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....
Modeling fixation locations using spatial point processes.
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.
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)
Statistical properties of several models of fractional random point processes
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.
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....
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....
Self-Exciting Point Process Modeling of Conversation Event Sequences
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.
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...
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.
A CASE STUDY ON POINT PROCESS MODELLING IN DISEASE MAPPING
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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.
Multiplicative point process as a model of trading activity
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.
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
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....
Marked point process for modelling seismic activity (case study in Sumatra and Java)
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.
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...
Development and evaluation of spatial point process models for epidermal nerve fibers.
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.
The importance of topographically corrected null models for analyzing ecological point processes.
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.
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....
Spatial Mixture Modelling for Unobserved Point Processes: Examples in Immunofluorescence Histology.
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.
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
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....
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.
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
Linear and quadratic models of point process systems: contributions of patterned input to output.
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.
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....
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.
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....
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....
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.
Detecting determinism from point processes.
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.
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.
Detection of bursts in extracellular spike trains using hidden semi-Markov point process models.
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.
Point process modeling and estimation: Advances in the analysis of dynamic neural spiking data
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
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.
Insights into mortality patterns and causes of death through a process point of view model.
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.
Point process models for localization and interdependence of punctate cellular structures.
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.
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....
Process-based coastal erosion modeling for Drew Point (North Slope, Alaska)
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).
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.
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
Plasmon point spread functions: How do we model plasmon-mediated emission processes?
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.
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...
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
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....
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...
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....
State estimation for temporal point processes
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
Stochastic dynamical model of a growing citation network based on a self-exciting point process.
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.
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
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....
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....
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...
Further developments of the Neyman-Scott clustered point process for modeling rainfall
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.
DEFF Research Database (Denmark)
Østergaard, Jacob; Kramer, Mark A.; Eden, Uri T.
2018-01-01
current. We then fit these spike train datawith a statistical model (a generalized linear model, GLM, with multiplicative influences of past spiking). For different levels of noise, we show how the GLM captures both the deterministic features of the Izhikevich neuron and the variability driven...... by the noise. We conclude that the GLM captures essential features of the simulated spike trains, but for near-deterministic spike trains, goodness-of-fit analyses reveal that the model does not fit very well in a statistical sense; the essential random part of the GLM is not captured....... are separately applied; understanding the relationships between these modeling approaches remains an area of active research. In this letter, we examine this relationship using simulation. To do so, we first generate spike train data from a well-known dynamical model, the Izhikevich neuron, with a noisy input...
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
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...
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...
Smooth random change point models.
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.
Processing Terrain Point Cloud Data
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.
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 SO_{2} mixing ratios and PM_{2.5} mass, but reproduced the range of observed SO_{2} 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
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.
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.
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....
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...
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...
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
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...
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...
Processing Terrain Point Cloud Data
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
Estimating Function Approaches for Spatial Point Processes
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
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...
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...
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.
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
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...
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....
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.
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)...
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.
Model for Semantically Rich Point Cloud Data
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.
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.
Poisson point processes imaging, tracking, and sensing
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.
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 (...
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...
Lombardo, Luigi; Opitz, Thomas; Huser, Raphaë l
2018-01-01
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 on the unobserved rainfall
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.
Directory of Open Access Journals (Sweden)
Lotfi Khribi
2017-12-01
Full Text Available In the Bayesian framework, the usual choice of prior in the prediction of homogeneous Poisson processes with random effects is the gamma one. Here, we propose the use of higher order maximum entropy priors. Their advantage is illustrated in a simulation study and the choice of the best order is established by two goodness-of-fit criteria: Kullback–Leibler divergence and a discrepancy measure. This procedure is illustrated on a warranty data set from the automobile industry.
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.
Extreme values, regular variation and point processes
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...
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.
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.
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
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...
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)
Pseudo-dynamic source modelling with 1-point and 2-point statistics of earthquake source parameters
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
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.
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.
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
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...
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....
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.
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
Framework for adaptive multiscale analysis of nonhomogeneous point processes.
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.
Some probabilistic properties of fractional point processes
Garra, Roberto
2017-05-16
In this article, the first hitting times of generalized Poisson processes N-f (t), related to Bernstein functions f are studied. For the spacefractional Poisson processes, N alpha (t), t > 0 ( corresponding to f = x alpha), the hitting probabilities P{T-k(alpha) < infinity} are explicitly obtained and analyzed. The processes N-f (t) are time-changed Poisson processes N( H-f (t)) with subordinators H-f (t) and here we study N(Sigma H-n(j= 1)f j (t)) and obtain probabilistic features of these extended counting processes. A section of the paper is devoted to processes of the form N( G(H,v) (t)) where G(H,v) (t) are generalized grey Brownian motions. This involves the theory of time-dependent fractional operators of the McBride form. While the time-fractional Poisson process is a renewal process, we prove that the space-time Poisson process is no longer a renewal process.
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....
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...
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.
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.
Some probabilistic properties of fractional point processes
Garra, Roberto; Orsingher, Enzo; Scavino, Marco
2017-01-01
P{T-k(alpha) < infinity} are explicitly obtained and analyzed. The processes N-f (t) are time-changed Poisson processes N( H-f (t)) with subordinators H-f (t) and here we study N(Sigma H-n(j= 1)f j (t)) and obtain probabilistic features
Intensity-dependent point spread image processing
International Nuclear Information System (INIS)
Cornsweet, T.N.; Yellott, J.I.
1984-01-01
There is ample anatomical, physiological and psychophysical evidence that the mammilian retina contains networks that mediate interactions among neighboring receptors, resulting in intersecting transformations between input images and their corresponding neural output patterns. The almost universally accepted view is that the principal form of interaction involves lateral inhibition, resulting in an output pattern that is the convolution of the input with a ''Mexican hat'' or difference-of-Gaussians spread function, having a positive center and a negative surround. A closely related process is widely applied in digital image processing, and in photography as ''unsharp masking''. The authors show that a simple and fundamentally different process, involving no inhibitory or subtractive terms can also account for the physiological and psychophysical findings that have been attributed to lateral inhibition. This process also results in a number of fundamental effects that occur in mammalian vision and that would be of considerable significance in robotic vision, but which cannot be explained by lateral inhibitory interaction
Pseudo-dynamic source modelling with 1-point and 2-point statistics of earthquake source parameters
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.
Optimal time points sampling in pathway modelling.
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.
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...
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
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
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....
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
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
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
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....
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....
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...
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...
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
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.
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
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...
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...
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.
Semantic Business Process Modeling
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.
Corner-point criterion for assessing nonlinear image processing imagers
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
Pointo - a Low Cost Solution to Point Cloud Processing
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
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.
On estimation of the intensity function of a point process
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
A J–function for inhomogeneous point processes
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
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.
Business process modeling in healthcare.
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.
Modeling nuclear processes by Simulink
Energy Technology Data Exchange (ETDEWEB)
Rashid, Nahrul Khair Alang Md, E-mail: nahrul@iium.edu.my [Faculty of Engineering, International Islamic University Malaysia, Jalan Gombak, Selangor (Malaysia)
2015-04-29
Modelling and simulation are essential parts in the study of dynamic systems behaviours. In nuclear engineering, modelling and simulation are important to assess the expected results of an experiment before the actual experiment is conducted or in the design of nuclear facilities. In education, modelling can give insight into the dynamic of systems and processes. Most nuclear processes can be described by ordinary or partial differential equations. Efforts expended to solve the equations using analytical or numerical solutions consume time and distract attention from the objectives of modelling itself. This paper presents the use of Simulink, a MATLAB toolbox software that is widely used in control engineering, as a modelling platform for the study of nuclear processes including nuclear reactor behaviours. Starting from the describing equations, Simulink models for heat transfer, radionuclide decay process, delayed neutrons effect, reactor point kinetic equations with delayed neutron groups, and the effect of temperature feedback are used as examples.
Modeling nuclear processes by Simulink
International Nuclear Information System (INIS)
Rashid, Nahrul Khair Alang Md
2015-01-01
Modelling and simulation are essential parts in the study of dynamic systems behaviours. In nuclear engineering, modelling and simulation are important to assess the expected results of an experiment before the actual experiment is conducted or in the design of nuclear facilities. In education, modelling can give insight into the dynamic of systems and processes. Most nuclear processes can be described by ordinary or partial differential equations. Efforts expended to solve the equations using analytical or numerical solutions consume time and distract attention from the objectives of modelling itself. This paper presents the use of Simulink, a MATLAB toolbox software that is widely used in control engineering, as a modelling platform for the study of nuclear processes including nuclear reactor behaviours. Starting from the describing equations, Simulink models for heat transfer, radionuclide decay process, delayed neutrons effect, reactor point kinetic equations with delayed neutron groups, and the effect of temperature feedback are used as examples
Modeling multiphase materials processes
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
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...
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.
Shot-noise-weighted processes : a new family of spatial point processes
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
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....
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...
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
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...
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....
Business Process Modeling: Perceived Benefits
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.
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.
Integrated modeling and analysis methodology for precision pointing applications
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.
Simple computation of reaction–diffusion processes on point clouds
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.
Simple computation of reaction–diffusion processes on point clouds
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.
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
Metrics for Business Process Models
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.
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...
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...
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.
Sand Point, Alaska Coastal Digital Elevation Model
National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Geophysical Data Center (NGDC) is building high-resolution digital elevation models (DEMs) for select U.S. coastal regions. These integrated...
Sand Point, Alaska Tsunami Forecast Grids for MOST Model
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....
Toke Point, Washington Tsunami Forecast Grids for MOST Model
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....
Model Process Control Language
National Aeronautics and Space Administration — The MPC (Model Process Control) language enables the capture, communication and preservation of a simulation instance, with sufficient detail that it can be...
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.)
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.
Using a Virtual Experiment to Analyze Infiltration Process from Point to Grid-cell Size Scale
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
Biosphere Process Model Report
Energy Technology Data Exchange (ETDEWEB)
J. Schmitt
2000-05-25
To evaluate the postclosure performance of a potential monitored geologic repository at Yucca Mountain, a Total System Performance Assessment (TSPA) will be conducted. Nine Process Model Reports (PMRs), including this document, are being developed to summarize the technical basis for each of the process models supporting the TSPA model. These reports cover the following areas: (1) Integrated Site Model; (2) Unsaturated Zone Flow and Transport; (3) Near Field Environment; (4) Engineered Barrier System Degradation, Flow, and Transport; (5) Waste Package Degradation; (6) Waste Form Degradation; (7) Saturated Zone Flow and Transport; (8) Biosphere; and (9) Disruptive Events. Analysis/Model Reports (AMRs) contain the more detailed technical information used to support TSPA and the PMRs. The AMRs consists of data, analyses, models, software, and supporting documentation that will be used to defend the applicability of each process model for evaluating the postclosure performance of the potential Yucca Mountain repository system. This documentation will ensure the traceability of information from its source through its ultimate use in the TSPA-Site Recommendation (SR) and in the National Environmental Policy Act (NEPA) analysis processes. The objective of the Biosphere PMR is to summarize (1) the development of the biosphere model, and (2) the Biosphere Dose Conversion Factors (BDCFs) developed for use in TSPA. The Biosphere PMR does not present or summarize estimates of potential radiation doses to human receptors. Dose calculations are performed as part of TSPA and will be presented in the TSPA documentation. The biosphere model is a component of the process to evaluate postclosure repository performance and regulatory compliance for a potential monitored geologic repository at Yucca Mountain, Nevada. The biosphere model describes those exposure pathways in the biosphere by which radionuclides released from a potential repository could reach a human receptor
Biosphere Process Model Report
International Nuclear Information System (INIS)
Schmitt, J.
2000-01-01
To evaluate the postclosure performance of a potential monitored geologic repository at Yucca Mountain, a Total System Performance Assessment (TSPA) will be conducted. Nine Process Model Reports (PMRs), including this document, are being developed to summarize the technical basis for each of the process models supporting the TSPA model. These reports cover the following areas: (1) Integrated Site Model; (2) Unsaturated Zone Flow and Transport; (3) Near Field Environment; (4) Engineered Barrier System Degradation, Flow, and Transport; (5) Waste Package Degradation; (6) Waste Form Degradation; (7) Saturated Zone Flow and Transport; (8) Biosphere; and (9) Disruptive Events. Analysis/Model Reports (AMRs) contain the more detailed technical information used to support TSPA and the PMRs. The AMRs consists of data, analyses, models, software, and supporting documentation that will be used to defend the applicability of each process model for evaluating the postclosure performance of the potential Yucca Mountain repository system. This documentation will ensure the traceability of information from its source through its ultimate use in the TSPA-Site Recommendation (SR) and in the National Environmental Policy Act (NEPA) analysis processes. The objective of the Biosphere PMR is to summarize (1) the development of the biosphere model, and (2) the Biosphere Dose Conversion Factors (BDCFs) developed for use in TSPA. The Biosphere PMR does not present or summarize estimates of potential radiation doses to human receptors. Dose calculations are performed as part of TSPA and will be presented in the TSPA documentation. The biosphere model is a component of the process to evaluate postclosure repository performance and regulatory compliance for a potential monitored geologic repository at Yucca Mountain, Nevada. The biosphere model describes those exposure pathways in the biosphere by which radionuclides released from a potential repository could reach a human receptor
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
Dew Point modelling using GEP based multi objective optimization
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...
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
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.
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...
Point Reyes, California Tsunami Forecast Grids for MOST Model
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)...
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)
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
Aerospace Materials Process Modelling
1988-08-01
Cooling Transformation diagram ( CCT diagram ) When a IT diagram is used in the heat process modelling, we suppose that a sudden cooling (instantaneous...processes. CE, chooses instead to study thermo-mechanical properties referring to a CCT diagram . This is thinked to be more reliable to give a true...k , mm-_____sml l ml A I 1 III 12.4 This determination is however based on the following approximations: i) A CCT diagram is valid only for the
Dense range images from sparse point clouds using multi-scale processing
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
Business Model Process Configurations
DEFF Research Database (Denmark)
Taran, Yariv; Nielsen, Christian; Thomsen, Peter
2015-01-01
, by developing (inductively) an ontological classification framework, in view of the BM process configurations typology developed. Design/methodology/approach – Given the inconsistencies found in the business model studies (e.g. definitions, configurations, classifications) we adopted the analytical induction...
Impact of selected troposphere models on Precise Point Positioning convergence
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
Seeking a fingerprint: analysis of point processes in actigraphy recording
Gudowska-Nowak, Ewa; Ochab, Jeremi K.; Oleś, Katarzyna; Beldzik, Ewa; Chialvo, Dante R.; Domagalik, Aleksandra; Fąfrowicz, Magdalena; Marek, Tadeusz; Nowak, Maciej A.; Ogińska, Halszka; Szwed, Jerzy; Tyburczyk, Jacek
2016-05-01
Motor activity of humans displays complex temporal fluctuations which can be characterised by scale-invariant statistics, thus demonstrating that structure and fluctuations of such kinetics remain similar over a broad range of time scales. Previous studies on humans regularly deprived of sleep or suffering from sleep disorders predicted a change in the invariant scale parameters with respect to those for healthy subjects. In this study we investigate the signal patterns from actigraphy recordings by means of characteristic measures of fractional point processes. We analyse spontaneous locomotor activity of healthy individuals recorded during a week of regular sleep and a week of chronic partial sleep deprivation. Behavioural symptoms of lack of sleep can be evaluated by analysing statistics of duration times during active and resting states, and alteration of behavioural organisation can be assessed by analysis of power laws detected in the event count distribution, distribution of waiting times between consecutive movements and detrended fluctuation analysis of recorded time series. We claim that among different measures characterising complexity of the actigraphy recordings and their variations implied by chronic sleep distress, the exponents characterising slopes of survival functions in resting states are the most effective biomarkers distinguishing between healthy and sleep-deprived groups.
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.
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.
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.
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...
The Hinkley Point decision: An analysis of the policy process
International Nuclear Information System (INIS)
Thomas, Stephen
2016-01-01
In 2006, the British government launched a policy to build nuclear power reactors based on a claim that the power produced would be competitive with fossil fuel and would require no public subsidy. A decade later, it is not clear how many, if any, orders will be placed and the claims on costs and subsidies have proved false. Despite this failure to deliver, the policy is still being pursued with undiminished determination. The finance model that is now proposed is seen as a model other European countries can follow so the success or otherwise of the British nuclear programme will have implications outside the UK. This paper contends that the checks and balances that should weed out misguided policies, have failed. It argues that the most serious failure is with the civil service and its inability to provide politicians with high quality advice – truth to power. It concludes that the failure is likely to be due to the unwillingness of politicians to listen to opinions that conflict with their beliefs. Other weaknesses include the lack of energy expertise in the media, the unwillingness of the public to engage in the policy process and the impotence of Parliamentary Committees. - Highlights: •Britain's nuclear power policy is failing due to high costs and problems of finance. •This has implications for European countries who want to use the same financing model. •The continued pursuit of a failing policy is due to poor advice from civil servants. •Lack of expertise in the media and lack of public engagement have contributed. •Parliamentary processes have not provided proper critical scrutiny.
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.
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
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.)
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.
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.
The Automation of Nowcast Model Assessment Processes
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
Business process model repositories : efficient process retrieval
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
The S-Process Branching-Point at 205PB
Tonchev, Anton; Tsoneva, N.; Bhatia, C.; Arnold, C. W.; Goriely, S.; Hammond, S. L.; Kelley, J. H.; Kwan, E.; Lenske, H.; Piekarewicz, J.; Raut, R.; Rusev, G.; Shizuma, T.; Tornow, W.
2017-09-01
Accurate neutron-capture cross sections for radioactive nuclei near the line of beta stability are crucial for understanding s-process nucleosynthesis. However, neutron-capture cross sections for short-lived radionuclides are difficult to measure due to the fact that the measurements require both highly radioactive samples and intense neutron sources. We consider photon scattering using monoenergetic and 100% linearly polarized photon beams to obtain the photoabsorption cross section on 206Pb below the neutron separation energy. This observable becomes an essential ingredient in the Hauser-Feshbach statistical model for calculations of capture cross sections on 205Pb. The newly obtained photoabsorption information is also used to estimate the Maxwellian-averaged radiative cross section of 205Pb(n,g)206Pb at 30 keV. The astrophysical impact of this measurement on s-process nucleosynthesis will be discussed. This work was performed under the auspices of US DOE by LLNL under Contract DE-AC52-07NA27344.
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.
Two point function for a simple general relativistic quantum model
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.
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...
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...
Effect of processing conditions on oil point pressure of moringa oleifera seed.
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.
Process model repositories and PNML
Hee, van K.M.; Post, R.D.J.; Somers, L.J.A.M.; Werf, van der J.M.E.M.; Kindler, E.
2004-01-01
Bringing system and process models together in repositories facilitates the interchange of model information between modelling tools, and allows the combination and interlinking of complementary models. Petriweb is a web application for managing such repositories. It supports hierarchical process
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.
Accuracy limit of rigid 3-point water models
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.
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...
Modeling styles in business process modeling
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
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...
Equivalence of functional limit theorems for stationary point processes and their Palm distributions
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
Modeling hard clinical end-point data in economic analyses.
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
Microbial profile and critical control points during processing of 'robo ...
African Journals Online (AJOL)
STORAGESEVER
2009-05-18
May 18, 2009 ... frying, surface fat draining, open-air cooling, and holding/packaging in polyethylene films during sales and distribution. The product was, however, classified under category III with respect to risk and the significance of monitoring and evaluation of quality using the hazard analysis critical control point.
Discussion of "Modern statistics for spatial point processes"
DEFF Research Database (Denmark)
Jensen, Eva Bjørn Vedel; Prokesová, Michaela; Hellmund, Gunnar
2007-01-01
ABSTRACT. The paper ‘Modern statistics for spatial point processes’ by Jesper Møller and Rasmus P. Waagepetersen is based on a special invited lecture given by the authors at the 21st Nordic Conference on Mathematical Statistics, held at Rebild, Denmark, in June 2006. At the conference, Antti...
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...
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 ...
Reconstruction of Consistent 3d CAD Models from Point Cloud Data Using a Priori CAD Models
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.
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.
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.
Process for structural geologic analysis of topography and point data
Eliason, Jay R.; Eliason, Valerie L. C.
1987-01-01
A quantitative method of geologic structural analysis of digital terrain data is described for implementation on a computer. Assuming selected valley segments are controlled by the underlying geologic structure, topographic lows in the terrain data, defining valley bottoms, are detected, filtered and accumulated into a series line segments defining contiguous valleys. The line segments are then vectorized to produce vector segments, defining valley segments, which may be indicative of the underlying geologic structure. Coplanar analysis is performed on vector segment pairs to determine which vectors produce planes which represent underlying geologic structure. Point data such as fracture phenomena which can be related to fracture planes in 3-dimensional space can be analyzed to define common plane orientation and locations. The vectors, points, and planes are displayed in various formats for interpretation.
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
Modeling the contribution of point sources and non-point sources to Thachin River water pollution.
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.
A MODELING METHOD OF FLUTTERING LEAVES BASED ON POINT CLOUD
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...
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.
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.
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.
Analysis of residual stress state in sheet metal parts processed by single point incremental forming
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.
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.
Lasso and probabilistic inequalities for multivariate point processes
DEFF Research Database (Denmark)
Hansen, Niels Richard; Reynaud-Bouret, Patricia; Rivoirard, Vincent
2015-01-01
Due to its low computational cost, Lasso is an attractive regularization method for high-dimensional statistical settings. In this paper, we consider multivariate counting processes depending on an unknown function parameter to be estimated by linear combinations of a fixed dictionary. To select...... for multivariate Hawkes processes are proven, which allows us to check these assumptions by considering general dictionaries based on histograms, Fourier or wavelet bases. Motivated by problems of neuronal activity inference, we finally carry out a simulation study for multivariate Hawkes processes and compare our...... methodology with the adaptive Lasso procedure proposed by Zou in (J. Amer. Statist. Assoc. 101 (2006) 1418–1429). We observe an excellent behavior of our procedure. We rely on theoretical aspects for the essential question of tuning our methodology. Unlike adaptive Lasso of (J. Amer. Statist. Assoc. 101 (2006...
Multi-Valued Modal Fixed Point Logics for Model Checking
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.
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)
Lasso and probabilistic inequalities for multivariate point processes
Hansen, Niels Richard; Reynaud-Bouret, Patricia; Rivoirard, Vincent
2012-01-01
Due to its low computational cost, Lasso is an attractive regularization method for high-dimensional statistical settings. In this paper, we consider multivariate counting processes depending on an unknown function parameter to be estimated by linear combinations of a fixed dictionary. To select coefficients, we propose an adaptive $\\ell_{1}$-penalization methodology, where data-driven weights of the penalty are derived from new Bernstein type inequalities for martingales. Oracle inequalities...
Generating process model collections
Yan, Z.; Dijkman, R.M.; Grefen, P.W.P.J.
2017-01-01
Business process management plays an important role in the management of organizations. More and more organizations describe their operations as business processes. It is common for organizations to have collections of thousands of business processes, but for reasons of confidentiality these
What makes process models understandable?
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
Recent tests of the equilibrium-point hypothesis (lambda model).
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.
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
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
The Comparison of Point Data Models for the Output of WRF Hydro Model in the IDV
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.
Modeling molecular boiling points using computed interaction energies.
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.
Nuclear binding around the RP-process waiting points $^{68}$Se and $^{72}$Kr
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.
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
Third generation masses from a two Higgs model fixed point
International Nuclear Information System (INIS)
Froggatt, C.D.; Knowles, I.G.; Moorhouse, R.G.
1990-01-01
The large mass ratio between the top and bottom quarks may be attributed to a hierarchy in the vacuum expectation values of scalar doublets. We consider an effective renormalisation group fixed point determination of the quartic scalar and third generation Yukawa couplings in such a two doublet model. This predicts a mass m t =220 GeV and a mass ratio m b /m τ =2.6. In its simplest form the model also predicts the scalar masses, including a light scalar with a mass of order the b quark mass. Experimental implications are discussed. (orig.)
Piecewise deterministic processes in biological models
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...
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.
Neuroscientific Model of Motivational Process
Kim, Sung-il
2013-01-01
Considering the neuroscientific findings on reward, learning, value, decision-making, and cognitive control, motivation can be parsed into three sub processes, a process of generating motivation, a process of maintaining motivation, and a process of regulating motivation. I propose a tentative neuroscientific model of motivational processes which consists of three distinct but continuous sub processes, namely reward-driven approach, value-based decision-making, and goal-directed control. Rewa...
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)
Dissipative N-point-vortex Models in the Plane
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.
Nuclear structure and weak rates of heavy waiting point nuclei under rp-process conditions
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.
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.
a Modeling Method of Fluttering Leaves Based on Point Cloud
Tang, J.; Wang, Y.; Zhao, Y.; Hao, W.; Ning, X.; Lv, K.; Shi, Z.; Zhao, M.
2017-09-01
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 are the rotation falling, the roll falling and the screw roll falling. At the same time, a parallel algorithm based on OpenMP is implemented to satisfy the needs of real-time in practical applications. Experimental results demonstrate that the proposed method is amenable to the incorporation of a variety of desirable effects.
A MODELING METHOD OF FLUTTERING LEAVES BASED ON POINT CLOUD
Directory of Open Access Journals (Sweden)
J. Tang
2017-09-01
Full Text Available 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 are the rotation falling, the roll falling and the screw roll falling. At the same time, a parallel algorithm based on OpenMP is implemented to satisfy the needs of real-time in practical applications. Experimental results demonstrate that the proposed method is amenable to the incorporation of a variety of desirable effects.
A relativistic point coupling model for nuclear structure calculations
International Nuclear Information System (INIS)
Buervenich, T.; Maruhn, J.A.; Madland, D.G.; Reinhard, P.G.
2002-01-01
A relativistic point coupling model is discussed focusing on a variety of aspects. In addition to the coupling using various bilinear Dirac invariants, derivative terms are also included to simulate finite-range effects. The formalism is presented for nuclear structure calculations of ground state properties of nuclei in the Hartree and Hartree-Fock approximations. Different fitting strategies for the determination of the parameters have been applied and the quality of the fit obtainable in this model is discussed. The model is then compared more generally to other mean-field approaches both formally and in the context of applications to ground-state properties of known and superheavy nuclei. Perspectives for further extensions such as an exact treatment of the exchange terms using a higher-order Fierz transformation are discussed briefly. (author)
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 ...
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
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.
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.
Modeling of column apparatus processes
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.
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.
UML in business process modeling
Directory of Open Access Journals (Sweden)
Bartosz Marcinkowski
2013-03-01
Full Text Available Selection and proper application of business process modeling methods and techniques have a significant impact on organizational improvement capabilities as well as proper understanding of functionality of information systems that shall support activity of the organization. A number of business process modeling notations were popularized in practice in recent decades. Most significant of the notations include Business Process Modeling Notation (OMG BPMN and several Unified Modeling Language (OMG UML extensions. In this paper, the assessment whether one of the most flexible and strictly standardized contemporary business process modeling notations, i.e. Rational UML Profile for Business Modeling, enable business analysts to prepare business models that are all-embracing and understandable by all the stakeholders. After the introduction, methodology of research is discussed. Section 2 presents selected case study results. The paper is concluded with a summary.
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.
The Critical Point Entanglement and Chaos in the Dicke Model
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Lina Bao
2015-07-01
Full Text Available Ground state properties and level statistics of the Dicke model for a finite number of atoms are investigated based on a progressive diagonalization scheme (PDS. Particle number statistics, the entanglement measure and the Shannon information entropy at the resonance point in cases with a finite number of atoms as functions of the coupling parameter are calculated. It is shown that the entanglement measure defined in terms of the normalized von Neumann entropy of the reduced density matrix of the atoms reaches its maximum value at the critical point of the quantum phase transition where the system is most chaotic. Noticeable change in the Shannon information entropy near or at the critical point of the quantum phase transition is also observed. In addition, the quantum phase transition may be observed not only in the ground state mean photon number and the ground state atomic inversion as shown previously, but also in fluctuations of these two quantities in the ground state, especially in the atomic inversion fluctuation.
TARDEC FIXED HEEL POINT (FHP): DRIVER CAD ACCOMMODATION MODEL VERIFICATION REPORT
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
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.
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
Conceptual models of information processing
Stewart, L. J.
1983-01-01
The conceptual information processing issues are examined. Human information processing is defined as an active cognitive process that is analogous to a system. It is the flow and transformation of information within a human. The human is viewed as an active information seeker who is constantly receiving, processing, and acting upon the surrounding environmental stimuli. Human information processing models are conceptual representations of cognitive behaviors. Models of information processing are useful in representing the different theoretical positions and in attempting to define the limits and capabilities of human memory. It is concluded that an understanding of conceptual human information processing models and their applications to systems design leads to a better human factors approach.
A Thermodynamic Point of View on Dark Energy Models
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Vincenzo F. Cardone
2017-07-01
Full Text Available We present a conjugate analysis of two different dark energy models, namely the Barboza–Alcaniz parameterization and the phenomenologically-motivated Hobbit model, investigating both their agreement with observational data and their thermodynamical properties. We successfully fit a wide dataset including the Hubble diagram of Type Ia Supernovae, the Hubble rate expansion parameter as measured from cosmic chronometers, the baryon acoustic oscillations (BAO standard ruler data and the Planck distance priors. This analysis allows us to constrain the model parameters, thus pointing at the region of the wide parameters space, which is worth focusing on. As a novel step, we exploit the strong connection between gravity and thermodynamics to further check models’ viability by investigating their thermodynamical quantities. In particular, we study whether the cosmological scenario fulfills the generalized second law of thermodynamics, and moreover, we contrast the two models, asking whether the evolution of the total entropy is in agreement with the expectation for a closed system. As a general result, we discuss whether thermodynamic constraints can be a valid complementary way to both constrain dark energy models and differentiate among rival scenarios.
Two-point functions in a holographic Kondo model
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.
SALLY, Dynamic Behaviour of Reactor Cooling Channel by Point Model
International Nuclear Information System (INIS)
Reiche, Chr.; Ziegenbein, D.
1981-01-01
1 - Nature of the physical problem solved: The dynamical behaviour of a cooling channel is calculated. Starting from an equilibrium state a perturbation is introduced into the system. That may be an outer reactivity perturbation or a change in the coolant velocity or in the coolant temperature. The neutron kinetics is treated in the framework of the one-point model. The cooling channel consists of a cladded and cooled fuel rod. The temperature distribution is taken into account as an array above a mesh of radial zones and axial layers. Heat transfer is considered in radial direction only, the thermodynamical coupling of the different layers is obtained by the coolant flow. The thermal material parameters are considered to be temperature independent. Reactivity feedback is introduced by means of reactivity coefficients for fuel, canning, and coolant. Doppler broadening is included. The first cooling cycle can be taken into account by a simple model. 2 - Method of solution: The integration of the point kinetics equations is done numerically by the P11 scheme. The system of temperature equations with constant heat resistance coefficients is solved by the method of factorization. 3 - Restrictions on the complexity of the problem: Given limits are: 10 radial fuel zones, 25 axial layers, 6 groups of delayed neutrons
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.
Topobathymetric LiDAR point cloud processing and landform classification in a tidal environment
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
Using Pareto points for model identification in predictive toxicology
2013-01-01
Predictive toxicology is concerned with the development of models that are able to predict the toxicity of chemicals. A reliable prediction of toxic effects of chemicals in living systems is highly desirable in cosmetics, drug design or food protection to speed up the process of chemical compound discovery while reducing the need for lab tests. There is an extensive literature associated with the best practice of model generation and data integration but management and automated identification of relevant models from available collections of models is still an open problem. Currently, the decision on which model should be used for a new chemical compound is left to users. This paper intends to initiate the discussion on automated model identification. We present an algorithm, based on Pareto optimality, which mines model collections and identifies a model that offers a reliable prediction for a new chemical compound. The performance of this new approach is verified for two endpoints: IGC50 and LogP. The results show a great potential for automated model identification methods in predictive toxicology. PMID:23517649
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.
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 &.
DEFF Research Database (Denmark)
Andrade Santacoloma, Paloma de Gracia
are affected (in a positive or negative way) by the presence of the other enzymes and compounds in the media. In this thesis the concept of multi-enzyme in-pot term is adopted for processes that are carried out by the combination of enzymes in a single reactor and implemented at pilot or industrial scale...... features of the process and provides the information required to structure the process model by using a step-by-step procedure with the required tools and methods. In this way, this framework increases efficiency of the model development process with respect to time and resources needed (fast and effective....... In this way the model parameters that drives the main dynamic behavior can be identified and thus a better understanding of this type of processes. In order to develop, test and verify the methodology, three case studies were selected, specifically the bi-enzyme process for the production of lactobionic acid...
Sato Processes in Default Modeling
DEFF Research Database (Denmark)
Kokholm, Thomas; Nicolato, Elisa
-change of a homogeneous Levy process. While the processes in these two classes share the same average behavior over time, the associated intensities exhibit very different properties. Concrete specifications are calibrated to data on the single names included in the iTraxx Europe index. The performances are compared......In reduced form default models, the instantaneous default intensity is classically the modeling object. Survival probabilities are then given by the Laplace transform of the cumulative hazard defined as the integrated intensity process. Instead, recent literature has shown a tendency towards...... specifying the cumulative hazard process directly. Within this framework we present a new model class where cumulative hazards are described by self-similar additive processes, also known as Sato processes. Furthermore we also analyze specifications obtained via a simple deterministic time...
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.
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. .
A customizable stochastic state point process filter (SSPPF) for neural spiking activity.
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.
Defining the end-point of mastication: A conceptual model.
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
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.
MIDAS/PK code development using point kinetics model
International Nuclear Information System (INIS)
Song, Y. M.; Park, S. H.
1999-01-01
In this study, a MIDAS/PK code has been developed for analyzing the ATWS (Anticipated Transients Without Scram) which can be one of severe accident initiating events. The MIDAS is an integrated computer code based on the MELCOR code to develop a severe accident risk reduction strategy by Korea Atomic Energy Research Institute. In the mean time, the Chexal-Layman correlation in the current MELCOR, which was developed under a BWR condition, is appeared to be inappropriate for a PWR. So as to provide ATWS analysis capability to the MIDAS code, a point kinetics module, PKINETIC, has first been developed as a stand-alone code whose reference model was selected from the current accident analysis codes. In the next step, the MIDAS/PK code has been developed via coupling PKINETIC with the MIDAS code by inter-connecting several thermal hydraulic parameters between the two codes. Since the major concern in the ATWS analysis is the primary peak pressure during the early few minutes into the accident, the peak pressure from the PKINETIC module and the MIDAS/PK are compared with the RETRAN calculations showing a good agreement between them. The MIDAS/PK code is considered to be valuable for analyzing the plant response during ATWS deterministically, especially for the early domestic Westinghouse plants which rely on the operator procedure instead of an AMSAC (ATWS Mitigating System Actuation Circuitry) against ATWS. This capability of ATWS analysis is also important from the view point of accident management and mitigation
Modeling elephant-mediated cascading effects of water point closure.
Hilbers, Jelle P; Van Langevelde, Frank; Prins, Herbert H T; Grant, C C; Peel, Mike J S; Coughenour, Michael B; De Knegt, Henrik J; Slotow, Rob; Smit, Izak P J; Kiker, Greg A; De Boer, Willem F
2015-03-01
Wildlife management to reduce the impact of wildlife on their habitat can be done in several ways, among which removing animals (by either culling or translocation) is most often used. There are, however, alternative ways to control wildlife densities, such as opening or closing water points. The effects of these alternatives are poorly studied. In this paper, we focus on manipulating large herbivores through the closure of water points (WPs). Removal of artificial WPs has been suggested in order to change the distribution of African elephants, which occur in high densities in national parks in Southern Africa and are thought to have a destructive effect on the vegetation. Here, we modeled the long-term effects of different scenarios of WP closure on the spatial distribution of elephants, and consequential effects on the vegetation and other herbivores in Kruger National Park, South Africa. Using a dynamic ecosystem model, SAVANNA, scenarios were evaluated that varied in availability of artificial WPs; levels of natural water; and elephant densities. Our modeling results showed that elephants can indirectly negatively affect the distributions of meso-mixed feeders, meso-browsers, and some meso-grazers under wet conditions. The closure of artificial WPs hardly had any effect during these natural wet conditions. Under dry conditions, the spatial distribution of both elephant bulls and cows changed when the availability of artificial water was severely reduced in the model. These changes in spatial distribution triggered changes in the spatial availability of woody biomass over the simulation period of 80 years, and this led to changes in the rest of the herbivore community, resulting in increased densities of all herbivores, except for giraffe and steenbok, in areas close to rivers. The spatial distributions of elephant bulls and cows showed to be less affected by the closure of WPs than most of the other herbivore species. Our study contributes to ecologically
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
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.
Forecasting Macedonian Business Cycle Turning Points Using Qual Var Model
Directory of Open Access Journals (Sweden)
Petrovska Magdalena
2016-09-01
Full Text Available This paper aims at assessing the usefulness of leading indicators in business cycle research and forecast. Initially we test the predictive power of the economic sentiment indicator (ESI within a static probit model as a leading indicator, commonly perceived to be able to provide a reliable summary of the current economic conditions. We further proceed analyzing how well an extended set of indicators performs in forecasting turning points of the Macedonian business cycle by employing the Qual VAR approach of Dueker (2005. In continuation, we evaluate the quality of the selected indicators in pseudo-out-of-sample context. The results show that the use of survey-based indicators as a complement to macroeconomic data work satisfactory well in capturing the business cycle developments in Macedonia.
Markov Decision Process Measurement Model.
LaMar, Michelle M
2018-03-01
Within-task actions can provide additional information on student competencies but are challenging to model. This paper explores the potential of using a cognitive model for decision making, the Markov decision process, to provide a mapping between within-task actions and latent traits of interest. Psychometric properties of the model are explored, and simulation studies report on parameter recovery within the context of a simple strategy game. The model is then applied to empirical data from an educational game. Estimates from the model are found to correlate more strongly with posttest results than a partial-credit IRT model based on outcome data alone.
Bridging the gap between a stationary point process and its Palm distribution
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
Social Models: Blueprints or Processes?
Little, Graham R.
1981-01-01
Discusses the nature and implications of two different models for societal planning: (1) the problem-solving process approach based on Karl Popper; and (2) the goal-setting "blueprint" approach based on Karl Marx. (DC)
Simple Models for Process Control
Czech Academy of Sciences Publication Activity Database
Gorez, R.; Klán, Petr
2011-01-01
Roč. 22, č. 2 (2011), s. 58-62 ISSN 0929-2268 Institutional research plan: CEZ:AV0Z10300504 Keywords : process model s * PID control * second order dynamics Subject RIV: JB - Sensors, Measurment, Regulation
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)
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.
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
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
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.
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....
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.
Model feedstock supply processing plants
Directory of Open Access Journals (Sweden)
V. M. Bautin
2013-01-01
Full Text Available The model of raw providing the processing enterprises entering into vertically integrated structure on production and processing of dairy raw materials, differing by an orientation on achievement of cumulative effect by the integrated structure acting as criterion function which maximizing is reached by optimization of capacities, volumes of deliveries of raw materials and its qualitative characteristics, costs of industrial processing of raw materials and demand for dairy production is developed.
Sato Processes in Default Modeling
DEFF Research Database (Denmark)
Kokholm, Thomas; Nicolato, Elisa
2010-01-01
In reduced form default models, the instantaneous default intensity is the classical modeling object. Survival probabilities are then given by the Laplace transform of the cumulative hazard defined as the integrated intensity process. Instead, recent literature tends to specify the cumulative haz...
Sato Processes in Default Modeling
DEFF Research Database (Denmark)
Kokholm, Thomas; Nicolato, Elisa
In reduced form default models, the instantaneous default intensity is classically the modeling object. Survival probabilities are then given by the Laplace transform of the cumulative hazard defined as the integrated intensity process. Instead, recent literature has shown a tendency towards...
Computer Modelling of Dynamic Processes
Directory of Open Access Journals (Sweden)
B. Rybakin
2000-10-01
Full Text Available Results of numerical modeling of dynamic problems are summed in the article up. These problems are characteristic for various areas of human activity, in particular for problem solving in ecology. The following problems are considered in the present work: computer modeling of dynamic effects on elastic-plastic bodies, calculation and determination of performances of gas streams in gas cleaning equipment, modeling of biogas formation processes.
Modelling Hospital Materials Management Processes
Directory of Open Access Journals (Sweden)
Raffaele Iannone
2013-06-01
integrated and detailed analysis and description model for hospital materials management data and tasks, which is able to tackle information from patient requirements to usage, from replenishment requests to supplying and handling activities. The model takes account of medical risk reduction, traceability and streamlined processes perspectives. Second, the paper translates this information into a business process model and mathematical formalization.The study provides a useful guide to the various relevant technology‐related, management and business issues, laying the foundations of an efficient reengineering of the supply chain to reduce healthcare costs and improve the quality of care.
Declarative modeling for process supervision
International Nuclear Information System (INIS)
Leyval, L.
1989-01-01
Our work is a contribution to computer aided supervision of continuous processes. It is inspired by an area of Artificial Intelligence: qualitative physics. Here, supervision is based on a model which continuously provides operators with a synthetic view of the process; but this model is founded on general principles of control theory rather than on physics. It involves concepts such as high gain or small time response. It helps in linking temporally the evolution of various variables. Moreover, the model provides predictions of the future behaviour of the process, which allows action advice and alarm filtering. This should greatly reduce the famous cognitive overload associated to any complex and dangerous evolution of the process
A Monte Carlo-adjusted goodness-of-fit test for parametric models describing spatial point patterns
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
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.
Retort process modelling for Indian traditional foods.
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.
Atmospheric mercury dispersion modelling from two nearest hypothetical point sources
Energy Technology Data Exchange (ETDEWEB)
Al Razi, Khandakar Md Habib; Hiroshi, Moritomi; Shinji, Kambara [Environmental and Renewable Energy System (ERES), Graduate School of Engineering, Gifu University, Yanagido, Gifu City, 501-1193 (Japan)
2012-07-01
The Japan coastal areas are still environmentally friendly, though there are multiple air emission sources originating as a consequence of several developmental activities such as automobile industries, operation of thermal power plants, and mobile-source pollution. Mercury is known to be a potential air pollutant in the region apart from SOX, NOX, CO and Ozone. Mercury contamination in water bodies and other ecosystems due to deposition of atmospheric mercury is considered a serious environmental concern. Identification of sources contributing to the high atmospheric mercury levels will be useful for formulating pollution control and mitigation strategies in the region. In Japan, mercury and its compounds were categorized as hazardous air pollutants in 1996 and are on the list of 'Substances Requiring Priority Action' published by the Central Environmental Council of Japan. The Air Quality Management Division of the Environmental Bureau, Ministry of the Environment, Japan, selected the current annual mean environmental air quality standard for mercury and its compounds of 0.04 ?g/m3. Long-term exposure to mercury and its compounds can have a carcinogenic effect, inducing eg, Minamata disease. This study evaluates the impact of mercury emissions on air quality in the coastal area of Japan. Average yearly emission of mercury from an elevated point source in this area with background concentration and one-year meteorological data were used to predict the ground level concentration of mercury. To estimate the concentration of mercury and its compounds in air of the local area, two different simulation models have been used. The first is the National Institute of Advanced Science and Technology Atmospheric Dispersion Model for Exposure and Risk Assessment (AIST-ADMER) that estimates regional atmospheric concentration and distribution. The second is the Hybrid Single Particle Lagrangian Integrated trajectory Model (HYSPLIT) that estimates the atmospheric
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.
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 .
Two-point boundary correlation functions of dense loop models
Directory of Open Access Journals (Sweden)
Alexi Morin-Duchesne, Jesper Lykke Jacobsen
2018-06-01
Full Text Available We investigate six types of two-point boundary correlation functions in the dense loop model. These are defined as ratios $Z/Z^0$ of partition functions on the $m\\times n$ square lattice, with the boundary condition for $Z$ depending on two points $x$ and $y$. We consider: the insertion of an isolated defect (a and a pair of defects (b in a Dirichlet boundary condition, the transition (c between Dirichlet and Neumann boundary conditions, and the connectivity of clusters (d, loops (e and boundary segments (f in a Neumann boundary condition. For the model of critical dense polymers, corresponding to a vanishing loop weight ($\\beta = 0$, we find determinant and pfaffian expressions for these correlators. We extract the conformal weights of the underlying conformal fields and find $\\Delta = -\\frac18$, $0$, $-\\frac3{32}$, $\\frac38$, $1$, $\\tfrac \\theta \\pi (1+\\tfrac{2\\theta}\\pi$, where $\\theta$ encodes the weight of one class of loops for the correlator of type f. These results are obtained by analysing the asymptotics of the exact expressions, and by using the Cardy-Peschel formula in the case where $x$ and $y$ are set to the corners. For type b, we find a $\\log|x-y|$ dependence from the asymptotics, and a $\\ln (\\ln n$ term in the corner free energy. This is consistent with the interpretation of the boundary condition of type b as the insertion of a logarithmic field belonging to a rank two Jordan cell. For the other values of $\\beta = 2 \\cos \\lambda$, we use the hypothesis of conformal invariance to predict the conformal weights and find $\\Delta = \\Delta_{1,2}$, $\\Delta_{1,3}$, $\\Delta_{0,\\frac12}$, $\\Delta_{1,0}$, $\\Delta_{1,-1}$ and $\\Delta_{\\frac{2\\theta}\\lambda+1,\\frac{2\\theta}\\lambda+1}$, extending the results of critical dense polymers. With the results for type f, we reproduce a Coulomb gas prediction for the valence bond entanglement entropy of Jacobsen and Saleur.
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.
Demystifying the cytokine network: Mathematical models point the way.
Morel, Penelope A; Lee, Robin E C; Faeder, James R
2017-10-01
Cytokines provide the means by which immune cells communicate with each other and with parenchymal cells. There are over one hundred cytokines and many exist in families that share receptor components and signal transduction pathways, creating complex networks. Reductionist approaches to understanding the role of specific cytokines, through the use of gene-targeted mice, have revealed further complexity in the form of redundancy and pleiotropy in cytokine function. Creating an understanding of the complex interactions between cytokines and their target cells is challenging experimentally. Mathematical and computational modeling provides a robust set of tools by which complex interactions between cytokines can be studied and analyzed, in the process creating novel insights that can be further tested experimentally. This review will discuss and provide examples of the different modeling approaches that have been used to increase our understanding of cytokine networks. This includes discussion of knowledge-based and data-driven modeling approaches and the recent advance in single-cell analysis. The use of modeling to optimize cytokine-based therapies will also be discussed. Copyright © 2016 Elsevier Ltd. All rights reserved.
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....
A marked point process approach for identifying neural correlates of tics in Tourette Syndrome.
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.
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
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...
Supervised Outlier Detection in Large-Scale Mvs Point Clouds for 3d City Modeling Applications
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.
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...
Neuroscientific Model of Motivational Process
Kim, Sung-il
2013-01-01
Considering the neuroscientific findings on reward, learning, value, decision-making, and cognitive control, motivation can be parsed into three sub processes, a process of generating motivation, a process of maintaining motivation, and a process of regulating motivation. I propose a tentative neuroscientific model of motivational processes which consists of three distinct but continuous sub processes, namely reward-driven approach, value-based decision-making, and goal-directed control. Reward-driven approach is the process in which motivation is generated by reward anticipation and selective approach behaviors toward reward. This process recruits the ventral striatum (reward area) in which basic stimulus-action association is formed, and is classified as an automatic motivation to which relatively less attention is assigned. By contrast, value-based decision-making is the process of evaluating various outcomes of actions, learning through positive prediction error, and calculating the value continuously. The striatum and the orbitofrontal cortex (valuation area) play crucial roles in sustaining motivation. Lastly, the goal-directed control is the process of regulating motivation through cognitive control to achieve goals. This consciously controlled motivation is associated with higher-level cognitive functions such as planning, retaining the goal, monitoring the performance, and regulating action. The anterior cingulate cortex (attention area) and the dorsolateral prefrontal cortex (cognitive control area) are the main neural circuits related to regulation of motivation. These three sub processes interact with each other by sending reward prediction error signals through dopaminergic pathway from the striatum and to the prefrontal cortex. The neuroscientific model of motivational process suggests several educational implications with regard to the generation, maintenance, and regulation of motivation to learn in the learning environment. PMID:23459598
Neuroscientific model of motivational process.
Kim, Sung-Il
2013-01-01
Considering the neuroscientific findings on reward, learning, value, decision-making, and cognitive control, motivation can be parsed into three sub processes, a process of generating motivation, a process of maintaining motivation, and a process of regulating motivation. I propose a tentative neuroscientific model of motivational processes which consists of three distinct but continuous sub processes, namely reward-driven approach, value-based decision-making, and goal-directed control. Reward-driven approach is the process in which motivation is generated by reward anticipation and selective approach behaviors toward reward. This process recruits the ventral striatum (reward area) in which basic stimulus-action association is formed, and is classified as an automatic motivation to which relatively less attention is assigned. By contrast, value-based decision-making is the process of evaluating various outcomes of actions, learning through positive prediction error, and calculating the value continuously. The striatum and the orbitofrontal cortex (valuation area) play crucial roles in sustaining motivation. Lastly, the goal-directed control is the process of regulating motivation through cognitive control to achieve goals. This consciously controlled motivation is associated with higher-level cognitive functions such as planning, retaining the goal, monitoring the performance, and regulating action. The anterior cingulate cortex (attention area) and the dorsolateral prefrontal cortex (cognitive control area) are the main neural circuits related to regulation of motivation. These three sub processes interact with each other by sending reward prediction error signals through dopaminergic pathway from the striatum and to the prefrontal cortex. The neuroscientific model of motivational process suggests several educational implications with regard to the generation, maintenance, and regulation of motivation to learn in the learning environment.
Multiscale Modeling of Point and Line Defects in Cubic Lattices
National Research Council Canada - National Science Library
Chung, P. W; Clayton, J. D
2007-01-01
.... This multiscale theory explicitly captures heterogeneity in microscopic atomic motion in crystalline materials, attributed, for example, to the presence of various point and line lattice defects...
ECONOMIC MODELING PROCESSES USING MATLAB
Directory of Open Access Journals (Sweden)
Anamaria G. MACOVEI
2008-06-01
Full Text Available To study economic phenomena and processes using mathem atical modeling, and to determine the approximatesolution to a problem we need to choose a method of calculation and a numerical computer program, namely thepackage of programs MatLab. Any economic process or phenomenon is a mathematical description of h is behavior,and thus draw up an economic and mathematical model that has the following stages: formulation of the problem, theanalysis process modeling, the production model and design verification, validation and implementation of the model.This article is presented an economic model and its modeling is using mathematical equations and software packageMatLab, which helps us approximation effective solution. As data entry is considered the net cost, the cost of direct andtotal cost and the link between them. I presented the basic formula for determining the total cost. Economic modelcalculations were made in MatLab software package and with graphic representation of its interpretation of the resultsachieved in terms of our specific problem.
Path modeling and process control
DEFF Research Database (Denmark)
Høskuldsson, Agnar; Rodionova, O.; Pomerantsev, A.
2007-01-01
and having three or more stages. The methods are applied to a process control of a multi-stage production process having 25 variables and one output variable. When moving along the process, variables change their roles. It is shown how the methods of path modeling can be applied to estimate variables...... be performed regarding the foreseeable output property y, and with respect to an admissible range of correcting actions for the parameters of the next stage. In this paper the basic principles of path modeling is presented. The mathematics is presented for processes having only one stage, having two stages...... of the next stage with the purpose of obtaining optimal or almost optimal quality of the output variable. An important aspect of the methods presented is the possibility of extensive graphic analysis of data that can provide the engineer with a detailed view of the multi-variate variation in data....
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
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)
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)....
Process Models for Security Architectures
Directory of Open Access Journals (Sweden)
Floarea NASTASE
2006-01-01
Full Text Available This paper presents a model for an integrated security system, which can be implemented in any organization. It is based on security-specific standards and taxonomies as ISO 7498-2 and Common Criteria. The functionalities are derived from the classes proposed in the Common Criteria document. In the paper we present the process model for each functionality and also we focus on the specific components.
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
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
Apparatus and method for implementing power saving techniques when processing floating point values
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.
Kruse, Christian; Rottensteiner, Franz; Hoberg, Thorsten; Ziems, Marcel; Rebke, Julia; Heipke, Christian
2018-04-01
The aftermath of wartime attacks is often felt long after the war ended, as numerous unexploded bombs may still exist in the ground. Typically, such areas are documented in so-called impact maps which are based on the detection of bomb craters. This paper proposes a method for the automatic detection of bomb craters in aerial wartime images that were taken during the Second World War. The object model for the bomb craters is represented by ellipses. A probabilistic approach based on marked point processes determines the most likely configuration of objects within the scene. Adding and removing new objects to and from the current configuration, respectively, changing their positions and modifying the ellipse parameters randomly creates new object configurations. Each configuration is evaluated using an energy function. High gradient magnitudes along the border of the ellipse are favored and overlapping ellipses are penalized. Reversible Jump Markov Chain Monte Carlo sampling in combination with simulated annealing provides the global energy optimum, which describes the conformance with a predefined model. For generating the impact map a probability map is defined which is created from the automatic detections via kernel density estimation. By setting a threshold, areas around the detections are classified as contaminated or uncontaminated sites, respectively. Our results show the general potential of the method for the automatic detection of bomb craters and its automated generation of an impact map in a heterogeneous image stock.
A Generic Modeling Process to Support Functional Fault Model Development
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.
Mathematical modelling in economic processes.
Directory of Open Access Journals (Sweden)
L.V. Kravtsova
2008-06-01
Full Text Available In article are considered a number of methods of mathematical modelling of economic processes and opportunities of use of spreadsheets Excel for reception of the optimum decision of tasks or calculation of financial operations with the help of the built-in functions.
Visualizing the process of process modeling with PPMCharts
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
Neuroscientific Model of Motivational Process
Directory of Open Access Journals (Sweden)
Sung-Il eKim
2013-03-01
Full Text Available Considering the neuroscientific findings on reward, learning, value, decision-making, and cognitive control, motivation can be parsed into three subprocesses, a process of generating motivation, a process of maintaining motivation, and a process of regulating motivation. I propose a tentative neuroscientific model of motivational processes which consists of three distinct but continuous subprocesses, namely reward-driven approach, value-based decision making, and goal-directed control. Reward-driven approach is the process in which motivation is generated by reward anticipation and selective approach behaviors toward reward. This process recruits the ventral striatum (reward area in which basic stimulus-action association is formed, and is classified as an automatic motivation to which relatively less attention is assigned. By contrast, value-based decision making is the process of evaluating various outcomes of actions, learning through positive prediction error, and calculating the value continuously. The striatum and the orbitofrontal cortex (valuation area play crucial roles in sustaining motivation. Lastly, the goal-directed control is the process of regulating motivation through cognitive control to achieve goals. This consciously controlled motivation is associated with higher-level cognitive functions such as planning, retaining the goal, monitoring the performance, and regulating action. The anterior cingulate cortex (attention area and the dorsolateral prefrontal cortex (cognitive control area are the main neural circuits related to regulation of motivation. These three subprocesses interact with each other by sending reward prediction error signals through dopaminergic pathway from the striatum and to the prefrontal cortex. The neuroscientific model of motivational process suggests several educational implications with regard to the generation, maintenance, and regulation of motivation to learn in the learning environment.
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)
HYDROLOGY AND SEDIMENT MODELING USING THE BASINS NON-POINT SOURCE MODEL
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...
Integrated Site Model Process Model Report
International Nuclear Information System (INIS)
Booth, T.
2000-01-01
The Integrated Site Model (ISM) provides a framework for discussing the geologic features and properties of Yucca Mountain, which is being evaluated as a potential site for a geologic repository for the disposal of nuclear waste. The ISM is important to the evaluation of the site because it provides 3-D portrayals of site geologic, rock property, and mineralogic characteristics and their spatial variabilities. The ISM is not a single discrete model; rather, it is a set of static representations that provide three-dimensional (3-D), computer representations of site geology, selected hydrologic and rock properties, and mineralogic-characteristics data. These representations are manifested in three separate model components of the ISM: the Geologic Framework Model (GFM), the Rock Properties Model (RPM), and the Mineralogic Model (MM). The GFM provides a representation of the 3-D stratigraphy and geologic structure. Based on the framework provided by the GFM, the RPM and MM provide spatial simulations of the rock and hydrologic properties, and mineralogy, respectively. Functional summaries of the component models and their respective output are provided in Section 1.4. Each of the component models of the ISM considers different specific aspects of the site geologic setting. Each model was developed using unique methodologies and inputs, and the determination of the modeled units for each of the components is dependent on the requirements of that component. Therefore, while the ISM represents the integration of the rock properties and mineralogy into a geologic framework, the discussion of ISM construction and results is most appropriately presented in terms of the three separate components. This Process Model Report (PMR) summarizes the individual component models of the ISM (the GFM, RPM, and MM) and describes how the three components are constructed and combined to form the ISM
Temperature distribution model for the semiconductor dew point detector
Weremczuk, Jerzy; Gniazdowski, Z.; Jachowicz, Ryszard; Lysko, Jan M.
2001-08-01
The simulation results of temperature distribution in the new type silicon dew point detector are presented in this paper. Calculations were done with use of the SMACEF simulation program. Fabricated structures, apart from the impedance detector used to the dew point detection, contained the resistive four terminal thermometer and two heaters. Two detector structures, the first one located on the silicon membrane and the second one placed on the bulk materials were compared in this paper.
Hazard analysis and critical control point (HACCP) for an ultrasound food processing operation.
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.
The application of prototype point processes for the summary and description of California wildfires
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.
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.)
Investigating the Process of Process Modeling with Eye Movement Analysis
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...
Welding process modelling and control
Romine, Peter L.; Adenwala, Jinen A.
1993-01-01
The research and analysis performed, and software developed, and hardware/software recommendations made during 1992 in development of the PC-based data acquisition system for support of Welding Process Modeling and Control is reported. A need was identified by the Metals Processing Branch of NASA Marshall Space Flight Center, for a mobile data aquisition and analysis system, customized for welding measurement and calibration. Several hardware configurations were evaluated and a PC-based system was chosen. The Welding Measurement System (WMS) is a dedicated instrument, strictly for the use of data aquisition and analysis. Although the WMS supports many of the functions associated with the process control, it is not the intention for this system to be used for welding process control.
Point, surface and volumetric heat sources in the thermal modelling of selective laser melting
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.
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....
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
Efficient LIDAR Point Cloud Data Managing and Processing in a Hadoop-Based Distributed Framework
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.
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
Advanced oxidation processes: overall models
Energy Technology Data Exchange (ETDEWEB)
Rodriguez, M. [Univ. de los Andes, Escuela Basica de Ingenieria, La Hechicera, Merida (Venezuela); Curco, D.; Addardak, A.; Gimenez, J.; Esplugas, S. [Dept. de Ingenieria Quimica. Univ. de Barcelona, Barcelona (Spain)
2003-07-01
Modelling AOPs implies to consider all the steps included in the process, that means, mass transfer, kinetic (reaction) and luminic steps. In this way, recent works develop models which relate the global reaction rate to catalyst concentration and radiation absorption. However, the application of such models requires to know what is the controlling step for the overall process. In this paper, a simple method is explained which allows to determine the controlling step. Thus, it is assumed that reactor is divided in two hypothetical zones (dark and illuminated), and according to the experimental results, obtained by varying only the reaction volume, it can be decided if reaction occurs only in the illuminated zone or in the all reactor, including dark zone. The photocatalytic degradation of phenol, by using titania degussa P-25 as catalyst, is studied as reaction model. The preliminary results obtained are presented here, showing that it seems that, in this case, reaction only occurs in the illuminated zone of photoreactor. A model is developed to explain this behaviour. (orig.)
Model for amorphous aggregation processes
Stranks, Samuel D.; Ecroyd, Heath; van Sluyter, Steven; Waters, Elizabeth J.; Carver, John A.; von Smekal, Lorenz
2009-11-01
The amorphous aggregation of proteins is associated with many phenomena, ranging from the formation of protein wine haze to the development of cataract in the eye lens and the precipitation of recombinant proteins during their expression and purification. While much literature exists describing models for linear protein aggregation, such as amyloid fibril formation, there are few reports of models which address amorphous aggregation. Here, we propose a model to describe the amorphous aggregation of proteins which is also more widely applicable to other situations where a similar process occurs, such as in the formation of colloids and nanoclusters. As first applications of the model, we have tested it against experimental turbidimetry data of three proteins relevant to the wine industry and biochemistry, namely, thaumatin, a thaumatinlike protein, and α -lactalbumin. The model is very robust and describes amorphous experimental data to a high degree of accuracy. Details about the aggregation process, such as shape parameters of the aggregates and rate constants, can also be extracted.
A New Blind Pointing Model Improves Large Reflector Antennas Precision Pointing at Ka-Band (32 GHz)
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).
Digital analyzer for point processes based on first-in-first-out memories
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.
AKaplan-Meier estimators of distance distributions for spatial point processes
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
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
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...
A Systematic Approach to Process Evaluation in the Central Oklahoma Turning Point (COTP) Partnership
Tolma, Eleni L.; Cheney, Marshall K.; Chrislip, David D.; Blankenship, Derek; Troup, Pam; Hann, Neil
2011-01-01
Formation is an important stage of partnership development. Purpose: To describe the systematic approach to process evaluation of a Turning Point initiative in central Oklahoma during the formation stage. The nine-month collaborative effort aimed to develop an action plan to promote health. Methods: A sound planning framework was used in the…
Business models & business cases for point-of-care testing
Staring, A.J.; Meertens, L. O.; Sikkel, N.
2016-01-01
Point-Of-Care Testing (POCT) enables clinical tests at or near the patient, with test results that are available instantly or in a very short time frame, to assist caregivers with immediate diagnosis and/or clinical intervention. The goal of POCT is to provide accurate, reliable, fast, and
Modeling elephant-mediated cascading effects of water point closure
Hilbers, J.P.; Langevelde, van F.; Prins, H.H.T.; Grant, C.C.; Peel, M.; Coughenour, M.B.; Knegt, de H.J.; Slotow, R.; Smit, I.; Kiker, G.A.; Boer, de W.F.
2015-01-01
Wildlife management to reduce the impact of wildlife on their habitat can be done in several ways, among which removing animals (by either culling or translocation) is most often used. There are however alternative ways to control wildlife densities, such as opening or closing water points. The
Probabilistic evaluation of process model matching techniques
Kuss, Elena; Leopold, Henrik; van der Aa, Han; Stuckenschmidt, Heiner; Reijers, Hajo A.
2016-01-01
Process model matching refers to the automatic identification of corresponding activities between two process models. It represents the basis for many advanced process model analysis techniques such as the identification of similar process parts or process model search. A central problem is how to
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
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)
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.
DEFF Research Database (Denmark)
Bey, Niki
2000-01-01
to three essential assessment steps, the method enables rough environmental evaluations and supports in this way material- and process-related decision-making in the early stages of design. In its overall structure, the Oil Point Method is related to Life Cycle Assessment - except for two main differences...... of environmental evaluation and only approximate information about the product and its life cycle. This dissertation addresses this challenge in presenting a method, which is tailored to these requirements of designers - the Oil Point Method (OPM). In providing environmental key information and confining itself...
Model uncertainty from a regulatory point of view
International Nuclear Information System (INIS)
Abramson, L.R.
1994-01-01
This paper discusses model uncertainty in the larger context of knowledge and random uncertainty. It explores some regulatory implications of model uncertainty and argues that, from a regulator's perspective, a conservative approach must be taken. As a consequence of this perspective, averaging over model results is ruled out
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.
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
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...
Bayesian analysis of spatial point processes in the neighbourhood of Voronoi networks
DEFF Research Database (Denmark)
Skare, Øivind; Møller, Jesper; Jensen, Eva Bjørn Vedel
2007-01-01
A model for an inhomogeneous Poisson process with high intensity near the edges of a Voronoi tessellation in 2D or 3D is proposed. The model is analysed in a Bayesian setting with priors on nuclei of the Voronoi tessellation and other model parameters. An MCMC algorithm is constructed to sample...
Bayesian analysis of spatial point processes in the neighbourhood of Voronoi networks
DEFF Research Database (Denmark)
Skare, Øivind; Møller, Jesper; Vedel Jensen, Eva B.
A model for an inhomogeneous Poisson process with high intensity near the edges of a Voronoi tessellation in 2D or 3D is proposed. The model is analysed in a Bayesian setting with priors on nuclei of the Voronoi tessellation and other model parameters. An MCMC algorithm is constructed to sample...
Mathematical modeling of biological processes
Friedman, Avner
2014-01-01
This book on mathematical modeling of biological processes includes a wide selection of biological topics that demonstrate the power of mathematics and computational codes in setting up biological processes with a rigorous and predictive framework. Topics include: enzyme dynamics, spread of disease, harvesting bacteria, competition among live species, neuronal oscillations, transport of neurofilaments in axon, cancer and cancer therapy, and granulomas. Complete with a description of the biological background and biological question that requires the use of mathematics, this book is developed for graduate students and advanced undergraduate students with only basic knowledge of ordinary differential equations and partial differential equations; background in biology is not required. Students will gain knowledge on how to program with MATLAB without previous programming experience and how to use codes in order to test biological hypothesis.
Modeling pellet impact drilling process
Kovalyov, A. V.; Ryabchikov, S. Ya; Isaev, Ye D.; Ulyanova, O. S.
2016-03-01
The paper describes pellet impact drilling which could be used to increase the drilling speed and the rate of penetration when drilling hard rocks. Pellet impact drilling implies rock destruction by metal pellets with high kinetic energy in the immediate vicinity of the earth formation encountered. The pellets are circulated in the bottom hole by a high velocity fluid jet, which is the principle component of the ejector pellet impact drill bit. The experiments conducted has allowed modeling the process of pellet impact drilling, which creates the scientific and methodological basis for engineering design of drilling operations under different geo-technical conditions.
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.
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.
AUTOMATED CALIBRATION OF FEM MODELS USING LIDAR POINT CLOUDS
Directory of Open Access Journals (Sweden)
B. Riveiro
2018-05-01
Full Text Available In present work it is pretended to estimate elastic parameters of beams through the combined use of precision geomatic techniques (laser scanning and structural behaviour simulation tools. The study has two aims, on the one hand, to develop an algorithm able to interpret automatically point clouds acquired by laser scanning systems of beams subjected to different load situations on experimental tests; and on the other hand, to minimize differences between deformation values given by simulation tools and those measured by laser scanning. In this way we will proceed to identify elastic parameters and boundary conditions of structural element so that surface stresses can be estimated more easily.
Performance Analysis of Several GPS/Galileo Precise Point Positioning Models.
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.
Time Series ARIMA Models of Undergraduate Grade Point Average.
Rogers, Bruce G.
The Auto-Regressive Integrated Moving Average (ARIMA) Models, often referred to as Box-Jenkins models, are regression methods for analyzing sequential dependent observations with large amounts of data. The Box-Jenkins approach, a three-stage procedure consisting of identification, estimation and diagnosis, was used to select the most appropriate…
Integrated modelling in materials and process technology
DEFF Research Database (Denmark)
Hattel, Jesper Henri
2008-01-01
Integrated modelling of entire process sequences and the subsequent in-service conditions, and multiphysics modelling of the single process steps are areas that increasingly support optimisation of manufactured parts. In the present paper, three different examples of modelling manufacturing...... processes from the viewpoint of combined materials and process modelling are presented: solidification of thin walled ductile cast iron, integrated modelling of spray forming and multiphysics modelling of friction stir welding. The fourth example describes integrated modelling applied to a failure analysis...
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.)
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.
Point process analyses of variations in smoking rate by setting, mood, gender, and dependence
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
Comments on: Spatiotemporal models for skewed processes
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.
Comments on: Spatiotemporal models for skewed processes
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.
Collapse models and perceptual processes
International Nuclear Information System (INIS)
Ghirardi, Gian Carlo; Romano, Raffaele
2014-01-01
Theories including a collapse mechanism have been presented various years ago. They are based on a modification of standard quantum mechanics in which nonlinear and stochastic terms are added to the evolution equation. Their principal merits derive from the fact that they are mathematically precise schemes accounting, on the basis of a unique universal dynamical principle, both for the quantum behavior of microscopic systems as well as for the reduction associated to measurement processes and for the classical behavior of macroscopic objects. Since such theories qualify themselves not as new interpretations but as modifications of the standard theory they can be, in principle, tested against quantum mechanics. Recently, various investigations identifying possible crucial test have been discussed. In spite of the extreme difficulty to perform such tests it seems that recent technological developments allow at least to put precise limits on the parameters characterizing the modifications of the evolution equation. Here we will simply mention some of the recent investigations in this direction, while we will mainly concentrate our attention to the way in which collapse theories account for definite perceptual process. The differences between the case of reductions induced by perceptions and those related to measurement procedures by means of standard macroscopic devices will be discussed. On this basis, we suggest a precise experimental test of collapse theories involving conscious observers. We make plausible, by discussing in detail a toy model, that the modified dynamics can give rise to quite small but systematic errors in the visual perceptual process.
Hillslope runoff processes and models
Kirkby, Mike
1988-07-01
Hillslope hydrology is concerned with the partition of precipitation as it passes through the vegetation and soil between overland flow and subsurface flow. Flow follows routes which attenuate and delay the flow to different extents, so that a knowledge of the relevant mechanisms is important. In the 1960s and 1970s, hillslope hydrology developed as a distinct topic through the application of new field observations to develop a generation of physically based forecasting models. In its short history, theory has continually been overturned by field observation. Thus the current tendency, particularly among temperate zone hydrologists, to dismiss all Hortonian overland flow as a myth, is now being corrected by a number of significant field studies which reveal the great range in both climatic and hillslope conditions. Some recent models have generally attempted to simplify the processes acting, for example including only vertical unsaturated flow and lateral saturated flows. Others explicitly forecast partial or contributing areas. With hindsight, the most complete and distributed models have generally shown little forecasting advantage over simpler approaches, perhaps trending towards reliable models which can run on desk top microcomputers. The variety now being recognised in hillslope hydrological responses should also lead to models which take account of more complex interactions, even if initially with a less secure physical and mathematical basis than the Richards equation. In particular, there is a need to respond to the variety of climatic responses, and to spatial variability on and beneath the surface, including the role of seepage macropores and pipes which call into question whether the hillside can be treated as a Darcian flow system.
Sand Point, Alaska MHW Coastal Digital Elevation Model
National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Geophysical Data Center (NGDC) is building high-resolution digital elevation models (DEMs) for select U.S. coastal regions. These integrated...
Business Process Modelling for Measuring Quality
Heidari, F.; Loucopoulos, P.; Brazier, F.M.
2013-01-01
Business process modelling languages facilitate presentation, communication and analysis of business processes with different stakeholders. This paper proposes an approach that drives specification and measurement of quality requirements and in doing so relies on business process models as
Lyapunov functions for the fixed points of the Lorenz model
International Nuclear Information System (INIS)
Bakasov, A.A.; Govorkov, B.B. Jr.
1992-11-01
We have shown how the explicit Lyapunov functions can be constructed in the framework of a regular procedure suggested and completed by Lyapunov a century ago (''method of critical cases''). The method completely covers all practically encountering subtle cases of stability study for ordinary differential equations when the linear stability analysis fails. These subtle cases, ''the critical cases'', according to Lyapunov, include both bifurcations of solutions and solutions of systems with symmetry. Being properly specialized and actually powerful in case of ODE's, this Lyapunov's method is formulated in simple language and should attract a wide interest of the physical audience. The method leads to inevitable construction of the explicit Lyapunov function, takes automatically into account the Fredholm alternative and avoids infinite step calculations. Easy and apparent physical interpretation of the Lyapunov function as a potential or as a time-dependent entropy provides one with more details about the local dynamics of the system at non-equilibrium phase transition points. Another advantage is that this Lyapunov's method consists of a set of very detailed explicit prescriptions which allow one to easy programmize the method for a symbolic processor. The application of the Lyapunov theory for critical cases has been done in this work to the real Lorenz equations and it is shown, in particular, that increasing σ at the Hopf bifurcation point suppresses the contribution of one of the variables to the destabilization of the system. The relation of the method to contemporary methods and its place among them have been clearly and extensively discussed. Due to Appendices, the paper is self-contained and does not require from a reader to approach results published only in Russian. (author). 38 refs
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.
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.
Modeling Dynamic Regulatory Processes in Stroke
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
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.
Second-order analysis of inhomogeneous spatial point processes with proportional intensity functions
DEFF Research Database (Denmark)
Guan, Yongtao; Waagepetersen, Rasmus; Beale, Colin M.
2008-01-01
of the intensity functions. The first approach is based on nonparametric kernel-smoothing, whereas the second approach uses a conditional likelihood estimation approach to fit a parametric model for the pair correlation function. A great advantage of the proposed methods is that they do not require the often...... to two spatial point patterns regarding the spatial distributions of birds in the U.K.'s Peak District in 1990 and 2004....
The environmental zero-point problem in evolutionary reaction norm modeling.
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.
RANS-VOF modelling of the Wavestar point absorber
DEFF Research Database (Denmark)
Ransley, E. J.; Greaves, D. M.; Raby, A.
2017-01-01
Highlights •A fully nonlinear, coupled model of the Wavestar WEC has been created using open-source CFD software, OpenFOAM®. •The response of the Wavestar WEC is simulated in regular waves with different steepness. •Predictions of body motion, surface elevation, fluid velocity, pressure and load ...
Cubature/ Unscented/ Sigma Point Kalman Filtering with Angular Measurement Models
2015-07-06
similarly transformed to work with the Laplace distribution. Cubature formulae for w(x) = 1 over regions of various shapes could be used for evaluating...measurement and process non- linearities, such as the cubature Kalman filter, can perform ex- tremely poorly in many applications involving angular...in the form of the “unscented transform ”) consider just converting such measurements into Cartesian coordinates and feeding the converted measurements
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
Parallel Processing of Big Point Clouds Using Z-Order Partitioning
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
Developing a Business Intelligence Process for a Training Module in SharePoint 2010
Schmidtchen, Bryce; Solano, Wanda M.; Albasini, Colby
2015-01-01
Prior to this project, training information for the employees of the National Center for Critical Processing and Storage (NCCIPS) was stored in an array of unrelated spreadsheets and SharePoint lists that had to be manually updated. By developing a content management system through a web application platform named SharePoint, this training system is now highly automated and provides a much less intensive method of storing training data and scheduling training courses. This system was developed by using SharePoint Designer and laying out the data structure for the interaction between different lists of data about the employees. The automation of data population inside of the lists was accomplished by implementing SharePoint workflows which essentially lay out the logic for how data is connected and calculated between certain lists. The resulting training system is constructed from a combination of five lists of data with a single list acting as the user-friendly interface. This interface is populated with the courses required for each employee and includes past and future information about course requirements. The employees of NCCIPS now have the ability to view, log, and schedule their training information and courses with much more ease. This system will relieve a significant amount of manual input and serve as a powerful informational resource for the employees of NCCIPS in the future.
Modeling non-point source pollutants in the vadose zone: Back to the basics
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
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.
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...
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.
Numerical Modeling of a Wave Energy Point Absorber
DEFF Research Database (Denmark)
Hernandez, Lorenzo Banos; Frigaard, Peter; Kirkegaard, Poul Henning
2009-01-01
The present study deals with numerical modelling of the Wave Star Energy WSE device. Hereby, linear potential theory is applied via a BEM code on the wave hydrodynamics exciting the floaters. Time and frequency domain solutions of the floater response are determined for regular and irregular seas....... Furthermore, these results are used to estimate the power and the energy absorbed by a single oscillating floater. Finally, a latching control strategy is analysed in open-loop configuration for energy maximization....
Numerical schemes for one-point closure turbulence models
International Nuclear Information System (INIS)
Larcher, Aurelien
2010-01-01
First-order Reynolds Averaged Navier-Stokes (RANS) turbulence models are studied in this thesis. These latter consist of the Navier-Stokes equations, supplemented with a system of balance equations describing the evolution of characteristic scalar quantities called 'turbulent scales'. In so doing, the contribution of the turbulent agitation to the momentum can be determined by adding a diffusive coefficient (called 'turbulent viscosity') in the Navier-Stokes equations, such that it is defined as a function of the turbulent scales. The numerical analysis problems, which are studied in this dissertation, are treated in the frame of a fractional step algorithm, consisting of an approximation on regular meshes of the Navier-Stokes equations by the nonconforming Crouzeix-Raviart finite elements, and a set of scalar convection-diffusion balance equations discretized by the standard finite volume method. A monotone numerical scheme based on the standard finite volume method is proposed so as to ensure that the turbulent scales, like the turbulent kinetic energy (k) and its dissipation rate (ε), remain positive in the case of the standard k - ε model, as well as the k - ε RNG and the extended k - ε - ν 2 models. The convergence of the proposed numerical scheme is then studied on a system composed of the incompressible Stokes equations and a steady convection-diffusion equation, which are both coupled by the viscosities and the turbulent production term. This reduced model allows to deal with the main difficulty encountered in the analysis of such problems: the definition of the turbulent production term leads to consider a class of convection-diffusion problems with an irregular right-hand side belonging to L 1 . Finally, to step towards the unsteady problem, the convergence of the finite volume scheme for a model convection-diffusion equation with L 1 data is proved. The a priori estimates on the solution and on its time derivative are obtained in discrete norms, for
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.
Citraresmi, A. D. P.; Wahyuni, E. E.
2018-03-01
The aim of this study was to inspect the implementation of Hazard Analysis and Critical Control Point (HACCP) for identification and prevention of potential hazards in the production process of dried anchovy at PT. Kelola Mina Laut (KML), Lobuk unit, Sumenep. Cold storage process is needed in each anchovy processing step in order to maintain its physical and chemical condition. In addition, the implementation of quality assurance system should be undertaken to maintain product quality. The research was conducted using a survey method, by following the whole process of making anchovy from the receiving raw materials to the packaging of final product. The method of data analysis used was descriptive analysis method. Implementation of HACCP at PT. KML, Lobuk unit, Sumenep was conducted by applying Pre Requisite Programs (PRP) and preparation stage consisting of 5 initial stages and 7 principles of HACCP. The results showed that CCP was found in boiling process flow with significant hazard of Listeria monocytogenesis bacteria and final sorting process with significant hazard of foreign material contamination in the product. Actions taken were controlling boiling temperature of 100 – 105°C for 3 - 5 minutes and training for sorting process employees.
Geographical point cloud modelling with the 3D medial axis transform
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,
Directory of Open Access Journals (Sweden)
Saidi Badreddine
2016-01-01
Full Text Available The single point incremental forming process is well-known to be perfectly suited for prototyping and small series. One of its fields of applicability is the medicine area for the forming of titanium prostheses or titanium medical implants. However this process is not yet very industrialized, mainly due its geometrical inaccuracy, its not homogeneous thickness distribution& Moreover considerable forces can occur. They must be controlled in order to preserve the tooling. In this paper, a numerical approach is proposed in order to minimize the maximum force achieved during the incremental forming of titanium sheets and to maximize the minimal thickness. A surface response methodology is used to find the optimal values of two input parameters of the process, the punch diameter and the vertical step size of the tool path.
Developing engineering processes through integrated modelling of product and process
DEFF Research Database (Denmark)
Nielsen, Jeppe Bjerrum; Hvam, Lars
2012-01-01
This article aims at developing an operational tool for integrated modelling of product assortments and engineering processes in companies making customer specific products. Integrating a product model in the design of engineering processes will provide a deeper understanding of the engineering...... activities as well as insight into how product features affect the engineering processes. The article suggests possible ways of integrating models of products with models of engineering processes. The models have been tested and further developed in an action research study carried out in collaboration...... with a major international engineering company....
Automatic extraction of process categories from process model collections
Malinova, M.; Dijkman, R.M.; Mendling, J.; Lohmann, N.; Song, M.; Wohed, P.
2014-01-01
Many organizations build up their business process management activities in an incremental way. As a result, there is no overarching structure defined at the beginning. However, as business process modeling initiatives often yield hundreds to thousands of process models, there is a growing need for
Quality control for electron beam processing of polymeric materials by end-point analysis
International Nuclear Information System (INIS)
DeGraff, E.; McLaughlin, W.L.
1981-01-01
Properties of certain plastics, e.g. polytetrafluoroethylene, polyethylene, ethylene vinyl acetate copolymer, can be modified selectively by ionizing radiation. One of the advantages of this treatment over chemical methods is better control of the process and the end-product properties. The most convenient method of dosimetry for monitoring quality control is post-irradiation evaluation of the plastic itself, e.g., melt index and melt point determination. It is shown that by proper calibration in terms of total dose and sufficiently reproducible radiation effects, such product test methods provide convenient and meaningful analyses. Other appropriate standardized analytical methods include stress-crack resistance, stress-strain-to-fracture testing and solubility determination. Standard routine dosimetry over the dose and dose rate ranges of interest confirm that measured product end points can be correlated with calibrated values of absorbed dose in the product within uncertainty limits of the measurements. (author)
A Massless-Point-Charge Model for the Electron
Directory of Open Access Journals (Sweden)
Daywitt W. C.
2010-04-01
Full Text Available “It is rather remarkable that the modern concept of electrodynamics is not quite 100 years old and yet still does not rest firmly upon uniformly accepted theoretical foun- dations. Maxwell’s theory of the electromagnetic field is firmly ensconced in modern physics, to be sure, but the details of how charged particles are to be coupled to this field remain somewhat uncertain, despite the enormous advances in quantum electrody- namics over the past 45 years. Our theories remain mathematically ill-posed and mired in conceptual ambiguities which quantum mechanics has only moved to another arena rather than resolve. Fundamentally, we still do not understand just what is a charged particle” [1, p.367]. As a partial answer to the preceeding quote, this paper presents a new model for the electron that combines the seminal work of Puthoff [2] with the theory of the Planck vacuum (PV [3], the basic idea for the model following from [2] with the PV theory adding some important details.
A Massless-Point-Charge Model for the Electron
Directory of Open Access Journals (Sweden)
Daywitt W. C.
2010-04-01
Full Text Available "It is rather remarkable that the modern concept of electrodynamics is not quite 100 years old and yet still does not rest firmly upon uniformly accepted theoretical foundations. Maxwell's theory of the electromagnetic field is firmly ensconced in modern physics, to be sure, but the details of how charged particles are to be coupled to this field remain somewhat uncertain, despite the enormous advances in quantum electrodynamics over the past 45 years. Our theories remain mathematically ill-posed and mired in conceptual ambiguities which quantum mechanics has only moved to another arena rather than resolve. Fundamentally, we still do not understand just what is a charged particle" (Grandy W.T. Jr. Relativistic quantum mechanics of leptons and fields. Kluwer Academic Publishers, Dordrecht-London, 1991, p.367. As a partial answer to the preceeding quote, this paper presents a new model for the electron that combines the seminal work of Puthoff with the theory of the Planck vacuum (PV, the basic idea for the model following from Puthoff with the PV theory adding some important details.
Dimensional modeling: beyond data processing constraints.
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
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
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.
Unemployment estimation: Spatial point referenced methods and models
Pereira, Soraia
2017-06-26
Portuguese Labor force survey, from 4th quarter of 2014 onwards, started geo-referencing the sampling units, namely the dwellings in which the surveys are carried. This opens new possibilities in analysing and estimating unemployment and its spatial distribution across any region. The labor force survey choose, according to an preestablished sampling criteria, a certain number of dwellings across the nation and survey the number of unemployed in these dwellings. Based on this survey, the National Statistical Institute of Portugal presently uses direct estimation methods to estimate the national unemployment figures. Recently, there has been increased interest in estimating these figures in smaller areas. Direct estimation methods, due to reduced sampling sizes in small areas, tend to produce fairly large sampling variations therefore model based methods, which tend to
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
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
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
Clusterless Decoding of Position From Multiunit Activity Using A Marked Point Process Filter
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
Process mining using BPMN: relating event logs and process models
Kalenkova, A.A.; van der Aalst, W.M.P.; Lomazova, I.A.; Rubin, V.A.
2017-01-01
Process-aware information systems (PAIS) are systems relying on processes, which involve human and software resources to achieve concrete goals. There is a need to develop approaches for modeling, analysis, improvement and monitoring processes within PAIS. These approaches include process mining
Process mining using BPMN : relating event logs and process models
Kalenkova, A.A.; Aalst, van der W.M.P.; Lomazova, I.A.; Rubin, V.A.
2015-01-01
Process-aware information systems (PAIS) are systems relying on processes, which involve human and software resources to achieve concrete goals. There is a need to develop approaches for modeling, analysis, improvement and monitoring processes within PAIS. These approaches include process mining
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.
On the estimation of the spherical contact distribution Hs(y) for spatial point processes
International Nuclear Information System (INIS)
Doguwa, S.I.
1990-08-01
RIPLEY (1977, Journal of the Royal Statistical Society, B39 172-212) proposed an estimator for the spherical contact distribution H s (s), of a spatial point process observed in a bounded planar region. However, this estimator is not defined for some distances of interest, in this bounded region. A new estimator for H s (y), is proposed for use with regular grid of sampling locations. This new estimator is defined for all distances of interest. It also appears to have a smaller bias and a smaller mean squared error than the previously suggested alternative. (author). 11 refs, 4 figs, 1 tab
Multiphysics modelling of manufacturing processes: A review
DEFF Research Database (Denmark)
Jabbari, Masoud; Baran, Ismet; Mohanty, Sankhya
2018-01-01
Numerical modelling is increasingly supporting the analysis and optimization of manufacturing processes in the production industry. Even if being mostly applied to multistep processes, single process steps may be so complex by nature that the needed models to describe them must include multiphysics...... the diversity in the field of modelling of manufacturing processes as regards process, materials, generic disciplines as well as length scales: (1) modelling of tape casting for thin ceramic layers, (2) modelling the flow of polymers in extrusion, (3) modelling the deformation process of flexible stamps...... for nanoimprint lithography, (4) modelling manufacturing of composite parts and (5) modelling the selective laser melting process. For all five examples, the emphasis is on modelling results as well as describing the models in brief mathematical details. Alongside with relevant references to the original work...
Modeling Suspension and Continuation of a Process
Directory of Open Access Journals (Sweden)
Oleg Svatos
2012-04-01
Full Text Available This work focuses on difficulties an analyst encounters when modeling suspension and continuation of a process in contemporary process modeling languages. As a basis there is introduced general lifecycle of an activity which is then compared to activity lifecycles supported by individual process modeling languages. The comparison shows that the contemporary process modeling languages cover the defined general lifecycle of an activity only partially. There are picked two popular process modeling languages and there is modeled real example, which reviews how the modeling languages can get along with their lack of native support of suspension and continuation of an activity. Upon the unsatisfying results of the contemporary process modeling languages in the modeled example, there is presented a new process modeling language which, as demonstrated, is capable of capturing suspension and continuation of an activity in much simpler and precise way.
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...
Computer Aided Continuous Time Stochastic Process Modelling
DEFF Research Database (Denmark)
Kristensen, N.R.; Madsen, Henrik; Jørgensen, Sten Bay
2001-01-01
A grey-box approach to process modelling that combines deterministic and stochastic modelling is advocated for identification of models for model-based control of batch and semi-batch processes. A computer-aided tool designed for supporting decision-making within the corresponding modelling cycle...
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.
Process modeling for Humanities: tracing and analyzing scientific processes
Hug , Charlotte; Salinesi , Camille; Deneckere , Rebecca; Lamasse , Stéphane
2011-01-01
International audience; This paper concerns epistemology and the understanding of research processes in Humanities, such as Archaeology. We believe that to properly understand research processes, it is essential to trace them. The collected traces depend on the process model established, which has to be as accurate as possible to exhaustively record the traces. In this paper, we briefly explain why the existing process models for Humanities are not sufficient to represent traces. We then pres...
Liao, Yuxi; Li, Hongbao; Zhang, Qiaosheng; Fan, Gong; Wang, Yiwen; Zheng, Xiaoxiang
2014-01-01
Decoding algorithm in motor Brain Machine Interfaces translates the neural signals to movement parameters. They usually assume the connection between the neural firings and movements to be stationary, which is not true according to the recent studies that observe the time-varying neuron tuning property. This property results from the neural plasticity and motor learning etc., which leads to the degeneration of the decoding performance when the model is fixed. To track the non-stationary neuron tuning during decoding, we propose a dual model approach based on Monte Carlo point process filtering method that enables the estimation also on the dynamic tuning parameters. When applied on both simulated neural signal and in vivo BMI data, the proposed adaptive method performs better than the one with static tuning parameters, which raises a promising way to design a long-term-performing model for Brain Machine Interfaces decoder.
The Impact of the Delivery of Prepared Power Point Presentations on the Learning Process
Directory of Open Access Journals (Sweden)
Auksė Marmienė
2011-04-01
Full Text Available This article describes the process of the preparation and delivery of Power Point presentations and how it can be used by teachers as a resource for classroom teaching. The advantages of this classroom activity covering some of the problems and providing a few suggestions for dealing with those difficulties are also outlined. The major objective of the present paper is to investigate the students ability to choose the material and the content of Power Point presentations on professional topics via the Internet as well as the ability to prepare and deliver the presentation in front of the audience. The factors which determine the choice of the presentation subject are also analysed in this paper. After the delivery students were requested to self- and peer-assess the difficulties they faced in preparation and performance of the presentations by writing the reports. Learners’ attitudes to the choice of the topic of Power Point presentations were surveyed by administering a self-assessment questionnaire.
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
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...
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.
Modeling a point-source release of 1,1,1-trichloroethane using EPA's SCREEN model
International Nuclear Information System (INIS)
Henriques, W.D.; Dixon, K.R.
1994-01-01
Using data from the Environmental Protection Agency's Toxic Release Inventory 1988 (EPA TRI88), pollutant concentration estimates were modeled for a point source air release of 1,1,1-trichloroethane at the Savannah River Plant located in Aiken, South Carolina. Estimates were calculating using the EPA's SCREEN model utilizing typical meteorological conditions to determine maximum impact of the plume under different mixing conditions for locations within 100 meters of the stack. Input data for the SCREEN model were then manipulated to simulate the impact of the release under urban conditions (for the purpose of assessing future landuse considerations) and under flare release options to determine if these parameters lessen or increase the probability of human or wildlife exposure to significant concentrations. The results were then compared to EPA reference concentrations (RfC) in order to assess the size of the buffer around the stack which may potentially have levels that exceed this level of safety
Process for quality assurance of welded joints for electrical resistance point welding
International Nuclear Information System (INIS)
Schaefer, R.; Singh, S.
1977-01-01
In order to guarantee the reproducibility of welded joints of even quality (above all in the metal working industry), it is proposed that before starting resistance point welding, a preheating current should be allowed to flow at the site of the weld. A given reduction of the total resistance at the site of the weld should effect the time when the preheating current is switched over to welding current. This value is always predetermined empirically. Further possibilities of controlling the welding process are described, where the measurement of thermal expansion of the parts is used. A standard welding time is given. The rated course of electrode movement during the process can be predicted and a running comparison of nominal and actual values can be carried out. (RW) [de
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.
Energy Technology Data Exchange (ETDEWEB)
Mugendiran, V.; Gnanavelbabu, A. [Anna University, Chennai, Tamilnadu (India)
2017-06-15
In this study, a surface based strain measurement was used to determine the formability of the sheet metal. A strain measurement may employ manual calculation of plastic strains based on the reference circle and the deformed circle. The manual calculation method has a greater margin of error in the practical applications. In this paper, an attempt has been made to compare the formability by implementing three different theoretical approaches: Namely conventional method, least square method and digital based strain measurements. As the sheet metal was formed by a single point incremental process the etched circles get deformed into elliptical shapes approximately, image acquisition has been done before and after forming. The plastic strains of the deformed circle grids are calculated based on the non- deformed reference. The coordinates of the deformed circles are measured by various image processing steps. Finally the strains obtained from the deformed circle are used to plot the forming limit diagram. To evaluate the accuracy of the system, the conventional, least square and digital based method of prediction of the forming limit diagram was compared. Conventional method and least square method have marginal error when compared with digital based processing method. Measurement of strain based on image processing agrees well and can be used to improve the accuracy and to reduce the measurement error in prediction of forming limit diagram.
International Nuclear Information System (INIS)
Mugendiran, V.; Gnanavelbabu, A.
2017-01-01
In this study, a surface based strain measurement was used to determine the formability of the sheet metal. A strain measurement may employ manual calculation of plastic strains based on the reference circle and the deformed circle. The manual calculation method has a greater margin of error in the practical applications. In this paper, an attempt has been made to compare the formability by implementing three different theoretical approaches: Namely conventional method, least square method and digital based strain measurements. As the sheet metal was formed by a single point incremental process the etched circles get deformed into elliptical shapes approximately, image acquisition has been done before and after forming. The plastic strains of the deformed circle grids are calculated based on the non- deformed reference. The coordinates of the deformed circles are measured by various image processing steps. Finally the strains obtained from the deformed circle are used to plot the forming limit diagram. To evaluate the accuracy of the system, the conventional, least square and digital based method of prediction of the forming limit diagram was compared. Conventional method and least square method have marginal error when compared with digital based processing method. Measurement of strain based on image processing agrees well and can be used to improve the accuracy and to reduce the measurement error in prediction of forming limit diagram.
Business process modeling for processing classified documents using RFID technology
Directory of Open Access Journals (Sweden)
Koszela Jarosław
2016-01-01
Full Text Available The article outlines the application of the processing approach to the functional description of the designed IT system supporting the operations of the secret office, which processes classified documents. The article describes the application of the method of incremental modeling of business processes according to the BPMN model to the description of the processes currently implemented (“as is” in a manual manner and target processes (“to be”, using the RFID technology for the purpose of their automation. Additionally, the examples of applying the method of structural and dynamic analysis of the processes (process simulation to verify their correctness and efficiency were presented. The extension of the process analysis method is a possibility of applying the warehouse of processes and process mining methods.
Neutron capture at the s-process branching points $^{171}$Tm and $^{204}$Tl
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...
Students’ Algebraic Thinking Process in Context of Point and Line Properties
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.
Process correlation analysis model for process improvement identification.
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.
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...
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...
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
Syntax highlighting in business process models
Reijers, H.A.; Freytag, T.; Mendling, J.; Eckleder, A.
2011-01-01
Sense-making of process models is an important task in various phases of business process management initiatives. Despite this, there is currently hardly any support in business process modeling tools to adequately support model comprehension. In this paper we adapt the concept of syntax
Configurable multi-perspective business process models
La Rosa, M.; Dumas, M.; Hofstede, ter A.H.M.; Mendling, J.
2011-01-01
A configurable process model provides a consolidated view of a family of business processes. It promotes the reuse of proven practices by providing analysts with a generic modeling artifact from which to derive individual process models. Unfortunately, the scope of existing notations for
Entry points to stimulation of expansion in hides and skins processing
African Journals Online (AJOL)
Only 3.4% of respondents add value to hides and skins by processing. ... For this status of the chain, it was proposed that a workable intervention model has to encompass placement of tanneries and slaughter slabs in the chain as new actors, linking chain actors, improving livestock services especially dipping, and ...
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
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.
Automatic 3D Building Detection and Modeling from Airborne LiDAR Point Clouds
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
User's manual for a process model code
International Nuclear Information System (INIS)
Kern, E.A.; Martinez, D.P.
1981-03-01
The MODEL code has been developed for computer modeling of materials processing facilities associated with the nuclear fuel cycle. However, it can also be used in other modeling applications. This report provides sufficient information for a potential user to apply the code to specific process modeling problems. Several examples that demonstrate most of the capabilities of the code are provided
Repairing process models to reflect reality
Fahland, D.; Aalst, van der W.M.P.; Barros, A.; Gal, A.; Kindler, E.
2012-01-01
Process mining techniques relate observed behavior (i.e., event logs) to modeled behavior (e.g., a BPMN model or a Petri net). Processes models can be discovered from event logs and conformance checking techniques can be used to detect and diagnose differences between observed and modeled behavior.
International Nuclear Information System (INIS)
Tweardy, Matthew C.; McConchie, Seth; Hayward, Jason P.
2017-01-01
An extension of the point kinetics model is developed in this paper 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. Finally, the spatial dependence of multiplication is also suspected of introducing further systematic bias for high multiplication uranium objects.
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.
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.
Genetic Process Mining: Alignment-based Process Model Mutation
Eck, van M.L.; Buijs, J.C.A.M.; Dongen, van B.F.; Fournier, F.; Mendling, J.
2015-01-01
The Evolutionary Tree Miner (ETM) is a genetic process discovery algorithm that enables the user to guide the discovery process based on preferences with respect to four process model quality dimensions: replay fitness, precision, generalization and simplicity. Traditionally, the ETM algorithm uses
A Typology for Modeling Processes in Clinical Guidelines and Protocols
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.
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.
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)
Finding Non-Zero Stable Fixed Points of the Weighted Kuramoto model is NP-hard
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...
Composing Models of Geographic Physical Processes
Hofer, Barbara; Frank, Andrew U.
Processes are central for geographic information science; yet geographic information systems (GIS) lack capabilities to represent process related information. A prerequisite to including processes in GIS software is a general method to describe geographic processes independently of application disciplines. This paper presents such a method, namely a process description language. The vocabulary of the process description language is derived formally from mathematical models. Physical processes in geography can be described in two equivalent languages: partial differential equations or partial difference equations, where the latter can be shown graphically and used as a method for application specialists to enter their process models. The vocabulary of the process description language comprises components for describing the general behavior of prototypical geographic physical processes. These process components can be composed by basic models of geographic physical processes, which is shown by means of an example.
MORTALITY MODELING WITH LEVY PROCESSES
Directory of Open Access Journals (Sweden)
M. Serhat Yucel, FRM
2012-07-01
Full Text Available Mortality and longevity risk is usually one of the main risk components ineconomic capital models of insurance companies. Above all, future mortalityexpectations are an important input in the modeling and pricing of long termproducts. Deviations from the expectation can lead insurance company even todefault if sufficient reserves and capital is not held. Thus, Modeling of mortalitytime series accurately is a vital concern for the insurance industry. The aim of thisstudy is to perform distributional and spectral testing to the mortality data andpracticed discrete and continuous time modeling. We believe, the results and thetechniques used in this study will provide a basis for Value at Risk formula incase of mortality.
Model-based software process improvement
Zettervall, Brenda T.
1994-01-01
The activities of a field test site for the Software Engineering Institute's software process definition project are discussed. Products tested included the improvement model itself, descriptive modeling techniques, the CMM level 2 framework document, and the use of process definition guidelines and templates. The software process improvement model represents a five stage cyclic approach for organizational process improvement. The cycles consist of the initiating, diagnosing, establishing, acting, and leveraging phases.
Kopernik : modeling business processes for digital customers
Estañol Lamarca, Montserrat; Castro, Manuel; Díaz-Montenegro, Sylvia; Teniente López, Ernest
2016-01-01
This paper presents the Kopernik methodology for modeling business processes for digital customers. These processes require a high degree of flexibility in the execution of their tasks or actions. We achieve this by using the artifact-centric approach to process modeling and the use of condition-action rules. The processes modeled following Kopernik can then be implemented in an existing commercial tool, Balandra.
The triconnected abstraction of process models
Polyvyanyy, Artem; Smirnov, Sergey; Weske, Mathias
2009-01-01
Contents: Artem Polyvanny, Sergey Smirnow, and Mathias Weske The Triconnected Abstraction of Process Models 1 Introduction 2 Business Process Model Abstraction 3 Preliminaries 4 Triconnected Decomposition 4.1 Basic Approach for Process Component Discovery 4.2 SPQR-Tree Decomposition 4.3 SPQR-Tree Fragments in the Context of Process Models 5 Triconnected Abstraction 5.1 Abstraction Rules 5.2 Abstraction Algorithm 6 Related Work and Conclusions
Investigation of Mediational Processes Using Parallel Process Latent Growth Curve Modeling
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
2011-11-01
Using a multidisciplinary team approach, the University of California, San Diego, Health System has been able to significantly reduce average door-to-balloon angioplasty times for patients with the most severe form of heart attacks, beating national recommendations by more than a third. The multidisciplinary team meets monthly to review all cases involving patients with ST-segment-elevation myocardial infarctions (STEMI) to see where process improvements can be made. Using this continuous quality improvement (CQI) process, the health system has reduced average door-to-balloon times from 120 minutes to less than 60 minutes, and administrators are now aiming for further progress. Among the improvements instituted by the multidisciplinary team are the implementation of a "greeter" with enough clinical expertise to quickly pick up on potential STEMI heart attacks as soon as patients walk into the ED, and the purchase of an electrocardiogram (EKG) machine so that evaluations can be done in the triage area. ED staff have prepared "STEMI" packets, including items such as special IV tubing and disposable leads, so that patients headed for the catheterization laboratory are prepared to undergo the procedure soon after arrival. All the clocks and devices used in the ED are synchronized so that analysts can later review how long it took to complete each step of the care process. Points of delay can then be targeted for improvement.
Modelling of Batch Process Operations
DEFF Research Database (Denmark)
Abdul Samad, Noor Asma Fazli; Cameron, Ian; Gani, Rafiqul
2011-01-01
Here a batch cooling crystalliser is modelled and simulated as is a batch distillation system. In the batch crystalliser four operational modes of the crystalliser are considered, namely: initial cooling, nucleation, crystal growth and product removal. A model generation procedure is shown that s...
Mathematical Modeling: A Structured Process
Anhalt, Cynthia Oropesa; Cortez, Ricardo
2015-01-01
Mathematical modeling, in which students use mathematics to explain or interpret physical, social, or scientific phenomena, is an essential component of the high school curriculum. The Common Core State Standards for Mathematics (CCSSM) classify modeling as a K-12 standard for mathematical practice and as a conceptual category for high school…
Solloway, C. B.; Wakeland, W.
1976-01-01
First-order Markov model developed on digital computer for population with specific characteristics. System is user interactive, self-documenting, and does not require user to have complete understanding of underlying model details. Contains thorough error-checking algorithms on input and default capabilities.
The (n, $\\gamma$) reaction in the s-process branching point $^{59}$Ni
We propose to measure the $^{59}$Ni(n,$\\gamma$)$^{56}$Fe cross section at the neutron time of flight (n TOF) facility with a dedicated chemical vapor deposition (CVD) diamond detector. The (n, ) reaction in the radioactive $^{59}$Ni is of relevance in nuclear astrophysics as it can be seen as a rst branching point in the astrophysical s-process. Its relevance in nuclear technology is especially related to material embrittlement in stainless steel. There is a strong discrepancy between available experimental data and the evaluated nuclear data les for this isotope. The aim of the measurement is to clarify this disagreement. The clear energy separation of the reaction products of neutron induced reactions in $^{59}$Ni makes it a very suitable candidate for a rst cross section measurement with the CVD diamond detector, which should serve in the future for similar measurements at n_TOF.
International Nuclear Information System (INIS)
Petersen, A.M.; Melamu, Rethabi; Knoetze, J.H.; Görgens, J.F.
2015-01-01
Highlights: • Process evaluation of thermochemical and biological routes for bagasse to fuels. • Pinch point analysis increases overall efficiencies by reducing utility consumption. • Advanced biological route increased efficiency and local environmental impacts. • Thermochemical routes have the highest efficiencies and low life cycle impacts. - Abstract: Three alternative processes for the production of liquid transportation biofuels from sugar cane bagasse were compared, on the perspective of energy efficiencies using process modelling, Process Environmental Assessments and Life Cycle Assessment. Bio-ethanol via two biological processes was considered, i.e. Separate Hydrolysis and Fermentation (Process 1) and Simultaneous Saccharification and Fermentation (Process 2), in comparison to Gasification and Fischer Tropsch synthesis for the production of synthetic fuels (Process 3). The energy efficiency of each process scenario was maximised by pinch point analysis for heat integration. The more advanced bio-ethanol process was Process 2 and it had a higher energy efficiency at 42.3%. Heat integration was critical for the Process 3, whereby the energy efficiency was increased from 51.6% to 55.7%. For both the Process Environmental and Life Cycle Assessment, Process 3 had the least potential for detrimental environmental impacts, due to its relatively high energy efficiency. Process 2 had the greatest Process Environmental Impact due to the intensive use of processing chemicals. Regarding the Life Cycle Assessments, Process 1 was the most severe due to its low energy efficiency
Transforming Collaborative Process Models into Interface Process Models by Applying an MDA Approach
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.
A Biomechanical Model of Single-joint Arm Movement Control Based on the Equilibrium Point Hypothesis
Masataka, SUZUKI; Yoshihiko, YAMAZAKI; Yumiko, TANIGUCHI; Department of Psychology, Kinjo Gakuin University; Department of Health and Physical Education, Nagoya Institute of Technology; College of Human Life and Environment, Kinjo Gakuin University
2003-01-01
SUZUKI,M., YAMAZAKI,Y. and TANIGUCHI,Y., A Biomechanical Model of Single-joint Arm Movement Control Based on the Equilibrium Point Hypothesis. Adv. Exerc. Sports Physiol., Vol.9, No.1 pp.7-25, 2003. According to the equilibrium point hypothesis of motor control, control action of muscles is not explicitly computed, but rather arises as a consequence of interaction among moving equilibrium point, reflex feedback and muscle mechanical properties. This approach is attractive as it obviates the n...
On the asymptotic ergodic capacity of FSO links with generalized pointing error model
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.
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
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
Roldán, J. B.; Miranda, E.; González-Cordero, G.; García-Fernández, P.; Romero-Zaliz, R.; González-Rodelas, P.; Aguilera, A. M.; González, M. B.; Jiménez-Molinos, F.
2018-01-01
A multivariate analysis of the parameters that characterize the reset process in Resistive Random Access Memory (RRAM) has been performed. The different correlations obtained can help to shed light on the current components that contribute in the Low Resistance State (LRS) of the technology considered. In addition, a screening method for the Quantum Point Contact (QPC) current component is presented. For this purpose, the second derivative of the current has been obtained using a novel numerical method which allows determining the QPC model parameters. Once the procedure is completed, a whole Resistive Switching (RS) series of thousands of curves is studied by means of a genetic algorithm. The extracted QPC parameter distributions are characterized in depth to get information about the filamentary pathways associated with LRS in the low voltage conduction regime.
Ab-initio modelling of thermodynamics and kinetics of point defects in indium oxide
International Nuclear Information System (INIS)
Agoston, Peter; Klein, Andreas; Albe, Karsten; Erhart, Paul
2008-01-01
The electrical and optical properties of indium oxide films strongly vary with the processing parameters. Especially the oxygen partial pressure and temperature determine properties like electrical conductivity, composition and transparency. Since this material owes its remarkable properties like the intrinsic n-type conductivity to its defect chemistry, it is important to understand both, the equilibrium defect thermodynamics and kinetics of the intrinsic point defects. In this contribution we present a defect model based on DFT total energy calculations using the GGA+U method. Further, the nudged elastic band method is employed in order to obtain a set of migration barriers for each defect species. Due to the complicated crystal structure of indium oxide a Kinetic Monte-Carlo algorithm was implemented, which allows to determine diffusion coefficients. The bulk tracer diffusion constant is predicted as a function of oxygen partial pressure, Fermi level and temperature for the pure material
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.
Modeling business processes: theoretical and practical aspects
Directory of Open Access Journals (Sweden)
V.V. Dubininа
2015-06-01
Full Text Available The essence of process-oriented enterprise management has been examined in the article. The content and types of information technology have been analyzed in the article, due to the complexity and differentiation of existing methods, as well as the specificity of language, terminology of the enterprise business processes modeling. The theoretical aspects of business processes modeling have been reviewed and the modern traditional modeling techniques received practical application in the visualization model of retailers activity have been studied in the article. In the process of theoretical analysis of the modeling methods found that UFO-toolkit method that has been developed by Ukrainian scientists due to it systemology integrated opportunities, is the most suitable for structural and object analysis of retailers business processes. It was designed visualized simulation model of the business process "sales" as is" of retailers using a combination UFO-elements with the aim of the further practical formalization and optimization of a given business process.
Construction and Updating of Event Models in Auditory Event Processing
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…
Segmenting Bone Parts for Bone Age Assessment using Point Distribution Model and Contour Modelling
Kaur, Amandeep; Singh Mann, Kulwinder, Dr.
2018-01-01
Bone age assessment (BAA) is a task performed on radiographs by the pediatricians in hospitals to predict the final adult height, to diagnose growth disorders by monitoring skeletal development. For building an automatic bone age assessment system the step in routine is to do image pre-processing of the bone X-rays so that features row can be constructed. In this research paper, an enhanced point distribution algorithm using contours has been implemented for segmenting bone parts as per well-established procedure of bone age assessment that would be helpful in building feature row and later on; it would be helpful in construction of automatic bone age assessment system. Implementation of the segmentation algorithm shows high degree of accuracy in terms of recall and precision in segmenting bone parts from left hand X-Rays.
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.
A Comparative of business process modelling techniques
Tangkawarow, I. R. H. T.; Waworuntu, J.
2016-04-01
In this era, there is a lot of business process modeling techniques. This article is the research about differences of business process modeling techniques. For each technique will explain about the definition and the structure. This paper presents a comparative analysis of some popular business process modelling techniques. The comparative framework is based on 2 criteria: notation and how it works when implemented in Somerleyton Animal Park. Each technique will end with the advantages and disadvantages. The final conclusion will give recommend of business process modeling techniques that easy to use and serve the basis for evaluating further modelling techniques.
Information-Processing Models and Curriculum Design
Calfee, Robert C.
1970-01-01
"This paper consists of three sections--(a) the relation of theoretical analyses of learning to curriculum design, (b) the role of information-processing models in analyses of learning processes, and (c) selected examples of the application of information-processing models to curriculum design problems." (Author)
How visual cognition influences process model comprehension
Petrusel, Razvan; Mendling, Jan; Reijers, Hajo A.
2017-01-01
Process analysts and other professionals extensively use process models to analyze business processes and identify performance improvement opportunities. Therefore, it is important that such models can be easily and properly understood. Previous research has mainly focused on two types of factors
Social software for business process modeling
Koschmider, A.; Song, M.S.; Reijers, H.A.
2010-01-01
Formal models of business processes are used for a variety of purposes. But where the elicitation of the characteristics of a business process usually takes place in a collaborative fashion, the building of the final, formal process model is done mostly by a single person. This article presents the
Virtual and Printed 3D Models for Teaching Crystal Symmetry and Point Groups
Casas, Lluís; Estop, Euge`nia
2015-01-01
Both, virtual and printed 3D crystal models can help students and teachers deal with chemical education topics such as symmetry and point groups. In the present paper, two freely downloadable tools (interactive PDF files and a mobile app) are presented as examples of the application of 3D design to study point-symmetry. The use of 3D printing to…
Near-real-time regional troposphere models for the GNSS precise point positioning technique
International Nuclear Information System (INIS)
Hadas, T; Kaplon, J; Bosy, J; Sierny, J; Wilgan, K
2013-01-01
The GNSS precise point positioning (PPP) technique requires high quality product (orbits and clocks) application, since their error directly affects the quality of positioning. For real-time purposes it is possible to utilize ultra-rapid precise orbits and clocks which are disseminated through the Internet. In order to eliminate as many unknown parameters as possible, one may introduce external information on zenith troposphere delay (ZTD). It is desirable that the a priori model is accurate and reliable, especially for real-time application. One of the open problems in GNSS positioning is troposphere delay modelling on the basis of ground meteorological observations. Institute of Geodesy and Geoinformatics of Wroclaw University of Environmental and Life Sciences (IGG WUELS) has developed two independent regional troposphere models for the territory of Poland. The first one is estimated in near-real-time regime using GNSS data from a Polish ground-based augmentation system named ASG-EUPOS established by Polish Head Office of Geodesy and Cartography (GUGiK) in 2008. The second one is based on meteorological parameters (temperature, pressure and humidity) gathered from various meteorological networks operating over the area of Poland and surrounding countries. This paper describes the methodology of both model calculation and verification. It also presents results of applying various ZTD models into kinematic PPP in the post-processing mode using Bernese GPS Software. Positioning results were used to assess the quality of the developed models during changing weather conditions. Finally, the impact of model application to simulated real-time PPP on precision, accuracy and convergence time is discussed. (paper)
Measuring similarity between business process models
Dongen, van B.F.; Dijkman, R.M.; Mendling, J.
2007-01-01
Quality aspects become increasingly important when business process modeling is used in a large-scale enterprise setting. In order to facilitate a storage without redundancy and an efficient retrieval of relevant process models in model databases it is required to develop a theoretical understanding
Steady-State Process Modelling
DEFF Research Database (Denmark)
Cameron, Ian; Gani, Rafiqul
2011-01-01
illustrate the “equation oriented” approach as well as the “sequential modular” approach to solving complex flowsheets for steady state applications. The applications include the Williams-Otto plant, the hydrodealkylation (HDA) of toluene, conversion of ethylene to ethanol and a bio-ethanol process....
The neutron capture cross section of the ${s}$-process branch point isotope $^{63}$Ni
Neutron capture nucleosynthesis in massive stars plays an important role in Galactic chemical evolution as well as for the analysis of abundance patterns in very old metal-poor halo stars. The so-called weak ${s}$-process component, which is responsible for most of the ${s}$ abundances between Fe and Sr, turned out to be very sensitive to the stellar neutron capture cross sections in this mass region and, in particular, of isotopes near the seed distribution around Fe. In this context, the unstable isotope $^{63}$Ni is of particular interest because it represents the first branching point in the reaction path of the ${s}$-process. We propose to measure this cross section at n_TOF from thermal energies up to 500 keV, covering the entire range of astrophysical interest. These data are needed to replace uncertain theoretical predicitons by first experimental information to understand the consequences of the $^{63}$Ni branching for the abundance pattern of the subsequent isotopes, especially for $^{63}$Cu and $^{...
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...
Statistical imitation system using relational interest points and Gaussian mixture models
CSIR Research Space (South Africa)
Claassens, J
2009-11-01
Full Text Available The author proposes an imitation system that uses relational interest points (RIPs) and Gaussian mixture models (GMMs) to characterize a behaviour. The system's structure is inspired by the Robot Programming by Demonstration (RDP) paradigm...
Styles in business process modeling: an exploration and a model
Pinggera, J.; Soffer, P.; Fahland, D.; Weidlich, M.; Zugal, S.; Weber, B.; Reijers, H.A.; Mendling, J.
2015-01-01
Business process models are an important means to design, analyze, implement, and control business processes. As with every type of conceptual model, a business process model has to meet certain syntactic, semantic, and pragmatic quality requirements to be of value. For many years, such quality
Process generalization in conceptual models
Wieringa, Roelf J.
In conceptual modeling, the universe of discourse (UoD) is divided into classes which have a taxonomic structure. The classes are usually defined in terms of attributes (all objects in a class share attribute names) and possibly of events. For enmple, the class of employees is the set of objects to
Numerical modelling of reflood processes
International Nuclear Information System (INIS)
Glynn, D.R.; Rhodes, N.; Tatchell, D.G.
1983-01-01
The use of a detailed computer model to investigate the effects of grid size and the choice of wall-to-fluid heat-transfer correlations on the predictions obtained for reflooding of a vertical heated channel is described. The model employs equations for the momentum and enthalpy of vapour and liquid and hence accounts for both thermal non-equilibrium and slip between the phases. Empirical correlations are used to calculate interphase and wall-to-fluid friction and heat-transfer as functions of flow regime and local conditions. The empirical formulae have remained fixed with the exception of the wall-to-fluid heat-transfer correlations. These have been varied according to the practices adopted in other computer codes used to model reflood, namely REFLUX, RELAP and TRAC. Calculations have been performed to predict the CSNI standard problem number 7, and the results are compared with experiment. It is shown that the results are substantially grid-independent, and that the choice of correlation has a significant influence on the general flow behaviour, the rate of quenching and on the maximum cladding temperature predicted by the model. It is concluded that good predictions of reflooding rates can be obtained with particular correlation sets. (author)
Reliable four-point flexion test and model for die-to-wafer direct bonding
Energy Technology Data Exchange (ETDEWEB)
Tabata, T., E-mail: toshiyuki.tabata@cea.fr; Sanchez, L.; Fournel, F.; Moriceau, H. [Univ. Grenoble Alpes, F-38000 Grenoble, France and CEA, LETI, MINATEC Campus, F-38054 Grenoble (France)
2015-07-07
For many years, wafer-to-wafer (W2W) direct bonding has been very developed particularly in terms of bonding energy measurement and bonding mechanism comprehension. Nowadays, die-to-wafer (D2W) direct bonding has gained significant attention, for instance, in photonics and microelectro-mechanics, which supposes controlled and reliable fabrication processes. So, whatever the stuck materials may be, it is not obvious whether bonded D2W structures have the same bonding strength as bonded W2W ones, because of possible edge effects of dies. For that reason, it has been strongly required to develop a bonding energy measurement technique which is suitable for D2W structures. In this paper, both D2W- and W2W-type standard SiO{sub 2}-to-SiO{sub 2} direct bonding samples are fabricated from the same full-wafer bonding. Modifications of the four-point flexion test (4PT) technique and applications for measuring D2W direct bonding energies are reported. Thus, the comparison between the modified 4PT and the double-cantilever beam techniques is drawn, also considering possible impacts of the conditions of measures such as the water stress corrosion at the debonding interface and the friction error at the loading contact points. Finally, reliability of a modified technique and a new model established for measuring D2W direct bonding energies is demonstrated.
Branching process models of cancer
Durrett, Richard
2015-01-01
This volume develops results on continuous time branching processes and applies them to study rate of tumor growth, extending classic work on the Luria-Delbruck distribution. As a consequence, the authors calculate the probability that mutations that confer resistance to treatment are present at detection and quantify the extent of tumor heterogeneity. As applications, the authors evaluate ovarian cancer screening strategies and give rigorous proofs for results of Heano and Michor concerning tumor metastasis. These notes should be accessible to students who are familiar with Poisson processes and continuous time. Richard Durrett is mathematics professor at Duke University, USA. He is the author of 8 books, over 200 journal articles, and has supervised more than 40 Ph.D. students. Most of his current research concerns the applications of probability to biology: ecology, genetics, and most recently cancer.
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.
Plasma Processing of Model Residential Solid Waste
Messerle, V. E.; Mossé, A. L.; Nikonchuk, A. N.; Ustimenko, A. B.; Baimuldin, R. V.
2017-09-01
The authors have tested the technology of processing of model residential solid waste. They have developed and created a pilot plasma unit based on a plasma chamber incinerator. The waste processing technology has been tested and prepared for commercialization.