the inherent heterogeneity in the spatial distribution, size, and quantity of different components among a cell population. Furthermore, CellOrganizer can generate quantitatively realistic synthetic images that reflect the underlying cell population. A current focus of the project is to model the complex, interdependent nature of organelle localization. We built upon previous work on developing multiple non-parametric models of organelles or structures that show punctate patterns. The previous models described the relationships between the subcellular localization of puncta and the positions of cell and nuclear membranes and microtubules. We extend these models to consider the relationship to the endoplasmic reticulum (ER), and to consider the relationship between the positions of different puncta of the same type. Our results do not suggest that the punctate patterns we examined are dependent on ER position or inter- and intra-class proximity. With these results, we built classifiers to update previous assignments of proteins to one of 11 patterns in three distinct cell lines. Our generative models demonstrate the ability to construct statistically accurate representations of puncta localization from simple cellular markers in distinct cell types, capturing the complex phenomena of cellular structure interaction with little human input. This protocol represents a novel approach to vesicular protein annotation, a field that is often neglected in high-throughput microscopy. These results suggest that spatial point process models provide useful insight with respect to the spatial dependence between cellular structures.

  7. Energy risk management through self-exciting marked point process

    International Nuclear Information System (INIS)

    Herrera, Rodrigo

    2013-01-01

    Crude oil is a dynamically traded commodity that affects many economies. We propose a collection of marked self-exciting point processes with dependent arrival rates for extreme events in oil markets and related risk measures. The models treat the time among extreme events in oil markets as a stochastic process. The main advantage of this approach is its capability to capture the short, medium and long-term behavior of extremes without involving an arbitrary stochastic volatility model or a prefiltration of the data, as is common in extreme value theory applications. We make use of the proposed model in order to obtain an improved estimate for the Value at Risk in oil markets. Empirical findings suggest that the reliability and stability of Value at Risk estimates improve as a result of finer modeling approach. This is supported by an empirical application in the representative West Texas Intermediate (WTI) and Brent crude oil markets. - Highlights: • We propose marked self-exciting point processes for extreme events in oil markets. • This approach captures the short and long-term behavior of extremes. • We improve the estimates for the VaR in the WTI and Brent crude oil markets

  8. Process-based coastal erosion modeling for Drew Point (North Slope, Alaska)

    Science.gov (United States)

    Ravens, Thomas M.; Jones, Benjamin M.; Zhang, Jinlin; Arp, Christopher D.; Schmutz, Joel A.

    2012-01-01

    A predictive, coastal erosion/shoreline change model has been developed for a small coastal segment near Drew Point, Beaufort Sea, Alaska. This coastal setting has experienced a dramatic increase in erosion since the early 2000’s. The bluffs at this site are 3-4 m tall and consist of ice-wedge bounded blocks of fine-grained sediments cemented by ice-rich permafrost and capped with a thin organic layer. The bluffs are typically fronted by a narrow (∼ 5  m wide) beach or none at all. During a storm surge, the sea contacts the base of the bluff and a niche is formed through thermal and mechanical erosion. The niche grows both vertically and laterally and eventually undermines the bluff, leading to block failure or collapse. The fallen block is then eroded both thermally and mechanically by waves and currents, which must occur before a new niche forming episode may begin. The erosion model explicitly accounts for and integrates a number of these processes including: (1) storm surge generation resulting from wind and atmospheric forcing, (2) erosional niche growth resulting from wave-induced turbulent heat transfer and sediment transport (using the Kobayashi niche erosion model), and (3) thermal and mechanical erosion of the fallen block. The model was calibrated with historic shoreline change data for one time period (1979-2002), and validated with a later time period (2002-2007).

  9. Birth-death models and coalescent point processes: the shape and probability of reconstructed phylogenies.

    Science.gov (United States)

    Lambert, Amaury; Stadler, Tanja

    2013-12-01

    Forward-in-time models of diversification (i.e., speciation and extinction) produce phylogenetic trees that grow "vertically" as time goes by. Pruning the extinct lineages out of such trees leads to natural models for reconstructed trees (i.e., phylogenies of extant species). Alternatively, reconstructed trees can be modelled by coalescent point processes (CPPs), where trees grow "horizontally" by the sequential addition of vertical edges. Each new edge starts at some random speciation time and ends at the present time; speciation times are drawn from the same distribution independently. CPPs lead to extremely fast computation of tree likelihoods and simulation of reconstructed trees. Their topology always follows the uniform distribution on ranked tree shapes (URT). We characterize which forward-in-time models lead to URT reconstructed trees and among these, which lead to CPP reconstructed trees. We show that for any "asymmetric" diversification model in which speciation rates only depend on time and extinction rates only depend on time and on a non-heritable trait (e.g., age), the reconstructed tree is CPP, even if extant species are incompletely sampled. If rates additionally depend on the number of species, the reconstructed tree is (only) URT (but not CPP). We characterize the common distribution of speciation times in the CPP description, and discuss incomplete species sampling as well as three special model cases in detail: (1) the extinction rate does not depend on a trait; (2) rates do not depend on time; (3) mass extinctions may happen additionally at certain points in the past. Copyright © 2013 Elsevier Inc. All rights reserved.

  10. Analysis of multi-species point patterns using multivariate log Gaussian Cox processes

    DEFF Research Database (Denmark)

    Waagepetersen, Rasmus; Guan, Yongtao; Jalilian, Abdollah

    Multivariate log Gaussian Cox processes are flexible models for multivariate point patterns. However, they have so far only been applied in bivariate cases. In this paper we move beyond the bivariate case in order to model multi-species point patterns of tree locations. In particular we address t...... of the data. The selected number of common latent fields provides an index of complexity of the multivariate covariance structure. Hierarchical clustering is used to identify groups of species with similar patterns of dependence on the common latent fields.......Multivariate log Gaussian Cox processes are flexible models for multivariate point patterns. However, they have so far only been applied in bivariate cases. In this paper we move beyond the bivariate case in order to model multi-species point patterns of tree locations. In particular we address...... the problems of identifying parsimonious models and of extracting biologically relevant information from the fitted models. The latent multivariate Gaussian field is decomposed into components given in terms of random fields common to all species and components which are species specific. This allows...

  11. Framework for adaptive multiscale analysis of nonhomogeneous point processes.

    Science.gov (United States)

    Helgason, Hannes; Bartroff, Jay; Abry, Patrice

    2011-01-01

    We develop the methodology for hypothesis testing and model selection in nonhomogeneous Poisson processes, with an eye toward the application of modeling and variability detection in heart beat data. Modeling the process' non-constant rate function using templates of simple basis functions, we develop the generalized likelihood ratio statistic for a given template and a multiple testing scheme to model-select from a family of templates. A dynamic programming algorithm inspired by network flows is used to compute the maximum likelihood template in a multiscale manner. In a numerical example, the proposed procedure is nearly as powerful as the super-optimal procedures that know the true template size and true partition, respectively. Extensions to general history-dependent point processes is discussed.

  12. Seed Dispersal, Microsites or Competition—What Drives Gap Regeneration in an Old-Growth Forest? An Application of Spatial Point Process Modelling

    Directory of Open Access Journals (Sweden)

    Georg Gratzer

    2018-04-01

    Full Text Available The spatial structure of trees is a template for forest dynamics and the outcome of a variety of processes in ecosystems. Identifying the contribution and magnitude of the different drivers is an age-old task in plant ecology. Recently, the modelling of a spatial point process was used to identify factors driving the spatial distribution of trees at stand scales. Processes driving the coexistence of trees, however, frequently unfold within gaps and questions on the role of resource heterogeneity within-gaps have become central issues in community ecology. We tested the applicability of a spatial point process modelling approach for quantifying the effects of seed dispersal, within gap light environment, microsite heterogeneity, and competition on the generation of within gap spatial structure of small tree seedlings in a temperate, old growth, mixed-species forest. By fitting a non-homogeneous Neyman–Scott point process model, we could disentangle the role of seed dispersal from niche partitioning for within gap tree establishment and did not detect seed densities as a factor explaining the clustering of small trees. We found only a very weak indication for partitioning of within gap light among the three species and detected a clear niche segregation of Picea abies (L. Karst. on nurse logs. The other two dominating species, Abies alba Mill. and Fagus sylvatica L., did not show signs of within gap segregation.

  13. Spatial Stochastic Point Models for Reservoir Characterization

    Energy Technology Data Exchange (ETDEWEB)

    Syversveen, Anne Randi

    1997-12-31

    The main part of this thesis discusses stochastic modelling of geology in petroleum reservoirs. A marked point model is defined for objects against a background in a two-dimensional vertical cross section of the reservoir. The model handles conditioning on observations from more than one well for each object and contains interaction between objects, and the objects have the correct length distribution when penetrated by wells. The model is developed in a Bayesian setting. The model and the simulation algorithm are demonstrated by means of an example with simulated data. The thesis also deals with object recognition in image analysis, in a Bayesian framework, and with a special type of spatial Cox processes called log-Gaussian Cox processes. In these processes, the logarithm of the intensity function is a Gaussian process. The class of log-Gaussian Cox processes provides flexible models for clustering. The distribution of such a process is completely characterized by the intensity and the pair correlation function of the Cox process. 170 refs., 37 figs., 5 tabs.

  14. SINGLE TREE DETECTION FROM AIRBORNE LASER SCANNING DATA USING A MARKED POINT PROCESS BASED METHOD

    Directory of Open Access Journals (Sweden)

    J. Zhang

    2013-05-01

    Full Text Available Tree detection and reconstruction is of great interest in large-scale city modelling. In this paper, we present a marked point process model to detect single trees from airborne laser scanning (ALS data. We consider single trees in ALS recovered canopy height model (CHM as a realization of point process of circles. Unlike traditional marked point process, we sample the model in a constraint configuration space by making use of image process techniques. A Gibbs energy is defined on the model, containing a data term which judge the fitness of the model with respect to the data, and prior term which incorporate the prior knowledge of object layouts. We search the optimal configuration through a steepest gradient descent algorithm. The presented hybrid framework was test on three forest plots and experiments show the effectiveness of the proposed method.

  15. Spatial point process analysis for a plant community with high biodiversity

    DEFF Research Database (Denmark)

    Illian, Janine; Møller, Jesper; Waagepetersen, Rasmus Plenge

    A complex multivariate spatial point pattern for a plant community with high biodiversity is modelled using a hierarchical multivariate point process model. In the model, interactions between plants with different post-fire regeneration strategies are of key interest. We consider initially...... a maximum likelihood approach to inference where problems arise due to unknown interaction radii for the plants. We next demonstrate that a Bayesian approach provides a flexible framework for incorporating prior information concerning the interaction radii. From an ecological perspective, we are able both...

  16. Novel evaluation metrics for sparse spatio-temporal point process hotspot predictions - a crime case study

    OpenAIRE

    Adepeju, M.; Rosser, G.; Cheng, T.

    2016-01-01

    Many physical and sociological processes are represented as discrete events in time and space. These spatio-temporal point processes are often sparse, meaning that they cannot be aggregated and treated with conventional regression models. Models based on the point process framework may be employed instead for prediction purposes. Evaluating the predictive performance of these models poses a unique challenge, as the same sparseness prevents the use of popular measures such as the root mean squ...

  17. Testing Local Independence between Two Point Processes

    DEFF Research Database (Denmark)

    Allard, Denis; Brix, Anders; Chadæuf, Joël

    2001-01-01

    Independence test, Inhomogeneous point processes, Local test, Monte Carlo, Nonstationary, Rotations, Spatial pattern, Tiger bush......Independence test, Inhomogeneous point processes, Local test, Monte Carlo, Nonstationary, Rotations, Spatial pattern, Tiger bush...

  18. Dew point vs bubble point : a misunderstood constraint on gravity drainage processes

    Energy Technology Data Exchange (ETDEWEB)

    Nenninger, J. [N-Solv Corp., Calgary, AB (Canada); Gunnewiek, L. [Hatch Ltd., Mississauga, ON (Canada)

    2009-07-01

    This study demonstrated that gravity drainage processes that use blended fluids such as solvents have an inherently unstable material balance due to differences between dew point and bubble point compositions. The instability can lead to the accumulation of volatile components within the chamber, and impair mass and heat transfer processes. Case studies were used to demonstrate the large temperature gradients within the vapour chamber caused by temperature differences between the bubble point and dew point for blended fluids. A review of published data showed that many experiments on in-situ processes do not account for unstable material balances caused by a lack of steam trap control. A study of temperature profiles during steam assisted gravity drainage (SAGD) studies showed significant temperature depressions caused by methane accumulations at the outside perimeter of the steam chamber. It was demonstrated that the condensation of large volumes of purified solvents provided an efficient mechanism for the removal of methane from the chamber. It was concluded that gravity drainage processes can be optimized by using pure propane during the injection process. 22 refs., 1 tab., 18 figs.

  19. Fixed-point signal processing

    CERN Document Server

    Padgett, Wayne T

    2009-01-01

    This book is intended to fill the gap between the ""ideal precision"" digital signal processing (DSP) that is widely taught, and the limited precision implementation skills that are commonly required in fixed-point processors and field programmable gate arrays (FPGAs). These skills are often neglected at the university level, particularly for undergraduates. We have attempted to create a resource both for a DSP elective course and for the practicing engineer with a need to understand fixed-point implementation. Although we assume a background in DSP, Chapter 2 contains a review of basic theory

  20. Spatio-temporal point process filtering methods with an application

    Czech Academy of Sciences Publication Activity Database

    Frcalová, B.; Beneš, V.; Klement, Daniel

    2010-01-01

    Roč. 21, 3-4 (2010), s. 240-252 ISSN 1180-4009 R&D Projects: GA AV ČR(CZ) IAA101120604 Institutional research plan: CEZ:AV0Z50110509 Keywords : cox point process * filtering * spatio-temporal modelling * spike Subject RIV: BA - General Mathematics Impact factor: 0.750, year: 2010

  1. Shot-noise-weighted processes : a new family of spatial point processes

    NARCIS (Netherlands)

    M.N.M. van Lieshout (Marie-Colette); I.S. Molchanov (Ilya)

    1995-01-01

    textabstractThe paper suggests a new family of of spatial point processes distributions. They are defined by means of densities with respect to the Poisson point process within a bounded set. These densities are given in terms of a functional of the shot-noise process with a given influence

  2. Modelling estimation and analysis of dynamic processes from image sequences using temporal random closed sets and point processes with application to the cell exocytosis and endocytosis

    OpenAIRE

    Díaz Fernández, Ester

    2010-01-01

    In this thesis, new models and methodologies are introduced for the analysis of dynamic processes characterized by image sequences with spatial temporal overlapping. The spatial temporal overlapping exists in many natural phenomena and should be addressed properly in several Science disciplines such as Microscopy, Material Sciences, Biology, Geostatistics or Communication Networks. This work is related to the Point Process and Random Closed Set theories, within Stochastic Ge...

  3. A Marked Point Process Framework for Extracellular Electrical Potentials

    Directory of Open Access Journals (Sweden)

    Carlos A. Loza

    2017-12-01

    Full Text Available Neuromodulations are an important component of extracellular electrical potentials (EEP, such as the Electroencephalogram (EEG, Electrocorticogram (ECoG and Local Field Potentials (LFP. This spatially temporal organized multi-frequency transient (phasic activity reflects the multiscale spatiotemporal synchronization of neuronal populations in response to external stimuli or internal physiological processes. We propose a novel generative statistical model of a single EEP channel, where the collected signal is regarded as the noisy addition of reoccurring, multi-frequency phasic events over time. One of the main advantages of the proposed framework is the exceptional temporal resolution in the time location of the EEP phasic events, e.g., up to the sampling period utilized in the data collection. Therefore, this allows for the first time a description of neuromodulation in EEPs as a Marked Point Process (MPP, represented by their amplitude, center frequency, duration, and time of occurrence. The generative model for the multi-frequency phasic events exploits sparseness and involves a shift-invariant implementation of the clustering technique known as k-means. The cost function incorporates a robust estimation component based on correntropy to mitigate the outliers caused by the inherent noise in the EEP. Lastly, the background EEP activity is explicitly modeled as the non-sparse component of the collected signal to further improve the delineation of the multi-frequency phasic events in time. The framework is validated using two publicly available datasets: the DREAMS sleep spindles database and one of the Brain-Computer Interface (BCI competition datasets. The results achieve benchmark performance and provide novel quantitative descriptions based on power, event rates and timing in order to assess behavioral correlates beyond the classical power spectrum-based analysis. This opens the possibility for a unifying point process framework of

  4. Investigation of Random Switching Driven by a Poisson Point Process

    DEFF Research Database (Denmark)

    Simonsen, Maria; Schiøler, Henrik; Leth, John-Josef

    2015-01-01

    This paper investigates the switching mechanism of a two-dimensional switched system, when the switching events are generated by a Poisson point process. A model, in the shape of a stochastic process, for such a system is derived and the distribution of the trajectory's position is developed...... together with marginal density functions for the coordinate functions. Furthermore, the joint probability distribution is given explicitly....

  5. Using a Virtual Experiment to Analyze Infiltration Process from Point to Grid-cell Size Scale

    Science.gov (United States)

    Barrios, M. I.

    2013-12-01

    The hydrological science requires the emergence of a consistent theoretical corpus driving the relationships between dominant physical processes at different spatial and temporal scales. However, the strong spatial heterogeneities and non-linearities of these processes make difficult the development of multiscale conceptualizations. Therefore, scaling understanding is a key issue to advance this science. This work is focused on the use of virtual experiments to address the scaling of vertical infiltration from a physically based model at point scale to a simplified physically meaningful modeling approach at grid-cell scale. Numerical simulations have the advantage of deal with a wide range of boundary and initial conditions against field experimentation. The aim of the work was to show the utility of numerical simulations to discover relationships between the hydrological parameters at both scales, and to use this synthetic experience as a media to teach the complex nature of this hydrological process. The Green-Ampt model was used to represent vertical infiltration at point scale; and a conceptual storage model was employed to simulate the infiltration process at the grid-cell scale. Lognormal and beta probability distribution functions were assumed to represent the heterogeneity of soil hydraulic parameters at point scale. The linkages between point scale parameters and the grid-cell scale parameters were established by inverse simulations based on the mass balance equation and the averaging of the flow at the point scale. Results have shown numerical stability issues for particular conditions and have revealed the complex nature of the non-linear relationships between models' parameters at both scales and indicate that the parameterization of point scale processes at the coarser scale is governed by the amplification of non-linear effects. The findings of these simulations have been used by the students to identify potential research questions on scale issues

  6. Processing Terrain Point Cloud Data

    KAUST Repository

    DeVore, Ronald

    2013-01-10

    Terrain point cloud data are typically acquired through some form of Light Detection And Ranging sensing. They form a rich resource that is important in a variety of applications including navigation, line of sight, and terrain visualization. Processing terrain data has not received the attention of other forms of surface reconstruction or of image processing. The goal of terrain data processing is to convert the point cloud into a succinct representation system that is amenable to the various application demands. The present paper presents a platform for terrain processing built on the following principles: (i) measuring distortion in the Hausdorff metric, which we argue is a good match for the application demands, (ii) a multiscale representation based on tree approximation using local polynomial fitting. The basic elements held in the nodes of the tree can be efficiently encoded, transmitted, visualized, and utilized for the various target applications. Several challenges emerge because of the variable resolution of the data, missing data, occlusions, and noise. Techniques for identifying and handling these challenges are developed. © 2013 Society for Industrial and Applied Mathematics.

  7. Imitation learning of Non-Linear Point-to-Point Robot Motions using Dirichlet Processes

    DEFF Research Database (Denmark)

    Krüger, Volker; Tikhanoff, Vadim; Natale, Lorenzo

    2012-01-01

    In this paper we discuss the use of the infinite Gaussian mixture model and Dirichlet processes for learning robot movements from demonstrations. Starting point of this work is an earlier paper where the authors learn a non-linear dynamic robot movement model from a small number of observations....... The model in that work is learned using a classical finite Gaussian mixture model (FGMM) where the Gaussian mixtures are appropriately constrained. The problem with this approach is that one needs to make a good guess for how many mixtures the FGMM should use. In this work, we generalize this approach...... our algorithm on the same data that was used in [5], where the authors use motion capture devices to record the demonstrations. As further validation we test our approach on novel data acquired on our iCub in a different demonstration scenario in which the robot is physically driven by the human...

  8. Insights into mortality patterns and causes of death through a process point of view model.

    Science.gov (United States)

    Anderson, James J; Li, Ting; Sharrow, David J

    2017-02-01

    Process point of view (POV) models of mortality, such as the Strehler-Mildvan and stochastic vitality models, represent death in terms of the loss of survival capacity through challenges and dissipation. Drawing on hallmarks of aging, we link these concepts to candidate biological mechanisms through a framework that defines death as challenges to vitality where distal factors defined the age-evolution of vitality and proximal factors define the probability distribution of challenges. To illustrate the process POV, we hypothesize that the immune system is a mortality nexus, characterized by two vitality streams: increasing vitality representing immune system development and immunosenescence representing vitality dissipation. Proximal challenges define three mortality partitions: juvenile and adult extrinsic mortalities and intrinsic adult mortality. Model parameters, generated from Swedish mortality data (1751-2010), exhibit biologically meaningful correspondences to economic, health and cause-of-death patterns. The model characterizes the twentieth century epidemiological transition mainly as a reduction in extrinsic mortality resulting from a shift from high magnitude disease challenges on individuals at all vitality levels to low magnitude stress challenges on low vitality individuals. Of secondary importance, intrinsic mortality was described by a gradual reduction in the rate of loss of vitality presumably resulting from reduction in the rate of immunosenescence. Extensions and limitations of a distal/proximal framework for characterizing more explicit causes of death, e.g. the young adult mortality hump or cancer in old age are discussed.

  9. Predicting seizures in untreated temporal lobe epilepsy using point-process nonlinear models of heartbeat dynamics.

    Science.gov (United States)

    Valenza, G; Romigi, A; Citi, L; Placidi, F; Izzi, F; Albanese, M; Scilingo, E P; Marciani, M G; Duggento, A; Guerrisi, M; Toschi, N; Barbieri, R

    2016-08-01

    Symptoms of temporal lobe epilepsy (TLE) are frequently associated with autonomic dysregulation, whose underlying biological processes are thought to strongly contribute to sudden unexpected death in epilepsy (SUDEP). While abnormal cardiovascular patterns commonly occur during ictal events, putative patterns of autonomic cardiac effects during pre-ictal (PRE) periods (i.e. periods preceding seizures) are still unknown. In this study, we investigated TLE-related heart rate variability (HRV) through instantaneous, nonlinear estimates of cardiovascular oscillations during inter-ictal (INT) and PRE periods. ECG recordings from 12 patients with TLE were processed to extract standard HRV indices, as well as indices of instantaneous HRV complexity (dominant Lyapunov exponent and entropy) and higher-order statistics (bispectra) obtained through definition of inhomogeneous point-process nonlinear models, employing Volterra-Laguerre expansions of linear, quadratic, and cubic kernels. Experimental results demonstrate that the best INT vs. PRE classification performance (balanced accuracy: 73.91%) was achieved only when retaining the time-varying, nonlinear, and non-stationary structure of heartbeat dynamical features. The proposed approach opens novel important avenues in predicting ictal events using information gathered from cardiovascular signals exclusively.

  10. Two-step estimation for inhomogeneous spatial point processes

    DEFF Research Database (Denmark)

    Waagepetersen, Rasmus; Guan, Yongtao

    This paper is concerned with parameter estimation for inhomogeneous spatial point processes with a regression model for the intensity function and tractable second order properties (K-function). Regression parameters are estimated using a Poisson likelihood score estimating function and in a second...... step minimum contrast estimation is applied for the residual clustering parameters. Asymptotic normality of parameter estimates is established under certain mixing conditions and we exemplify how the results may be applied in ecological studies of rain forests....

  11. Characterization results and Markov chain Monte Carlo algorithms including exact simulation for some spatial point processes

    DEFF Research Database (Denmark)

    Häggström, Olle; Lieshout, Marie-Colette van; Møller, Jesper

    1999-01-01

    The area-interaction process and the continuum random-cluster model are characterized in terms of certain functional forms of their respective conditional intensities. In certain cases, these two point process models can be derived from a bivariate point process model which in many respects...... is simpler to analyse and simulate. Using this correspondence we devise a two-component Gibbs sampler, which can be used for fast and exact simulation by extending the recent ideas of Propp and Wilson. We further introduce a Swendsen-Wang type algorithm. The relevance of the results within spatial statistics...

  12. Integrated modeling and analysis methodology for precision pointing applications

    Science.gov (United States)

    Gutierrez, Homero L.

    2002-07-01

    Space-based optical systems that perform tasks such as laser communications, Earth imaging, and astronomical observations require precise line-of-sight (LOS) pointing. A general approach is described for integrated modeling and analysis of these types of systems within the MATLAB/Simulink environment. The approach can be applied during all stages of program development, from early conceptual design studies to hardware implementation phases. The main objective is to predict the dynamic pointing performance subject to anticipated disturbances and noise sources. Secondary objectives include assessing the control stability, levying subsystem requirements, supporting pointing error budgets, and performing trade studies. The integrated model resides in Simulink, and several MATLAB graphical user interfaces (GUI"s) allow the user to configure the model, select analysis options, run analyses, and process the results. A convenient parameter naming and storage scheme, as well as model conditioning and reduction tools and run-time enhancements, are incorporated into the framework. This enables the proposed architecture to accommodate models of realistic complexity.

  13. A three-dimensional point process model for the spatial distribution of disease occurrence in relation to an exposure source

    DEFF Research Database (Denmark)

    Grell, Kathrine; Diggle, Peter J; Frederiksen, Kirsten

    2015-01-01

    We study methods for how to include the spatial distribution of tumours when investigating the relation between brain tumours and the exposure from radio frequency electromagnetic fields caused by mobile phone use. Our suggested point process model is adapted from studies investigating spatial...... the Interphone Study, a large multinational case-control study on the association between brain tumours and mobile phone use....

  14. Monte Carlo based toy model for fission process

    International Nuclear Information System (INIS)

    Kurniadi, R.; Waris, A.; Viridi, S.

    2014-01-01

    There are many models and calculation techniques to obtain visible image of fission yield process. In particular, fission yield can be calculated by using two calculations approach, namely macroscopic approach and microscopic approach. This work proposes another calculation approach in which the nucleus is treated as a toy model. Hence, the fission process does not represent real fission process in nature completely. The toy model is formed by Gaussian distribution of random number that randomizes distance like the distance between particle and central point. The scission process is started by smashing compound nucleus central point into two parts that are left central and right central points. These three points have different Gaussian distribution parameters such as mean (μ CN , μ L , μ R ), and standard deviation (σ CN , σ L , σ R ). By overlaying of three distributions, the number of particles (N L , N R ) that are trapped by central points can be obtained. This process is iterated until (N L , N R ) become constant numbers. Smashing process is repeated by changing σ L and σ R , randomly

  15. Two-step estimation for inhomogeneous spatial point processes

    DEFF Research Database (Denmark)

    Waagepetersen, Rasmus; Guan, Yongtao

    2009-01-01

    The paper is concerned with parameter estimation for inhomogeneous spatial point processes with a regression model for the intensity function and tractable second-order properties (K-function). Regression parameters are estimated by using a Poisson likelihood score estimating function and in the ...... and in the second step minimum contrast estimation is applied for the residual clustering parameters. Asymptotic normality of parameter estimates is established under certain mixing conditions and we exemplify how the results may be applied in ecological studies of rainforests....

  16. Dense range images from sparse point clouds using multi-scale processing

    NARCIS (Netherlands)

    Do, Q.L.; Ma, L.; With, de P.H.N.

    2013-01-01

    Multi-modal data processing based on visual and depth/range images has become relevant in computer vision for 3D reconstruction applications such as city modeling, robot navigation etc. In this paper, we generate highaccuracy dense range images from sparse point clouds to facilitate such

  17. TUNNEL POINT CLOUD FILTERING METHOD BASED ON ELLIPTIC CYLINDRICAL MODEL

    Directory of Open Access Journals (Sweden)

    N. Zhu

    2016-06-01

    Full Text Available The large number of bolts and screws that attached to the subway shield ring plates, along with the great amount of accessories of metal stents and electrical equipments mounted on the tunnel walls, make the laser point cloud data include lots of non-tunnel section points (hereinafter referred to as non-points, therefore affecting the accuracy for modeling and deformation monitoring. This paper proposed a filtering method for the point cloud based on the elliptic cylindrical model. The original laser point cloud data was firstly projected onto a horizontal plane, and a searching algorithm was given to extract the edging points of both sides, which were used further to fit the tunnel central axis. Along the axis the point cloud was segmented regionally, and then fitted as smooth elliptic cylindrical surface by means of iteration. This processing enabled the automatic filtering of those inner wall non-points. Experiments of two groups showed coincident results, that the elliptic cylindrical model based method could effectively filter out the non-points, and meet the accuracy requirements for subway deformation monitoring. The method provides a new mode for the periodic monitoring of tunnel sections all-around deformation in subways routine operation and maintenance.

  18. Zirconium - ab initio modelling of point defects diffusion

    International Nuclear Information System (INIS)

    Gasca, Petrica

    2010-01-01

    Zirconium is the main element of the cladding found in pressurized water reactors, under an alloy form. Under irradiation, the cladding elongate significantly, phenomena attributed to the vacancy dislocation loops growth in the basal planes of the hexagonal compact structure. The understanding of the atomic scale mechanisms originating this process motivated this work. Using the ab initio atomic modeling technique we studied the structure and mobility of point defects in Zirconium. This led us to find four interstitial point defects with formation energies in an interval of 0.11 eV. The migration paths study allowed the discovery of activation energies, used as entry parameters for a kinetic Monte Carlo code. This code was developed for calculating the diffusion coefficient of the interstitial point defect. Our results suggest a migration parallel to the basal plane twice as fast as one parallel to the c direction, with an activation energy of 0.08 eV, independent of the direction. The vacancy diffusion coefficient, estimated with a two-jump model, is also anisotropic, with a faster process in the basal planes than perpendicular to them. Hydrogen influence on the vacancy dislocation loops nucleation was also studied, due to recent experimental observations of cladding growth acceleration in the presence of this element [fr

  19. Variational approach for spatial point process intensity estimation

    DEFF Research Database (Denmark)

    Coeurjolly, Jean-Francois; Møller, Jesper

    is assumed to be of log-linear form β+θ⊤z(u) where z is a spatial covariate function and the focus is on estimating θ. The variational estimator is very simple to implement and quicker than alternative estimation procedures. We establish its strong consistency and asymptotic normality. We also discuss its...... finite-sample properties in comparison with the maximum first order composite likelihood estimator when considering various inhomogeneous spatial point process models and dimensions as well as settings were z is completely or only partially known....

  20. Point cloud processing for smart systems

    Directory of Open Access Journals (Sweden)

    Jaromír Landa

    2013-01-01

    Full Text Available High population as well as the economical tension emphasises the necessity of effective city management – from land use planning to urban green maintenance. The management effectiveness is based on precise knowledge of the city environment. Point clouds generated by mobile and terrestrial laser scanners provide precise data about objects in the scanner vicinity. From these data pieces the state of the roads, buildings, trees and other objects important for this decision-making process can be obtained. Generally, they can support the idea of “smart” or at least “smarter” cities.Unfortunately the point clouds do not provide this type of information automatically. It has to be extracted. This extraction is done by expert personnel or by object recognition software. As the point clouds can represent large areas (streets or even cities, usage of expert personnel to identify the required objects can be very time-consuming, therefore cost ineffective. Object recognition software allows us to detect and identify required objects semi-automatically or automatically.The first part of the article reviews and analyses the state of current art point cloud object recognition techniques. The following part presents common formats used for point cloud storage and frequently used software tools for point cloud processing. Further, a method for extraction of geospatial information about detected objects is proposed. Therefore, the method can be used not only to recognize the existence and shape of certain objects, but also to retrieve their geospatial properties. These objects can be later directly used in various GIS systems for further analyses.

  1. Point kinetics modeling

    International Nuclear Information System (INIS)

    Kimpland, R.H.

    1996-01-01

    A normalized form of the point kinetics equations, a prompt jump approximation, and the Nordheim-Fuchs model are used to model nuclear systems. Reactivity feedback mechanisms considered include volumetric expansion, thermal neutron temperature effect, Doppler effect and void formation. A sample problem of an excursion occurring in a plutonium solution accidentally formed in a glovebox is presented

  2. Robust non-rigid point set registration using student's-t mixture model.

    Directory of Open Access Journals (Sweden)

    Zhiyong Zhou

    Full Text Available The Student's-t mixture model, which is heavily tailed and more robust than the Gaussian mixture model, has recently received great attention on image processing. In this paper, we propose a robust non-rigid point set registration algorithm using the Student's-t mixture model. Specifically, first, we consider the alignment of two point sets as a probability density estimation problem and treat one point set as Student's-t mixture model centroids. Then, we fit the Student's-t mixture model centroids to the other point set which is treated as data. Finally, we get the closed-form solutions of registration parameters, leading to a computationally efficient registration algorithm. The proposed algorithm is especially effective for addressing the non-rigid point set registration problem when significant amounts of noise and outliers are present. Moreover, less registration parameters have to be set manually for our algorithm compared to the popular coherent points drift (CPD algorithm. We have compared our algorithm with other state-of-the-art registration algorithms on both 2D and 3D data with noise and outliers, where our non-rigid registration algorithm showed accurate results and outperformed the other algorithms.

  3. Bayesian inference for multivariate point processes observed at sparsely distributed times

    DEFF Research Database (Denmark)

    Rasmussen, Jakob Gulddahl; Møller, Jesper; Aukema, B.H.

    We consider statistical and computational aspects of simulation-based Bayesian inference for a multivariate point process which is only observed at sparsely distributed times. For specicity we consider a particular data set which has earlier been analyzed by a discrete time model involving unknown...... normalizing constants. We discuss the advantages and disadvantages of using continuous time processes compared to discrete time processes in the setting of the present paper as well as other spatial-temporal situations. Keywords: Bark beetle, conditional intensity, forest entomology, Markov chain Monte Carlo...

  4. Hazard rate model and statistical analysis of a compound point process

    Czech Academy of Sciences Publication Activity Database

    Volf, Petr

    2005-01-01

    Roč. 41, č. 6 (2005), s. 773-786 ISSN 0023-5954 R&D Projects: GA ČR(CZ) GA402/04/1294 Institutional research plan: CEZ:AV0Z10750506 Keywords : couting process * compound process * Cox regression model * intensity Subject RIV: BB - Applied Statistics, Operational Research Impact factor: 0.343, year: 2005

  5. Coupling aerosol-cloud-radiative processes in the WRF-Chem model: Investigating the radiative impact of elevated point sources

    Directory of Open Access Journals (Sweden)

    E. G. Chapman

    2009-02-01

    Full Text Available The local and regional influence of elevated point sources on summertime aerosol forcing and cloud-aerosol interactions in northeastern North America was investigated using the WRF-Chem community model. The direct effects of aerosols on incoming solar radiation were simulated using existing modules to relate aerosol sizes and chemical composition to aerosol optical properties. Indirect effects were simulated by adding a prognostic treatment of cloud droplet number and adding modules that activate aerosol particles to form cloud droplets, simulate aqueous-phase chemistry, and tie a two-moment treatment of cloud water (cloud water mass and cloud droplet number to precipitation and an existing radiation scheme. Fully interactive feedbacks thus were created within the modified model, with aerosols affecting cloud droplet number and cloud radiative properties, and clouds altering aerosol size and composition via aqueous processes, wet scavenging, and gas-phase-related photolytic processes. Comparisons of a baseline simulation with observations show that the model captured the general temporal cycle of aerosol optical depths (AODs and produced clouds of comparable thickness to observations at approximately the proper times and places. The model overpredicted SO2 mixing ratios and PM2.5 mass, but reproduced the range of observed SO2 to sulfate aerosol ratios, suggesting that atmospheric oxidation processes leading to aerosol sulfate formation are captured in the model. The baseline simulation was compared to a sensitivity simulation in which all emissions at model levels above the surface layer were set to zero, thus removing stack emissions. Instantaneous, site-specific differences for aerosol and cloud related properties between the two simulations could be quite large, as removing above-surface emission sources influenced when and where clouds formed within the modeling domain. When summed spatially over the finest

  6. A logistic regression estimating function for spatial Gibbs point processes

    DEFF Research Database (Denmark)

    Baddeley, Adrian; Coeurjolly, Jean-François; Rubak, Ege

    We propose a computationally efficient logistic regression estimating function for spatial Gibbs point processes. The sample points for the logistic regression consist of the observed point pattern together with a random pattern of dummy points. The estimating function is closely related to the p......We propose a computationally efficient logistic regression estimating function for spatial Gibbs point processes. The sample points for the logistic regression consist of the observed point pattern together with a random pattern of dummy points. The estimating function is closely related...

  7. Point process models for spatio-temporal distance sampling data from a large-scale survey of blue whales

    KAUST Repository

    Yuan, Yuan; Bachl, Fabian E.; Lindgren, Finn; Borchers, David L.; Illian, Janine B.; Buckland, Stephen T.; Rue, Haavard; Gerrodette, Tim

    2017-01-01

    Distance sampling is a widely used method for estimating wildlife population abundance. The fact that conventional distance sampling methods are partly design-based constrains the spatial resolution at which animal density can be estimated using these methods. Estimates are usually obtained at survey stratum level. For an endangered species such as the blue whale, it is desirable to estimate density and abundance at a finer spatial scale than stratum. Temporal variation in the spatial structure is also important. We formulate the process generating distance sampling data as a thinned spatial point process and propose model-based inference using a spatial log-Gaussian Cox process. The method adopts a flexible stochastic partial differential equation (SPDE) approach to model spatial structure in density that is not accounted for by explanatory variables, and integrated nested Laplace approximation (INLA) for Bayesian inference. It allows simultaneous fitting of detection and density models and permits prediction of density at an arbitrarily fine scale. We estimate blue whale density in the Eastern Tropical Pacific Ocean from thirteen shipboard surveys conducted over 22 years. We find that higher blue whale density is associated with colder sea surface temperatures in space, and although there is some positive association between density and mean annual temperature, our estimates are consistent with no trend in density across years. Our analysis also indicates that there is substantial spatially structured variation in density that is not explained by available covariates.

  8. Point process models for spatio-temporal distance sampling data from a large-scale survey of blue whales

    KAUST Repository

    Yuan, Yuan

    2017-12-28

    Distance sampling is a widely used method for estimating wildlife population abundance. The fact that conventional distance sampling methods are partly design-based constrains the spatial resolution at which animal density can be estimated using these methods. Estimates are usually obtained at survey stratum level. For an endangered species such as the blue whale, it is desirable to estimate density and abundance at a finer spatial scale than stratum. Temporal variation in the spatial structure is also important. We formulate the process generating distance sampling data as a thinned spatial point process and propose model-based inference using a spatial log-Gaussian Cox process. The method adopts a flexible stochastic partial differential equation (SPDE) approach to model spatial structure in density that is not accounted for by explanatory variables, and integrated nested Laplace approximation (INLA) for Bayesian inference. It allows simultaneous fitting of detection and density models and permits prediction of density at an arbitrarily fine scale. We estimate blue whale density in the Eastern Tropical Pacific Ocean from thirteen shipboard surveys conducted over 22 years. We find that higher blue whale density is associated with colder sea surface temperatures in space, and although there is some positive association between density and mean annual temperature, our estimates are consistent with no trend in density across years. Our analysis also indicates that there is substantial spatially structured variation in density that is not explained by available covariates.

  9. 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.

  10. 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.

  11. Predicting wildfire occurrence distribution with spatial point process models and its uncertainty assessment: a case study in the Lake Tahoe Basin, USA

    Science.gov (United States)

    Jian Yang; Peter J. Weisberg; Thomas E. Dilts; E. Louise Loudermilk; Robert M. Scheller; Alison Stanton; Carl Skinner

    2015-01-01

    Strategic fire and fuel management planning benefits from detailed understanding of how wildfire occurrences are distributed spatially under current climate, and from predictive models of future wildfire occurrence given climate change scenarios. In this study, we fitted historical wildfire occurrence data from 1986 to 2009 to a suite of spatial point process (SPP)...

  12. Effect of processing conditions on oil point pressure of moringa oleifera seed.

    Science.gov (United States)

    Aviara, N A; Musa, W B; Owolarafe, O K; Ogunsina, B S; Oluwole, F A

    2015-07-01

    Seed oil expression is an important economic venture in rural Nigeria. The traditional techniques of carrying out the operation is not only energy sapping and time consuming but also wasteful. In order to reduce the tedium involved in the expression of oil from moringa oleifera seed and develop efficient equipment for carrying out the operation, the oil point pressure of the seed was determined under different processing conditions using a laboratory press. The processing conditions employed were moisture content (4.78, 6.00, 8.00 and 10.00 % wet basis), heating temperature (50, 70, 85 and 100 °C) and heating time (15, 20, 25 and 30 min). Results showed that the oil point pressure increased with increase in seed moisture content, but decreased with increase in heating temperature and heating time within the above ranges. Highest oil point pressure value of 1.1239 MPa was obtained at the processing conditions of 10.00 % moisture content, 50 °C heating temperature and 15 min heating time. The lowest oil point pressure obtained was 0.3164 MPa and it occurred at the moisture content of 4.78 %, heating temperature of 100 °C and heating time of 30 min. Analysis of Variance (ANOVA) showed that all the processing variables and their interactions had significant effect on the oil point pressure of moringa oleifera seed at 1 % level of significance. This was further demonstrated using Response Surface Methodology (RSM). Tukey's test and Duncan's Multiple Range Analysis successfully separated the means and a multiple regression equation was used to express the relationship existing between the oil point pressure of moringa oleifera seed and its moisture content, processing temperature, heating time and their interactions. The model yielded coefficients that enabled the oil point pressure of the seed to be predicted with very high coefficient of determination.

  13. A tutorial on Palm distributions for spatial point processes

    DEFF Research Database (Denmark)

    Coeurjolly, Jean-Francois; Møller, Jesper; Waagepetersen, Rasmus Plenge

    2017-01-01

    This tutorial provides an introduction to Palm distributions for spatial point processes. Initially, in the context of finite point processes, we give an explicit definition of Palm distributions in terms of their density functions. Then we review Palm distributions in the general case. Finally, we...

  14. Modelling aggregation on the large scale and regularity on the small scale in spatial point pattern datasets

    DEFF Research Database (Denmark)

    Lavancier, Frédéric; Møller, Jesper

    We consider a dependent thinning of a regular point process with the aim of obtaining aggregation on the large scale and regularity on the small scale in the resulting target point process of retained points. Various parametric models for the underlying processes are suggested and the properties...

  15. Properties of spatial Cox process models

    DEFF Research Database (Denmark)

    Møller, Jesper

    Probabilistic properties of Cox processes of relevance for statistical modelling and inference are studied. Particularly, we study the most important classes of Cox processes, including log Gaussian Cox processes, shot noise Cox processes, and permanent Cox processes. We consider moment properties...... and point process operations such as thinning, displacements, and superpositioning. We also discuss how to simulate specific Cox processes....

  16. Elastic-plastic adhesive contact of rough surfaces using n-point asperity model

    International Nuclear Information System (INIS)

    Sahoo, Prasanta; Mitra, Anirban; Saha, Kashinath

    2009-01-01

    This study considers an analysis of the elastic-plastic contact of rough surfaces in the presence of adhesion using an n-point asperity model. The multiple-point asperity model, developed by Hariri et al (2006 Trans ASME: J. Tribol. 128 505-14) is integrated into the elastic-plastic adhesive contact model developed by Roy Chowdhury and Ghosh (1994 Wear 174 9-19). This n-point asperity model differs from the conventional Greenwood and Williamson model (1966 Proc. R. Soc. Lond. A 295 300-19) in considering the asperities not as fixed entities but as those that change through the contact process, and hence it represents the asperities in a more realistic manner. The newly defined adhesion index and plasticity index defined for the n-point asperity model are used to consider the different conditions that arise because of varying load, surface and material parameters. A comparison between the load-separation behaviour of the new model and the conventional one shows a significant difference between the two depending on combinations of mean separation, adhesion index and plasticity index.

  17. The Automation of Nowcast Model Assessment Processes

    Science.gov (United States)

    2016-09-01

    secondly, provide modelers with the information needed to understand the model errors and how their algorithm changes might mitigate these errors. In...by ARL modelers. 2. Development Environment The automation of Point-Stat processes (i.e., PSA) was developed using Python 3.5.* Python was selected...because it is easy to use, widely used for scripting, and satisfies all the requirements to automate the implementation of the Point-Stat tool. In

  18. Point processes and the position distribution of infinite boson systems

    International Nuclear Information System (INIS)

    Fichtner, K.H.; Freudenberg, W.

    1987-01-01

    It is shown that to each locally normal state of a boson system one can associate a point process that can be interpreted as the position distribution of the state. The point process contains all information one can get by position measurements and is determined by the latter. On the other hand, to each so-called Σ/sup c/-point process Q they relate a locally normal state with position distribution Q

  19. 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.

  20. Nuclear binding around the RP-process waiting points $^{68}$Se and $^{72}$Kr

    CERN Multimedia

    2002-01-01

    Encouraged by the success of mass determinations of nuclei close to the Z=N line performed at ISOLTRAP during the year 2000 and of the recent decay spectroscopy studies on neutron-deficient Kr isotopes (IS351 collaboration), we aim to measure masses and proton separation energies of the bottleneck nuclei defining the flow of the astrophysical rp-process beyond A$\\sim$70. In detail, the program includes mass measurements of the rp-process waiting point nuclei $^{68}$Se and $^{72}$Kr and determination of proton separation energies of the proton-unbound $^{69}$Br and $^{73}$Rb via $\\beta$-decays of $^{69}$Kr and $^{73}$Sr, respectively. The aim of the project is to complete the experimental database for astrophysical network calculations and for the liquid-drop type of mass models typically used in the modelling of the astrophysical rp process in the region. The first beamtime is scheduled for the August 2001 and the aim is to measure the absolute mass of the waiting-point nucleus $^{72}$Kr.

  1. A new statistical scission-point model fed with microscopic ingredients to predict fission fragments distributions; Developpement d'un nouveau modele de point de scission base sur des ingredients microscopiques

    Energy Technology Data Exchange (ETDEWEB)

    Heinrich, S

    2006-07-01

    Nucleus fission process is a very complex phenomenon and, even nowadays, no realistic models describing the overall process are available. The work presented here deals with a theoretical description of fission fragments distributions in mass, charge, energy and deformation. We have reconsidered and updated the B.D. Wilking Scission Point model. Our purpose was to test if this statistic model applied at the scission point and by introducing new results of modern microscopic calculations allows to describe quantitatively the fission fragments distributions. We calculate the surface energy available at the scission point as a function of the fragments deformations. This surface is obtained from a Hartree Fock Bogoliubov microscopic calculation which guarantee a realistic description of the potential dependence on the deformation for each fragment. The statistic balance is described by the level densities of the fragment. We have tried to avoid as much as possible the input of empirical parameters in the model. Our only parameter, the distance between each fragment at the scission point, is discussed by comparison with scission configuration obtained from full dynamical microscopic calculations. Also, the comparison between our results and experimental data is very satisfying and allow us to discuss the success and limitations of our approach. We finally proposed ideas to improve the model, in particular by applying dynamical corrections. (author)

  2. Extreme values, regular variation and point processes

    CERN Document Server

    Resnick, Sidney I

    1987-01-01

    Extremes Values, Regular Variation and Point Processes is a readable and efficient account of the fundamental mathematical and stochastic process techniques needed to study the behavior of extreme values of phenomena based on independent and identically distributed random variables and vectors It presents a coherent treatment of the distributional and sample path fundamental properties of extremes and records It emphasizes the core primacy of three topics necessary for understanding extremes the analytical theory of regularly varying functions; the probabilistic theory of point processes and random measures; and the link to asymptotic distribution approximations provided by the theory of weak convergence of probability measures in metric spaces The book is self-contained and requires an introductory measure-theoretic course in probability as a prerequisite Almost all sections have an extensive list of exercises which extend developments in the text, offer alternate approaches, test mastery and provide for enj...

  3. 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.

  4. 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

  5. Analysis of the stochastic channel model by Saleh & Valenzuela via the theory of point processes

    DEFF Research Database (Denmark)

    Jakobsen, Morten Lomholt; Pedersen, Troels; Fleury, Bernard Henri

    2012-01-01

    and underlying features, like the intensity function of the component delays and the delaypower intensity. The flexibility and clarity of the mathematical instruments utilized to obtain these results lead us to conjecture that the theory of spatial point processes provides a unifying mathematical framework...

  6. ON THE ESTIMATION OF DISTANCE DISTRIBUTION FUNCTIONS FOR POINT PROCESSES AND RANDOM SETS

    Directory of Open Access Journals (Sweden)

    Dietrich Stoyan

    2011-05-01

    Full Text Available This paper discusses various estimators for the nearest neighbour distance distribution function D of a stationary point process and for the quadratic contact distribution function Hq of a stationary random closed set. It recommends the use of Hanisch's estimator of D, which is of Horvitz-Thompson type, and the minussampling estimator of Hq. This recommendation is based on simulations for Poisson processes and Boolean models.

  7. Point process-based modeling of multiple debris flow landslides using INLA: an application to the 2009 Messina disaster

    KAUST Repository

    Lombardo, Luigi

    2018-02-13

    We develop a stochastic modeling approach based on spatial point processes of log-Gaussian Cox type for a collection of around 5000 landslide events provoked by a precipitation trigger in Sicily, Italy. Through the embedding into a hierarchical Bayesian estimation framework, we can use the integrated nested Laplace approximation methodology to make inference and obtain the posterior estimates of spatially distributed covariate and random effects. Several mapping units are useful to partition a given study area in landslide prediction studies. These units hierarchically subdivide the geographic space from the highest grid-based resolution to the stronger morphodynamic-oriented slope units. Here we integrate both mapping units into a single hierarchical model, by treating the landslide triggering locations as a random point pattern. This approach diverges fundamentally from the unanimously used presence–absence structure for areal units since we focus on modeling the expected landslide count jointly within the two mapping units. Predicting this landslide intensity provides more detailed and complete information as compared to the classically used susceptibility mapping approach based on relative probabilities. To illustrate the model’s versatility, we compute absolute probability maps of landslide occurrences and check their predictive power over space. While the landslide community typically produces spatial predictive models for landslides only in the sense that covariates are spatially distributed, no actual spatial dependence has been explicitly integrated so far. Our novel approach features a spatial latent effect defined at the slope unit level, allowing us to assess the spatial influence that remains unexplained by the covariates in the model. For rainfall-induced landslides in regions where the raingauge network is not sufficient to capture the spatial distribution of the triggering precipitation event, this latent effect provides valuable imaging support

  8. Pointo - a Low Cost Solution to Point Cloud Processing

    Science.gov (United States)

    Houshiar, H.; Winkler, S.

    2017-11-01

    With advance in technology access to data especially 3D point cloud data becomes more and more an everyday task. 3D point clouds are usually captured with very expensive tools such as 3D laser scanners or very time consuming methods such as photogrammetry. Most of the available softwares for 3D point cloud processing are designed for experts and specialists in this field and are usually very large software packages containing variety of methods and tools. This results in softwares that are usually very expensive to acquire and also very difficult to use. Difficulty of use is caused by complicated user interfaces that is required to accommodate a large list of features. The aim of these complex softwares is to provide a powerful tool for a specific group of specialist. However they are not necessary required by the majority of the up coming average users of point clouds. In addition to complexity and high costs of these softwares they generally rely on expensive and modern hardware and only compatible with one specific operating system. Many point cloud customers are not point cloud processing experts or willing to spend the high acquisition costs of these expensive softwares and hardwares. In this paper we introduce a solution for low cost point cloud processing. Our approach is designed to accommodate the needs of the average point cloud user. To reduce the cost and complexity of software our approach focuses on one functionality at a time in contrast with most available softwares and tools that aim to solve as many problems as possible at the same time. Our simple and user oriented design improve the user experience and empower us to optimize our methods for creation of an efficient software. In this paper we introduce Pointo family as a series of connected softwares to provide easy to use tools with simple design for different point cloud processing requirements. PointoVIEWER and PointoCAD are introduced as the first components of the Pointo family to provide a

  9. Bayesian Estimation Of Shift Point In Poisson Model Under Asymmetric Loss Functions

    Directory of Open Access Journals (Sweden)

    uma srivastava

    2012-01-01

    Full Text Available The paper deals with estimating  shift point which occurs in any sequence of independent observations  of Poisson model in statistical process control. This shift point occurs in the sequence when  i.e. m  life data are observed. The Bayes estimator on shift point 'm' and before and after shift process means are derived for symmetric and asymmetric loss functions under informative and non informative priors. The sensitivity analysis of Bayes estimators are carried out by simulation and numerical comparisons with  R-programming. The results shows the effectiveness of shift in sequence of Poisson disribution .

  10. A scalable and multi-purpose point cloud server (PCS) for easier and faster point cloud data management and processing

    Science.gov (United States)

    Cura, Rémi; Perret, Julien; Paparoditis, Nicolas

    2017-05-01

    In addition to more traditional geographical data such as images (rasters) and vectors, point cloud data are becoming increasingly available. Such data are appreciated for their precision and true three-Dimensional (3D) nature. However, managing point clouds can be difficult due to scaling problems and specificities of this data type. Several methods exist but are usually fairly specialised and solve only one aspect of the management problem. In this work, we propose a comprehensive and efficient point cloud management system based on a database server that works on groups of points (patches) rather than individual points. This system is specifically designed to cover the basic needs of point cloud users: fast loading, compressed storage, powerful patch and point filtering, easy data access and exporting, and integrated processing. Moreover, the proposed system fully integrates metadata (like sensor position) and can conjointly use point clouds with other geospatial data, such as images, vectors, topology and other point clouds. Point cloud (parallel) processing can be done in-base with fast prototyping capabilities. Lastly, the system is built on open source technologies; therefore it can be easily extended and customised. We test the proposed system with several billion points obtained from Lidar (aerial and terrestrial) and stereo-vision. We demonstrate loading speeds in the ˜50 million pts/h per process range, transparent-for-user and greater than 2 to 4:1 compression ratio, patch filtering in the 0.1 to 1 s range, and output in the 0.1 million pts/s per process range, along with classical processing methods, such as object detection.

  11. Poisson point processes imaging, tracking, and sensing

    CERN Document Server

    Streit, Roy L

    2010-01-01

    This overview of non-homogeneous and multidimensional Poisson point processes and their applications features mathematical tools and applications from emission- and transmission-computed tomography to multiple target tracking and distributed sensor detection.

  12. Model plant Key Measurement Points

    International Nuclear Information System (INIS)

    Schneider, R.A.

    1984-01-01

    For IAEA safeguards a Key Measurement Point is defined as the location where nuclear material appears in such a form that it may be measured to determine material flow or inventory. This presentation describes in an introductory manner the key measurement points and associated measurements for the model plant used in this training course

  13. Reconstruction of Consistent 3d CAD Models from Point Cloud Data Using a Priori CAD Models

    Science.gov (United States)

    Bey, A.; Chaine, R.; Marc, R.; Thibault, G.; Akkouche, S.

    2011-09-01

    We address the reconstruction of 3D CAD models from point cloud data acquired in industrial environments, using a pre-existing 3D model as an initial estimate of the scene to be processed. Indeed, this prior knowledge can be used to drive the reconstruction so as to generate an accurate 3D model matching the point cloud. We more particularly focus our work on the cylindrical parts of the 3D models. We propose to state the problem in a probabilistic framework: we have to search for the 3D model which maximizes some probability taking several constraints into account, such as the relevancy with respect to the point cloud and the a priori 3D model, and the consistency of the reconstructed model. The resulting optimization problem can then be handled using a stochastic exploration of the solution space, based on the random insertion of elements in the configuration under construction, coupled with a greedy management of the conflicts which efficiently improves the configuration at each step. We show that this approach provides reliable reconstructed 3D models by presenting some results on industrial data sets.

  14. Distinguishing different types of inhomogeneity in Neyman-Scott point processes

    Czech Academy of Sciences Publication Activity Database

    Mrkvička, Tomáš

    2014-01-01

    Roč. 16, č. 2 (2014), s. 385-395 ISSN 1387-5841 Institutional support: RVO:60077344 Keywords : clustering * growing clusters * inhomogeneous cluster centers * inhomogeneous point process * location dependent scaling * Neyman-Scott point process Subject RIV: BA - General Mathematics Impact factor: 0.913, year: 2014

  15. 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

  16. System identification to characterize human use of ethanol based on generative point-process models of video games with ethanol rewards.

    Science.gov (United States)

    Ozil, Ipek; Plawecki, Martin H; Doerschuk, Peter C; O'Connor, Sean J

    2011-01-01

    The influence of family history and genetics on the risk for the development of abuse or dependence is a major theme in alcoholism research. Recent research have used endophenotypes and behavioral paradigms to help detect further genetic contributions to this disease. Electronic tasks, essentially video games, which provide alcohol as a reward in controlled environments and with specified exposures have been developed to explore some of the behavioral and subjective characteristics of individuals with or at risk for alcohol substance use disorders. A generative model (containing parameters with unknown values) of a simple game involving a progressive work paradigm is described along with the associated point process signal processing that allows system identification of the model. The system is demonstrated on human subject data. The same human subject completing the task under different circumstances, e.g., with larger and smaller alcohol reward values, is assigned different parameter values. Potential meanings of the different parameter values are described.

  17. Room acoustics modeling using a point-cloud representation of the room geometry

    DEFF Research Database (Denmark)

    Markovic, Milos; Olesen, Søren Krarup; Hammershøi, Dorte

    2013-01-01

    Room acoustics modeling is usually based on the room geometry that is parametrically described prior to a sound transmission calculation. This is a highly room-specific task and rather time consuming if a complex geometry is to be described. Here, a run time generic method for an arbitrary room...... geometry acquisition is presented. The method exploits a depth sensor of the Kinect device that provides a point based information of a scanned room interior. After post-processing of the Kinect output data, a 3D point-cloud model of the room is obtained. Sound transmission between two selected points...... level of user immersion by a real time acoustical simulation of a dynamic scenes....

  18. Some properties of point processes in statistical optics

    International Nuclear Information System (INIS)

    Picinbono, B.; Bendjaballah, C.

    2010-01-01

    The analysis of the statistical properties of the point process (PP) of photon detection times can be used to determine whether or not an optical field is classical, in the sense that its statistical description does not require the methods of quantum optics. This determination is, however, more difficult than ordinarily admitted and the first aim of this paper is to illustrate this point by using some results of the PP theory. For example, it is well known that the analysis of the photodetection of classical fields exhibits the so-called bunching effect. But this property alone cannot be used to decide the nature of a given optical field. Indeed, we have presented examples of point processes for which a bunching effect appears and yet they cannot be obtained from a classical field. These examples are illustrated by computer simulations. Similarly, it is often admitted that for fields with very low light intensity the bunching or antibunching can be described by using the statistical properties of the distance between successive events of the point process, which simplifies the experimental procedure. We have shown that, while this property is valid for classical PPs, it has no reason to be true for nonclassical PPs, and we have presented some examples of this situation also illustrated by computer simulations.

  19. Exact 2-point function in Hermitian matrix model

    International Nuclear Information System (INIS)

    Morozov, A.; Shakirov, Sh.

    2009-01-01

    J. Harer and D. Zagier have found a strikingly simple generating function [1,2] for exact (all-genera) 1-point correlators in the Gaussian Hermitian matrix model. In this paper we generalize their result to 2-point correlators, using Toda integrability of the model. Remarkably, this exact 2-point correlation function turns out to be an elementary function - arctangent. Relation to the standard 2-point resolvents is pointed out. Some attempts of generalization to 3-point and higher functions are described.

  20. Probabilistic safety assessment and optimal control of hazardous technological systems. A marked point process approach

    International Nuclear Information System (INIS)

    Holmberg, J.

    1997-04-01

    The thesis models risk management as an optimal control problem for a stochastic process. The approach classes the decisions made by management into three categories according to the control methods of a point process: (1) planned process lifetime, (2) modification of the design, and (3) operational decisions. The approach is used for optimization of plant shutdown criteria and surveillance test strategies of a hypothetical nuclear power plant

  1. MATHEMATICAL MODELING OF AC ELECTRIC POINT MOTOR

    Directory of Open Access Journals (Sweden)

    S. YU. Buryak

    2014-03-01

    Full Text Available Purpose. In order to ensure reliability, security, and the most important the continuity of the transportation process, it is necessary to develop, implement, and then improve the automated methods of diagnostic mechanisms, devices and rail transport systems. Only systems that operate in real time mode and transmit data on the instantaneous state of the control objects can timely detect any faults and thus provide additional time for their correction by railway employees. Turnouts are one of the most important and responsible components, and therefore require the development and implementation of such diagnostics system.Methodology. Achieving the goal of monitoring and control of railway automation objects in real time is possible only with the use of an automated process of the objects state diagnosing. For this we need to know the diagnostic features of a control object, which determine its state at any given time. The most rational way of remote diagnostics is the shape and current spectrum analysis that flows in the power circuits of railway automatics. Turnouts include electric motors, which are powered by electric circuits, and the shape of the current curve depends on both the condition of the electric motor, and the conditions of the turnout maintenance. Findings. For the research and analysis of AC electric point motor it was developed its mathematical model. The calculation of parameters and interdependencies between the main factors affecting the operation of the asynchronous machine was conducted. The results of the model operation in the form of time dependences of the waveform curves of current on the load on engine shaft were obtained. Originality. During simulation the model of AC electric point motor, which satisfies the conditions of adequacy was built. Practical value. On the basis of the constructed model we can study the AC motor in various mode of operation, record and analyze current curve, as a response to various changes

  2. A J–function for inhomogeneous point processes

    NARCIS (Netherlands)

    M.N.M. van Lieshout (Marie-Colette)

    2010-01-01

    htmlabstractWe propose new summary statistics for intensity-reweighted moment stationary point processes that generalise the well known J-, empty space, and nearest-neighbour distance dis- tribution functions, represent them in terms of generating functionals and conditional intensities, and relate

  3. Topobathymetric LiDAR point cloud processing and landform classification in a tidal environment

    Science.gov (United States)

    Skovgaard Andersen, Mikkel; Al-Hamdani, Zyad; Steinbacher, Frank; Rolighed Larsen, Laurids; Brandbyge Ernstsen, Verner

    2017-04-01

    Historically it has been difficult to create high resolution Digital Elevation Models (DEMs) in land-water transition zones due to shallow water depth and often challenging environmental conditions. This gap of information has been reflected as a "white ribbon" with no data in the land-water transition zone. In recent years, the technology of airborne topobathymetric Light Detection and Ranging (LiDAR) has proven capable of filling out the gap by simultaneously capturing topographic and bathymetric elevation information, using only a single green laser. We collected green LiDAR point cloud data in the Knudedyb tidal inlet system in the Danish Wadden Sea in spring 2014. Creating a DEM from a point cloud requires the general processing steps of data filtering, water surface detection and refraction correction. However, there is no transparent and reproducible method for processing green LiDAR data into a DEM, specifically regarding the procedure of water surface detection and modelling. We developed a step-by-step procedure for creating a DEM from raw green LiDAR point cloud data, including a procedure for making a Digital Water Surface Model (DWSM) (see Andersen et al., 2017). Two different classification analyses were applied to the high resolution DEM: A geomorphometric and a morphological classification, respectively. The classification methods were originally developed for a small test area; but in this work, we have used the classification methods to classify the complete Knudedyb tidal inlet system. References Andersen MS, Gergely Á, Al-Hamdani Z, Steinbacher F, Larsen LR, Ernstsen VB (2017). Processing and performance of topobathymetric lidar data for geomorphometric and morphological classification in a high-energy tidal environment. Hydrol. Earth Syst. Sci., 21: 43-63, doi:10.5194/hess-21-43-2017. Acknowledgements This work was funded by the Danish Council for Independent Research | Natural Sciences through the project "Process-based understanding and

  4. 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...

  5. Analysis of relationship between registration performance of point cloud statistical model and generation method of corresponding points

    International Nuclear Information System (INIS)

    Yamaoka, Naoto; Watanabe, Wataru; Hontani, Hidekata

    2010-01-01

    Most of the time when we construct statistical point cloud model, we need to calculate the corresponding points. Constructed statistical model will not be the same if we use different types of method to calculate the corresponding points. This article proposes the effect to statistical model of human organ made by different types of method to calculate the corresponding points. We validated the performance of statistical model by registering a surface of an organ in a 3D medical image. We compare two methods to calculate corresponding points. The first, the 'Generalized Multi-Dimensional Scaling (GMDS)', determines the corresponding points by the shapes of two curved surfaces. The second approach, the 'Entropy-based Particle system', chooses corresponding points by calculating a number of curved surfaces statistically. By these methods we construct the statistical models and using these models we conducted registration with the medical image. For the estimation, we use non-parametric belief propagation and this method estimates not only the position of the organ but also the probability density of the organ position. We evaluate how the two different types of method that calculates corresponding points affects the statistical model by change in probability density of each points. (author)

  6. Statistical representation of a spray as a point process

    International Nuclear Information System (INIS)

    Subramaniam, S.

    2000-01-01

    The statistical representation of a spray as a finite point process is investigated. One objective is to develop a better understanding of how single-point statistical information contained in descriptions such as the droplet distribution function (ddf), relates to the probability density functions (pdfs) associated with the droplets themselves. Single-point statistical information contained in the droplet distribution function (ddf) is shown to be related to a sequence of single surrogate-droplet pdfs, which are in general different from the physical single-droplet pdfs. It is shown that the ddf contains less information than the fundamental single-point statistical representation of the spray, which is also described. The analysis shows which events associated with the ensemble of spray droplets can be characterized by the ddf, and which cannot. The implications of these findings for the ddf approach to spray modeling are discussed. The results of this study also have important consequences for the initialization and evolution of direct numerical simulations (DNS) of multiphase flows, which are usually initialized on the basis of single-point statistics such as the droplet number density in physical space. If multiphase DNS are initialized in this way, this implies that even the initial representation contains certain implicit assumptions concerning the complete ensemble of realizations, which are invalid for general multiphase flows. Also the evolution of a DNS initialized in this manner is shown to be valid only if an as yet unproven commutation hypothesis holds true. Therefore, it is questionable to what extent DNS that are initialized in this manner constitute a direct simulation of the physical droplets. Implications of these findings for large eddy simulations of multiphase flows are also discussed. (c) 2000 American Institute of Physics

  7. A customizable stochastic state point process filter (SSPPF) for neural spiking activity.

    Science.gov (United States)

    Xin, Yao; Li, Will X Y; Min, Biao; Han, Yan; Cheung, Ray C C

    2013-01-01

    Stochastic State Point Process Filter (SSPPF) is effective for adaptive signal processing. In particular, it has been successfully applied to neural signal coding/decoding in recent years. Recent work has proven its efficiency in non-parametric coefficients tracking in modeling of mammal nervous system. However, existing SSPPF has only been realized in commercial software platforms which limit their computational capability. In this paper, the first hardware architecture of SSPPF has been designed and successfully implemented on field-programmable gate array (FPGA), proving a more efficient means for coefficient tracking in a well-established generalized Laguerre-Volterra model for mammalian hippocampal spiking activity research. By exploring the intrinsic parallelism of the FPGA, the proposed architecture is able to process matrices or vectors with random size, and is efficiently scalable. Experimental result shows its superior performance comparing to the software implementation, while maintaining the numerical precision. This architecture can also be potentially utilized in the future hippocampal cognitive neural prosthesis design.

  8. IMAGE TO POINT CLOUD METHOD OF 3D-MODELING

    Directory of Open Access Journals (Sweden)

    A. G. Chibunichev

    2012-07-01

    Full Text Available This article describes the method of constructing 3D models of objects (buildings, monuments based on digital images and a point cloud obtained by terrestrial laser scanner. The first step is the automated determination of exterior orientation parameters of digital image. We have to find the corresponding points of the image and point cloud to provide this operation. Before the corresponding points searching quasi image of point cloud is generated. After that SIFT algorithm is applied to quasi image and real image. SIFT algorithm allows to find corresponding points. Exterior orientation parameters of image are calculated from corresponding points. The second step is construction of the vector object model. Vectorization is performed by operator of PC in an interactive mode using single image. Spatial coordinates of the model are calculated automatically by cloud points. In addition, there is automatic edge detection with interactive editing available. Edge detection is performed on point cloud and on image with subsequent identification of correct edges. Experimental studies of the method have demonstrated its efficiency in case of building facade modeling.

  9. Interior Point Methods on GPU with application to Model Predictive Control

    DEFF Research Database (Denmark)

    Gade-Nielsen, Nicolai Fog

    The goal of this thesis is to investigate the application of interior point methods to solve dynamical optimization problems, using a graphical processing unit (GPU) with a focus on problems arising in Model Predictice Control (MPC). Multi-core processors have been available for over ten years now...... software package called GPUOPT, available under the non-restrictive MIT license. GPUOPT includes includes a primal-dual interior-point method, which supports both the CPU and the GPU. It is implemented as multiple components, where the matrix operations and solver for the Newton directions is separated...

  10. Discrete Approximations of Determinantal Point Processes on Continuous Spaces: Tree Representations and Tail Triviality

    Science.gov (United States)

    Osada, Hirofumi; Osada, Shota

    2018-01-01

    We prove tail triviality of determinantal point processes μ on continuous spaces. Tail triviality has been proved for such processes only on discrete spaces, and hence we have generalized the result to continuous spaces. To do this, we construct tree representations, that is, discrete approximations of determinantal point processes enjoying a determinantal structure. There are many interesting examples of determinantal point processes on continuous spaces such as zero points of the hyperbolic Gaussian analytic function with Bergman kernel, and the thermodynamic limit of eigenvalues of Gaussian random matrices for Sine_2 , Airy_2 , Bessel_2 , and Ginibre point processes. Our main theorem proves all these point processes are tail trivial.

  11. Probabilistic safety assessment and optimal control of hazardous technological systems. A marked point process approach

    Energy Technology Data Exchange (ETDEWEB)

    Holmberg, J [VTT Automation, Espoo (Finland)

    1997-04-01

    The thesis models risk management as an optimal control problem for a stochastic process. The approach classes the decisions made by management into three categories according to the control methods of a point process: (1) planned process lifetime, (2) modification of the design, and (3) operational decisions. The approach is used for optimization of plant shutdown criteria and surveillance test strategies of a hypothetical nuclear power plant. 62 refs. The thesis includes also five previous publications by author.

  12. Process modeling and control applied to real-time monitoring of distillation processes by near-infrared spectroscopy.

    Science.gov (United States)

    de Oliveira, Rodrigo R; Pedroza, Ricardo H P; Sousa, A O; Lima, Kássio M G; de Juan, Anna

    2017-09-08

    A distillation device that acquires continuous and synchronized measurements of temperature, percentage of distilled fraction and NIR spectra has been designed for real-time monitoring of distillation processes. As a process model, synthetic commercial gasoline batches produced in Brazil, which contain mixtures of pure gasoline blended with ethanol have been analyzed. The information provided by this device, i.e., distillation curves and NIR spectra, has served as initial information for the proposal of new strategies of process modeling and multivariate statistical process control (MSPC). Process modeling based on PCA batch analysis provided global distillation trajectories, whereas multiset MCR-ALS analysis is proposed to obtain a component-wise characterization of the distillation evolution and distilled fractions. Distillation curves, NIR spectra or compressed NIR information under the form of PCA scores and MCR-ALS concentration profiles were tested as the seed information to build MSPC models. New on-line PCA-based MSPC approaches, some inspired on local rank exploratory methods for process analysis, are proposed and work as follows: a) MSPC based on individual process observation models, where multiple local PCA models are built considering the sole information in each observation point; b) Fixed Size Moving Window - MSPC, in which local PCA models are built considering a moving window of the current and few past observation points; and c) Evolving MSPC, where local PCA models are built with an increasing window of observations covering all points since the beginning of the process until the current observation. Performance of different approaches has been assessed in terms of sensitivity to fault detection and number of false alarms. The outcome of this work will be of general use to define strategies for on-line process monitoring and control and, in a more specific way, to improve quality control of petroleum derived fuels and other substances submitted

  13. Mixed-Poisson Point Process with Partially-Observed Covariates: Ecological Momentary Assessment of Smoking.

    Science.gov (United States)

    Neustifter, Benjamin; Rathbun, Stephen L; Shiffman, Saul

    2012-01-01

    Ecological Momentary Assessment is an emerging method of data collection in behavioral research that may be used to capture the times of repeated behavioral events on electronic devices, and information on subjects' psychological states through the electronic administration of questionnaires at times selected from a probability-based design as well as the event times. A method for fitting a mixed Poisson point process model is proposed for the impact of partially-observed, time-varying covariates on the timing of repeated behavioral events. A random frailty is included in the point-process intensity to describe variation among subjects in baseline rates of event occurrence. Covariate coefficients are estimated using estimating equations constructed by replacing the integrated intensity in the Poisson score equations with a design-unbiased estimator. An estimator is also proposed for the variance of the random frailties. Our estimators are robust in the sense that no model assumptions are made regarding the distribution of the time-varying covariates or the distribution of the random effects. However, subject effects are estimated under gamma frailties using an approximate hierarchical likelihood. The proposed approach is illustrated using smoking data.

  14. Critical Control Points in the Processing of Cassava Tuber for Ighu ...

    African Journals Online (AJOL)

    Determination of the critical control points in the processing of cassava tuber into Ighu was carried out. The critical control points were determined according to the Codex guidelines for the application of the HACCP system by conducting hazard analysis. Hazard analysis involved proper examination of each processing step ...

  15. Accuracy limit of rigid 3-point water models

    Science.gov (United States)

    Izadi, Saeed; Onufriev, Alexey V.

    2016-08-01

    Classical 3-point rigid water models are most widely used due to their computational efficiency. Recently, we introduced a new approach to constructing classical rigid water models [S. Izadi et al., J. Phys. Chem. Lett. 5, 3863 (2014)], which permits a virtually exhaustive search for globally optimal model parameters in the sub-space that is most relevant to the electrostatic properties of the water molecule in liquid phase. Here we apply the approach to develop a 3-point Optimal Point Charge (OPC3) water model. OPC3 is significantly more accurate than the commonly used water models of same class (TIP3P and SPCE) in reproducing a comprehensive set of liquid bulk properties, over a wide range of temperatures. Beyond bulk properties, we show that OPC3 predicts the intrinsic charge hydration asymmetry (CHA) of water — a characteristic dependence of hydration free energy on the sign of the solute charge — in very close agreement with experiment. Two other recent 3-point rigid water models, TIP3PFB and H2ODC, each developed by its own, completely different optimization method, approach the global accuracy optimum represented by OPC3 in both the parameter space and accuracy of bulk properties. Thus, we argue that an accuracy limit of practical 3-point rigid non-polarizable models has effectively been reached; remaining accuracy issues are discussed.

  16. Second-order analysis of structured inhomogeneous spatio-temporal point processes

    DEFF Research Database (Denmark)

    Møller, Jesper; Ghorbani, Mohammad

    Statistical methodology for spatio-temporal point processes is in its infancy. We consider second-order analysis based on pair correlation functions and K-functions for first general inhomogeneous spatio-temporal point processes and second inhomogeneous spatio-temporal Cox processes. Assuming...... spatio-temporal separability of the intensity function, we clarify different meanings of second-order spatio-temporal separability. One is second-order spatio-temporal independence and relates e.g. to log-Gaussian Cox processes with an additive covariance structure of the underlying spatio......-temporal Gaussian process. Another concerns shot-noise Cox processes with a separable spatio-temporal covariance density. We propose diagnostic procedures for checking hypotheses of second-order spatio-temporal separability, which we apply on simulated and real data (the UK 2001 epidemic foot and mouth disease data)....

  17. Fermentation process diagnosis using a mathematical model

    Energy Technology Data Exchange (ETDEWEB)

    Yerushalmi, L; Volesky, B; Votruba, J

    1988-09-01

    Intriguing physiology of a solvent-producing strain of Clostridium acetobutylicum led to the synthesis of a mathematical model of the acetone-butanol fermentation process. The model presented is capable of describing the process dynamics and the culture behavior during a standard and a substandard acetone-butanol fermentation. In addition to the process kinetic parameters, the model includes the culture physiological parameters, such as the cellular membrane permeability and the number of membrane sites for active transport of sugar. Computer process simulation studies for different culture conditions used the model, and quantitatively pointed out the importance of selected culture parameters that characterize the cell membrane behaviour and play an important role in the control of solvent synthesis by the cell. The theoretical predictions by the new model were confirmed by experimental determination of the cellular membrane permeability.

  18. Microbial profile and critical control points during processing of 'robo ...

    African Journals Online (AJOL)

    Microbial profile and critical control points during processing of 'robo' snack from ... the relevant critical control points especially in relation to raw materials and ... to the quality of the various raw ingredients used were the roasting using earthen

  19. A new statistical scission-point model fed with microscopic ingredients to predict fission fragments distributions

    International Nuclear Information System (INIS)

    Heinrich, S.

    2006-01-01

    Nucleus fission process is a very complex phenomenon and, even nowadays, no realistic models describing the overall process are available. The work presented here deals with a theoretical description of fission fragments distributions in mass, charge, energy and deformation. We have reconsidered and updated the B.D. Wilking Scission Point model. Our purpose was to test if this statistic model applied at the scission point and by introducing new results of modern microscopic calculations allows to describe quantitatively the fission fragments distributions. We calculate the surface energy available at the scission point as a function of the fragments deformations. This surface is obtained from a Hartree Fock Bogoliubov microscopic calculation which guarantee a realistic description of the potential dependence on the deformation for each fragment. The statistic balance is described by the level densities of the fragment. We have tried to avoid as much as possible the input of empirical parameters in the model. Our only parameter, the distance between each fragment at the scission point, is discussed by comparison with scission configuration obtained from full dynamical microscopic calculations. Also, the comparison between our results and experimental data is very satisfying and allow us to discuss the success and limitations of our approach. We finally proposed ideas to improve the model, in particular by applying dynamical corrections. (author)

  20. 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.

  1. Weak interaction rates for Kr and Sr waiting-point nuclei under rp-process conditions

    International Nuclear Information System (INIS)

    Sarriguren, P.

    2009-01-01

    Weak interaction rates are studied in neutron deficient Kr and Sr waiting-point isotopes in ranges of densities and temperatures relevant for the rp process. The nuclear structure is described within a microscopic model (deformed QRPA) that reproduces not only the half-lives but also the Gamow-Teller strength distributions recently measured. The various sensitivities of the decay rates to both density and temperature are discussed. Continuum electron capture is shown to contribute significantly to the weak rates at rp-process conditions.

  2. A Comparative Study of Applying Active-Set and Interior Point Methods in MPC for Controlling Nonlinear pH Process

    Directory of Open Access Journals (Sweden)

    Syam Syafiie

    2014-06-01

    Full Text Available A comparative study of Model Predictive Control (MPC using active-set method and interior point methods is proposed as a control technique for highly non-linear pH process. The process is a strong acid-strong base system. A strong acid of hydrochloric acid (HCl and a strong base of sodium hydroxide (NaOH with the presence of buffer solution sodium bicarbonate (NaHCO3 are used in a neutralization process flowing into reactor. The non-linear pH neutralization model governed in this process is presented by multi-linear models. Performance of both controllers is studied by evaluating its ability of set-point tracking and disturbance-rejection. Besides, the optimization time is compared between these two methods; both MPC shows the similar performance with no overshoot, offset, and oscillation. However, the conventional active-set method gives a shorter control action time for small scale optimization problem compared to MPC using IPM method for pH control.

  3. Equivalence of functional limit theorems for stationary point processes and their Palm distributions

    NARCIS (Netherlands)

    Nieuwenhuis, G.

    1989-01-01

    Let P be the distribution of a stationary point process on the real line and let P0 be its Palm distribution. In this paper we consider two types of functional limit theorems, those in terms of the number of points of the point process in (0, t] and those in terms of the location of the nth point

  4. Relationship between ammonia stomatal compensation point and nitrogen metabolism in arable crops: Current status of knowledge and potential modelling approaches

    International Nuclear Information System (INIS)

    Massad, Raia Silvia; Loubet, Benjamin; Tuzet, Andree; Cellier, Pierre

    2008-01-01

    The ammonia stomatal compensation point of plants is determined by leaf temperature, ammonium concentration ([NH 4 + ] apo ) and pH of the apoplastic solution. The later two depend on the adjacent cells metabolism and on leaf inputs and outputs through the xylem and phloem. Until now only empirical models have been designed to model the ammonia stomatal compensation point, except the model of Riedo et al. (2002. Coupling soil-plant-atmosphere exchange of ammonia with ecosystem functioning in grasslands. Ecological Modelling 158, 83-110), which represents the exchanges between the plant's nitrogen pools. The first step to model the ammonia stomatal compensation point is to adequately model [NH 4 + ] apo . This [NH 4 + ] apo has been studied experimentally, but there are currently no process-based quantitative models describing its relation to plant metabolism and environmental conditions. This study summarizes the processes involved in determining the ammonia stomatal compensation point at the leaf scale and qualitatively evaluates the ability of existing whole plant N and C models to include a model for [NH 4 + ] apo . - A model for ammonia stomatal compensation point at the leaf level scale was developed

  5. TARDEC FIXED HEEL POINT (FHP): DRIVER CAD ACCOMMODATION MODEL VERIFICATION REPORT

    Science.gov (United States)

    2017-11-09

    Public Release Disclaimer: Reference herein to any specific commercial company, product , process, or service by trade name, trademark, manufacturer , or...not actively engaged HSI until MSB or the Engineering Manufacturing and Development (EMD) Phase, resulting in significant design and cost changes...and shall not be used for advertising or product endorsement purposes. TARDEC Fixed Heel Point (FHP): Driver CAD Accommodation Model Verification

  6. Application of the nudged elastic band method to the point-to-point radio wave ray tracing in IRI modeled ionosphere

    Science.gov (United States)

    Nosikov, I. A.; Klimenko, M. V.; Bessarab, P. F.; Zhbankov, G. A.

    2017-07-01

    Point-to-point ray tracing is an important problem in many fields of science. While direct variational methods where some trajectory is transformed to an optimal one are routinely used in calculations of pathways of seismic waves, chemical reactions, diffusion processes, etc., this approach is not widely known in ionospheric point-to-point ray tracing. We apply the Nudged Elastic Band (NEB) method to a radio wave propagation problem. In the NEB method, a chain of points which gives a discrete representation of the radio wave ray is adjusted iteratively to an optimal configuration satisfying the Fermat's principle, while the endpoints of the trajectory are kept fixed according to the boundary conditions. Transverse displacements define the radio ray trajectory, while springs between the points control their distribution along the ray. The method is applied to a study of point-to-point ionospheric ray tracing, where the propagation medium is obtained with the International Reference Ionosphere model taking into account traveling ionospheric disturbances. A 2-dimensional representation of the optical path functional is developed and used to gain insight into the fundamental difference between high and low rays. We conclude that high and low rays are minima and saddle points of the optical path functional, respectively.

  7. Two-point model for divertor transport

    International Nuclear Information System (INIS)

    Galambos, J.D.; Peng, Y.K.M.

    1984-04-01

    Plasma transport along divertor field lines was investigated using a two-point model. This treatment requires considerably less effort to find solutions to the transport equations than previously used one-dimensional (1-D) models and is useful for studying general trends. It also can be a valuable tool for benchmarking more sophisticated models. The model was used to investigate the possibility of operating in the so-called high density, low temperature regime

  8. Predicting acid dew point with a semi-empirical model

    International Nuclear Information System (INIS)

    Xiang, Baixiang; Tang, Bin; Wu, Yuxin; Yang, Hairui; Zhang, Man; Lu, Junfu

    2016-01-01

    Highlights: • The previous semi-empirical models are systematically studied. • An improved thermodynamic correlation is derived. • A semi-empirical prediction model is proposed. • The proposed semi-empirical model is validated. - Abstract: Decreasing the temperature of exhaust flue gas in boilers is one of the most effective ways to further improve the thermal efficiency, electrostatic precipitator efficiency and to decrease the water consumption of desulfurization tower, while, when this temperature is below the acid dew point, the fouling and corrosion will occur on the heating surfaces in the second pass of boilers. So, the knowledge on accurately predicting the acid dew point is essential. By investigating the previous models on acid dew point prediction, an improved thermodynamic correlation formula between the acid dew point and its influencing factors is derived first. And then, a semi-empirical prediction model is proposed, which is validated with the data both in field test and experiment, and comparing with the previous models.

  9. Point-point and point-line moving-window correlation spectroscopy and its applications

    Science.gov (United States)

    Zhou, Qun; Sun, Suqin; Zhan, Daqi; Yu, Zhiwu

    2008-07-01

    In this paper, we present a new extension of generalized two-dimensional (2D) correlation spectroscopy. Two new algorithms, namely point-point (P-P) correlation and point-line (P-L) correlation, have been introduced to do the moving-window 2D correlation (MW2D) analysis. The new method has been applied to a spectral model consisting of two different processes. The results indicate that P-P correlation spectroscopy can unveil the details and re-constitute the entire process, whilst the P-L can provide general feature of the concerned processes. Phase transition behavior of dimyristoylphosphotidylethanolamine (DMPE) has been studied using MW2D correlation spectroscopy. The newly proposed method verifies that the phase transition temperature is 56 °C, same as the result got from a differential scanning calorimeter. To illustrate the new method further, a lysine and lactose mixture has been studied under thermo perturbation. Using the P-P MW2D, the Maillard reaction of the mixture was clearly monitored, which has been very difficult using conventional display of FTIR spectra.

  10. From Particles and Point Clouds to Voxel Models: High Resolution Modeling of Dynamic Landscapes in Open Source GIS

    Science.gov (United States)

    Mitasova, H.; Hardin, E. J.; Kratochvilova, A.; Landa, M.

    2012-12-01

    Multitemporal data acquired by modern mapping technologies provide unique insights into processes driving land surface dynamics. These high resolution data also offer an opportunity to improve the theoretical foundations and accuracy of process-based simulations of evolving landforms. We discuss development of new generation of visualization and analytics tools for GRASS GIS designed for 3D multitemporal data from repeated lidar surveys and from landscape process simulations. We focus on data and simulation methods that are based on point sampling of continuous fields and lead to representation of evolving surfaces as series of raster map layers or voxel models. For multitemporal lidar data we present workflows that combine open source point cloud processing tools with GRASS GIS and custom python scripts to model and analyze dynamics of coastal topography (Figure 1) and we outline development of coastal analysis toolbox. The simulations focus on particle sampling method for solving continuity equations and its application for geospatial modeling of landscape processes. In addition to water and sediment transport models, already implemented in GIS, the new capabilities under development combine OpenFOAM for wind shear stress simulation with a new module for aeolian sand transport and dune evolution simulations. Comparison of observed dynamics with the results of simulations is supported by a new, integrated 2D and 3D visualization interface that provides highly interactive and intuitive access to the redesigned and enhanced visualization tools. Several case studies will be used to illustrate the presented methods and tools and demonstrate the power of workflows built with FOSS and highlight their interoperability.Figure 1. Isosurfaces representing evolution of shoreline and a z=4.5m contour between the years 1997-2011at Cape Hatteras, NC extracted from a voxel model derived from series of lidar-based DEMs.

  11. Stochastic process corrosion growth models for pipeline reliability

    International Nuclear Information System (INIS)

    Bazán, Felipe Alexander Vargas; Beck, André Teófilo

    2013-01-01

    Highlights: •Novel non-linear stochastic process corrosion growth model is proposed. •Corrosion rate modeled as random Poisson pulses. •Time to corrosion initiation and inherent time-variability properly represented. •Continuous corrosion growth histories obtained. •Model is shown to precisely fit actual corrosion data at two time points. -- Abstract: Linear random variable corrosion models are extensively employed in reliability analysis of pipelines. However, linear models grossly neglect well-known characteristics of the corrosion process. Herein, a non-linear model is proposed, where corrosion rate is represented as a Poisson square wave process. The resulting model represents inherent time-variability of corrosion growth, produces continuous growth and leads to mean growth at less-than-one power of time. Different corrosion models are adjusted to the same set of actual corrosion data for two inspections. The proposed non-linear random process corrosion growth model leads to the best fit to the data, while better representing problem physics

  12. Model-based testing for space-time interaction using point processes: An application to psychiatric hospital admissions in an urban area.

    Science.gov (United States)

    Meyer, Sebastian; Warnke, Ingeborg; Rössler, Wulf; Held, Leonhard

    2016-05-01

    Spatio-temporal interaction is inherent to cases of infectious diseases and occurrences of earthquakes, whereas the spread of other events, such as cancer or crime, is less evident. Statistical significance tests of space-time clustering usually assess the correlation between the spatial and temporal (transformed) distances of the events. Although appealing through simplicity, these classical tests do not adjust for the underlying population nor can they account for a distance decay of interaction. We propose to use the framework of an endemic-epidemic point process model to jointly estimate a background event rate explained by seasonal and areal characteristics, as well as a superposed epidemic component representing the hypothesis of interest. We illustrate this new model-based test for space-time interaction by analysing psychiatric inpatient admissions in Zurich, Switzerland (2007-2012). Several socio-economic factors were found to be associated with the admission rate, but there was no evidence of general clustering of the cases. Copyright © 2016 Elsevier Ltd. All rights reserved.

  13. Relationship between ammonia stomatal compensation point and nitrogen metabolism in arable crops: Current status of knowledge and potential modelling approaches

    Energy Technology Data Exchange (ETDEWEB)

    Massad, Raia Silvia [Institut National de la Recherche Agronomique (INRA), Environnement et Grandes Cultures, 78850 Thiverval-Grignon (France)], E-mail: massad@grignon.inra.fr; Loubet, Benjamin; Tuzet, Andree; Cellier, Pierre [Institut National de la Recherche Agronomique (INRA), Environnement et Grandes Cultures, 78850 Thiverval-Grignon (France)

    2008-08-15

    The ammonia stomatal compensation point of plants is determined by leaf temperature, ammonium concentration ([NH{sub 4}{sup +}]{sub apo}) and pH of the apoplastic solution. The later two depend on the adjacent cells metabolism and on leaf inputs and outputs through the xylem and phloem. Until now only empirical models have been designed to model the ammonia stomatal compensation point, except the model of Riedo et al. (2002. Coupling soil-plant-atmosphere exchange of ammonia with ecosystem functioning in grasslands. Ecological Modelling 158, 83-110), which represents the exchanges between the plant's nitrogen pools. The first step to model the ammonia stomatal compensation point is to adequately model [NH{sub 4}{sup +}]{sub apo}. This [NH{sub 4}{sup +}]{sub apo} has been studied experimentally, but there are currently no process-based quantitative models describing its relation to plant metabolism and environmental conditions. This study summarizes the processes involved in determining the ammonia stomatal compensation point at the leaf scale and qualitatively evaluates the ability of existing whole plant N and C models to include a model for [NH{sub 4}{sup +}]{sub apo}. - A model for ammonia stomatal compensation point at the leaf level scale was developed.

  14. Numerical modeling of laser assisted tape winding process

    Science.gov (United States)

    Zaami, Amin; Baran, Ismet; Akkerman, Remko

    2017-10-01

    Laser assisted tape winding (LATW) has become more and more popular way of producing new thermoplastic products such as ultra-deep sea water riser, gas tanks, structural parts for aerospace applications. Predicting the temperature in LATW has been a source of great interest since the temperature at nip-point plays a key role for mechanical interface performance. Modeling the LATW process includes several challenges such as the interaction of optics and heat transfer. In the current study, numerical modeling of the optical behavior of laser radiation on circular surfaces is investigated based on a ray tracing and non-specular reflection model. The non-specular reflection is implemented considering the anisotropic reflective behavior of the fiber-reinforced thermoplastic tape using a bidirectional reflectance distribution function (BRDF). The proposed model in the present paper includes a three-dimensional circular geometry, in which the effects of reflection from different ranges of the circular surface as well as effect of process parameters on temperature distribution are studied. The heat transfer model is constructed using a fully implicit method. The effect of process parameters on the nip-point temperature is examined. Furthermore, several laser distributions including Gaussian and linear are examined which has not been considered in literature up to now.

  15. Dew Point modelling using GEP based multi objective optimization

    OpenAIRE

    Shroff, Siddharth; Dabhi, Vipul

    2013-01-01

    Different techniques are used to model the relationship between temperatures, dew point and relative humidity. Gene expression programming is capable of modelling complex realities with great accuracy, allowing at the same time, the extraction of knowledge from the evolved models compared to other learning algorithms. We aim to use Gene Expression Programming for modelling of dew point. Generally, accuracy of the model is the only objective used by selection mechanism of GEP. This will evolve...

  16. A two-point kinetic model for the PROTEUS reactor

    International Nuclear Information System (INIS)

    Dam, H. van.

    1995-03-01

    A two-point reactor kinetic model for the PROTEUS-reactor is developed and the results are described in terms of frequency dependent reactivity transfer functions for the core and the reflector. It is shown that at higher frequencies space-dependent effects occur which imply failure of the one-point kinetic model. In the modulus of the transfer functions these effects become apparent above a radian frequency of about 100 s -1 , whereas for the phase behaviour the deviation from a point model already starts at a radian frequency of 10 s -1 . (orig.)

  17. Corner-point criterion for assessing nonlinear image processing imagers

    Science.gov (United States)

    Landeau, Stéphane; Pigois, Laurent; Foing, Jean-Paul; Deshors, Gilles; Swiathy, Greggory

    2017-10-01

    Range performance modeling of optronics imagers attempts to characterize the ability to resolve details in the image. Today, digital image processing is systematically used in conjunction with the optoelectronic system to correct its defects or to exploit tiny detection signals to increase performance. In order to characterize these processing having adaptive and non-linear properties, it becomes necessary to stimulate the imagers with test patterns whose properties are similar to the actual scene image ones, in terms of dynamic range, contours, texture and singular points. This paper presents an approach based on a Corner-Point (CP) resolution criterion, derived from the Probability of Correct Resolution (PCR) of binary fractal patterns. The fundamental principle lies in the respectful perception of the CP direction of one pixel minority value among the majority value of a 2×2 pixels block. The evaluation procedure considers the actual image as its multi-resolution CP transformation, taking the role of Ground Truth (GT). After a spatial registration between the degraded image and the original one, the degradation is statistically measured by comparing the GT with the degraded image CP transformation, in terms of localized PCR at the region of interest. The paper defines this CP criterion and presents the developed evaluation techniques, such as the measurement of the number of CP resolved on the target, the transformation CP and its inverse transform that make it possible to reconstruct an image of the perceived CPs. Then, this criterion is compared with the standard Johnson criterion, in the case of a linear blur and noise degradation. The evaluation of an imaging system integrating an image display and a visual perception is considered, by proposing an analysis scheme combining two methods: a CP measurement for the highly non-linear part (imaging) with real signature test target and conventional methods for the more linear part (displaying). The application to

  18. Comprehensive overview of the Point-by-Point model of prompt emission in fission

    Energy Technology Data Exchange (ETDEWEB)

    Tudora, A. [University of Bucharest, Faculty of Physics, Bucharest Magurele (Romania); Hambsch, F.J. [European Commission, Joint Research Centre, Directorate G - Nuclear Safety and Security, Unit G2, Geel (Belgium)

    2017-08-15

    The investigation of prompt emission in fission is very important in understanding the fission process and to improve the quality of evaluated nuclear data required for new applications. In the last decade remarkable efforts were done for both the development of prompt emission models and the experimental investigation of the properties of fission fragments and the prompt neutrons and γ-ray emission. The accurate experimental data concerning the prompt neutron multiplicity as a function of fragment mass and total kinetic energy for {sup 252}Cf(SF) and {sup 235}U(n,f) recently measured at JRC-Geel (as well as other various prompt emission data) allow a consistent and very detailed validation of the Point-by-Point (PbP) deterministic model of prompt emission. The PbP model results describe very well a large variety of experimental data starting from the multi-parametric matrices of prompt neutron multiplicity ν(A,TKE) and γ-ray energy E{sub γ}(A,TKE) which validate the model itself, passing through different average prompt emission quantities as a function of A (e.g., ν(A), E{sub γ}(A), left angle ε right angle (A) etc.), as a function of TKE (e.g., ν(TKE), E{sub γ}(TKE)) up to the prompt neutron distribution P(ν) and the total average prompt neutron spectrum. The PbP model does not use free or adjustable parameters. To calculate the multi-parametric matrices it needs only data included in the reference input parameter library RIPL of IAEA. To provide average prompt emission quantities as a function of A, of TKE and total average quantities the multi-parametric matrices are averaged over reliable experimental fragment distributions. The PbP results are also in agreement with the results of the Monte Carlo prompt emission codes FIFRELIN, CGMF and FREYA. The good description of a large variety of experimental data proves the capability of the PbP model to be used in nuclear data evaluations and its reliability to predict prompt emission data for fissioning

  19. A Typology for Modeling Processes in Clinical Guidelines and Protocols

    Science.gov (United States)

    Tu, Samson W.; Musen, Mark A.

    We analyzed the graphical representations that are used by various guideline-modeling methods to express process information embodied in clinical guidelines and protocols. From this analysis, we distilled four modeling formalisms and the processes they typically model: (1) flowcharts for capturing problem-solving processes, (2) disease-state maps that link decision points in managing patient problems over time, (3) plans that specify sequences of activities that contribute toward a goal, (4) workflow specifications that model care processes in an organization. We characterized the four approaches and showed that each captures some aspect of what a guideline may specify. We believe that a general guideline-modeling system must provide explicit representation for each type of process.

  20. Process and results of analytical framework and typology development for POINT

    DEFF Research Database (Denmark)

    Gudmundsson, Henrik; Lehtonen, Markku; Bauler, Tom

    2009-01-01

    POINT is a project about how indicators are used in practice; to what extent and in what way indicators actually influence, support, or hinder policy and decision making processes, and what could be done to enhance the positive role of indicators in such processes. The project needs an analytical......, a set of core concepts and associated typologies, a series of analytic schemes proposed, and a number of research propositions and questions for the subsequent empirical work in POINT....

  1. Modeling hard clinical end-point data in economic analyses.

    Science.gov (United States)

    Kansal, Anuraag R; Zheng, Ying; Palencia, Roberto; Ruffolo, Antonio; Hass, Bastian; Sorensen, Sonja V

    2013-11-01

    The availability of hard clinical end-point data, such as that on cardiovascular (CV) events among patients with type 2 diabetes mellitus, is increasing, and as a result there is growing interest in using hard end-point data of this type in economic analyses. This study investigated published approaches for modeling hard end-points from clinical trials and evaluated their applicability in health economic models with different disease features. A review of cost-effectiveness models of interventions in clinically significant therapeutic areas (CV diseases, cancer, and chronic lower respiratory diseases) was conducted in PubMed and Embase using a defined search strategy. Only studies integrating hard end-point data from randomized clinical trials were considered. For each study included, clinical input characteristics and modeling approach were summarized and evaluated. A total of 33 articles (23 CV, eight cancer, two respiratory) were accepted for detailed analysis. Decision trees, Markov models, discrete event simulations, and hybrids were used. Event rates were incorporated either as constant rates, time-dependent risks, or risk equations based on patient characteristics. Risks dependent on time and/or patient characteristics were used where major event rates were >1%/year in models with fewer health states (Models of infrequent events or with numerous health states generally preferred constant event rates. The detailed modeling information and terminology varied, sometimes requiring interpretation. Key considerations for cost-effectiveness models incorporating hard end-point data include the frequency and characteristics of the relevant clinical events and how the trial data is reported. When event risk is low, simplification of both the model structure and event rate modeling is recommended. When event risk is common, such as in high risk populations, more detailed modeling approaches, including individual simulations or explicitly time-dependent event rates, are

  2. Pedagogic process modeling: Humanistic-integrative approach

    Directory of Open Access Journals (Sweden)

    Boritko Nikolaj M.

    2007-01-01

    Full Text Available The paper deals with some current problems of modeling the dynamics of the subject-features development of the individual. The term "process" is considered in the context of the humanistic-integrative approach, in which the principles of self education are regarded as criteria for efficient pedagogic activity. Four basic characteristics of the pedagogic process are pointed out: intentionality reflects logicality and regularity of the development of the process; discreteness (stageability in dicates qualitative stages through which the pedagogic phenomenon passes; nonlinearity explains the crisis character of pedagogic processes and reveals inner factors of self-development; situationality requires a selection of pedagogic conditions in accordance with the inner factors, which would enable steering the pedagogic process. Offered are two steps for singling out a particular stage and the algorithm for developing an integrative model for it. The suggested conclusions might be of use for further theoretic research, analyses of educational practices and for realistic predicting of pedagogical phenomena. .

  3. A hierarchical model exhibiting the Kosterlitz-Thouless fixed point

    International Nuclear Information System (INIS)

    Marchetti, D.H.U.; Perez, J.F.

    1985-01-01

    A hierarchical model for 2-d Coulomb gases displaying a line stable of fixed points describing the Kosterlitz-Thouless phase transition is constructed. For Coulomb gases corresponding to Z sub(N)- models these fixed points are stable for an intermediate temperature interval. (Author) [pt

  4. Modelling occupants’ heating set-point prefferences

    DEFF Research Database (Denmark)

    Andersen, Rune Vinther; Olesen, Bjarne W.; Toftum, Jørn

    2011-01-01

    consumption. Simultaneous measurement of the set-point of thermostatic radiator valves (trv), and indoor and outdoor environment characteristics was carried out in 15 dwellings in Denmark in 2008. Linear regression was used to infer a model of occupants’ interactions with trvs. This model could easily...... be implemented in most simulation software packages to increase the validity of the simulation outcomes....

  5. Fixed Points in Discrete Models for Regulatory Genetic Networks

    Directory of Open Access Journals (Sweden)

    Orozco Edusmildo

    2007-01-01

    Full Text Available It is desirable to have efficient mathematical methods to extract information about regulatory iterations between genes from repeated measurements of gene transcript concentrations. One piece of information is of interest when the dynamics reaches a steady state. In this paper we develop tools that enable the detection of steady states that are modeled by fixed points in discrete finite dynamical systems. We discuss two algebraic models, a univariate model and a multivariate model. We show that these two models are equivalent and that one can be converted to the other by means of a discrete Fourier transform. We give a new, more general definition of a linear finite dynamical system and we give a necessary and sufficient condition for such a system to be a fixed point system, that is, all cycles are of length one. We show how this result for generalized linear systems can be used to determine when certain nonlinear systems (monomial dynamical systems over finite fields are fixed point systems. We also show how it is possible to determine in polynomial time when an ordinary linear system (defined over a finite field is a fixed point system. We conclude with a necessary condition for a univariate finite dynamical system to be a fixed point system.

  6. Fuzzy Logic Based Set-Point Weighting Controller Tuning for an Internal Model Control Based PID Controller

    Directory of Open Access Journals (Sweden)

    Maruthai Suresh

    2009-10-01

    Full Text Available Controller tuning is the process of adjusting the parameters of the selected controller to achieve optimum response for the controlled process. For many of the control problems, a satisfactory performance is obtained by using PID controllers. One of the main problems with mathematical models of physical systems is that the parameters used in the models cannot be determined with absolute accuracy. The values of the parameters may change with time or various effects. In these cases, conventional controller tuning methods suffer when trying a lot to produce optimum response. In order to overcome these difficulties a fuzzy logic based Set- Point weighting controller tuning method is proposed. The effectiveness of the proposed scheme is analyzed through computer simulation using SIMULINK software and the results are presented. The fuzzy logic based simulation results are compared with Cohen-Coon (CC, Ziegler- Nichols (ZN, Ziegler – Nichols with Set- Point weighting (ZN-SPW, Internal Model Control (IMC and Internal model based PID controller responses (IMC-PID. The effects of process modeling errors and the importance of controller tuning have been brought out using the proposed control scheme.

  7. Impact of selected troposphere models on Precise Point Positioning convergence

    Science.gov (United States)

    Kalita, Jakub; Rzepecka, Zofia

    2016-04-01

    The Precise Point Positioning (PPP) absolute method is currently intensively investigated in order to reach fast convergence time. Among various sources that influence the convergence of the PPP, the tropospheric delay is one of the most important. Numerous models of tropospheric delay are developed and applied to PPP processing. However, with rare exceptions, the quality of those models does not allow fixing the zenith path delay tropospheric parameter, leaving difference between nominal and final value to the estimation process. Here we present comparison of several PPP result sets, each of which based on different troposphere model. The respective nominal values are adopted from models: VMF1, GPT2w, MOPS and ZERO-WET. The PPP solution admitted as reference is based on the final troposphere product from the International GNSS Service (IGS). The VMF1 mapping function was used for all processing variants in order to provide capability to compare impact of applied nominal values. The worst case initiates zenith wet delay with zero value (ZERO-WET). Impact from all possible models for tropospheric nominal values should fit inside both IGS and ZERO-WET border variants. The analysis is based on data from seven IGS stations located in mid-latitude European region from year 2014. For the purpose of this study several days with the most active troposphere were selected for each of the station. All the PPP solutions were determined using gLAB open-source software, with the Kalman filter implemented independently by the authors of this work. The processing was performed on 1 hour slices of observation data. In addition to the analysis of the output processing files, the presented study contains detailed analysis of the tropospheric conditions for the selected data. The overall results show that for the height component the VMF1 model outperforms GPT2w and MOPS by 35-40% and ZERO-WET variant by 150%. In most of the cases all solutions converge to the same values during first

  8. A Generic Modeling Process to Support Functional Fault Model Development

    Science.gov (United States)

    Maul, William A.; Hemminger, Joseph A.; Oostdyk, Rebecca; Bis, Rachael A.

    2016-01-01

    Functional fault models (FFMs) are qualitative representations of a system's failure space that are used to provide a diagnostic of the modeled system. An FFM simulates the failure effect propagation paths within a system between failure modes and observation points. These models contain a significant amount of information about the system including the design, operation and off nominal behavior. The development and verification of the models can be costly in both time and resources. In addition, models depicting similar components can be distinct, both in appearance and function, when created individually, because there are numerous ways of representing the failure space within each component. Generic application of FFMs has the advantages of software code reuse: reduction of time and resources in both development and verification, and a standard set of component models from which future system models can be generated with common appearance and diagnostic performance. This paper outlines the motivation to develop a generic modeling process for FFMs at the component level and the effort to implement that process through modeling conventions and a software tool. The implementation of this generic modeling process within a fault isolation demonstration for NASA's Advanced Ground System Maintenance (AGSM) Integrated Health Management (IHM) project is presented and the impact discussed.

  9. Implementation of 5S tools as a starting point in business process reengineering

    Directory of Open Access Journals (Sweden)

    Vorkapić Miloš 0000-0002-3463-8665

    2017-01-01

    Full Text Available The paper deals with the analysis of elements which represent a starting point in implementation of a business process reengineering. We have used Lean tools through the analysis of 5S model in our research. On the example of finalization of the finished transmitter in IHMT-CMT production, 5S tools were implemented with a focus on Quality elements although the theory shows that BPR and TQM are two opposite activities in an enterprise. We wanted to distinguish the significance of employees’ self-discipline which helps the process of product finalization to develop in time and without waste and losses. In addition, the employees keep their work place clean, tidy and functional.

  10. The environmental zero-point problem in evolutionary reaction norm modeling.

    Science.gov (United States)

    Ergon, Rolf

    2018-04-01

    There is a potential problem in present quantitative genetics evolutionary modeling based on reaction norms. Such models are state-space models, where the multivariate breeder's equation in some form is used as the state equation that propagates the population state forward in time. These models use the implicit assumption of a constant reference environment, in many cases set to zero. This zero-point is often the environment a population is adapted to, that is, where the expected geometric mean fitness is maximized. Such environmental reference values follow from the state of the population system, and they are thus population properties. The environment the population is adapted to, is, in other words, an internal population property, independent of the external environment. It is only when the external environment coincides with the internal reference environment, or vice versa, that the population is adapted to the current environment. This is formally a result of state-space modeling theory, which is an important theoretical basis for evolutionary modeling. The potential zero-point problem is present in all types of reaction norm models, parametrized as well as function-valued, and the problem does not disappear when the reference environment is set to zero. As the environmental reference values are population characteristics, they ought to be modeled as such. Whether such characteristics are evolvable is an open question, but considering the complexity of evolutionary processes, such evolvability cannot be excluded without good arguments. As a straightforward solution, I propose to model the reference values as evolvable mean traits in their own right, in addition to other reaction norm traits. However, solutions based on an evolvable G matrix are also possible.

  11. On-line validation of linear process models using generalized likelihood ratios

    International Nuclear Information System (INIS)

    Tylee, J.L.

    1981-12-01

    A real-time method for testing the validity of linear models of nonlinear processes is described and evaluated. Using generalized likelihood ratios, the model dynamics are continually monitored to see if the process has moved far enough away from the nominal linear model operating point to justify generation of a new linear model. The method is demonstrated using a seventh-order model of a natural circulation steam generator

  12. A point particle model of lightly bound skyrmions

    Directory of Open Access Journals (Sweden)

    Mike Gillard

    2017-04-01

    Full Text Available A simple model of the dynamics of lightly bound skyrmions is developed in which skyrmions are replaced by point particles, each carrying an internal orientation. The model accounts well for the static energy minimizers of baryon number 1≤B≤8 obtained by numerical simulation of the full field theory. For 9≤B≤23, a large number of static solutions of the point particle model are found, all closely resembling size B subsets of a face centred cubic lattice, with the particle orientations dictated by a simple colouring rule. Rigid body quantization of these solutions is performed, and the spin and isospin of the corresponding ground states extracted. As part of the quantization scheme, an algorithm to compute the symmetry group of an oriented point cloud, and to determine its corresponding Finkelstein–Rubinstein constraints, is devised.

  13. A 3D Printing Model Watermarking Algorithm Based on 3D Slicing and Feature Points

    Directory of Open Access Journals (Sweden)

    Giao N. Pham

    2018-02-01

    Full Text Available With the increase of three-dimensional (3D printing applications in many areas of life, a large amount of 3D printing data is copied, shared, and used several times without any permission from the original providers. Therefore, copyright protection and ownership identification for 3D printing data in communications or commercial transactions are practical issues. This paper presents a novel watermarking algorithm for 3D printing models based on embedding watermark data into the feature points of a 3D printing model. Feature points are determined and computed by the 3D slicing process along the Z axis of a 3D printing model. The watermark data is embedded into a feature point of a 3D printing model by changing the vector length of the feature point in OXY space based on the reference length. The x and y coordinates of the feature point will be then changed according to the changed vector length that has been embedded with a watermark. Experimental results verified that the proposed algorithm is invisible and robust to geometric attacks, such as rotation, scaling, and translation. The proposed algorithm provides a better method than the conventional works, and the accuracy of the proposed algorithm is much higher than previous methods.

  14. Modelling of thermal field and point defect dynamics during silicon single crystal growth using CZ technique

    Science.gov (United States)

    Sabanskis, A.; Virbulis, J.

    2018-05-01

    Mathematical modelling is employed to numerically analyse the dynamics of the Czochralski (CZ) silicon single crystal growth. The model is axisymmetric, its thermal part describes heat transfer by conduction and thermal radiation, and allows to predict the time-dependent shape of the crystal-melt interface. Besides the thermal field, the point defect dynamics is modelled using the finite element method. The considered process consists of cone growth and cylindrical phases, including a short period of a reduced crystal pull rate, and a power jump to avoid large diameter changes. The influence of the thermal stresses on the point defects is also investigated.

  15. FINDING CUBOID-BASED BUILDING MODELS IN POINT CLOUDS

    Directory of Open Access Journals (Sweden)

    W. Nguatem

    2012-07-01

    Full Text Available In this paper, we present an automatic approach for the derivation of 3D building models of level-of-detail 1 (LOD 1 from point clouds obtained from (dense image matching or, for comparison only, from LIDAR. Our approach makes use of the predominance of vertical structures and orthogonal intersections in architectural scenes. After robustly determining the scene's vertical direction based on the 3D points we use it as constraint for a RANSAC-based search for vertical planes in the point cloud. The planes are further analyzed to segment reliable outlines for rectangular surface within these planes, which are connected to construct cuboid-based building models. We demonstrate that our approach is robust and effective over a range of real-world input data sets with varying point density, amount of noise, and outliers.

  16. A decision model for the risk management of hazardous processes

    International Nuclear Information System (INIS)

    Holmberg, J.E.

    1997-03-01

    A decision model for risk management of hazardous processes as an optimisation problem of a point process is formulated in the study. In the approach, the decisions made by the management are divided into three categories: (1) planned process lifetime, (2) selection of the design and, (3) operational decisions. These three controlling methods play quite different roles in the practical risk management, which is also reflected in our approach. The optimisation of the process lifetime is related to the licensing problem of the process. It provides a boundary condition for a feasible utility function that is used as the actual objective function, i.e., maximizing the process lifetime utility. By design modifications, the management can affect the inherent accident hazard rate of the process. This is usually a discrete optimisation task. The study particularly concentrates upon the optimisation of the operational strategies given a certain design and licensing time. This is done by a dynamic risk model (marked point process model) representing the stochastic process of events observable or unobservable to the decision maker. An optimal long term control variable guiding the selection of operational alternatives in short term problems is studied. The optimisation problem is solved by the stochastic quasi-gradient procedure. The approach is illustrated by a case study. (23 refs.)

  17. Optimal time points sampling in pathway modelling.

    Science.gov (United States)

    Hu, Shiyan

    2004-01-01

    Modelling cellular dynamics based on experimental data is at the heart of system biology. Considerable progress has been made to dynamic pathway modelling as well as the related parameter estimation. However, few of them gives consideration for the issue of optimal sampling time selection for parameter estimation. Time course experiments in molecular biology rarely produce large and accurate data sets and the experiments involved are usually time consuming and expensive. Therefore, to approximate parameters for models with only few available sampling data is of significant practical value. For signal transduction, the sampling intervals are usually not evenly distributed and are based on heuristics. In the paper, we investigate an approach to guide the process of selecting time points in an optimal way to minimize the variance of parameter estimates. In the method, we first formulate the problem to a nonlinear constrained optimization problem by maximum likelihood estimation. We then modify and apply a quantum-inspired evolutionary algorithm, which combines the advantages of both quantum computing and evolutionary computing, to solve the optimization problem. The new algorithm does not suffer from the morass of selecting good initial values and being stuck into local optimum as usually accompanied with the conventional numerical optimization techniques. The simulation results indicate the soundness of the new method.

  18. Definition of distance for nonlinear time series analysis of marked point process data

    Energy Technology Data Exchange (ETDEWEB)

    Iwayama, Koji, E-mail: koji@sat.t.u-tokyo.ac.jp [Research Institute for Food and Agriculture, Ryukoku Univeristy, 1-5 Yokotani, Seta Oe-cho, Otsu-Shi, Shiga 520-2194 (Japan); Hirata, Yoshito; Aihara, Kazuyuki [Institute of Industrial Science, The University of Tokyo, 4-6-1 Komaba, Meguro-ku, Tokyo 153-8505 (Japan)

    2017-01-30

    Marked point process data are time series of discrete events accompanied with some values, such as economic trades, earthquakes, and lightnings. A distance for marked point process data allows us to apply nonlinear time series analysis to such data. We propose a distance for marked point process data which can be calculated much faster than the existing distance when the number of marks is small. Furthermore, under some assumptions, the Kullback–Leibler divergences between posterior distributions for neighbors defined by this distance are small. We performed some numerical simulations showing that analysis based on the proposed distance is effective. - Highlights: • A new distance for marked point process data is proposed. • The distance can be computed fast enough for a small number of marks. • The method to optimize parameter values of the distance is also proposed. • Numerical simulations indicate that the analysis based on the distance is effective.

  19. Methodology for Modeling and Analysis of Business Processes (MMABP

    Directory of Open Access Journals (Sweden)

    Vaclav Repa

    2015-10-01

    Full Text Available This paper introduces the methodology for modeling business processes. Creation of the methodology is described in terms of the Design Science Method. Firstly, the gap in contemporary Business Process Modeling approaches is identified and general modeling principles which can fill the gap are discussed. The way which these principles have been implemented in the main features of created methodology is described. Most critical identified points of the business process modeling are process states, process hierarchy and the granularity of process description. The methodology has been evaluated by use in the real project. Using the examples from this project the main methodology features are explained together with the significant problems which have been met during the project. Concluding from these problems together with the results of the methodology evaluation the needed future development of the methodology is outlined.

  20. Modelling Template for the Development of the Process Flowsheet

    DEFF Research Database (Denmark)

    Fedorova, Marina; Gani, Rafiqul

    2015-01-01

    Models are playing important roles in design and analysis of chemicals/bio-chemicals based products and the processes that manufacture them. Model-based methods and tools have the potential to decrease the number of experiments, which can be expensive and time consuming, and point to candidates...... in connection to other modelling tools within the modelling framework are forming a user-friendly system, which will make the model development process easier and faster and provide the way for unified and consistent model documentation. The modeller can use the template for their specific problem or to extend...... models systematically, efficiently and reliably. In this way, development of products and processes can be faster, cheaper and very efficient. The developed modelling framework involves three main parts: 1) a modelling tool, that includes algorithms for model generation; 2) a template library, which...

  1. Parallel Processing of Big Point Clouds Using Z-Order Partitioning

    Science.gov (United States)

    Alis, C.; Boehm, J.; Liu, K.

    2016-06-01

    As laser scanning technology improves and costs are coming down, the amount of point cloud data being generated can be prohibitively difficult and expensive to process on a single machine. This data explosion is not only limited to point cloud data. Voluminous amounts of high-dimensionality and quickly accumulating data, collectively known as Big Data, such as those generated by social media, Internet of Things devices and commercial transactions, are becoming more prevalent as well. New computing paradigms and frameworks are being developed to efficiently handle the processing of Big Data, many of which utilize a compute cluster composed of several commodity grade machines to process chunks of data in parallel. A central concept in many of these frameworks is data locality. By its nature, Big Data is large enough that the entire dataset would not fit on the memory and hard drives of a single node hence replicating the entire dataset to each worker node is impractical. The data must then be partitioned across worker nodes in a manner that minimises data transfer across the network. This is a challenge for point cloud data because there exist different ways to partition data and they may require data transfer. We propose a partitioning based on Z-order which is a form of locality-sensitive hashing. The Z-order or Morton code is computed by dividing each dimension to form a grid then interleaving the binary representation of each dimension. For example, the Z-order code for the grid square with coordinates (x = 1 = 012, y = 3 = 112) is 10112 = 11. The number of points in each partition is controlled by the number of bits per dimension: the more bits, the fewer the points. The number of bits per dimension also controls the level of detail with more bits yielding finer partitioning. We present this partitioning method by implementing it on Apache Spark and investigating how different parameters affect the accuracy and running time of the k nearest neighbour algorithm

  2. Fermentation of Saccharomyces cerevisiae - Combining kinetic modeling and optimization techniques points out avenues to effective process design.

    Science.gov (United States)

    Scheiblauer, Johannes; Scheiner, Stefan; Joksch, Martin; Kavsek, Barbara

    2018-09-14

    A combined experimental/theoretical approach is presented, for improving the predictability of Saccharomyces cerevisiae fermentations. In particular, a mathematical model was developed explicitly taking into account the main mechanisms of the fermentation process, allowing for continuous computation of key process variables, including the biomass concentration and the respiratory quotient (RQ). For model calibration and experimental validation, batch and fed-batch fermentations were carried out. Comparison of the model-predicted biomass concentrations and RQ developments with the corresponding experimentally recorded values shows a remarkably good agreement for both batch and fed-batch processes, confirming the adequacy of the model. Furthermore, sensitivity studies were performed, in order to identify model parameters whose variations have significant effects on the model predictions: our model responds with significant sensitivity to the variations of only six parameters. These studies provide a valuable basis for model reduction, as also demonstrated in this paper. Finally, optimization-based parametric studies demonstrate how our model can be utilized for improving the efficiency of Saccharomyces cerevisiae fermentations. Copyright © 2018 Elsevier Ltd. All rights reserved.

  3. Generation of a statistical shape model with probabilistic point correspondences and the expectation maximization- iterative closest point algorithm

    International Nuclear Information System (INIS)

    Hufnagel, Heike; Pennec, Xavier; Ayache, Nicholas; Ehrhardt, Jan; Handels, Heinz

    2008-01-01

    Identification of point correspondences between shapes is required for statistical analysis of organ shapes differences. Since manual identification of landmarks is not a feasible option in 3D, several methods were developed to automatically find one-to-one correspondences on shape surfaces. For unstructured point sets, however, one-to-one correspondences do not exist but correspondence probabilities can be determined. A method was developed to compute a statistical shape model based on shapes which are represented by unstructured point sets with arbitrary point numbers. A fundamental problem when computing statistical shape models is the determination of correspondences between the points of the shape observations of the training data set. In the absence of landmarks, exact correspondences can only be determined between continuous surfaces, not between unstructured point sets. To overcome this problem, we introduce correspondence probabilities instead of exact correspondences. The correspondence probabilities are found by aligning the observation shapes with the affine expectation maximization-iterative closest points (EM-ICP) registration algorithm. In a second step, the correspondence probabilities are used as input to compute a mean shape (represented once again by an unstructured point set). Both steps are unified in a single optimization criterion which depe nds on the two parameters 'registration transformation' and 'mean shape'. In a last step, a variability model which best represents the variability in the training data set is computed. Experiments on synthetic data sets and in vivo brain structure data sets (MRI) are then designed to evaluate the performance of our algorithm. The new method was applied to brain MRI data sets, and the estimated point correspondences were compared to a statistical shape model built on exact correspondences. Based on established measures of ''generalization ability'' and ''specificity'', the estimates were very satisfactory

  4. Point, surface and volumetric heat sources in the thermal modelling of selective laser melting

    Science.gov (United States)

    Yang, Yabin; Ayas, Can

    2017-10-01

    Selective laser melting (SLM) is a powder based additive manufacturing technique suitable for producing high precision metal parts. However, distortions and residual stresses within products arise during SLM because of the high temperature gradients created by the laser heating. Residual stresses limit the load resistance of the product and may even lead to fracture during the built process. It is therefore of paramount importance to predict the level of part distortion and residual stress as a function of SLM process parameters which requires a reliable thermal modelling of the SLM process. Consequently, a key question arises which is how to describe the laser source appropriately. Reasonable simplification of the laser representation is crucial for the computational efficiency of the thermal model of the SLM process. In this paper, first a semi-analytical thermal modelling approach is described. Subsequently, the laser heating is modelled using point, surface and volumetric sources, in order to compare the influence of different laser source geometries on the thermal history prediction of the thermal model. The present work provides guidelines on appropriate representation of the laser source in the thermal modelling of the SLM process.

  5. Edit distance for marked point processes revisited: An implementation by binary integer programming

    Energy Technology Data Exchange (ETDEWEB)

    Hirata, Yoshito; Aihara, Kazuyuki [Institute of Industrial Science, The University of Tokyo, 4-6-1 Komaba, Meguro-ku, Tokyo 153-8505 (Japan)

    2015-12-15

    We implement the edit distance for marked point processes [Suzuki et al., Int. J. Bifurcation Chaos 20, 3699–3708 (2010)] as a binary integer program. Compared with the previous implementation using minimum cost perfect matching, the proposed implementation has two advantages: first, by using the proposed implementation, we can apply a wide variety of software and hardware, even spin glasses and coherent ising machines, to calculate the edit distance for marked point processes; second, the proposed implementation runs faster than the previous implementation when the difference between the numbers of events in two time windows for a marked point process is large.

  6. Quantification of annual wildfire risk; A spatio-temporal point process approach.

    Directory of Open Access Journals (Sweden)

    Paula Pereira

    2013-10-01

    Full Text Available Policy responses for local and global firemanagement depend heavily on the proper understanding of the fire extent as well as its spatio-temporal variation across any given study area. Annual fire risk maps are important tools for such policy responses, supporting strategic decisions such as location-allocation of equipment and human resources. Here, we define risk of fire in the narrow sense as the probability of its occurrence without addressing the loss component. In this paper, we study the spatio-temporal point patterns of wildfires and model them by a log Gaussian Cox processes. Themean of predictive distribution of randomintensity function is used in the narrow sense, as the annual fire risk map for next year.

  7. Parametric Architectural Design with Point-clouds

    DEFF Research Database (Denmark)

    Zwierzycki, Mateusz; Evers, Henrik Leander; Tamke, Martin

    2016-01-01

    This paper investigates the efforts and benefits of the implementation of point clouds into architectural design processes and tools. Based on a study on the principal work processes of designers with point clouds the prototypical plugin/library - Volvox - was developed for the parametric modelling...

  8. Thermodynamic-behaviour model for air-cooled screw chillers with a variable set-point condensing temperature

    International Nuclear Information System (INIS)

    Chan, K.T.; Yu, F.W.

    2006-01-01

    This paper presents a thermodynamic model to evaluate the coefficient of performance (COP) of an air-cooled screw chiller under various operating conditions. The model accounts for the real process phenomena, including the capacity control of screw compressors and variations in the heat-transfer coefficients of an evaporator and a condenser at part load. It also contains an algorithm to determine how the condenser fans are staged in response to a set-point condensing temperature. The model parameters are identified, based on the performance data of chiller specifications. The chiller model is validated using a wide range of operating data of an air-cooled screw chiller. The difference between the measured and modelled COPs is within ±10% for 86% of the data points. The chiller's COP can increase by up to 115% when the set-point condensing temperature is adjusted, based on any given outdoor temperature. Having identified the variation in the chiller's COP, a suitable strategy is proposed for air-cooled screw chillers to operate at maximum efficiency as much as possible when they have to satisfy a building's cooling-load

  9. Structure Based Thermostability Prediction Models for Protein Single Point Mutations with Machine Learning Tools.

    Directory of Open Access Journals (Sweden)

    Lei Jia

    Full Text Available Thermostability issue of protein point mutations is a common occurrence in protein engineering. An application which predicts the thermostability of mutants can be helpful for guiding decision making process in protein design via mutagenesis. An in silico point mutation scanning method is frequently used to find "hot spots" in proteins for focused mutagenesis. ProTherm (http://gibk26.bio.kyutech.ac.jp/jouhou/Protherm/protherm.html is a public database that consists of thousands of protein mutants' experimentally measured thermostability. Two data sets based on two differently measured thermostability properties of protein single point mutations, namely the unfolding free energy change (ddG and melting temperature change (dTm were obtained from this database. Folding free energy change calculation from Rosetta, structural information of the point mutations as well as amino acid physical properties were obtained for building thermostability prediction models with informatics modeling tools. Five supervised machine learning methods (support vector machine, random forests, artificial neural network, naïve Bayes classifier, K nearest neighbor and partial least squares regression are used for building the prediction models. Binary and ternary classifications as well as regression models were built and evaluated. Data set redundancy and balancing, the reverse mutations technique, feature selection, and comparison to other published methods were discussed. Rosetta calculated folding free energy change ranked as the most influential features in all prediction models. Other descriptors also made significant contributions to increasing the accuracy of the prediction models.

  10. Modelling financial high frequency data using point processes

    DEFF Research Database (Denmark)

    Hautsch, Nikolaus; Bauwens, Luc

    In this chapter written for a forthcoming Handbook of Financial Time Series to be published by Springer-Verlag, we review the econometric literature on dynamic duration and intensity processes applied to high frequency financial data, which was boosted by the work of Engle and Russell (1997...

  11. Quantifying structural uncertainty on fault networks using a marked point process within a Bayesian framework

    Science.gov (United States)

    Aydin, Orhun; Caers, Jef Karel

    2017-08-01

    Faults are one of the building-blocks for subsurface modeling studies. Incomplete observations of subsurface fault networks lead to uncertainty pertaining to location, geometry and existence of faults. In practice, gaps in incomplete fault network observations are filled based on tectonic knowledge and interpreter's intuition pertaining to fault relationships. Modeling fault network uncertainty with realistic models that represent tectonic knowledge is still a challenge. Although methods that address specific sources of fault network uncertainty and complexities of fault modeling exists, a unifying framework is still lacking. In this paper, we propose a rigorous approach to quantify fault network uncertainty. Fault pattern and intensity information are expressed by means of a marked point process, marked Strauss point process. Fault network information is constrained to fault surface observations (complete or partial) within a Bayesian framework. A structural prior model is defined to quantitatively express fault patterns, geometries and relationships within the Bayesian framework. Structural relationships between faults, in particular fault abutting relations, are represented with a level-set based approach. A Markov Chain Monte Carlo sampler is used to sample posterior fault network realizations that reflect tectonic knowledge and honor fault observations. We apply the methodology to a field study from Nankai Trough & Kumano Basin. The target for uncertainty quantification is a deep site with attenuated seismic data with only partially visible faults and many faults missing from the survey or interpretation. A structural prior model is built from shallow analog sites that are believed to have undergone similar tectonics compared to the site of study. Fault network uncertainty for the field is quantified with fault network realizations that are conditioned to structural rules, tectonic information and partially observed fault surfaces. We show the proposed

  12. A Monte Carlo-adjusted goodness-of-fit test for parametric models describing spatial point patterns

    KAUST Repository

    Dao, Ngocanh; Genton, Marc G.

    2014-01-01

    Assessing the goodness-of-fit (GOF) for intricate parametric spatial point process models is important for many application fields. When the probability density of the statistic of the GOF test is intractable, a commonly used procedure is the Monte

  13. Evolving chemometric models for predicting dynamic process parameters in viscose production

    Energy Technology Data Exchange (ETDEWEB)

    Cernuda, Carlos [Department of Knowledge-Based Mathematical Systems, Johannes Kepler University Linz (Austria); Lughofer, Edwin, E-mail: edwin.lughofer@jku.at [Department of Knowledge-Based Mathematical Systems, Johannes Kepler University Linz (Austria); Suppan, Lisbeth [Kompetenzzentrum Holz GmbH, St. Peter-Str. 25, 4021 Linz (Austria); Roeder, Thomas; Schmuck, Roman [Lenzing AG, 4860 Lenzing (Austria); Hintenaus, Peter [Software Research Center, Paris Lodron University Salzburg (Austria); Maerzinger, Wolfgang [i-RED Infrarot Systeme GmbH, Linz (Austria); Kasberger, Juergen [Recendt GmbH, Linz (Austria)

    2012-05-06

    Highlights: Black-Right-Pointing-Pointer Quality assurance of process parameters in viscose production. Black-Right-Pointing-Pointer Automatic prediction of spin-bath concentrations based on FTNIR spectra. Black-Right-Pointing-Pointer Evolving chemometric models for efficiently handling changing system dynamics over time (no time-intensive re-calibration needed). Black-Right-Pointing-Pointer Significant reduction of huge errors produced by statistical state-of-the-art calibration methods. Black-Right-Pointing-Pointer Sufficient flexibility achieved by gradual forgetting mechanisms. - Abstract: In viscose production, it is important to monitor three process parameters in order to assure a high quality of the final product: the concentrations of H{sub 2}SO{sub 4}, Na{sub 2}SO{sub 4} and Z{sub n}SO{sub 4}. During on-line production these process parameters usually show a quite high dynamics depending on the fiber type that is produced. Thus, conventional chemometric models, which are trained based on collected calibration spectra from Fourier transform near infrared (FT-NIR) measurements and kept fixed during the whole life-time of the on-line process, show a quite imprecise and unreliable behavior when predicting the concentrations of new on-line data. In this paper, we are demonstrating evolving chemometric models which are able to adapt automatically to varying process dynamics by updating their inner structures and parameters in a single-pass incremental manner. These models exploit the Takagi-Sugeno fuzzy model architecture, being able to model flexibly different degrees of non-linearities implicitly contained in the mapping between near infrared spectra (NIR) and reference values. Updating the inner structures is achieved by moving the position of already existing local regions and by evolving (increasing non-linearity) or merging (decreasing non-linearity) new local linear predictors on demand, which are guided by distance-based and similarity criteria. Gradual

  14. A simple model for correcting the zero point energy problem in classical trajectory simulations of polyatomic molecules

    International Nuclear Information System (INIS)

    Miller, W.H.; Hase, W.L.; Darling, C.L.

    1989-01-01

    A simple model is proposed for correcting problems with zero point energy in classical trajectory simulations of dynamical processes in polyatomic molecules. The ''problems'' referred to are that classical mechanics allows the vibrational energy in a mode to decrease below its quantum zero point value, and since the total energy is conserved classically this can allow too much energy to pool in other modes. The proposed model introduces hard sphere-like terms in action--angle variables that prevent the vibrational energy in any mode from falling below its zero point value. The algorithm which results is quite simple in terms of the cartesian normal modes of the system: if the energy in a mode k, say, decreases below its zero point value at time t, then at this time the momentum P k for that mode has its sign changed, and the trajectory continues. This is essentially a time reversal for mode k (only exclamation point), and it conserves the total energy of the system. One can think of the model as supplying impulsive ''quantum kicks'' to a mode whose energy attempts to fall below its zero point value, a kind of ''Planck demon'' analogous to a Brownian-like random force. The model is illustrated by application to a model of CH overtone relaxation

  15. The Model of the Production Process for the Quality Management

    Directory of Open Access Journals (Sweden)

    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.

  16. Point-Mass Model for Nano-Patterning Using Dip-Pen Nanolithography (DPN

    Directory of Open Access Journals (Sweden)

    Seok-Won Kang

    2011-04-01

    Full Text Available Micro-cantilevers are frequently used as scanning probes and sensors in micro-electromechanical systems (MEMS. Usually micro-cantilever based sensors operate by detecting changes in cantilever vibration modes (e.g., bending or torsional vibration frequency or surface stresses - when a target analyte is adsorbed on the surface. The catalyst for chemical reactions (i.e., for a specific analyte can be deposited on micro-cantilevers by using Dip-Pen Nanolithography (DPN technique. In this study, we simulate the vibration mode in nano-patterning processes by using a Point-Mass Model (or Lumped Parameter Model. The results from the simulations are used to derive the stability of writing and reading mode for a particular driving frequency during the DPN process. In addition, we analyze the sensitivity of the tip-sample interaction forces in fluid (ink solution by utilizing the Derjaguin-Muller-Toporov (DMT contact theory.

  17. Mass measurement on the rp-process waiting point {sup 72}Kr

    Energy Technology Data Exchange (ETDEWEB)

    Rodriguez, D. [Gesellschaft fuer Schwerionenforschung mbH, Darmstadt (Germany); Kolhinen, V.S. [Jyvaeskylae Univ. (Finland); Audi, G. [CSNSM-IN2P3-Centre National de la Recherche Scientifique (CNRS), 91 - Orsay (FR)] [and others

    2004-06-01

    The mass of one of the three major waiting points in the astrophysical rp-process {sup 72}Kr was measured for the first time with the Penning trap mass spectrometer ISOLTRAP. The measurement yielded a relative mass uncertainty of {delta}m/m=1.2 x 10{sup -7} ({delta}m=8 keV). Other Kr isotopes, also needed for astrophysical calculations, were measured with more than one order of magnitude improved accuracy. We use the ISOLTRAP masses of{sup 72-74}Kr to reanalyze the role of the {sup 72}Kr waiting point in the rp-process during X-ray bursts. (orig.)

  18. Identification of Influential Points in a Linear Regression Model

    Directory of Open Access Journals (Sweden)

    Jan Grosz

    2011-03-01

    Full Text Available The article deals with the detection and identification of influential points in the linear regression model. Three methods of detection of outliers and leverage points are described. These procedures can also be used for one-sample (independentdatasets. This paper briefly describes theoretical aspects of several robust methods as well. Robust statistics is a powerful tool to increase the reliability and accuracy of statistical modelling and data analysis. A simulation model of the simple linear regression is presented.

  19. Marked point process framework for living probabilistic safety assessment and risk follow-up

    International Nuclear Information System (INIS)

    Arjas, Elja; Holmberg, Jan

    1995-01-01

    We construct a model for living probabilistic safety assessment (PSA) by applying the general framework of marked point processes. The framework provides a theoretically rigorous approach for considering risk follow-up of posterior hazards. In risk follow-up, the hazard of core damage is evaluated synthetically at time points in the past, by using some observed events as logged history and combining it with re-evaluated potential hazards. There are several alternatives for doing this, of which we consider three here, calling them initiating event approach, hazard rate approach, and safety system approach. In addition, for a comparison, we consider a core damage hazard arising in risk monitoring. Each of these four definitions draws attention to a particular aspect in risk assessment, and this is reflected in the behaviour of the consequent risk importance measures. Several alternative measures are again considered. The concepts and definitions are illustrated by a numerical example

  20. Parametric statistical change point analysis

    CERN Document Server

    Chen, Jie

    2000-01-01

    This work is an in-depth study of the change point problem from a general point of view and a further examination of change point analysis of the most commonly used statistical models Change point problems are encountered in such disciplines as economics, finance, medicine, psychology, signal processing, and geology, to mention only several The exposition is clear and systematic, with a great deal of introductory material included Different models are presented in each chapter, including gamma and exponential models, rarely examined thus far in the literature Other models covered in detail are the multivariate normal, univariate normal, regression, and discrete models Extensive examples throughout the text emphasize key concepts and different methodologies are used, namely the likelihood ratio criterion, and the Bayesian and information criterion approaches A comprehensive bibliography and two indices complete the study

  1. Modeling of Landslides with the Material Point Method

    DEFF Research Database (Denmark)

    Andersen, Søren Mikkel; Andersen, Lars

    2008-01-01

    A numerical model for studying the dynamic evolution of landslides is presented. The numerical model is based on the Generalized Interpolation Material Point Method. A simplified slope with a house placed on top is analysed. An elasto-plastic material model based on the Mohr-Coulomb yield criterion...

  2. Modelling of Landslides with the Material-point Method

    DEFF Research Database (Denmark)

    Andersen, Søren; Andersen, Lars

    2009-01-01

    A numerical model for studying the dynamic evolution of landslides is presented. The numerical model is based on the Generalized Interpolation Material Point Method. A simplified slope with a house placed on top is analysed. An elasto-plastic material model based on the Mohr-Coulomb yield criterion...

  3. A Unified Point Process Probabilistic Framework to Assess Heartbeat Dynamics and Autonomic Cardiovascular Control

    Directory of Open Access Journals (Sweden)

    Zhe eChen

    2012-02-01

    Full Text Available In recent years, time-varying inhomogeneous point process models have been introduced for assessment of instantaneous heartbeat dynamics as well as specific cardiovascular control mechanisms and hemodynamics. Assessment of the model's statistics is established through the Wiener-Volterra theory and a multivariate autoregressive (AR structure. A variety of instantaneous cardiovascular metrics, such as heart rate (HR, heart rate variability (HRV, respiratory sinus arrhythmia (RSA, and baroreceptor-cardiac reflex (baroreflex sensitivity (BRS, are derived within a parametric framework and instantaneously updated with adaptive and local maximum likelihood estimation algorithms. Inclusion of second order nonlinearities, with subsequent bispectral quantification in the frequency domain, further allows for definition of instantaneous metrics of nonlinearity. We here organize a comprehensive review of the devised methods as applied to experimental recordings from healthy subjects during propofol anesthesia. Collective results reveal interesting dynamic trends across the different pharmacological interventions operated within each anesthesia session, confirming the ability of the algorithm to track important changes in cardiorespiratory elicited interactions, and pointing at our mathematical approach as a promising monitoring tool for an accurate, noninvasive assessment in clinical practice.

  4. Nuclear structure and weak rates of heavy waiting point nuclei under rp-process conditions

    Science.gov (United States)

    Nabi, Jameel-Un; Böyükata, Mahmut

    2017-01-01

    The structure and the weak interaction mediated rates of the heavy waiting point (WP) nuclei 80Zr, 84Mo, 88Ru, 92Pd and 96Cd along N = Z line were studied within the interacting boson model-1 (IBM-1) and the proton-neutron quasi-particle random phase approximation (pn-QRPA). The energy levels of the N = Z WP nuclei were calculated by fitting the essential parameters of IBM-1 Hamiltonian and their geometric shapes were predicted by plotting potential energy surfaces (PESs). Half-lives, continuum electron capture rates, positron decay rates, electron capture cross sections of WP nuclei, energy rates of β-delayed protons and their emission probabilities were later calculated using the pn-QRPA. The calculated Gamow-Teller strength distributions were compared with previous calculation. We present positron decay and continuum electron capture rates on these WP nuclei under rp-process conditions using the same model. For the rp-process conditions, the calculated total weak rates are twice the Skyrme HF+BCS+QRPA rates for 80Zr. For remaining nuclei the two calculations compare well. The electron capture rates are significant and compete well with the corresponding positron decay rates under rp-process conditions. The finding of the present study supports that electron capture rates form an integral part of the weak rates under rp-process conditions and has an important role for the nuclear model calculations.

  5. Comparison of sparse point distribution models

    DEFF Research Database (Denmark)

    Erbou, Søren Gylling Hemmingsen; Vester-Christensen, Martin; Larsen, Rasmus

    2010-01-01

    This paper compares several methods for obtaining sparse and compact point distribution models suited for data sets containing many variables. These are evaluated on a database consisting of 3D surfaces of a section of the pelvic bone obtained from CT scans of 33 porcine carcasses. The superior m...

  6. DNA denaturation through a model of the partition points on a one-dimensional lattice

    International Nuclear Information System (INIS)

    Mejdani, R.; Huseini, H.

    1994-08-01

    We have shown that by using a model of the partition points gas on a one-dimensional lattice, we can study, besides the saturation curves obtained before for the enzyme kinetics, also the denaturation process, i.e. the breaking of the hydrogen bonds connecting the two strands, under treatment by heat of DNA. We think that this model, as a very simple model and mathematically transparent, can be advantageous for pedagogic goals or other theoretical investigations in chemistry or modern biology. (author). 29 refs, 4 figs

  7. HYDROLOGY AND SEDIMENT MODELING USING THE BASINS NON-POINT SOURCE MODEL

    Science.gov (United States)

    The Non-Point Source Model (Hydrologic Simulation Program-Fortran, or HSPF) within the EPA Office of Water's BASINS watershed modeling system was used to simulate streamflow and total suspended solids within Contentnea Creek, North Carolina, which is a tributary of the Neuse Rive...

  8. Multi-Model Adaptive Fuzzy Controller for a CSTR Process

    Directory of Open Access Journals (Sweden)

    Shubham Gogoria

    2015-09-01

    Full Text Available Continuous Stirred Tank Reactors are intensively used to control exothermic reactions in chemical industries. It is a very complex multi-variable system with non-linear characteristics. This paper deals with linearization of the mathematical model of a CSTR Process. Multi model adaptive fuzzy controller has been designed to control the reactor concentration and temperature of CSTR process. This method combines the output of multiple Fuzzy controllers, which are operated at various operating points. The proposed solution is a straightforward implementation of Fuzzy controller with gain scheduler to control the linearly inseparable parameters of a highly non-linear process.

  9. Modeling and measurement of boiling point elevation during water vaporization from aqueous urea for SCR applications

    International Nuclear Information System (INIS)

    Dan, Ho Jin; Lee, Joon Sik

    2016-01-01

    Understanding of water vaporization is the first step to anticipate the conversion process of urea into ammonia in the exhaust stream. As aqueous urea is a mixture and the urea in the mixture acts as a non-volatile solute, its colligative properties should be considered during water vaporization. The elevation of boiling point for urea water solution is measured with respect to urea mole fraction. With the boiling-point elevation relation, a model for water vaporization is proposed underlining the correction of the heat of vaporization of water in the urea water mixture due to the enthalpy of urea dissolution in water. The model is verified by the experiments of water vaporization as well. Finally, the water vaporization model is applied to the water vaporization of aqueous urea droplets. It is shown that urea decomposition can begin before water evaporation finishes due to the boiling-point elevation

  10. Modeling and measurement of boiling point elevation during water vaporization from aqueous urea for SCR applications

    Energy Technology Data Exchange (ETDEWEB)

    Dan, Ho Jin; Lee, Joon Sik [Seoul National University, Seoul (Korea, Republic of)

    2016-03-15

    Understanding of water vaporization is the first step to anticipate the conversion process of urea into ammonia in the exhaust stream. As aqueous urea is a mixture and the urea in the mixture acts as a non-volatile solute, its colligative properties should be considered during water vaporization. The elevation of boiling point for urea water solution is measured with respect to urea mole fraction. With the boiling-point elevation relation, a model for water vaporization is proposed underlining the correction of the heat of vaporization of water in the urea water mixture due to the enthalpy of urea dissolution in water. The model is verified by the experiments of water vaporization as well. Finally, the water vaporization model is applied to the water vaporization of aqueous urea droplets. It is shown that urea decomposition can begin before water evaporation finishes due to the boiling-point elevation.

  11. Doubly stochastic Poisson process models for precipitation at fine time-scales

    Science.gov (United States)

    Ramesh, Nadarajah I.; Onof, Christian; Xie, Dichao

    2012-09-01

    This paper considers a class of stochastic point process models, based on doubly stochastic Poisson processes, in the modelling of rainfall. We examine the application of this class of models, a neglected alternative to the widely-known Poisson cluster models, in the analysis of fine time-scale rainfall intensity. These models are mainly used to analyse tipping-bucket raingauge data from a single site but an extension to multiple sites is illustrated which reveals the potential of this class of models to study the temporal and spatial variability of precipitation at fine time-scales.

  12. CLINSULF sub-dew-point process for sulphur recovery

    Energy Technology Data Exchange (ETDEWEB)

    Heisel, M.; Marold, F.

    1988-01-01

    In a 2-reactor system, the CLINSULF process allows very high sulphur recovery rates. When operated at 100/sup 0/C at the outlet, i.e. below the sulphur solidification point, a sulphur recovery rate of more than 99.2% was achieved in a 2-reactor series. Assuming a 70% sulphur recovery in an upstream Claus furnace plus sulphur condenser, an overall sulphur recovery of more than 99.8% results for the 2-reactor system. This is approximately 2% higher than in conventional Claus plus SDP units, which mostly consist of 4 reactors or more. This means the the CLINSULF SSP process promises to be an improvement both in respect of efficiency and low investment cost.

  13. Sand Point, Alaska Tsunami Forecast Grids for MOST Model

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The Sand Point, Alaska Forecast Model Grids provides bathymetric data strictly for tsunami inundation modeling with the Method of Splitting Tsunami (MOST) model....

  14. Toke Point, Washington Tsunami Forecast Grids for MOST Model

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The Toke Point, Washington Forecast Model Grids provides bathymetric data strictly for tsunami inundation modeling with the Method of Splitting Tsunami (MOST) model....

  15. Digital analyzer for point processes based on first-in-first-out memories

    Science.gov (United States)

    Basano, Lorenzo; Ottonello, Pasquale; Schiavi, Enore

    1992-06-01

    We present an entirely new version of a multipurpose instrument designed for the statistical analysis of point processes, especially those characterized by high bunching. A long sequence of pulses can be recorded in the RAM bank of a personal computer via a suitably designed front end which employs a pair of first-in-first-out (FIFO) memories; these allow one to build an analyzer that, besides being simpler from the electronic point of view, is capable of sustaining much higher intensity fluctuations of the point process. The overflow risk of the device is evaluated by treating the FIFO pair as a queueing system. The apparatus was tested using both a deterministic signal and a sequence of photoelectrons obtained from laser light scattered by random surfaces.

  16. Efficient point cloud data processing in shipbuilding: Reformative component extraction method and registration method

    Directory of Open Access Journals (Sweden)

    Jingyu Sun

    2014-07-01

    Full Text Available To survive in the current shipbuilding industry, it is of vital importance for shipyards to have the ship components’ accuracy evaluated efficiently during most of the manufacturing steps. Evaluating components’ accuracy by comparing each component’s point cloud data scanned by laser scanners and the ship’s design data formatted in CAD cannot be processed efficiently when (1 extract components from point cloud data include irregular obstacles endogenously, or when (2 registration of the two data sets have no clear direction setting. This paper presents reformative point cloud data processing methods to solve these problems. K-d tree construction of the point cloud data fastens a neighbor searching of each point. Region growing method performed on the neighbor points of the seed point extracts the continuous part of the component, while curved surface fitting and B-spline curved line fitting at the edge of the continuous part recognize the neighbor domains of the same component divided by obstacles’ shadows. The ICP (Iterative Closest Point algorithm conducts a registration of the two sets of data after the proper registration’s direction is decided by principal component analysis. By experiments conducted at the shipyard, 200 curved shell plates are extracted from the scanned point cloud data, and registrations are conducted between them and the designed CAD data using the proposed methods for an accuracy evaluation. Results show that the methods proposed in this paper support the accuracy evaluation targeted point cloud data processing efficiently in practice.

  17. Zero-point energy in bag models

    International Nuclear Information System (INIS)

    Milton, K.A.

    1979-01-01

    The zero-point (Casimir) energy of free vector (gluon) fields confined to a spherical cavity (bag) is computed. With a suitable renormalization the result for eight gluons is E = + 0.51/a. This result is substantially larger than that for a spherical shell (where both interior and exterior modes are present), and so affects Johnson's model of the QCD vacuum. It is also smaller than, and of opposite sign to, the value used in bag model phenomenology, so it will have important implications there. 1 figure

  18. Point kinetics model with one-dimensional (radial) heat conduction formalism

    International Nuclear Information System (INIS)

    Jain, V.K.

    1989-01-01

    A point-kinetics model with one-dimensional (radial) heat conduction formalism has been developed. The heat conduction formalism is based on corner-mesh finite difference method. To get average temperatures in various conducting regions, a novel weighting scheme has been devised. The heat conduction model has been incorporated in the point-kinetics code MRTF-FUEL. The point-kinetics equations are solved using the method of real integrating factors. It has been shown by analysing the simulation of hypothetical loss of regulation accident in NAPP reactor that the model is superior to the conventional one in accuracy and speed of computation. (author). 3 refs., 3 tabs

  19. PARALLEL PROCESSING OF BIG POINT CLOUDS USING Z-ORDER-BASED PARTITIONING

    Directory of Open Access Journals (Sweden)

    C. Alis

    2016-06-01

    Full Text Available As laser scanning technology improves and costs are coming down, the amount of point cloud data being generated can be prohibitively difficult and expensive to process on a single machine. This data explosion is not only limited to point cloud data. Voluminous amounts of high-dimensionality and quickly accumulating data, collectively known as Big Data, such as those generated by social media, Internet of Things devices and commercial transactions, are becoming more prevalent as well. New computing paradigms and frameworks are being developed to efficiently handle the processing of Big Data, many of which utilize a compute cluster composed of several commodity grade machines to process chunks of data in parallel. A central concept in many of these frameworks is data locality. By its nature, Big Data is large enough that the entire dataset would not fit on the memory and hard drives of a single node hence replicating the entire dataset to each worker node is impractical. The data must then be partitioned across worker nodes in a manner that minimises data transfer across the network. This is a challenge for point cloud data because there exist different ways to partition data and they may require data transfer. We propose a partitioning based on Z-order which is a form of locality-sensitive hashing. The Z-order or Morton code is computed by dividing each dimension to form a grid then interleaving the binary representation of each dimension. For example, the Z-order code for the grid square with coordinates (x = 1 = 012, y = 3 = 112 is 10112 = 11. The number of points in each partition is controlled by the number of bits per dimension: the more bits, the fewer the points. The number of bits per dimension also controls the level of detail with more bits yielding finer partitioning. We present this partitioning method by implementing it on Apache Spark and investigating how different parameters affect the accuracy and running time of the k nearest

  20. Modeling post-wildfire hydrological processes with ParFlow

    Science.gov (United States)

    Escobar, I. S.; Lopez, S. R.; Kinoshita, A. M.

    2017-12-01

    Wildfires alter the natural processes within a watershed, such as surface runoff, evapotranspiration rates, and subsurface water storage. Post-fire hydrologic models are typically one-dimensional, empirically-based models or two-dimensional, conceptually-based models with lumped parameter distributions. These models are useful for modeling and predictions at the watershed outlet; however, do not provide detailed, distributed hydrologic processes at the point scale within the watershed. This research uses ParFlow, a three-dimensional, distributed hydrologic model to simulate post-fire hydrologic processes by representing the spatial and temporal variability of soil burn severity (via hydrophobicity) and vegetation recovery. Using this approach, we are able to evaluate the change in post-fire water components (surface flow, lateral flow, baseflow, and evapotranspiration). This work builds upon previous field and remote sensing analysis conducted for the 2003 Old Fire Burn in Devil Canyon, located in southern California (USA). This model is initially developed for a hillslope defined by a 500 m by 1000 m lateral extent. The subsurface reaches 12.4 m and is assigned a variable cell thickness to explicitly consider soil burn severity throughout the stages of recovery and vegetation regrowth. We consider four slope and eight hydrophobic layer configurations. Evapotranspiration is used as a proxy for vegetation regrowth and is represented by the satellite-based Simplified Surface Energy Balance (SSEBOP) product. The pre- and post-fire surface runoff, subsurface storage, and surface storage interactions are evaluated at the point scale. Results will be used as a basis for developing and fine-tuning a watershed-scale model. Long-term simulations will advance our understanding of post-fire hydrological partitioning between water balance components and the spatial variability of watershed processes, providing improved guidance for post-fire watershed management. In reference

  1. Modelling and control of a flotation process

    International Nuclear Information System (INIS)

    Ding, L.; Gustafsson, T.

    1999-01-01

    A general description of a flotation process is given. The dynamic model of a MIMO nonlinear subprocess in flotation, i. e. the pulp levels in five compartments in series is developed and the model is verified with real data from a production plant. In order to reject constant disturbances five extra states are introduced and the model is modified. An exact linearization has been made for the non-linear model and a linear quadratic gaussian controller is proposed based on the linearized model. The simulation result shows an improved performance of the pulp level control when the set points are changed or a disturbance occur. In future the controller will be tested in production. (author)

  2. On statistical analysis of compound point process

    Czech Academy of Sciences Publication Activity Database

    Volf, Petr

    2006-01-01

    Roč. 35, 2-3 (2006), s. 389-396 ISSN 1026-597X R&D Projects: GA ČR(CZ) GA402/04/1294 Institutional research plan: CEZ:AV0Z10750506 Keywords : counting process * compound process * hazard function * Cox -model Subject RIV: BB - Applied Statistics, Operational Research

  3. On the (R,s,Q) Inventory Model when Demand is Modelled as a Compound Process

    NARCIS (Netherlands)

    Janssen, F.B.S.L.P.; Heuts, R.M.J.; de Kok, T.

    1996-01-01

    In this paper we present an approximation method to compute the reorder point s in a (R; s; Q) inventory model with a service level restriction, where demand is modelled as a compound Bernoulli process, that is, with a xed probability there is positive demand during a time unit, otherwise demand is

  4. Customer Order Decoupling Point Selection Model in Mass Customization Based on MAS

    Institute of Scientific and Technical Information of China (English)

    XU Xuanguo; LI Xiangyang

    2006-01-01

    Mass customization relates to the ability of providing individually designed products or services to customer with high process flexibility or integration. Literatures on mass customization have been focused on mechanism of MC, but little on customer order decoupling point selection. The aim of this paper is to present a model for customer order decoupling point selection of domain knowledge interactions between enterprises and customers in mass customization. Based on the analysis of other researchers' achievements combining the demand problems of customer and enterprise, a model of group decision for customer order decoupling point selection is constructed based on quality function deployment and multi-agent system. Considering relatively the decision makers of independent functional departments as independent decision agents, a decision agent set is added as the third dimensionality to house of quality, the cubic quality function deployment is formed. The decision-making can be consisted of two procedures: the first one is to build each plane house of quality in various functional departments to express each opinions; the other is to evaluate and gather the foregoing sub-decisions by a new plane quality function deployment. Thus, department decision-making can well use its domain knowledge by ontology, and total decision-making can keep simple by avoiding too many customer requirements.

  5. Cutting force model for high speed machining process

    International Nuclear Information System (INIS)

    Haber, R. E.; Jimenez, J. E.; Jimenez, A.; Lopez-Coronado, J.

    2004-01-01

    This paper presents cutting force-based models able to describe a high speed machining process. The model considers the cutting force as output variable, essential for the physical processes that are taking place in high speed machining. Moreover, this paper shows the mathematical development to derive the integral-differential equations, and the algorithms implemented in MATLAB to predict the cutting force in real time MATLAB is a software tool for doing numerical computations with matrices and vectors. It can also display information graphically and includes many toolboxes for several research and applications areas. Two end mill shapes are considered (i. e. cylindrical and ball end mill) for real-time implementation of the developed algorithms. the developed models are validated in slot milling operations. The results corroborate the importance of the cutting force variable for predicting tool wear in high speed machining operations. The developed models are the starting point for future work related with vibration analysis, process stability and dimensional surface finish in high speed machining processes. (Author) 19 refs

  6. Point-Structured Human Body Modeling Based on 3D Scan Data

    Directory of Open Access Journals (Sweden)

    Ming-June Tsai

    2018-01-01

    Full Text Available A novel point-structured geometrical modelling for realistic human body is introduced in this paper. This technique is based on the feature extraction from the 3D body scan data. Anatomic feature such as the neck, the arm pits, the crotch points, and other major feature points are recognized. The body data is then segmented into 6 major parts. A body model is then constructed by re-sampling the scanned data to create a point-structured mesh. The body model contains body geodetic landmarks in latitudinal and longitudinal curves passing through those feature points. The body model preserves the perfect body shape and all the body dimensions but requires little space. Therefore, the body model can be used as a mannequin in garment industry, or as a manikin in various human factor designs, but the most important application is to use as a virtue character to animate the body motion in mocap (motion capture systems. By adding suitable joint freedoms between the segmented body links, kinematic and dynamic properties of the motion theories can be applied to the body model. As a result, a 3D virtual character that is fully resembled the original scanned individual is vividly animating the body motions. The gaps between the body segments due to motion can be filled up by skin blending technique using the characteristic of the point-structured model. The model has the potential to serve as a standardized datatype to archive body information for all custom-made products.

  7. Analysis of residual stress state in sheet metal parts processed by single point incremental forming

    Science.gov (United States)

    Maaß, F.; Gies, S.; Dobecki, M.; Brömmelhoff, K.; Tekkaya, A. E.; Reimers, W.

    2018-05-01

    The mechanical properties of formed metal components are highly affected by the prevailing residual stress state. A selective induction of residual compressive stresses in the component, can improve the product properties such as the fatigue strength. By means of single point incremental forming (SPIF), the residual stress state can be influenced by adjusting the process parameters during the manufacturing process. To achieve a fundamental understanding of the residual stress formation caused by the SPIF process, a valid numerical process model is essential. Within the scope of this paper the significance of kinematic hardening effects on the determined residual stress state is presented based on numerical simulations. The effect of the unclamping step after the manufacturing process is also analyzed. An average deviation of the residual stress amplitudes in the clamped and unclamped condition of 18 % reveals, that the unclamping step needs to be considered to reach a high numerical prediction quality.

  8. 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

  9. ALTERNATIVE METHODOLOGIES FOR THE ESTIMATION OF LOCAL POINT DENSITY INDEX: MOVING TOWARDS ADAPTIVE LIDAR DATA PROCESSING

    Directory of Open Access Journals (Sweden)

    Z. Lari

    2012-07-01

    Full Text Available Over the past few years, LiDAR systems have been established as a leading technology for the acquisition of high density point clouds over physical surfaces. These point clouds will be processed for the extraction of geo-spatial information. Local point density is one of the most important properties of the point cloud that highly affects the performance of data processing techniques and the quality of extracted information from these data. Therefore, it is necessary to define a standard methodology for the estimation of local point density indices to be considered for the precise processing of LiDAR data. Current definitions of local point density indices, which only consider the 2D neighbourhood of individual points, are not appropriate for 3D LiDAR data and cannot be applied for laser scans from different platforms. In order to resolve the drawbacks of these methods, this paper proposes several approaches for the estimation of the local point density index which take the 3D relationship among the points and the physical properties of the surfaces they belong to into account. In the simplest approach, an approximate value of the local point density for each point is defined while considering the 3D relationship among the points. In the other approaches, the local point density is estimated by considering the 3D neighbourhood of the point in question and the physical properties of the surface which encloses this point. The physical properties of the surfaces enclosing the LiDAR points are assessed through eigen-value analysis of the 3D neighbourhood of individual points and adaptive cylinder methods. This paper will discuss these approaches and highlight their impact on various LiDAR data processing activities (i.e., neighbourhood definition, region growing, segmentation, boundary detection, and classification. Experimental results from airborne and terrestrial LiDAR data verify the efficacy of considering local point density variation for

  10. Flat Knitting Loop Deformation Simulation Based on Interlacing Point Model

    Directory of Open Access Journals (Sweden)

    Jiang Gaoming

    2017-12-01

    Full Text Available In order to create realistic loop primitives suitable for the faster CAD of the flat-knitted fabric, we have performed research on the model of the loop as well as the variation of the loop surface. This paper proposes an interlacing point-based model for the loop center curve, and uses the cubic Bezier curve to fit the central curve of the regular loop, elongated loop, transfer loop, and irregular deformed loop. In this way, a general model for the central curve of the deformed loop is obtained. The obtained model is then utilized to perform texture mapping, texture interpolation, and brightness processing, simulating a clearly structured and lifelike deformed loop. The computer program LOOP is developed by using the algorithm. The deformed loop is simulated with different yarns, and the deformed loop is applied to design of a cable stitch, demonstrating feasibility of the proposed algorithm. This paper provides a loop primitive simulation method characterized by lifelikeness, yarn material variability, and deformation flexibility, and facilitates the loop-based fast computer-aided design (CAD of the knitted fabric.

  11. Bridging the gap between a stationary point process and its Palm distribution

    NARCIS (Netherlands)

    Nieuwenhuis, G.

    1994-01-01

    In the context of stationary point processes measurements are usually made from a time point chosen at random or from an occurrence chosen at random. That is, either the stationary distribution P or its Palm distribution P° is the ruling probability measure. In this paper an approach is presented to

  12. Retort process modelling for Indian traditional foods.

    Science.gov (United States)

    Gokhale, S V; Lele, S S

    2014-11-01

    Indian traditional staple and snack food is typically a heterogeneous recipe that incorporates varieties of vegetables, lentils and other ingredients. Modelling the retorting process of multilayer pouch packed Indian food was achieved using lumped-parameter approach. A unified model is proposed to estimate cold point temperature. Initial process conditions, retort temperature and % solid content were the significantly affecting independent variables. A model was developed using combination of vegetable solids and water, which was then validated using four traditional Indian vegetarian products: Pulav (steamed rice with vegetables), Sambar (south Indian style curry containing mixed vegetables and lentils), Gajar Halawa (carrot based sweet product) and Upama (wheat based snack product). The predicted and experimental values of temperature profile matched with ±10 % error which is a good match considering the food was a multi component system. Thus the model will be useful as a tool to reduce number of trials required to optimize retorting of various Indian traditional vegetarian foods.

  13. On estimation of the intensity function of a point process

    NARCIS (Netherlands)

    Lieshout, van M.N.M.

    2010-01-01

    Abstract. Estimation of the intensity function of spatial point processes is a fundamental problem. In this paper, we interpret the Delaunay tessellation field estimator recently introduced by Schaap and Van de Weygaert as an adaptive kernel estimator and give explicit expressions for the mean and

  14. Modeling of Maximum Power Point Tracking Controller for Solar Power System

    Directory of Open Access Journals (Sweden)

    Aryuanto Soetedjo

    2012-09-01

    Full Text Available In this paper, a Maximum Power Point Tracking (MPPT controller for solar power system is modeled using MATLAB Simulink. The model consists of PV module, buck converter, and MPPT controller. The contribution of the work is in the modeling of buck converter that allowing the input voltage of the converter, i.e. output voltage of PV is changed by varying the duty cycle, so that the maximum power point could be tracked when the environmental changes. The simulation results show that the developed model performs well in tracking the maximum power point (MPP of the PV module using Perturb and Observe (P&O Algorithm.

  15. Interevent Time Distribution of Renewal Point Process, Case Study: Extreme Rainfall in South Sulawesi

    Science.gov (United States)

    Sunusi, Nurtiti

    2018-03-01

    The study of time distribution of occurrences of extreme rain phenomena plays a very important role in the analysis and weather forecast in an area. The timing of extreme rainfall is difficult to predict because its occurrence is random. This paper aims to determine the inter event time distribution of extreme rain events and minimum waiting time until the occurrence of next extreme event through a point process approach. The phenomenon of extreme rain events over a given period of time is following a renewal process in which the time for events is a random variable τ. The distribution of random variable τ is assumed to be a Pareto, Log Normal, and Gamma. To estimate model parameters, a moment method is used. Consider Rt as the time of the last extreme rain event at one location is the time difference since the last extreme rainfall event. if there are no extreme rain events up to t 0, there will be an opportunity for extreme rainfall events at (t 0, t 0 + δt 0). Furthermore from the three models reviewed, the minimum waiting time until the next extreme rainfall will be determined. The result shows that Log Nrmal model is better than Pareto and Gamma model for predicting the next extreme rainfall in South Sulawesi while the Pareto model can not be used.

  16. Sample size and classification error for Bayesian change-point models with unlabelled sub-groups and incomplete follow-up.

    Science.gov (United States)

    White, Simon R; Muniz-Terrera, Graciela; Matthews, Fiona E

    2018-05-01

    Many medical (and ecological) processes involve the change of shape, whereby one trajectory changes into another trajectory at a specific time point. There has been little investigation into the study design needed to investigate these models. We consider the class of fixed effect change-point models with an underlying shape comprised two joined linear segments, also known as broken-stick models. We extend this model to include two sub-groups with different trajectories at the change-point, a change and no change class, and also include a missingness model to account for individuals with incomplete follow-up. Through a simulation study, we consider the relationship of sample size to the estimates of the underlying shape, the existence of a change-point, and the classification-error of sub-group labels. We use a Bayesian framework to account for the missing labels, and the analysis of each simulation is performed using standard Markov chain Monte Carlo techniques. Our simulation study is inspired by cognitive decline as measured by the Mini-Mental State Examination, where our extended model is appropriate due to the commonly observed mixture of individuals within studies who do or do not exhibit accelerated decline. We find that even for studies of modest size ( n = 500, with 50 individuals observed past the change-point) in the fixed effect setting, a change-point can be detected and reliably estimated across a range of observation-errors.

  17. Point Reyes, California Tsunami Forecast Grids for MOST Model

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The Point Reyes, California Forecast Model Grids provides bathymetric data strictly for tsunami inundation modeling with the Method of Splitting Tsunami (MOST)...

  18. A Companion Model Approach to Modelling and Simulation of Industrial Processes

    International Nuclear Information System (INIS)

    Juslin, K.

    2005-09-01

    Modelling and simulation provides for huge possibilities if broadly taken up by engineers as a working method. However, when considering the launching of modelling and simulation tools in an engineering design project, they shall be easy to learn and use. Then, there is no time to write equations, to consult suppliers' experts, or to manually transfer data from one tool to another. The answer seems to be in the integration of easy to use and dependable simulation software with engineering tools. Accordingly, the modelling and simulation software shall accept as input such structured design information on industrial unit processes and their connections, as provided for by e.g. CAD software and product databases. The software technology, including required specification and communication standards, is already available. Internet based service repositories make it possible for equipment manufacturers to supply 'extended products', including such design data as needed by engineers engaged in process and automation integration. There is a market niche evolving for simulation service centres, operating in co-operation with project consultants, equipment manufacturers, process integrators, automation designers, plant operating personnel, and maintenance centres. The companion model approach for specification and solution of process simulation models, as presented herein, is developed from the above premises. The focus is on how to tackle real world processes, which from the modelling point of view are heterogeneous, dynamic, very stiff, very nonlinear and only piece vice continuous, without extensive manual interventions of human experts. An additional challenge, to solve the arising equations fast and reliable, is dealt with, as well. (orig.)

  19. Application of random-point processes to the detection of radiation sources

    International Nuclear Information System (INIS)

    Woods, J.W.

    1978-01-01

    In this report the mathematical theory of random-point processes is reviewed and it is shown how use of the theory can obtain optimal solutions to the problem of detecting radiation sources. As noted, the theory also applies to image processing in low-light-level or low-count-rate situations. Paralleling Snyder's work, the theory is extended to the multichannel case of a continuous, two-dimensional (2-D), energy-time space. This extension essentially involves showing that the data are doubly stochastic Poisson (DSP) point processes in energy as well as time. Further, a new 2-D recursive formulation is presented for the radiation-detection problem with large computational savings over nonrecursive techniques when the number of channels is large (greater than or equal to 30). Finally, some adaptive strategies for on-line ''learning'' of unknown, time-varying signal and background-intensity parameters and statistics are present and discussed. These adaptive procedures apply when a complete statistical description is not available a priori

  20. Improved point-kinetics model for the BWR control rod drop accident

    International Nuclear Information System (INIS)

    Neogy, P.; Wakabayashi, T.; Carew, J.F.

    1985-01-01

    A simple prescription to account for spatial feedback weighting effects in RDA (rod drop accident) point-kinetics analyses has been derived and tested. The point-kinetics feedback model is linear in the core peaking factor, F/sub Q/, and in the core average void fraction and fuel temperature. Comparison with detailed spatial kinetics analyses indicates that the improved point-kinetics model provides an accurate description of the BWR RDA

  1. Mathematical modeling of biomass fuels formation process

    International Nuclear Information System (INIS)

    Gaska, Krzysztof; Wandrasz, Andrzej J.

    2008-01-01

    The increasing demand for thermal and electric energy in many branches of industry and municipal management accounts for a drastic diminishing of natural resources (fossil fuels). Meanwhile, in numerous technical processes, a huge mass of wastes is produced. A segregated and converted combustible fraction of the wastes, with relatively high calorific value, may be used as a component of formed fuels. The utilization of the formed fuel components from segregated groups of waste in associated processes of co-combustion with conventional fuels causes significant savings resulting from partial replacement of fossil fuels, and reduction of environmental pollution resulting directly from the limitation of waste migration to the environment (soil, atmospheric air, surface and underground water). The realization of technological processes with the utilization of formed fuel in associated thermal systems should be qualified by technical criteria, which means that elementary processes as well as factors of sustainable development, from a global viewpoint, must not be disturbed. The utilization of post-process waste should be preceded by detailed technical, ecological and economic analyses. In order to optimize the mixing process of fuel components, a mathematical model of the forming process was created. The model is defined as a group of data structures which uniquely identify a real process and conversion of this data in algorithms based on a problem of linear programming. The paper also presents the optimization of parameters in the process of forming fuels using a modified simplex algorithm with a polynomial worktime. This model is a datum-point in the numerical modeling of real processes, allowing a precise determination of the optimal elementary composition of formed fuels components, with assumed constraints and decision variables of the task

  2. From Point Clouds to Building Information Models: 3D Semi-Automatic Reconstruction of Indoors of Existing Buildings

    Directory of Open Access Journals (Sweden)

    Hélène Macher

    2017-10-01

    Full Text Available The creation of as-built Building Information Models requires the acquisition of the as-is state of existing buildings. Laser scanners are widely used to achieve this goal since they permit to collect information about object geometry in form of point clouds and provide a large amount of accurate data in a very fast way and with a high level of details. Unfortunately, the scan-to-BIM (Building Information Model process remains currently largely a manual process which is time consuming and error-prone. In this paper, a semi-automatic approach is presented for the 3D reconstruction of indoors of existing buildings from point clouds. Several segmentations are performed so that point clouds corresponding to grounds, ceilings and walls are extracted. Based on these point clouds, walls and slabs of buildings are reconstructed and described in the IFC format in order to be integrated into BIM software. The assessment of the approach is proposed thanks to two datasets. The evaluation items are the degree of automation, the transferability of the approach and the geometric quality of results of the 3D reconstruction. Additionally, quality indexes are introduced to inspect the results in order to be able to detect potential errors of reconstruction.

  3. AKaplan-Meier estimators of distance distributions for spatial point processes

    NARCIS (Netherlands)

    Baddeley, A.J.; Gill, R.D.

    1997-01-01

    When a spatial point process is observed through a bounded window, edge effects hamper the estimation of characteristics such as the empty space function $F$, the nearest neighbour distance distribution $G$, and the reduced second order moment function $K$. Here we propose and study product-limit

  4. Deep inelastic processes and the parton model

    International Nuclear Information System (INIS)

    Altarelli, G.

    The lecture was intended as an elementary introduction to the physics of deep inelastic phenomena from the point of view of theory. General formulae and facts concerning inclusive deep inelastic processes in the form: l+N→l'+hadrons (electroproduction, neutrino scattering) are first recalled. The deep inelastic annihilation e + e - →hadrons is then envisaged. The light cone approach, the parton model and their relation are mainly emphasized

  5. Near-infrared spectroscopic monitoring of a series of industrial batch processes using a bilinear grey model

    OpenAIRE

    Van Sprang, ENM; Ramaker, HJ; Westerhuis, JA; Smilde, AK; Gurden, SP; Wienke, D

    2003-01-01

    A good process understanding is the foundation for process optimization, process monitoring, end-point detection, and estimation of the end-product quality. Performing good process measurements and the construction of process models will contribute to a better process understanding. To improve the process knowledge it is common to build process models. These models are often based on first principles such as kinetic rates or mass balances. These types of models are also known as hard or white...

  6. The Investigation of Accuracy of 3 Dimensional Models Generated From Point Clouds with Terrestrial Laser Scanning

    Science.gov (United States)

    Gumus, Kutalmis; Erkaya, Halil

    2013-04-01

    In Terrestrial laser scanning (TLS) applications, it is necessary to take into consideration the conditions that affect the scanning process, especially the general characteristics of the laser scanner, geometric properties of the scanned object (shape, size, etc.), and its spatial location in the environment. Three dimensional models obtained with TLS, allow determining the geometric features and relevant magnitudes of the scanned object in an indirect way. In order to compare the spatial location and geometric accuracy of the 3-dimensional model created by Terrestrial laser scanning, it is necessary to use measurement tools that give more precise results than TLS. Geometric comparisons are performed by analyzing the differences between the distances, the angles between surfaces and the measured values taken from cross-sections between the data from the 3-dimensional model created with TLS and the values measured by other measurement devices The performance of the scanners, the size and shape of the scanned objects are tested using reference objects the sizes of which are determined with high precision. In this study, the important points to consider when choosing reference objects were highlighted. The steps up to processing the point clouds collected by scanning, regularizing these points and modeling in 3 dimensions was presented visually. In order to test the geometric correctness of the models obtained by Terrestrial laser scanners, sample objects with simple geometric shapes such as cubes, rectangular prisms and cylinders that are made of concrete were used as reference models. Three dimensional models were generated by scanning these reference models with Trimble Mensi GS 100. The dimension of the 3D model that is created from point clouds was compared with the precisely measured dimensions of the reference objects. For this purpose, horizontal and vertical cross-sections were taken from the reference objects and generated 3D models and the proximity of

  7. The Comparison of Point Data Models for the Output of WRF Hydro Model in the IDV

    Science.gov (United States)

    Ho, Y.; Weber, J.

    2017-12-01

    WRF Hydro netCDF output files contain streamflow, flow depth, longitude, latitude, altitude and stream order values for each forecast point. However, the data are not CF compliant. The total number of forecast points for the US CONUS is approximately 2.7 million and it is a big challenge for any visualization and analysis tool. The IDV point cloud display shows point data as a set of points colored by parameter. This display is very efficient compared to a standard point type display for rendering a large number of points. The one problem we have is that the data I/O can be a bottleneck issue when dealing with a large collection of point input files. In this presentation, we will experiment with different point data models and their APIs to access the same WRF Hydro model output. The results will help us construct a CF compliant netCDF point data format for the community.

  8. Determination of the Number of Fixture Locating Points for Sheet Metal By Grey Model

    Directory of Open Access Journals (Sweden)

    Yang Bo

    2017-01-01

    Full Text Available In the process of the traditional fixture design for sheet metal part based on the "N-2-1" locating principle, the number of fixture locating points is determined by trial and error or the experience of the designer. To that end, a new design method based on grey theory is proposed to determine the number of sheet metal fixture locating points in this paper. Firstly, the training sample set is generated by Latin hypercube sampling (LHS and finite element analysis (FEA. Secondly, the GM(1, 1 grey model is constructed based on the established training sample set to approximate the mapping relationship between the number of fixture locating points and the concerned sheet metal maximum deformation. Thirdly, the final number of fixture locating points for sheet metal can be inversely calculated under the allowable maximum deformation. Finally, a sheet metal case is conducted and the results indicate that the proposed approach is effective and efficient in determining the number of fixture locating points for sheet metal.

  9. Simple computation of reaction–diffusion processes on point clouds

    KAUST Repository

    Macdonald, Colin B.

    2013-05-20

    The study of reaction-diffusion processes is much more complicated on general curved surfaces than on standard Cartesian coordinate spaces. Here we show how to formulate and solve systems of reaction-diffusion equations on surfaces in an extremely simple way, using only the standard Cartesian form of differential operators, and a discrete unorganized point set to represent the surface. Our method decouples surface geometry from the underlying differential operators. As a consequence, it becomes possible to formulate and solve rather general reaction-diffusion equations on general surfaces without having to consider the complexities of differential geometry or sophisticated numerical analysis. To illustrate the generality of the method, computations for surface diffusion, pattern formation, excitable media, and bulk-surface coupling are provided for a variety of complex point cloud surfaces.

  10. Simple computation of reaction–diffusion processes on point clouds

    KAUST Repository

    Macdonald, Colin B.; Merriman, Barry; Ruuth, Steven J.

    2013-01-01

    The study of reaction-diffusion processes is much more complicated on general curved surfaces than on standard Cartesian coordinate spaces. Here we show how to formulate and solve systems of reaction-diffusion equations on surfaces in an extremely simple way, using only the standard Cartesian form of differential operators, and a discrete unorganized point set to represent the surface. Our method decouples surface geometry from the underlying differential operators. As a consequence, it becomes possible to formulate and solve rather general reaction-diffusion equations on general surfaces without having to consider the complexities of differential geometry or sophisticated numerical analysis. To illustrate the generality of the method, computations for surface diffusion, pattern formation, excitable media, and bulk-surface coupling are provided for a variety of complex point cloud surfaces.

  11. Mean-field inference of Hawkes point processes

    International Nuclear Information System (INIS)

    Bacry, Emmanuel; Gaïffas, Stéphane; Mastromatteo, Iacopo; Muzy, Jean-François

    2016-01-01

    We propose a fast and efficient estimation method that is able to accurately recover the parameters of a d-dimensional Hawkes point-process from a set of observations. We exploit a mean-field approximation that is valid when the fluctuations of the stochastic intensity are small. We show that this is notably the case in situations when interactions are sufficiently weak, when the dimension of the system is high or when the fluctuations are self-averaging due to the large number of past events they involve. In such a regime the estimation of a Hawkes process can be mapped on a least-squares problem for which we provide an analytic solution. Though this estimator is biased, we show that its precision can be comparable to the one of the maximum likelihood estimator while its computation speed is shown to be improved considerably. We give a theoretical control on the accuracy of our new approach and illustrate its efficiency using synthetic datasets, in order to assess the statistical estimation error of the parameters. (paper)

  12. Dissipative N-point-vortex Models in the Plane

    Science.gov (United States)

    Shashikanth, Banavara N.

    2010-02-01

    A method is presented for constructing point vortex models in the plane that dissipate the Hamiltonian function at any prescribed rate and yet conserve the level sets of the invariants of the Hamiltonian model arising from the SE (2) symmetries. The method is purely geometric in that it uses the level sets of the Hamiltonian and the invariants to construct the dissipative field and is based on elementary classical geometry in ℝ3. Extension to higher-dimensional spaces, such as the point vortex phase space, is done using exterior algebra. The method is in fact general enough to apply to any smooth finite-dimensional system with conserved quantities, and, for certain special cases, the dissipative vector field constructed can be associated with an appropriately defined double Nambu-Poisson bracket. The most interesting feature of this method is that it allows for an infinite sequence of such dissipative vector fields to be constructed by repeated application of a symmetric linear operator (matrix) at each point of the intersection of the level sets.

  13. Three-dimensional point-cloud room model in room acoustics simulations

    DEFF Research Database (Denmark)

    Markovic, Milos; Olesen, Søren Krarup; Hammershøi, Dorte

    2013-01-01

    acquisition and its representation with a 3D point-cloud model, as well as utilization of such a model for the room acoustics simulations. A room is scanned with a commercially available input device (Kinect for Xbox360) in two different ways; the first one involves the device placed in the middle of the room...... and rotated around the vertical axis while for the second one the device is moved within the room. Benefits of both approaches were analyzed. The device's depth sensor provides a set of points in a three-dimensional coordinate system which represents scanned surfaces of the room interior. These data are used...... to build a 3D point-cloud model of the room. Several models are created to meet requirements of different room acoustics simulation algorithms: plane fitting and uniform voxel grid for geometric methods and triangulation mesh for the numerical methods. Advantages of the proposed method over the traditional...

  14. Three-dimensional point-cloud room model for room acoustics simulations

    DEFF Research Database (Denmark)

    Markovic, Milos; Olesen, Søren Krarup; Hammershøi, Dorte

    2013-01-01

    acquisition and its representation with a 3D point-cloud model, as well as utilization of such a model for the room acoustics simulations. A room is scanned with a commercially available input device (Kinect for Xbox360) in two different ways; the first one involves the device placed in the middle of the room...... and rotated around the vertical axis while for the second one the device is moved within the room. Benefits of both approaches were analyzed. The device's depth sensor provides a set of points in a three-dimensional coordinate system which represents scanned surfaces of the room interior. These data are used...... to build a 3D point-cloud model of the room. Several models are created to meet requirements of different room acoustics simulation algorithms: plane fitting and uniform voxel grid for geometric methods and triangulation mesh for the numerical methods. Advantages of the proposed method over the traditional...

  15. Flash-Point prediction for binary partially miscible aqueous-organic mixtures

    OpenAIRE

    Liaw, Horng-Jang; Chen, Chien Tsun; Gerbaud, Vincent

    2008-01-01

    Flash point is the most important variable used to characterize fire and explosion hazard of liquids. Herein, partially miscible mixtures are presented within the context of liquid-liquid extraction processes and heterogeneous distillation processes. This paper describes development of a model for predicting the flash point of binary partially miscible mixtures of aqueous-organic system. To confirm the predictive efficiency of the derived flash points, the model was verified by comparing the ...

  16. Extracting valley-ridge lines from point-cloud-based 3D fingerprint models.

    Science.gov (United States)

    Pang, Xufang; Song, Zhan; Xie, Wuyuan

    2013-01-01

    3D fingerprinting is an emerging technology with the distinct advantage of touchless operation. More important, 3D fingerprint models contain more biometric information than traditional 2D fingerprint images. However, current approaches to fingerprint feature detection usually must transform the 3D models to a 2D space through unwrapping or other methods, which might introduce distortions. A new approach directly extracts valley-ridge features from point-cloud-based 3D fingerprint models. It first applies the moving least-squares method to fit a local paraboloid surface and represent the local point cloud area. It then computes the local surface's curvatures and curvature tensors to facilitate detection of the potential valley and ridge points. The approach projects those points to the most likely valley-ridge lines, using statistical means such as covariance analysis and cross correlation. To finally extract the valley-ridge lines, it grows the polylines that approximate the projected feature points and removes the perturbations between the sampled points. Experiments with different 3D fingerprint models demonstrate this approach's feasibility and performance.

  17. A New Blind Pointing Model Improves Large Reflector Antennas Precision Pointing at Ka-Band (32 GHz)

    Science.gov (United States)

    Rochblatt, David J.

    2009-01-01

    The National Aeronautics and Space Administration (NASA), Jet Propulsion Laboratory (JPL)-Deep Space Network (DSN) subnet of 34-m Beam Waveguide (BWG) Antennas was recently upgraded with Ka-Band (32-GHz) frequency feeds for space research and communication. For normal telemetry tracking a Ka-Band monopulse system is used, which typically yields 1.6-mdeg mean radial error (MRE) pointing accuracy on the 34-m diameter antennas. However, for the monopulse to be able to acquire and lock, for special radio science applications where monopulse cannot be used, or as a back-up for the monopulse, high-precision open-loop blind pointing is required. This paper describes a new 4th order pointing model and calibration technique, which was developed and applied to the DSN 34-m BWG antennas yielding 1.8 to 3.0-mdeg MRE pointing accuracy and amplitude stability of 0.2 dB, at Ka-Band, and successfully used for the CASSINI spacecraft occultation experiment at Saturn and Titan. In addition, the new 4th order pointing model was used during a telemetry experiment at Ka-Band (32 GHz) utilizing the Mars Reconnaissance Orbiter (MRO) spacecraft while at a distance of 0.225 astronomical units (AU) from Earth and communicating with a DSN 34-m BWG antenna at a record high rate of 6-megabits per second (Mb/s).

  18. Using CASE to Exploit Process Modeling in Technology Transfer

    Science.gov (United States)

    Renz-Olar, Cheryl

    2003-01-01

    A successful business will be one that has processes in place to run that business. Creating processes, reengineering processes, and continually improving processes can be accomplished through extensive modeling. Casewise(R) Corporate Modeler(TM) CASE is a computer aided software engineering tool that will enable the Technology Transfer Department (TT) at NASA Marshall Space Flight Center (MSFC) to capture these abilities. After successful implementation of CASE, it could then go on to be applied in other departments at MSFC and other centers at NASA. The success of a business process is dependent upon the players working as a team and continuously improving the process. A good process fosters customer satisfaction as well as internal satisfaction in the organizational infrastructure. CASE provides a method for business process success through functions consisting of systems and processes business models; specialized diagrams; matrix management; simulation; report generation and publishing; and, linking, importing, and exporting documents and files. The software has an underlying repository or database to support these functions. The Casewise. manual informs us that dynamics modeling is a technique used in business design and analysis. Feedback is used as a tool for the end users and generates different ways of dealing with the process. Feedback on this project resulted from collection of issues through a systems analyst interface approach of interviews with process coordinators and Technical Points of Contact (TPOCs).

  19. Numerical investigation of the recruitment process in open marine population models

    International Nuclear Information System (INIS)

    Angulo, O; López-Marcos, J C; López-Marcos, M A; Martínez-Rodríguez, J

    2011-01-01

    The changes in the dynamics, produced by the recruitment process in an open marine population model, are investigated from a numerical point of view. The numerical method considered, based on the representation of the solution along the characteristic lines, approximates properly the steady states of the model, and is used to analyze the asymptotic behavior of the solutions of the model

  20. Accurate modeling and maximum power point detection of ...

    African Journals Online (AJOL)

    Accurate modeling and maximum power point detection of photovoltaic ... Determination of MPP enables the PV system to deliver maximum available power. ..... adaptive artificial neural network: Proposition for a new sizing procedure.

  1. Supervised Outlier Detection in Large-Scale Mvs Point Clouds for 3d City Modeling Applications

    Science.gov (United States)

    Stucker, C.; Richard, A.; Wegner, J. D.; Schindler, K.

    2018-05-01

    We propose to use a discriminative classifier for outlier detection in large-scale point clouds of cities generated via multi-view stereo (MVS) from densely acquired images. What makes outlier removal hard are varying distributions of inliers and outliers across a scene. Heuristic outlier removal using a specific feature that encodes point distribution often delivers unsatisfying results. Although most outliers can be identified correctly (high recall), many inliers are erroneously removed (low precision), too. This aggravates object 3D reconstruction due to missing data. We thus propose to discriminatively learn class-specific distributions directly from the data to achieve high precision. We apply a standard Random Forest classifier that infers a binary label (inlier or outlier) for each 3D point in the raw, unfiltered point cloud and test two approaches for training. In the first, non-semantic approach, features are extracted without considering the semantic interpretation of the 3D points. The trained model approximates the average distribution of inliers and outliers across all semantic classes. Second, semantic interpretation is incorporated into the learning process, i.e. we train separate inlieroutlier classifiers per semantic class (building facades, roof, ground, vegetation, fields, and water). Performance of learned filtering is evaluated on several large SfM point clouds of cities. We find that results confirm our underlying assumption that discriminatively learning inlier-outlier distributions does improve precision over global heuristics by up to ≍ 12 percent points. Moreover, semantically informed filtering that models class-specific distributions further improves precision by up to ≍ 10 percent points, being able to remove very isolated building, roof, and water points while preserving inliers on building facades and vegetation.

  2. Generalized enthalpy model of a high-pressure shift freezing process

    KAUST Repository

    Smith, N. A. S.

    2012-05-02

    High-pressure freezing processes are a novel emerging technology in food processing, offering significant improvements to the quality of frozen foods. To be able to simulate plateau times and thermal history under different conditions, in this work, we present a generalized enthalpy model of the high-pressure shift freezing process. The model includes the effects of pressure on conservation of enthalpy and incorporates the freezing point depression of non-dilute food samples. In addition, the significant heat-transfer effects of convection in the pressurizing medium are accounted for by solving the two-dimensional Navier-Stokes equations. We run the model for several numerical tests where the food sample is agar gel, and find good agreement with experimental data from the literature. © 2012 The Royal Society.

  3. A linear dynamic model for rotor-spun composite yarn spinning process

    International Nuclear Information System (INIS)

    Yang, R H; Wang, S Y

    2008-01-01

    A linear dynamic model is established for the stable rotor-spun composite yarn spinning process. Approximate oscillating frequencies in the vertical and horizontal directions are obtained. By suitable choice of certain processing parameters, the mixture construction after the convergent point can be optimally matched. The presented study is expected to provide a general pathway to understand the motion of the rotor-spun composite yarn spinning process

  4. End point detection in ion milling processes by sputter-induced optical emission spectroscopy

    International Nuclear Information System (INIS)

    Lu, C.; Dorian, M.; Tabei, M.; Elsea, A.

    1984-01-01

    The characteristic optical emission from the sputtered material during ion milling processes can provide an unambiguous indication of the presence of the specific etched species. By monitoring the intensity of a representative emission line, the etching process can be precisely terminated at an interface. Enhancement of the etching end point is possible by using a dual-channel photodetection system operating in a ratio or difference mode. The installation of the optical detection system to an existing etching chamber has been greatly facilitated by the use of optical fibers. Using a commercial ion milling system, experimental data for a number of etching processes have been obtained. The result demonstrates that sputter-induced optical emission spectroscopy offers many advantages over other techniques in detecting the etching end point of ion milling processes

  5. Modeling molecular boiling points using computed interaction energies.

    Science.gov (United States)

    Peterangelo, Stephen C; Seybold, Paul G

    2017-12-20

    The noncovalent van der Waals interactions between molecules in liquids are typically described in textbooks as occurring between the total molecular dipoles (permanent, induced, or transient) of the molecules. This notion was tested by examining the boiling points of 67 halogenated hydrocarbon liquids using quantum chemically calculated molecular dipole moments, ionization potentials, and polarizabilities obtained from semi-empirical (AM1 and PM3) and ab initio Hartree-Fock [HF 6-31G(d), HF 6-311G(d,p)], and density functional theory [B3LYP/6-311G(d,p)] methods. The calculated interaction energies and an empirical measure of hydrogen bonding were employed to model the boiling points of the halocarbons. It was found that only terms related to London dispersion energies and hydrogen bonding proved significant in the regression analyses, and the performances of the models generally improved at higher levels of quantum chemical computation. An empirical estimate for the molecular polarizabilities was also tested, and the best models for the boiling points were obtained using either this empirical polarizability itself or the polarizabilities calculated at the B3LYP/6-311G(d,p) level, along with the hydrogen-bonding parameter. The results suggest that the cohesive forces are more appropriately described as resulting from highly localized interactions rather than interactions between the global molecular dipoles.

  6. Assessment of Peer Mediation Process from Conflicting Students’ Point of Views

    Directory of Open Access Journals (Sweden)

    Fulya TÜRK

    2016-12-01

    Full Text Available The purpose of this study was to analyze peer mediation process that was applied in a high school on conflicting students’ point of views. This research was carried out in a high school in Denizli. After ten sessions of training in peer mediation, peer mediators mediated peers’ real conflicts. In the research, 41 students (28 girls, 13 boys who got help at least once were interviewed as a party to the conflict. Through semistructured interviews with conflicting students, the mediation process has been evaluated through the point of views of students. Eight questions were asked about the conflicting parties. Verbal data obtained from interviews were analyzed using the content analysis. When conflicting students’ opinions and experiences about peer mediation were analyzed, it is seen that they were satisfied regarding the process, they have resolved their conflicts in a constructive and peaceful way, their friendship has been continuing as before. All of these results also indicate that peer mediation is an effective method of resolving student conflicts constructively

  7. An Improved Nonlinear Five-Point Model for Photovoltaic Modules

    Directory of Open Access Journals (Sweden)

    Sakaros Bogning Dongue

    2013-01-01

    Full Text Available This paper presents an improved nonlinear five-point model capable of analytically describing the electrical behaviors of a photovoltaic module for each generic operating condition of temperature and solar irradiance. The models used to replicate the electrical behaviors of operating PV modules are usually based on some simplified assumptions which provide convenient mathematical model which can be used in conventional simulation tools. Unfortunately, these assumptions cause some inaccuracies, and hence unrealistic economic returns are predicted. As an alternative, we used the advantages of a nonlinear analytical five-point model to take into account the nonideal diode effects and nonlinear effects generally ignored, which PV modules operation depends on. To verify the capability of our method to fit PV panel characteristics, the procedure was tested on three different panels. Results were compared with the data issued by manufacturers and with the results obtained using the five-parameter model proposed by other authors.

  8. Hierarchical model generation for architecture reconstruction using laser-scanned point clouds

    Science.gov (United States)

    Ning, Xiaojuan; Wang, Yinghui; Zhang, Xiaopeng

    2014-06-01

    Architecture reconstruction using terrestrial laser scanner is a prevalent and challenging research topic. We introduce an automatic, hierarchical architecture generation framework to produce full geometry of architecture based on a novel combination of facade structures detection, detailed windows propagation, and hierarchical model consolidation. Our method highlights the generation of geometric models automatically fitting the design information of the architecture from sparse, incomplete, and noisy point clouds. First, the planar regions detected in raw point clouds are interpreted as three-dimensional clusters. Then, the boundary of each region extracted by projecting the points into its corresponding two-dimensional plane is classified to obtain detailed shape structure elements (e.g., windows and doors). Finally, a polyhedron model is generated by calculating the proposed local structure model, consolidated structure model, and detailed window model. Experiments on modeling the scanned real-life buildings demonstrate the advantages of our method, in which the reconstructed models not only correspond to the information of architectural design accurately, but also satisfy the requirements for visualization and analysis.

  9. Geographical point cloud modelling with the 3D medial axis transform

    NARCIS (Netherlands)

    Peters, R.Y.

    2018-01-01

    A geographical point cloud is a detailed three-dimensional representation of the geometry of our geographic environment.
    Using geographical point cloud modelling, we are able to extract valuable information from geographical point clouds that can be used for applications in asset management,

  10. Hazard analysis and critical control point (HACCP) for an ultrasound food processing operation.

    Science.gov (United States)

    Chemat, Farid; Hoarau, Nicolas

    2004-05-01

    Emerging technologies, such as ultrasound (US), used for food and drink production often cause hazards for product safety. Classical quality control methods are inadequate to control these hazards. Hazard analysis of critical control points (HACCP) is the most secure and cost-effective method for controlling possible product contamination or cross-contamination, due to physical or chemical hazard during production. The following case study on the application of HACCP to an US food-processing operation demonstrates how the hazards at the critical control points of the process are effectively controlled through the implementation of HACCP.

  11. New analytically solvable models of relativistic point interactions

    International Nuclear Information System (INIS)

    Gesztesy, F.; Seba, P.

    1987-01-01

    Two new analytically solvable models of relativistic point interactions in one dimension (being natural extensions of the nonrelativistic δ-resp, δ'-interaction) are considered. Their spectral properties in the case of finitely many point interactions as well as in the periodic case are fully analyzed. Moreover the spectrum is explicitely determined in the case of independent, identically distributed random coupling constants and the analog of the Saxon and Huther conjecture concerning gaps in the energy spectrum of such systems is derived

  12. A marked point process approach for identifying neural correlates of tics in Tourette Syndrome.

    Science.gov (United States)

    Loza, Carlos A; Shute, Jonathan B; Principe, Jose C; Okun, Michael S; Gunduz, Aysegul

    2017-07-01

    We propose a novel interpretation of local field potentials (LFP) based on a marked point process (MPP) framework that models relevant neuromodulations as shifted weighted versions of prototypical temporal patterns. Particularly, the MPP samples are categorized according to the well known oscillatory rhythms of the brain in an effort to elucidate spectrally specific behavioral correlates. The result is a transient model for LFP. We exploit data-driven techniques to fully estimate the model parameters with the added feature of exceptional temporal resolution of the resulting events. We utilize the learned features in the alpha and beta bands to assess correlations to tic events in patients with Tourette Syndrome (TS). The final results show stronger coupling between LFP recorded from the centromedian-paraficicular complex of the thalamus and the tic marks, in comparison to electrocorticogram (ECoG) recordings from the hand area of the primary motor cortex (M1) in terms of the area under the curve (AUC) of the receiver operating characteristic (ROC) curve.

  13. A non-ideal model for predicting the effect of dissolved salt on the flash point of solvent mixtures.

    Science.gov (United States)

    Liaw, Horng-Jang; Wang, Tzu-Ai

    2007-03-06

    Flash point is one of the major quantities used to characterize the fire and explosion hazard of liquids. Herein, a liquid with dissolved salt is presented in a salt-distillation process for separating close-boiling or azeotropic systems. The addition of salts to a liquid may reduce fire and explosion hazard. In this study, we have modified a previously proposed model for predicting the flash point of miscible mixtures to extend its application to solvent/salt mixtures. This modified model was verified by comparison with the experimental data for organic solvent/salt and aqueous-organic solvent/salt mixtures to confirm its efficacy in terms of prediction of the flash points of these mixtures. The experimental results confirm marked increases in liquid flash point increment with addition of inorganic salts relative to supplementation with equivalent quantities of water. Based on this evidence, it appears reasonable to suggest potential application for the model in assessment of the fire and explosion hazard for solvent/salt mixtures and, further, that addition of inorganic salts may prove useful for hazard reduction in flammable liquids.

  14. Putting to point the production process of iodine-131 by dry distillation (Preoperational tests)

    International Nuclear Information System (INIS)

    Alanis M, J.

    2002-12-01

    With the purpose of putting to point the process of production of 131 I, one of the objectives of carrying out the realization of operational tests of the production process of iodine-131, it was of verifying the operation of each one of the following components: heating systems, vacuum system, mechanical system and peripheral equipment that are part of the production process of iodine-131, another of the objectives, was settling down the optimal parameters that were applied in each process during the obtaining of iodine-131, it is necessary to point out that this objective is very important, since the components of the equipment are new and its behavior during the process is different to the equipment where its were carried out the experimental studies. (Author)

  15. 2D modeling of direct laser metal deposition process using a finite particle method

    Science.gov (United States)

    Anedaf, T.; Abbès, B.; Abbès, F.; Li, Y. M.

    2018-05-01

    Direct laser metal deposition is one of the material additive manufacturing processes used to produce complex metallic parts. A thorough understanding of the underlying physical phenomena is required to obtain a high-quality parts. In this work, a mathematical model is presented to simulate the coaxial laser direct deposition process tacking into account of mass addition, heat transfer, and fluid flow with free surface and melting. The fluid flow in the melt pool together with mass and energy balances are solved using the Computational Fluid Dynamics (CFD) software NOGRID-points, based on the meshless Finite Pointset Method (FPM). The basis of the computations is a point cloud, which represents the continuum fluid domain. Each finite point carries all fluid information (density, velocity, pressure and temperature). The dynamic shape of the molten zone is explicitly described by the point cloud. The proposed model is used to simulate a single layer cladding.

  16. 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

  17. A delta-rule model of numerical and non-numerical order processing.

    Science.gov (United States)

    Verguts, Tom; Van Opstal, Filip

    2014-06-01

    Numerical and non-numerical order processing share empirical characteristics (distance effect and semantic congruity), but there are also important differences (in size effect and end effect). At the same time, models and theories of numerical and non-numerical order processing developed largely separately. Currently, we combine insights from 2 earlier models to integrate them in a common framework. We argue that the same learning principle underlies numerical and non-numerical orders, but that environmental features determine the empirical differences. Implications for current theories on order processing are pointed out. PsycINFO Database Record (c) 2014 APA, all rights reserved.

  18. Performance Analysis of Several GPS/Galileo Precise Point Positioning Models.

    Science.gov (United States)

    Afifi, Akram; El-Rabbany, Ahmed

    2015-06-19

    This paper examines the performance of several precise point positioning (PPP) models, which combine dual-frequency GPS/Galileo observations in the un-differenced and between-satellite single-difference (BSSD) modes. These include the traditional un-differenced model, the decoupled clock model, the semi-decoupled clock model, and the between-satellite single-difference model. We take advantage of the IGS-MGEX network products to correct for the satellite differential code biases and the orbital and satellite clock errors. Natural Resources Canada's GPSPace PPP software is modified to handle the various GPS/Galileo PPP models. A total of six data sets of GPS and Galileo observations at six IGS stations are processed to examine the performance of the various PPP models. It is shown that the traditional un-differenced GPS/Galileo PPP model, the GPS decoupled clock model, and the semi-decoupled clock GPS/Galileo PPP model improve the convergence time by about 25% in comparison with the un-differenced GPS-only model. In addition, the semi-decoupled GPS/Galileo PPP model improves the solution precision by about 25% compared to the traditional un-differenced GPS/Galileo PPP model. Moreover, the BSSD GPS/Galileo PPP model improves the solution convergence time by about 50%, in comparison with the un-differenced GPS PPP model, regardless of the type of BSSD combination used. As well, the BSSD model improves the precision of the estimated parameters by about 50% and 25% when the loose and the tight combinations are used, respectively, in comparison with the un-differenced GPS-only model. Comparable results are obtained through the tight combination when either a GPS or a Galileo satellite is selected as a reference.

  19. Effect of river flow fluctuations on riparian vegetation dynamics: Processes and models

    Science.gov (United States)

    Vesipa, Riccardo; Camporeale, Carlo; Ridolfi, Luca

    2017-12-01

    Several decades of field observations, laboratory experiments and mathematical modelings have demonstrated that the riparian environment is a disturbance-driven ecosystem, and that the main source of disturbance is river flow fluctuations. The focus of the present work has been on the key role that flow fluctuations play in determining the abundance, zonation and species composition of patches of riparian vegetation. To this aim, the scientific literature on the subject, over the last 20 years, has been reviewed. First, the most relevant ecological, morphological and chemical mechanisms induced by river flow fluctuations are described from a process-based perspective. The role of flow variability is discussed for the processes that affect the recruitment of vegetation, the vegetation during its adult life, and the morphological and nutrient dynamics occurring in the riparian habitat. Particular emphasis has been given to studies that were aimed at quantifying the effect of these processes on vegetation, and at linking them to the statistical characteristics of the river hydrology. Second, the advances made, from a modeling point of view, have been considered and discussed. The main models that have been developed to describe the dynamics of riparian vegetation have been presented. Different modeling approaches have been compared, and the corresponding advantages and drawbacks have been pointed out. Finally, attention has been paid to identifying the processes considered by the models, and these processes have been compared with those that have actually been observed or measured in field/laboratory studies.

  20. Fragmentation approach to the point-island model with hindered aggregation: Accessing the barrier energy

    Science.gov (United States)

    González, Diego Luis; Pimpinelli, Alberto; Einstein, T. L.

    2017-07-01

    We study the effect of hindered aggregation on the island formation process in a one- (1D) and two-dimensional (2D) point-island model for epitaxial growth with arbitrary critical nucleus size i . In our model, the attachment of monomers to preexisting islands is hindered by an additional attachment barrier, characterized by length la. For la=0 the islands behave as perfect sinks while for la→∞ they behave as reflecting boundaries. For intermediate values of la, the system exhibits a crossover between two different kinds of processes, diffusion-limited aggregation and attachment-limited aggregation. We calculate the growth exponents of the density of islands and monomers for the low coverage and aggregation regimes. The capture-zone (CZ) distributions are also calculated for different values of i and la. In order to obtain a good spatial description of the nucleation process, we propose a fragmentation model, which is based on an approximate description of nucleation inside of the gaps for 1D and the CZs for 2D. In both cases, the nucleation is described by using two different physically rooted probabilities, which are related with the microscopic parameters of the model (i and la). We test our analytical model with extensive numerical simulations and previously established results. The proposed model describes excellently the statistical behavior of the system for arbitrary values of la and i =1 , 2, and 3.

  1. Stochastic dynamical model of a growing citation network based on a self-exciting point process.

    Science.gov (United States)

    Golosovsky, Michael; Solomon, Sorin

    2012-08-31

    We put under experimental scrutiny the preferential attachment model that is commonly accepted as a generating mechanism of the scale-free complex networks. To this end we chose a citation network of physics papers and traced the citation history of 40,195 papers published in one year. Contrary to common belief, we find that the citation dynamics of the individual papers follows the superlinear preferential attachment, with the exponent α=1.25-1.3. Moreover, we show that the citation process cannot be described as a memoryless Markov chain since there is a substantial correlation between the present and recent citation rates of a paper. Based on our findings we construct a stochastic growth model of the citation network, perform numerical simulations based on this model and achieve an excellent agreement with the measured citation distributions.

  2. 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

  3. Set points, settling points and some alternative models: theoretical options to understand how genes and environments combine to regulate body adiposity

    Directory of Open Access Journals (Sweden)

    John R. Speakman

    2011-11-01

    Full Text Available The close correspondence between energy intake and expenditure over prolonged time periods, coupled with an apparent protection of the level of body adiposity in the face of perturbations of energy balance, has led to the idea that body fatness is regulated via mechanisms that control intake and energy expenditure. Two models have dominated the discussion of how this regulation might take place. The set point model is rooted in physiology, genetics and molecular biology, and suggests that there is an active feedback mechanism linking adipose tissue (stored energy to intake and expenditure via a set point, presumably encoded in the brain. This model is consistent with many of the biological aspects of energy balance, but struggles to explain the many significant environmental and social influences on obesity, food intake and physical activity. More importantly, the set point model does not effectively explain the ‘obesity epidemic’ – the large increase in body weight and adiposity of a large proportion of individuals in many countries since the 1980s. An alternative model, called the settling point model, is based on the idea that there is passive feedback between the size of the body stores and aspects of expenditure. This model accommodates many of the social and environmental characteristics of energy balance, but struggles to explain some of the biological and genetic aspects. The shortcomings of these two models reflect their failure to address the gene-by-environment interactions that dominate the regulation of body weight. We discuss two additional models – the general intake model and the dual intervention point model – that address this issue and might offer better ways to understand how body fatness is controlled.

  4. Reduction of bias in neutron multiplicity assay using a weighted point model

    Energy Technology Data Exchange (ETDEWEB)

    Geist, W. H. (William H.); Krick, M. S. (Merlyn S.); Mayo, D. R. (Douglas R.)

    2004-01-01

    Accurate assay of most common plutonium samples was the development goal for the nondestructive assay technique of neutron multiplicity counting. Over the past 20 years the technique has been proven for relatively pure oxides and small metal items. Unfortunately, the technique results in large biases when assaying large metal items. Limiting assumptions, such as unifoh multiplication, in the point model used to derive the multiplicity equations causes these biases for large dense items. A weighted point model has been developed to overcome some of the limitations in the standard point model. Weighting factors are detemiined from Monte Carlo calculations using the MCNPX code. Monte Carlo calculations give the dependence of the weighting factors on sample mass and geometry, and simulated assays using Monte Carlo give the theoretical accuracy of the weighted-point-model assay. Measured multiplicity data evaluated with both the standard and weighted point models are compared to reference values to give the experimental accuracy of the assay. Initial results show significant promise for the weighted point model in reducing or eliminating biases in the neutron multiplicity assay of metal items. The negative biases observed in the assay of plutonium metal samples are caused by variations in the neutron multiplication for neutrons originating in various locations in the sample. The bias depends on the mass and shape of the sample and depends on the amount and energy distribution of the ({alpha},n) neutrons in the sample. When the standard point model is used, this variable-multiplication bias overestimates the multiplication and alpha values of the sample, and underestimates the plutonium mass. The weighted point model potentially can provide assay accuracy of {approx}2% (1 {sigma}) for cylindrical plutonium metal samples < 4 kg with {alpha} < 1 without knowing the exact shape of the samples, provided that the ({alpha},n) source is uniformly distributed throughout the

  5. Neutral-point voltage dynamic model of three-level NPC inverter for reactive load

    DEFF Research Database (Denmark)

    Maheshwari, Ram Krishan; Munk-Nielsen, Stig; Busquets-Monge, Sergio

    2012-01-01

    A three-level neutral-point-clamped inverter needs a controller for the neutral-point voltage. Typically, the controller design is based on a dynamic model. The dynamic model of the neutral-point voltage depends on the pulse width modulation technique used for the inverter. A pulse width modulati...

  6. Theory of Single Point Incremental Forming

    DEFF Research Database (Denmark)

    Martins, P.A.F.; Bay, Niels; Skjødt, Martin

    2008-01-01

    This paper presents a closed-form theoretical analysis modelling the fundamentals of single point incremental forming and explaining the experimental and numerical results available in the literature for the past couple of years. The model is based on membrane analysis with bi-directional in-plan......-plane contact friction and is focused on the extreme modes of deformation that are likely to be found in single point incremental forming processes. The overall investigation is supported by experimental work performed by the authors and data retrieved from the literature.......This paper presents a closed-form theoretical analysis modelling the fundamentals of single point incremental forming and explaining the experimental and numerical results available in the literature for the past couple of years. The model is based on membrane analysis with bi-directional in...

  7. Pseudo-critical point in anomalous phase diagrams of simple plasma models

    Science.gov (United States)

    Chigvintsev, A. Yu; Iosilevskiy, I. L.; Noginova, L. Yu

    2016-11-01

    Anomalous phase diagrams in subclass of simplified (“non-associative”) Coulomb models is under discussion. The common feature of this subclass is absence on definition of individual correlations for charges of opposite sign. It is e.g. modified OCP of ions on uniformly compressible background of ideal Fermi-gas of electrons OCP(∼), or a superposition of two non-ideal OCP(∼) models of ions and electrons etc. In contrast to the ordinary OCP model on non-compressible (“rigid”) background OCP(#) two new phase transitions with upper critical point, boiling and sublimation, appear in OCP(∼) phase diagram in addition to the well-known Wigner crystallization. The point is that the topology of phase diagram in OCP(∼) becomes anomalous at high enough value of ionic charge number Z. Namely, the only one unified crystal- fluid phase transition without critical point exists as continuous superposition of melting and sublimation in OCP(∼) at the interval (Z 1 points at both boundary values Z = Z 1 ≈ 35.5 and Z = Z 2 ≈ 40.0. It should be stressed that critical isotherm is exactly cubic in both these pseudo-critical points. In this study we have improved our previous calculations and utilized more complicated model components equation of state provided by Chabrier and Potekhin (1998 Phys. Rev. E 58 4941).

  8. An Automated Approach to the Generation of Structured Building Information Models from Unstructured 3d Point Cloud Scans

    DEFF Research Database (Denmark)

    Tamke, Martin; Evers, Henrik Leander; Wessel, Raoul

    2016-01-01

    In this paper we present and evaluate an approach for the automatic generation of building models in IFC BIM format from unstructured Point Cloud scans, as they result from 3dlaser scans of buildings. While the actual measurement process is relatively fast, 85% of the overall time are spend...... on the interpretation and transformation of the resulting Point Cloud data into information, which can be used in architectural and engineering design workflows. Our approach to tackle this problem, is in contrast to existing ones which work on the levels of points, based on the detection of building elements...

  9. Modeling the contribution of point sources and non-point sources to Thachin River water pollution.

    Science.gov (United States)

    Schaffner, Monika; Bader, Hans-Peter; Scheidegger, Ruth

    2009-08-15

    Major rivers in developing and emerging countries suffer increasingly of severe degradation of water quality. The current study uses a mathematical Material Flow Analysis (MMFA) as a complementary approach to address the degradation of river water quality due to nutrient pollution in the Thachin River Basin in Central Thailand. This paper gives an overview of the origins and flow paths of the various point- and non-point pollution sources in the Thachin River Basin (in terms of nitrogen and phosphorus) and quantifies their relative importance within the system. The key parameters influencing the main nutrient flows are determined and possible mitigation measures discussed. The results show that aquaculture (as a point source) and rice farming (as a non-point source) are the key nutrient sources in the Thachin River Basin. Other point sources such as pig farms, households and industries, which were previously cited as the most relevant pollution sources in terms of organic pollution, play less significant roles in comparison. This order of importance shifts when considering the model results for the provincial level. Crosschecks with secondary data and field studies confirm the plausibility of our simulations. Specific nutrient loads for the pollution sources are derived; these can be used for a first broad quantification of nutrient pollution in comparable river basins. Based on an identification of the sensitive model parameters, possible mitigation scenarios are determined and their potential to reduce the nutrient load evaluated. A comparison of simulated nutrient loads with measured nutrient concentrations shows that nutrient retention in the river system may be significant. Sedimentation in the slow flowing surface water network as well as nitrogen emission to the air from the warm oxygen deficient waters are certainly partly responsible, but also wetlands along the river banks could play an important role as nutrient sinks.

  10. BPLOM: BPM Level-Oriented Methodology for Incremental Business Process Modeling and Code Generation on Mobile Platforms

    Directory of Open Access Journals (Sweden)

    Jaime Solis Martines

    2013-06-01

    Full Text Available The requirements engineering phase is the departure point for the development process of any kind of computer application, it determines the functionality needed in the working scenario of the program. Although this is a crucial point in application development, as incorrect requirement definition leads to costly error appearance in later stages of the development process, application domain experts’ implication remains minor. In order to correct this scenario, business process modeling notations were introduced to favor business expert implication in this phase, but notation complexity prevents this participation to reach its ideal state. Hence, we promote the definition of a level oriented business process methodology, which encourages the adaptation of the modeling notation to the modeling and technical knowledge shown by the expert. This approach reduces the complexity found by domain experts and enables them to model their processes completely with a level of technical detail directly proportional to their knowledge.

  11. Can the Hazard Assessment and Critical Control Points (HACCP) system be used to design process-based hygiene concepts?

    Science.gov (United States)

    Hübner, N-O; Fleßa, S; Haak, J; Wilke, F; Hübner, C; Dahms, C; Hoffmann, W; Kramer, A

    2011-01-01

    Recently, the HACCP (Hazard Analysis and Critical Control Points) concept was proposed as possible way to implement process-based hygiene concepts in clinical practice, but the extent to which this food safety concept can be transferred into the health care setting is unclear. We therefore discuss possible ways for a translation of the principles of the HACCP for health care settings. While a direct implementation of food processing concepts into health care is not very likely to be feasible and will probably not readily yield the intended results, the underlying principles of process-orientation, in-process safety control and hazard analysis based counter measures are transferable to clinical settings. In model projects the proposed concepts should be implemented, monitored, and evaluated under real world conditions.

  12. A travel time forecasting model based on change-point detection method

    Science.gov (United States)

    LI, Shupeng; GUANG, Xiaoping; QIAN, Yongsheng; ZENG, Junwei

    2017-06-01

    Travel time parameters obtained from road traffic sensors data play an important role in traffic management practice. A travel time forecasting model is proposed for urban road traffic sensors data based on the method of change-point detection in this paper. The first-order differential operation is used for preprocessing over the actual loop data; a change-point detection algorithm is designed to classify the sequence of large number of travel time data items into several patterns; then a travel time forecasting model is established based on autoregressive integrated moving average (ARIMA) model. By computer simulation, different control parameters are chosen for adaptive change point search for travel time series, which is divided into several sections of similar state.Then linear weight function is used to fit travel time sequence and to forecast travel time. The results show that the model has high accuracy in travel time forecasting.

  13. Analysis of the resolution processes of three modeling tasks

    Directory of Open Access Journals (Sweden)

    Cèsar Gallart Palau

    2017-08-01

    Full Text Available In this paper we present a comparative analysis of the resolution process of three modeling tasks performed by secondary education students (13-14 years, designed from three different points of view: The Modelling-eliciting Activities, the LEMA project, and the Realistic Mathematical Problems. The purpose of this analysis is to obtain a methodological characterization of them in order to provide to secondary education teachers a proper selection and sequencing of tasks for their implementation in the classroom.

  14. Near-infrared spectroscopic monitoring of a series of industrial batch processes using a bilinear grey model

    NARCIS (Netherlands)

    van Sprang, Eric N. M.; Ramaker, Henk-Jan; Westerhuis, Johan A.; Smilde, Age K.; Gurden, Stephen P.; Wienke, Dietrich

    2003-01-01

    A good process understanding is the foundation for process optimization, process monitoring, end-point detection, and estimation of the end-product quality. Performing good process measurements and the construction of process models will contribute to a better process understanding. To improve the

  15. Geometric anisotropic spatial point pattern analysis and Cox processes

    DEFF Research Database (Denmark)

    Møller, Jesper; Toftaker, Håkon

    . In particular we study Cox process models with an elliptical pair correlation function, including shot noise Cox processes and log Gaussian Cox processes, and we develop estimation procedures using summary statistics and Bayesian methods. Our methodology is illustrated on real and synthetic datasets of spatial...

  16. Mathematical model for calculation of the heat-hydraulic modes of heating points of heat-supplying systems

    Science.gov (United States)

    Shalaginova, Z. I.

    2016-03-01

    The mathematical model and calculation method of the thermal-hydraulic modes of heat points, based on the theory of hydraulic circuits, being developed at the Melentiev Energy Systems Institute are presented. The redundant circuit of the heat point was developed, in which all possible connecting circuits (CC) of the heat engineering equipment and the places of possible installation of control valve were inserted. It allows simulating the operating modes both at central heat points (CHP) and individual heat points (IHP). The configuration of the desired circuit is carried out automatically by removing the unnecessary links. The following circuits connecting the heating systems (HS) are considered: the dependent circuit (direct and through mixing elevator) and independent one (through the heater). The following connecting circuits of the load of hot water supply (HWS) were considered: open CC (direct water pumping from pipelines of heat networks) and a closed CC with connecting the HWS heaters on single-level (serial and parallel) and two-level (sequential and combined) circuits. The following connecting circuits of the ventilation systems (VS) were also considered: dependent circuit and independent one through a common heat exchanger with HS load. In the heat points, water temperature regulators for the hot water supply and ventilation and flow regulators for the heating system, as well as to the inlet as a whole, are possible. According to the accepted decomposition, the model of the heat point is an integral part of the overall heat-hydraulic model of the heat-supplying system having intermediate control stages (CHP and IHP), which allows to consider the operating modes of the heat networks of different levels connected with each other through CHP as well as connected through IHP of consumers with various connecting circuits of local systems of heat consumption: heating, ventilation and hot water supply. The model is implemented in the Angara data-processing

  17. Integrated catchment modelling within a strategic planning and decision making process: Werra case study

    Science.gov (United States)

    Dietrich, Jörg; Funke, Markus

    Integrated water resources management (IWRM) redefines conventional water management approaches through a closer cross-linkage between environment and society. The role of public participation and socio-economic considerations becomes more important within the planning and decision making process. In this paper we address aspects of the integration of catchment models into such a process taking the implementation of the European Water Framework Directive (WFD) as an example. Within a case study situated in the Werra river basin (Central Germany), a systems analytic decision process model was developed. This model uses the semantics of the Unified Modeling Language (UML) activity model. As an example application, the catchment model SWAT and the water quality model RWQM1 were applied to simulate the effect of phosphorus emissions from non-point and point sources on water quality. The decision process model was able to guide the participants of the case study through the interdisciplinary planning and negotiation of actions. Further improvements of the integration framework include tools for quantitative uncertainty analyses, which are crucial for real life application of models within an IWRM decision making toolbox. For the case study, the multi-criteria assessment of actions indicates that the polluter pays principle can be met at larger scales (sub-catchment or river basin) without significantly compromising cost efficiency for the local situation.

  18. 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

    2018-01-01

    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…

  19. 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.

  20. Models development for natural circulation and its transition process in nuclear power plant

    International Nuclear Information System (INIS)

    Yu Lei; Cai Qi; Cai Zhangsheng; Xie Haiyan

    2008-01-01

    On the basis of nuclear power plant (NPP) best-estimate transient analysis code RELAP5/MOD3, the point reactor kinetics model in RELAP5/MOD3 was replaced by the two-group, 3-D space and time dependent neutron kinetic model, in order to exactly analyze the responses of key parameters in natural circulation and its transition process considering the reactivity feedback. The coupled model for three-dimensional physics and thermohydraulics was established and corresponding computing code was developed. Using developed code, natural circulation of NPP and its transiton process were calculated and analyzed. Compared with the experiment data, the calculated results show that its high precise avoids the shortage that the point reactor equation can not reflect the reactivity exactly. This code can be a computing and analysis tool for forced circulation and natural circulation and their transitions. (authors)

  1. Pseudo-critical point in anomalous phase diagrams of simple plasma models

    International Nuclear Information System (INIS)

    Chigvintsev, A Yu; Iosilevskiy, I L; Noginova, L Yu

    2016-01-01

    Anomalous phase diagrams in subclass of simplified (“non-associative”) Coulomb models is under discussion. The common feature of this subclass is absence on definition of individual correlations for charges of opposite sign. It is e.g. modified OCP of ions on uniformly compressible background of ideal Fermi-gas of electrons OCP(∼), or a superposition of two non-ideal OCP(∼) models of ions and electrons etc. In contrast to the ordinary OCP model on non-compressible (“rigid”) background OCP(#) two new phase transitions with upper critical point, boiling and sublimation, appear in OCP(∼) phase diagram in addition to the well-known Wigner crystallization. The point is that the topology of phase diagram in OCP(∼) becomes anomalous at high enough value of ionic charge number Z . Namely, the only one unified crystal- fluid phase transition without critical point exists as continuous superposition of melting and sublimation in OCP(∼) at the interval ( Z 1 < Z < Z 2 ). The most remarkable is appearance of pseudo-critical points at both boundary values Z = Z 1 ≈ 35.5 and Z = Z 2 ≈ 40.0. It should be stressed that critical isotherm is exactly cubic in both these pseudo-critical points. In this study we have improved our previous calculations and utilized more complicated model components equation of state provided by Chabrier and Potekhin (1998 Phys. Rev. E 58 4941). (paper)

  2. Modeling non-point source pollutants in the vadose zone: Back to the basics

    Science.gov (United States)

    Corwin, Dennis L.; Letey, John, Jr.; Carrillo, Marcia L. K.

    More than ever before in the history of scientific investigation, modeling is viewed as a fundamental component of the scientific method because of the relatively recent development of the computer. No longer must the scientific investigator be confined to artificially isolated studies of individual processes that can lead to oversimplified and sometimes erroneous conceptions of larger phenomena. Computer models now enable scientists to attack problems related to open systems such as climatic change, and the assessment of environmental impacts, where the whole of the interactive processes are greater than the sum of their isolated components. Environmental assessment involves the determination of change of some constituent over time. This change can be measured in real time or predicted with a model. The advantage of prediction, like preventative medicine, is that it can be used to alter the occurrence of potentially detrimental conditions before they are manifest. The much greater efficiency of preventative, rather than remedial, efforts strongly justifies the need for an ability to accurately model environmental contaminants such as non-point source (NPS) pollutants. However, the environmental modeling advances that have accompanied computer technological development are a mixed blessing. Where once we had a plethora of discordant data without a holistic theory, now the pendulum has swung so that we suffer from a growing stockpile of models of which a significant number have never been confirmed or even attempts made to confirm them. Modeling has become an end in itself rather than a means because of limited research funding, the high cost of field studies, limitations in time and patience, difficulty in cooperative research and pressure to publish papers as quickly as possible. Modeling and experimentation should be ongoing processes that reciprocally enhance one another with sound, comprehensive experiments serving as the building blocks of models and models

  3. KNOWLEDGE-BASED OBJECT DETECTION IN LASER SCANNING POINT CLOUDS

    Directory of Open Access Journals (Sweden)

    F. Boochs

    2012-07-01

    Full Text Available Object identification and object processing in 3D point clouds have always posed challenges in terms of effectiveness and efficiency. In practice, this process is highly dependent on human interpretation of the scene represented by the point cloud data, as well as the set of modeling tools available for use. Such modeling algorithms are data-driven and concentrate on specific features of the objects, being accessible to numerical models. We present an approach that brings the human expert knowledge about the scene, the objects inside, and their representation by the data and the behavior of algorithms to the machine. This “understanding” enables the machine to assist human interpretation of the scene inside the point cloud. Furthermore, it allows the machine to understand possibilities and limitations of algorithms and to take this into account within the processing chain. This not only assists the researchers in defining optimal processing steps, but also provides suggestions when certain changes or new details emerge from the point cloud. Our approach benefits from the advancement in knowledge technologies within the Semantic Web framework. This advancement has provided a strong base for applications based on knowledge management. In the article we will present and describe the knowledge technologies used for our approach such as Web Ontology Language (OWL, used for formulating the knowledge base and the Semantic Web Rule Language (SWRL with 3D processing and topologic built-ins, aiming to combine geometrical analysis of 3D point clouds, and specialists’ knowledge of the scene and algorithmic processing.

  4. Knowledge-Based Object Detection in Laser Scanning Point Clouds

    Science.gov (United States)

    Boochs, F.; Karmacharya, A.; Marbs, A.

    2012-07-01

    Object identification and object processing in 3D point clouds have always posed challenges in terms of effectiveness and efficiency. In practice, this process is highly dependent on human interpretation of the scene represented by the point cloud data, as well as the set of modeling tools available for use. Such modeling algorithms are data-driven and concentrate on specific features of the objects, being accessible to numerical models. We present an approach that brings the human expert knowledge about the scene, the objects inside, and their representation by the data and the behavior of algorithms to the machine. This "understanding" enables the machine to assist human interpretation of the scene inside the point cloud. Furthermore, it allows the machine to understand possibilities and limitations of algorithms and to take this into account within the processing chain. This not only assists the researchers in defining optimal processing steps, but also provides suggestions when certain changes or new details emerge from the point cloud. Our approach benefits from the advancement in knowledge technologies within the Semantic Web framework. This advancement has provided a strong base for applications based on knowledge management. In the article we will present and describe the knowledge technologies used for our approach such as Web Ontology Language (OWL), used for formulating the knowledge base and the Semantic Web Rule Language (SWRL) with 3D processing and topologic built-ins, aiming to combine geometrical analysis of 3D point clouds, and specialists' knowledge of the scene and algorithmic processing.

  5. Four point functions in the SL(2,R) WZW model

    Energy Technology Data Exchange (ETDEWEB)

    Minces, Pablo [Instituto de Astronomia y Fisica del Espacio (IAFE), C.C. 67 Suc. 28, 1428 Buenos Aires (Argentina)]. E-mail: minces@iafe.uba.ar; Nunez, Carmen [Instituto de Astronomia y Fisica del Espacio (IAFE), C.C. 67 Suc. 28, 1428 Buenos Aires (Argentina) and Physics Department, University of Buenos Aires, Ciudad Universitaria, Pab. I, 1428 Buenos Aires (Argentina)]. E-mail: carmen@iafe.uba.ar

    2007-04-19

    We consider winding conserving four point functions in the SL(2,R) WZW model for states in arbitrary spectral flow sectors. We compute the leading order contribution to the expansion of the amplitudes in powers of the cross ratio of the four points on the worldsheet, both in the m- and x-basis, with at least one state in the spectral flow image of the highest weight discrete representation. We also perform certain consistency check on the winding conserving three point functions.

  6. Four point functions in the SL(2,R) WZW model

    International Nuclear Information System (INIS)

    Minces, Pablo; Nunez, Carmen

    2007-01-01

    We consider winding conserving four point functions in the SL(2,R) WZW model for states in arbitrary spectral flow sectors. We compute the leading order contribution to the expansion of the amplitudes in powers of the cross ratio of the four points on the worldsheet, both in the m- and x-basis, with at least one state in the spectral flow image of the highest weight discrete representation. We also perform certain consistency check on the winding conserving three point functions

  7. Ferrimagnetism and compensation points in a decorated 3D Ising model

    International Nuclear Information System (INIS)

    Oitmaa, J.; Zheng, W.

    2003-01-01

    Full text: Ferrimagnets are materials where ions on different sublattices have opposing magnetic moments which do not exactly cancel even at zero temperature. An intriguing possibility then is the existence of a compensation point, below the Curie temperature, where the net moment changes sign. This has obvious technological significance. Most theoretical studies of such systems have used mean-field approaches, making it difficult to distinguish real properties of the model from artefacts of the approximation. For this reason a number of simpler models have been proposed, where treatments beyond mean-field theory are possible. Of particular interest are decorated systems, which can be mapped exactly onto simpler models and, in this way, either solved exactly or to a high degree of numerical precision. We use this approach to study a ferrimagnetic Ising system with spins 1/2 at the sites of a simple cubic lattice and spins S=1 or 3/2 located on the bonds. Our results, which are exact to high numerical precision, show a number of surprising and interesting features: for S=1 the possibility of zero, one or two compensation points, re-entrant behaviour, and up to three critical points; for S=3/2 always a simple critical point and zero or one compensation point

  8. Synthesis of Numerical Methods for Modeling Wave Energy Converter-Point Absorbers: Preprint

    Energy Technology Data Exchange (ETDEWEB)

    Li, Y.; Yu, Y. H.

    2012-05-01

    During the past few decades, wave energy has received significant attention among all ocean energy formats. Industry has proposed hundreds of prototypes such as an oscillating water column, a point absorber, an overtopping system, and a bottom-hinged system. In particular, many researchers have focused on modeling the floating-point absorber as the technology to extract wave energy. Several modeling methods have been used such as the analytical method, the boundary-integral equation method, the Navier-Stokes equations method, and the empirical method. However, no standardized method has been decided. To assist the development of wave energy conversion technologies, this report reviews the methods for modeling the floating-point absorber.

  9. COST VOLUME PROFIT MODEL, THE BREAK -EVEN POINT AND THE DECISION MAKING PROCESS IN THE HOSPITALITY INDUSTRY

    Directory of Open Access Journals (Sweden)

    Scorte Carmen

    2010-12-01

    Full Text Available Management accounting and cost calculation in the hospitality industry is a pathless land. The prezent article is a starting point of a long scientific approach on the domain of the hospitality industry and on the managerial accounting in this area. Our intention is to put the spot light back on the thorny problem of applying Financial Accounting and specifically its implementation in the hospitality industry. One aim of this article is to provide a picture of CVP analysis in decision making with customizing the hospitality industry. To cope with the crisis period, the competition and to achieve the expected profits of the hospitality industry ,managers have the possibility to apply CVP analysis, one of the most simple and useful analytical tools. This paper will address the basic version of the CVP model, exemplifying the main indicators of the particular model for the hospitality industry that can help guide decision-making.

  10. Comments on: Spatiotemporal models for skewed processes

    KAUST Repository

    Genton, Marc G.

    2017-09-04

    We would first like to thank the authors for this paper that highlights the important problem of building models for non-Gaussian space-time processes. We will hereafter refer to the paper as SGV, and we also would like to acknowledge and thank them for providing us with the temporally detrended temperatures, plotted in their Figure 1, along with the coordinates of the twenty-one locations and the posterior means of the parameters for the MA1 model. We find much of interest to discuss in this paper, and as we progress through points of interest, we pose some questions to the authors that we hope they will be able to address.

  11. Comments on: Spatiotemporal models for skewed processes

    KAUST Repository

    Genton, Marc G.; Hering, Amanda S.

    2017-01-01

    We would first like to thank the authors for this paper that highlights the important problem of building models for non-Gaussian space-time processes. We will hereafter refer to the paper as SGV, and we also would like to acknowledge and thank them for providing us with the temporally detrended temperatures, plotted in their Figure 1, along with the coordinates of the twenty-one locations and the posterior means of the parameters for the MA1 model. We find much of interest to discuss in this paper, and as we progress through points of interest, we pose some questions to the authors that we hope they will be able to address.

  12. Mathematical model for hysteresis phenomenon in moisture transport of concrete carbonation process

    International Nuclear Information System (INIS)

    Aiki, Toyohiko; Kumazaki, Kota

    2012-01-01

    From civil engineering point of view it is very important to construct and analyze a mathematical model for a mechanism of concrete carbonation process. On this subject there are several mathematical results concerned with a one-dimensional model, in which hysteresis effects are neglected. Our aim is to give a model with hysteresis effects appearing in carbonation process. In this paper, as the first step of this research we focus only on moisture transport in the process and propose an initial boundary value problem for a system of partial differential equations as a mathematical model. Also, we give results on the existence of a solution to the problem, globally in time and the uniqueness in only one-dimensional case without proofs.

  13. Multi-Class Simultaneous Adaptive Segmentation and Quality Control of Point Cloud Data

    Directory of Open Access Journals (Sweden)

    Ayman Habib

    2016-01-01

    Full Text Available 3D modeling of a given site is an important activity for a wide range of applications including urban planning, as-built mapping of industrial sites, heritage documentation, military simulation, and outdoor/indoor analysis of airflow. Point clouds, which could be either derived from passive or active imaging systems, are an important source for 3D modeling. Such point clouds need to undergo a sequence of data processing steps to derive the necessary information for the 3D modeling process. Segmentation is usually the first step in the data processing chain. This paper presents a region-growing multi-class simultaneous segmentation procedure, where planar, pole-like, and rough regions are identified while considering the internal characteristics (i.e., local point density/spacing and noise level of the point cloud in question. The segmentation starts with point cloud organization into a kd-tree data structure and characterization process to estimate the local point density/spacing. Then, proceeding from randomly-distributed seed points, a set of seed regions is derived through distance-based region growing, which is followed by modeling of such seed regions into planar and pole-like features. Starting from optimally-selected seed regions, planar and pole-like features are then segmented. The paper also introduces a list of hypothesized artifacts/problems that might take place during the region-growing process. Finally, a quality control process is devised to detect, quantify, and mitigate instances of partially/fully misclassified planar and pole-like features. Experimental results from airborne and terrestrial laser scanning as well as image-based point clouds are presented to illustrate the performance of the proposed segmentation and quality control framework.

  14. Properties of spatial Cox process models

    DEFF Research Database (Denmark)

    Møller, Jesper

    2005-01-01

    Particularly, we study the most important classes of Cox processes, including log Gaussian Cox processes, shot noise Cox processes, and permanent Cox processes. We consider moment properties and point process operations such as thinning, displacements, and super positioning. We also discuss how...... to simulate specific Cox processes....

  15. On the diffusion process of irradiation-induced point defects in the stress field of a moving dislocation

    International Nuclear Information System (INIS)

    Steinbach, E.

    1987-01-01

    The cellular model of a dislocation is used for an investigation of the time-dependent diffusion process of irradiation-induced point defects interacting with the stress field of a moving dislocation. An analytic solution is given taking into account the elastic interaction due to the first-order size effect and the stress-induced interaction, the kinematic interaction due to the dislocation motion as well as the presence of secondary neutral sinks. The results for the space and time-dependent point defect concentration, represented in terms of Mathieu-Bessel and Mathieu-Hankel functions, emphasize the influence of the parameters which have been taken into consideration. Proceeding from these solutions, formulae for the diffusion flux reaching unit length of the dislocation, which plays an important role with regard to void swelling and irradiation-induced creep, are derived

  16. Continuation-like semantics for modeling structural process anomalies

    Directory of Open Access Journals (Sweden)

    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.

  17. Episodic grammar: a computational model of the interaction between episodic and semantic memory in language processing

    NARCIS (Netherlands)

    Borensztajn, G.; Zuidema, W.; Carlson, L.; Hoelscher, C.; Shipley, T.F.

    2011-01-01

    We present a model of the interaction of semantic and episodic memory in language processing. Our work shows how language processing can be understood in terms of memory retrieval. We point out that the perceived dichotomy between rule-based versus exemplar-based language modelling can be

  18. A Multi-Point Method Considering the Maximum Power Point Tracking Dynamic Process for Aerodynamic Optimization of Variable-Speed Wind Turbine Blades

    Directory of Open Access Journals (Sweden)

    Zhiqiang Yang

    2016-05-01

    Full Text Available Due to the dynamic process of maximum power point tracking (MPPT caused by turbulence and large rotor inertia, variable-speed wind turbines (VSWTs cannot maintain the optimal tip speed ratio (TSR from cut-in wind speed up to the rated speed. Therefore, in order to increase the total captured wind energy, the existing aerodynamic design for VSWT blades, which only focuses on performance improvement at a single TSR, needs to be improved to a multi-point design. In this paper, based on a closed-loop system of VSWTs, including turbulent wind, rotor, drive train and MPPT controller, the distribution of operational TSR and its description based on inflow wind energy are investigated. Moreover, a multi-point method considering the MPPT dynamic process for the aerodynamic optimization of VSWT blades is proposed. In the proposed method, the distribution of operational TSR is obtained through a dynamic simulation of the closed-loop system under a specific turbulent wind, and accordingly the multiple design TSRs and the corresponding weighting coefficients in the objective function are determined. Finally, using the blade of a National Renewable Energy Laboratory (NREL 1.5 MW wind turbine as the baseline, the proposed method is compared with the conventional single-point optimization method using the commercial software Bladed. Simulation results verify the effectiveness of the proposed method.

  19. Apparatus and method for implementing power saving techniques when processing floating point values

    Science.gov (United States)

    Kim, Young Moon; Park, Sang Phill

    2017-10-03

    An apparatus and method are described for reducing power when reading and writing graphics data. For example, one embodiment of an apparatus comprises: a graphics processor unit (GPU) to process graphics data including floating point data; a set of registers, at least one of the registers of the set partitioned to store the floating point data; and encode/decode logic to reduce a number of binary 1 values being read from the at least one register by causing a specified set of bit positions within the floating point data to be read out as 0s rather than 1s.

  20. 3D Modeling of Building Indoor Spaces and Closed Doors from Imagery and Point Clouds

    Directory of Open Access Journals (Sweden)

    Lucía Díaz-Vilariño

    2015-02-01

    Full Text Available 3D models of indoor environments are increasingly gaining importance due to the wide range of applications to which they can be subjected: from redesign and visualization to monitoring and simulation. These models usually exist only for newly constructed buildings; therefore, the development of automatic approaches for reconstructing 3D indoors from imagery and/or point clouds can make the process easier, faster and cheaper. Among the constructive elements defining a building interior, doors are very common elements and their detection can be very useful either for knowing the environment structure, to perform an efficient navigation or to plan appropriate evacuation routes. The fact that doors are topologically connected to walls by being coplanar, together with the unavoidable presence of clutter and occlusions indoors, increases the inherent complexity of the automation of the recognition process. In this work, we present a pipeline of techniques used for the reconstruction and interpretation of building interiors based on point clouds and images. The methodology analyses the visibility problem of indoor environments and goes in depth with door candidate detection. The presented approach is tested in real data sets showing its potential with a high door detection rate and applicability for robust and efficient envelope reconstruction.

  1. Dimensional modeling: beyond data processing constraints.

    Science.gov (United States)

    Bunardzic, A

    1995-01-01

    The focus of information processing requirements is shifting from the on-line transaction processing (OLTP) issues to the on-line analytical processing (OLAP) issues. While the former serves to ensure the feasibility of the real-time on-line transaction processing (which has already exceeded a level of up to 1,000 transactions per second under normal conditions), the latter aims at enabling more sophisticated analytical manipulation of data. The OLTP requirements, or how to efficiently get data into the system, have been solved by applying the Relational theory in the form of Entity-Relation model. There is presently no theory related to OLAP that would resolve the analytical processing requirements as efficiently as Relational theory provided for the transaction processing. The "relational dogma" also provides the mathematical foundation for the Centralized Data Processing paradigm in which mission-critical information is incorporated as 'one and only one instance' of data, thus ensuring data integrity. In such surroundings, the information that supports business analysis and decision support activities is obtained by running predefined reports and queries that are provided by the IS department. In today's intensified competitive climate, businesses are finding that this traditional approach is not good enough. The only way to stay on top of things, and to survive and prosper, is to decentralize the IS services. The newly emerging Distributed Data Processing, with its increased emphasis on empowering the end user, does not seem to find enough merit in the relational database model to justify relying upon it. Relational theory proved too rigid and complex to accommodate the analytical processing needs. In order to satisfy the OLAP requirements, or how to efficiently get the data out of the system, different models, metaphors, and theories have been devised. All of them are pointing to the need for simplifying the highly non-intuitive mathematical constraints found

  2. Mathematical modeling and hydrodynamics of Electrochemical deburring process

    Science.gov (United States)

    Prabhu, Satisha; Abhishek Kumar, K., Dr

    2018-04-01

    The electrochemical deburring (ECD) is a variation of electrochemical machining is considered as one of the efficient methods for deburring of intersecting features and internal parts. Since manual deburring costs are comparatively high one can potentially use this method in both batch production and flow production. The other advantage of this process is that time of deburring as is on the order of seconds as compared to other methods. In this paper, the mathematical modeling of Electrochemical deburring is analysed from its deburring time and base metal removal point of view. Simultaneously material removal rate is affected by electrolyte temperature and bubble formation. The mathematical model and hydrodynamics of the process throw limelight upon optimum velocity calculations which can be theoretically determined. The analysis can be the powerful tool for prediction of the above-mentioned parameters by experimentation.

  3. Benchmark models, planes lines and points for future SUSY searches at the LHC

    International Nuclear Information System (INIS)

    AbdusSalam, S.S.; Allanach, B.C.; Dreiner, H.K.

    2012-03-01

    We define benchmark models for SUSY searches at the LHC, including the CMSSM, NUHM, mGMSB, mAMSB, MM-AMSB and p19MSSM, as well as models with R-parity violation and the NMSSM. Within the parameter spaces of these models, we propose benchmark subspaces, including planes, lines and points along them. The planes may be useful for presenting results of the experimental searches in different SUSY scenarios, while the specific benchmark points may serve for more detailed detector performance tests and comparisons. We also describe algorithms for defining suitable benchmark points along the proposed lines in the parameter spaces, and we define a few benchmark points motivated by recent fits to existing experimental data.

  4. Benchmark models, planes lines and points for future SUSY searches at the LHC

    Energy Technology Data Exchange (ETDEWEB)

    AbdusSalam, S.S. [The Abdus Salam International Centre for Theoretical Physics, Trieste (Italy); Allanach, B.C. [Cambridge Univ. (United Kingdom). Dept. of Applied Mathematics and Theoretical Physics; Dreiner, H.K. [Bonn Univ. (DE). Bethe Center for Theoretical Physics and Physikalisches Inst.] (and others)

    2012-03-15

    We define benchmark models for SUSY searches at the LHC, including the CMSSM, NUHM, mGMSB, mAMSB, MM-AMSB and p19MSSM, as well as models with R-parity violation and the NMSSM. Within the parameter spaces of these models, we propose benchmark subspaces, including planes, lines and points along them. The planes may be useful for presenting results of the experimental searches in different SUSY scenarios, while the specific benchmark points may serve for more detailed detector performance tests and comparisons. We also describe algorithms for defining suitable benchmark points along the proposed lines in the parameter spaces, and we define a few benchmark points motivated by recent fits to existing experimental data.

  5. Benchmark Models, Planes, Lines and Points for Future SUSY Searches at the LHC

    CERN Document Server

    AbdusSalam, S S; Dreiner, H K; Ellis, J; Ellwanger, U; Gunion, J; Heinemeyer, S; Krämer, M; Mangano, M L; Olive, K A; Rogerson, S; Roszkowski, L; Schlaffer, M; Weiglein, G

    2011-01-01

    We define benchmark models for SUSY searches at the LHC, including the CMSSM, NUHM, mGMSB, mAMSB, MM-AMSB and p19MSSM, as well as models with R-parity violation and the NMSSM. Within the parameter spaces of these models, we propose benchmark subspaces, including planes, lines and points along them. The planes may be useful for presenting results of the experimental searches in different SUSY scenarios, while the specific benchmark points may serve for more detailed detector performance tests and comparisons. We also describe algorithms for defining suitable benchmark points along the proposed lines in the parameter spaces, and we define a few benchmark points motivated by recent fits to existing experimental data.

  6. An Automated Approach to the Generation of Structured Building Information Models from Unstructured 3d Point Cloud Scans

    DEFF Research Database (Denmark)

    Tamke, Martin; Evers, Henrik Leander; Wessel, Raoul

    2016-01-01

    In this paper we present and evaluate an approach for the automatic generation of building models in IFC BIM format from unstructured Point Cloud scans, as they result from 3dlaser scans of buildings. While the actual measurement process is relatively fast, 85% of the overall time are spend...

  7. Georeferenced Point Clouds: A Survey of Features and Point Cloud Management

    Directory of Open Access Journals (Sweden)

    Johannes Otepka

    2013-10-01

    Full Text Available This paper presents a survey of georeferenced point clouds. Concentration is, on the one hand, put on features, which originate in the measurement process themselves, and features derived by processing the point cloud. On the other hand, approaches for the processing of georeferenced point clouds are reviewed. This includes the data structures, but also spatial processing concepts. We suggest a categorization of features into levels that reflect the amount of processing. Point clouds are found across many disciplines, which is reflected in the versatility of the literature suggesting specific features.

  8. Minimization of energy consumption in HVAC systems with data-driven models and an interior-point method

    International Nuclear Information System (INIS)

    Kusiak, Andrew; Xu, Guanglin; Zhang, Zijun

    2014-01-01

    Highlights: • We study the energy saving of HVAC systems with a data-driven approach. • We conduct an in-depth analysis of the topology of developed Neural Network based HVAC model. • We apply interior-point method to solving a Neural Network based HVAC optimization model. • The uncertain building occupancy is incorporated in the minimization of HVAC energy consumption. • A significant potential of saving HVAC energy is discovered. - Abstract: In this paper, a data-driven approach is applied to minimize energy consumption of a heating, ventilating, and air conditioning (HVAC) system while maintaining the thermal comfort of a building with uncertain occupancy level. The uncertainty of arrival and departure rate of occupants is modeled by the Poisson and uniform distributions, respectively. The internal heating gain is calculated from the stochastic process of the building occupancy. Based on the observed and simulated data, a multilayer perceptron algorithm is employed to model and simulate the HVAC system. The data-driven models accurately predict future performance of the HVAC system based on the control settings and the observed historical information. An optimization model is formulated and solved with the interior-point method. The optimization results are compared with the results produced by the simulation models

  9. Processing Terrain Point Cloud Data

    KAUST Repository

    DeVore, Ronald; Petrova, Guergana; Hielsberg, Matthew; Owens, Luke; Clack, Billy; Sood, Alok

    2013-01-01

    Terrain point cloud data are typically acquired through some form of Light Detection And Ranging sensing. They form a rich resource that is important in a variety of applications including navigation, line of sight, and terrain visualization

  10. A Combined Control Chart for Identifying Out–Of–Control Points in Multivariate Processes

    Directory of Open Access Journals (Sweden)

    Marroquín–Prado E.

    2010-10-01

    Full Text Available The Hotelling's T2 control chart is widely used to identify out–of–control signals in multivariate processes. However, this chart is not sensitive to small shifts in the process mean vec tor. In this work we propose a control chart to identify out–of–control signals. The proposed chart is a combination of Hotelling's T2 chart, M chart proposed by Hayter et al. (1994 and a new chart based on Principal Components. The combination of these charts identifies any type and size of change in the process mean vector. Us ing simulation and the Average Run Length (ARL, the performance of the proposed control chart is evaluated. The ARL means the average points within control before an out–of–control point is detected, The results of the simulation show that the proposed chart is more sensitive that each one of the three charts individually

  11. Final Report Collaborative Project. Improving the Representation of Coastal and Estuarine Processes in Earth System Models

    Energy Technology Data Exchange (ETDEWEB)

    Bryan, Frank [National Center for Atmospheric Research, Boulder, CO (United States); Dennis, John [National Center for Atmospheric Research, Boulder, CO (United States); MacCready, Parker [Univ. of Washington, Seattle, WA (United States); Whitney, Michael [Univ. of Connecticut

    2015-11-20

    This project aimed to improve long term global climate simulations by resolving and enhancing the representation of the processes involved in the cycling of freshwater through estuaries and coastal regions. This was a collaborative multi-institution project consisting of physical oceanographers, climate model developers, and computational scientists. It specifically targeted the DOE objectives of advancing simulation and predictive capability of climate models through improvements in resolution and physical process representation. The main computational objectives were: 1. To develop computationally efficient, but physically based, parameterizations of estuary and continental shelf mixing processes for use in an Earth System Model (CESM). 2. To develop a two-way nested regional modeling framework in order to dynamically downscale the climate response of particular coastal ocean regions and to upscale the impact of the regional coastal processes to the global climate in an Earth System Model (CESM). 3. To develop computational infrastructure to enhance the efficiency of data transfer between specific sources and destinations, i.e., a point-to-point communication capability, (used in objective 1) within POP, the ocean component of CESM.

  12. Nonuniform multiview color texture mapping of image sequence and three-dimensional model for faded cultural relics with sift feature points

    Science.gov (United States)

    Li, Na; Gong, Xingyu; Li, Hongan; Jia, Pengtao

    2018-01-01

    For faded relics, such as Terracotta Army, the 2D-3D registration between an optical camera and point cloud model is an important part for color texture reconstruction and further applications. This paper proposes a nonuniform multiview color texture mapping for the image sequence and the three-dimensional (3D) model of point cloud collected by Handyscan3D. We first introduce nonuniform multiview calibration, including the explanation of its algorithm principle and the analysis of its advantages. We then establish transformation equations based on sift feature points for the multiview image sequence. At the same time, the selection of nonuniform multiview sift feature points is introduced in detail. Finally, the solving process of the collinear equations based on multiview perspective projection is given with three steps and the flowchart. In the experiment, this method is applied to the color reconstruction of the kneeling figurine, Tangsancai lady, and general figurine. These results demonstrate that the proposed method provides an effective support for the color reconstruction of the faded cultural relics and be able to improve the accuracy of 2D-3D registration between the image sequence and the point cloud model.

  13. Point process analyses of variations in smoking rate by setting, mood, gender, and dependence

    Science.gov (United States)

    Shiffman, Saul; Rathbun, Stephen L.

    2010-01-01

    The immediate emotional and situational antecedents of ad libitum smoking are still not well understood. We re-analyzed data from Ecological Momentary Assessment using novel point-process analyses, to assess how craving, mood, and social setting influence smoking rate, as well as assessing the moderating effects of gender and nicotine dependence. 304 smokers recorded craving, mood, and social setting using electronic diaries when smoking and at random nonsmoking times over 16 days of smoking. Point-process analysis, which makes use of the known random sampling scheme for momentary variables, examined main effects of setting and interactions with gender and dependence. Increased craving was associated with higher rates of smoking, particularly among women. Negative affect was not associated with smoking rate, even in interaction with arousal, but restlessness was associated with substantially higher smoking rates. Women's smoking tended to be less affected by negative affect. Nicotine dependence had little moderating effect on situational influences. Smoking rates were higher when smokers were alone or with others smoking, and smoking restrictions reduced smoking rates. However, the presence of others smoking undermined the effects of restrictions. The more sensitive point-process analyses confirmed earlier findings, including the surprising conclusion that negative affect by itself was not related to smoking rates. Contrary to hypothesis, men's and not women's smoking was influenced by negative affect. Both smoking restrictions and the presence of others who are not smoking suppress smoking, but others’ smoking undermines the effects of restrictions. Point-process analyses of EMA data can bring out even small influences on smoking rate. PMID:21480683

  14. APPROACH TO SYNTHESIS OF PASSIVE INFRARED DETECTORS BASED ON QUASI-POINT MODEL OF QUALIFIED INTRUDER

    Directory of Open Access Journals (Sweden)

    I. V. Bilizhenko

    2017-01-01

    Full Text Available Subject of Research. The paper deals with synthesis of passive infra red (PIR detectors with enhanced detection capability of qualified intruder who uses different types of detection countermeasures: the choice of specific movement direction and disguise in infrared band. Methods. We propose an approach based on quasi-point model of qualified intruder. It includes: separation of model priority parameters, formation of partial detection patterns adapted to those parameters and multi channel signal processing. Main Results. Quasi-pointmodel of qualified intruder consisting of different fragments was suggested. Power density difference was used for model parameters estimation. Criteria were formulated for detection pattern parameters choice on the basis of model parameters. Pyroelectric sensor with nine sensitive elements was applied for increasing the signal information content. Multi-channel processing with multiple partial detection patterns was proposed optimized for detection of intruder's specific movement direction. Practical Relevance. Developed functional device diagram can be realized both by hardware and software and is applicable as one of detection channels for dual technology passive infrared and microwave detectors.

  15. Numerical Simulation of a Grinding Process Model for the Spatial Work-pieces: Development of Modeling Techniques

    Directory of Open Access Journals (Sweden)

    S. A. Voronov

    2015-01-01

    Full Text Available The article presents a literature review in simulation of grinding processes. It takes into consideration the statistical, energy based, and imitation approaches to simulation of grinding forces. Main stages of interaction between abrasive grains and machined surface are shown. The article describes main approaches to the geometry modeling of forming new surfaces when grinding. The review of approaches to the chip and pile up effect numerical modeling is shown. Advantages and disadvantages of grain-to-surface interaction by means of finite element method and molecular dynamics method are considered. The article points out that it is necessary to take into consideration the system dynamics and its effect on the finished surface. Structure of the complex imitation model of grinding process dynamics for flexible work-pieces with spatial surface geometry is proposed from the literature review. The proposed model of spatial grinding includes the model of work-piece dynamics, model of grinding wheel dynamics, phenomenological model of grinding forces based on 3D geometry modeling algorithm. Model gives the following results for spatial grinding process: vibration of machining part and grinding wheel, machined surface geometry, static deflection of the surface and grinding forces under various cutting conditions.

  16. An Automated Approach to the Generation of Structured Building Information Models from Unstructured 3d Point Cloud Scans

    DEFF Research Database (Denmark)

    Tamke, Martin; Evers, Henrik Leander; Wessel, Raoul

    2016-01-01

    In this paper we present and evaluate an approach for the automatic generation of building models in IFC BIM format from unstructured Point Cloud scans, as they result from 3dlaser scans of buildings. While the actual measurement process is relatively fast, 85% of the overall time are spend on th...

  17. 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.

  18. EBTR design-point selection

    International Nuclear Information System (INIS)

    Krakowski, R.A.; Bathke, C.G.

    1981-01-01

    The procedure used to select the design point for the ELMO Bumpy Torus Reactor (EBTR) study is described. The models used in each phase of the selection process are described, with an emphasis placed on the parametric design curves produced by each model. The tradeoffs related to burn physics, stability/equilibrium, electron-ring physics, and magnetics design are discussed. The resulting design point indicates a plasma with a 35-m major radius and a 1-m minor radium operating at an average core-plasma beta of 0.17, which at approx. 30 keV produces an average neutron wall loading of 1.4 MW/m 2 while maintaining key magnet (< 10 T) and total power (less than or equal to 4000 MWt) constraints

  19. Adaptation to Elastic Loads and BMI Robot Controls During Rat Locomotion examined with Point-Process GLMs.

    Directory of Open Access Journals (Sweden)

    Weiguo eSong

    2015-04-01

    Full Text Available Currently little is known about how a mechanically coupled BMI system’s actions are integrated into ongoing body dynamics. We tested a locomotor task augmented with a BMI system driving a robot mechanically interacting with a rat under three conditions: control locomotion (BL, ‘simple elastic load’ (E and ‘BMI with elastic load’ (BMI/E. The effect of the BMI was to allow compensation of the elastic load as a function of the neural drive. Neurons recorded here were close to one another in cortex, all within a 200 micron diameter horizontal distance of one another. The interactions of these close assemblies of neurons may differ from those among neurons at longer distances in BMI tasks and thus are important to explore. A point process generalized linear model (GLM, was used to examine connectivity at two different binning timescales (1ms vs. 10ms. We used GLM models to fit non-Poisson neural dynamics solely using other neurons’ prior neural activity as covariates. Models at different timescales were compared based on Kolmogorov-Smirnov (KS goodness-of-fit and parsimony. About 15% of cells with non-Poisson firing were well fitted with the neuron-to-neuron models alone. More such cells were fitted at the 1ms binning than 10ms. Positive connection parameters (‘excitation’ ~70% exceeded negative parameters (‘inhibition’ ~30%. Significant connectivity changes in the GLM determined networks of well-fitted neurons occurred between the conditions. However, a common core of connections comprising at least ~15% of connections persisted between any two of the three conditions. Significantly almost twice as many connections were in common between the two load conditions (~27%, compared to between either load condition and the baseline. This local point process GLM identified neural correlation structure and the changes seen across task conditions in the rats in this neural subset may be intrinsic to cortex or due to feedback and input

  20. Prospects for direct neutron capture measurements on s-process branching point isotopes

    Energy Technology Data Exchange (ETDEWEB)

    Guerrero, C.; Lerendegui-Marco, J.; Quesada, J.M. [Universidad de Sevilla, Dept. de Fisica Atomica, Molecular y Nuclear, Sevilla (Spain); Domingo-Pardo, C. [CSIC-Universidad de Valencia, Instituto de Fisica Corpuscular, Valencia (Spain); Kaeppeler, F. [Karlsruhe Institute of Technology, Institut fuer Kernphysik, Karlsruhe (Germany); Palomo, F.R. [Universidad de Sevilla, Dept. de Ingenieria Electronica, Sevilla (Spain); Reifarth, R. [Goethe-Universitaet Frankfurt am Main, Frankfurt am Main (Germany)

    2017-05-15

    The neutron capture cross sections of several unstable key isotopes acting as branching points in the s-process are crucial for stellar nucleosynthesis studies, but they are very challenging to measure directly due to the difficult production of sufficient sample material, the high activity of the resulting samples, and the actual (n, γ) measurement, where high neutron fluxes and effective background rejection capabilities are required. At present there are about 21 relevant s-process branching point isotopes whose cross section could not be measured yet over the neutron energy range of interest for astrophysics. However, the situation is changing with some very recent developments and upcoming technologies. This work introduces three techniques that will change the current paradigm in the field: the use of γ-ray imaging techniques in (n, γ) experiments, the production of moderated neutron beams using high-power lasers, and double capture experiments in Maxwellian neutron beams. (orig.)

  1. Determination of the impact of RGB points cloud attribute quality on color-based segmentation process

    Directory of Open Access Journals (Sweden)

    Bartłomiej Kraszewski

    2015-06-01

    Full Text Available The article presents the results of research on the effect that radiometric quality of point cloud RGB attributes have on color-based segmentation. In the research, a point cloud with a resolution of 5 mm, received from FAROARO Photon 120 scanner, described the fragment of an office’s room and color images were taken by various digital cameras. The images were acquired by SLR Nikon D3X, and SLR Canon D200 integrated with the laser scanner, compact camera Panasonic TZ-30 and a mobile phone digital camera. Color information from images was spatially related to point cloud in FAROARO Scene software. The color-based segmentation of testing data was performed with the use of a developed application named “RGB Segmentation”. The application was based on public Point Cloud Libraries (PCL and allowed to extract subsets of points fulfilling the criteria of segmentation from the source point cloud using region growing method.Using the developed application, the segmentation of four tested point clouds containing different RGB attributes from various images was performed. Evaluation of segmentation process was performed based on comparison of segments acquired using the developed application and extracted manually by an operator. The following items were compared: the number of obtained segments, the number of correctly identified objects and the correctness of segmentation process. The best correctness of segmentation and most identified objects were obtained using the data with RGB attribute from Nikon D3X images. Based on the results it was found that quality of RGB attributes of point cloud had impact only on the number of identified objects. In case of correctness of the segmentation, as well as its error no apparent relationship between the quality of color information and the result of the process was found.[b]Keywords[/b]: terrestrial laser scanning, color-based segmentation, RGB attribute, region growing method, digital images, points cloud

  2. Assessment of saddle-point-mass predictions for astrophysical applications

    Energy Technology Data Exchange (ETDEWEB)

    Kelic, A.; Schmidt, K.H.

    2005-07-01

    Using available experimental data on fission barriers and ground-state masses, a detailed study on the predictions of different models concerning the isospin dependence of saddle-point masses is performed. Evidence is found that several macroscopic models yield unrealistic saddle-point masses for very neutron-rich nuclei, which are relevant for the r-process nucleosynthesis. (orig.)

  3. Fixed-Point Configurable Hardware Components

    Directory of Open Access Journals (Sweden)

    Rocher Romuald

    2006-01-01

    Full Text Available To reduce the gap between the VLSI technology capability and the designer productivity, design reuse based on IP (intellectual properties is commonly used. In terms of arithmetic accuracy, the generated architecture can generally only be configured through the input and output word lengths. In this paper, a new kind of method to optimize fixed-point arithmetic IP has been proposed. The architecture cost is minimized under accuracy constraints defined by the user. Our approach allows exploring the fixed-point search space and the algorithm-level search space to select the optimized structure and fixed-point specification. To significantly reduce the optimization and design times, analytical models are used for the fixed-point optimization process.

  4. COLLISION VISUALIZATION OF A LASER-SCANNED POINT CLOUD OF STREETS AND A FESTIVAL FLOAT MODEL USED FOR THE REVIVAL OF A TRADITIONAL PROCESSION ROUTE

    Directory of Open Access Journals (Sweden)

    W. Li

    2017-09-01

    Full Text Available Recently, laser-scanning technology, especially mobile mapping systems (MMSs, has been applied to measure 3D urban scenes. Thus, it has become possible to simulate a traditional cultural event in a virtual space constructed using measured point clouds. In this paper, we take the festival float procession in the Gion Festival that has a long history in Kyoto City, Japan. The city government plans to revive the original procession route that is narrow and not used at present. For the revival, it is important to know whether a festival float collides with houses, billboards, electric wires or other objects along the original route. Therefore, in this paper, we propose a method for visualizing the collisions of point cloud objects. The advantageous features of our method are (1 a see-through visualization with a correct depth feel that is helpful to robustly determine the collision areas, (2 the ability to visualize areas of high collision risk as well as real collision areas, and (3 the ability to highlight target visualized areas by increasing the point densities there.

  5. Collision Visualization of a Laser-Scanned Point Cloud of Streets and a Festival Float Model Used for the Revival of a Traditional Procession Route

    Science.gov (United States)

    Li, W.; Shigeta, K.; Hasegawa, K.; Li, L.; Yano, K.; Tanaka, S.

    2017-09-01

    Recently, laser-scanning technology, especially mobile mapping systems (MMSs), has been applied to measure 3D urban scenes. Thus, it has become possible to simulate a traditional cultural event in a virtual space constructed using measured point clouds. In this paper, we take the festival float procession in the Gion Festival that has a long history in Kyoto City, Japan. The city government plans to revive the original procession route that is narrow and not used at present. For the revival, it is important to know whether a festival float collides with houses, billboards, electric wires or other objects along the original route. Therefore, in this paper, we propose a method for visualizing the collisions of point cloud objects. The advantageous features of our method are (1) a see-through visualization with a correct depth feel that is helpful to robustly determine the collision areas, (2) the ability to visualize areas of high collision risk as well as real collision areas, and (3) the ability to highlight target visualized areas by increasing the point densities there.

  6. A first packet processing subdomain cluster model based on SDN

    Science.gov (United States)

    Chen, Mingyong; Wu, Weimin

    2017-08-01

    For the current controller cluster packet processing performance bottlenecks and controller downtime problems. An SDN controller is proposed to allocate the priority of each device in the SDN (Software Defined Network) network, and the domain contains several network devices and Controller, the controller is responsible for managing the network equipment within the domain, the switch performs data delivery based on the load of the controller, processing network equipment data. The experimental results show that the model can effectively solve the risk of single point failure of the controller, and can solve the performance bottleneck of the first packet processing.

  7. 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

  8. Heat source model for welding process

    International Nuclear Information System (INIS)

    Doan, D.D.

    2006-10-01

    One of the major industrial stakes of the welding simulation relates to the control of mechanical effects of the process (residual stress, distortions, fatigue strength... ). These effects are directly dependent on the temperature evolutions imposed during the welding process. To model this thermal loading, an original method is proposed instead of the usual methods like equivalent heat source approach or multi-physical approach. This method is based on the estimation of the weld pool shape together with the heat flux crossing the liquid/solid interface, from experimental data measured in the solid part. Its originality consists in solving an inverse Stefan problem specific to the welding process, and it is shown how to estimate the parameters of the weld pool shape. To solve the heat transfer problem, the interface liquid/solid is modeled by a Bezier curve ( 2-D) or a Bezier surface (3-D). This approach is well adapted to a wide diversity of weld pool shapes met for the majority of the current welding processes (TIG, MlG-MAG, Laser, FE, Hybrid). The number of parameters to be estimated is weak enough, according to the cases considered from 2 to 5 in 20 and 7 to 16 in 3D. A sensitivity study leads to specify the location of the sensors, their number and the set of measurements required to a good estimate. The application of the method on test results of welding TIG on thin stainless steel sheets in emerging and not emerging configurations, shows that only one measurement point is enough to estimate the various weld pool shapes in 20, and two points in 3D, whatever the penetration is full or not. In the last part of the work, a methodology is developed for the transient analysis. It is based on the Duvaut's transformation which overpasses the discontinuity of the liquid metal interface and therefore gives a continuous variable for the all spatial domain. Moreover, it allows to work on a fixed mesh grid and the new inverse problem is equivalent to identify a source

  9. Sigma models in the presence of dynamical point-like defects

    International Nuclear Information System (INIS)

    Doikou, Anastasia; Karaiskos, Nikos

    2013-01-01

    Point-like Liouville integrable dynamical defects are introduced in the context of the Landau–Lifshitz and Principal Chiral (Faddeev–Reshetikhin) models. Based primarily on the underlying quadratic algebra we identify the first local integrals of motion, the associated Lax pairs as well as the relevant sewing conditions around the defect point. The involution of the integrals of motion is shown taking into account the sewing conditions.

  10. Model-based decoding, information estimation, and change-point detection techniques for multineuron spike trains.

    Science.gov (United States)

    Pillow, Jonathan W; Ahmadian, Yashar; Paninski, Liam

    2011-01-01

    One of the central problems in systems neuroscience is to understand how neural spike trains convey sensory information. Decoding methods, which provide an explicit means for reading out the information contained in neural spike responses, offer a powerful set of tools for studying the neural coding problem. Here we develop several decoding methods based on point-process neural encoding models, or forward models that predict spike responses to stimuli. These models have concave log-likelihood functions, which allow efficient maximum-likelihood model fitting and stimulus decoding. We present several applications of the encoding model framework to the problem of decoding stimulus information from population spike responses: (1) a tractable algorithm for computing the maximum a posteriori (MAP) estimate of the stimulus, the most probable stimulus to have generated an observed single- or multiple-neuron spike train response, given some prior distribution over the stimulus; (2) a gaussian approximation to the posterior stimulus distribution that can be used to quantify the fidelity with which various stimulus features are encoded; (3) an efficient method for estimating the mutual information between the stimulus and the spike trains emitted by a neural population; and (4) a framework for the detection of change-point times (the time at which the stimulus undergoes a change in mean or variance) by marginalizing over the posterior stimulus distribution. We provide several examples illustrating the performance of these estimators with simulated and real neural data.

  11. A Labeling Model Based on the Region of Movability for Point-Feature Label Placement

    Directory of Open Access Journals (Sweden)

    Lin Li

    2016-09-01

    Full Text Available Automatic point-feature label placement (PFLP is a fundamental task for map visualization. As the dominant solutions to the PFLP problem, fixed-position and slider models have been widely studied in previous research. However, the candidate labels generated with these models are set to certain fixed positions or a specified track line for sliding. Thus, the whole surrounding space of a point feature is not sufficiently used for labeling. Hence, this paper proposes a novel label model based on the region of movability, which comes from plane collision detection theory. The model defines a complete conflict-free search space for label placement. On the premise of no conflict with the point, line, and area features, the proposed model utilizes the surrounding zone of the point feature to generate candidate label positions. By combining with heuristic search method, the model achieves high-quality label placement. In addition, the flexibility of the proposed model enables placing arbitrarily shaped labels.

  12. On the asymptotic ergodic capacity of FSO links with generalized pointing error model

    KAUST Repository

    Al-Quwaiee, Hessa

    2015-09-11

    Free-space optical (FSO) communication systems are negatively affected by two physical phenomenon, namely, scintillation due to atmospheric turbulence and pointing errors. To quantize the effect of these two factors on FSO system performance, we need an effective mathematical model for them. Scintillations are typically modeled by the log-normal and Gamma-Gamma distributions for weak and strong turbulence conditions, respectively. In this paper, we propose and study a generalized pointing error model based on the Beckmann distribution. We then derive the asymptotic ergodic capacity of FSO systems under the joint impact of turbulence and generalized pointing error impairments. © 2015 IEEE.

  13. Two step estimation for Neyman-Scott point process with inhomogeneous cluster centers

    Czech Academy of Sciences Publication Activity Database

    Mrkvička, T.; Muška, Milan; Kubečka, Jan

    2014-01-01

    Roč. 24, č. 1 (2014), s. 91-100 ISSN 0960-3174 R&D Projects: GA ČR(CZ) GA206/07/1392 Institutional support: RVO:60077344 Keywords : bayesian method * clustering * inhomogeneous point process Subject RIV: EH - Ecology, Behaviour Impact factor: 1.623, year: 2014

  14. Shape Modelling Using Markov Random Field Restoration of Point Correspondences

    DEFF Research Database (Denmark)

    Paulsen, Rasmus Reinhold; Hilger, Klaus Baggesen

    2003-01-01

    A method for building statistical point distribution models is proposed. The novelty in this paper is the adaption of Markov random field regularization of the correspondence field over the set of shapes. The new approach leads to a generative model that produces highly homogeneous polygonized sh...

  15. A Model Stitching Architecture for Continuous Full Flight-Envelope Simulation of Fixed-Wing Aircraft and Rotorcraft from Discrete Point Linear Models

    Science.gov (United States)

    2016-04-01

    AND ROTORCRAFT FROM DISCRETE -POINT LINEAR MODELS Eric L. Tobias and Mark B. Tischler Aviation Development Directorate Aviation and Missile...Stitching Architecture for Continuous Full Flight-Envelope Simulation of Fixed-Wing Aircraft and Rotorcraft from Discrete -Point Linear Models 5...of discrete -point linear models and trim data. The model stitching simulation architecture is applicable to any aircraft configuration readily

  16. Identifying influential data points in hydrological model calibration and their impact on streamflow predictions

    Science.gov (United States)

    Wright, David; Thyer, Mark; Westra, Seth

    2015-04-01

    Highly influential data points are those that have a disproportionately large impact on model performance, parameters and predictions. However, in current hydrological modelling practice the relative influence of individual data points on hydrological model calibration is not commonly evaluated. This presentation illustrates and evaluates several influence diagnostics tools that hydrological modellers can use to assess the relative influence of data. The feasibility and importance of including influence detection diagnostics as a standard tool in hydrological model calibration is discussed. Two classes of influence diagnostics are evaluated: (1) computationally demanding numerical "case deletion" diagnostics; and (2) computationally efficient analytical diagnostics, based on Cook's distance. These diagnostics are compared against hydrologically orientated diagnostics that describe changes in the model parameters (measured through the Mahalanobis distance), performance (objective function displacement) and predictions (mean and maximum streamflow). These influence diagnostics are applied to two case studies: a stage/discharge rating curve model, and a conceptual rainfall-runoff model (GR4J). Removing a single data point from the calibration resulted in differences to mean flow predictions of up to 6% for the rating curve model, and differences to mean and maximum flow predictions of up to 10% and 17%, respectively, for the hydrological model. When using the Nash-Sutcliffe efficiency in calibration, the computationally cheaper Cook's distance metrics produce similar results to the case-deletion metrics at a fraction of the computational cost. However, Cooks distance is adapted from linear regression with inherit assumptions on the data and is therefore less flexible than case deletion. Influential point detection diagnostics show great potential to improve current hydrological modelling practices by identifying highly influential data points. The findings of this

  17. Hybrid Scheme for Modeling Local Field Potentials from Point-Neuron Networks.

    Science.gov (United States)

    Hagen, Espen; Dahmen, David; Stavrinou, Maria L; Lindén, Henrik; Tetzlaff, Tom; van Albada, Sacha J; Grün, Sonja; Diesmann, Markus; Einevoll, Gaute T

    2016-12-01

    With rapidly advancing multi-electrode recording technology, the local field potential (LFP) has again become a popular measure of neuronal activity in both research and clinical applications. Proper understanding of the LFP requires detailed mathematical modeling incorporating the anatomical and electrophysiological features of neurons near the recording electrode, as well as synaptic inputs from the entire network. Here we propose a hybrid modeling scheme combining efficient point-neuron network models with biophysical principles underlying LFP generation by real neurons. The LFP predictions rely on populations of network-equivalent multicompartment neuron models with layer-specific synaptic connectivity, can be used with an arbitrary number of point-neuron network populations, and allows for a full separation of simulated network dynamics and LFPs. We apply the scheme to a full-scale cortical network model for a ∼1 mm 2 patch of primary visual cortex, predict laminar LFPs for different network states, assess the relative LFP contribution from different laminar populations, and investigate effects of input correlations and neuron density on the LFP. The generic nature of the hybrid scheme and its public implementation in hybridLFPy form the basis for LFP predictions from other and larger point-neuron network models, as well as extensions of the current application with additional biological detail. © The Author 2016. Published by Oxford University Press.

  18. Temporal Information Processing and Stability Analysis of the MHSN Neuron Model in DDF

    Directory of Open Access Journals (Sweden)

    Saket Kumar Choudhary

    2016-12-01

    Full Text Available Implementation of a neuron like information processing structure at hardware level is a burning research problem. In this article, we analyze the modified hybrid spiking neuron model (the MHSN model in distributed delay framework (DDF for hardware level implementation point of view. We investigate its temporal information processing capability in term of inter-spike-interval (ISI distribution. We also perform the stability analysis of the MHSN model, in which, we compute nullclines, steady state solution, eigenvalues corresponding the MHSN model. During phase plane analysis, we notice that the MHSN model generates limit cycle oscillations which is an important phenomenon in many biological processes. Qualitative behavior of these limit cycle does not changes due to the variation in applied input stimulus, however, delay effect the spiking activity and duration of cycle get altered.

  19. Multi-Valued Modal Fixed Point Logics for Model Checking

    Science.gov (United States)

    Nishizawa, Koki

    In this paper, I will show how multi-valued logics are used for model checking. Model checking is an automatic technique to analyze correctness of hardware and software systems. A model checker is based on a temporal logic or a modal fixed point logic. That is to say, a system to be checked is formalized as a Kripke model, a property to be satisfied by the system is formalized as a temporal formula or a modal formula, and the model checker checks that the Kripke model satisfies the formula. Although most existing model checkers are based on 2-valued logics, recently new attempts have been made to extend the underlying logics of model checkers to multi-valued logics. I will summarize these new results.

  20. Predictive error dependencies when using pilot points and singular value decomposition in groundwater model calibration

    DEFF Research Database (Denmark)

    Christensen, Steen; Doherty, John

    2008-01-01

    A significant practical problem with the pilot point method is to choose the location of the pilot points. We present a method that is intended to relieve the modeler from much of this responsibility. The basic idea is that a very large number of pilot points are distributed more or less uniformly...... over the model area. Singular value decomposition (SVD) of the (possibly weighted) sensitivity matrix of the pilot point based model produces eigenvectors of which we pick a small number corresponding to significant eigenvalues. Super parameters are defined as factors through which parameter...... combinations corresponding to the chosen eigenvectors are multiplied to obtain the pilot point values. The model can thus be transformed from having many-pilot-point parameters to having a few super parameters that can be estimated by nonlinear regression on the basis of the available observations. (This...

  1. The application of prototype point processes for the summary and description of California wildfires

    Science.gov (United States)

    Nichols, K.; Schoenberg, F.P.; Keeley, J.E.; Bray, A.; Diez, D.

    2011-01-01

    A method for summarizing repeated realizations of a space-time marked point process, known as prototyping, is discussed and applied to catalogues of wildfires in California. Prototype summaries are constructed for varying time intervals using California wildfire data from 1990 to 2006. Previous work on prototypes for temporal and space-time point processes is extended here to include methods for computing prototypes with marks and the incorporation of prototype summaries into hierarchical clustering algorithms, the latter of which is used to delineate fire seasons in California. Other results include summaries of patterns in the spatial-temporal distribution of wildfires within each wildfire season. ?? 2011 Blackwell Publishing Ltd.

  2. A FAST METHOD FOR MEASURING THE SIMILARITY BETWEEN 3D MODEL AND 3D POINT CLOUD

    Directory of Open Access Journals (Sweden)

    Z. Zhang

    2016-06-01

    Full Text Available This paper proposes a fast method for measuring the partial Similarity between 3D Model and 3D point Cloud (SimMC. It is crucial to measure SimMC for many point cloud-related applications such as 3D object retrieval and inverse procedural modelling. In our proposed method, the surface area of model and the Distance from Model to point Cloud (DistMC are exploited as measurements to calculate SimMC. Here, DistMC is defined as the weighted distance of the distances between points sampled from model and point cloud. Similarly, Distance from point Cloud to Model (DistCM is defined as the average distance of the distances between points in point cloud and model. In order to reduce huge computational burdens brought by calculation of DistCM in some traditional methods, we define SimMC as the ratio of weighted surface area of model to DistMC. Compared to those traditional SimMC measuring methods that are only able to measure global similarity, our method is capable of measuring partial similarity by employing distance-weighted strategy. Moreover, our method is able to be faster than other partial similarity assessment methods. We demonstrate the superiority of our method both on synthetic data and laser scanning data.

  3. Finding a single point of truth

    Energy Technology Data Exchange (ETDEWEB)

    Sokolov, S.; Thijssen, H. [Autodesk Inc, Toronto, ON (Canada); Laslo, D.; Martin, J. [Autodesk Inc., San Rafael, CA (United States)

    2010-07-01

    Electric utilities collect large volumes of data at every level of their business, including SCADA, Smart Metering and Smart Grid initiatives, LIDAR and other 3D imagery surveys. Different types of database systems are used to store the information, rendering data flow within the utility business process extremely complicated. The industry trend has been to endure redundancy of data input and maintenance of multiple copies of the same data across different solution data sets. Efforts have been made to improve the situation with point to point interfaces, but with the tools and solutions available today, a single point of truth can be achieved. Consolidated and validated data can be published into a data warehouse at the right point in the process, making the information available to all other enterprise systems and solutions. This paper explained how the single point of truth spatial data warehouse and process automation services can be configured to streamline the flow of data within the utility business process using the initiate-plan-execute-close (IPEC) utility workflow model. The paper first discussed geospatial challenges faced by utilities and then presented the approach and technology aspects. It was concluded that adoption of systems and solutions that can function with and be controlled by the IPEC workflow can provide significant improvement for utility operations, particularly if those systems are coupled with the spatial data warehouse that reflects a single point of truth. 6 refs., 3 figs.

  4. EFFICIENT LIDAR POINT CLOUD DATA MANAGING AND PROCESSING IN A HADOOP-BASED DISTRIBUTED FRAMEWORK

    Directory of Open Access Journals (Sweden)

    C. Wang

    2017-10-01

    Full Text Available Light Detection and Ranging (LiDAR is one of the most promising technologies in surveying and mapping，city management, forestry, object recognition, computer vision engineer and others. However, it is challenging to efficiently storage, query and analyze the high-resolution 3D LiDAR data due to its volume and complexity. In order to improve the productivity of Lidar data processing, this study proposes a Hadoop-based framework to efficiently manage and process LiDAR data in a distributed and parallel manner, which takes advantage of Hadoop’s storage and computing ability. At the same time, the Point Cloud Library (PCL, an open-source project for 2D/3D image and point cloud processing, is integrated with HDFS and MapReduce to conduct the Lidar data analysis algorithms provided by PCL in a parallel fashion. The experiment results show that the proposed framework can efficiently manage and process big LiDAR data.

  5. Efficient LIDAR Point Cloud Data Managing and Processing in a Hadoop-Based Distributed Framework

    Science.gov (United States)

    Wang, C.; Hu, F.; Sha, D.; Han, X.

    2017-10-01

    Light Detection and Ranging (LiDAR) is one of the most promising technologies in surveying and mapping city management, forestry, object recognition, computer vision engineer and others. However, it is challenging to efficiently storage, query and analyze the high-resolution 3D LiDAR data due to its volume and complexity. In order to improve the productivity of Lidar data processing, this study proposes a Hadoop-based framework to efficiently manage and process LiDAR data in a distributed and parallel manner, which takes advantage of Hadoop's storage and computing ability. At the same time, the Point Cloud Library (PCL), an open-source project for 2D/3D image and point cloud processing, is integrated with HDFS and MapReduce to conduct the Lidar data analysis algorithms provided by PCL in a parallel fashion. The experiment results show that the proposed framework can efficiently manage and process big LiDAR data.

  6. Critical Points in Distance Learning System

    Directory of Open Access Journals (Sweden)

    Airina Savickaitė

    2013-08-01

    Full Text Available Purpose – This article presents the results of distance learning system analysis, i.e. the critical elements of the distance learning system. The critical points of distance learning are a part of distance education online environment interactivity/community process model. The most important is the fact that the critical point is associated with distance learning participants. Design/methodology/approach – Comparative review of articles and analysis of distance learning module. Findings – A modern man is a lifelong learner and distance learning is a way to be a modern person. The focus on a learner and feedback is the most important thing of learning distance system. Also, attention should be paid to the lecture-appropriate knowledge and ability to convey information. Distance system adaptation is the way to improve the learner’s learning outcomes. Research limitations/implications – Different learning disciplines and learning methods may have different critical points. Practical implications – The information of analysis could be important for both lecturers and students, who studies distance education systems. There are familiar critical points which may deteriorate the quality of learning. Originality/value – The study sought to develop remote systems for applications in order to improve the quality of knowledge. Keywords: distance learning, process model, critical points. Research type: review of literature and general overview.

  7. The quantum nonlinear Schroedinger model with point-like defect

    International Nuclear Information System (INIS)

    Caudrelier, V; Mintchev, M; Ragoucy, E

    2004-01-01

    We establish a family of point-like impurities which preserve the quantum integrability of the nonlinear Schroedinger model in 1+1 spacetime dimensions. We briefly describe the construction of the exact second quantized solution of this model in terms of an appropriate reflection-transmission algebra. The basic physical properties of the solution, including the spacetime symmetry of the bulk scattering matrix, are also discussed. (letter to the editor)

  8. Students’ Algebraic Thinking Process in Context of Point and Line Properties

    Science.gov (United States)

    Nurrahmi, H.; Suryadi, D.; Fatimah, S.

    2017-09-01

    Learning of schools algebra is limited to symbols and operating procedures, so students are able to work on problems that only require the ability to operate symbols but unable to generalize a pattern as one of part of algebraic thinking. The purpose of this study is to create a didactic design that facilitates students to do algebraic thinking process through the generalization of patterns, especially in the context of the property of point and line. This study used qualitative method and includes Didactical Design Research (DDR). The result is students are able to make factual, contextual, and symbolic generalization. This happen because the generalization arises based on facts on local terms, then the generalization produced an algebraic formula that was described in the context and perspective of each student. After that, the formula uses the algebraic letter symbol from the symbol t hat uses the students’ language. It can be concluded that the design has facilitated students to do algebraic thinking process through the generalization of patterns, especially in the context of property of the point and line. The impact of this study is this design can use as one of material teaching alternative in learning of school algebra.

  9. From Point Cloud to Textured Model, the Zamani Laser Scanning ...

    African Journals Online (AJOL)

    roshan

    meshed models based on dense points has received mixed reaction from the wide range of potential end users of the final ... data, can be subdivided into the stages of data acquisition, registration, data cleaning, modelling, hole filling ..... provide management tools for site management at local and regional level. The project ...

  10. Hybrid Scheme for Modeling Local Field Potentials from Point-Neuron Networks

    DEFF Research Database (Denmark)

    Hagen, Espen; Dahmen, David; Stavrinou, Maria L

    2016-01-01

    on populations of network-equivalent multicompartment neuron models with layer-specific synaptic connectivity, can be used with an arbitrary number of point-neuron network populations, and allows for a full separation of simulated network dynamics and LFPs. We apply the scheme to a full-scale cortical network......With rapidly advancing multi-electrode recording technology, the local field potential (LFP) has again become a popular measure of neuronal activity in both research and clinical applications. Proper understanding of the LFP requires detailed mathematical modeling incorporating the anatomical...... and electrophysiological features of neurons near the recording electrode, as well as synaptic inputs from the entire network. Here we propose a hybrid modeling scheme combining efficient point-neuron network models with biophysical principles underlying LFP generation by real neurons. The LFP predictions rely...

  11. Prediction model for initial point of net vapor generation for low-flow boiling

    International Nuclear Information System (INIS)

    Sun Qi; Zhao Hua; Yang Ruichang

    2003-01-01

    The prediction of the initial point of net vapor generation is significant for the calculation of phase distribution in sub-cooled boiling. However, most of the investigations were developed in high-flow boiling, and there is no common model that could be successfully applied for the low-flow boiling. A predictive model for the initial point of net vapor generation for low-flow forced convection and natural circulation is established here, by the analysis of evaporation and condensation heat transfer. The comparison between experimental data and calculated results shows that this model can predict the net vapor generation point successfully in low-flow sub-cooled boiling

  12. Hygienic-sanitary working practices and implementation of a Hazard Analysis and Critical Control Point (HACCP plan in lobster processing industries

    Directory of Open Access Journals (Sweden)

    Cristina Farias da Fonseca

    2013-03-01

    Full Text Available This study aimed to verify the hygienic-sanitary working practices and to create and implement a Hazard Analysis Critical Control Point (HACCP in two lobster processing industries in Pernambuco State, Brazil. The industries studied process frozen whole lobsters, frozen whole cooked lobsters, and frozen lobster tails for exportation. The application of the hygienic-sanitary checklist in the industries analyzed achieved conformity rates over 96% to the aspects evaluated. The use of the Hazard Analysis Critical Control Point (HACCP plan resulted in the detection of two critical control points (CCPs including the receiving and classification steps in the processing of frozen lobster and frozen lobster tails, and an additional critical control point (CCP was detected during the cooking step of processing of the whole frozen cooked lobster. The proper implementation of the Hazard Analysis Critical Control Point (HACCP plan in the lobster processing industries studied proved to be the safest and most cost-effective method to monitor each critical control point (CCP hazards.

  13. Fast covariance estimation for innovations computed from a spatial Gibbs point process

    DEFF Research Database (Denmark)

    Coeurjolly, Jean-Francois; Rubak, Ege

    In this paper, we derive an exact formula for the covariance of two innovations computed from a spatial Gibbs point process and suggest a fast method for estimating this covariance. We show how this methodology can be used to estimate the asymptotic covariance matrix of the maximum pseudo...

  14. Steam generators secondary side chemical cleaning at Point Lepreau using the Siemen's high temperature process

    International Nuclear Information System (INIS)

    Verma, K.; MacNeil, C.; Odar, S.

    1996-01-01

    The secondary sides of all four steam generators at the Point Lepreau Nuclear Generating Stations were cleaned during the 1995 annual outage run-down using the Siemens high temperature chemical cleaning process. Traditionally all secondary side chemical cleaning exercises in CANDU as well as the other nuclear power stations in North America have been conducted using a process developed in conjunction with the Electric Power Research Institute (EPRI). The Siemens high temperature process was applied for the first time in North America at the Point Lepreau Nuclear Generating Station (PLGS). The paper discusses experiences related to the pre and post award chemical cleaning activities, chemical cleaning application, post cleaning inspection results and waste handling activities. (author)

  15. An Efficient Method to Create Digital Terrain Models from Point Clouds Collected by Mobile LiDAR Systems

    Science.gov (United States)

    Gézero, L.; Antunes, C.

    2017-05-01

    The digital terrain models (DTM) assume an essential role in all types of road maintenance, water supply and sanitation projects. The demand of such information is more significant in developing countries, where the lack of infrastructures is higher. In recent years, the use of Mobile LiDAR Systems (MLS) proved to be a very efficient technique in the acquisition of precise and dense point clouds. These point clouds can be a solution to obtain the data for the production of DTM in remote areas, due mainly to the safety, precision, speed of acquisition and the detail of the information gathered. However, the point clouds filtering and algorithms to separate "terrain points" from "no terrain points", quickly and consistently, remain a challenge that has caught the interest of researchers. This work presents a method to create the DTM from point clouds collected by MLS. The method is based in two interactive steps. The first step of the process allows reducing the cloud point to a set of points that represent the terrain's shape, being the distance between points inversely proportional to the terrain variation. The second step is based on the Delaunay triangulation of the points resulting from the first step. The achieved results encourage a wider use of this technology as a solution for large scale DTM production in remote areas.

  16. Generalized correlation of latent heats of vaporization of coal liquid model compounds between their freezing points and critical points

    Energy Technology Data Exchange (ETDEWEB)

    Sivaraman, A.; Kobuyashi, R.; Mayee, J.W.

    1984-02-01

    Based on Pitzer's three-parameter corresponding states principle, the authors have developed a correlation of the latent heat of vaporization of aromatic coal liquid model compounds for a temperature range from the freezing point to the critical point. An expansion of the form L = L/sub 0/ + ..omega..L /sub 1/ is used for the dimensionless latent heat of vaporization. This model utilizes a nonanalytic functional form based on results derived from renormalization group theory of fluids in the vicinity of the critical point. A simple expression for the latent heat of vaporization L = D/sub 1/epsilon /SUP 0.3333/ + D/sub 2/epsilon /SUP 0.8333/ + D/sub 4/epsilon /SUP 1.2083/ + E/sub 1/epsilon + E/sub 2/epsilon/sup 2/ + E/sub 3/epsilon/sup 3/ is cast in a corresponding states principle correlation for coal liquid compounds. Benzene, the basic constituent of the functional groups of the multi-ring coal liquid compounds, is used as the reference compound in the present correlation. This model works very well at both low and high reduced temperatures approaching the critical point (0.02 < epsilon = (T /SUB c/ - T)/(T /SUB c/- 0.69)). About 16 compounds, including single, two, and three-ring compounds, have been tested and the percent root-mean-square deviations in latent heat of vaporization reported and estimated through the model are 0.42 to 5.27%. Tables of the coefficients of L/sub 0/ and L/sub 1/ are presented. The contributing terms of the latent heat of vaporization function are also presented in a table for small increments of epsilon.

  17. One loop beta functions and fixed points in higher derivative sigma models

    International Nuclear Information System (INIS)

    Percacci, Roberto; Zanusso, Omar

    2010-01-01

    We calculate the one loop beta functions of nonlinear sigma models in four dimensions containing general two- and four-derivative terms. In the O(N) model there are four such terms and nontrivial fixed points exist for all N≥4. In the chiral SU(N) models there are in general six couplings, but only five for N=3 and four for N=2; we find fixed points only for N=2, 3. In the approximation considered, the four-derivative couplings are asymptotically free but the coupling in the two-derivative term has a nonzero limit. These results support the hypothesis that certain sigma models may be asymptotically safe.

  18. Using the ACT-R architecture to specify 39 quantitative process models of decision making

    Directory of Open Access Journals (Sweden)

    Julian N. Marewski

    2011-08-01

    Full Text Available Hypotheses about decision processes are often formulated qualitatively and remain silent about the interplay of decision, memorial, and other cognitive processes. At the same time, existing decision models are specified at varying levels of detail, making it difficult to compare them. We provide a methodological primer on how detailed cognitive architectures such as ACT-R allow remedying these problems. To make our point, we address a controversy, namely, whether noncompensatory or compensatory processes better describe how people make decisions from the accessibility of memories. We specify 39 models of accessibility-based decision processes in ACT-R, including the noncompensatory recognition heuristic and various other popular noncompensatory and compensatory decision models. Additionally, to illustrate how such models can be tested, we conduct a model comparison, fitting the models to one experiment and letting them generalize to another. Behavioral data are best accounted for by race models. These race models embody the noncompensatory recognition heuristic and compensatory models as a race between competing processes, dissolving the dichotomy between existing decision models.

  19. 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

  20. Development of Property Models with Uncertainty Estimate for Process Design under Uncertainty

    DEFF Research Database (Denmark)

    Hukkerikar, Amol; Sarup, Bent; Abildskov, Jens

    more reliable predictions with a new and improved set of model parameters for GC (group contribution) based and CI (atom connectivity index) based models and to quantify the uncertainties in the estimated property values from a process design point-of-view. This includes: (i) parameter estimation using....... The comparison of model prediction uncertainties with reported range of measurement uncertainties is presented for the properties with related available data. The application of the developed methodology to quantify the effect of these uncertainties on the design of different unit operations (distillation column......, the developed methodology can be used to quantify the sensitivity of process design to uncertainties in property estimates; obtain rationally the risk/safety factors in process design; and identify additional experimentation needs in order to reduce most critical uncertainties....

  1. 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.

  2. 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

  3. Joint Clustering and Component Analysis of Correspondenceless Point Sets: Application to Cardiac Statistical Modeling.

    Science.gov (United States)

    Gooya, Ali; Lekadir, Karim; Alba, Xenia; Swift, Andrew J; Wild, Jim M; Frangi, Alejandro F

    2015-01-01

    Construction of Statistical Shape Models (SSMs) from arbitrary point sets is a challenging problem due to significant shape variation and lack of explicit point correspondence across the training data set. In medical imaging, point sets can generally represent different shape classes that span healthy and pathological exemplars. In such cases, the constructed SSM may not generalize well, largely because the probability density function (pdf) of the point sets deviates from the underlying assumption of Gaussian statistics. To this end, we propose a generative model for unsupervised learning of the pdf of point sets as a mixture of distinctive classes. A Variational Bayesian (VB) method is proposed for making joint inferences on the labels of point sets, and the principal modes of variations in each cluster. The method provides a flexible framework to handle point sets with no explicit point-to-point correspondences. We also show that by maximizing the marginalized likelihood of the model, the optimal number of clusters of point sets can be determined. We illustrate this work in the context of understanding the anatomical phenotype of the left and right ventricles in heart. To this end, we use a database containing hearts of healthy subjects, patients with Pulmonary Hypertension (PH), and patients with Hypertrophic Cardiomyopathy (HCM). We demonstrate that our method can outperform traditional PCA in both generalization and specificity measures.

  4. Nonlinear signal processing using neural networks: Prediction and system modelling

    Energy Technology Data Exchange (ETDEWEB)

    Lapedes, A.; Farber, R.

    1987-06-01

    The backpropagation learning algorithm for neural networks is developed into a formalism for nonlinear signal processing. We illustrate the method by selecting two common topics in signal processing, prediction and system modelling, and show that nonlinear applications can be handled extremely well by using neural networks. The formalism is a natural, nonlinear extension of the linear Least Mean Squares algorithm commonly used in adaptive signal processing. Simulations are presented that document the additional performance achieved by using nonlinear neural networks. First, we demonstrate that the formalism may be used to predict points in a highly chaotic time series with orders of magnitude increase in accuracy over conventional methods including the Linear Predictive Method and the Gabor-Volterra-Weiner Polynomial Method. Deterministic chaos is thought to be involved in many physical situations including the onset of turbulence in fluids, chemical reactions and plasma physics. Secondly, we demonstrate the use of the formalism in nonlinear system modelling by providing a graphic example in which it is clear that the neural network has accurately modelled the nonlinear transfer function. It is interesting to note that the formalism provides explicit, analytic, global, approximations to the nonlinear maps underlying the various time series. Furthermore, the neural net seems to be extremely parsimonious in its requirements for data points from the time series. We show that the neural net is able to perform well because it globally approximates the relevant maps by performing a kind of generalized mode decomposition of the maps. 24 refs., 13 figs.

  5. [On-line processing mechanisms in text comprehension: a theoretical review on constructing situation models].

    Science.gov (United States)

    Iseki, Ryuta

    2004-12-01

    This article reviewed research on construction of situation models during reading. To position variety of research in overall process appropriately, an unitary framework was devised in terms of three theories for on-line processing: resonance process, event-indexing model, and constructionist theory. Resonance process was treated as a basic activation mechanism in the framework. Event-indexing model was regarded as a screening system which selected and encoded activated information in situation models along with situational dimensions. Constructionist theory was considered to have a supervisory role based on coherence and explanation. From a view of the unitary framework, some problems concerning each theory were examined and possible interpretations were given. Finally, it was pointed out that there were little theoretical arguments on associative processing at global level and encoding text- and inference-information into long-term memory.

  6. 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.

  7. 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...

  8. Recent tests of the equilibrium-point hypothesis (lambda model).

    Science.gov (United States)

    Feldman, A G; Ostry, D J; Levin, M F; Gribble, P L; Mitnitski, A B

    1998-07-01

    The lambda model of the equilibrium-point hypothesis (Feldman & Levin, 1995) is an approach to motor control which, like physics, is based on a logical system coordinating empirical data. The model has gone through an interesting period. On one hand, several nontrivial predictions of the model have been successfully verified in recent studies. In addition, the explanatory and predictive capacity of the model has been enhanced by its extension to multimuscle and multijoint systems. On the other hand, claims have recently appeared suggesting that the model should be abandoned. The present paper focuses on these claims and concludes that they are unfounded. Much of the experimental data that have been used to reject the model are actually consistent with it.

  9. 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....

  10. Further developments of the Neyman-Scott clustered point process for modeling rainfall

    Science.gov (United States)

    Cowpertwait, Paul S. P.

    1991-07-01

    This paper provides some useful results for modeling rainfall. It extends work on the Neyman-Scott cluster model for simulating rainfall time series. Several important properties have previously been found for the model, for example, the expectation and variance of the amount of rain captured in an arbitrary time interval (Rodriguez-Iturbe et al., 1987a), In this paper additional properties are derived, such as the probability of an arbitrary interval of any chosen length being dry. In applications this is a desirable property to have, and is often used for fitting stochastic rainfall models to field data. The model is currently being used in rainfall time series research directed toward improving sewage systems in the United Kingdom. To illustrate the model's performance an example is given, where the model is fitted to 10 years of hourly data taken from Blackpool, England.

  11. Application of Bayesian Techniques to Model the Burden of Human Salmonellosis Attributable to U.S. Food Commodities at the Point of Processing: Adaptation of a Danish Model

    DEFF Research Database (Denmark)

    Guo, Chuanfa; Hoekstra, Robert M.; Schroeder, Carl M.

    2011-01-01

    -of-processing foodborne illness attribution model by adapting the Hald Salmonella Bayesian source attribution model. Key model outputs include estimates of the relative proportions of domestically acquired sporadic human Salmonella infections resulting from contamination of raw meat, poultry, and egg products processed...... in the United States from 1998 through 2003. The current model estimates the relative contribution of chicken (48%), ground beef (28%), turkey (17%), egg products (6%), intact beef (1%), and pork (...

  12. Prediction of the Flash Point of Binary and Ternary Straight-Chain Alkane Mixtures

    Directory of Open Access Journals (Sweden)

    X. Li

    2014-01-01

    Full Text Available The flash point is an important physical property used to estimate the fire hazard of a flammable liquid. To avoid the occurrence of fire or explosion, many models are used to predict the flash point; however, these models are complex, and the calculation process is cumbersome. For pure flammable substances, the research for predicting the flash point is systematic and comprehensive. For multicomponent mixtures, especially a hydrocarbon mixture, the current research is insufficient to predict the flash point. In this study, a model was developed to predict the flash point of straight-chain alkane mixtures using a simple calculation process. The pressure, activity coefficient, and other associated physicochemical parameters are not required for the calculation in the proposed model. A series of flash points of binary and ternary mixtures of straight-chain alkanes were determined. The results of the model present consistent experimental results with an average absolute deviation for the binary mixtures of 0.7% or lower and an average absolute deviation for the ternary mixtures of 1.03% or lower.

  13. Thermodynamic and Process Modelling of Gas Hydrate Systems in CO2 Capture Processes

    DEFF Research Database (Denmark)

    Herslund, Peter Jørgensen

    A novel gas separation technique based on gas hydrate formation (solid precipitation) is investigated by means of thermodynamic modeling and experimental investigations. This process has previously been proposed for application in post-combustion carbon dioxide capture from power station flue gases...... formation may be performed at pressures of approximately 20 MPa and temperatures below 280 K. Thermodynamic promoters are needed, to reduce the pressure requirement of the process, thereby making it competitive to existing capture technologies. A literature study is presented focusing mainly...... on thermodynamic gas hydrate promotion by hydrate formers stabilising the classical gas clathrate hydrate structures (sI, sII and sH) at low to moderate pressures. Much literature is available on this subject. Both experimental and theoretical studies presented in the literature have pointed out cyclopentane...

  14. Benchmarking of radiological departments. Starting point for successful process optimization

    International Nuclear Information System (INIS)

    Busch, Hans-Peter

    2010-01-01

    Continuous optimization of the process of organization and medical treatment is part of the successful management of radiological departments. The focus of this optimization can be cost units such as CT and MRI or the radiological parts of total patient treatment. Key performance indicators for process optimization are cost- effectiveness, service quality and quality of medical treatment. The potential for improvements can be seen by comparison (benchmark) with other hospitals and radiological departments. Clear definitions of key data and criteria are absolutely necessary for comparability. There is currently little information in the literature regarding the methodology and application of benchmarks especially from the perspective of radiological departments and case-based lump sums, even though benchmarking has frequently been applied to radiological departments by hospital management. The aim of this article is to describe and discuss systematic benchmarking as an effective starting point for successful process optimization. This includes the description of the methodology, recommendation of key parameters and discussion of the potential for cost-effectiveness analysis. The main focus of this article is cost-effectiveness (efficiency and effectiveness) with respect to cost units and treatment processes. (orig.)

  15. Estimation of landfill emission lifespan using process oriented modeling

    International Nuclear Information System (INIS)

    Ustohalova, Veronika; Ricken, Tim; Widmann, Renatus

    2006-01-01

    Depending on the particular pollutants emitted, landfills may require service activities lasting from hundreds to thousands of years. Flexible tools allowing long-term predictions of emissions are of key importance to determine the nature and expected duration of maintenance and post-closure activities. A highly capable option represents predictions based on models and verified by experiments that are fast, flexible and allow for the comparison of various possible operation scenarios in order to find the most appropriate one. The intention of the presented work was to develop a experimentally verified multi-dimensional predictive model capable of quantifying and estimating processes taking place in landfill sites where coupled process description allows precise time and space resolution. This constitutive 2-dimensional model is based on the macromechanical theory of porous media (TPM) for a saturated thermo-elastic porous body. The model was used to simulate simultaneously occurring processes: organic phase transition, gas emissions, heat transport, and settlement behavior on a long time scale for municipal solid waste deposited in a landfill. The relationships between the properties (composition, pore structure) of a landfill and the conversion and multi-phase transport phenomena inside it were experimentally determined. In this paper, we present both the theoretical background of the model and the results of the simulations at one single point as well as in a vertical landfill cross section

  16. Hardware-accelerated Point Generation and Rendering of Point-based Impostors

    DEFF Research Database (Denmark)

    Bærentzen, Jakob Andreas

    2005-01-01

    This paper presents a novel scheme for generating points from triangle models. The method is fast and lends itself well to implementation using graphics hardware. The triangle to point conversion is done by rendering the models, and the rendering may be performed procedurally or by a black box API....... I describe the technique in detail and discuss how the generated point sets can easily be used as impostors for the original triangle models used to create the points. Since the points reside solely in GPU memory, these impostors are fairly efficient. Source code is available online....

  17. Deep inelastic processes. Phenomenology. Quark-parton model

    International Nuclear Information System (INIS)

    Ioffe, B.L.; Lipatov, L.N.; Khoze, V.A.

    1983-01-01

    Main theoretical approaches and experimental results related to deep inelastic processes are systematically outlined: electroproduction, neutrino scattering on nucleon, electron-positron pairs annihilation into hadron γγ collisions, production of lepton pairs in hadron collisions with a large effective mass or hadrons with large transverse momenta. Kinematics and phenomenology, space-time description of deep inelastic processes, sum rules, parton and quark-parton models are considered. The experiment is briefly discussed in the book. It is performed from the stand point of comparing it with the theory, experimental data are given as of June, 1982. Since the time of accomplishing the study on the manuscript a number of new experimental results not changing however the statements made in the book appeared. Principal consists in experiments with colliding proton-antiproton beams in CERN, which resulted in discovery of intermediate W-bozon

  18. 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...

  19. Simulation of ultrasonic surface waves with multi-Gaussian and point source beam models

    International Nuclear Information System (INIS)

    Zhao, Xinyu; Schmerr, Lester W. Jr.; Li, Xiongbing; Sedov, Alexander

    2014-01-01

    In the past decade, multi-Gaussian beam models have been developed to solve many complicated bulk wave propagation problems. However, to date those models have not been extended to simulate the generation of Rayleigh waves. Here we will combine Gaussian beams with an explicit high frequency expression for the Rayleigh wave Green function to produce a three-dimensional multi-Gaussian beam model for the fields radiated from an angle beam transducer mounted on a solid wedge. Simulation results obtained with this model are compared to those of a point source model. It is shown that the multi-Gaussian surface wave beam model agrees well with the point source model while being computationally much more efficient

  20. 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.

  1. 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.

  2. Penultimate modeling of spatial extremes: statistical inference for max-infinitely divisible processes

    KAUST Repository

    Huser, Raphaël

    2018-01-09

    Extreme-value theory for stochastic processes has motivated the statistical use of max-stable models for spatial extremes. However, fitting such asymptotic models to maxima observed over finite blocks is problematic when the asymptotic stability of the dependence does not prevail in finite samples. This issue is particularly serious when data are asymptotically independent, such that the dependence strength weakens and eventually vanishes as events become more extreme. We here aim to provide flexible sub-asymptotic models for spatially indexed block maxima, which more realistically account for discrepancies between data and asymptotic theory. We develop models pertaining to the wider class of max-infinitely divisible processes, extending the class of max-stable processes while retaining dependence properties that are natural for maxima: max-id models are positively associated, and they yield a self-consistent family of models for block maxima defined over any time unit. We propose two parametric construction principles for max-id models, emphasizing a point process-based generalized spectral representation, that allows for asymptotic independence while keeping the max-stable extremal-$t$ model as a special case. Parameter estimation is efficiently performed by pairwise likelihood, and we illustrate our new modeling framework with an application to Dutch wind gust maxima calculated over different time units.

  3. Femtosecond photoelectron point projection microscope

    International Nuclear Information System (INIS)

    Quinonez, Erik; Handali, Jonathan; Barwick, Brett

    2013-01-01

    By utilizing a nanometer ultrafast electron source in a point projection microscope we demonstrate that images of nanoparticles with spatial resolutions of the order of 100 nanometers can be obtained. The duration of the emission process of the photoemitted electrons used to make images is shown to be of the order of 100 fs using an autocorrelation technique. The compact geometry of this photoelectron point projection microscope does not preclude its use as a simple ultrafast electron microscope, and we use simple analytic models to estimate temporal resolutions that can be expected when using it as a pump-probe ultrafast electron microscope. These models show a significant increase in temporal resolution when comparing to ultrafast electron microscopes based on conventional designs. We also model the microscopes spectroscopic abilities to capture ultrafast phenomena such as the photon induced near field effect

  4. Changing the values of parameters on lot size reorder point model

    Directory of Open Access Journals (Sweden)

    Chang Hung-Chi

    2003-01-01

    Full Text Available The Just-In-Time (JIT philosophy has received a great deal of attention. Several actions such as improving quality, reducing setup cost and shortening lead time have been recognized as effective ways to achieve the underlying goal of JIT. This paper considers the partial backorders, lot size reorder point inventory system with an imperfect production process. The objective is to simultaneously optimize the lot size, reorder point, process quality, setup cost and lead time, constrained on a service level. We assume the explicit distributional form of lead time demand is unknown but the mean and standard deviation are given. The minimax distribution free approach is utilized to solve the problem and a numerical example is provided to illustrate the results. .

  5. Empiric model for mean generation time adjustment factor for classic point kinetics equations

    Energy Technology Data Exchange (ETDEWEB)

    Goes, David A.B.V. de; Martinez, Aquilino S.; Goncalves, Alessandro da C., E-mail: david.goes@poli.ufrj.br, E-mail: aquilino@lmp.ufrj.br, E-mail: alessandro@con.ufrj.br [Coordenacao de Pos-Graduacao e Pesquisa de Engenharia (COPPE/UFRJ), Rio de Janeiro, RJ (Brazil). Departamento de Engenharia Nuclear

    2017-11-01

    Point reactor kinetics equations are the easiest way to observe the neutron production time behavior in a nuclear reactor. These equations are derived from the neutron transport equation using an approximation called Fick's law leading to a set of first order differential equations. The main objective of this study is to review classic point kinetics equation in order to approximate its results to the case when it is considered the time variation of the neutron currents. The computational modeling used for the calculations is based on the finite difference method. The results obtained with this model are compared with the reference model and then it is determined an empirical adjustment factor that modifies the point reactor kinetics equation to the real scenario. (author)

  6. Empiric model for mean generation time adjustment factor for classic point kinetics equations

    International Nuclear Information System (INIS)

    Goes, David A.B.V. de; Martinez, Aquilino S.; Goncalves, Alessandro da C.

    2017-01-01

    Point reactor kinetics equations are the easiest way to observe the neutron production time behavior in a nuclear reactor. These equations are derived from the neutron transport equation using an approximation called Fick's law leading to a set of first order differential equations. The main objective of this study is to review classic point kinetics equation in order to approximate its results to the case when it is considered the time variation of the neutron currents. The computational modeling used for the calculations is based on the finite difference method. The results obtained with this model are compared with the reference model and then it is determined an empirical adjustment factor that modifies the point reactor kinetics equation to the real scenario. (author)

  7. Modelling the behaviour of 210Po in high temperature processes

    International Nuclear Information System (INIS)

    Mora, J.C.; Robles, B.; Corbacho, J.A.; Gasco, Catalina; Gazquez, M.J.

    2011-01-01

    In several Naturally Occurring Radioactive Material (NORM) industries, relatively high temperatures are used as part of their industrial processes. In coal combustion, as occur in other high temperature processes, an increase of the activity concentration of every natural radioisotope is produced both, in residues and by-products. An additional increase can be observed in the activity concentration of radionuclides of elements with low boiling point. This work is centred in the increase of polonium, more precisely in its radioisotope Po-210, present in the natural chains, and with a half-life long enough to be considered for radiation protection purposes. This additional increase appears mainly in the residual particles that are suspended in the flue gases: the fly-ashes. Besides, scales, with a high concentration of this radioisotope, were observed. These scales are produced on surfaces with a temperature lower than the boiling point of the chemical element. Both, the accumulation in particles and the production of scales are attributed to condensation effects. When effective doses for the public and the workers are evaluated, taking into account these increases in activity concentrations, the use of theoretical models is necessary. In this work a theoretical description of those effects is presented. Moreover, a verification of the predictions of the model was performed by comparing them with measurements carried on in coal-fired power plants. The same description here presented is applicable in general to the behaviour of Po-210 in other NORM industries where high temperature processes involving raw materials are used, as can be ceramic, cement production, tiles production or steel processing.

  8. Near-infrared spectroscopic monitoring of a series of industrial batch processes using a bilinear grey model.

    Science.gov (United States)

    van Sprang, Eric N M; Ramaker, Henk-Jan; Westerhuis, Johan A; Smilde, Age K; Gurden, Stephen P; Wienke, Dietrich

    2003-08-01

    A good process understanding is the foundation for process optimization, process monitoring, end-point detection, and estimation of the end-product quality. Performing good process measurements and the construction of process models will contribute to a better process understanding. To improve the process knowledge it is common to build process models. These models are often based on first principles such as kinetic rates or mass balances. These types of models are also known as hard or white models. White models are characterized by being generally applicable but often having only a reasonable fit to real process data. Other commonly used types of models are empirical or black-box models such as regression and neural nets. Black-box models are characterized by having a good data fit but they lack a chemically meaningful model interpretation. Alternative models are grey models, which are combinations of white models and black models. The aim of a grey model is to combine the advantages of both black-box models and white models. In a qualitative case study of monitoring industrial batches using near-infrared (NIR) spectroscopy, it is shown that grey models are a good tool for detecting batch-to-batch variations and an excellent tool for process diagnosis compared to common spectroscopic monitoring tools.

  9. Modeling Dynamic Regulatory Processes in Stroke

    Science.gov (United States)

    McDermott, Jason E.; Jarman, Kenneth; Taylor, Ronald; Lancaster, Mary; Shankaran, Harish; Vartanian, Keri B.; Stevens, Susan L.; Stenzel-Poore, Mary P.; Sanfilippo, Antonio

    2012-01-01

    The ability to examine the behavior of biological systems in silico has the potential to greatly accelerate the pace of discovery in diseases, such as stroke, where in vivo analysis is time intensive and costly. In this paper we describe an approach for in silico examination of responses of the blood transcriptome to neuroprotective agents and subsequent stroke through the development of dynamic models of the regulatory processes observed in the experimental gene expression data. First, we identified functional gene clusters from these data. Next, we derived ordinary differential equations (ODEs) from the data relating these functional clusters to each other in terms of their regulatory influence on one another. Dynamic models were developed by coupling these ODEs into a model that simulates the expression of regulated functional clusters. By changing the magnitude of gene expression in the initial input state it was possible to assess the behavior of the networks through time under varying conditions since the dynamic model only requires an initial starting state, and does not require measurement of regulatory influences at each time point in order to make accurate predictions. We discuss the implications of our models on neuroprotection in stroke, explore the limitations of the approach, and report that an optimized dynamic model can provide accurate predictions of overall system behavior under several different neuroprotective paradigms. PMID:23071432

  10. Two point function for a simple general relativistic quantum model

    OpenAIRE

    Colosi, Daniele

    2007-01-01

    We study the quantum theory of a simple general relativistic quantum model of two coupled harmonic oscillators and compute the two-point function following a proposal first introduced in the context of loop quantum gravity.

  11. 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

  12. Some application of the model of partition points on a one-dimensional lattice

    International Nuclear Information System (INIS)

    Mejdani, R.

    1991-07-01

    We have shown that by using a model of the gas of partition points on one-dimensional lattice, we can find some results about the enzyme kinetics or the average domain-size, which we have obtained before by using a correlated Walks' theory or a probabilistic (combinatoric) way. We have discussed also the problem related with the spread of an infection of disease and the stochastic model of partition points. We think that this model, as a very simple model and mathematically transparent, can be advantageous for other theoretical investigations in chemistry or modern biology. (author). 14 refs, 6 figs, 1 tab

  13. MATHEMATICAL MODELING, AUTOMATION AND CONTROL OF THE BIOCONVERSION OF SORBITOL TO SORBOSE IN THE VITAMIN C PRODUCTION PROCESS I. MATHEMATICAL MODELING

    Directory of Open Access Journals (Sweden)

    A. Bonomi

    1997-12-01

    Full Text Available In 1990, the Biotechnology and the Control Systems Groups of IPT started developing a system for the control and automation of fermentation processes, applied to the oxidation of sorbitol to sorbose by the bacteria Gluconobacter oxydans, the microbial step of the vitamin C production process, that was chosen as a case study. Initially, a thirteen-parameter model was fitted to represent the batch operation of the system utilizing a nonlinear regression analysis, the flexible polyhedron method. Based on these results, a model for the continuous process (with the same kinetic equations was constructed and its optimum operating point obtained

  14. An aggregate method to calibrate the reference point of cumulative prospect theory-based route choice model for urban transit network

    Science.gov (United States)

    Zhang, Yufeng; Long, Man; Luo, Sida; Bao, Yu; Shen, Hanxia

    2015-12-01

    Transit route choice model is the key technology of public transit systems planning and management. Traditional route choice models are mostly based on expected utility theory which has an evident shortcoming that it cannot accurately portray travelers' subjective route choice behavior for their risk preferences are not taken into consideration. Cumulative prospect theory (CPT), a brand new theory, can be used to describe travelers' decision-making process under the condition of uncertainty of transit supply and risk preferences of multi-type travelers. The method to calibrate the reference point, a key parameter to CPT-based transit route choice model, determines the precision of the model to a great extent. In this paper, a new method is put forward to obtain the value of reference point which combines theoretical calculation and field investigation results. Comparing the proposed method with traditional method, it shows that the new method can promote the quality of CPT-based model by improving the accuracy in simulating travelers' route choice behaviors based on transit trip investigation from Nanjing City, China. The proposed method is of great significance to logical transit planning and management, and to some extent makes up the defect that obtaining the reference point is solely based on qualitative analysis.

  15. Modeling treatment of ischemic heart disease with partially observable Markov decision processes.

    Science.gov (United States)

    Hauskrecht, M; Fraser, H

    1998-01-01

    Diagnosis of a disease and its treatment are not separate, one-shot activities. Instead they are very often dependent and interleaved over time, mostly due to uncertainty about the underlying disease, uncertainty associated with the response of a patient to the treatment and varying cost of different diagnostic (investigative) and treatment procedures. The framework of Partially observable Markov decision processes (POMDPs) developed and used in operations research, control theory and artificial intelligence communities is particularly suitable for modeling such a complex decision process. In the paper, we show how the POMDP framework could be used to model and solve the problem of the management of patients with ischemic heart disease, and point out modeling advantages of the framework over standard decision formalisms.

  16. FIRST PRISMATIC BUILDING MODEL RECONSTRUCTION FROM TOMOSAR POINT CLOUDS

    Directory of Open Access Journals (Sweden)

    Y. Sun

    2016-06-01

    Full Text Available This paper demonstrates for the first time the potential of explicitly modelling the individual roof surfaces to reconstruct 3-D prismatic building models using spaceborne tomographic synthetic aperture radar (TomoSAR point clouds. The proposed approach is modular and works as follows: it first extracts the buildings via DSM generation and cutting-off the ground terrain. The DSM is smoothed using BM3D denoising method proposed in (Dabov et al., 2007 and a gradient map of the smoothed DSM is generated based on height jumps. Watershed segmentation is then adopted to oversegment the DSM into different regions. Subsequently, height and polygon complexity constrained merging is employed to refine (i.e., to reduce the retrieved number of roof segments. Coarse outline of each roof segment is then reconstructed and later refined using quadtree based regularization plus zig-zag line simplification scheme. Finally, height is associated to each refined roof segment to obtain the 3-D prismatic model of the building. The proposed approach is illustrated and validated over a large building (convention center in the city of Las Vegas using TomoSAR point clouds generated from a stack of 25 images using Tomo-GENESIS software developed at DLR.

  17. A MODELING METHOD OF FLUTTERING LEAVES BASED ON POINT CLOUD

    OpenAIRE

    J. Tang; Y. Wang; Y. Zhao; Y. Zhao; W. Hao; X. Ning; K. Lv; Z. Shi; M. Zhao

    2017-01-01

    Leaves falling gently or fluttering are common phenomenon in nature scenes. The authenticity of leaves falling plays an important part in the dynamic modeling of natural scenes. The leaves falling model has a widely applications in the field of animation and virtual reality. We propose a novel modeling method of fluttering leaves based on point cloud in this paper. According to the shape, the weight of leaves and the wind speed, three basic trajectories of leaves falling are defined, which ar...

  18. EBT time-dependent point model code: description and user's guide

    International Nuclear Information System (INIS)

    Roberts, J.F.; Uckan, N.A.

    1977-07-01

    A D-T time-dependent point model has been developed to assess the energy balance in an EBT reactor plasma. Flexibility is retained in the model to permit more recent data to be incorporated as they become available from the theoretical and experimental studies. This report includes the physics models involved, the program logic, and a description of the variables and routines used. All the files necessary for execution are listed, and the code, including a post-execution plotting routine, is discussed

  19. Accurate prediction of the dew points of acidic combustion gases by using an artificial neural network model

    International Nuclear Information System (INIS)

    ZareNezhad, Bahman; Aminian, Ali

    2011-01-01

    This paper presents a new approach based on using an artificial neural network (ANN) model for predicting the acid dew points of the combustion gases in process and power plants. The most important acidic combustion gases namely, SO 3 , SO 2 , NO 2 , HCl and HBr are considered in this investigation. Proposed Network is trained using the Levenberg-Marquardt back propagation algorithm and the hyperbolic tangent sigmoid activation function is applied to calculate the output values of the neurons of the hidden layer. According to the network's training, validation and testing results, a three layer neural network with nine neurons in the hidden layer is selected as the best architecture for accurate prediction of the acidic combustion gases dew points over wide ranges of acid and moisture concentrations. The proposed neural network model can have significant application in predicting the condensation temperatures of different acid gases to mitigate the corrosion problems in stacks, pollution control devices and energy recovery systems.

  20. Grey-Markov prediction model based on background value optimization and central-point triangular whitenization weight function

    Science.gov (United States)

    Ye, Jing; Dang, Yaoguo; Li, Bingjun

    2018-01-01

    Grey-Markov forecasting model is a combination of grey prediction model and Markov chain which show obvious optimization effects for data sequences with characteristics of non-stationary and volatility. However, the state division process in traditional Grey-Markov forecasting model is mostly based on subjective real numbers that immediately affects the accuracy of forecasting values. To seek the solution, this paper introduces the central-point triangular whitenization weight function in state division to calculate possibilities of research values in each state which reflect preference degrees in different states in an objective way. On the other hand, background value optimization is applied in the traditional grey model to generate better fitting data. By this means, the improved Grey-Markov forecasting model is built. Finally, taking the grain production in Henan Province as an example, it verifies this model's validity by comparing with GM(1,1) based on background value optimization and the traditional Grey-Markov forecasting model.

  1. A Multi-scale Modeling System with Unified Physics to Study Precipitation Processes

    Science.gov (United States)

    Tao, W. K.

    2017-12-01

    In recent years, exponentially increasing computer power has extended Cloud Resolving Model (CRM) integrations from hours to months, the number of computational grid points from less than a thousand to close to ten million. Three-dimensional models are now more prevalent. Much attention is devoted to precipitating cloud systems where the crucial 1-km scales are resolved in horizontal domains as large as 10,000 km in two-dimensions, and 1,000 x 1,000 km2 in three-dimensions. Cloud resolving models now provide statistical information useful for developing more realistic physically based parameterizations for climate models and numerical weather prediction models. It is also expected that NWP and mesoscale model can be run in grid size similar to cloud resolving model through nesting technique. Recently, a multi-scale modeling system with unified physics was developed at NASA Goddard. It consists of (1) a cloud-resolving model (Goddard Cumulus Ensemble model, GCE model), (2) a regional scale model (a NASA unified weather research and forecast, WRF), and (3) a coupled CRM and global model (Goddard Multi-scale Modeling Framework, MMF). The same microphysical processes, long and short wave radiative transfer and land processes and the explicit cloud-radiation, and cloud-land surface interactive processes are applied in this multi-scale modeling system. This modeling system has been coupled with a multi-satellite simulator to use NASA high-resolution satellite data to identify the strengths and weaknesses of cloud and precipitation processes simulated by the model. In this talk, a review of developments and applications of the multi-scale modeling system will be presented. In particular, the results from using multi-scale modeling system to study the precipitation, processes and their sensitivity on model resolution and microphysics schemes will be presented. Also how to use of the multi-satellite simulator to improve precipitation processes will be discussed.

  2. Tricritical point in quantum phase transitions of the Coleman–Weinberg model at Higgs mass

    International Nuclear Information System (INIS)

    Fiolhais, Miguel C.N.; Kleinert, Hagen

    2013-01-01

    The tricritical point, which separates first and second order phase transitions in three-dimensional superconductors, is studied in the four-dimensional Coleman–Weinberg model, and the similarities as well as the differences with respect to the three-dimensional result are exhibited. The position of the tricritical point in the Coleman–Weinberg model is derived and found to be in agreement with the Thomas–Fermi approximation in the three-dimensional Ginzburg–Landau theory. From this we deduce a special role of the tricritical point for the Standard Model Higgs sector in the scope of the latest experimental results, which suggests the unexpected relevance of tricritical behavior in the electroweak interactions.

  3. 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.

  4. A Correlated Random Effects Model for Non-homogeneous Markov Processes with Nonignorable Missingness.

    Science.gov (United States)

    Chen, Baojiang; Zhou, Xiao-Hua

    2013-05-01

    Life history data arising in clusters with prespecified assessment time points for patients often feature incomplete data since patients may choose to visit the clinic based on their needs. Markov process models provide a useful tool describing disease progression for life history data. The literature mainly focuses on time homogeneous process. In this paper we develop methods to deal with non-homogeneous Markov process with incomplete clustered life history data. A correlated random effects model is developed to deal with the nonignorable missingness, and a time transformation is employed to address the non-homogeneity in the transition model. Maximum likelihood estimate based on the Monte-Carlo EM algorithm is advocated for parameter estimation. Simulation studies demonstrate that the proposed method works well in many situations. We also apply this method to an Alzheimer's disease study.

  5. Accuracy Constraint Determination in Fixed-Point System Design

    Directory of Open Access Journals (Sweden)

    Serizel R

    2008-01-01

    Full Text Available Most of digital signal processing applications are specified and designed with floatingpoint arithmetic but are finally implemented using fixed-point architectures. Thus, the design flow requires a floating-point to fixed-point conversion stage which optimizes the implementation cost under execution time and accuracy constraints. This accuracy constraint is linked to the application performances and the determination of this constraint is one of the key issues of the conversion process. In this paper, a method is proposed to determine the accuracy constraint from the application performance. The fixed-point system is modeled with an infinite precision version of the system and a single noise source located at the system output. Then, an iterative approach for optimizing the fixed-point specification under the application performance constraint is defined and detailed. Finally the efficiency of our approach is demonstrated by experiments on an MP3 encoder.

  6. The Process-Oriented Simulation (POS) model for common cause failures: recent progress

    International Nuclear Information System (INIS)

    Berg, H.P.; Goertz, R.; Schimetschka, E.; Kesten, J.

    2006-01-01

    A common-cause failure (CCF) model based on stochastic simulation has been developed to complement the established approaches and to overcome some of their shortcomings. Reflecting the models proximity to the CCF process it was called Process Oriented Simulation (POS) Model. In recent years, some progress has been made to render the POS model fit for practical applications comprising the development of parameter estimates and a number of test applications in areas where results were already available - especially from CCF benchmarks - and comparison can provide insights in strong and weak points of the different approaches. In this paper, a detailed description of the POS model is provided together with the approach to parameter estimation and representative test applications. It is concluded, that the POS model has a number of strengths - especially the feature to provide reasonable extrapolation to CCF groups with high degrees of redundancy - and thus a considerable potential to complement the insights obtained from existing modeling. (orig.)

  7. Application of SADT and ARIS methodologies for modeling and management of business processes of information systems

    Directory of Open Access Journals (Sweden)

    O. V. Fedorova

    2018-01-01

    Full Text Available The article is devoted to application of SADT and ARIS methodologies for modeling and management of business processes of information systems. The relevance of this article is beyond doubt, because the design of the architecture of information systems, based on a thorough system analysis of the subject area, is of paramount importance for the development of information systems in general. The authors conducted a serious work on the analysis of the application of SADT and ARIS methodologies for modeling and managing business processes of information systems. The analysis was carried out both in terms of modeling business processes (notation and applying the CASE-tool, and in terms of business process management. The first point of view reflects the interaction of the business analyst and the programmer in the development of the information system. The second point of view is the interaction of the business analyst and the customer. The basis of many modern methodologies for modeling business processes is the SADT methodology. Using the methodology of the IDEF family, it is possible to efficiently display and analyze the activity models of a wide range of complex information systems in various aspects. CASE-tool ARIS is a complex of tools for analysis and modeling of the organization's activities. The methodical basis of ARIS is a set of different modeling methods that reflect different views on the system under study. The authors' conclusions are fully justified. The results of the work can be useful for specialists in the field of modeling business processes of information systems. In addition, the article has an oriented character when working on the constituent elements of curricula for students specializing in information specialties and management, provides an update of the content and structure of disciplines on modeling the architecture of information systems and organization management, using models.

  8. A Point Kinetics Model for Estimating Neutron Multiplication of Bare Uranium Metal in Tagged Neutron Measurements

    Science.gov (United States)

    Tweardy, Matthew C.; McConchie, Seth; Hayward, Jason P.

    2017-07-01

    An extension of the point kinetics model is developed to describe the neutron multiplicity response of a bare uranium object under interrogation by an associated particle imaging deuterium-tritium (D-T) measurement system. This extended model is used to estimate the total neutron multiplication of the uranium. Both MCNPX-PoliMi simulations and data from active interrogation measurements of highly enriched and depleted uranium geometries are used to evaluate the potential of this method and to identify the sources of systematic error. The detection efficiency correction for measured coincidence response is identified as a large source of systematic error. If the detection process is not considered, results suggest that the method can estimate total multiplication to within 13% of the simulated value. Values for multiplicity constants in the point kinetics equations are sensitive to enrichment due to (n, xn) interactions by D-T neutrons and can introduce another significant source of systematic bias. This can theoretically be corrected if isotopic composition is known a priori. The spatial dependence of multiplication is also suspected of introducing further systematic bias for high multiplication uranium objects.

  9. Switching and optimizing control for coal flotation process based on a hybrid model

    Science.gov (United States)

    Dong, Zhiyong; Wang, Ranfeng; Fan, Minqiang; Fu, Xiang

    2017-01-01

    Flotation is an important part of coal preparation, and the flotation column is widely applied as efficient flotation equipment. This process is complex and affected by many factors, with the froth depth and reagent dosage being two of the most important and frequently manipulated variables. This paper proposes a new method of switching and optimizing control for the coal flotation process. A hybrid model is built and evaluated using industrial data. First, wavelet analysis and principal component analysis (PCA) are applied for signal pre-processing. Second, a control model for optimizing the set point of the froth depth is constructed based on fuzzy control, and a control model is designed to optimize the reagent dosages based on expert system. Finally, the least squares-support vector machine (LS-SVM) is used to identify the operating conditions of the flotation process and to select one of the two models (froth depth or reagent dosage) for subsequent operation according to the condition parameters. The hybrid model is developed and evaluated on an industrial coal flotation column and exhibits satisfactory performance. PMID:29040305

  10. Two-point model for electron transport in EBT

    International Nuclear Information System (INIS)

    Chiu, S.C.; Guest, G.E.

    1980-01-01

    The electron transport in EBT is simulated by a two-point model corresponding to the central plasma and the edge. The central plasma is assumed to obey neoclassical collisionless transport. The edge plasma is assumed turbulent and modeled by Bohm diffusion. The steady-state temperatures and densities in both regions are obtained as functions of neutral influx and microwave power. It is found that as the neutral influx decreases and power increases, the edge density decreases while the core density increases. We conclude that if ring instability is responsible for the T-M mode transition, and if stability is correlated with cold electron density at the edge, it will depend sensitively on ambient gas pressure and microwave power

  11. Improving the Pattern Reproducibility of Multiple-Point-Based Prior Models Using Frequency Matching

    DEFF Research Database (Denmark)

    Cordua, Knud Skou; Hansen, Thomas Mejer; Mosegaard, Klaus

    2014-01-01

    Some multiple-point-based sampling algorithms, such as the snesim algorithm, rely on sequential simulation. The conditional probability distributions that are used for the simulation are based on statistics of multiple-point data events obtained from a training image. During the simulation, data...... events with zero probability in the training image statistics may occur. This is handled by pruning the set of conditioning data until an event with non-zero probability is found. The resulting probability distribution sampled by such algorithms is a pruned mixture model. The pruning strategy leads...... to a probability distribution that lacks some of the information provided by the multiple-point statistics from the training image, which reduces the reproducibility of the training image patterns in the outcome realizations. When pruned mixture models are used as prior models for inverse problems, local re...

  12. A Traffic Model for Machine-Type Communications Using Spatial Point Processes

    DEFF Research Database (Denmark)

    Thomsen, Henning; Manchón, Carles Navarro; Fleury, Bernard Henri

    2018-01-01

    , where the generated traffic by a given device depends on its position and event positions. We first consider the case where devices and events are static and devices generate traffic according to a Bernoulli process, where we derive the total rate from the devices at the base station. We then extend...

  13. Understanding Coupled Earth-Surface Processes through Experiments and Models (Invited)

    Science.gov (United States)

    Overeem, I.; Kim, W.

    2013-12-01

    Traditionally, both numerical models and experiments have been purposefully designed to ';isolate' singular components or certain processes of a larger mountain to deep-ocean interconnected source-to-sink (S2S) transport system. Controlling factors driven by processes outside of the domain of immediate interest were treated and simplified as input or as boundary conditions. Increasingly, earth surface processes scientists appreciate feedbacks and explore these feedbacks with more dynamically coupled approaches to their experiments and models. Here, we discuss key concepts and recent advances made in coupled modeling and experimental setups. In addition, we emphasize challenges and new frontiers to coupled experiments. Experiments have highlighted the important role of self-organization; river and delta systems do not always need to be forced by external processes to change or develop characteristic morphologies. Similarly modeling f.e. has shown that intricate networks in tidal deltas are stable because of the interplay between river avulsions and the tidal current scouring with both processes being important to develop and maintain the dentritic networks. Both models and experiment have demonstrated that seemingly stable systems can be perturbed slightly and show dramatic responses. Source-to-sink models were developed for both the Fly River System in Papua New Guinea and the Waipaoa River in New Zealand. These models pointed to the importance of upstream-downstream effects and enforced our view of the S2S system as a signal transfer and dampening conveyor belt. Coupled modeling showed that deforestation had extreme effects on sediment fluxes draining from the catchment of the Waipaoa River in New Zealand, and that this increase in sediment production rapidly shifted the locus of offshore deposition. The challenge in designing coupled models and experiments is both technological as well as intellectual. Our community advances to make numerical model coupling more

  14. Improved DEA Cross Efficiency Evaluation Method Based on Ideal and Anti-Ideal Points

    Directory of Open Access Journals (Sweden)

    Qiang Hou

    2018-01-01

    Full Text Available A new model is introduced in the process of evaluating efficiency value of decision making units (DMUs through data envelopment analysis (DEA method. Two virtual DMUs called ideal point DMU and anti-ideal point DMU are combined to form a comprehensive model based on the DEA method. The ideal point DMU is taking self-assessment system according to efficiency concept. The anti-ideal point DMU is taking other-assessment system according to fairness concept. The two distinctive ideal point models are introduced to the DEA method and combined through using variance ration. From the new model, a reasonable result can be obtained. Numerical examples are provided to illustrate the new constructed model and certify the rationality of the constructed model through relevant analysis with the traditional DEA model.

  15. Reconstruction of measurable three-dimensional point cloud model based on large-scene archaeological excavation sites

    Science.gov (United States)

    Zhang, Chun-Sen; Zhang, Meng-Meng; Zhang, Wei-Xing

    2017-01-01

    This paper outlines a low-cost, user-friendly photogrammetric technique with nonmetric cameras to obtain excavation site digital sequence images, based on photogrammetry and computer vision. Digital camera calibration, automatic aerial triangulation, image feature extraction, image sequence matching, and dense digital differential rectification are used, combined with a certain number of global control points of the excavation site, to reconstruct the high precision of measured three-dimensional (3-D) models. Using the acrobatic figurines in the Qin Shi Huang mausoleum excavation as an example, our method solves the problems of little base-to-height ratio, high inclination, unstable altitudes, and significant ground elevation changes affecting image matching. Compared to 3-D laser scanning, the 3-D color point cloud obtained by this method can maintain the same visual result and has advantages of low project cost, simple data processing, and high accuracy. Structure-from-motion (SfM) is often used to reconstruct 3-D models of large scenes and has lower accuracy if it is a reconstructed 3-D model of a small scene at close range. Results indicate that this method quickly achieves 3-D reconstruction of large archaeological sites and produces heritage site distribution of orthophotos providing a scientific basis for accurate location of cultural relics, archaeological excavations, investigation, and site protection planning. This proposed method has a comprehensive application value.

  16. Application of catastrophe theory to a point model for bumpy torus with neoclassical non-resonant electrons

    Energy Technology Data Exchange (ETDEWEB)

    Punjabi, A; Vahala, G [College of William and Mary, Williamsburg, VA (USA). Dept. of Physics

    1983-12-01

    The point model for the toroidal core plasma in the ELMO Bumpy Torus (with neoclassical non-resonant electrons) is examined in the light of catastrophe theory. Even though the point model equations do not constitute a gradient dynamic system, the equilibrium surfaces are similar to those of the canonical cusp catastrophe. The point model is then extended to incorporate ion cyclotron resonance heating. A detailed parametric study of the equilibria is presented. Further, the nonlinear time evolution of these equilibria is studied, and it is observed that the point model obeys the delay convention (and hence hysteresis) and shows catastrophes at the fold edges of the equilibrium surfaces. Tentative applications are made to experimental results.

  17. Factors influencing superimposition error of 3D cephalometric landmarks by plane orientation method using 4 reference points: 4 point superimposition error regression model.

    Science.gov (United States)

    Hwang, Jae Joon; Kim, Kee-Deog; Park, Hyok; Park, Chang Seo; Jeong, Ho-Gul

    2014-01-01

    Superimposition has been used as a method to evaluate the changes of orthodontic or orthopedic treatment in the dental field. With the introduction of cone beam CT (CBCT), evaluating 3 dimensional changes after treatment became possible by superimposition. 4 point plane orientation is one of the simplest ways to achieve superimposition of 3 dimensional images. To find factors influencing superimposition error of cephalometric landmarks by 4 point plane orientation method and to evaluate the reproducibility of cephalometric landmarks for analyzing superimposition error, 20 patients were analyzed who had normal skeletal and occlusal relationship and took CBCT for diagnosis of temporomandibular disorder. The nasion, sella turcica, basion and midpoint between the left and the right most posterior point of the lesser wing of sphenoidal bone were used to define a three-dimensional (3D) anatomical reference co-ordinate system. Another 15 reference cephalometric points were also determined three times in the same image. Reorientation error of each landmark could be explained substantially (23%) by linear regression model, which consists of 3 factors describing position of each landmark towards reference axes and locating error. 4 point plane orientation system may produce an amount of reorientation error that may vary according to the perpendicular distance between the landmark and the x-axis; the reorientation error also increases as the locating error and shift of reference axes viewed from each landmark increases. Therefore, in order to reduce the reorientation error, accuracy of all landmarks including the reference points is important. Construction of the regression model using reference points of greater precision is required for the clinical application of this model.

  18. Single-point incremental forming and formability-failure diagrams

    DEFF Research Database (Denmark)

    Silva, M.B.; Skjødt, Martin; Atkins, A.G.

    2008-01-01

    In a recent work [1], the authors constructed a closed-form analytical model that is capable of dealing with the fundamentals of single point incremental forming and explaining the experimental and numerical results published in the literature over the past couple of years. The model is based...... of deformation that are commonly found in general single point incremental forming processes; and (ii) to investigate the formability limits of SPIF in terms of ductile damage mechanics and the question of whether necking does, or does not, precede fracture. Experimentation by the authors together with data...

  19. Boiling points of halogenated ethanes: an explanatory model implicating weak intermolecular hydrogen-halogen bonding.

    Science.gov (United States)

    Beauchamp, Guy

    2008-10-23

    This study explores via structural clues the influence of weak intermolecular hydrogen-halogen bonds on the boiling point of halogenated ethanes. The plot of boiling points of 86 halogenated ethanes versus the molar refraction (linked to polarizability) reveals a series of straight lines, each corresponding to one of nine possible arrangements of hydrogen and halogen atoms on the two-carbon skeleton. A multiple linear regression model of the boiling points could be designed based on molar refraction and subgroup structure as independent variables (R(2) = 0.995, standard error of boiling point 4.2 degrees C). The model is discussed in view of the fact that molar refraction can account for approximately 83.0% of the observed variation in boiling point, while 16.5% could be ascribed to weak C-X...H-C intermolecular interactions. The difference in the observed boiling point of molecules having similar molar refraction values but differing in hydrogen-halogen intermolecular bonds can reach as much as 90 degrees C.

  20. Markov Random Field Restoration of Point Correspondences for Active Shape Modelling

    DEFF Research Database (Denmark)

    Hilger, Klaus Baggesen; Paulsen, Rasmus Reinhold; Larsen, Rasmus

    2004-01-01

    In this paper it is described how to build a statistical shape model using a training set with a sparse of landmarks. A well defined model mesh is selected and fitted to all shapes in the training set using thin plate spline warping. This is followed by a projection of the points of the warped...

  1. 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...

  2. Two-point functions in a holographic Kondo model

    Science.gov (United States)

    Erdmenger, Johanna; Hoyos, Carlos; O'Bannon, Andy; Papadimitriou, Ioannis; Probst, Jonas; Wu, Jackson M. S.

    2017-03-01

    We develop the formalism of holographic renormalization to compute two-point functions in a holographic Kondo model. The model describes a (0 + 1)-dimensional impurity spin of a gauged SU( N ) interacting with a (1 + 1)-dimensional, large- N , strongly-coupled Conformal Field Theory (CFT). We describe the impurity using Abrikosov pseudo-fermions, and define an SU( N )-invariant scalar operator O built from a pseudo-fermion and a CFT fermion. At large N the Kondo interaction is of the form O^{\\dagger}O, which is marginally relevant, and generates a Renormalization Group (RG) flow at the impurity. A second-order mean-field phase transition occurs in which O condenses below a critical temperature, leading to the Kondo effect, including screening of the impurity. Via holography, the phase transition is dual to holographic superconductivity in (1 + 1)-dimensional Anti-de Sitter space. At all temperatures, spectral functions of O exhibit a Fano resonance, characteristic of a continuum of states interacting with an isolated resonance. In contrast to Fano resonances observed for example in quantum dots, our continuum and resonance arise from a (0 + 1)-dimensional UV fixed point and RG flow, respectively. In the low-temperature phase, the resonance comes from a pole in the Green's function of the form - i2, which is characteristic of a Kondo resonance.

  3. Two-point functions in a holographic Kondo model

    Energy Technology Data Exchange (ETDEWEB)

    Erdmenger, Johanna [Institut für Theoretische Physik und Astrophysik, Julius-Maximilians-Universität Würzburg,Am Hubland, D-97074 Würzburg (Germany); Max-Planck-Institut für Physik (Werner-Heisenberg-Institut),Föhringer Ring 6, D-80805 Munich (Germany); Hoyos, Carlos [Department of Physics, Universidad de Oviedo, Avda. Calvo Sotelo 18, 33007, Oviedo (Spain); O’Bannon, Andy [STAG Research Centre, Physics and Astronomy, University of Southampton,Highfield, Southampton SO17 1BJ (United Kingdom); Papadimitriou, Ioannis [SISSA and INFN - Sezione di Trieste, Via Bonomea 265, I 34136 Trieste (Italy); Probst, Jonas [Rudolf Peierls Centre for Theoretical Physics, University of Oxford,1 Keble Road, Oxford OX1 3NP (United Kingdom); Wu, Jackson M.S. [Department of Physics and Astronomy, University of Alabama, Tuscaloosa, AL 35487 (United States)

    2017-03-07

    We develop the formalism of holographic renormalization to compute two-point functions in a holographic Kondo model. The model describes a (0+1)-dimensional impurity spin of a gauged SU(N) interacting with a (1+1)-dimensional, large-N, strongly-coupled Conformal Field Theory (CFT). We describe the impurity using Abrikosov pseudo-fermions, and define an SU(N)-invariant scalar operator O built from a pseudo-fermion and a CFT fermion. At large N the Kondo interaction is of the form O{sup †}O, which is marginally relevant, and generates a Renormalization Group (RG) flow at the impurity. A second-order mean-field phase transition occurs in which O condenses below a critical temperature, leading to the Kondo effect, including screening of the impurity. Via holography, the phase transition is dual to holographic superconductivity in (1+1)-dimensional Anti-de Sitter space. At all temperatures, spectral functions of O exhibit a Fano resonance, characteristic of a continuum of states interacting with an isolated resonance. In contrast to Fano resonances observed for example in quantum dots, our continuum and resonance arise from a (0+1)-dimensional UV fixed point and RG flow, respectively. In the low-temperature phase, the resonance comes from a pole in the Green’s function of the form −i〈O〉{sup 2}, which is characteristic of a Kondo resonance.

  4. Multiple Monte Carlo Testing with Applications in Spatial Point Processes

    DEFF Research Database (Denmark)

    Mrkvička, Tomáš; Myllymäki, Mari; Hahn, Ute

    with a function as the test statistic, 3) several Monte Carlo tests with functions as test statistics. The rank test has correct (global) type I error in each case and it is accompanied with a p-value and with a graphical interpretation which shows which subtest or which distances of the used test function......(s) lead to the rejection at the prescribed significance level of the test. Examples of null hypothesis from point process and random set statistics are used to demonstrate the strength of the rank envelope test. The examples include goodness-of-fit test with several test functions, goodness-of-fit test...

  5. The effect of post-processing treatments on inflection points in current–voltage curves of roll-to-roll processed polymer photovoltaics

    DEFF Research Database (Denmark)

    Lilliedal, Mathilde Raad; Medford, Andrew James; Vesterager Madsen, Morten

    2010-01-01

    Inflection point behaviour is often observed in the current–voltage (IV) curve of polymer solar cells. This phenomenon is examined in the context of flexible roll-to-roll (R2R) processed polymer solar cells in a large series of devices with a layer structure of: PET–ITO–ZnO–P3HT...... characterization of device interfaces was carried out in order to identify possible chemical processes that are related to photo-annealing. A possible mechanism based on ZnO photoconductivity, photooxidation and redistribution of oxygen inside the cell is proposed, and it is anticipated that the findings......:PCBM–PEDOT:PSS–Ag. The devices were manufactured using a combination of slot-die coating and screen printing; they were then encapsulated by lamination using a polymer based barrier material. All manufacturing steps were carried out in ambient air. The freshly prepared devices showed a consistent inflection point in the IV...

  6. 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.

  7. 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 &.

  8. The inverse Gamma process: A family of continuous stochastic models for describing state-dependent deterioration phenomena

    International Nuclear Information System (INIS)

    Guida, M.; Pulcini, G.

    2013-01-01

    This paper proposes the family of non-stationary inverse Gamma processes for modeling state-dependent deterioration processes with nonlinear trend. The proposed family of processes, which is based on the assumption that the “inverse” time process is Gamma, is mathematically more tractable than previously proposed state-dependent processes, because, unlike the previous models, the inverse Gamma process is a time-continuous and state-continuous model and does not require discretization of time and state. The conditional distribution of the deterioration growth over a generic time interval, the conditional distribution of the residual life and the residual reliability of the unit, given the current state, are provided. Point and interval estimation of the parameters which index the proposed process, as well as of several quantities of interest, are also discussed. Finally, the proposed model is applied to the wear process of the liners of some Diesel engines which was previously analyzed and proved to be a purely state-dependent process. The comparison of the inferential results obtained under the competitor models shows the ability of the Inverse Gamma process to adequately model the observed state-dependent wear process

  9. Thermodynamic analysis on theoretical models of cycle combined heat exchange process: The reversible heat exchange process

    International Nuclear Information System (INIS)

    Zhang, Chenghu; Li, Yaping

    2017-01-01

    Concept of reversible heat exchange process as the theoretical model of the cycle combined heat exchanger could be useful to determine thermodynamics characteristics and the limitation values in the isolated heat exchange system. In this study, the classification of the reversible heat exchange processes is presented, and with the numerical method, medium temperature variation tendency and the useful work production and usage in the whole process are investigated by the construction and solution of the mathematical descriptions. Various values of medium inlet temperatures and heat capacity ratio are considered to analyze the effects of process parameters on the outlet temperature lift/drop. The maximum process work transferred from the Carnot cycle region to the reverse cycle region is also researched. Moreover, influence of the separating point between different sub-processes on temperature variation profile and the process work production are analyzed. In addition, the heat-exchange-enhancement-factor is defined to study the enhancement effect of the application of the idealized process in the isolated heat exchange system, and the variation degree of this factor with process parameters change is obtained. The research results of this paper can be a theoretical guidance to construct the cycle combined heat exchange process in the practical system. - Highlights: • A theoretical model of Cycle combined heat exchange process is proposed. • The classification of reversible heat exchange process are presented. • Effects of Inlet temperatures and heat capacity ratio on process are analyzed. • Process work transmission through the whole process is studied. • Heat-exchange-enhancement-factor can be a criteria to express the application effect of the idealized process.

  10. Care Model Design for E-Health: Integration of Point-of-Care Testing at Dutch General Practices

    Directory of Open Access Journals (Sweden)

    Bart Verhees

    2017-12-01

    Full Text Available Point-of-care testing (POCT—laboratory tests performed with new mobile devices and online technologies outside of the central laboratory—is rapidly outpacing the traditional laboratory test market, growing at a rate of 12 to 15% each year. POCT impacts the diagnostic process of care providers by yielding high efficiency benefits in terms of turnaround time and related quality improvements in the reduction of errors. However, the implementation of this disruptive eHealth technology requires the integration and transformation of diagnostic services across the boundaries of healthcare organizations. Research has revealed both advantages and barriers of POCT implementations, yet to date, there is no business model for the integration of POCT within general practice. The aim of this article is to contribute with a design for a care model that enables the integration of POCT in primary healthcare. In this research, we used a design modelling toolkit for data collection at five general practices. Through an iterative design process, we modelled the actors and value transactions, and designed an optimized care model for the dynamic integration of POCTs into the GP’s network of care delivery. The care model design will have a direct bearing on improving the integration of POCT through the connectivity and norm guidelines between the general practice, the POC technology, and the diagnostic centre.

  11. Care Model Design for E-Health: Integration of Point-of-Care Testing at Dutch General Practices.

    Science.gov (United States)

    Verhees, Bart; van Kuijk, Kees; Simonse, Lianne

    2017-12-21

    Point-of-care testing (POCT)-laboratory tests performed with new mobile devices and online technologies outside of the central laboratory-is rapidly outpacing the traditional laboratory test market, growing at a rate of 12 to 15% each year. POCT impacts the diagnostic process of care providers by yielding high efficiency benefits in terms of turnaround time and related quality improvements in the reduction of errors. However, the implementation of this disruptive eHealth technology requires the integration and transformation of diagnostic services across the boundaries of healthcare organizations. Research has revealed both advantages and barriers of POCT implementations, yet to date, there is no business model for the integration of POCT within general practice. The aim of this article is to contribute with a design for a care model that enables the integration of POCT in primary healthcare. In this research, we used a design modelling toolkit for data collection at five general practices. Through an iterative design process, we modelled the actors and value transactions, and designed an optimized care model for the dynamic integration of POCTs into the GP's network of care delivery. The care model design will have a direct bearing on improving the integration of POCT through the connectivity and norm guidelines between the general practice, the POC technology, and the diagnostic centre.

  12. Automatic 3D Building Detection and Modeling from Airborne LiDAR Point Clouds

    Science.gov (United States)

    Sun, Shaohui

    Urban reconstruction, with an emphasis on man-made structure modeling, is an active research area with broad impact on several potential applications. Urban reconstruction combines photogrammetry, remote sensing, computer vision, and computer graphics. Even though there is a huge volume of work that has been done, many problems still remain unsolved. Automation is one of the key focus areas in this research. In this work, a fast, completely automated method to create 3D watertight building models from airborne LiDAR (Light Detection and Ranging) point clouds is presented. The developed method analyzes the scene content and produces multi-layer rooftops, with complex rigorous boundaries and vertical walls, that connect rooftops to the ground. The graph cuts algorithm is used to separate vegetative elements from the rest of the scene content, which is based on the local analysis about the properties of the local implicit surface patch. The ground terrain and building rooftop footprints are then extracted, utilizing the developed strategy, a two-step hierarchical Euclidean clustering. The method presented here adopts a "divide-and-conquer" scheme. Once the building footprints are segmented from the terrain and vegetative areas, the whole scene is divided into individual pendent processing units which represent potential points on the rooftop. For each individual building region, significant features on the rooftop are further detected using a specifically designed region-growing algorithm with surface smoothness constraints. The principal orientation of each building rooftop feature is calculated using a minimum bounding box fitting technique, and is used to guide the refinement of shapes and boundaries of the rooftop parts. Boundaries for all of these features are refined for the purpose of producing strict description. Once the description of the rooftops is achieved, polygonal mesh models are generated by creating surface patches with outlines defined by detected

  13. Clusterless Decoding of Position From Multiunit Activity Using A Marked Point Process Filter

    Science.gov (United States)

    Deng, Xinyi; Liu, Daniel F.; Kay, Kenneth; Frank, Loren M.; Eden, Uri T.

    2016-01-01

    Point process filters have been applied successfully to decode neural signals and track neural dynamics. Traditionally, these methods assume that multiunit spiking activity has already been correctly spike-sorted. As a result, these methods are not appropriate for situations where sorting cannot be performed with high precision such as real-time decoding for brain-computer interfaces. As the unsupervised spike-sorting problem remains unsolved, we took an alternative approach that takes advantage of recent insights about clusterless decoding. Here we present a new point process decoding algorithm that does not require multiunit signals to be sorted into individual units. We use the theory of marked point processes to construct a function that characterizes the relationship between a covariate of interest (in this case, the location of a rat on a track) and features of the spike waveforms. In our example, we use tetrode recordings, and the marks represent a four-dimensional vector of the maximum amplitudes of the spike waveform on each of the four electrodes. In general, the marks may represent any features of the spike waveform. We then use Bayes’ rule to estimate spatial location from hippocampal neural activity. We validate our approach with a simulation study and with experimental data recorded in the hippocampus of a rat moving through a linear environment. Our decoding algorithm accurately reconstructs the rat’s position from unsorted multiunit spiking activity. We then compare the quality of our decoding algorithm to that of a traditional spike-sorting and decoding algorithm. Our analyses show that the proposed decoding algorithm performs equivalently or better than algorithms based on sorted single-unit activity. These results provide a path toward accurate real-time decoding of spiking patterns that could be used to carry out content-specific manipulations of population activity in hippocampus or elsewhere in the brain. PMID:25973549

  14. Finding Non-Zero Stable Fixed Points of the Weighted Kuramoto model is NP-hard

    OpenAIRE

    Taylor, Richard

    2015-01-01

    The Kuramoto model when considered over the full space of phase angles [$0,2\\pi$) can have multiple stable fixed points which form basins of attraction in the solution space. In this paper we illustrate the fundamentally complex relationship between the network topology and the solution space by showing that determining the possibility of multiple stable fixed points from the network topology is NP-hard for the weighted Kuramoto Model. In the case of the unweighted model this problem is shown...

  15. Indoor Navigation from Point Clouds: 3d Modelling and Obstacle Detection

    Science.gov (United States)

    Díaz-Vilariño, L.; Boguslawski, P.; Khoshelham, K.; Lorenzo, H.; Mahdjoubi, L.

    2016-06-01

    In the recent years, indoor modelling and navigation has become a research of interest because many stakeholders require navigation assistance in various application scenarios. The navigational assistance for blind or wheelchair people, building crisis management such as fire protection, augmented reality for gaming, tourism or training emergency assistance units are just some of the direct applications of indoor modelling and navigation. Navigational information is traditionally extracted from 2D drawings or layouts. Real state of indoors, including opening position and geometry for both windows and doors, and the presence of obstacles is commonly ignored. In this work, a real indoor-path planning methodology based on 3D point clouds is developed. The value and originality of the approach consist on considering point clouds not only for reconstructing semantically-rich 3D indoor models, but also for detecting potential obstacles in the route planning and using these for readapting the routes according to the real state of the indoor depictured by the laser scanner.

  16. INDOOR NAVIGATION FROM POINT CLOUDS: 3D MODELLING AND OBSTACLE DETECTION

    Directory of Open Access Journals (Sweden)

    L. Díaz-Vilariño

    2016-06-01

    Full Text Available In the recent years, indoor modelling and navigation has become a research of interest because many stakeholders require navigation assistance in various application scenarios. The navigational assistance for blind or wheelchair people, building crisis management such as fire protection, augmented reality for gaming, tourism or training emergency assistance units are just some of the direct applications of indoor modelling and navigation. Navigational information is traditionally extracted from 2D drawings or layouts. Real state of indoors, including opening position and geometry for both windows and doors, and the presence of obstacles is commonly ignored. In this work, a real indoor-path planning methodology based on 3D point clouds is developed. The value and originality of the approach consist on considering point clouds not only for reconstructing semantically-rich 3D indoor models, but also for detecting potential obstacles in the route planning and using these for readapting the routes according to the real state of the indoor depictured by the laser scanner.

  17. Catalysts macroporosity and their efficiency in sulphur sub-dew point Claus tail gas treating processes

    Energy Technology Data Exchange (ETDEWEB)

    Tsybulevski, A.M.; Pearson, M. [Alcoa Industrial Chemicals, 16010 Barker`s Point Lane, Houston, TX (United States); Morgun, L.V.; Filatova, O.E. [All-Russian Research Institute of Natural Gases and Gas Technologies VNIIGAZ, Moscow (Russian Federation); Sharp, M. [Porocel Corporation, Westheimer, Houston, TX (United States)

    1996-10-08

    The efficiency of 4 samples of alumina catalyst has been studied experimentally in the course of the Claus `tail gas` treating processes at the sulphur sub-dew point (TGTP). The samples were characterized by the same chemical and crystallographic composition, the same volume of micropores, the same surface area and the same catalytic activity but differed appreciably in the volume of macropores. An increase in the effective operation time of the catalysts before breakthrough of unrecoverable sulphur containing compounds, with the increasing macropore volume has been established. A theoretical model of the TGTP has been considered and it has been shown that the increase in the sulphur capacity of the catalysts with a larger volume of macropores is due to an increase in the catalysts efficiency factor and a slower decrease in their diffusive permeability during filling of micropores by sulphur

  18. Neutron capture at the s-process branching points $^{171}$Tm and $^{204}$Tl

    CERN Multimedia

    Branching points in the s-process are very special isotopes for which there is a competition between the neutron capture and the subsequent b-decay chain producing the heavy elements beyond Fe. Typically, the knowledge on the associated capture cross sections is very poor due to the difficulty in obtaining enough material of these radioactive isotopes and to measure the cross section of a sample with an intrinsic activity; indeed only 2 out o the 21 ${s}$-process branching points have ever been measured by using the time-of-flight method. In this experiment we aim at measuring for the first time the capture cross sections of $^{171}$Tm and $^{204}$Tl, both of crucial importance for understanding the nucleosynthesis of heavy elements in AGB stars. The combination of both (n,$\\gamma$) measurements on $^{171}$Tm and $^{204}$Tl will allow one to accurately constrain neutron density and the strength of the 13C(α,n) source in low mass AGB stars. Additionally, the cross section of $^{204}$Tl is also of cosmo-chrono...

  19. Research on an uplink carrier sense multiple access algorithm of large indoor visible light communication networks based on an optical hard core point process.

    Science.gov (United States)

    Nan, Zhufen; Chi, Xuefen

    2016-12-20

    The IEEE 802.15.7 protocol suggests that it could coordinate the channel access process based on the competitive method of carrier sensing. However, the directionality of light and randomness of diffuse reflection would give rise to a serious imperfect carrier sense (ICS) problem [e.g., hidden node (HN) problem and exposed node (EN) problem], which brings great challenges in realizing the optical carrier sense multiple access (CSMA) mechanism. In this paper, the carrier sense process implemented by diffuse reflection light is modeled as the choice of independent sets. We establish an ICS model with the presence of ENs and HNs for the multi-point to multi-point visible light communication (VLC) uplink communications system. Considering the severe optical ICS problem, an optical hard core point process (OHCPP) is developed, which characterizes the optical CSMA for the indoor VLC uplink communications system. Due to the limited coverage of the transmitted optical signal, in our OHCPP, the ENs within the transmitters' carrier sense region could be retained provided that they could not corrupt the ongoing communications. Moreover, because of the directionality of both light emitting diode (LED) transmitters and receivers, theoretical analysis of the HN problem becomes difficult. In this paper, we derive the closed-form expression for approximating the outage probability and transmission capacity of VLC networks with the presence of HNs and ENs. Simulation results validate the analysis and also show the existence of an optimal physical carrier-sensing threshold that maximizes the transmission capacity for a given emission angle of LED.

  20. A Matérn model of the spatial covariance structure of point rain rates

    KAUST Repository

    Sun, Ying; Bowman, Kenneth P.; Genton, Marc G.; Tokay, Ali

    2014-01-01

    It is challenging to model a precipitation field due to its intermittent and highly scale-dependent nature. Many models of point rain rates or areal rainfall observations have been proposed and studied for different time scales. Among them, the spectral model based on a stochastic dynamical equation for the instantaneous point rain rate field is attractive, since it naturally leads to a consistent space–time model. In this paper, we note that the spatial covariance structure of the spectral model is equivalent to the well-known Matérn covariance model. Using high-quality rain gauge data, we estimate the parameters of the Matérn model for different time scales and demonstrate that the Matérn model is superior to an exponential model, particularly at short time scales.

  1. A Matérn model of the spatial covariance structure of point rain rates

    KAUST Repository

    Sun, Ying

    2014-07-15

    It is challenging to model a precipitation field due to its intermittent and highly scale-dependent nature. Many models of point rain rates or areal rainfall observations have been proposed and studied for different time scales. Among them, the spectral model based on a stochastic dynamical equation for the instantaneous point rain rate field is attractive, since it naturally leads to a consistent space–time model. In this paper, we note that the spatial covariance structure of the spectral model is equivalent to the well-known Matérn covariance model. Using high-quality rain gauge data, we estimate the parameters of the Matérn model for different time scales and demonstrate that the Matérn model is superior to an exponential model, particularly at short time scales.

  2. 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.

  3. On Lie point symmetry of classical Wess-Zumino-Witten model

    International Nuclear Information System (INIS)

    Maharana, Karmadeva

    2001-06-01

    We perform the group analysis of Witten's equations of motion for a particle moving in the presence of a magnetic monopole, and also when constrained to move on the surface of a sphere, which is the classical example of Wess-Zumino-Witten model. We also consider variations of this model. Our analysis gives the generators of the corresponding Lie point symmetries. The Lie symmetry corresponding to Kepler's third law is obtained in two related examples. (author)

  4. A mixture model for robust point matching under multi-layer motion.

    Directory of Open Access Journals (Sweden)

    Jiayi Ma

    Full Text Available This paper proposes an efficient mixture model for establishing robust point correspondences between two sets of points under multi-layer motion. Our algorithm starts by creating a set of putative correspondences which can contain a number of false correspondences, or outliers, in addition to the true correspondences (inliers. Next we solve for correspondence by interpolating a set of spatial transformations on the putative correspondence set based on a mixture model, which involves estimating a consensus of inlier points whose matching follows a non-parametric geometrical constraint. We formulate this as a maximum a posteriori (MAP estimation of a Bayesian model with hidden/latent variables indicating whether matches in the putative set are outliers or inliers. We impose non-parametric geometrical constraints on the correspondence, as a prior distribution, in a reproducing kernel Hilbert space (RKHS. MAP estimation is performed by the EM algorithm which by also estimating the variance of the prior model (initialized to a large value is able to obtain good estimates very quickly (e.g., avoiding many of the local minima inherent in this formulation. We further provide a fast implementation based on sparse approximation which can achieve a significant speed-up without much performance degradation. We illustrate the proposed method on 2D and 3D real images for sparse feature correspondence, as well as a public available dataset for shape matching. The quantitative results demonstrate that our method is robust to non-rigid deformation and multi-layer/large discontinuous motion.

  5. Upscaling Empirically Based Conceptualisations to Model Tropical Dominant Hydrological Processes for Historical Land Use Change

    Science.gov (United States)

    Toohey, R.; Boll, J.; Brooks, E.; Jones, J.

    2009-12-01

    Surface runoff and percolation to ground water are two hydrological processes of concern to the Atlantic slope of Costa Rica because of their impacts on flooding and drinking water contamination. As per legislation, the Costa Rican Government funds land use management from the farm to the regional scale to improve or conserve hydrological ecosystem services. In this study, we examined how land use (e.g., forest, coffee, sugar cane, and pasture) affects hydrological response at the point, plot (1 m2), and the field scale (1-6ha) to empirically conceptualize the dominant hydrological processes in each land use. Using our field data, we upscaled these conceptual processes into a physically-based distributed hydrological model at the field, watershed (130 km2), and regional (1500 km2) scales. At the point and plot scales, the presence of macropores and large roots promoted greater vertical percolation and subsurface connectivity in the forest and coffee field sites. The lack of macropores and large roots, plus the addition of management artifacts (e.g., surface compaction and a plough layer), altered the dominant hydrological processes by increasing lateral flow and surface runoff in the pasture and sugar cane field sites. Macropores and topography were major influences on runoff generation at the field scale. Also at the field scale, antecedent moisture conditions suggest a threshold behavior as a temporal control on surface runoff generation. However, in this tropical climate with very intense rainstorms, annual surface runoff was less than 10% of annual precipitation at the field scale. Significant differences in soil and hydrological characteristics observed at the point and plot scales appear to have less significance when upscaled to the field scale. At the point and plot scales, percolation acted as the dominant hydrological process in this tropical environment. However, at the field scale for sugar cane and pasture sites, saturation-excess runoff increased as

  6. 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...

  7. Laser scanner data processing and 3D modeling using a free and open source software

    International Nuclear Information System (INIS)

    Gabriele, Fatuzzo; Michele, Mangiameli; Giuseppe, Mussumeci; Salvatore, Zito

    2015-01-01

    The laser scanning is a technology that allows in a short time to run the relief geometric objects with a high level of detail and completeness, based on the signal emitted by the laser and the corresponding return signal. When the incident laser radiation hits the object to detect, then the radiation is reflected. The purpose is to build a three-dimensional digital model that allows to reconstruct the reality of the object and to conduct studies regarding the design, restoration and/or conservation. When the laser scanner is equipped with a digital camera, the result of the measurement process is a set of points in XYZ coordinates showing a high density and accuracy with radiometric and RGB tones. In this case, the set of measured points is called “point cloud” and allows the reconstruction of the Digital Surface Model. Even the post-processing is usually performed by closed source software, which is characterized by Copyright restricting the free use, free and open source software can increase the performance by far. Indeed, this latter can be freely used providing the possibility to display and even custom the source code. The experience started at the Faculty of Engineering in Catania is aimed at finding a valuable free and open source tool, MeshLab (Italian Software for data processing), to be compared with a reference closed source software for data processing, i.e. RapidForm. In this work, we compare the results obtained with MeshLab and Rapidform through the planning of the survey and the acquisition of the point cloud of a morphologically complex statue

  8. Laser scanner data processing and 3D modeling using a free and open source software

    Energy Technology Data Exchange (ETDEWEB)

    Gabriele, Fatuzzo [Dept. of Industrial and Mechanical Engineering, University of Catania (Italy); Michele, Mangiameli, E-mail: amichele.mangiameli@dica.unict.it; Giuseppe, Mussumeci; Salvatore, Zito [Dept. of Civil Engineering and Architecture, University of Catania (Italy)

    2015-03-10

    The laser scanning is a technology that allows in a short time to run the relief geometric objects with a high level of detail and completeness, based on the signal emitted by the laser and the corresponding return signal. When the incident laser radiation hits the object to detect, then the radiation is reflected. The purpose is to build a three-dimensional digital model that allows to reconstruct the reality of the object and to conduct studies regarding the design, restoration and/or conservation. When the laser scanner is equipped with a digital camera, the result of the measurement process is a set of points in XYZ coordinates showing a high density and accuracy with radiometric and RGB tones. In this case, the set of measured points is called “point cloud” and allows the reconstruction of the Digital Surface Model. Even the post-processing is usually performed by closed source software, which is characterized by Copyright restricting the free use, free and open source software can increase the performance by far. Indeed, this latter can be freely used providing the possibility to display and even custom the source code. The experience started at the Faculty of Engineering in Catania is aimed at finding a valuable free and open source tool, MeshLab (Italian Software for data processing), to be compared with a reference closed source software for data processing, i.e. RapidForm. In this work, we compare the results obtained with MeshLab and Rapidform through the planning of the survey and the acquisition of the point cloud of a morphologically complex statue.

  9. Modeling Dynamic Food Choice Processes to Understand Dietary Intervention Effects.

    Science.gov (United States)

    Marcum, Christopher Steven; Goldring, Megan R; McBride, Colleen M; Persky, Susan

    2018-02-17

    Meal construction is largely governed by nonconscious and habit-based processes that can be represented as a collection of in dividual, micro-level food choices that eventually give rise to a final plate. Despite this, dietary behavior intervention research rarely captures these micro-level food choice processes, instead measuring outcomes at aggregated levels. This is due in part to a dearth of analytic techniques to model these dynamic time-series events. The current article addresses this limitation by applying a generalization of the relational event framework to model micro-level food choice behavior following an educational intervention. Relational event modeling was used to model the food choices that 221 mothers made for their child following receipt of an information-based intervention. Participants were randomized to receive either (a) control information; (b) childhood obesity risk information; (c) childhood obesity risk information plus a personalized family history-based risk estimate for their child. Participants then made food choices for their child in a virtual reality-based food buffet simulation. Micro-level aspects of the built environment, such as the ordering of each food in the buffet, were influential. Other dynamic processes such as choice inertia also influenced food selection. Among participants receiving the strongest intervention condition, choice inertia decreased and the overall rate of food selection increased. Modeling food selection processes can elucidate the points at which interventions exert their influence. Researchers can leverage these findings to gain insight into nonconscious and uncontrollable aspects of food selection that influence dietary outcomes, which can ultimately improve the design of dietary interventions.

  10. 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

  11. A semi-analytical stationary model of a point-to-plane corona discharge

    International Nuclear Information System (INIS)

    Yanallah, K; Pontiga, F

    2012-01-01

    A semi-analytical model of a dc corona discharge is formulated to determine the spatial distribution of charged particles (electrons, negative ions and positive ions) and the electric field in pure oxygen using a point-to-plane electrode system. A key point in the modeling is the integration of Gauss' law and the continuity equation of charged species along the electric field lines, and the use of Warburg's law and the corona current–voltage characteristics as input data in the boundary conditions. The electric field distribution predicted by the model is compared with the numerical solution obtained using a finite-element technique. The semi-analytical solutions are obtained at a negligible computational cost, and provide useful information to characterize and control the corona discharge in different technological applications. (paper)

  12. 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

  13. Two- and three-point functions in the D=1 matrix model

    International Nuclear Information System (INIS)

    Ben-Menahem, S.

    1991-01-01

    The critical behavior of the genus-zero two-point function in the D=1 matrix model is carefully analyzed for arbitrary embedding-space momentum. Kostov's result is recovered for momenta below a certain value P 0 (which is 1/√α' in the continuum language), with a non-universal form factor which is expressed simply in terms of the critical fermion trajectory. For momenta above P 0 , the Kostov scaling term is found to be subdominant. We then extend the large-N WKB treatment to calculate the genus-zero three-point function, and elucidate its critical behavior when all momenta are below P 0 . The resulting universal scaling behavior, as well as the non-universal form factor for the three-point function, are related to the two-point functions of the individual external momenta, through the factorization familiar from continuum conformal field theories. (orig.)

  14. Cauchy cluster process

    DEFF Research Database (Denmark)

    Ghorbani, Mohammad

    2013-01-01

    In this paper we introduce an instance of the well-know Neyman–Scott cluster process model with clusters having a long tail behaviour. In our model the offspring points are distributed around the parent points according to a circular Cauchy distribution. Using a modified Cramér-von Misses test...

  15. 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.

  16. Defining the end-point of mastication: A conceptual model.

    Science.gov (United States)

    Gray-Stuart, Eli M; Jones, Jim R; Bronlund, John E

    2017-10-01

    The great risks of swallowing are choking and aspiration of food into the lungs. Both are rare in normal functioning humans, which is remarkable given the diversity of foods and the estimated 10 million swallows performed in a lifetime. Nevertheless, it remains a major challenge to define the food properties that are necessary to ensure a safe swallow. Here, the mouth is viewed as a well-controlled processor where mechanical sensory assessment occurs throughout the occlusion-circulation cycle of mastication. Swallowing is a subsequent action. It is proposed here that, during mastication, temporal maps of interfacial property data are generated, which the central nervous system compares against a series of criteria in order to be sure that the bolus is safe to swallow. To determine these criteria, an engineering hazard analysis tool, alongside an understanding of fluid and particle mechanics, is used to deduce the mechanisms by which food may deposit or become stranded during swallowing. These mechanisms define the food properties that must be avoided. By inverting the thinking, from hazards to ensuring safety, six criteria arise which are necessary for a safe-to-swallow bolus. A new conceptual model is proposed to define when food is safe to swallow during mastication. This significantly advances earlier mouth models. The conceptual model proposed in this work provides a framework of decision-making to define when food is safe to swallow. This will be of interest to designers of dietary foods, foods for dysphagia sufferers and will aid the further development of mastication robots for preparation of artificial boluses for digestion research. It enables food designers to influence the swallow-point properties of their products. For example, a product may be designed to satisfy five of the criteria for a safe-to-swallow bolus, which means the sixth criterion and its attendant food properties define the swallow-point. Alongside other organoleptic factors, these

  17. An IFC schema extension and binary serialization format to efficiently integrate point cloud data into building models

    NARCIS (Netherlands)

    Krijnen, T.F.; Beetz, J.

    2017-01-01

    In this paper we suggest an extension to the Industry Foundation Classes (IFC) model to integrate point cloud datasets. The proposal includes a schema extension to the core model allowing the storage of points, either as Cartesian coordinates, points in parametric space of associated building

  18. The algorithm to generate color point-cloud with the registration between panoramic image and laser point-cloud

    International Nuclear Information System (INIS)

    Zeng, Fanyang; Zhong, Ruofei

    2014-01-01

    Laser point cloud contains only intensity information and it is necessary for visual interpretation to obtain color information from other sensor. Cameras can provide texture, color, and other information of the corresponding object. Points with color information of corresponding pixels in digital images can be used to generate color point-cloud and is conducive to the visualization, classification and modeling of point-cloud. Different types of digital cameras are used in different Mobile Measurement Systems (MMS).the principles and processes for generating color point-cloud in different systems are not the same. The most prominent feature of the panoramic images is the field of 360 degrees view angle in the horizontal direction, to obtain the image information around the camera as much as possible. In this paper, we introduce a method to generate color point-cloud with panoramic image and laser point-cloud, and deduce the equation of the correspondence between points in panoramic images and laser point-clouds. The fusion of panoramic image and laser point-cloud is according to the collinear principle of three points (the center of the omnidirectional multi-camera system, the image point on the sphere, the object point). The experimental results show that the proposed algorithm and formulae in this paper are correct

  19. Spatiotemporal processing of gated cardiac SPECT images using deformable mesh modeling

    International Nuclear Information System (INIS)

    Brankov, Jovan G.; Yang Yongyi; Wernick, Miles N.

    2005-01-01

    In this paper we present a spatiotemporal processing approach, based on deformable mesh modeling, for noise reduction in gated cardiac single-photon emission computed tomography images. Because of the partial volume effect (PVE), clinical cardiac-gated perfusion images exhibit a phenomenon known as brightening--the myocardium appears to become brighter as the heart wall thickens. Although brightening is an artifact, it serves as an important diagnostic feature for assessment of wall thickening in clinical practice. Our proposed processing algorithm aims to preserve this important diagnostic feature while reducing the noise level in the images. The proposed algorithm is based on the use of a deformable mesh for modeling the cardiac motion in a gated cardiac sequence, based on which the images are processed by smoothing along space-time trajectories of object points while taking into account the PVE. Our experiments demonstrate that the proposed algorithm can yield significantly more-accurate results than several existing methods

  20. An analytical calculation of neighbourhood order probabilities for high dimensional Poissonian processes and mean field models

    International Nuclear Information System (INIS)

    Tercariol, Cesar Augusto Sangaletti; Kiipper, Felipe de Moura; Martinez, Alexandre Souto

    2007-01-01

    Consider that the coordinates of N points are randomly generated along the edges of a d-dimensional hypercube (random point problem). The probability P (d,N) m,n that an arbitrary point is the mth nearest neighbour to its own nth nearest neighbour (Cox probabilities) plays an important role in spatial statistics. Also, it has been useful in the description of physical processes in disordered media. Here we propose a simpler derivation of Cox probabilities, where we stress the role played by the system dimensionality d. In the limit d → ∞, the distances between pair of points become independent (random link model) and closed analytical forms for the neighbourhood probabilities are obtained both for the thermodynamic limit and finite-size system. Breaking the distance symmetry constraint drives us to the random map model, for which the Cox probabilities are obtained for two cases: whether a point is its own nearest neighbour or not

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