946 resultados para Kolmogorov-Smirnov
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The Kolmogorov approach to turbulence is applied to the Burgers turbulence in the stochastic adhesion model of large-scale structure formation. As the perturbative approach to this model is unreliable, here a new, non-perturbative approach, based on a suitable formulation of Kolmogorov's scaling laws, is proposed. This approach suggests that the power-law exponent of the matter density two-point correlation function is in the range 1–1.33, but it also suggests that the adhesion model neglects important aspects of the gravitational dynamics.
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MSC 2010: 26A33, 35R11, 35R60, 35Q84, 60H10 Dedicated to 80-th anniversary of Professor Rudolf Gorenflo
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Experimental results for a reactive non-buoyant plume of nitric oxide (NO) in a turbulent grid flow doped with ozone (O3) are presented. The Damkohler number (Nd) for the experiment is of order unity indicating the turbulence and chemistry have similar timescales and both affect the chemical reaction rate. Continuous measurements of two components of velocity using hot-wire anemometry and the two reactants using chemiluminescent analysers have been made. A spatial resolution for the reactants of four Kolmogorov scales has been possible because of the novel design of the experiment. Measurements at this resolution for a reactive plume are not found in the literature. The experiment has been conducted relatively close to the grid in the region where self-similarity of the plume has not yet developed. Statistics of a conserved scalar, deduced from both reactive and non-reactive scalars by conserved scalar theory, are used to establish the mixing field of the plume, which is found to be consistent with theoretical considerations and with those found by other investigators in non-reative flows. Where appropriate the reactive species means and higher moments, probability density functions, joint statistics and spectra are compared with their respective frozen, equilibrium and reaction-dominated limits deduced from conserved scalar theory. The theoretical limits bracket reactive scalar statistics where this should be so according to conserved scalar theory. Both reactants approach their equilibrium limits with greater distance downstream. In the region of measurement, the plume reactant behaves as the reactant not in excess and the ambient reactant behaves as the reactant in excess. The reactant covariance lies outside its frozen and equilibrium limits for this value of Vd. The reaction rate closure of Toor (1969) is compared with the measured reaction rate. The gradient model is used to obtain turbulent diffusivities from turbulent fluxes. Diffusivity of a non-reactive scalar is found to be close to that measured in non-reactive flows by others.
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Spreading cell fronts play an essential role in many physiological processes. Classically, models of this process are based on the Fisher-Kolmogorov equation; however, such continuum representations are not always suitable as they do not explicitly represent behaviour at the level of individual cells. Additionally, many models examine only the large time asymptotic behaviour, where a travelling wave front with a constant speed has been established. Many experiments, such as a scratch assay, never display this asymptotic behaviour, and in these cases the transient behaviour must be taken into account. We examine the transient and asymptotic behaviour of moving cell fronts using techniques that go beyond the continuum approximation via a volume-excluding birth-migration process on a regular one-dimensional lattice. We approximate the averaged discrete results using three methods: (i) mean-field, (ii) pair-wise, and (iii) one-hole approximations. We discuss the performace of these methods, in comparison to the averaged discrete results, for a range of parameter space, examining both the transient and asymptotic behaviours. The one-hole approximation, based on techniques from statistical physics, is not capable of predicting transient behaviour but provides excellent agreement with the asymptotic behaviour of the averaged discrete results, provided that cells are proliferating fast enough relative to their rate of migration. The mean-field and pair-wise approximations give indistinguishable asymptotic results, which agree with the averaged discrete results when cells are migrating much more rapidly than they are proliferating. The pair-wise approximation performs better in the transient region than does the mean-field, despite having the same asymptotic behaviour. Our results show that each approximation only works in specific situations, thus we must be careful to use a suitable approximation for a given system, otherwise inaccurate predictions could be made.
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In order to execute, study, or improve operating procedures, companies document them as business process models. Often, business process analysts capture every single exception handling or alternative task handling scenario within a model. Such a tendency results in large process specifications. The core process logic becomes hidden in numerous modeling constructs. To fulfill different tasks, companies develop several model variants of the same business process at different abstraction levels. Afterwards, maintenance of such model groups involves a lot of synchronization effort and is erroneous. We propose an abstraction technique that allows generalization of process models. Business process model abstraction assumes a detailed model of a process to be available and derives coarse-grained models from it. The task of abstraction is to tell significant model elements from insignificant ones and to reduce the latter. We propose to learn insignificant process elements from supplementary model information, e.g., task execution time or frequency of task occurrence. Finally, we discuss a mechanism for user control of the model abstraction level – an abstraction slider.
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Real world business process models may consist of hundreds of elements and have sophisticated structure. Although there are tasks where such models are valuable and appreciated, in general complexity has a negative influence on model comprehension and analysis. Thus, means for managing the complexity of process models are needed. One approach is abstraction of business process models-creation of a process model which preserves the main features of the initial elaborate process model, but leaves out insignificant details. In this paper we study the structural aspects of process model abstraction and introduce an abstraction approach based on process structure trees (PST). The developed approach assures that the abstracted process model preserves the ordering constraints of the initial model. It surpasses pattern-based process model abstraction approaches, allowing to handle graph-structured process models of arbitrary structure. We also provide an evaluation of the proposed approach.
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Companies use business process models to represent their working procedures in order to deploy services to markets, to analyze them, and to improve upon them. Competitive markets necessitate complex procedures, which lead to large process specifications with sophisticated structures. Real world process models can often incorporate hundreds of modeling constructs. While a large degree of detail complicates the comprehension of the processes, it is essential to many analysis tasks. This paper presents a technique to abstract, i.e., to simplify process models. Given a detailed model, we introduce abstraction rules which generalize process fragments in order to bring the model to a higher abstraction level. The approach is suited for the abstraction of large process specifications in order to aid model comprehension as well as decomposing problems of process model analysis. The work is based on process structure trees that have recently been introduced to the field of business process management.
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Process models provide companies efficient means for managing their business processes. Tasks where process models are employed are different by nature and require models of various abstraction levels. However, maintaining several models of one business process involves a lot of synchronization effort and is erroneous. Business process model abstraction assumes a detailed model of a process to be available and derives coarse grained models from it. The task of abstraction is to tell significant model elements from insignificant ones and to reduce the latter. In this paper we argue that process model abstraction can be driven by different abstraction criteria. Criterion choice depends on a task which abstraction facilitates. We propose an abstraction slider - a mechanism that allows user control of the model abstraction level. We discuss examples of combining the slider with different abstraction criteria and sets of process model transformation rules.
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Business processes are an important instrument for understanding and improving how companies provide goods and services to customers. Therefore, many companies have documented their business processes well, often in the Event-driven Process Chains (EPC). Unfortunately, in many cases the resulting EPCs are rather complex, so that the overall process logic is hidden in low level process details. This paper proposes abstraction mechanisms for process models that aim to reduce their complexity, while keeping the overall process structure. We assume that functions are marked with efforts and splits are marked with probabilities. This information is used to separate important process parts from less important ones. Real world process models are used to validate the approach.
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- Introduction There is limited understanding of how young adults’ driving behaviour varies according to long-term substance involvement. It is possible that regular users of amphetamine-type stimulants (i.e. ecstasy (MDMA) and methamphetamine) may have a greater predisposition to engage in drink/drug driving compared to non-users. We compare offence rates, and self-reported drink/drug driving rates, for stimulant users and non-users in Queensland, and examine contributing factors. - Methods The Natural History Study of Drug Use is a prospective longitudinal study using population screening to recruit a probabilistic sample of amphetamine-type stimulant users and non-users aged 19-23 years. At the 4 ½ year follow-up, consent was obtained to extract data from participants’ Queensland driver records (ATS users: n=217, non-users: n=135). Prediction models were developed of offence rates in stimulant users controlling for factors such as aggression and delinquency. - Results Stimulant users were more likely than non-users to have had a drink-driving offence (8.7% vs. 0.8%, p < 0.001). Further, about 26% of ATS users and 14% of non-users self-reported driving under the influence of alcohol during the last 12 months. Among stimulant users, drink-driving was independently associated with last month high-volume alcohol consumption (Incident Rate Ratio (IRR): 5.70, 95% CI: 2.24-14.52), depression (IRR: 1.28, 95% CI: 1.07-1.52), low income (IRR: 3.57, 95% CI: 1.12-11.38), and male gender (IRR: 5.40, 95% CI: 2.05-14.21). - Conclusions Amphetamine-type stimulant use is associated with increased long-term risk of drink-driving, due to a number of behavioural and social factors. Inter-sectoral approaches which target long-term behaviours may reduce offending rates.
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Normalisoitu kompressioetäisyys NCD on mitta kahden dataobjektin välisen keskinäisen etäisyyden laskemiseen. Etäisyysmitta kuvaa sitä, kuinka paljon kahdessa vertailtavassa dataobjektissa on samankaltaisuutta. NCD on normalisoidun informaatioetäisyyden NID:n approksimointi. NID perustuu dataobjektien Kolmogorov-kompleksisuuteen. Dataobjektit kuvataan bittijonoina ja niissä on sitä enemmän samankaltaisuutta, mitä enemmän ne sisältävät keskinäisinformaatiota. NID on universaali siinä mielessä, että se poikkeaa korkeintaan vakiotermin verran optimaalisesta menetelmästä. Vakiotermi ei puolestaan riipu lainkaan vertailtavista dataobjekteista. NCD approksimoi NID:tä reaalimaailman tiivistäjillä, minkä vuoksi se on vain näennäisuniversaali, mutta siitä huolimatta käyttökelpoinen. NCD:n nojalla muodostetaan datasta etäisyysmatriisi, jonka avulla alkiot voidaan ryvästää ja havainnollistaa erityisen kvartettimenetelmän avulla puurakenteeseen. Menetelmää on sovellettu lupaavasti monella alalla. Tutkielma käy läpi menetelmän taustalla olevan teorian ja esittelee sen sovelluskohteita sekä paneutuu erityisesti stemmatologiseen Heinrichi-aineistoon, jota testataan CompLearn-ilmaisohjelmalla, joka tuottaa etäisyysmatriisin sekä muodostaa puurakenteen kvartettimenetelmällä.
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Investigations have been carried out of some aspects of the fine-scale structure of turbulence in grid flows, in boundary layers in a zero pressure gradient and in a boundary layer in a strong favourable pressure gradient leading to relaminarization. Using a narrow-band filter with suitable mid-band frequencies, the properties of the fine-scale structure (appearing as high frequency pulses in the filtered signal) were analysed using the variable discriminator level technique employed earlier by Rao, Narasimha & Badri Narayanan (1971). It was found that, irrespective of the type of flow, the characteristic pulse frequency (say Np) defined by Rao et al. was about 0·6 times the frequency of the zero crossings. It was also found that, over the small range of Reynolds numbers tested, the ratio of the width of the fine-scale regions to the Kolmogorov scale increased linearly with Reynolds number in grid turbulence as well as in flat-plate boundarylayer flow. Nearly lognormal distributions were exhibited by this ratio as well as by the interval between successive zero crossings. The values of Np and of the zero-crossing rate were found to be nearly constant across the boundary layer, except towards its outer edge and very near the wall. In the zero-pressure-gradient boundary-layer flow, very near the wall the high frequency pulses were found to occur mostly when the longitudinal velocity fluctuation u was positive (i.e. above the mean), whereas in the outer part of the boundary layer the pulses more often occurred when u was negative. During acceleration this correlation between the fine-scale motion and the sign of u was less marked.
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In an estuary, mixing and dispersion resulting from turbulence and small scale fluctuation has strong spatio-temporal variability which cannot be resolved in conventional hydrodynamic models while some models employs parameterizations large water bodies. This paper presents small scale diffusivity estimates from high resolution drifters sampled at 10 Hz for periods of about 4 hours to resolve turbulence and shear diffusivity within a tidal shallow estuary (depth < 3 m). Taylor's diffusion theorem forms the basis of a first order estimate for the diffusivity scale. Diffusivity varied between 0.001 – 0.02 m2/s during the flood tide experiment. The diffusivity showed strong dependence (R2 > 0.9) on the horizontal mean velocity within the channel. Enhanced diffusivity caused by shear dispersion resulting from the interaction of large scale flow with the boundary geometries was observed. Turbulence within the shallow channel showed some similarities with the boundary layer flow which include consistency with slope of 5/3 predicted by Kolmogorov's similarity hypothesis within the inertial subrange. The diffusivities scale locally by 4/3 power law following Okubo's scaling and the length scale scales as 3/2 power law of the time scale. The diffusivity scaling herein suggests that the modelling of small scale mixing within tidal shallow estuaries can be approached from classical turbulence scaling upon identifying pertinent parameters.