Using DNS and Statistical Learning to Model Bubbly Channel Flow
Ma, Ming; Lu, Jiacai; Tryggvason, Gretar
2015-11-01
The transient evolution of laminar bubbly flow in a vertical channel is examined by direct numerical simulation (DNS). Nearly spherical bubbles, initially distributed evenly in a fully developed parabolic flow, are driven relatively quickly to the walls, where they increase the drag and reduce the flow rate on a longer time scale. Once the flow rate has been decreased significantly, some of the bubbles move back into the channel interior and the void fraction there approaches the value needed to balance the weight of the mixture and the imposed pressure gradient. A database generated by averaging the DNS results is used to model the closure terms in a simple model of the average flow. Those terms relate the averaged lateral flux of the bubbles, the velocity fluctuations and the averaged surface tension force to the fluid shear, the void fraction and its gradient, as well as the distance to the nearest wall. An aggregated neural network is used for the statistically leaning of unknown closures, and closure relationships are tested by following the evolution of bubbly channel flow with different initial conditions. It is found that the model predictions are in reasonably good agreement with DNS results. Supported by NSF.
A new simple model for composite fading channels: Second order statistics and channel capacity
Yilmaz, Ferkan
2010-09-01
In this paper, we introduce the most general composite fading distribution to model the envelope and the power of the received signal in such fading channels as millimeter wave (60 GHz or above) fading channels and free-space optical channels, which we term extended generalized-K (EGK) composite fading distribution. We obtain the second-order statistics of the received signal envelope characterized by the EGK composite fading distribution. Expressions for probability density function, cumulative distribution function, level crossing rate and average fade duration, moments, amount of fading and average capacity are derived. Numerical and computer simulation examples validate the accuracy of the presented mathematical analysis. © 2010 IEEE.
A Novel Statistical Channel Model for Turbulence-Induced Fading in Free-Space Optical Systems
Aminikashani, Mohammadreza; Kavehrad, Mohsen
2015-01-01
In this paper, we propose a new probability distribution function which accurately describes turbulence-induced fading under a wide range of turbulence conditions. The proposed model, termed Double Generalized Gamma (Double GG), is based on a doubly stochastic theory of scintillation and developed via the product of two Generalized Gamma (GG) distributions. The proposed Double GG distribution generalizes many existing turbulence channel models and provides an excellent fit to the published plane and spherical waves simulation data. Using this new statistical channel model, we derive closed form expressions for the outage probability and the average bit error as well as corresponding asymptotic expressions of free-space optical communication systems over turbulence channels. We demonstrate that our derived expressions cover many existing results in the literature earlier reported for Gamma-Gamma, Double-Weibull and K channels as special cases.
Statistical model of natural stimuli predicts edge-like pooling of spatial frequency channels in V2
Directory of Open Access Journals (Sweden)
Gutmann Michael
2005-02-01
Full Text Available Abstract Background It has been shown that the classical receptive fields of simple and complex cells in the primary visual cortex emerge from the statistical properties of natural images by forcing the cell responses to be maximally sparse or independent. We investigate how to learn features beyond the primary visual cortex from the statistical properties of modelled complex-cell outputs. In previous work, we showed that a new model, non-negative sparse coding, led to the emergence of features which code for contours of a given spatial frequency band. Results We applied ordinary independent component analysis to modelled outputs of complex cells that span different frequency bands. The analysis led to the emergence of features which pool spatially coherent across-frequency activity in the modelled primary visual cortex. Thus, the statistically optimal way of processing complex-cell outputs abandons separate frequency channels, while preserving and even enhancing orientation tuning and spatial localization. As a technical aside, we found that the non-negativity constraint is not necessary: ordinary independent component analysis produces essentially the same results as our previous work. Conclusion We propose that the pooling that emerges allows the features to code for realistic low-level image features related to step edges. Further, the results prove the viability of statistical modelling of natural images as a framework that produces quantitative predictions of visual processing.
Statistical properties of chaotic scattering with one open channel
International Nuclear Information System (INIS)
The correspondence between statistical properties of decaying states and fluctuations in resonance scattering is studied in a statistical model with one open channel. The model is described by an ensemble of random nonhermitian matrices. The dependence of the correlation length on the coupling parameter both for the S-matrix and the cross-section is studied numerically. 37 refs., 7 figs
THESEE-3, Orgel Reactor Performance and Statistic Hot Channel Factors
International Nuclear Information System (INIS)
1 - Nature of physical problem solved: The code applies to a heavy-water moderated organic-cooled reactor channel. Different fuel cluster models can be used (circular or hexagonal patterns). The code gives coolant temperatures and velocities and cladding temperatures throughout the channel and also channel performances, such as power, outlet temperature, boiling and burn-out safety margins (see THESEE-1). In a further step, calculations are performed with statistical values obtained by random retrieval of geometrical in- put data and taking into account construction tolerances, vibrations, etc. The code evaluates the mean value and standard deviation for the more important thermal and hydraulic parameters. 2 - Method of solution: First step calculations are performed for nominal values of parameters by solving iteratively the non-linear system of equations which give the pressure drops in subchannels of the current zone (see THESEE-1). Then a Gaussian probability distribution of possible statistical values of the geometrical input data is assumed. A random number generation routine determines the statistical case. Calculations are performed in the same way as for the nominal case. In the case of several channels, statistical performances must be adjusted to equalize the normal pressure drop. A special subroutine (AVERAGE) then determines the mean value and standard deviation, and thus probability functions of the most significant thermal and hydraulic results. 3 - Restrictions on the complexity of the problem: Maximum 7 fuel clusters, each divided into 10 axial zones. Fuel bundle geometries are restricted to the following models - circular pattern 6/7, 18/19, 36/67 rods, with or without fillers. The fuel temperature distribution is not studied. The probability distribution of the statistical input is assumed to be a Gaussian function. The principle of random retrieval of statistical values is correct, but some additional correlations could be found from a more
Modeling cosmic void statistics
Hamaus, Nico; Wandelt, Benjamin D
2014-01-01
Understanding the internal structure and spatial distribution of cosmic voids is crucial when considering them as probes of cosmology. We present recent advances in modeling void density- and velocity-profiles in real space, as well as void two-point statistics in redshift space, by examining voids identified via the watershed transform in state-of-the-art $\\Lambda$CDM n-body simulations and mock galaxy catalogs. The simple and universal characteristics that emerge from these statistics indicate the self-similarity of large-scale structure and suggest cosmic voids to be among the most pristine objects to consider for future studies on the nature of dark energy, dark matter and modified gravity.
Institute of Scientific and Technical Information of China (English)
Wang Hui-Song; Zeng Gui-Hua
2008-01-01
In this paper,the effect of imperfect channel state information at the receiver, which is caused by noise and other interference, on the multi-access channel capacity is analysed through a statistical-mechanical approach. Replica analyses focus on analytically studying how the minimum mean square error (MMSE) channel estimation error appears in a multiuser channel capacity formula. And the relevant mathematical expressions are derived. At the same time,numerical simulation results are demonstrated to validate the Replica analyses. The simulation results show how the system parameters, such as channel estimation error, system load and signal-to-noise ratio, affect the channel capacity.
Molecular Na-channel excitability from statistical physics
Ramírez-Piscina, L.; Sancho, J. M.
2014-12-01
The excitable properties of the neural cell membrane is the driving mechanism of the neural pulses. Coordinated ionic fluxes across Na and K channels are the devices responsible of this function. Here we present a simple microscopic physical scenario which accounts for this phenomenology. The main elements are ions and channel doors that obey the standard formulation of statistical physics (overdamped Langevin equations) with appropriate nonlinear interacting potentials. From these equations we obtain the ionic flux and the dynamics of the membrane potential. We show that the excitable properties of the membrane are present in a single and simple Na channel. From this framework, additional microscopic information can be obtained, such as statistics of single-channels dynamics or the energetics of action potential events.
Wu, Yongpeng; Wen, Chao-Kai; Xiao, Chengshan; Gao, Xiqi; Schober, Robert
2014-01-01
In this paper, we investigate the design of linear precoders for the multiple-input multiple-output (MIMO) multiple access channel (MAC). We assume that statistical channel state information (CSI) is available at the transmitters and consider the problem under the practical finite alphabet input assumption. First, we derive an asymptotic (in the large system limit) expression for the weighted sum rate (WSR) of the MIMO MAC with finite alphabet inputs and Weichselberger's MIMO channel model. S...
Channel Statistics for MIMO Handsets in Data Mode
DEFF Research Database (Denmark)
Nielsen, Jesper Ødum; Yanakiev, Boyan; Barrio, Samantha Caporal Del; Pedersen, Gert Frølund
The presented work is based on a large dual- band, dual-base outdoor-to-indoor multiple-input multiple- output (MIMO) channel measurement campaign, involving ten different realistic MIMO handsets, held in data mode by eight test users. Various different use cases (UCs) are measured. Statistics on...
First passage time statistics for two-channel diffusion
Godec, Aljaz
2016-01-01
We present rigorous results for the mean first passage time and first passage time statistics for two-channel Markov additive diffusion in a 3-dimensional spherical domain. Inspired by biophysical examples we assume that the particle can only recognise the target in one of the modes, which is shown to effect a non-trivial first passage behaviour. We also address the scenario of intermittent immobilisation. In both cases we prove that despite the perfectly non-recurrent motion of two-channel Markov additive diffusion in 3 dimensions the first passage statistics at long times do not display Poisson-like behaviour if none of the phases has a vanishing diffusion coefficient. This stands in stark contrast to the standard (one-channel) Markov diffusion counterpart. We also discuss the relevance of our results in the context of cellular signalling.
Surface oscillations and statistical equilibrium of planar channeling
International Nuclear Information System (INIS)
By tracing the ion density distribution in transverse phase space, planar channeling at small depth is investigated in detail. Damping of surface oscillations of nuclear encounter probability, as a consequence of motion of ions which do not reach equilibrium, is shown to be caused mainly by diffusion in transverse momentum. Depth evolution of phase space ion density is presented schematically and several quantities characterizing the equalization process are evaluated. The rate of approach to statistical equilibrium is obtained as a function of transverse energy. It is shown that well channeled ions which have oscillation amplitudes of about a quarter of the interplanar spacing are the hardest to reach equilibrium. (author)
Model Selection by Friedman Statistics
Adil Korkmaz; Muharrem Burak ONEMLI
2011-01-01
This study investigates an application of Friedman statistic as a model selection methodology on post estimation data. The Friedman statistic is employed for testing the possible differences between related samples by ranking the data. Similarly, we suggest ranking of competing models based on a specific multiple comparison procedure for identifying differences between models. As a non-parametric test statistic, it does not make assumptions regarding the underlying distribution of data, howe...
Statistical Model for Content Extraction
DEFF Research Database (Denmark)
Qureshi, Pir Abdul Rasool; Memon, Nasrullah
2011-01-01
We present a statistical model for content extraction from HTML documents. The model operates on Document Object Model (DOM) tree of the corresponding HTML document. It evaluates each tree node and associated statistical features to predict significance of the node towards overall content...
New test of the nuclear statistical model
International Nuclear Information System (INIS)
High resolution proton resonance measurements provide a new test of the nuclear statistical model. For a sequence of levels with the same spin and parity the width correlation rho/sub W/ and the amplitude correlation rho/sub A/ are determined separately for the inelastic decay channels. The observed correlations average about 0.5 and are ascribed to direction reactions between the inelastic channels. For a multivariate Gausian distribution rho/sup 2//sub A//rho/sub W/=1. The present data provide the first opportunity to test this prediction directly
Statistical Model of Extreme Shear
DEFF Research Database (Denmark)
Larsen, Gunner Chr.; Hansen, Kurt Schaldemose
2004-01-01
In order to continue cost-optimisation of modern large wind turbines, it is important to continously increase the knowledge on wind field parameters relevant to design loads. This paper presents a general statistical model that offers site-specific prediction of the probability density function...... model that, on a statistically consistent basis, describe the most likely spatial shape of an extreme wind shear event. Predictions from the model have been compared with results from an extreme value data analysis, based on a large number of high-sampled full-scale time series measurements. the...... consistent, given the inevitabel uncertainties associated with model as well as with the extreme value data analysis. Keywords: Statistical model, extreme wind conditions, statistical analysis, turbulence, wind loading, statistical analysis, turbulence, wind loading, wind shear, wind turbines....
Foundational Issues in Statistical Modeling: Statistical Model Specification and Validation
Directory of Open Access Journals (Sweden)
Aris Spanos
2011-01-01
Full Text Available Statistical model specification and validation raise crucial foundational problems whose pertinent resolution holds the key to learning from data by securing the reliability of frequentist inference. The paper questions the judiciousness of several current practices, including the theory-driven approach, and the Akaike-type model selection procedures, arguing that they often lead to unreliable inferences. This is primarily due to the fact that goodness-of-fit/prediction measures and other substantive and pragmatic criteria are of questionable value when the estimated model is statistically misspecified. Foisting one's favorite model on the data often yields estimated models which are both statistically and substantively misspecified, but one has no way to delineate between the two sources of error and apportion blame. The paper argues that the error statistical approach can address this Duhemian ambiguity by distinguishing between statistical and substantive premises and viewing empirical modeling in a piecemeal way with a view to delineate the various issues more effectively. It is also argued that Hendry's general to specific procedures does a much better job in model selection than the theory-driven and the Akaike-type procedures primary because of its error statistical underpinnings.
Statistical modelling with quantile functions
Gilchrist, Warren
2000-01-01
Galton used quantiles more than a hundred years ago in describing data. Tukey and Parzen used them in the 60s and 70s in describing populations. Since then, the authors of many papers, both theoretical and practical, have used various aspects of quantiles in their work. Until now, however, no one put all the ideas together to form what turns out to be a general approach to statistics.Statistical Modelling with Quantile Functions does just that. It systematically examines the entire process of statistical modelling, starting with using the quantile function to define continuous distributions. The author shows that by using this approach, it becomes possible to develop complex distributional models from simple components. A modelling kit can be developed that applies to the whole model - deterministic and stochastic components - and this kit operates by adding, multiplying, and transforming distributions rather than data.Statistical Modelling with Quantile Functions adds a new dimension to the practice of stati...
Diffeomorphic Statistical Deformation Models
DEFF Research Database (Denmark)
Hansen, Michael Sass; Hansen, Mads/Fogtman; Larsen, Rasmus
2007-01-01
manifold and that the distance between two deformations are given by the metric introduced by the L2-norm in the parameter space. The chosen L2-norm is shown to have a clear and intuitive interpretation on the usual nonlinear manifold. Our model is validated on a set of MR images of corpus callosum with...
A Statistical Programme Assignment Model
DEFF Research Database (Denmark)
Rosholm, Michael; Staghøj, Jonas; Svarer, Michael
When treatment effects of active labour market programmes are heterogeneous in an observable way across the population, the allocation of the unemployed into different programmes becomes a particularly important issue. In this paper, we present a statistical model designed to improve the present...... duration of unemployment spells may result if a statistical programme assignment model is introduced. We discuss several issues regarding the plementation of such a system, especially the interplay between the statistical model and case workers....
Statistical Theory of Selectivity and Conductivity in Biological Channels
Luchinsky, D G; Kaufman, I; Timucin, D A; Eisenberg, R S; McClintock, P V E
2016-01-01
We present an equilibrium statistical-mechanical theory of selectivity in biological ion channels. In doing so, we introduce a grand canonical ensemble for ions in a channel's selectivity filter coupled to internal and external bath solutions for a mixture of ions at arbitrary concentrations, we use linear response theory to find the current through the filter for small gradients of electrochemical potential, and we show that the conductivity of the filter is given by the generalized Einstein relation. We apply the theory to the permeation of ions through the potassium selectivity filter, and are thereby able to resolve the long-standing paradox of why the high selectivity of the filter brings no associated delay in permeation. We show that the Eisenman selectivity relation follows directly from the condition of diffusion-limited conductivity through the filter. We also discuss the effect of wall fluctuations on the filter conductivity.
Kawano, T; Hilaire, S
2016-01-01
A model to calculate particle-induced reaction cross sections with statistical Hauser-Feshbach theory including direct reactions is given. The energy average of scattering matrix from the coupled-channels optical model is diagonalized by the transformation proposed by Engelbrecht and Weidenm\\"{u}ller. The ensemble average of $S$-matrix elements in the diagonalized channel space is approximated by a model of Moldauer [Phys.Rev.C {\\bf 12}, 744 (1975)] using newly parametrized channel degree-of-freedom $\
Pupo, Amaury; Baez-Nieto, David; Martínez, Agustín; Latorre, Ramón; González, Carlos
2014-01-01
Voltage-gated proton channels are integral membrane proteins with the capacity to permeate elementary particles in a voltage and pH dependent manner. These proteins have been found in several species and are involved in various physiological processes. Although their primary topology is known, lack of details regarding their structures in the open conformation has limited analyses toward a deeper understanding of the molecular determinants of their function and regulation. Consequently, the f...
Sensometrics: Thurstonian and Statistical Models
DEFF Research Database (Denmark)
Christensen, Rune Haubo Bojesen
area of computational statistics, it is described how the Laplace approximation can be implemented on a case-by-case basis for flexible estimation of nonlinear mixed eects models with normally distributed response. The two R packages sensR and ordinal implement and support the methodological...... statistical package applicable to statistical problems far beyond sensometrics. A series of tutorials, user guides and reference manuals accompany these R packages. Finally, a number of chapters provide background theory on the development and computation of Thurstonian models for a range of binomial......This thesis is concerned with the development and bridging of Thurstonian and statistical models for sensory discrimination testing as applied in the scientific discipline of sensometrics. In sensory discrimination testing sensory differences between products are detected and quantified by the use...
Statistical Model of Extreme Shear
DEFF Research Database (Denmark)
Hansen, Kurt Schaldemose; Larsen, Gunner Chr.
2005-01-01
In order to continue cost-optimisation of modern large wind turbines, it is important to continuously increase the knowledge of wind field parameters relevant to design loads. This paper presents a general statistical model that offers site-specific prediction of the probability density function...... model that, on a statistically consistent basis, describes the most likely spatial shape of an extreme wind shear event. Predictions from the model have been compared with results from an extreme value data analysis, based on a large number of full-scale measurements recorded with a high sampling rate...
Textual information access statistical models
Gaussier, Eric
2013-01-01
This book presents statistical models that have recently been developed within several research communities to access information contained in text collections. The problems considered are linked to applications aiming at facilitating information access:- information extraction and retrieval;- text classification and clustering;- opinion mining;- comprehension aids (automatic summarization, machine translation, visualization).In order to give the reader as complete a description as possible, the focus is placed on the probability models used in the applications
New Statistical Models for Copolymerization
Directory of Open Access Journals (Sweden)
Martin S. Engler
2016-06-01
Full Text Available For many years, copolymerization has been studied using mathematical and statistical models. Here, we present new Markov chain models for copolymerization kinetics: the Bernoulli and Geometric models. They model copolymer synthesis as a random process and are based on a basic reaction scheme. In contrast to previous Markov chain approaches to copolymerization, both models take variable chain lengths and time-dependent monomer probabilities into account and allow for computing sequence likelihoods and copolymer fingerprints. Fingerprints can be computed from copolymer mass spectra, potentially allowing us to estimate the model parameters from measured fingerprints. We compare both models against Monte Carlo simulations. We find that computing the models is fast and memory efficient.
Wireless Channel Propagation Models Evaluation
Raikel Bordón López; Reinier Alonso Quintana; Samuel Montejo Sánchez
2012-01-01
In the design of wireless communications systems, channel modelling is an efficient alternative to predict the path loss. In this paper we present a comparative study between Okumura, Hata, Walfisch-Bertoni and Walfisch-Ikegami propagation models. We present a developed software tool, which is useful to evaluate these models from a graphical user interface. The main objective is to analyze and compare path loss predictions, taking into account different environment conditions and a common val...
Improved model for statistical alignment
Energy Technology Data Exchange (ETDEWEB)
Miklos, I.; Toroczkai, Z. (Zoltan)
2001-01-01
The statistical approach to molecular sequence evolution involves the stochastic modeling of the substitution, insertion and deletion processes. Substitution has been modeled in a reliable way for more than three decades by using finite Markov-processes. Insertion and deletion, however, seem to be more difficult to model, and thc recent approaches cannot acceptably deal with multiple insertions and deletions. A new method based on a generating function approach is introduced to describe the multiple insertion process. The presented algorithm computes the approximate joint probability of two sequences in 0(13) running time where 1 is the geometric mean of the sequence lengths.
Statistical bootstrap model and annihilations
Möhring, H J
1974-01-01
The statistical bootstrap model (SBM) describes the decay of single, high mass, hadronic states (fireballs, clusters) into stable particles. Coupling constants B, one for each isospin multiplet of stable particles, are the only free parameter of the model. They are related to the maximum temperature parameter T/sub 0/. The various versions of the SMB can be classified into two groups: full statistical bootstrap models and linear ones. The main results of the model are the following: i) All momentum spectra are isotropic; especially the exclusive ones are described by invariant phase space. The inclusive and semi-inclusive single-particle distributions are asymptotically of pure exponential shape; the slope is governed by T /sub 0/ only. ii) The model parameter B for pions has been obtained by fitting the multiplicity distribution in pp and pn at rest, and corresponds to T/sub 0/=0.167 GeV in the full SBM with exotics. The average pi /sup -/ multiplicity for the linear and the full SBM (both with exotics) is c...
A Survey of Fading Models for Mobile Radio Channel Characterization
Directory of Open Access Journals (Sweden)
L. D. Arya
2010-02-01
Full Text Available Future 3G and 4G mobile communication systems will be required to support wide range of data rates and quality of service matrix. For the efficient design of data link and transport protocols system designer needs knowledge of the statistical properties of physicallayer. Studies have shown that without proper characterization of the channel, blind application of existing protocols and transmission policy may results in disastrous performance unless proper measures are not being taken. Channel characterization also helps in llocation of resources, selection of transmission policy andprotocols. A feasible measure is to have an accurate and thoroughly reproducible optimum channel model which can mimic the mobile radio channel in diversities of fading error environments. Objective of channel model is to supply proper outputs for designing of upper layer protocol in such a fashion as if it were running on the actualphysical layer. The model should fit very well to the measured data and should easily handle analytically. Various approaches for characterization of fading mobile channels have appeared in iterature over last five decades. This article surveys the fading channel models for proper characterization of the radio channel andprovides approaches to classify the existing channel models. The paper also presents the contribution made by these channel models with their assumptions, suitability, applications, shortcomingsand further improvement issues. In present environment Markov Models are best suited for characterization of the fading radio channel. Inthese models radio channel is presented in terms of fading states and modeled as stochastic process. A proper constructed channel model may be valuable means to enhance the reliability and capacity of future mobile radio channel.
Statistical models for seismic magnitude
Christoffersson, Anders
1980-02-01
In this paper some statistical models in connection with seismic magnitude are presented. Two main situations are treated. The first deals with the estimation of magnitude for an event, using a fixed network of stations and taking into account the detection and bias properties of the individual stations. The second treats the problem of estimating seismicity, and detection and bias properties of individual stations. The models are applied to analyze the magnitude bias effects for an earthquake aftershock sequence from Japan, as recorded by a hypothetical network of 15 stations. It is found that network magnitudes computed by the conventional averaging technique are considerably biased, and that a maximum likelihood approach using instantaneous noise-level estimates for non-detecting stations gives the most consistent magnitude estimates. Finally, the models are applied to evaluate the detection characteristics and associated seismicity as recorded by three VELA arrays: UBO (Uinta Basin), TFO (Tonto Forest) and WMO (Wichita Mountains).
On the Second Order Statistics of the Multihop Rayleigh Fading Channel
Hadzi-Velkov, Zoran; Karagiannidis, George K; 10.1109/TCOMM.2009.06.070460
2009-01-01
Second order statistics provides a dynamic representation of a fading channel and plays an important role in the evaluation and design of the wireless communication systems. In this paper, we present a novel analytical framework for the evaluation of important second order statistical parameters, as the level crossing rate (LCR) and the average fade duration (AFD) of the amplify-and-forward multihop Rayleigh fading channel. More specifically, motivated by the fact that this channel is a cascaded one and can be modeled as the product of N fading amplitudes, we derive novel analytical expressions for the average LCR and the AFD of the product of N Rayleigh fading envelopes (or of the recently so-called N*Rayleigh channel). Furthermore, we derive simple and efficient closed-form approximations to the aforementioned parameters, using the multivariate Laplace approximation theorem. It is shown that our general results reduce to the corresponding ones of the specific dual-hop case, previously published. Numerical a...
A Unifying Statistical Model for Atmospheric Optical Scintillation
Jurado-Navas, Antonio; Garrido-Balsells, José María; Paris, José Francisco; Puerta-Notario, Antonio
2011-01-01
In this paper we develop a new statistical model for the irradiance fluctuations of an unbounded optical wavefront (plane and spherical waves) propagating through a turbulent medium under all irradiance fluctuation conditions in homogeneous, isotropic turbulence. The major advantage of the model is that leads to closed-form and mathematically-tractable expressions for the fundamental channel statistics of an unbounded optical wavefront under all turbulent regimes. Furthermore, it unifies most...
Channel network identification from high-resolution DTM: a statistical approach
Directory of Open Access Journals (Sweden)
G. Sofia
2010-12-01
Full Text Available A statistical approach to LiDAR derived topographic attributes for the automatic extraction of channel network is presented in this paper. The basis of this approach is to use statistical descriptors to identify channel where terrain geometry denotes significant convergences. Two case study areas of different morphology and degree of organization are used with their 1 m LiDAR Digital Terrain Models (DTMs. Topographic attribute maps (curvature and openness for different window sizes are derived from the DTMs in order to detect surface convergences. For the choice of the optimum kernel size, a statistical analysis on values distributions of these maps is carried out. For the network extraction, we propose a three-step method based (a on the normalization and overlapping of openness and minimum curvature in order to highlight the more likely surface convergences, (b a weighting of the upslope area according to such normalized maps in order to identify drainage flow paths and flow accumulation consistent with terrain geometry, (c the z-score normalization of the weighted upslope area and the use of z-score values as non-subjective threshold for channel network identification. As a final step for optimal definition and representation of the whole network, a noise-filtering and connection procedure is applied. The advantage of the proposed methodology, and the efficiency and accurate localization of extracted features are demonstrated using LiDAR data of two different areas and comparing both extractions with field surveyed networks.
Statistical models for trisomic phenotypes
Energy Technology Data Exchange (ETDEWEB)
Lamb, N.E.; Sherman, S.L.; Feingold, E. [Emory Univ., Atlanta, GA (United States)
1996-01-01
Certain genetic disorders are rare in the general population but more common in individuals with specific trisomies, which suggests that the genes involved in the etiology of these disorders may be located on the trisomic chromosome. As with all aneuploid syndromes, however, a considerable degree of variation exists within each phenotype so that any given trait is present only among a subset of the trisomic population. We have previously presented a simple gene-dosage model to explain this phenotypic variation and developed a strategy to map genes for such traits. The mapping strategy does not depend on the simple model but works in theory under any model that predicts that affected individuals have an increased likelihood of disomic homozygosity at the trait locus. This paper explores the robustness of our mapping method by investigating what kinds of models give an expected increase in disomic homozygosity. We describe a number of basic statistical models for trisomic phenotypes. Some of these are logical extensions of standard models for disomic phenotypes, and some are more specific to trisomy. Where possible, we discuss genetic mechanisms applicable to each model. We investigate which models and which parameter values give an expected increase in disomic homozygosity in individuals with the trait. Finally, we determine the sample sizes required to identify the increased disomic homozygosity under each model. Most of the models we explore yield detectable increases in disomic homozygosity for some reasonable range of parameter values, usually corresponding to smaller trait frequencies. It therefore appears that our mapping method should be effective for a wide variety of moderately infrequent traits, even though the exact mode of inheritance is unlikely to be known. 21 refs., 8 figs., 1 tab.
Bae, Minja; Park, Jihyun; Kim, Jongju; Xue, Dandan; Park, Kyu-Chil; Yoon, Jong Rak
2016-07-01
The bit error rate of an underwater acoustic communication system is related to multipath fading statistics, which determine the signal-to-noise ratio. The amplitude and delay of each path depend on sea surface roughness, propagation medium properties, and source-to-receiver range as a function of frequency. Therefore, received signals will show frequency-dependent fading. A shallow-water acoustic communication channel generally shows a few strong multipaths that interfere with each other and the resulting interference affects the fading statistics model. In this study, frequency-selective fading statistics are modeled on the basis of the phasor representation of the complex path amplitude. The fading statistics distribution is parameterized by the frequency-dependent constructive or destructive interference of multipaths. At a 16 m depth with a muddy bottom, a wave height of 0.2 m, and source-to-receiver ranges of 100 and 400 m, fading statistics tend to show a Rayleigh distribution at a destructive interference frequency, but a Rice distribution at a constructive interference frequency. The theoretical fading statistics well matched the experimental ones.
Degenerate RFID Channel Modeling for Positioning Applications
Directory of Open Access Journals (Sweden)
A. Povalac
2012-12-01
Full Text Available This paper introduces the theory of channel modeling for positioning applications in UHF RFID. It explains basic parameters for channel characterization from both the narrowband and wideband point of view. More details are given about ranging and direction finding. Finally, several positioning scenarios are analyzed with developed channel models. All the described models use a degenerate channel, i.e. combined signal propagation from the transmitter to the tag and from the tag to the receiver.
Modeling of weak lensing statistics. II. Configuration-space statistics
Valageas, Patrick; Nishimichi, Takahiro
2011-01-01
We investigate the performance of an analytic model of the 3D matter distribution, which combines perturbation theory with halo models, for weak lensing configuration-space statistics. We compare our predictions for the weak lensing convergence two-point and three-point correlation functions with numerical simulations and fitting formulas proposed in previous works. We also consider the second and third-order moments of the smoothed convergence and of the aperture-mass. As in our previous study of Fourier-space weak lensing statistics, we find that our model provides better agreement with simulations than published fitting formulas. Moreover, we check that we recover the dependence on cosmology of these weak lensing statistics. This approach allows us to obtain the quantitative relationship between these integrated weak lensing statistics and the various contributions to the underlying 3D density fluctuations, decomposed over perturbative, 2-halo, or 1-halo terms.
Statistical simulation of rarefied gas flows in micro-channels
International Nuclear Information System (INIS)
Rarefied gas flows through micro-channels are simulated using particle approaches, named as the information preservation (IP) method and the direct simulation Monte Carlo (DSMC) method. In simulating the low speed flows in long micro-channels the DSMC method encounters the problem of large sample size demand and the difficulty of regulating boundary conditions at the inlet and outlet. Some important computational issues in the calculation of long micro-channel flows by using the IP method, such as the use the conservative form of the mass conservation equation to guarantee the adjustment of the inlet and outlet boundary conditions and the super-relaxation scheme to accelerate the convergence process, are addressed. Stream-wise pressure distributions and mass fluxes through micro-channels given by the IP method agree well with experimental data measured in long micro-channels by Pong et al. (with a height to length ratio of 1.2:3000), Shih et al. (1.2:4800), Arkilic et al. and Arkilic (1.3:7500), respectively. The famous Knudsen minimum of normalized mass flux is observed in IP and DSMC calculations of a short micro-channel over the entire flow regime from continuum to free molecular, whereas the slip Navier-Stokes solution fails to predict it
International Nuclear Information System (INIS)
An overview is given of existing CPR design criteria and the methods used in BWR reload analysis to evaluate the impact of channel bow on CPR margins. Potential weaknesses in today's methodologies are discussed. Westinghouse in collaboration with KKL and Axpo - operator and owner of the Leibstadt NPP - has developed an optimized CPR methodology based on a new criterion to protect against dryout during normal operation and with a more rigorous treatment of channel bow. The new steady-state criterion is expressed in terms of an upper limit of 0.01 for the dryout failure probability per year. This is considered a meaningful and appropriate criterion that can be directly related to the probabilistic criteria set-up for the analyses of Anticipated Operation Occurrences (AOOs) and accidents. In the Monte Carlo approach a statistical modeling of channel bow and an accurate evaluation of CPR response functions allow the associated CPR penalties to be included directly in the plant SLMCPR and OLMCPR in a best-estimate manner. In this way, the treatment of channel bow is equivalent to all other uncertainties affecting CPR. Emphasis is put on quantifying the statistical distribution of channel bow throughout the core using measurement data. The optimized CPR methodology has been implemented in the Westinghouse Monte Carlo code, McSLAP. The methodology improves the quality of dryout safety assessments by supplying more valuable information and better control of conservatisms in establishing operational limits for CPR. The methodology is demonstrated with application examples from the introduction at KKL. (authors)
Four-channel delay generator model 5740
International Nuclear Information System (INIS)
The 4-channel delay generator model 5740 generates 4-pulse groups in independent channels. The device offers the possibility of controlling both the time intervals between the pulses of a group and the rate of generation of groups
Visualizing statistical models and concepts
Farebrother, RW
2002-01-01
Examines classic algorithms, geometric diagrams, and mechanical principles for enhancing visualization of statistical estimation procedures and mathematical concepts in physics, engineering, and computer programming.
Institute of Scientific and Technical Information of China (English)
ZHAO Zhen-shan; XU Guo-zhi
2007-01-01
In real multiple-input multiple-output (MIMO) systems, the perfect channel state information (CSI) may be costly or impossible to acquire. But the channel statistical information can be considered relatively stationary during long-term transmission.The statistical information can be obtained at the receiver and fed back to the transmitter and do not require frequent update. By exploiting channel mean and covariance information at the transmitter simultaneously, this paper investigates the optimal transmission strategy for spatially correlated MIMO channels. An upper bound of ergodic capacity is derived and taken as the performance criterion. Simulation results are also given to show the performance improvement of the optimal transmission strategy.
Higher order capacity statistics of multi-hop transmission systems over Rayleigh fading channels
Yilmaz, Ferkan
2012-03-01
In this paper, we present an exact analytical expression to evaluate the higher order statistics of the channel capacity for amplify and forward (AF) multihop transmission systems operating over Rayleigh fading channels. Furthermore, we present simple and efficient closed-form expression to the higher order moments of the channel capacity of dual hop transmission system with Rayleigh fading channels. In order to analyze the behavior of the higher order capacity statistics and investigate the usefulness of the mathematical analysis, some selected numerical and simulation results are presented. Our results are found to be in perfect agreement. © 2012 IEEE.
Channel models for wireless body area networks.
Takizawa, Kenichi; Aoyagi, Akahiro; Takada, Jun-Ichi; Katayama, Norihiko; Yekeh, Kamya; Takehiko, Yazdandoost; Kohno, Kobayashi Ryuji
2008-01-01
Wireless patient monitoring using wearable sensors is a promising application. This paper provides stochastic channel models for wireless body area network (WBAN) on the human body. Parameters of the channel models are extracted from measured channel transfer functions (CTFs) in a hospital room. Measured frequency bands are selected so as to include permissible bands for WBAN; ultra wideband (UWB), the industry, science and medical (ISM) bands, and wireless medical telemetry system (WMTS) bands. As channel models, both a path loss model and a power delay profile (PDP) model are considered. But, even though path loss models are derived for the all frequency bands, PDP model is only for the UWB band due to the highly frequency selectiveness of UWB channels. The parameters extracted from the measurement results are summarized for each channel model. PMID:19162968
Box model for channels of human migration
Vitanov, Nikolay K
2016-01-01
We discuss a mathematical model of migration channel based on the truncated Waring distribution. The truncated Waring distribution is obtained for a more general model of motion of substance through a channel containing finite number of boxes. The model is applied then for case of migrants moving through a channel consisting of finite number of countries or cities. The number of migrants in the channel strongly depends on the number of migrants that enter the channel through the country of entrance. It is shown that if the final destination country is very popular then large percentage of migrants may concentrate there.
Probing NWP model deficiencies by statistical postprocessing
DEFF Research Database (Denmark)
Rosgaard, Martin Haubjerg; Nielsen, Henrik Aalborg; Nielsen, Torben S.;
2016-01-01
The objective in this article is twofold. On one hand, a Model Output Statistics (MOS) framework for improved wind speed forecast accuracy is described and evaluated. On the other hand, the approach explored identifies unintuitive explanatory value from a diagnostic variable in an operational....... Based on the statistical model candidates inferred from the data, the lifted index NWP model diagnostic is consistently found among the NWP model predictors of the best performing statistical models across sites....
Radio propagation measurement and channel modelling
Salous, Sana
2013-01-01
While there are numerous books describing modern wireless communication systems that contain overviews of radio propagation and radio channel modelling, there are none that contain detailed information on the design, implementation and calibration of radio channel measurement equipment, the planning of experiments and the in depth analysis of measured data. The book would begin with an explanation of the fundamentals of radio wave propagation and progress through a series of topics, including the measurement of radio channel characteristics, radio channel sounders, measurement strategies
Scheduling with Rate Adaptation under Incomplete Knowledge of Channel/Estimator Statistics
Ouyang, Wenzhuo; Eryilmaz, Atilla; Shroff, Ness B
2010-01-01
In time-varying wireless networks, the state of the communication channels are subject to random variations, and hence need to be estimated for efficient rate adaptation and scheduling. The estimation mechanism possesses inaccuracies that need to be tackled in a probabilistic framework. In this work, we study scheduling with rate adaptation in single-hop queueing networks under two levels of channel uncertainty: when the channel estimates are inaccurate but complete knowledge of the channel/estimator joint statistics is available at the scheduler; and when the knowledge of the joint statistics is incomplete. In the former case, we characterize the network stability region and show that a maximum-weight type scheduling policy is throughput-optimal. In the latter case, we propose a joint channel statistics - scheduling policy. With an associated trade-off in average packet delay and convergence time, the proposed policy has a stability region arbitrarily close to the stability region of the network under full k...
Indoor MIMO Channel Measurement and Modeling
DEFF Research Database (Denmark)
Nielsen, Jesper Ødum; Andersen, Jørgen Bach
2005-01-01
Forming accurate models of the multiple input multiple output (MIMO) channel is essential both for simulation as well as understanding of the basic properties of the channel. This paper investigates different known models using measurements obtained with a 16x32 MIMO channel sounder for the 5.8GHz...... accurate model for Gaussian channels. For each of the environments different sizes of both the transmitter and receiver antenna arrays are investigated, 2x2 up to 16x32. Generally it was found that in terms of capacity cumulative distribution functions (CDFs) all models fit well for small array sizes, but...
Yilmaz, Ferkan
2012-06-01
The exact analysis of the higher-order statistics of the channel capacity (i.e., higher-order ergodic capacity) often leads to complicated expressions involving advanced special functions. In this paper, we provide a generic framework for the computation of the higher-order statistics of the channel capacity over generalized fading channels. As such, this novel framework for the higher-order statistics results in simple, closed-form expressions which are shown to be asymptotically tight bounds in the high signal-to-noise ratio (SNR) regime of a variety of fading environment. In addition, it reveals the existence of differences (i.e., constant capacity gaps in log-domain) among different fading environments. By asymptotically tight bound we mean that the high SNR limit of the difference between the actual higher-order statistics of the channel capacity and its asymptotic bound (i.e., lower bound) tends to zero. The mathematical formalism is illustrated with some selected numerical examples that validate the correctness of our newly derived results. © 2012 IEEE.
Chaudhury, Srabanti; Cao, Jianshu; Sinitsyn, Nikolai A
2013-01-17
We consider a generic stochastic model of ion transport through a single channel with arbitrary internal structure and kinetic rates of transitions between internal states. This model is also applicable to describe kinetics of a class of enzymes in which turnover events correspond to conversion of substrate into product by a single enzyme molecule. We show that measurement of statistics of single molecule transition time through the channel contains only restricted information about internal structure of the channel. In particular, the most accessible flux fluctuation characteristics, such as the Poisson indicator (P) and the Fano factor (F) as function of solute concentration, depend only on three parameters in addition to the parameters of the Michaelis-Menten curve that characterizes average current through the channel. Nevertheless, measurement of Poisson indicator or Fano factor for such renewal processes can discriminate reactions with multiple intermediate steps as well as provide valuable information about the internal kinetic rates. PMID:23198705
New Approaches for Channel Prediction Based on Sinusoidal Modeling
Directory of Open Access Journals (Sweden)
Ekman Torbjörn
2007-01-01
Full Text Available Long-range channel prediction is considered to be one of the most important enabling technologies to future wireless communication systems. The prediction of Rayleigh fading channels is studied in the frame of sinusoidal modeling in this paper. A stochastic sinusoidal model to represent a Rayleigh fading channel is proposed. Three different predictors based on the statistical sinusoidal model are proposed. These methods outperform the standard linear predictor (LP in Monte Carlo simulations, but underperform with real measurement data, probably due to nonstationary model parameters. To mitigate these modeling errors, a joint moving average and sinusoidal (JMAS prediction model and the associated joint least-squares (LS predictor are proposed. It combines the sinusoidal model with an LP to handle unmodeled dynamics in the signal. The joint LS predictor outperforms all the other sinusoidal LMMSE predictors in suburban environments, but still performs slightly worse than the standard LP in urban environments.
A Semi-Deterministic Channel Model for VANETs Simulations
Directory of Open Access Journals (Sweden)
Jonathan Ledy
2012-01-01
Full Text Available Today's advanced simulators facilitate thorough studies on Vehicular Ad hoc NETworks (VANETs. However the choice of the physical layer model in such simulators is a crucial issue that impacts the results. A solution to this challenge might be found with a hybrid model. In this paper, we propose a semi-deterministic channel propagation model for VANETs called UM-CRT. It is based on CRT (Communication Ray Tracer and SCME—UM (Spatial Channel Model Extended—Urban Micro which are, respectively, a deterministic channel simulator and a statistical channel model. It uses a process which adjusts the statistical model using relevant parameters obtained from the deterministic simulator. To evaluate realistic VANET transmissions, we have integrated our hybrid model in fully compliant 802.11 p and 802.11 n physical layers. This framework is then used with the NS-2 network simulator. Our simulation results show that UM-CRT is adapted for VANETs simulations in urban areas as it gives a good approximation of realistic channel propagation mechanisms while improving significantly simulation time.
Statistical Modeling of SAR Images: A Survey
Directory of Open Access Journals (Sweden)
Gui Gao
2010-01-01
Full Text Available Statistical modeling is essential to SAR (Synthetic Aperture Radar image interpretation. It aims to describe SAR images through statistical methods and reveal the characteristics of these images. Moreover, statistical modeling can provide a technical support for a comprehensive understanding of terrain scattering mechanism, which helps to develop algorithms for effective image interpretation and creditable image simulation. Numerous statistical models have been developed to describe SAR image data, and the purpose of this paper is to categorize and evaluate these models. We first summarize the development history and the current researching state of statistical modeling, then different SAR image models developed from the product model are mainly discussed in detail. Relevant issues are also discussed. Several promising directions for future research are concluded at last.
Actuarial statistics with generalized linear mixed models
K. Antonio; J. Beirlant
2007-01-01
Over the last decade the use of generalized linear models (GLMs) in actuarial statistics has received a lot of attention, starting from the actuarial illustrations in the standard text by McCullagh and Nelder [McCullagh, P., Nelder, J.A., 1989. Generalized linear models. In: Monographs on Statistics
Statistical Models and Methods for Lifetime Data
Lawless, Jerald F
2011-01-01
Praise for the First Edition"An indispensable addition to any serious collection on lifetime data analysis and . . . a valuable contribution to the statistical literature. Highly recommended . . ."-Choice"This is an important book, which will appeal to statisticians working on survival analysis problems."-Biometrics"A thorough, unified treatment of statistical models and methods used in the analysis of lifetime data . . . this is a highly competent and agreeable statistical textbook."-Statistics in MedicineThe statistical analysis of lifetime or response time data is a key tool in engineering,
On Ergodic Secrecy Capacity of Multiple Input Wiretap Channel with Statistical CSIT
Lin, Shih-Chun
2012-01-01
We consider the secure transmission in ergodic fast-Rayleigh fading multiple-input single-output single-antennaeavesdropper (MISOSE) wiretap channels. We assume that the statistics of both the legitimate and eavesdropper channels is the only available channel state information at the transmitter (CSIT). By introducing a new secrecy capacity upper bound, we prove that the secrecy capacity is achieved by Gaussian input without prefixing. To attain this, we form another MISOSE channel for upper-bounding, and tighten the bound by finding the worst correlations between the legitimate and eavesdropper channel coefficients. The resulting upper bound is tighter than the others in the literature which are based on modifying the correlation between the noises at the legitimate receiver and eavesdropper. Next, we fully characterize the ergodic secrecy capacity by showing that the optimal channel input covariance matrix is a scaled identity matrix, with the transmit power allocated uniformly among the antennas. The key t...
Statistical properties of wall shear stress fluctuations in turbulent channel flows
International Nuclear Information System (INIS)
Highlights: ► Accurate measurements of instantaneous wall shear stress are conducted. ► LDA is used to measure near-wall streamwise velocity. ► Electrochemical probe is used to measure wall shear stress. ► Frequency response and non-uniform correction methods were used to provide an accurate, well-resolved wall-statistics database. ► Reynolds number dependency of the statistical wall quantities is investigated. - Abstract: Instantaneous velocity and wall shear stress measurements are conducted in a turbulent channel flow in the Kármán number range of Reτ = 74–400. A one-dimensional LDA system is used to measure the streamwise velocity fluctuations, and an electrochemical technique is utilized to measure the instantaneous wall shear stress. For the latter, frequency response and nonuniform correction methods are used to provide an accurate, well-resolved wall statistics database. The Reynolds number dependency of the statistical wall quantities is carefully investigated. The corrected relative wall shear stress fluctuations fit well with the best DNS data available and meet the need for clarification of the small discrepancy observed in the literature between the experimental and numerical results of such quantities. Higher-order statistics of the wall shear stress, spectra, and the turbulence kinetic energy budget at the wall are also investigated. The present paper shows that the electrochemical technique is a powerful experimental method for hydrodynamic studies involving highly unsteady flows. The study brings with it important consequences, especially in the context of the current debate regarding the appropriate scaling as well as the validation of new predictive models of near-wall turbulence.
Directory of Open Access Journals (Sweden)
PRAKASH PATIL
2012-05-01
Full Text Available The future short range wireless communication in an indoor environment jncludes the nondirected Infrared (IR Wireless communication. It is essential since there is a tremendous growth of bigger residential and commercial complexes. Also, nowadays use of portable devices such as LAPTOP, PDA etc. has been increased and the connectivity to such devices is the must without any interruption. In indoor environment both the transmitter and receiver are located inside the room. An empty rectangular is considered for the simulationpurpose. The major interest in this simulation deals with the diffuse configuration (Non-directed Non-LOS of the transmitter and the receiver. The IR wireless channel modeling is performed with multipath IR signals transmitted by the IR Transmitter and received by the receiver after multiple reflections from the reflecting surfaces such as ceiling, floor walls etc.Impulse response is the fundamental predictor of IR channel modeling and it is characterized by using Monte Carlo simulation.This paper estimates the mean received power and variance for different statistical distributions such as Rician, Gamma and Nakagami derived from histograms curve fitting for various receiver heights and radii. in time domain approach.
Statistical modelling of fish stocks
DEFF Research Database (Denmark)
Kvist, Trine
1999-01-01
for modelling the dynamics of a fish population is suggested. A new approach is introduced to analyse the sources of variation in age composition data, which is one of the most important sources of information in the cohort based models for estimation of stock abundancies and mortalities. The approach combines...... and it is argued that an approach utilising stochastic differential equations might be advantagous in fish stoch assessments....
Channel Measurements and Modelling for Indoor Power Line Communications
Directory of Open Access Journals (Sweden)
Zhang Peiling
2013-04-01
Full Text Available In order to obtain power line communications channel transmission characteristics, impulse responses measurements were performed on the basis of PN sequence’s excellent periodic autocorrelation properties. Meanwhile, a compensation method in frequency domain was proposed to improve the measurement precision. Then, the empirical multipath channel model of power line is presented from the measured results. The simulation and experimental measurement results not only have verified the efficiency of the proposed model, but also showed that the measurement method has fast, simple and convenient characteristic. Finally, the statistical characteristics of path amplitude and the delay spread are obtained through the analysis of measured results.
Yilmaz, Ferkan
2012-12-01
The higher-order statistics (HOS) of the channel capacity μn=E[logn (1+γ end)], where n ∈ N denotes the order of the statistics, has received relatively little attention in the literature, due in part to the intractability of its analysis. In this letter, we propose a novel and unified analysis, which is based on the moment generating function (MGF) technique, to exactly compute the HOS of the channel capacity. More precisely, our mathematical formalism can be readily applied to maximal-ratio-combining (MRC) receivers operating in generalized fading environments. The mathematical formalism is illustrated by some numerical examples focusing on the correlated generalized fading environments. © 2012 IEEE.
Quantile Probability and Statistical Data Modeling
Parzen, Emanuel
2004-01-01
Quantile and conditional quantile statistical thinking, as I have innovated it in my research since 1976, is outlined in this comprehensive survey and introductory course in quantile data analysis. We propose that a unification of the theory and practice of statistical methods of data modeling may be possible by a quantile perspective. Our broad range of topics of univariate and bivariate probability and statistics are best summarized by the key words. Two fascinating practical examples are g...
Sensitivity Analysis and Statistical Convergence of a Saltating Particle Model
Maldonado, S
2016-01-01
Saltation models provide considerable insight into near-bed sediment transport. This paper outlines a simple, efficient numerical model of stochastic saltation, which is validated against previously published experimental data on saltation in a channel of nearly horizontal bed. Convergence tests are systematically applied to ensure the model is free from statistical errors emanating from the number of particle hops considered. Two criteria for statistical convergence are derived; according to the first criterion, at least $10^3$ hops appear to be necessary for convergent results, whereas $10^4$ saltations seem to be the minimum required in order to achieve statistical convergence in accordance with the second criterion. Two empirical formulae for lift force are considered: one dependent on the slip (relative) velocity of the particle multiplied by the vertical gradient of the horizontal flow velocity component; the other dependent on the difference between the squares of the slip velocity components at the to...
Uncertainty the soul of modeling, probability & statistics
Briggs, William
2016-01-01
This book presents a philosophical approach to probability and probabilistic thinking, considering the underpinnings of probabilistic reasoning and modeling, which effectively underlie everything in data science. The ultimate goal is to call into question many standard tenets and lay the philosophical and probabilistic groundwork and infrastructure for statistical modeling. It is the first book devoted to the philosophy of data aimed at working scientists and calls for a new consideration in the practice of probability and statistics to eliminate what has been referred to as the "Cult of Statistical Significance". The book explains the philosophy of these ideas and not the mathematics, though there are a handful of mathematical examples. The topics are logically laid out, starting with basic philosophy as related to probability, statistics, and science, and stepping through the key probabilistic ideas and concepts, and ending with statistical models. Its jargon-free approach asserts that standard methods, suc...
Statistical Model-Based Face Pose Estimation
Institute of Scientific and Technical Information of China (English)
GE Xinliang; YANG Jie; LI Feng; WANG Huahua
2007-01-01
A robust face pose estimation approach is proposed by using face shape statistical model approach and pose parameters are represented by trigonometric functions. The face shape statistical model is firstly built by analyzing the face shapes from different people under varying poses. The shape alignment is vital in the process of building the statistical model. Then, six trigonometric functions are employed to represent the face pose parameters. Lastly, the mapping function is constructed between face image and face pose by linearly relating different parameters. The proposed approach is able to estimate different face poses using a few face training samples. Experimental results are provided to demonstrate its efficiency and accuracy.
Automated statistical modeling of analytical measurement systems
International Nuclear Information System (INIS)
The statistical modeling of analytical measurement systems at the Idaho Chemical Processing Plant (ICPP) has been completely automated through computer software. The statistical modeling of analytical measurement systems is one part of a complete quality control program used by the Remote Analytical Laboratory (RAL) at the ICPP. The quality control program is an integration of automated data input, measurement system calibration, database management, and statistical process control. The quality control program and statistical modeling program meet the guidelines set forth by the American Society for Testing Materials and American National Standards Institute. A statistical model is a set of mathematical equations describing any systematic bias inherent in a measurement system and the precision of a measurement system. A statistical model is developed from data generated from the analysis of control standards. Control standards are samples which are made up at precise known levels by an independent laboratory and submitted to the RAL. The RAL analysts who process control standards do not know the values of those control standards. The object behind statistical modeling is to describe real process samples in terms of their bias and precision and, to verify that a measurement system is operating satisfactorily. The processing of control standards gives us this ability
Chemical and statistical soot modeling
Blanquart, Guillaume
2008-01-01
The combustion of petroleum based fuels like kerosene, gasoline, or diesel leads to the formation of several kind of pollutants. Among them, soot particles are particularly bad for their severe consequences on human health. Over the past decades, strict regulations have been placed on car and aircraft engines in order to limit these particulate matter emissions. Designing low emission engines requires the use of predictive soot models which can be applied to the combustion of real fuels. ...
Quantum Biological Channel Modeling and Capacity Calculation
Directory of Open Access Journals (Sweden)
Ivan B. Djordjevic
2012-12-01
Full Text Available Quantum mechanics has an important role in photosynthesis, magnetoreception, and evolution. There were many attempts in an effort to explain the structure of genetic code and transfer of information from DNA to protein by using the concepts of quantum mechanics. The existing biological quantum channel models are not sufficiently general to incorporate all relevant contributions responsible for imperfect protein synthesis. Moreover, the problem of determination of quantum biological channel capacity is still an open problem. To solve these problems, we construct the operator-sum representation of biological channel based on codon basekets (basis vectors, and determine the quantum channel model suitable for study of the quantum biological channel capacity and beyond. The transcription process, DNA point mutations, insertions, deletions, and translation are interpreted as the quantum noise processes. The various types of quantum errors are classified into several broad categories: (i storage errors that occur in DNA itself as it represents an imperfect storage of genetic information, (ii replication errors introduced during DNA replication process, (iii transcription errors introduced during DNA to mRNA transcription, and (iv translation errors introduced during the translation process. By using this model, we determine the biological quantum channel capacity and compare it against corresponding classical biological channel capacity. We demonstrate that the quantum biological channel capacity is higher than the classical one, for a coherent quantum channel model, suggesting that quantum effects have an important role in biological systems. The proposed model is of crucial importance towards future study of quantum DNA error correction, developing quantum mechanical model of aging, developing the quantum mechanical models for tumors/cancer, and study of intracellular dynamics in general.
Different Manhattan project: automatic statistical model generation
Yap, Chee Keng; Biermann, Henning; Hertzmann, Aaron; Li, Chen; Meyer, Jon; Pao, Hsing-Kuo; Paxia, Salvatore
2002-03-01
We address the automatic generation of large geometric models. This is important in visualization for several reasons. First, many applications need access to large but interesting data models. Second, we often need such data sets with particular characteristics (e.g., urban models, park and recreation landscape). Thus we need the ability to generate models with different parameters. We propose a new approach for generating such models. It is based on a top-down propagation of statistical parameters. We illustrate the method in the generation of a statistical model of Manhattan. But the method is generally applicable in the generation of models of large geographical regions. Our work is related to the literature on generating complex natural scenes (smoke, forests, etc) based on procedural descriptions. The difference in our approach stems from three characteristics: modeling with statistical parameters, integration of ground truth (actual map data), and a library-based approach for texture mapping.
Directory of Open Access Journals (Sweden)
Mandana Samari Kermani
2016-01-01
Full Text Available The interaction of spherical solid particles with turbulent eddies in a 3-D turbulent channel flow with friction Reynolds number was studied. A generalized lattice Boltzmann equation (GLBE was used for computation of instantaneous turbulent flow field for which large eddy simulation (LES was employed. The sub-grid-scale (SGS turbulence effects were simulated through a shear-improved Smagorinsky model (SISM, which can predict turbulent near wall region without any wall function. Statistical properties of particles behavior such as root mean square (RMS velocities were studied as a function of dimensionless particle relaxation time ( by using a Lagrangian approach. Combination of SISM in GLBE with particle tracking analysis in turbulent channel flow is novelty of the present work. Both GLBE and SISM solve the flow field equations locally. This is an advantage of this method and makes it easy implementing. Comparison of the present results with previous available data indicated that SISM in GLBE is a reliable method for simulation of turbulent flows which is a key point to predict particles behavior correctly.
Axial electron channeling statistical method of site occupancy determination
Institute of Scientific and Technical Information of China (English)
YE; Jia
2001-01-01
Karman, Th., Zur theorie der spanungszustnde in plastischen und sandartigen medion, Nachr. Gesellsch. Wissensch., Gttingen, 1909.［17］Szczepinski, W., Introduction to the Mechanics of Plastic Forming of Metals, Netherlands: Sijthoff and Noordhoff, 1979.［18］Chen, W. F., Limit Analysis and Soil Plasticity, New York: Elsevier, 1975.［19］Yu, M. H., He, L. N., A new model and theory on yield and failure of materials under complex stress state, Mechanical Behaviors of Materials～6, Oxford: Pergamon Press, 1991, 3: 841—846.［20］Yu, M. H., New System of Strength Theory (in Chinese), Xi'an: Xi'an Jiaotong Universitry Press, 1992.［21］Yu, M. H., He, L. N., Song, L. Y., Twin shear stress theory and its generalization, Scientia Sinica (Science in China), Series A, 1985, 28(11): 1174—1183.［22］Yu, M. H., Yang, S. Y. et al., Unified elasto-plastic associated and non-associated constitutive model and its engineering applications, Computers and Structures, 1999, 71: 627—636.［23］Ma, G. W., Shoji, I., Plastic limit analysis of circular plates with respect to unified yield criterion, Int. J. Mech. Sci., 1998, 40(10): 963.［24］Ma, G. W., Hao, H., Unified plastic limit analyses of circular plates under arbitrary load, Journal of Applied Mechanics, ASME, 1999, 66(2): 568.［25］Qiang, H. F., Lu, N., Liu, B. J., Unified solutions of crack tip plastic zone under small scale yielding, Chinese Journal of Mechanical Engineering, (in Chinese with English abstract), 1999, 35(1): 34—38.［26］Yang, S. Y., Yu, M. H., Constitutive descriptions of multiphase poropus media, Acta Mechanica Sinica (in Chinese with English abstract), 2000, 32(1):11—24.［27］Yang, S. Y., Yu, M. H., An elasto-plastic damage model for saturated and unsaturated geomaterials, Acta Mechanica Sinica (in Chinese with English abstract), 2000, 32(2): 198—206.［28］Cheng, H. X., Li, J. J., Zhang, G. S. et al., Finite element analysis program system HAJIF(X), Chinese Journal of
Topology for statistical modeling of petascale data.
Energy Technology Data Exchange (ETDEWEB)
Pascucci, Valerio (University of Utah, Salt Lake City, UT); Mascarenhas, Ajith Arthur; Rusek, Korben (Texas A& M University, College Station, TX); Bennett, Janine Camille; Levine, Joshua (University of Utah, Salt Lake City, UT); Pebay, Philippe Pierre; Gyulassy, Attila (University of Utah, Salt Lake City, UT); Thompson, David C.; Rojas, Joseph Maurice (Texas A& M University, College Station, TX)
2011-07-01
This document presents current technical progress and dissemination of results for the Mathematics for Analysis of Petascale Data (MAPD) project titled 'Topology for Statistical Modeling of Petascale Data', funded by the Office of Science Advanced Scientific Computing Research (ASCR) Applied Math program. Many commonly used algorithms for mathematical analysis do not scale well enough to accommodate the size or complexity of petascale data produced by computational simulations. The primary goal of this project is thus to develop new mathematical tools that address both the petascale size and uncertain nature of current data. At a high level, our approach is based on the complementary techniques of combinatorial topology and statistical modeling. In particular, we use combinatorial topology to filter out spurious data that would otherwise skew statistical modeling techniques, and we employ advanced algorithms from algebraic statistics to efficiently find globally optimal fits to statistical models. This document summarizes the technical advances we have made to date that were made possible in whole or in part by MAPD funding. These technical contributions can be divided loosely into three categories: (1) advances in the field of combinatorial topology, (2) advances in statistical modeling, and (3) new integrated topological and statistical methods.
Epidemiology and Statistical Modeling in Burn Injuries
Sadeghi Bazargani, Homayoun
2010-01-01
An important issue in assessing the epidemiology of injuries, including burns, is the investigation of appropriate methodologies and statistical modeling techniques to study injuries in an efficient and trustworthy manner. The overall aim of this thesis is to analyze epidemiological patterns and assess the appropriateness of supervised statistical models to investigate burn risks and patterns. This thesis contains four papers: the first two concern descriptive epidemiology of burns in Arda...
Sustainable development - models and statistics
International Nuclear Information System (INIS)
What have environmental accounting, material flow accounting and environmental economic modelling taught us so far? This workshop is an event arranged by the ConAccount material flow accounting network, with an aim to bring together material flow accounting and environmental accounting. The objectives of the workshop are to discuss linkages of information systems for material flows and environmental accounts, to exchange experience, and to focus on the possibilities for analysis. The workshop is focused on the interface between material flows, economic and social development and environmental pressures. Attention is given to integrated methodological approaches dealing with explanation of trends and current status of industrial and societal metabolism and the development of future scenarios. The first day was devoted to plenary presentations that focus on the linkages between different aspects of environmental accounting and material flows. The second day was arranged in parallel sessions where the respective fields focus on presenting work within the respective areas. Parallel sessions: SEEA System of Economic and Environmental Accounts. MFA Material Flow Analysis, methodology and case studies SFA Substance Flow Analysis, methodology and case studies. At present, available conference contributions can only be accessed via Internet. However, a printed version is planned for mid-2002
Accelerated life models modeling and statistical analysis
Bagdonavicius, Vilijandas
2001-01-01
Failure Time DistributionsIntroductionParametric Classes of Failure Time DistributionsAccelerated Life ModelsIntroductionGeneralized Sedyakin's ModelAccelerated Failure Time ModelProportional Hazards ModelGeneralized Proportional Hazards ModelsGeneralized Additive and Additive-Multiplicative Hazards ModelsChanging Shape and Scale ModelsGeneralizationsModels Including Switch-Up and Cycling EffectsHeredity HypothesisSummaryAccelerated Degradation ModelsIntroductionDegradation ModelsModeling the Influence of Explanatory Varia
Matrix Tricks for Linear Statistical Models
Puntanen, Simo; Styan, George PH
2011-01-01
In teaching linear statistical models to first-year graduate students or to final-year undergraduate students there is no way to proceed smoothly without matrices and related concepts of linear algebra; their use is really essential. Our experience is that making some particular matrix tricks very familiar to students can substantially increase their insight into linear statistical models (and also multivariate statistical analysis). In matrix algebra, there are handy, sometimes even very simple "tricks" which simplify and clarify the treatment of a problem - both for the student and
Infinite Random Graphs as Statistical Mechanical Models
DEFF Research Database (Denmark)
Durhuus, Bergfinnur Jøgvan; Napolitano, George Maria
2011-01-01
We discuss two examples of infinite random graphs obtained as limits of finite statistical mechanical systems: a model of two-dimensional dis-cretized quantum gravity defined in terms of causal triangulated surfaces, and the Ising model on generic random trees. For the former model we describe a...
Discrete stochastic modeling of calcium channel dynamics
Baer, M E; Levine, H; Tsimring, L S; Baer, Markus; Falcke, Martin; Levine, Herbert; Tsimring, Lev S.
1999-01-01
We propose a simple discrete stochastic model for calcium dynamics in living cells. Specifically, the calcium concentration distribution is assumed to give rise to a set of probabilities for the opening/closing of channels which release calcium thereby changing those probabilities. We study this model in one dimension, analytically in the mean-field limit of large number of channels per site N, and numerically for small N. As the number of channels per site is increased, the transition from a non-propagating region of activity to a propagating one changes in nature from one described by directed percolation to that of deterministic depinning in a spatially discrete system. Also, for a small number of channels a propagating calcium wave can leave behind a novel fluctuation-driven state, in a parameter range where the limiting deterministic model exhibits only single pulse propagation.
Statistical physics of pairwise probability models
DEFF Research Database (Denmark)
Roudi, Yasser; Aurell, Erik; Hertz, John
2009-01-01
(dansk abstrakt findes ikke) Statistical models for describing the probability distribution over the states of biological systems are commonly used for dimensional reduction. Among these models, pairwise models are very attractive in part because they can be fit using a reasonable amount of data......: knowledge of the means and correlations between pairs of elements in the system is sufficient. Not surprisingly, then, using pairwise models for studying neural data has been the focus of many studies in recent years. In this paper, we describe how tools from statistical physics can be employed for studying...
Distributions with given marginals and statistical modelling
Fortiana, Josep; Rodriguez-Lallena, José
2002-01-01
This book contains a selection of the papers presented at the meeting `Distributions with given marginals and statistical modelling', held in Barcelona (Spain), July 17-20, 2000. In 24 chapters, this book covers topics such as the theory of copulas and quasi-copulas, the theory and compatibility of distributions, models for survival distributions and other well-known distributions, time series, categorical models, definition and estimation of measures of dependence, monotonicity and stochastic ordering, shape and separability of distributions, hidden truncation models, diagonal families, orthogonal expansions, tests of independence, and goodness of fit assessment. These topics share the use and properties of distributions with given marginals, this being the fourth specialised text on this theme. The innovative aspect of the book is the inclusion of statistical aspects such as modelling, Bayesian statistics, estimation, and tests.
Directory of Open Access Journals (Sweden)
CHEN, Z.
2014-11-01
Full Text Available Impulse noise in power line communication (PLC channel seriously degrades the performance of Multiple-Input Multiple-Output (MIMO system. To remedy this problem, a MIMO detection method based on fractional lower order statistics (FLOS for PLC channel with impulse noise is proposed in this paper. The alpha stable distribution is used to model impulse noise, and FLOS is applied to construct the criteria of MIMO detection. Then the optimal detection solution is obtained by recursive least squares algorithm. Finally, the transmitted signals in PLC MIMO system are restored with the obtained detection matrix. The proposed method does not require channel estimation and has low computational complexity. The simulation results show that the proposed method has a better PLC MIMO detection performance than the existing ones under impulsive noise environment.
Discrete Stochastic Modeling of Calcium Channel Dynamics
International Nuclear Information System (INIS)
We propose a discrete stochastic model for calcium dynamics in living cells. A set of probabilities for the opening/closing of calcium channels is assumed to depend on the calcium concentration. We study this model in one dimension, analytically in the limit of a large number of channels per site N , and numerically for small N . As the number of channels per site is increased, the transition from a nonpropagating region of activity to a propagating one changes from one described by directed percolation to that of deterministic depinning in a spatially discrete system. Also, for a small number of channels a propagating calcium wave can leave behind a novel fluctuation-driven state. (c) 2000 The American Physical Society
Advances in statistical models for data analysis
Minerva, Tommaso; Vichi, Maurizio
2015-01-01
This edited volume focuses on recent research results in classification, multivariate statistics and machine learning and highlights advances in statistical models for data analysis. The volume provides both methodological developments and contributions to a wide range of application areas such as economics, marketing, education, social sciences and environment. The papers in this volume were first presented at the 9th biannual meeting of the Classification and Data Analysis Group (CLADAG) of the Italian Statistical Society, held in September 2013 at the University of Modena and Reggio Emilia, Italy.
Cluster radiative emission and statistical models
Lusanna, L
1974-01-01
After reviewing some statistical models of multiple production, a cluster radiative emission picture in configuration space is proposed and, with the aid of an extension of the Gottfried model, the rapidity and mass distributions of clusters are determined. They agree with the independent cluster production model of Pokorski and Van Hove. (see CERN preprint TH-1772 (1971). Some connections with the thermodynamical model and some problems about the mass spectra are discussed. (17 refs).
Simple statistical model for branched aggregates
DEFF Research Database (Denmark)
Lemarchand, Claire; Hansen, Jesper Schmidt
2015-01-01
We propose a statistical model that can reproduce the size distribution of any branched aggregate, including amylopectin, dendrimers, molecular clusters of monoalcohols, and asphaltene nanoaggregates. It is based on the conditional probability for one molecule to form a new bond with a molecule......, given that it already has bonds with others. The model is applied here to asphaltene nanoaggregates observed in molecular dynamics simulations of Cooee bitumen. The variation with temperature of the probabilities deduced from this model is discussed in terms of statistical mechanics arguments. The...... relevance of the statistical model in the case of asphaltene nanoaggregates is checked by comparing the predicted value of the probability for one molecule to have exactly i bonds with the same probability directly measured in the molecular dynamics simulations. The agreement is satisfactory...
Performance modeling, loss networks, and statistical multiplexing
Mazumdar, Ravi
2009-01-01
This monograph presents a concise mathematical approach for modeling and analyzing the performance of communication networks with the aim of understanding the phenomenon of statistical multiplexing. The novelty of the monograph is the fresh approach and insights provided by a sample-path methodology for queueing models that highlights the important ideas of Palm distributions associated with traffic models and their role in performance measures. Also presented are recent ideas of large buffer, and many sources asymptotics that play an important role in understanding statistical multiplexing. I
Statistical Modeling for Radiation Hardness Assurance
Ladbury, Raymond L.
2014-01-01
We cover the models and statistics associated with single event effects (and total ionizing dose), why we need them, and how to use them: What models are used, what errors exist in real test data, and what the model allows us to say about the DUT will be discussed. In addition, how to use other sources of data such as historical, heritage, and similar part and how to apply experience, physics, and expert opinion to the analysis will be covered. Also included will be concepts of Bayesian statistics, data fitting, and bounding rates.
Statistical Physics and Modeling of Human Mobility
Gallotti, Riccardo
2013-01-01
In this thesis, we extend some ideas of statistical physics to describe the properties of human mobility. By using a database containing GPS measures of individual paths (position, velocity and covered space at a spatial scale of 2 Km or a time scale of 30 sec), which includes the 2% of the private vehicles in Italy, we succeed in determining some statistical empirical laws pointing out "universal" characteristics of human mobility. Developing simple stochastic models suggesting possible expl...
Model for neural signaling leap statistics
International Nuclear Information System (INIS)
We present a simple model for neural signaling leaps in the brain considering only the thermodynamic (Nernst) potential in neuron cells and brain temperature. We numerically simulated connections between arbitrarily localized neurons and analyzed the frequency distribution of the distances reached. We observed qualitative change between Normal statistics (with T 37.50C, awaken regime) and Levy statistics (T = 35.50C, sleeping period), characterized by rare events of long range connections.
Statistical Hot Spot Model for Explosive Detonation
Energy Technology Data Exchange (ETDEWEB)
Nichols, III, A L
2005-07-14
The Non-local Thermodynamic Equilibrium Statistical Hot Spot Model (NLTE SHS), a new model for explosive detonation, is described. In this model, the formation, ignition, propagation, and extinction of hot spots is explicitly modeled. The equation of state of the explosive mixture is treated with a non-local equilibrium thermodynamic assumption. A methodology for developing the parameters for the model is discussed, and applied to the detonation velocity diameter effect. Examination of these results indicates where future improvements to the model can be made.
Statistical Hot Spot Model for Explosive Detonation
Energy Technology Data Exchange (ETDEWEB)
Nichols III, A L
2004-05-10
The Non-local Thermodynamic Equilibrium Statistical Hot Spot Model (NLTE SHS), a new model for explosive detonation, is described. In this model, the formation, ignition, propagation, and extinction of hot spots is explicitly modeled. The equation of state of the explosive mixture is treated with a nonlocal equilibrium thermodynamic assumption. A methodology for developing the parameters for the model is discussed, and applied to the detonation velocity diameter effect. Examination of these results indicates where future improvements to the model can be made.
Growth curve models and statistical diagnostics
Pan, Jian-Xin
2002-01-01
Growth-curve models are generalized multivariate analysis-of-variance models. These models are especially useful for investigating growth problems on short times in economics, biology, medical research, and epidemiology. This book systematically introduces the theory of the GCM with particular emphasis on their multivariate statistical diagnostics, which are based mainly on recent developments made by the authors and their collaborators. The authors provide complete proofs of theorems as well as practical data sets and MATLAB code.
Statistical modelling for ship propulsion efficiency
DEFF Research Database (Denmark)
Petersen, Jóan Petur; Jacobsen, Daniel J.; Winther, Ole
2012-01-01
This paper presents a state-of-the-art systems approach to statistical modelling of fuel efficiency in ship propulsion, and also a novel and publicly available data set of high quality sensory data. Two statistical model approaches are investigated and compared: artificial neural networks and...... Gaussian processes (GP). The data presented is a publicly available full-scale data set, with a whole range of features sampled over a period of 2 months. We further discuss interpretations of the operational data in relation to the underlying physical system....
An R companion to linear statistical models
Hay-Jahans, Christopher
2011-01-01
Focusing on user-developed programming, An R Companion to Linear Statistical Models serves two audiences: those who are familiar with the theory and applications of linear statistical models and wish to learn or enhance their skills in R; and those who are enrolled in an R-based course on regression and analysis of variance. For those who have never used R, the book begins with a self-contained introduction to R that lays the foundation for later chapters.This book includes extensive and carefully explained examples of how to write programs using the R programming language. These examples cove
Bayesian models a statistical primer for ecologists
Hobbs, N Thompson
2015-01-01
Bayesian modeling has become an indispensable tool for ecological research because it is uniquely suited to deal with complexity in a statistically coherent way. This textbook provides a comprehensive and accessible introduction to the latest Bayesian methods-in language ecologists can understand. Unlike other books on the subject, this one emphasizes the principles behind the computations, giving ecologists a big-picture understanding of how to implement this powerful statistical approach. Bayesian Models is an essential primer for non-statisticians. It begins with a definition of probabili
Statistical modeling of the arterial vascular tree
Beck, Thomas; Godenschwager, Christian; Bauer, Miriam; Bernhardt, Dominik; Dillmann, Rüdiger
2011-03-01
Automatic examination of medical images becomes increasingly important due to the rising amount of data. Therefore automated methods are required which combine anatomical knowledge and robust segmentation to examine the structure of interest. We propose a statistical model of the vascular tree based on vascular landmarks and unbranched vessel sections. An undirected graph provides anatomical topology, semantics, existing landmarks and attached vessel sections. The atlas was built using semi-automatically generated geometric models of various body regions ranging from carotid arteries to the lower legs. Geometric models contain vessel centerlines as well as orthogonal cross-sections in equidistant intervals with the vessel contour having the form of a polygon path. The geometric vascular model is supplemented by anatomical landmarks which are not necessarily related to the vascular system. These anatomical landmarks define point correspondences which are used for registration with a Thin-Plate-Spline interpolation. After the registration process, the models were merged to form the statistical model which can be mapped to unseen images based on a subset of anatomical landmarks. This approach provides probability distributions for the location of landmarks, vessel-specific geometric properties including shape, expected radii and branching points and vascular topology. The applications of this statistical model include model-based extraction of the vascular tree which greatly benefits from vessel-specific geometry description and variation ranges. Furthermore, the statistical model can be applied as a basis for computer aided diagnosis systems as indicator for pathologically deformed vessels and the interaction with the geometric model is significantly more user friendly for physicians through anatomical names.
Computer Modelling of Channel Furnace
Czech Academy of Sciences Publication Activity Database
Musil, Ladislav; Matička, O.
Poznan: Politechnika Poznanska, 2003 - (Nawrowski, R.; Warchlewska, D.), s. 391-394 ISBN 83-912306-4-3. [Konferencja Naukowo - Techniczna /8./. Poznan/Kiekrz (PL), 07.05.2003-09.05.2003] R&D Projects: GA ČR GA102/03/0047 Keywords : electromagnetic field * computer modelling Subject RIV: JA - Electronics ; Optoelectronics, Electrical Engineering
Topology for Statistical Modeling of Petascale Data.
Energy Technology Data Exchange (ETDEWEB)
Bennett, Janine Camille; Pebay, Philippe Pierre; Pascucci, Valerio; Levine, Joshua; Gyulassy, Attila; Rojas, Joseph Maurice
2014-07-01
This document presents current technical progress and dissemination of results for the Mathematics for Analysis of Petascale Data (MAPD) project titled "Topology for Statistical Modeling of Petascale Data", funded by the Office of Science Advanced Scientific Computing Research (ASCR) Applied Math program.
Statistical Model Checking for Biological Systems
DEFF Research Database (Denmark)
David, Alexandre; Larsen, Kim Guldstrand; Legay, Axel;
2014-01-01
Statistical Model Checking (SMC) is a highly scalable simulation-based verification approach for testing and estimating the probability that a stochastic system satisfies a given linear temporal property. The technique has been applied to (discrete and continuous time) Markov chains, stochastic...
Statistical Modeling Efforts for Headspace Gas
International Nuclear Information System (INIS)
The purpose of this document is to describe the statistical modeling effort for gas concentrations in WIPP storage containers. The concentration (in ppm) of CO2 in the headspace volume of standard waste box (SWB) 68685 is shown. A Bayesian approach and an adaptive Metropolis-Hastings algorithm were used.
Statistical model semiquantitatively approximates arabinoxylooligosaccharides' structural diversity
DEFF Research Database (Denmark)
Dotsenko, Gleb; Nielsen, Michael Krogsgaard; Lange, Lene
2016-01-01
A statistical model describing the random distribution of substituted xylopyranosyl residues in arabinoxylooligosaccharides is suggested and compared with existing experimental data. Structural diversity of arabinoxylooligosaccharides of various length, originating from different arabinoxylans...... only for prediction and quantification of arabinoxylooligosaccharides' structural diversity, but also for estimate of yield and selection of the optimal source of arabinoxylan for production of arabinoxylooligosaccharides with desired structural features....
Statistical Modeling Efforts for Headspace Gas
Energy Technology Data Exchange (ETDEWEB)
Weaver, Brian Phillip [Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
2016-03-17
The purpose of this document is to describe the statistical modeling effort for gas concentrations in WIPP storage containers. The concentration (in ppm) of CO_{2} in the headspace volume of standard waste box (SWB) 68685 is shown. A Bayesian approach and an adaptive Metropolis-Hastings algorithm were used.
International Nuclear Information System (INIS)
We describe a method for computing linear observer statistics for maximum a posteriori (MAP) reconstructions of PET images. The method is based on a theoretical approximation for the mean and covariance of MAP reconstructions. In particular, we derive here a closed form for the channelized Hotelling observer (CHO) statistic applied to 2D MAP images. We show reasonably good correspondence between these theoretical results and Monte Carlo studies. The accuracy and low computational cost of the approximation allow us to analyze the observer performance over a wide range of operating conditions and parameter settings for the MAP reconstruction algorithm
The Channel Network model and field applications
International Nuclear Information System (INIS)
The Channel Network model describes the fluid flow and solute transport in fractured media. The model is based on field observations, which indicate that flow and transport take place in a three-dimensional network of connected channels. The channels are generated in the model from observed stochastic distributions and solute transport is modeled taking into account advection and rock interactions, such as matrix diffusion and sorption within the rock. The most important site-specific data for the Channel Network model are the conductance distribution of the channels and the flow-wetted surface. The latter is the surface area of the rock in contact with the flowing water. These parameters may be estimated from hydraulic measurements. For the Aespoe site, several borehole data sets are available, where a packer distance of 3 meters was used. Numerical experiments were performed in order to study the uncertainties in the determination of the flow-wetted surface and conductance distribution. Synthetic data were generated along a borehole and hydraulic tests with different packer distances were simulated. The model has previously been used to study the Long-term Pumping and Tracer Test (LPT2) carried out in the Aespoe Hard Rock Laboratory (HRL) in Sweden, where the distance travelled by the tracers was of the order hundreds of meters. Recently, the model has been used to simulate the tracer tests performed in the TRUE experiment at HRL, with travel distance of the order of tens of meters. Several tracer tests with non-sorbing and sorbing species have been performed
A statistical model for mapping morphological shape
Li Jiahan; Das Kiranmoy; Berg Arthur; Fu Guifang; Li Runze; Wu Rongling
2010-01-01
Abstract Background Living things come in all shapes and sizes, from bacteria, plants, and animals to humans. Knowledge about the genetic mechanisms for biological shape has far-reaching implications for a range spectrum of scientific disciplines including anthropology, agriculture, developmental biology, evolution and biomedicine. Results We derived a statistical model for mapping specific genes or quantitative trait loci (QTLs) that control morphological shape. The model was formulated with...
Statistical Model Checking for Stochastic Hybrid Systems
DEFF Research Database (Denmark)
David, Alexandre; Du, Dehui; Larsen, Kim Guldstrand; Legay, Axel; Mikučionis, Marius; Poulsen, Danny Bøgsted; Sedwards, Sean
This paper presents novel extensions and applications of the UPPAAL-SMC model checker. The extensions allow for statistical model checking of stochastic hybrid systems. We show how our race-based stochastic semantics extends to networks of hybrid systems, and indicate the integration technique...... applied for implementing this semantics in the UPPAAL-SMC simulation engine. We report on two applications of the resulting tool-set coming from systems biology and energy aware buildings....
Directed Models For Statistical Relational Learning
Khosravi, Hassan
2012-01-01
Statistical Relational Learning is a new branch of machine learning that aims to model a joint distribution over relational data. Relational data consists of different types of objects where each object is characterized with a different set of attributes. The structure of relational data presents an opportunity for objects to carry additional information via their links and enables the model to show correlations among objects and their relationships. This dissertation focuses on learning gra...
Statistical analysis of the factors induced defect formation during welding tubes for fuel channels
International Nuclear Information System (INIS)
Using as an example the welding of the mounting joints of 160x10mm 08Kh18N10T steel tubes for fuel channels of the RBM-K-1000 reactor, considered is the effect of the three main factors, causing formation of the defects in welded joints: constructional, technological and organizational. Emperic equations of the defectiveness and the above mentioned factors for the statistical analysis of the welding quality during the mounting of nuclear power stations are suggested
Performance modeling, stochastic networks, and statistical multiplexing
Mazumdar, Ravi R
2013-01-01
This monograph presents a concise mathematical approach for modeling and analyzing the performance of communication networks with the aim of introducing an appropriate mathematical framework for modeling and analysis as well as understanding the phenomenon of statistical multiplexing. The models, techniques, and results presented form the core of traffic engineering methods used to design, control and allocate resources in communication networks.The novelty of the monograph is the fresh approach and insights provided by a sample-path methodology for queueing models that highlights the importan
Statistical physics of pairwise probability models
Directory of Open Access Journals (Sweden)
Yasser Roudi
2009-11-01
Full Text Available Statistical models for describing the probability distribution over the states of biological systems are commonly used for dimensional reduction. Among these models, pairwise models are very attractive in part because they can be fit using a reasonable amount of data: knowledge of the means and correlations between pairs of elements in the system is sufficient. Not surprisingly, then, using pairwise models for studying neural data has been the focus of many studies in recent years. In this paper, we describe how tools from statistical physics can be employed for studying and using pairwise models. We build on our previous work on the subject and study the relation between different methods for fitting these models and evaluating their quality. In particular, using data from simulated cortical networks we study how the quality of various approximate methods for inferring the parameters in a pairwise model depends on the time bin chosen for binning the data. We also study the effect of the size of the time bin on the model quality itself, again using simulated data. We show that using finer time bins increases the quality of the pairwise model. We offer new ways of deriving the expressions reported in our previous work for assessing the quality of pairwise models.
Equilibrium statistical mechanics of lattice models
Lavis, David A
2015-01-01
Most interesting and difficult problems in equilibrium statistical mechanics concern models which exhibit phase transitions. For graduate students and more experienced researchers this book provides an invaluable reference source of approximate and exact solutions for a comprehensive range of such models. Part I contains background material on classical thermodynamics and statistical mechanics, together with a classification and survey of lattice models. The geometry of phase transitions is described and scaling theory is used to introduce critical exponents and scaling laws. An introduction is given to finite-size scaling, conformal invariance and Schramm—Loewner evolution. Part II contains accounts of classical mean-field methods. The parallels between Landau expansions and catastrophe theory are discussed and Ginzburg—Landau theory is introduced. The extension of mean-field theory to higher-orders is explored using the Kikuchi—Hijmans—De Boer hierarchy of approximations. In Part III the use of alge...
Statistical Compressed Sensing of Gaussian Mixture Models
Yu, Guoshen
2011-01-01
A novel framework of compressed sensing, namely statistical compressed sensing (SCS), that aims at efficiently sampling a collection of signals that follow a statistical distribution, and achieving accurate reconstruction on average, is introduced. SCS based on Gaussian models is investigated in depth. For signals that follow a single Gaussian model, with Gaussian or Bernoulli sensing matrices of O(k) measurements, considerably smaller than the O(k log(N/k)) required by conventional CS based on sparse models, where N is the signal dimension, and with an optimal decoder implemented via linear filtering, significantly faster than the pursuit decoders applied in conventional CS, the error of SCS is shown tightly upper bounded by a constant times the best k-term approximation error, with overwhelming probability. The failure probability is also significantly smaller than that of conventional sparsity-oriented CS. Stronger yet simpler results further show that for any sensing matrix, the error of Gaussian SCS is u...
Statistical Modelling of Wind Proles - Data Analysis and Modelling
DEFF Research Database (Denmark)
Jónsson, Tryggvi; Pinson, Pierre
The aim of the analysis presented in this document is to investigate whether statistical models can be used to make very short-term predictions of wind profiles.......The aim of the analysis presented in this document is to investigate whether statistical models can be used to make very short-term predictions of wind profiles....
A Noisy-Channel Model for Document Compression
Daumé, Hal
2009-01-01
We present a document compression system that uses a hierarchical noisy-channel model of text production. Our compression system first automatically derives the syntactic structure of each sentence and the overall discourse structure of the text given as input. The system then uses a statistical hierarchical model of text production in order to drop non-important syntactic and discourse constituents so as to generate coherent, grammatical document compressions of arbitrary length. The system outperforms both a baseline and a sentence-based compression system that operates by simplifying sequentially all sentences in a text. Our results support the claim that discourse knowledge plays an important role in document summarization.
Consumption Model Calibration and Related Statistical Problems
Czech Academy of Sciences Publication Activity Database
Brabec, Marek; Malý, Marek; Pelikán, Emil; Konár, Ondřej
Athens: WSEAS Press, 2009 - (Perlovsky, L.; Dionysiou, D.; Kostic, L.; Gonzalez-Concepcion, C.; Jaberg, H.; Mastorakis, N.; Zaharim, A.; Sopian, K.), s. 141-146 ISBN 978-960-474-091-8. [AEBD '09. World Multiconference on Applied Economics, Business and Development . Tenerife (ES), 01.07.2009-03.07.2009] R&D Projects: GA AV ČR 1ET400300513 Institutional research plan: CEZ:AV0Z10300504 Keywords : linear calibration * natural gas consumption modeling * Bayesian approach * statistical model * time-varying calibration * state-space model Subject RIV: JE - Non-nuclear Energetics, Energy Consumption ; Use
Does the choice of the forcing term affect flow statistics in DNS of turbulent channel flow?
Quadrio, Maurizio; Hasegawa, Yosuke
2015-01-01
We seek possible statistical consequences of the way a forcing term is added to the Navier--Stokes equations in the Direct Numerical Simulation (DNS) of incompressible channel flow. Simulations driven by constant flow rate, constant pressure gradient and constant power input are used to build large databases, and in particular to store the complete temporal trace of the wall-shear stress for later analysis. As these approaches correspond to different dynamical systems, it can in principle be envisaged that these differences are reflect by certain statistics of the turbulent flow field. The instantaneous realizations of the flow in the various simulations are obviously different, but, as expected, the usual one-point, one-time statistics do not show any appreciable difference. However, the PDF for the fluctuations of the streamwise component of wall friction reveals that the simulation with constant flow rate presents lower probabilities for extreme events of large positive friction. The low probability value ...
Introduction to statistical models and non-extensive statistics
Biro, T. S.
2005-01-01
Quark matter is being expected to be found in heavy ion collisions on the basis of calculations in the framework of traditional, extensive thermodynamics. Recently a non-extensive generalization of the thermodynamics is emerging in the theoretical research. We review here some basic concepts in statistics, kinetic theory and thermodynamics, in particular those encountered in non-extensive thermodynamics. This offers an introduction into the theoretical basis of considering non-extensive parto...
Statistical Modeling of Retinal Optical Coherence Tomography.
Amini, Zahra; Rabbani, Hossein
2016-06-01
In this paper, a new model for retinal Optical Coherence Tomography (OCT) images is proposed. This statistical model is based on introducing a nonlinear Gaussianization transform to convert the probability distribution function (pdf) of each OCT intra-retinal layer to a Gaussian distribution. The retina is a layered structure and in OCT each of these layers has a specific pdf which is corrupted by speckle noise, therefore a mixture model for statistical modeling of OCT images is proposed. A Normal-Laplace distribution, which is a convolution of a Laplace pdf and Gaussian noise, is proposed as the distribution of each component of this model. The reason for choosing Laplace pdf is the monotonically decaying behavior of OCT intensities in each layer for healthy cases. After fitting a mixture model to the data, each component is gaussianized and all of them are combined by Averaged Maximum A Posterior (AMAP) method. To demonstrate the ability of this method, a new contrast enhancement method based on this statistical model is proposed and tested on thirteen healthy 3D OCTs taken by the Topcon 3D OCT and five 3D OCTs from Age-related Macular Degeneration (AMD) patients, taken by Zeiss Cirrus HD-OCT. Comparing the results with two contending techniques, the prominence of the proposed method is demonstrated both visually and numerically. Furthermore, to prove the efficacy of the proposed method for a more direct and specific purpose, an improvement in the segmentation of intra-retinal layers using the proposed contrast enhancement method as a preprocessing step, is demonstrated. PMID:26800532
STATISTICAL MODELS USED IN PROJECT MANAGEMENT
Georgeta-Narcisa CIOBOTAR
2009-01-01
“Statistical Models used in Project Management” is approaching major interest issues within the actual research context, when research activities are grouped per project. An observer of the phenomena taking place today in the higher education and research can not fail to notice the importance of scientific research have achieved through programs or projects as part of European higher education and the need to establish closer links between Common European Higher Education Area and European Re...
Polyhedral approach to statistical learning graphical models
Czech Academy of Sciences Publication Activity Database
Studený, Milan; Hemmecke, R.; Vomlel, Jiří; Lindner, S.
Osaka : JST CREST, 2010. s. 1-4. [The 2nd CREST-SBM International Conference "Harmony of Groebner Bases and the Moderm Industrial Socienty". 28.06.2010-02.07.2010, Hotel Hankyu Expo Park, Osaka] Institutional research plan: CEZ:AV0Z10750506 Keywords : Bayesian network * polyhedral approach * imset Subject RIV: BA - General Mathematics http://library.utia.cas.cz/separaty/2010/MTR/studeny-polyhedral approach to statistical learning graphical models.pdf
Invariant geometric structures on statistical models
Czech Academy of Sciences Publication Activity Database
Schwachhöfer, L.; Ay, N.; Jost, J.; Le, Hong-Van
Cham: Springer, 2015 - (Nielsen, F.; Barbaresco, F.), s. 150-158. (Lecture Notes in Computer Science. 9389). ISBN 978-3-319-25039-7. [International Conference on Geometric Science of Information (GSI) 2015 /2./. Palaiseau (FR), 28.10.2015-30.10.2015] Institutional support: RVO:67985840 Keywords : geometric structures * statistical models Subject RIV: BA - General Mathematics http://link.springer.com/chapter/10.1007/978-3-319-25040-3_17
Invariant geometric structures on statistical models
Czech Academy of Sciences Publication Activity Database
Schwachhöfer, L.; Ay, N.; Jost, J.; Le, Hong-Van
Cham : Springer, 2015 - (Nielsen, F.; Barbaresco, F.), s. 150-158 ISBN 978-3-319-25039-7. - (Lecture Notes in Computer Science. 9389). [International Conference on Geometric Science of Information (GSI) 2015 /2./. Palaiseau (FR), 28.10.2015-30.10.2015] Institutional support: RVO:67985840 Keywords : geometric structures * statistical models Subject RIV: BA - General Mathematics http://link.springer.com/chapter/10.1007/978-3-319-25040-3_17
Institute of Scientific and Technical Information of China (English)
Zhao Zhi-Jin; Zheng Shi-Lian; Xu Chun-Yun; Kong Xian-Zheng
2007-01-01
Hidden Markov models (HMMs) have been used to model burst error sources of wireless channels. This paper proposes a hybrid method of using genetic algorithm (GA) and simulated annealing (SA) to train HMM for discrete channel modelling. The proposed method is compared with pure GA, and experimental results show that the HMMs trained by the hybrid method can better describe the error sequences due to SA's ability of facilitating hill-climbing at the later stage of the search. The burst error statistics of the HMMs trained by the proposed method and the corresponding error sequences are also presented to validate the proposed method.
Yilmaz, Ferkan
2010-01-01
In this paper, we present a unified approach to analyze the exact statistical characteristics of the harmonic mean of N ≥ 2 statistically independent and non-identically distributed random variables (RVs), which we term the N-normalized harmonic distribution (i.e., NHD distribution), for the purpose of modeling the amplify-and-forward multihop relay channels. We present exact statistical metrics for the moments-generating function (MGF), moments (Mellin moments-generating function), probability density function (PDF) and cumulative distribution function (CDF) of the NHD distribution. Aside from unifying past results based on the geometric-mean approximation of the harmonic-mean, our approach relies on the algebraic combination of Mellin and Laplace transforms to obtain exact single integral expressions which can be easily computed using the Gauss-Laguerre quadrature rule or can be readily expressed in terms of the multivariable Meijer\\'s G of Fox\\'s H functions. Numerical and simulation results, performed to verify the correctness of the proposed formulation, are in perfect agreement. The proposed formulation can be used to analyze the performance measures of the amplify-and-forward multihop relay channels such as outage probability, outage capacity, average capacity and average bit error probabilities. © 2009 IEEE.
Modelling debris flows down general channels
Directory of Open Access Journals (Sweden)
S. P. Pudasaini
2005-01-01
Full Text Available This paper is an extension of the single-phase cohesionless dry granular avalanche model over curved and twisted channels proposed by Pudasaini and Hutter (2003. It is a generalisation of the Savage and Hutter (1989, 1991 equations based on simple channel topography to a two-phase fluid-solid mixture of debris material. Important terms emerging from the correct treatment of the kinematic and dynamic boundary condition, and the variable basal topography are systematically taken into account. For vanishing fluid contribution and torsion-free channel topography our new model equations exactly degenerate to the previous Savage-Hutter model equations while such a degeneration was not possible by the Iverson and Denlinger (2001 model, which, in fact, also aimed to extend the Savage and Hutter model. The model equations of this paper have been rigorously derived; they include the effects of the curvature and torsion of the topography, generally for arbitrarily curved and twisted channels of variable channel width. The equations are put into a standard conservative form of partial differential equations. From these one can easily infer the importance and influence of the pore-fluid-pressure distribution in debris flow dynamics. The solid-phase is modelled by applying a Coulomb dry friction law whereas the fluid phase is assumed to be an incompressible Newtonian fluid. Input parameters of the equations are the internal and bed friction angles of the solid particles, the viscosity and volume fraction of the fluid, the total mixture density and the pore pressure distribution of the fluid at the bed. Given the bed topography and initial geometry and the initial velocity profile of the debris mixture, the model equations are able to describe the dynamics of the depth profile and bed parallel depth-averaged velocity distribution from the initial position to the final deposit. A shock capturing, total variation diminishing numerical scheme is implemented to
Strings, Integrable Systems, Geometry and Statistical Models
Marshakov, A
2004-01-01
The role of integrable systems in string theory is discussed. We remind old examples of the correspondence between stringy partition functions or effective actions and integrable equations, based on effective application of the matrix model technique. Then we turn to a new example, coming from the Nekrasov deformation of the Seiberg-Witten prepotential. In the last case the deformed theory is described by a different statistical model, which becomes equivalent to a partition function of a topological string. The full partition function of string theory arises therefore always as a certain "quantization" of its quasiclassical geometry.
A Wideband Channel Model for Intravehicular Nomadic Systems
Directory of Open Access Journals (Sweden)
François Bellens
2011-01-01
Full Text Available The increase in electronic entertainment equipments within vehicles has rendered the idea of replacing the wired links with intra-vehicle personal area networks. Ultra-wideband (UWB seems an appropriate candidate technology to meet the required data rates for interconnecting such devices. In particular, the multiband OFDM (MB-OFDM is able to provide very high transfer rates (up to 480 MBps over relatively short distances and low transmit power. In order to evaluate the performances of UWB systems within vehicles, a reliable channel model is needed. In this paper, a nomadic system where a base station placed in the center of the dashboard wants to communicate with fixed devices placed at the rear seat is investigated. A single-input single-output (SISO channel model for intra-vehicular communication (IVC systems is proposed, based on reverberation chamber theory. The model is based on measurements conducted in real traffic conditions, with a varying number of passengers in the car. Temporal variations of the wireless channels are also characterized and parametrized. The proposed model is validated by comparing model-independent statistics with the measurements.
A Dynamic Wideband Directional Channel Model for Vehicle-to-Vehicle Communications
He, Ruisi; Renaudin, Olivier; Kolmonen, Veli-Matti; Haneda, Katsuyuki; Zhong, Zhangdui; Ai, Bo; Oestges, Claude
2015-01-01
Vehicle-to-vehicle (V2V) communications have received a lot of attention due to their numerous applications in traffic safety. The design, testing, and improvement of the V2V system hinge critically on the understanding of the propagation channels. An important feature of the V2V channel is the time variance. To statistically model the time-variant V2V channels, a dynamic wideband directional channel model is proposed in this paper, based on measurements conducted at 5.3 GHz in suburban, urba...
A survey of statistical network models
Goldenberg, Anna; Fienberg, Stephen E; Airoldi, Edoardo M
2009-01-01
Networks are ubiquitous in science and have become a focal point for discussion in everyday life. Formal statistical models for the analysis of network data have emerged as a major topic of interest in diverse areas of study, and most of these involve a form of graphical representation. Probability models on graphs date back to 1959. Along with empirical studies in social psychology and sociology from the 1960s, these early works generated an active network community and a substantial literature in the 1970s. This effort moved into the statistical literature in the late 1970s and 1980s, and the past decade has seen a burgeoning network literature in statistical physics and computer science. The growth of the World Wide Web and the emergence of online networking communities such as Facebook, MySpace, and LinkedIn, and a host of more specialized professional network communities has intensified interest in the study of networks and network data. Our goal in this review is to provide the reader with an entry poin...
Radio Channel Modelling Using Stochastic Propagation Graphs
DEFF Research Database (Denmark)
Pedersen, Troels; Fleury, Bernard Henri
2007-01-01
In this contribution the radio channel model proposed in [1] is extended to include multiple transmitters and receivers. The propagation environment is modelled using random graphs where vertices of a graph represent scatterers and edges model the wave propagation between scatterers. Furthermore......, we develop a closed form analytical expression for the transfer matrix of the propagation graph. It is shown by simulation that impulse response and the delay-power spectrum of the graph exhibit exponentially decaying power as a result of the recursive scattering structure of the graph. The impulse...
Statistical entropy of a nuclear spectrometer vis-a-vis communication channel
International Nuclear Information System (INIS)
The aim of this paper is to present an esoteric model of a nuclear spectrometer e.g. a gamma ray spectrometer as a communication channel. The source entropy, receiver entropy, and joint entropy of a gamma ray spectrometer were estimated for an observed 1 K gamma spectrum containing a 662 keV peak from a 137Cs source. The information loss estimated for the observed gamma spectrum was of the order of 94.5%. In a typical communication engineering channel, the information loss is of the order of 30%. The information loss in a gamma spectrometer is far more than that in a communication channel. Hence the information extraction in a nuclear spectrometer is extremely challenging vis-a-vis communication channel. This also explains high redundancy of spectral channels, and justifies that a priori information required is much more than the a posteriori information extracted in nuclear spectrometers. Also the model amply justifies wide ranging results for the IAEA intercomparison of spectral analysis programs in which 212 results from 163 laboratories from 34 countries were compared
Does the choice of the forcing term affect flow statistics in DNS of turbulent channel flow?
Quadrio, Maurizio; Frohnapfel, Bettina; Hasegawa, Yosuke
2016-01-01
We seek possible statistical consequences of the way a forcing term is added to the Navier--Stokes equations in the Direct Numerical Simulation (DNS) of incompressible channel flow. Simulations driven by constant flow rate, constant pressure gradient and constant power input are used to build large databases, and in particular to store the complete temporal trace of the wall-shear stress for later analysis. As these approaches correspond to different dynamical systems, it can in principle be envisaged that these differences are reflect by certain statistics of the turbulent flow field. The instantaneous realizations of the flow in the various simulations are obviously different, but, as expected, the usual one-point, one-time statistics do not show any appreciable difference. However, the PDF for the fluctuations of the streamwise component of wall friction reveals that the simulation with constant flow rate presents lower probabilities for extreme events of large positive friction. The low probability value of such events explains their negligible contribution to the commonly computed statistics; however, the very existence of a difference in the PDF demonstrates that the forcing term is not entirely uninfluential. Other statistics for wall-based quantities (the two components of friction and pressure) are examined; in particular spatio-temporal autocorrelations show small differences at large temporal separations, where unfortunately the residual statistical uncertainty is still of the same order of the observed difference. Hence we suggest that the specific choice of the forcing term does not produce important statistical consequences, unless one is interested in the strongest events of high wall friction, that are underestimated by a simulation run at constant flow rate.
Directory of Open Access Journals (Sweden)
G. Sofia
2011-05-01
Full Text Available A statistical approach to LiDAR derived topographic attributes for the automatic extraction of channel network and for the choice of the scale to apply for parameter evaluation is presented in this paper. The basis of this approach is to use distribution analysis and statistical descriptors to identify channels where terrain geometry denotes significant convergences. Two case study areas with different morphology and degree of organization are used with their 1 m LiDAR Digital Terrain Models (DTMs. Topographic attribute maps (curvature and openness for various window sizes are derived from the DTMs in order to detect surface convergences. A statistical analysis on value distributions considering each window size is carried out for the choice of the optimum kernel. We propose a three-step method to extract the network based (a on the normalization and overlapping of openness and minimum curvature to highlight the more likely surface convergences, (b a weighting of the upslope area according to these normalized maps to identify drainage flow paths and flow accumulation consistent with terrain geometry, (c the standard score normalization of the weighted upslope area and the use of standard score values as non subjective threshold for channel network identification. As a final step for optimal definition and representation of the whole network, a noise-filtering and connection procedure is applied. The advantage of the proposed methodology, and the efficiency and accurate localization of extracted features are demonstrated using LiDAR data of two different areas and comparing both extractions with field surveyed networks.
Effects of roughness on density-weighted particle statistics in turbulent channel flows
Energy Technology Data Exchange (ETDEWEB)
Milici, Barbara [Faculty of Engineering and Architecture, Cittadella Universitaria - 94100 - Enna (Italy)
2015-12-31
The distribution of inertial particles in turbulent flows is strongly influenced by the characteristics of the coherent turbulent structures which develop in the carrier flow field. In wall-bounded flows, these turbulent structures, which control the turbulent regeneration cycles, are strongly affected by the roughness of the wall, nevertheless its effects on the particle transport in two-phase turbulent flows has been still poorly investigated. The issue is discussed here by addressing DNS combined with LPT to obtain statistics of velocity and preferential accumulation of a dilute dispersion of heavy particles in a turbulent channel flow, bounded by irregular two-dimensional rough surfaces, in the one-way coupling regime.
Effects of roughness on density-weighted particle statistics in turbulent channel flows
Milici, Barbara
2015-12-01
The distribution of inertial particles in turbulent flows is strongly influenced by the characteristics of the coherent turbulent structures which develop in the carrier flow field. In wall-bounded flows, these turbulent structures, which control the turbulent regeneration cycles, are strongly affected by the roughness of the wall, nevertheless its effects on the particle transport in two-phase turbulent flows has been still poorly investigated. The issue is discussed here by addressing DNS combined with LPT to obtain statistics of velocity and preferential accumulation of a dilute dispersion of heavy particles in a turbulent channel flow, bounded by irregular two-dimensional rough surfaces, in the one-way coupling regime.
Statistical Analysis of Multipath Fading Channels Using Generalizations of Shot Noise
Directory of Open Access Journals (Sweden)
Djouadi SeddikM
2008-01-01
Full Text Available Abstract This paper provides a connection between the shot-noise analysis of Rice and the statistical analysis of multipath fading wireless channels when the received signals are a low-pass signal and a bandpass signal. Under certain conditions, explicit expressions are obtained for autocorrelation functions, power spectral densities, and moment-generating functions. In addition, a central limit theorem is derived identifying the mean and covariance of the received signals, which is a generalization of Campbell_s theorem. The results are easily applicable to transmitted signals which are random and to CDMA signals.
Modelling of meander migration in an incised channel
Institute of Scientific and Technical Information of China (English)
Jianchun HUANG; Blair P GREIMANN; Timothy J RANDLE
2014-01-01
An updated linear computer model for meandering rivers with incision has been developed. The model simulates the bed topography, flow field, and bank erosion rate in an incised meandering channel. In a scenario where the upstream sediment load decreases (e.g., after dam closure or soil conservation), alluvial river experiences cross section deepening and slope flattening. The channel migration rate might be affected in two ways:decreased channel slope and steeped bank height. The proposed numerical model combines the traditional one-dimensional (1D) sediment transport model in simulating the channel erosion and the linear model for channel meandering. A non-equilibrium sediment transport model is used to update the channel bed elevation and gradations. A linear meandering model was used to calculate the channel alignment and bank erosion/accretion, which in turn was used by the 1D sediment transport model. In the 1D sediment transport model, the channel bed elevation and gradations are represented in each channel cross section. In the meandering model, the bed elevation and gradations are stored in two dimensional (2D) cells to represent the channel and terrain properties (elevation and gradation). A new method is proposed to exchange information regarding bed elevations and bed material fractions between 1D river geometry and 2D channel and terrain. The ability of the model is demonstrated using the simulation of the laboratory channel migration of Friedkin in which channel incision occurs at the upstream end.
A statistical model of aggregate fragmentation
International Nuclear Information System (INIS)
A statistical model of fragmentation of aggregates is proposed, based on the stochastic propagation of cracks through the body. The propagation rules are formulated on a lattice and mimic two important features of the process—a crack moves against the stress gradient while dissipating energy during its growth. We perform numerical simulations of the model for two-dimensional lattice and reveal that the mass distribution for small- and intermediate-size fragments obeys a power law, F(m)∝m−3/2, in agreement with experimental observations. We develop an analytical theory which explains the detected power law and demonstrate that the overall fragment mass distribution in our model agrees qualitatively with that one observed in experiments. (paper)
Statistical modeling approach for detecting generalized synchronization.
Schumacher, Johannes; Haslinger, Robert; Pipa, Gordon
2012-05-01
Detecting nonlinear correlations between time series presents a hard problem for data analysis. We present a generative statistical modeling method for detecting nonlinear generalized synchronization. Truncated Volterra series are used to approximate functional interactions. The Volterra kernels are modeled as linear combinations of basis splines, whose coefficients are estimated via l(1) and l(2) regularized maximum likelihood regression. The regularization manages the high number of kernel coefficients and allows feature selection strategies yielding sparse models. The method's performance is evaluated on different coupled chaotic systems in various synchronization regimes and analytical results for detecting m : n phase synchrony are presented. Experimental applicability is demonstrated by detecting nonlinear interactions between neuronal local field potentials recorded in different parts of macaque visual cortex. PMID:23004851
Statistical Decision-Tree Models for Parsing
Magerman, D M
1995-01-01
Syntactic natural language parsers have shown themselves to be inadequate for processing highly-ambiguous large-vocabulary text, as is evidenced by their poor performance on domains like the Wall Street Journal, and by the movement away from parsing-based approaches to text-processing in general. In this paper, I describe SPATTER, a statistical parser based on decision-tree learning techniques which constructs a complete parse for every sentence and achieves accuracy rates far better than any published result. This work is based on the following premises: (1) grammars are too complex and detailed to develop manually for most interesting domains; (2) parsing models must rely heavily on lexical and contextual information to analyze sentences accurately; and (3) existing {$n$}-gram modeling techniques are inadequate for parsing models. In experiments comparing SPATTER with IBM's computer manuals parser, SPATTER significantly outperforms the grammar-based parser. Evaluating SPATTER against the Penn Treebank Wall ...
Polyhedral approach to statistical learning graphical models
Czech Academy of Sciences Publication Activity Database
Studený, Milan; Haws, D.; Hemmecke, R.; Lindner, S.
Singapore : World Scientific Press, 2012, s. 346-372. ISBN 978-981-4383-45-5. [The 2nd CREST-SBM International Conference "Harmony of Groebner Bases and the Modern Industrial Society". Osaka (JP), 28.06.2012-2.07.2012] R&D Projects: GA ČR GA201/08/0539 Institutional support: RVO:67985556 Keywords : Bayesian network stucture * standard imset * characteristic imset * polyhedral geometry Subject RIV: BA - General Mathematics http://library.utia.cas.cz/separaty/2012/MTR/studeny-polyhedral approach to statistical learning graphical models.pdf
Distributed Parametric and Statistical Model Checking
Directory of Open Access Journals (Sweden)
Peter Bulychev
2011-10-01
Full Text Available Statistical Model Checking (SMC is a trade-off between testing and formal verification. The core idea of the approach is to conduct some simulations of the system and verify if they satisfy some given property. In this paper we show that SMC is easily parallelizable on a master/slaves architecture by introducing a series of algorithms that scale almost linearly with respect to the number of slave computers. Our approach has been implemented in the UPPAAL SMC toolset and applied on non-trivial case studies.
Projecting Policy Effects with Statistical Models Projecting Policy Effects with Statistical Models
Directory of Open Access Journals (Sweden)
Christopher Sims
1988-03-01
Full Text Available This paper attempts to briefly discus the current frontiers in quantitative modeling for forecastina and policy analvsis. It does so by summarizing some recent developmenrs in three areas: reduced form forecasting models; theoretical models including elements of stochastic optimization; and identification. In the process, the paper tries to provide some remarks on the direction we seem to be headed. Projecting Policy Effects with Statistical Models
Statistical modelling of tropical cyclone tracks: modelling cyclone lysis
Hall, T; Hall, Tim; Jewson, Stephen
2005-01-01
We describe results from the fifth stage of a project to build a statistical model of tropical cyclone tracks. The previous stages considered genesis and the shape of tracks. We now consider in more detail how to represent the lysis (death) of tropical cyclones. Improving the lysis model turns out to bring a significant improvement to the track model overall.
Attacking and Defending Covert Channels and Behavioral Models
Crespi, Valentino; Giani, Annarita
2011-01-01
In this paper we present methods for attacking and defending $k$-gram statistical analysis techniques that are used, for example, in network traffic analysis and covert channel detection. The main new result is our demonstration of how to use a behavior's or process' $k$-order statistics to build a stochastic process that has those same $k$-order stationary statistics but possesses different, deliberately designed, $(k+1)$-order statistics if desired. Such a model realizes a "complexification" of the process or behavior which a defender can use to monitor whether an attacker is shaping the behavior. By deliberately introducing designed $(k+1)$-order behaviors, the defender can check to see if those behaviors are present in the data. We also develop constructs for source codes that respect the $k$-order statistics of a process while encoding covert information. One fundamental consequence of these results is that certain types of behavior analyses techniques come down to an {\\em arms race} in the sense that th...
Turbulent structures and statistics in turbulent channel flow with two-dimensional slits
International Nuclear Information System (INIS)
Direct numerical simulation (DNS, hereafter) of turbulent channel flow with periodic two-dimensional slits has been performed in order to investigate the turbulent statistics and the turbulent structures behind the slits. The Reynolds numbers based on the friction velocity and the channel half width are 10-1500. In the wake region, the mean flow becomes asymmetric with respect to the centerline of the geometry through the Coanda effect. Large-scale vortices are generated at the height of the slit edges. These vortices become deformed in various scenarios and break up into disordered small-scale structures in the shear layers behind the slit. The small-scale vortices are convected toward the channel center. The budgets of the Reynolds stresses have been computed. The significant differences are found between the budgets in this study and those in a backward-facing step turbulence. The positive Reynolds shear stress u'v'-bar is observed owing to the flow contraction just behind the slit. The wake region was classified into several categories based upon the budgets of the Reynolds stresses and turbulent structures
Turbulent structures and statistics in turbulent channel flow with two-dimensional slits
Energy Technology Data Exchange (ETDEWEB)
Makino, Soichiro [Department of Mechanical Engineering, Tokyo University of Science, Noda-shi, Chiba 278-8510 (Japan)], E-mail: a7502126@rs.noda.tus.ac.jp; Iwamoto, Kaoru; Kawamura, Hiroshi [Department of Mechanical Engineering, Tokyo University of Science, Noda-shi, Chiba 278-8510 (Japan)
2008-06-15
Direct numerical simulation (DNS, hereafter) of turbulent channel flow with periodic two-dimensional slits has been performed in order to investigate the turbulent statistics and the turbulent structures behind the slits. The Reynolds numbers based on the friction velocity and the channel half width are 10-1500. In the wake region, the mean flow becomes asymmetric with respect to the centerline of the geometry through the Coanda effect. Large-scale vortices are generated at the height of the slit edges. These vortices become deformed in various scenarios and break up into disordered small-scale structures in the shear layers behind the slit. The small-scale vortices are convected toward the channel center. The budgets of the Reynolds stresses have been computed. The significant differences are found between the budgets in this study and those in a backward-facing step turbulence. The positive Reynolds shear stress u'v'-bar is observed owing to the flow contraction just behind the slit. The wake region was classified into several categories based upon the budgets of the Reynolds stresses and turbulent structures.
Statistical model semiquantitatively approximates arabinoxylooligosaccharides' structural diversity.
Dotsenko, Gleb; Nielsen, Michael Krogsgaard; Lange, Lene
2016-05-13
A statistical model describing the random distribution of substituted xylopyranosyl residues in arabinoxylooligosaccharides is suggested and compared with existing experimental data. Structural diversity of arabinoxylooligosaccharides of various length, originating from different arabinoxylans (wheat flour arabinoxylan (arabinose/xylose, A/X = 0.47); grass arabinoxylan (A/X = 0.24); wheat straw arabinoxylan (A/X = 0.15); and hydrothermally pretreated wheat straw arabinoxylan (A/X = 0.05)), is semiquantitatively approximated using the proposed model. The suggested approach can be applied not only for prediction and quantification of arabinoxylooligosaccharides' structural diversity, but also for estimate of yield and selection of the optimal source of arabinoxylan for production of arabinoxylooligosaccharides with desired structural features. PMID:27043469
Physics-based statistical model and simulation method of RF propagation in urban environments
Pao, Hsueh-Yuan; Dvorak, Steven L.
2010-09-14
A physics-based statistical model and simulation/modeling method and system of electromagnetic wave propagation (wireless communication) in urban environments. In particular, the model is a computationally efficient close-formed parametric model of RF propagation in an urban environment which is extracted from a physics-based statistical wireless channel simulation method and system. The simulation divides the complex urban environment into a network of interconnected urban canyon waveguides which can be analyzed individually; calculates spectral coefficients of modal fields in the waveguides excited by the propagation using a database of statistical impedance boundary conditions which incorporates the complexity of building walls in the propagation model; determines statistical parameters of the calculated modal fields; and determines a parametric propagation model based on the statistical parameters of the calculated modal fields from which predictions of communications capability may be made.
Atmospheric corrosion: statistical validation of models
International Nuclear Information System (INIS)
In this paper we discuss two different methods for validation of regression models, applied to corrosion data. One of them is based on the correlation coefficient and the other one is the statistical test of lack of fit. Both methods are used here to analyse fitting of bi logarithmic model in order to predict corrosion for very low carbon steel substrates in rural and urban-industrial atmospheres in Uruguay. Results for parameters A and n of the bi logarithmic model are reported here. For this purpose, all repeated values were used instead of using average values as usual. Modelling is carried out using experimental data corresponding to steel substrates under the same initial meteorological conditions ( in fact, they are put in the rack at the same time). Results of correlation coefficient are compared with the lack of it tested at two different signification levels (α=0.01 and α=0.05). Unexpected differences between them are explained and finally, it is possible to conclude, at least in the studied atmospheres, that the bi logarithmic model does not fit properly the experimental data. (Author) 18 refs
Analytical Model for Outdoor Millimeter Wave Channels using Geometry-Based Stochastic Approach
Muhammad, Nor Aishah; Wang, Peng; Li, Yonghui; Vucetic, Branka
2016-01-01
The severe bandwidth shortage in conventional microwave bands has spurred the exploration of the millimeter wave (MMW) spectrum for the next revolution in wireless communications. However, there is still lack of proper channel modeling for the MMW wireless propagation, especially in the case of outdoor environments. In this paper, we develop a geometry-based stochastic channel model to statistically characterize the effect of all the first-order reflection paths between the transmitter and re...
Selection models for information channels : Applications in multichannel digital marketing
Winberg, Victor; Eckerdal, Nils
2015-01-01
In all digital marketing efforts, different information channels must be selected and used to reach customers. In this thesis, data describing the interactions that members of the loyalty program of a Nordic airline company have had with three information channels is used to estimate four selection models. These multinomial logistic regression models have the purpose of selecting which channel(s) best suits a given member. The models are evaluated and the one that best fits the given situatio...
Wireless multi-antenna channels modeling and simulation
Primak, Serguei
2011-01-01
This book offers a practical guide on how to use and apply channel models for system evaluation In this book, the authors focus on modeling and simulation of multiple antennas channels, including multiple input multiple output (MIMO) communication channels, and the impact of such models on channel estimation and system performance. Both narrowband and wideband models are addressed. Furthermore, the book covers topics related to modeling of MIMO channel, their numerical simulation, estimation and prediction, as well as applications to receive diversity, capacity and space-time c
Thermonuclear reaction rates from statistical model calculations
International Nuclear Information System (INIS)
The quality of statistical model predictions for thermonuclear reaction rates is based on the accuracy of theoretical determinations of particle and photon transmission coefficients as well as of level densities of excited states in nuclei. The square well potentials for neutrons, protons and alpha particles, used in previous approaches, have been replaced in this work by realistic optical potentials which reproduce nicely experimental data, e.g. the neutron strength functions. E1 γ-transitions are calculated in the framework of the Giant Dipole Resonance model. The width ΓGDR(A.Z) is based on a macroscopic-microscopic model which results in a good agreement with the observed shell structure. The nuclear level densities are still computed with the aid of the back-shifted Fermi-gas model. The relation between the level density parameters a and δ and the shell correction term of nuclear mass formulae is obtained by using the most recent experimental level densities at the neutron separation energy. Cross sections predictions obtained within this framework are expected to lie safety within a factor of 2 of experimental values
Statistical Shape Modeling of Cam Femoroacetabular Impingement
Energy Technology Data Exchange (ETDEWEB)
Harris, Michael D.; Dater, Manasi; Whitaker, Ross; Jurrus, Elizabeth R.; Peters, Christopher L.; Anderson, Andrew E.
2013-10-01
In this study, statistical shape modeling (SSM) was used to quantify three-dimensional (3D) variation and morphologic differences between femurs with and without cam femoroacetabular impingement (FAI). 3D surfaces were generated from CT scans of femurs from 41 controls and 30 cam FAI patients. SSM correspondence particles were optimally positioned on each surface using a gradient descent energy function. Mean shapes for control and patient groups were defined from the resulting particle configurations. Morphological differences between group mean shapes and between the control mean and individual patients were calculated. Principal component analysis was used to describe anatomical variation present in both groups. The first 6 modes (or principal components) captured statistically significant shape variations, which comprised 84% of cumulative variation among the femurs. Shape variation was greatest in femoral offset, greater trochanter height, and the head-neck junction. The mean cam femur shape protruded above the control mean by a maximum of 3.3 mm with sustained protrusions of 2.5-3.0 mm along the anterolateral head-neck junction and distally along the anterior neck, corresponding well with reported cam lesion locations and soft-tissue damage. This study provides initial evidence that SSM can describe variations in femoral morphology in both controls and cam FAI patients and may be useful for developing new measurements of pathological anatomy. SSM may also be applied to characterize cam FAI severity and provide templates to guide patient-specific surgical resection of bone.
New advances in statistical modeling and applications
Santos, Rui; Oliveira, Maria; Paulino, Carlos
2014-01-01
This volume presents selected papers from the XIXth Congress of the Portuguese Statistical Society, held in the town of Nazaré, Portugal, from September 28 to October 1, 2011. All contributions were selected after a thorough peer-review process. It covers a broad range of papers in the areas of statistical science, probability and stochastic processes, extremes and statistical applications.
Statistical Model Checking of Rich Models and Properties
DEFF Research Database (Denmark)
Poulsen, Danny Bøgsted
undecidability issues for the traditional model checking approaches. Statistical model checking has proven itself a valuable supplement to model checking and this thesis is concerned with extending this software validation technique to stochastic hybrid systems. The thesis consists of two parts: the first part...... motivates why existing model checking technology should be supplemented by new techniques. It also contains a brief introduction to probability theory and concepts covered by the six papers making up the second part. The first two papers are concerned with developing online monitoring techniques for...... systems. The fifth paper shows how stochastic hybrid automata are useful for modelling biological systems and the final paper is concerned with showing how statistical model checking is efficiently distributed. In parallel with developing the theory contained in the papers, a substantial part of this work...
Modeling of channel erosion downstream spillway dams
Directory of Open Access Journals (Sweden)
M.A. Mikhalev
2013-03-01
Full Text Available The channel erosion downstream spillway dams in non-cohesive materials has been analyzed from the viewpoint of methods of similarity and dimension theory. The obtained criterion equation connects the maximum depth of the local erosion with its determining parameters: length of concrete lining of bed in the down water of the spillway dam; Froude number at the contracted cross section; Archimedes and Reynolds criterions; submergence factor of hydraulic jump. The problem may be formulated as follows: the geometric size of the structure, kinematics and dynamics of the flows in the model are similar to that in the prototype. Conditions under which the characteristic depth of the local erosion in the model would be recomputed into the prototype, like any geometric size, are being discussed.
Baroclinic Channel Model in Fluid Dynamics
Directory of Open Access Journals (Sweden)
Kharatti Lal
2016-02-01
Full Text Available A complex flow structure is studied using a 2-dimentional baroclinic channel model Unsteady Navier - stokes equation coupled with equation of thermal energy ,salinity and the equation of state are implemented .System closure is achieved through a modified Prandtl, s mixing length formulation of turbulence dissipation The model is applied in a region where the fluid flow is effected by various forcing equation .In this case ,flow is estuarine region affected by diurnal tide and the fresh water inflow in to the estuary and a submerged structure is considered giving possible insight in to stress effects on submerged structure .the result show that in the time evolution of the vertical velocity along downstream edge changes sign from negative to positive .as the dike length increases the primary cell splits and flow becomes turbulent du e to the non-linear effect caused by the dike .these are found to agree favourably with result published in the open literature.
Mathematical Modeling on Open Limestone Channel
Bandstra, Joel; Wu, Naiyi
2014-01-01
Acid mine drainage (AMD) is the outflow of acidic water from metal mines or coal mines. When exposed to air and water, metal sulfides from the deposits of the mines are oxidized and produce acid, metal ions and sulfate, which lower the pH value of the water. An open limestone channel (OLC) is a passive and low cost way to neutralize AMD. The dissolution of calcium into the water increases the pH value of the solution. A differential equation model is numerically solved to predict the variation of concentration of each species in the OLC solution. The diffusion of Calcium due to iron precipitates is modeled by a linear equation. The results give the variation of pH value and the concentration of Calcium.
Application of Statistical Analysis Software in Food Scientific Modeling
Miaochao Chen; Kong Xiangsheng; Kan Chen
2014-01-01
In food scientific researches, sophisticated statistical analysis problems often can be met and in this study, through SPSS statistical analysis software, the method of the curve regression model and the multiple regression model that both are common in food science has been established and the experimental results show that the method can be effectively used in the statistical analysis model of food science.
Statistical model investigation of nuclear fission
International Nuclear Information System (INIS)
To assist in the improvement of fission product yield data libraries, the statistical theory of fission was investigated. Calculation of the theory employs a recent nuclear mass formula and nuclear density of states expression. Yields computed with a simple statement of the theory do not give satisfactory results. A slowly varying empirical parameter is introduced to improve agreement between measured and calculated yields. The parameter is interpreted as the spacing between the tips of the fragments at the instant of scission or as the length of a neck in the fissioning nucleus immediately prior to scission. With this spacing parameter semi-quantitative agreement is obtained between calculated and measured mass chain yields for six cases investigated, 233U(n/sub th/, f), 235U(n/sub th, f), 239Pu(n/sub th/, f), 235U(n+14, f), 238U(n+14, f), and 252Cf(sf). An indication of the source of mass asymmetry in fission is presented. The model developed predicts a mass and energy dependence of some of the parameters of models currently in use in data generation. A procedure for the estimation of the fission product yields for an arbitrary fissioning system is proposed. 63 references
Statistical Ensemble Theory of Gompertz Growth Model
Takuya Yamano
2009-01-01
An ensemble formulation for the Gompertz growth function within the framework of statistical mechanics is presented, where the two growth parameters are assumed to be statistically distributed. The growth can be viewed as a self-referential process, which enables us to use the Bose-Einstein statistics picture. The analytical entropy expression pertain to the law can be obtained in terms of the growth velocity distribution as well as the Gompertz function itself for the whole process.
Statistical Ensemble Theory of Gompertz Growth Model
Directory of Open Access Journals (Sweden)
Takuya Yamano
2009-11-01
Full Text Available An ensemble formulation for the Gompertz growth function within the framework of statistical mechanics is presented, where the two growth parameters are assumed to be statistically distributed. The growth can be viewed as a self-referential process, which enables us to use the Bose-Einstein statistics picture. The analytical entropy expression pertain to the law can be obtained in terms of the growth velocity distribution as well as the Gompertz function itself for the whole process.
Modeling of channel patterns in short tidal basins
Marciano, R.; Wang, Z.B.; Hibma, A.; De Vriend, H.J.; Defina, A.
2005-01-01
We model branching channel patterns in short tidal basins with two methods. A theoretical stability analysis leads to a relationship between the number of channels and physical parameters of the tidal system. The analysis reveals that width and spacing of the channels should decrease as the slope of
Statistical modeling of global soil NOx emissions
Yan, Xiaoyuan; Ohara, Toshimasa; Akimoto, Hajime
2005-09-01
On the basis of field measurements of NOx emissions from soils, we developed a statistical model to describe the influences of soil organic carbon (SOC) content, soil pH, land-cover type, climate, and nitrogen input on NOx emission. While also considering the effects of soil temperature, soil moisture change-induced pulse emission, and vegetation fire, we simulated NOx emissions from global soils at resolutions of 0.5° and 6 hours. Canopy reduction was included in both data processing and flux simulation. NOx emissions were positively correlated with SOC content and negatively correlated with soil pH. Soils in dry or temperate regions had higher NOx emission potentials than soils in cold or tropical regions. Needleleaf forest and agricultural soils had high NOx emissions. The annual NOx emission from global soils was calculated to be 7.43 Tg N, decreasing to 4.97 Tg N after canopy reduction. Global averages of nitrogen fertilizer-induced emission ratios were 1.16% above soil and 0.70% above canopy. Soil moisture change-induced pulse emission contributed about 4% to global annual NOx emission, and the effect of vegetation fire on soil NOx emission was negligible.
Gunashekar, S. D.; Warrington, E. M.; Siddle, D. R.
2010-12-01
This paper presents long-term statistics additional to those previously published pertaining to evaporation duct propagation of UHF radio waves in the British Channel Islands, with particular focus on a completely over-sea 50 km transhorizon path. The importance of the evaporation duct as an anomalous propagation mechanism in marine and coastal regions is highlighted. In particular, the influence of various atmospheric parameters on the performance of a popular operational evaporation duct model is examined. The strengths and weaknesses of this model are evaluated under specific atmospheric conditions. The relationship between the continually varying evaporation duct height and transmitter-receiver antenna geometries is analyzed, and a range of statistics related to the implications of this relationship on the received signal strength is presented. The various issues under investigation are of direct relevance in the planning of long-range, over-sea radio systems operating in the UHF band, and have implications for the radio regulatory work carried out by organizations such as the International Telecommunication Union.
Statistical model evaluation of (n,xn) and (n,xnf) cross sections for heavy nuclei
International Nuclear Information System (INIS)
A method for a statistical model evaluation of fission, (n,2n) and (n,3n) cross sections from 2MeV to 20MeV neutrons on 237U, 238U, 239U and 239Pu is presented. It consists of the determination of fission width parameters by a fit to known fission cross-sections. This method makes use of neutron transmission coefficients from an adapted coupled channel model. The neutron, fission and radiative widths are calculated by the statistical model including Fermi gas model level densities. Results are given for 237U, 238U, 239U and 239Pu nuclei
Statistics-based investigation on typhoon transition modeling
DEFF Research Database (Denmark)
Zhang, Shuoyun; Nishijima, Kazuyoshi
The present study revisits the statistical modeling of typhoon transition. The objective of the study is to provide insights on plausible statistical typhoon transition models based on extensive statistical analysis. First, the correlation structures of the typhoon transition are estimated in terms...
Channel Modelling for Multiprobe Over-the-Air MIMO Testing
Directory of Open Access Journals (Sweden)
Pekka Kyösti
2012-01-01
a fading emulator, an anechoic chamber, and multiple probes. Creation of a propagation environment inside an anechoic chamber requires unconventional radio channel modelling, namely, a specific mapping of the original models onto the probe antennas. We introduce two novel methods to generate fading emulator channel coefficients; the prefaded signals synthesis and the plane wave synthesis. To verify both methods we present a set of simulation results. We also show that the geometric description is a prerequisite for the original channel model.
On Application Of Langevin Dynamics In Logarithmic Potential To Model Ion Channel Gate Activity.
Wawrzkiewicz-Jałowiecka, Agata; Borys, Przemysław; Grzywna, Zbigniew J
2015-12-01
We model the activity of an ion channel gate by Langevin dynamics in a logarithmic potential. This approach enables one to describe the power-law dwell-time distributions of the considered system, and the long-term correlations between the durations of the subsequent channel states, or fractal scaling of statistical characteristics of the gate's movement with time. Activity of an ion channel gate is described as an overdamped motion of the reaction coordinate in a confining logarithmic potential, which ensures great flexibility of the model. Depending on the chosen parameters, it allows one to reproduce many types of gate dynamics within the family of non-Markovian, anomalous conformational diffusion processes. In this study we apply the constructed model to largeconductance voltage and Ca2+-activated potassium channels (BKCa). The interpretation of model assumptions and parameters is provided in terms of this biological system. Our results show good agreement with the experimental data. PMID:26317442
A model for the distribution channels planning process
Neves, M.F.; Zuurbier, P.; Campomar, M.C.
2001-01-01
Research of existing literature reveals some models (sequence of steps) for companies that want to plan distribution channels. None of these models uses strong contributions from transaction cost economics, bringing a possibility to elaborate on a "distribution channels planning model", with these c
[Model of the selective calcium channel of characean algae].
Lunevskiĭ, V Z; Zherelova, O M; Aleksandrov, A A; Vinokurov, M G; Berestovskiĭ, G N
1980-01-01
The present work was intended to further investigate the selective filter of calcium channel on both a cell membrane and reconstructed channels. For the studies on cell membranes, an inhibitor of chloride channels was chosen (ethacrynic acid) to pass currents only through the calcium channels. On both the cells and reconstructed channels, permeability of ions of different crystal radii and valencies was investigated. The obtained results suggest that the channel represents a wide water pore with a diameter larger than 8 A into which ions go together with the nearest water shell. The values of the maximal currents are given by electrostatic interaction of the ions with the anion center of the channel. A phenomenological two-barrier model of the channel is given which describes the movement of all the ions studied. PMID:6251921
Dividing Streamline Formation Channel Confluences by Physical Modeling
Directory of Open Access Journals (Sweden)
Minarni Nur Trilita
2010-02-01
Full Text Available Confluence channels are often found in open channel network system and is the most important element. The incoming flow from the branch channel to the main cause various forms and cause vortex flow. Phenomenon can cause erosion of the side wall of the channel, the bed channel scour and sedimentation in the downstream confluence channel. To control these problems needed research into the current width of the branch channel. The incoming flow from the branch channel to the main channel flow bounded by a line distributors (dividing streamline. In this paper, the wide dividing streamline observed in the laboratory using a physical model of two open channels, a square that formed an angle of 30º. Observations were made with a variety of flow coming from each channel. The results obtained in the laboratory observation that the width of dividing streamline flow is influenced by the discharge ratio between the channel branch with the main channel. While the results of a comparison with previous studies showing that the observation in the laboratory is smaller than the results of previous research.
Dynamical Properties of Potassium Ion Channels with a Hierarchical Model
Institute of Scientific and Technical Information of China (English)
ZHAN Yong; AN Hai-Long; YU Hui; ZHANG Su-Hua; HAN Ying-Rong
2006-01-01
@@ It is well known that potassium ion channels have higher permeability than K ions, and the permeable rate of a single K ion channel is about 108 ions per second. We develop a hierarchical model of potassium ion channel permeation involving ab initio quantum calculations and Brownian dynamics simulations, which can consistently explain a range of channel dynamics. The results show that the average velocity of K ions, the mean permeable time of K ions and the permeable rate of single channel are about 0.92nm/ns, 4.35ns and 2.30×108 ions/s,respectively.
Integer Set Compression and Statistical Modeling
DEFF Research Database (Denmark)
Larsson, N. Jesper
2014-01-01
enumeration of elements may be arbitrary or random, but where statistics is kept in order to estimate probabilities of elements. We present a recursive subset-size encoding method that is able to benefit from statistics, explore the effects of permuting the enumeration order based on element probabilities......Compression of integer sets and sequences has been extensively studied for settings where elements follow a uniform probability distribution. In addition, methods exist that exploit clustering of elements in order to achieve higher compression performance. In this work, we address the case where...
A model study in hadron statistical bootstrap
Hagedorn, Rolf
1973-01-01
In the framework of the statistical bootstrap the decay of a fireball is considered as an exact inverse of its statistical composition. This assumption leads to a bootstrap formulated in terms of integral equations for all kinds of distributions of the fireball's decay products. Solutions of the equations are obtained in terms of power series and of K-transforms and determine in the general case their asymptotic behaviour for large fireball mass. Relations to a thermodynamical description are established and illustrated by effective temperatures. The approach to the asymptotic limits is easy to investigate in a simplified linear bootstrap where the K-transforms can be more explicitly calculated. (30 refs).
Enhanced surrogate models for statistical design exploiting space mapping technology
DEFF Research Database (Denmark)
Koziel, Slawek; Bandler, John W.; Mohamed, Achmed S.;
2005-01-01
We present advances in microwave and RF device modeling exploiting Space Mapping (SM) technology. We propose new SM modeling formulations utilizing input mappings, output mappings, frequency scaling and quadratic approximations. Our aim is to enhance circuit models for statistical analysis...
Modeling Human Performance in Statistical Word Segmentation
Frank, Michael C.; Goldwater, Sharon; Griffiths, Thomas L.; Tenenbaum, Joshua B.
2010-01-01
The ability to discover groupings in continuous stimuli on the basis of distributional information is present across species and across perceptual modalities. We investigate the nature of the computations underlying this ability using statistical word segmentation experiments in which we vary the length of sentences, the amount of exposure, and…
Comparison of Statistical Models for Regional Crop Trial Analysis
Institute of Scientific and Technical Information of China (English)
ZHANG Qun-yuan; KONG Fan-ling
2002-01-01
Based on the review and comparison of main statistical analysis models for estimating varietyenvironment cell means in regional crop trials, a new statistical model, LR-PCA composite model was proposed, and the predictive precision of these models were compared by cross validation of an example data. Results showed that the order of model precision was LR-PCA model ＞ AMMI model ＞ PCA model ＞ Treatment Means (TM) model ＞ Linear Regression (LR) model ＞ Additive Main Effects ANOVA model. The precision gain factor of LR-PCA model was 1.55, increasing by 8.4% compared with AMMI.
Power Curve Modeling in Complex Terrain Using Statistical Models
Bulaevskaya, V.; Wharton, S.; Clifton, A.; Qualley, G.; Miller, W.
2014-12-01
Traditional power output curves typically model power only as a function of the wind speed at the turbine hub height. While the latter is an essential predictor of power output, wind speed information in other parts of the vertical profile, as well as additional atmospheric variables, are also important determinants of power. The goal of this work was to determine the gain in predictive ability afforded by adding wind speed information at other heights, as well as other atmospheric variables, to the power prediction model. Using data from a wind farm with a moderately complex terrain in the Altamont Pass region in California, we trained three statistical models, a neural network, a random forest and a Gaussian process model, to predict power output from various sets of aforementioned predictors. The comparison of these predictions to the observed power data revealed that considerable improvements in prediction accuracy can be achieved both through the addition of predictors other than the hub-height wind speed and the use of statistical models. This work was performed under the auspices of the U.S. Department of Energy by Lawrence Livermore National Laboratory under contract DE-AC52-07NA27344 and was funded by Wind Uncertainty Quantification Laboratory Directed Research and Development Project at LLNL under project tracking code 12-ERD-069.
A 3D Geometry-based Stochastic Model for 5G Massive MIMO Channels
Directory of Open Access Journals (Sweden)
Yi Xie
2015-09-01
Full Text Available Massive MIMO is one of the most promising technologies for the fifth generation (5G mobile communication systems. In order to better assess the system performance, it is essential to build a corresponding channel model accurately. In this paper, a three-dimension (3D two-cylinder regular-shaped geometry-based stochastic model (GBSM for non-isotropic scattering massive MIMO channels is proposed. Based on geometric method, all the scatters are distributed on the surface of a cylinder as equivalent scatters. Non-stationary property is that one antenna has its own visible area of scatters by using a virtual sphere. The proposed channel model is evaluated by comparing with the 3GPP 3D channel model [1]. The statistical properties are investigated. Simulation results show that close agreements are achieved between the characteristics of the proposed channel model and those of the 3GPP channel model, which justify the correctness of the proposed model. The model has advantages such as good applicability.
A 0-Memory Model for Single Ion Channel
Institute of Scientific and Technical Information of China (English)
Zhou Wenqing; Fan Jiqian; Guan Yongyuan
1998-01-01
This paper discusses a 0-memory model for a single ion channel. The renewal rates of the open-class and the close-class are proposed to deseribe kinetic properties of a single ion channel. Further more, a procedure to estimate the parameters in the model is suggested and illustrated with examples in pharmacology.
Information analysis of census data by using statistical models
Czech Academy of Sciences Publication Activity Database
Grim, Jiří; Hora, J.; Boček, Pavel; Somol, Petr; Pudil, P.
Prague : Czech Statistical Office , 2004 - (Krovák, J.), s. 1-7 [Statistics - Investment in the Future . Prague (CZ), 06.09.2004-07.09.2004] R&D Projects: GA ČR GA402/02/1271 EU Projects: European Commission(XE) 507752 - MUSCLE Institutional research plan: CEZ:AV0Z1075907 Keywords : statistical databases * information analysis * statistical models Subject RIV: AO - Sociology, Demography
New perspective in statistical modeling of wall-bounded turbulence
She, Zhen-Su; Chen, Xi; Wu, You; Hussain, Fazle
2010-12-01
Despite dedicated effort for many decades, statistical description of highly technologically important wall turbulence remains a great challenge. Current models are unfortunately incomplete, or empirical, or qualitative. After a review of the existing theories of wall turbulence, we present a new framework, called the structure ensemble dynamics (SED), which aims at integrating the turbulence dynamics into a quantitative description of the mean flow. The SED theory naturally evolves from a statistical physics understanding of non-equilibrium open systems, such as fluid turbulence, for which mean quantities are intimately coupled with the fluctuation dynamics. Starting from the ensemble-averaged Navier-Stokes (EANS) equations, the theory postulates the existence of a finite number of statistical states yielding a multi-layer picture for wall turbulence. Then, it uses order functions (ratios of terms in the mean momentum as well as energy equations) to characterize the states and transitions between states. Application of the SED analysis to an incompressible channel flow and a compressible turbulent boundary layer shows that the order functions successfully reveal the multi-layer structure for wall-bounded turbulence, which arises as a quantitative extension of the traditional view in terms of sub-layer, buffer layer, log layer and wake. Furthermore, an idea of using a set of hyperbolic functions for modeling transitions between layers is proposed for a quantitative model of order functions across the entire flow domain. We conclude that the SED provides a theoretical framework for expressing the yet-unknown effects of fluctuation structures on the mean quantities, and offers new methods to analyze experimental and simulation data. Combined with asymptotic analysis, it also offers a way to evaluate convergence of simulations. The SED approach successfully describes the dynamics at both momentum and energy levels, in contrast with all prevalent approaches describing
The statistical model for parton distributions
Bourrely, Claude; Buccella, Franco; Soffer, Jacques
2012-01-01
The phenomenological motivations, the expressions and the comparison with experiment of the parton distributions inspired by the quantum statistics are described. The Fermi-Dirac expressions for the quarks and their antiparticles automatically account for the correlation between the shape and the first moments of the valence partons, as well as the flavor and spin asymmetries of the sea. One is able to describe with a small number of parameters both unpolarized and polarized structure functions.
International Nuclear Information System (INIS)
An appropriate theoretical model for fission fragment mass distribution (FFMD) of a highly excited heavy nucleus involves multidimensional Langevin dynamical calculations. Though a full Langevin simulation provides a more accurate description of fission dynamics, it is often replaced by a combined dynamical and statistical model (CDSM). This is essentially done because the demand on computer time for a full Langevin calculation is very large. In CDSM, the Langevin dynamical computation is pursued for a time interval during which the initial transients are settled and the fission width has reached a stationary value. The decay of the compound nucleus in subsequent times is followed treating fission at par with other decay channels, such as particle and γ emission channels which are already included in the calculation from the beginning, and using statistical methods. Evidently, CDSM takes less computer time than full dynamical model simulation
Chelli, Ali
2014-01-01
In this paper, we derive a new geometrical blind bend scattering model for vehicle-to- infrastructure (V2I) communications. The proposed model takes into account single-bounce and double- bounce scattering stemming from fixed scatterers located on both sides of a curved street. Starting from the geometrical blind bend model, the exact expression of the angle of departure (AOD) is derived. Based on this expression, the probability density function (PDF) of the AOD and the Doppler power spectrum are determined. Analytical expressions for the channel gain and the temporal autocorrelation function (ACF) are provided under non-line-of-sight (NLOS) conditions. Additionally, we investigate the impact of the position of transmitting vehicle relatively to the receiving road-side unit on the channel statistics. Moreover, we study the performance of different digital modulations over a sum of singly and doubly scattered (SSDS) channel. Note that the proposed V2I channel model falls under the umbrella of SSDS channels since the transmitted signal undergoes a combination of single-bounce and double-bounce scattering. We study some characteristic quantities of SSDS channels and derive expressions for the average symbol error probability of several modulation schemes over SSDS channels with and without diversity combining. The validity of these analytical expressions is confirmed by computer-based simulations.
Portable space mapping for efficient statistical modeling of passive components
Zhang, L; Aaen, PH; Wood, J.
2012-01-01
In this paper, a portable space-mapping technique is presented for efficient statistical modeling of passive components. The proposed technique utilizes the cost-effective model composition of a statistical space mapping, while introducing the portable mapping concept for flexible model development for passive modeling. The portable mapping is a single-development-multiple-use versatile wrapper, such that after development it can be conveniently combined with any nominal model to form a set o...
Field Statistics in a One-Dimensional Reverberation Chamber Model
Canavero, Flavio
2009-01-01
This work focuses on building a fairly simple yet physically appropriate 1D model for a Reverberation Chamber which claims to be able to analytically predict the statistical behavior of such a chamber, without forsaking to the benefits of deterministic models. The statistical properties are introduced by varying the size of a 1D stirrer or the cavity size itself. A validation analysis shows agreement with other theories and measured results on real RCs. Field statistics in undermoded regime i...
A statistical model of future human actions
International Nuclear Information System (INIS)
A critical review has been carried out of models of future human actions during the long term post-closure period of a radioactive waste repository. Various Markov models have been considered as alternatives to the standard Poisson model, and the problems of parameterisation have been addressed. Where the simplistic Poisson model unduly exaggerates the intrusion risk, some form of Markov model may have to be introduced. This situation may well arise for shallow repositories, but it is less likely for deep repositories. Recommendations are made for a practical implementation of a computer based model and its associated database. (Author)
Transport properties in network models with perfectly conducting channels
International Nuclear Information System (INIS)
We study the transport properties of disordered electron systems that contain perfectly conducting channels. Two quantum network models that belong to different universality classes, unitary and symplectic, are simulated numerically. The perfectly conducting channel in the unitary class can be realized in zigzag graphene nano-ribbons and that in the symplectic class is known to appear in metallic carbon nanotubes. The existence of a perfectly conducting channel leads to novel conductance distribution functions and a shortening of the conductance decay length.
Transport properties in network models with perfectly conducting channels
Energy Technology Data Exchange (ETDEWEB)
Kobayashi, K; Hirose, K; Ohtsuki, T [Department of Physics, Sophia University, 102-8554 Tokyo (Japan); Obuse, H [Department of Physics, Kyoto University, 606-8501 Kyoto (Japan); Slevin, K [Department of Physics, Osaka University, 560-0043 Osaka (Japan)], E-mail: k-koji@sophia.ac.jp
2009-02-01
We study the transport properties of disordered electron systems that contain perfectly conducting channels. Two quantum network models that belong to different universality classes, unitary and symplectic, are simulated numerically. The perfectly conducting channel in the unitary class can be realized in zigzag graphene nano-ribbons and that in the symplectic class is known to appear in metallic carbon nanotubes. The existence of a perfectly conducting channel leads to novel conductance distribution functions and a shortening of the conductance decay length.
Transport properties in network models with perfectly conducting channels
Kobayashi, Koji; Hirose, Kosuke; Obuse, Hideaki; Ohtsuki, Tomi; Slevin, Keith
2008-01-01
We study the transport properties of disordered electron systems that contain perfectly conducting channels. Two quantum network models that belong to different universality classes, unitary and symplectic, are simulated numerically. The perfectly conducting channel in the unitary class can be realized in zigzag graphene nano-ribbons and that in the symplectic class is known to appear in metallic carbon nanotubes. The existence of a perfectly conducting channel leads to novel conductance dist...
Yu, Yang; Bing-Zhong, Wang; Shuai, Ding
2016-05-01
Utilizing channel reciprocity, time reversal (TR) technique increases the signal-to-noise ratio (SNR) at the receiver with very low transmitter complexity in complex multipath environment. Present research works about TR multiple-input multiple-output (MIMO) communication all focus on the system implementation and network building. The aim of this work is to analyze the influence of antenna coupling on the capacity of wideband TR MIMO system, which is a realistic question in designing a practical communication system. It turns out that antenna coupling stabilizes the capacity in a small variation range with statistical wideband channel response. Meanwhile, antenna coupling only causes a slight detriment to the channel capacity in a wideband TR MIMO system. Comparatively, uncorrelated stochastic channels without coupling exhibit a wider range of random capacity distribution which greatly depends on the statistical channel. The conclusions drawn from information difference entropy theory provide a guideline for designing better high-performance wideband TR MIMO communication systems. Project supported by the National Natural Science Foundation of China (Grant Nos. 61331007, 61361166008, and 61401065) and the Specialized Research Fund for the Doctoral Program of Higher Education of China (Grant No. 20120185130001).
Statistical modelling of traffic safety development
DEFF Research Database (Denmark)
Christens, Peter
2004-01-01
there were 6861 injury trafficc accidents reported by the police, resulting in 4519 minor injuries, 3946 serious injuries, and 431 fatalities. The general purpose of the research was to improve the insight into aggregated road safety methodology in Denmark. The aim was to analyse advanced statistical...... methods, that were designed to study developments over time, including effects of interventions. This aim has been achieved by investigating variations in aggregated Danish traffic accident series and by applying state of the art methodologies to specific case studies. The thesis comprises an introduction...
Statistical image processing and multidimensional modeling
Fieguth, Paul
2010-01-01
Images are all around us! The proliferation of low-cost, high-quality imaging devices has led to an explosion in acquired images. When these images are acquired from a microscope, telescope, satellite, or medical imaging device, there is a statistical image processing task: the inference of something - an artery, a road, a DNA marker, an oil spill - from imagery, possibly noisy, blurry, or incomplete. A great many textbooks have been written on image processing. However this book does not so much focus on images, per se, but rather on spatial data sets, with one or more measurements taken over
Hayslett, H T
1991-01-01
Statistics covers the basic principles of Statistics. The book starts by tackling the importance and the two kinds of statistics; the presentation of sample data; the definition, illustration and explanation of several measures of location; and the measures of variation. The text then discusses elementary probability, the normal distribution and the normal approximation to the binomial. Testing of statistical hypotheses and tests of hypotheses about the theoretical proportion of successes in a binomial population and about the theoretical mean of a normal population are explained. The text the
Book review: Statistical Analysis and Modelling of Spatial Point Patterns
DEFF Research Database (Denmark)
Møller, Jesper
2009-01-01
Statistical Analysis and Modelling of Spatial Point Patterns by J. Illian, A. Penttinen, H. Stoyan and D. Stoyan. Wiley (2008), ISBN 9780470014912......Statistical Analysis and Modelling of Spatial Point Patterns by J. Illian, A. Penttinen, H. Stoyan and D. Stoyan. Wiley (2008), ISBN 9780470014912...
Infinite statistics condensate as a model of dark matter
Energy Technology Data Exchange (ETDEWEB)
Ebadi, Zahra; Mirza, Behrouz [Department of Physics, Isfahan University of Technology, Isfahan, 84156–83111 (Iran, Islamic Republic of); Mohammadzadeh, Hosein, E-mail: z.ebadi@ph.iut.ac.ir, E-mail: b.mirza@cc.iut.ac.ir, E-mail: mohammadzadeh@uma.ac.ir [Department of Physics, University of Mohaghegh Ardabili, P.O. Box 179, Ardabil (Iran, Islamic Republic of)
2013-11-01
In some models, dark matter is considered as a condensate bosonic system. In this paper, we prove that condensation is also possible for particles that obey infinite statistics and derive the critical condensation temperature. We argue that a condensed state of a gas of very weakly interacting particles obeying infinite statistics could be considered as a consistent model of dark matter.
Multivariate statistical modelling based on generalized linear models
Fahrmeir, Ludwig
1994-01-01
This book is concerned with the use of generalized linear models for univariate and multivariate regression analysis. Its emphasis is to provide a detailed introductory survey of the subject based on the analysis of real data drawn from a variety of subjects including the biological sciences, economics, and the social sciences. Where possible, technical details and proofs are deferred to an appendix in order to provide an accessible account for non-experts. Topics covered include: models for multi-categorical responses, model checking, time series and longitudinal data, random effects models, and state-space models. Throughout, the authors have taken great pains to discuss the underlying theoretical ideas in ways that relate well to the data at hand. As a result, numerous researchers whose work relies on the use of these models will find this an invaluable account to have on their desks. "The basic aim of the authors is to bring together and review a large part of recent advances in statistical modelling of m...
Statistical Tests for Mixed Linear Models
Khuri, André I; Sinha, Bimal K
2011-01-01
An advanced discussion of linear models with mixed or random effects. In recent years a breakthrough has occurred in our ability to draw inferences from exact and optimum tests of variance component models, generating much research activity that relies on linear models with mixed and random effects. This volume covers the most important research of the past decade as well as the latest developments in hypothesis testing. It compiles all currently available results in the area of exact and optimum tests for variance component models and offers the only comprehensive treatment for these models a
Statistical Model of the 3-D Braided Composites Strength
Institute of Scientific and Technical Information of China (English)
XIAO Laiyuan; ZUO Weiwei; CAI Ganwei; LIAO Daoxun
2007-01-01
Based on the statistical model for the tensile statistical strength of unidirectional composite materials and the stress analysis of 3-D braided composites, a new method is proposed to calculate the tensile statistical strength of the 3-D braided composites. With this method, the strength of 3-D braided composites can be calculated with very large accuracy, and the statistical parameters of 3-D braided composites can be determined. The numerical result shows that the tensile statistical strength of 3-D braided composites can be predicted using this method.
Introduction to matrix models and statistical mechanics on random lattices
International Nuclear Information System (INIS)
Matrix models are a powerful technique to solve some models of statistical mechanics on random planar lattices. A simple introduction is given, to illustrate the basic analytical methods and few applications. (author). 23 refs
Statistical Performance Analysis and Modeling Techniques for Nanometer VLSI Designs
Shen, Ruijing; Yu, Hao
2012-01-01
Since process variation and chip performance uncertainties have become more pronounced as technologies scale down into the nanometer regime, accurate and efficient modeling or characterization of variations from the device to the architecture level have become imperative for the successful design of VLSI chips. This book provides readers with tools for variation-aware design methodologies and computer-aided design (CAD) of VLSI systems, in the presence of process variations at the nanometer scale. It presents the latest developments for modeling and analysis, with a focus on statistical interconnect modeling, statistical parasitic extractions, statistical full-chip leakage and dynamic power analysis considering spatial correlations, statistical analysis and modeling for large global interconnects and analog/mixed-signal circuits. Provides readers with timely, systematic and comprehensive treatments of statistical modeling and analysis of VLSI systems with a focus on interconnects, on-chip power grids and ...
Modeling channelized and distributed subglacial drainage in two dimensions
Werder, Mauro A.; Hewitt, Ian J.; Schoof, Christian G.; Flowers, Gwenn E.
2013-12-01
We present a two-dimensional Glacier Drainage System model (GlaDS) that couples distributed and channelized subglacial water flow. Distributed flow occurs through linked cavities that are represented as a continuous water sheet of variable thickness. Channelized flow occurs through Röthlisberger channels that can form on any of the edges of a prescribed, unstructured network of potential channels. Water storage is accounted for in an englacial aquifer and in moulins, which also act as point sources of water to the subglacial system. Solutions are presented for a synthetic topography designed to mimic an ice sheet margin. For low discharge, all the flow is accommodated in the sheet, whereas for sufficiently high discharge, the model exhibits a channelization instability which leads to the formation of a self-organized channel system. The random orientation of the network edges allows the channel system geometry to be relatively unbiased, in contrast to previous structured grid-based models. Under steady conditions, the model supports the classical view of the subglacial drainage system, with low pressure regions forming around the channels. Under diurnally varying input, water flows in and out of the channels, and a rather complex spatiotemporal pattern of water pressures is predicted. We explore the effects of parameter variations on the channel system topology and mean effective pressure. The model is then applied to a mountain glacier and forced with meltwater calculated by a temperature index model. The results are broadly consistent with our current understanding of the glacier drainage system and demonstrate the applicability of the model to real settings.
Statistical Modeling of Large-Scale Scientific Simulation Data
Energy Technology Data Exchange (ETDEWEB)
Eliassi-Rad, T; Baldwin, C; Abdulla, G; Critchlow, T
2003-11-15
With the advent of massively parallel computer systems, scientists are now able to simulate complex phenomena (e.g., explosions of a stars). Such scientific simulations typically generate large-scale data sets over the spatio-temporal space. Unfortunately, the sheer sizes of the generated data sets make efficient exploration of them impossible. Constructing queriable statistical models is an essential step in helping scientists glean new insight from their computer simulations. We define queriable statistical models to be descriptive statistics that (1) summarize and describe the data within a user-defined modeling error, and (2) are able to answer complex range-based queries over the spatiotemporal dimensions. In this chapter, we describe systems that build queriable statistical models for large-scale scientific simulation data sets. In particular, we present our Ad-hoc Queries for Simulation (AQSim) infrastructure, which reduces the data storage requirements and query access times by (1) creating and storing queriable statistical models of the data at multiple resolutions, and (2) evaluating queries on these models of the data instead of the entire data set. Within AQSim, we focus on three simple but effective statistical modeling techniques. AQSim's first modeling technique (called univariate mean modeler) computes the ''true'' (unbiased) mean of systematic partitions of the data. AQSim's second statistical modeling technique (called univariate goodness-of-fit modeler) uses the Andersen-Darling goodness-of-fit method on systematic partitions of the data. Finally, AQSim's third statistical modeling technique (called multivariate clusterer) utilizes the cosine similarity measure to cluster the data into similar groups. Our experimental evaluations on several scientific simulation data sets illustrate the value of using these statistical models on large-scale simulation data sets.
Statistical Modelling of Extreme Rainfall in Taiwan
Lan-Fen Chu; Michael McAleer; Ching-Chung Chang
2012-01-01
In this paper, the annual maximum daily rainfall data from 1961 to 2010 are modelled for 18 stations in Taiwan. We fit the rainfall data with stationary and non-stationary generalized extreme value distributions (GEV), and estimate their future behaviour based on the best fitting model. The non-stationary model means that the parameter of location of the GEV distribution is formulated as linear and quadratic functions of time to detect temporal trends in the maximum rainfall. Future behavior ...
Statistical Modelling of Extreme Rainfall in Taiwan
Lan-Fen Chu; Michael McAleer; Ching-Chung Chang
2013-01-01
In this paper, the annual maximum daily rainfall data from 1961 to 2010 are modelled for 18 stations in Taiwan. We fit the rainfall data with stationary and non-stationary generalized extreme value distributions (GEV), and estimate their future behaviour based on the best fitting model. The non-stationary model means that the parameter of location of the GEV distribution is formulated as linear and quadratic functions of time to detect temporal trends in the maximum rainfall. Future behavior ...
Statistical modeling and extrapolation of carcinogenesis data
International Nuclear Information System (INIS)
Mathematical models of carcinogenesis are reviewed, including pharmacokinetic models for metabolic activation of carcinogenic substances. Maximum likelihood procedures for fitting these models to epidemiological data are discussed, including situations where the time to tumor occurrence is unobservable. The plausibility of different possible shapes of the dose response curve at low doses is examined, and a robust method for linear extrapolation to low doses is proposed and applied to epidemiological data on radiation carcinogenesis
Fluctuations of offshore wind generation: Statistical modelling
DEFF Research Database (Denmark)
Pinson, Pierre; Christensen, Lasse E.A.; Madsen, Henrik;
2007-01-01
production averaged at a 1, 5, and 10-minute rate. The exercise consists in one-step ahead forecasting of these time-series with the various regime-switching models. It is shown that the MSAR model, for which the succession of regimes is represented by a hidden Markov chain, significantly outperforms......) and Markov-Switching AutoRegressive (MSAR) models are considered. The particularities of these models are presented, as well as methods for the estimation of their parameters. Simulation results are given for the case of the Horns Rev and Nysted offshore wind farms in Denmark, for time-series of power...
Statistics of Certain Models of Evolution
Standish, Russell K.
1998-01-01
In a recent paper, Newman surveys the literature on power law spectra in evolution, self-organised criticality and presents a model of his own to arrive at a conclusion that self-organised criticality is not necessary for evolution. Not only did he miss a key model (Ecolab) that has a clear self-organised critical mechanism, but also Newman's model exhibits the same mechanism that gives rise to power law behaviour as does Ecolab. Newman's model is, in fact, a ``mean field'' approximation of a...
A two channel model for N(1535)
International Nuclear Information System (INIS)
The first negative parity state of the nucleon resonance IV(1535)is pre-dominantly described as an eta-nucleon (skyrmion) bound state, which subsequently couples to the pion-nucleon system. Solving the two channel problem approximately, it is shown how bound state properties are improved to describe the nature of the resonance. (author) 10 refs., 1 tab
Statistical Modelling of Extreme Rainfall in Taiwan
L. Chu (LanFen); M.J. McAleer (Michael); C-H. Chang (Chu-Hsiang)
2013-01-01
textabstractIn this paper, the annual maximum daily rainfall data from 1961 to 2010 are modelled for 18 stations in Taiwan. We fit the rainfall data with stationary and non-stationary generalized extreme value distributions (GEV), and estimate their future behaviour based on the best fitting model.
Statistical Modelling of Extreme Rainfall in Taiwan
L-F. Chu (Lan-Fen); M.J. McAleer (Michael); C-C. Chang (Ching-Chung)
2012-01-01
textabstractIn this paper, the annual maximum daily rainfall data from 1961 to 2010 are modelled for 18 stations in Taiwan. We fit the rainfall data with stationary and non-stationary generalized extreme value distributions (GEV), and estimate their future behaviour based on the best fitting model.
Statistical models of shape optimisation and evaluation
Davies, Rhodri; Taylor, Chris
2008-01-01
Addresses one of the key issues in shape modelling: that of establishing a meaningful correspondence between a set of shapesUses a novel approach to establishing correspondence by casting model-building as an optimisation problem Includes practical examples of applications for both 2D and 3D sets of shapesFull implementation details, perviously unpublished, provided
A numerical model for meltwater channel evolution in glaciers
Directory of Open Access Journals (Sweden)
A. H. Jarosch
2011-10-01
Full Text Available Meltwater channels form an integral part of the hydrological system of a glacier. Better understanding of how meltwater channels develop and evolve is required to fully comprehend supraglacial and englacial meltwater drainage. Incision of supraglacial stream channels and subsequent roof closure by ice deformation has been proposed in recent literature as a possible englacial conduit formation process. Field evidence for supraglacial stream incision has been found in Svalbard and Nepal. In Iceland, where volcanic activity provides meltwater with temperatures above 0 °C, rapid enlargement of supraglacial channels has been observed. By coupling, for the first time, a numerical ice dynamic model to a hydraulic model which includes heat transfer, we investigate the evolution of meltwater channels and their incision behaviour. We present results for different, constant meltwater fluxes, different channel slopes, different meltwater temperatures as well as temporal variations in meltwater flux. The key parameters governing incision rate and depth are the channel slope and the meltwater temperature loss to the ice. Meltwater flux controls channel width and to a lesser degree incision behaviour. Calculated Nusselt numbers suggest that turbulent forced convection is the main heat transfer mechanism in the studied meltwater channels.
A vehicle-to-infrastructure channel model for blind corner scattering environments
Chelli, Ali
2013-09-01
In this paper, we derive a new geometrical blind corner scattering model for vehicle-to-infrastructure (V2I) communications. The proposed model takes into account single-bounce and double-bounce scattering stemming from fixed scatterers located on both sides of the curved street. Starting from the geometrical blind corner model, the exact expression of the angle of departure (AOD) is derived. Based on this expression, the probability density function (PDF) of the AOD and the Doppler power spectrum are determined. Analytical expressions for the channel gain and the temporal autocorrelation function (ACF) are provided under non-line-of-sight (NLOS) conditions. Moreover, we investigate the impact of the position of transmitting vehicle relatively to the receiving road-side unit on the channel statistics. The proposed channel model is useful for the design and analysis of future V2I communication systems. Copyright © 2013 by the Institute of Electrical and Electronic Engineers, Inc.
Statistical Language Models for On-line Handwritten Sentence Recognition
Quiniou, Solen; Anquetil, Eric; Carbonnel, Sabine
2005-01-01
This paper investigates the integration of a statistical language model into an on-line recognition system in order to improve word recognition in the context of handwritten sentences. Two kinds of models have been considered: n-gram and n-class models (with a statistical approach to create word classes). All these models are trained over the Susanne corpus and experiments are carried out on sentences from this corpus which were written by several writers. The use of a statistical language mo...
Statistical modeling of violin bowing parameter contours
Maestre G??mez, Esteban
2009-01-01
We present a framework for modeling right-hand gestures in bowed-string instrument playing, applied to violin. Nearly non-intrusive sensing techniques allow for accurate acquisition of relevant timbre-related bowing gesture parameter cues. We model the temporal contour of bow transversal velocity, bow pressing force, and bow-bridge distance as sequences of short segments, in particular B??ezier cubic curve segments. Considering different articulations, dynamics, and contexts, a number of n...
Beta decay properties from a statistical model
International Nuclear Information System (INIS)
The present work assumes that any intrinsic structure in the nuclei involved is not important. Only spin, parity, and energy are considered. Quantities such as half-life, average beta energy, or average gamma energy can be obtained by integrals over the beta strength function weighted by kinematic and other factors. The beta strength function is proportional to the level density multiplied by a reduced transition probability. Delayed neutron emission is calculated by assuming that the daughter is a compound nucleus which then statistically decays as in the Hauser-Feshbach approach. Using the ENDF/B-V fission product file which contains 877 nuclei, energy-dependent reduced transition probabilities were found for allowed 0+ → 1+ transitions (50 cases) and for other allowed transitions (over 600 cases), corresponding to log ft values of 4.3 and 5.6 respectively. No dependence on either transition energy or on mass was found. A reduced transition probability corresponding to log ft of 7.1 was used for first forbidden transitions. Some results are presented and discussed
Yilmaz, Ferkan
2014-01-01
Higher order statistics (HOS) of the channel capacity provide useful information regarding the level of reliability of signal transmission at a particular rate. In this paper, we propose a novel and unified analysis, which is based on the moment-generating function (MGF) approach, to efficiently and accurately compute the HOS of the channel capacity for amplify-and-forward (AF) multihop transmission over generalized fading channels. More precisely, our easy-to-use and tractable mathematical formalism requires only the reciprocal MGFs of the transmission hop signal-to-noise ratio (SNR). Numerical and simulation results, which are performed to exemplify the usefulness of the proposed MGF-based analysis, are shown to be in perfect agreement. © 2013 IEEE.
Links to sources of cancer-related statistics, including the Surveillance, Epidemiology and End Results (SEER) Program, SEER-Medicare datasets, cancer survivor prevalence data, and the Cancer Trends Progress Report.
Functional summary statistics for the Johnson-Mehl model
DEFF Research Database (Denmark)
Møller, Jesper; Ghorbani, Mohammad
The Johnson-Mehl germination-growth model is a spatio-temporal point process model which among other things have been used for the description of neurotransmitters datasets. However, for such datasets parametric Johnson-Mehl models fitted by maximum likelihood have yet not been evaluated by means...... of functional summary statistics. This paper therefore invents four functional summary statistics adapted to the Johnson-Mehl model, with two of them based on the second-order properties and the other two on the nuclei-boundary distances for the associated Johnson-Mehl tessellation. The functional summary...... statistics theoretical properties are investigated, non-parametric estimators are suggested, and their usefulness for model checking is examined in a simulation study. The functional summary statistics are also used for checking fitted parametric Johnson-Mehl models for a neurotransmitters dataset....
Statistical modelling in biostatistics and bioinformatics selected papers
Peng, Defen
2014-01-01
This book presents selected papers on statistical model development related mainly to the fields of Biostatistics and Bioinformatics. The coverage of the material falls squarely into the following categories: (a) Survival analysis and multivariate survival analysis, (b) Time series and longitudinal data analysis, (c) Statistical model development and (d) Applied statistical modelling. Innovations in statistical modelling are presented throughout each of the four areas, with some intriguing new ideas on hierarchical generalized non-linear models and on frailty models with structural dispersion, just to mention two examples. The contributors include distinguished international statisticians such as Philip Hougaard, John Hinde, Il Do Ha, Roger Payne and Alessandra Durio, among others, as well as promising newcomers. Some of the contributions have come from researchers working in the BIO-SI research programme on Biostatistics and Bioinformatics, centred on the Universities of Limerick and Galway in Ireland and fu...
Contributions in Radio Channel Sounding, Modeling, and Estimation
DEFF Research Database (Denmark)
Pedersen, Troels
2009-01-01
This thesis spans over three strongly related topics in wireless communication: channel-sounding, -modeling, and -estimation. Three main problems are addressed: optimization of spatio-temporal apertures for channel sounding; estimation of per-path power spectral densities (psds); and modeling of...... reverberant channels. We develop a theory for optimization of spatio-temporal apertures used in multiple-input multiple-output (MIMO) channel sounding. Initially, we focus on joint estimation of bi-direction and Doppler frequency from time-division multiplexing (TDM) MIMO measurements. We introduce and...... analyze a bi-spatio-temporal ambiguity function for spatio-temporal channel sounding. The analysis reveals that by proper design of the spatio-temporal aperture, the maximum estimable Doppler frequency of a TDM-MIMO sounder is as high as that of a traditional single-input single-output sounder. We give...
NUMERICAL MODELING OF SUSPENDED SEDIMENT TRANSPORT IN CHANNEL BENDS
Institute of Scientific and Technical Information of China (English)
HUANG Sui-liang; JIA Y. F.; WANG Sam S. Y.
2006-01-01
An algorithm to compute three-dimensional sediment transport effect was proposed in this paper to enhance the capability of depth-averaged numerical models. This algorithm took into account of non-uniform distributions of flow velocities and suspended sediment concentrations along water depth, it significantly enhanced the applicability of 2D models in simulating open channel flows, especially in channel bends. Preliminary numerical experiments in a U-shaped and a sine-generated experimental channel indicate that the proposed method performs quite well in predicting the change of bed-deformation in channel bends due to suspended sediment transport. This method provides an effective alternative for the simulations of channel morphodynamic changes.
Statistical Contact Model for Confined Molecules
Santamaria, Ruben; de la Paz, Antonio Alvarez; Roskop, Luke; Adamowicz, Ludwik
2016-06-01
A theory that describes in a realistic form a system of atoms under the effects of temperature and confinement is presented. The theory departs from a Lagrangian of the Zwanzig type and contains the main ingredients for describing a system of atoms immersed in a heat bath that is also formed by atoms. The equations of motion are derived according to Lagrangian mechanics. The application of statistical mechanics to describe the bulk effects greatly reduces the complexity of the equations. The resultant equations of motion are of the Langevin type with the viscosity and the temperature of the heat reservoir able to influence the trajectories of the particles. The pressure effects are introduced mechanically by using a container with an atomic structure immersed in the heat bath. The relevant variables that determine the equation of state are included in the formulation. The theory is illustrated by the derivation of the equation of state for a system with 76 atoms confined inside of a 180-atom fullerene-like cage that is immersed in fluid forming the heat bath at a temperature of 350 K and with the friction coefficient of 3.0 {ps}^{-1} . The atoms are of the type believed to form the cores of the Uranus and Neptune planets. The dynamic and the static pressures of the confined system are varied in the 3-5 KBar and 2-30 MBar ranges, respectively. The formulation can be equally used to analyze chemical reactions under specific conditions of pressure and temperature, determine the structure of clusters with their corresponding equation of state, the conditions for hydrogen storage, etc. The theory is consistent with the principles of thermodynamics and it is intrinsically ergodic, of general use, and the first of this kind.
Behavioral and Statistical Models of Educational Inequality
DEFF Research Database (Denmark)
Holm, Anders; Breen, Richard
2016-01-01
This paper addresses the question of how students and their families make educational decisions. We describe three types of behavioral model that might underlie decision-making and we show that they have consequences for what decisions are made. Our study thus has policy implications if we wish to...
A Statistical Model for Energy Intensity
Directory of Open Access Journals (Sweden)
Marjaneh Issapour
2012-12-01
Full Text Available A promising approach to improve scientific literacy in regards to global warming and climate change is using a simulation as part of a science education course. The simulation needs to employ scientific analysis of actual data from internationally accepted and reputable databases to demonstrate the reality of the current climate change situation. One of the most important criteria for using a simulation in a science education course is the fidelity of the model. The realism of the events and consequences modeled in the simulation is significant as well. Therefore, all underlying equations and algorithms used in the simulation must have real-world scientific basis. The "Energy Choices" simulation is one such simulation. The focus of this paper is the development of a mathematical model for "Energy Intensity" as a part of the overall system dynamics in "Energy Choices" simulation. This model will define the "Energy Intensity" as a function of other independent variables that can be manipulated by users of the simulation. The relationship discovered by this research will be applied to an algorithm in the "Energy Choices" simulation.
Analyzing and Improving Statistical Language Models for Speech Recognition
Ueberla, J P
1994-01-01
In many current speech recognizers, a statistical language model is used to indicate how likely it is that a certain word will be spoken next, given the words recognized so far. How can statistical language models be improved so that more complex speech recognition tasks can be tackled? Since the knowledge of the weaknesses of any theory often makes improving the theory easier, the central idea of this thesis is to analyze the weaknesses of existing statistical language models in order to subsequently improve them. To that end, we formally define a weakness of a statistical language model in terms of the logarithm of the total probability, LTP, a term closely related to the standard perplexity measure used to evaluate statistical language models. We apply our definition of a weakness to a frequently used statistical language model, called a bi-pos model. This results, for example, in a new modeling of unknown words which improves the performance of the model by 14% to 21%. Moreover, one of the identified weak...
ENHANCING HYDROLOGICAL SIMULATION PROGRAM - FORTRAN MODEL CHANNEL HYDRAULIC REPRESENTATION
The Hydrological Simulation Program– FORTRAN (HSPF) is a comprehensive watershed model that employs depth-area - volume - flow relationships known as the hydraulic function table (FTABLE) to represent the hydraulic characteristics of stream channel cross-sections and reservoirs. ...
Effects of subfilter velocity modelling on dispersed phase in LES of heated channel flow
International Nuclear Information System (INIS)
A non-isothermal turbulent flow with the dispersed phase is modelled using the Large Eddy Simulation (LES) approach for fluid, one-way coupled with the equations of point-particle evolution. The channel is heated at both walls and isoflux boundary conditions are applied for fluid. Particle velocity and thermal statistics are computed. Of particular interest are the r.m.s. profiles and the probability density function of particle temperature in the near-wall region. We compare our findings with available reference data for particle-laden, heated channel flow. Moreover, an open issue in LES is the influence of non-resolved (residual) scales of fluid velocity and temperature fields on particles. In the present contribution, we apply a stochastic model for subfilter fluid velocity at the particle positions that aims at reconstructing the effects of the smallest scales of turbulence on particle dynamics. We analyse the impact of this model on particle thermal statistics.
Effects of subfilter velocity modelling on dispersed phase in LES of heated channel flow
Pozorski, Jacek; Knorps, Maria; Łuniewski, Mirosław
2011-12-01
A non-isothermal turbulent flow with the dispersed phase is modelled using the Large Eddy Simulation (LES) approach for fluid, one-way coupled with the equations of point-particle evolution. The channel is heated at both walls and isoflux boundary conditions are applied for fluid. Particle velocity and thermal statistics are computed. Of particular interest are the r.m.s. profiles and the probability density function of particle temperature in the near-wall region. We compare our findings with available reference data for particle-laden, heated channel flow. Moreover, an open issue in LES is the influence of non-resolved (residual) scales of fluid velocity and temperature fields on particles. In the present contribution, we apply a stochastic model for subfilter fluid velocity at the particle positions that aims at reconstructing the effects of the smallest scales of turbulence on particle dynamics. We analyse the impact of this model on particle thermal statistics.
A Model of Statistics Performance Based on Achievement Goal Theory.
Bandalos, Deborah L.; Finney, Sara J.; Geske, Jenenne A.
2003-01-01
Tests a model of statistics performance based on achievement goal theory. Both learning and performance goals affected achievement indirectly through study strategies, self-efficacy, and test anxiety. Implications of these findings for teaching and learning statistics are discussed. (Contains 47 references, 3 tables, 3 figures, and 1 appendix.)…
Kolmogorov complexity, pseudorandom generators and statistical models testing
Czech Academy of Sciences Publication Activity Database
Šindelář, Jan; Boček, Pavel
2002-01-01
Roč. 38, č. 6 (2002), s. 747-759. ISSN 0023-5954 R&D Projects: GA ČR GA102/99/1564 Institutional research plan: CEZ:AV0Z1075907 Keywords : Kolmogorov complexity * pseudorandom generators * statistical models testing Subject RIV: BB - Applied Statistics, Operational Research Impact factor: 0.341, year: 2002
Impact of Clustering in Indoor MIMO Propagation Using a Hybrid Channel Model
Directory of Open Access Journals (Sweden)
Tang Zhongwei
2005-01-01
Full Text Available The clustering of propagating signals in indoor environments can influence the performance of multiple-input multiple-output (MIMO systems that employ multiple-element antennas at the transmitter and receiver. In order to clarify the effect of clustering propagation on the performance of indoor MIMO systems, we propose a simple and efficient indoor MIMO channel model. The proposed model, which is validated with on-site measurements, combines the statistical characteristics of signal clusters with deterministic ray tracing approach. Using the proposed model, the effect of signal clusters and the presence of the line-of-sight component in indoor Ricean channels are studied. Simulation results on channel efficiency and the angular sensitivity for different antenna array topologies inside a specified indoor scenario are also provided. Our investigations confirm that the clustering of signals significantly affects the spatial correlation, and hence, the achievable indoor MIMO capacity.
Statistical mechanics model of angiogenic tumor growth.
Ferreira, António Luis; Lipowska, Dorota; Lipowski, Adam
2012-01-01
We examine a lattice model of tumor growth where the survival of tumor cells depends on the supplied nutrients. When such a supply is random, the extinction of tumors belongs to the directed percolation universality class. However, when the supply is correlated with the distribution of tumor cells, which as we suggest might mimic the angiogenic growth, the extinction shows different critical behavior. Such a correlation affects also the morphology of the growing tumors and drastically raises tumor-survival probability. PMID:22400505
Improved Credit Scoring with Multilevel Statistical Modelling
Khudnitskaya, Alesia S.
2011-01-01
This dissertation introduces a new type of credit scoring model which assesses credit worthiness of applicants for a loan by forecasting their probability of default. The multilevel scorecard is an improved alternative to the conventional scoring techniques which are regularly applied in retail banking such as discriminant analysis, decision trees and logistic regression scorecards. In addition, this thesis proposes a new way of data clustering for a multilevel structure which ...
A Statistical Model for Energy Intensity
Marjaneh Issapour; Lori L. Scarlatos; Herbert F. Lewis
2012-01-01
A promising approach to improve scientific literacy in regards to global warming and climate change is using a simulation as part of a science education course. The simulation needs to employ scientific analysis of actual data from internationally accepted and reputable databases to demonstrate the reality of the current climate change situation. One of the most important criteria for using a simulation in a science education course is the fidelity of the model. The realism of the events and ...
Modeling statistical properties of written text.
Directory of Open Access Journals (Sweden)
M Angeles Serrano
Full Text Available Written text is one of the fundamental manifestations of human language, and the study of its universal regularities can give clues about how our brains process information and how we, as a society, organize and share it. Among these regularities, only Zipf's law has been explored in depth. Other basic properties, such as the existence of bursts of rare words in specific documents, have only been studied independently of each other and mainly by descriptive models. As a consequence, there is a lack of understanding of linguistic processes as complex emergent phenomena. Beyond Zipf's law for word frequencies, here we focus on burstiness, Heaps' law describing the sublinear growth of vocabulary size with the length of a document, and the topicality of document collections, which encode correlations within and across documents absent in random null models. We introduce and validate a generative model that explains the simultaneous emergence of all these patterns from simple rules. As a result, we find a connection between the bursty nature of rare words and the topical organization of texts and identify dynamic word ranking and memory across documents as key mechanisms explaining the non trivial organization of written text. Our research can have broad implications and practical applications in computer science, cognitive science and linguistics.
On Angular Sampling Methods for 3-D Spatial Channel Models
DEFF Research Database (Denmark)
Fan, Wei; Jämsä, Tommi; Nielsen, Jesper Ødum; Pedersen, Gert Frølund
2015-01-01
This paper discusses generating three dimensional (3D) spatial channel models with emphasis on the angular sampling methods. Three angular sampling methods, i.e. modified uniform power sampling, modified uniform angular sampling, and random pairing methods are proposed and investigated in detail....... The random pairing method, which uses only twenty sinusoids in the ray-based model for generating the channels, presents good results if the spatial channel cluster is with a small elevation angle spread. For spatial clusters with large elevation angle spreads, however, the random pairing method would...
S-Channel Dark Matter Simplified Models and Unitarity
Englert, Christoph; McCullough, Matthew; Spannowsky, Michael
2016-01-01
The ultraviolet structure of $s$-channel mediator dark matter simplified models at hadron colliders is considered. In terms of commonly studied $s$-channel mediator simplified models it is argued that at arbitrarily high energies the perturbative description of dark matter production in high energy scattering at hadron colliders will break down in a number of cases. This is analogous to the well documented breakdown of an EFT description of dark matter collider production. With this in mind, ...
A NEW PUNCHTHROUGH MODEL FOR SHORT CHANNEL MOSFET
Chen, D.; Li, Zhenyu
1988-01-01
After the source-drain punchthrough was considered detailly, a new set of analytical models for punchthrough voltage VP were suggested, which are suitable to NMOSFET with uniformly doped substrate or channel ion-implanted substrate and PMOSFET with buried channel, as well as a high speed numerical simulation method was developed for autosearching of VP. Excellent agreements were shown between the results of numerical simulation and analytical models.
Mixed deterministic statistical modelling of regional ozone air pollution
Kalenderski, Stoitchko Dimitrov
2011-03-17
We develop a physically motivated statistical model for regional ozone air pollution by separating the ground-level pollutant concentration field into three components, namely: transport, local production and large-scale mean trend mostly dominated by emission rates. The model is novel in the field of environmental spatial statistics in that it is a combined deterministic-statistical model, which gives a new perspective to the modelling of air pollution. The model is presented in a Bayesian hierarchical formalism, and explicitly accounts for advection of pollutants, using the advection equation. We apply the model to a specific case of regional ozone pollution-the Lower Fraser valley of British Columbia, Canada. As a predictive tool, we demonstrate that the model vastly outperforms existing, simpler modelling approaches. Our study highlights the importance of simultaneously considering different aspects of an air pollution problem as well as taking into account the physical bases that govern the processes of interest. © 2011 John Wiley & Sons, Ltd..
Improving statistical reasoning theoretical models and practical implications
Sedlmeier, Peter
1999-01-01
This book focuses on how statistical reasoning works and on training programs that can exploit people''s natural cognitive capabilities to improve their statistical reasoning. Training programs that take into account findings from evolutionary psychology and instructional theory are shown to have substantially larger effects that are more stable over time than previous training regimens. The theoretical implications are traced in a neural network model of human performance on statistical reasoning problems. This book apppeals to judgment and decision making researchers and other cognitive scientists, as well as to teachers of statistics and probabilistic reasoning.
Fusion yield: Guderley model and Tsallis statistics
Haubold, H. J.; KUMAR, D
2010-01-01
The reaction rate probability integral is extended from Maxwell-Boltzmann approach to a more general approach by using the pathway model introduced by Mathai [Mathai A.M.:2005, A pathway to matrix-variate gamma and normal densities, Linear Algebra and Its Applications}, 396, 317-328]. The extended thermonuclear reaction rate is obtained in closed form via a Meijer's G-function and the so obtained G-function is represented as a solution of a homogeneous linear differential equation. A physical...
Fusion yield: Guderley model and Tsallis statistics
Haubold, H J
2010-01-01
The reaction rate probability integral is extended from Maxwell-Boltzmann approach to a more general approach by using the pathway model introduced by Mathai [Mathai A.M.:2005, A pathway to matrix-variate gamma and normal densities, Linear Algebra and Its Applications}, 396, 317-328]. The extended thermonuclear reaction rate is obtained in closed form via a Meijer's G-function and the so obtained G-function is represented as a solution of a homogeneous linear differential equation. A physical model for the hydrodynamical process in a fusion plasma compressed and laser-driven spherical shock wave is used for evaluating the fusion energy integral by integrating the extended thermonuclear reaction rate integral over the temperature. The result obtained is compared with the standard fusion yield obtained by Haubold and John in 1981.[Haubold, H.J. and John, R.W.:1981, Analytical representation of the thermonuclear reaction rate and fusion energy production in a spherical plasma shock wave, Plasma Physics, 23, 399-...
Statistical Analysis and Modeling of Elastic Functions
Srivastava, Anuj; Kurtek, Sebastian; Klassen, Eric; Marron, J S
2011-01-01
We introduce a novel geometric framework for separating, analyzing and modeling the $x$ (or horizontal) and the $y$ (or vertical) variability in time-warped functional data of the type frequently studied in growth curve analysis. This framework is based on the use of the Fisher-Rao Riemannian metric that provides a proper distance for: (1) aligning, comparing and modeling functions and (2) analyzing the warping functions. A convenient square-root velocity function (SRVF) representation transforms the Fisher-Rao metric to the standard $\\ltwo$ metric, a tool that is applied twice in this framework. Firstly, it is applied to the given functions where it leads to a parametric family of penalized-$\\ltwo$ distances in SRVF space. The parameter controls the levels of elasticity of the individual functions. These distances are then used to define Karcher means and the individual functions are optimally warped to align them to the Karcher means to extract the $y$ variability. Secondly, the resulting warping functions,...
3D Massive MIMO Systems: Channel Modeling and Performance Analysis
Nadeem, Qurrat-Ul-Ain
2015-03-01
Multiple-input-multiple-output (MIMO) systems of current LTE releases are capable of adaptation in the azimuth only. More recently, the trend is to enhance the system performance by exploiting the channel\\'s degrees of freedom in the elevation through the dynamic adaptation of the vertical antenna beam pattern. This necessitates the derivation and characterization of three-dimensional (3D) channels. Over the years, channel models have evolved to address the challenges of wireless communication technologies. In parallel to theoretical studies on channel modeling, many standardized channel models like COST-based models, 3GPP SCM, WINNER, ITU have emerged that act as references for industries and telecommunication companies to assess system-level and link-level performances of advanced signal processing techniques over real-like channels. Given the existing channels are only two dimensional (2D) in nature; a large effort in channel modeling is needed to study the impact of the channel component in the elevation direction. The first part of this work sheds light on the current 3GPP activity around 3D channel modeling and beamforming, an aspect that to our knowledge has not been extensively covered by a research publication. The standardized MIMO channel model is presented, that incorporates both the propagation effects of the environment and the radio effects of the antennas. In order to facilitate future studies on the use of 3D beamforming, the main features of the proposed 3D channel model are discussed. A brief overview of the future 3GPP 3D channel model being outlined for the next generation of wireless networks is also provided. In the subsequent part of this work, we present an information-theoretic channel model for MIMO systems that supports the elevation dimension. The model is based on the principle of maximum entropy, which enables us to determine the distribution of the channel matrix consistent with the prior information on the angles of departure and
Statistical Physics and Dynamical Systems: Models of Phase Transitions
Patwardhan, Ajay
2007-01-01
This paper explores the connection between dynamical system properties and statistical physics of ensembles of such systems. Simple models are used to give novel phase transitions; particularly for finite N particle systems with many physically interesting examples.
A novel statistical generative model dedicated to face recognition
Heusch, Guillaume; Marcel, Sébastien
2009-01-01
In this paper, a novel statistical generative model to describe a face is presented, and is applied to the face authentication task. Classical generative models used so far in face recognition, such as Gaussian Mixture Models (GMMs) and Hidden Markov Models (HMMs) for instance, are making strong assumptions on the observations derived from a face image. Indeed, such models usually assume that local observations are independent, which is obviously not the case in a face. The presented model he...
International Nuclear Information System (INIS)
For the year 1999 and 2000, part of the figures shown in the tables of the Energy Review are preliminary or estimated. The annual statistics of the Energy Review appear in more detail from the publication Energiatilastot - Energy Statistics issued annually, which also includes historical time series over a longer period (see e.g., Energiatilastot 1998, Statistics Finland, Helsinki 1999, ISSN 0785-3165). The inside of the Review's back cover shows the energy units and the conversion coefficients used for them. Explanatory notes to the statistical tables can be found after tables and figures. The figures presents: Changes in the volume of GNP and energy consumption, Changes in the volume of GNP and electricity, Coal consumption, Natural gas consumption, Peat consumption, Domestic oil deliveries, Import prices of oil, Consumer prices of principal oil products, Fuel prices for heat production, Fuel prices for electricity production, Carbon dioxide emissions, Total energy consumption by source and CO2-emissions, Electricity supply, Energy imports by country of origin in January-March 2000, Energy exports by recipient country in January-March 2000, Consumer prices of liquid fuels, Consumer prices of hard coal, natural gas and indigenous fuels, Average electricity price by type of consumer, Price of district heating by type of consumer, Excise taxes, value added taxes and fiscal charges and fees included in consumer prices of some energy sources and Energy taxes and precautionary stock fees on oil products
CHANNEL MORPHOLOGY TOOL (CMT): A GIS-BASED AUTOMATED EXTRACTION MODEL FOR CHANNEL GEOMETRY
Energy Technology Data Exchange (ETDEWEB)
JUDI, DAVID [Los Alamos National Laboratory; KALYANAPU, ALFRED [Los Alamos National Laboratory; MCPHERSON, TIMOTHY [Los Alamos National Laboratory; BERSCHEID, ALAN [Los Alamos National Laboratory
2007-01-17
This paper describes an automated Channel Morphology Tool (CMT) developed in ArcGIS 9.1 environment. The CMT creates cross-sections along a stream centerline and uses a digital elevation model (DEM) to create station points with elevations along each of the cross-sections. The generated cross-sections may then be exported into a hydraulic model. Along with the rapid cross-section generation the CMT also eliminates any cross-section overlaps that might occur due to the sinuosity of the channels using the Cross-section Overlap Correction Algorithm (COCoA). The CMT was tested by extracting cross-sections from a 5-m DEM for a 50-km channel length in Houston, Texas. The extracted cross-sections were compared directly with surveyed cross-sections in terms of the cross-section area. Results indicated that the CMT-generated cross-sections satisfactorily matched the surveyed data.
A no extensive statistical model for the nucleon structure function
Trevisan, Luis A.; Mirez, Carlos
2013-03-01
We studied an application of nonextensive thermodynamics to describe the structure function of nucleon, in a model where the usual Fermi-Dirac and Bose-Einstein energy distribution were replaced by the equivalent functions of the q-statistical. The parameters of the model are given by an effective temperature T, the q parameter (from Tsallis statistics), and two chemical potentials given by the corresponding up (u) and down (d) quark normalization in the nucleon.
a Nonextensive Statistical Model for the Nucleon Structure Function
Trevisan, Luis Augusto; Mirez, Carlos
2013-07-01
We studied an application of nonextensive thermodynamics to describe the structure function of nucleon, in a model where the usual Fermi-Dirac and Bose-Einstein energy distribution were replaced by the equivalent functions of the q-statistical. The parameters of the model are given by an effective temperature T, the q parameter (from Tsallis statistics), and two chemical potentials given by the corresponding up (u) and down (d) quark normalizations in the nucleon.
Building Statistical Shape Spaces for 3D Human Modeling
Pishchulin, Leonid; Wuhrer, Stefanie; Helten, Thomas; Theobalt, Christian; Schiele, Bernt
2015-01-01
Statistical models of 3D human shape and pose learned from scan databases have developed into valuable tools to solve a variety of vision and graphics problems. Unfortunately, most publicly available models are of limited expressiveness as they were learned on very small databases that hardly reflect the true variety in human body shapes. In this paper, we contribute by rebuilding a widely used statistical body representation from the largest commercially available scan database, and making t...
Statistical Language Modeling for Automatic Speech Recognition of Agglutinative Languages
Ar&#;soy, Ebru; Kurimo, Mikko; Sara&#;lar, Murat; Hirsim&#;ki, Teemu; Pylkk&#;nen, Janne; Alum&#;e, Tanel; Sak, Ha&#;im
2008-01-01
This work presents statistical language models trained on different agglutinative languages utilizing a lexicon based on the recently proposed unsupervised statistical morphs. The significance of this work is that similarly generated sub-word unit lexica are developed and successfully evaluated in three different LVCSR systems in different languages. In each case the morph-based approach is at least as good or better than a very large vocabulary wordbased LVCSR language model. Even though usi...
Statistical modelling of mitochondrial power supply.
James, A T; Wiskich, J T; Conyers, R A
1989-01-01
By experiment and theory, formulae are derived to calculate the response of mitochondrial power supply, in flux and potential, to an ATP consuming enzyme load, incorporating effects of varying amounts of (i) enzyme, (ii) total circulating adenylate, and (iii) inhibition of the ATP/ADP translocase. The formulae, which apply between about 20% and 80% of maximum respiration, are the same as for the current and voltage of an electrical circuit in which a battery with potential, linear in the logarithm of the total adenylate, charges another battery whose opposing potential is also linear in the same logarithm, through three resistances. These resistances produce loss of potential due to dis-equilibrium of (i) intramitochondrial oxidative phosphorylation, (ii) the ATP/ADP translocase, and (iii) the ATP-consuming enzyme load. The model is represented geometrically by the following configuration: when potential is plotted against flux, the points lie on two pencils of lines each concurrent at zero respiration, the two pencils describing the respective characteristics of the mitochondrion and enzyme. Control coefficients and elasticities are calculated from the formulae. PMID:2708917
MODELING OF VEHICULAR STEERING EFFICIENCY IN TRAFFIC DIRECTION MOTION CHANNEL
V. A. Ganai; S. A. O. Diab Abdullah
2011-01-01
The paper formulates and solves an actual problem pertaining to vehicular steering efficiency in traffic direction motion channel. Models of operator-drivers with low, medium and high rates in motivational perception of road conditions and also a model for controlling a traffic direction motion have been taken into ccount in the paper. Modeling has been done by using MATLAB.
A process-based model of submarine channel deposition
Peakall, J.
2011-12-01
Models of system scale architecture have been developed primarily from outcrop-based observations, and intra-channel architecture models are largely absent. Here, a process-based model of submarine channel deposition is developed that explains large-scale channel architecture, and predicts patterns and variability of intra-channel architecture. Flow dynamics: The 3D flow field is crucial in determining sediment routing and deposition in channels. Experimental, analytical and computational fluid dynamic modelling has demonstrated that the 3D flow fields in submarine channels can exhibit one of two states. Either 'river-like' where secondary flows exhibit basally directed inward flow at bend apices, or 'river-reversed' flow where the flow-cell is flipped and basally directed flows are towards the outer bank at bend apices. Debate centres around the relative frequency of each. What is clear is that they are controlled by factors such as flow stratification, sediment load, sediment size, basal slope, and Froude numbers, with higher values encouraging flow-reversal and vice-versa. Such changes in secondary flow are linked to changes in the position of the downstream velocity core; this moves towards the outer bank in the river-reversed case. Importantly, many submarine channels are likely to show both river-like and river-reversed behaviour in the same channel due to changes in downstream flow properties, and consequently as flow waxes and then ultimately wanes, the position of the transformation between these two regimes will migrate progressively upstream (waning flow) or downstream (waxing flow). Furthermore, there will be variation over the lifetime of the channel, with early stage erosive and bypass channel phases exhibiting enhanced river-reversed flow relative to river-like, with this ratio changing as channels progressively move into depositional and then strongly depositional phases. Sedimentary deposits: A key first-order control on intra-channel architecture
FLOOD ROUTING MODELS IN CONFLUENT AND DIVIDING CHANNELS
Institute of Scientific and Technical Information of China (English)
范平; 李家春; 刘青泉
2004-01-01
By introducing a water depth connecting formula, the hydraulic equations in the dividing channel system were coupled and the relation of discharge distribution between the branches of the dividing channels can be yielded. In this manner, a numerical model for the confluent channels was established to study the variation of backwater effects with the parameters in the channel junction. The meeting of flood peaks in the mainstream and tributary can be analyzed with this model. The flood peak meeting is found to be a major factor for the extremely high water level in the mainstream during the 1998 Yangtze River flood. Subsequently the variations of discharge distribution and water level with channel parameters between each branch in this system were studied as well. As a result, flood evolution caused by Jingjiang River shortcut and sediment deposition in the entrance of dividing channels of the Yangtze River may be qualitatively elucidated. It is suggested to be an effective measure for flood mitigation to enhance regulation capability of reservoirs available upstream of the tributaries and harness branch entrance channels.
Modeling Channelization in Coastal Wetlands with Ecological Feedbacks
Hughes, Z. J.; Mahadevan, A.; Pennings, S.; FitzGerald, D.
2014-12-01
In coastal wetlands in Georgia and South Carolina, dendritic channel networks are actively incising headward at the rate of nearly 2 m/yr. The future geomorphic evolution of these marshes remains in question as rates of relative sea-level rise increase. Our objective is to understand the mechanisms that lead to the evolution of these channel networks through field observations and modeling. We model the geomorphological evolution of tidal creeks by viewing the wetland as a permeable medium. The porosity of the medium affects its hydraulic conductivity, which in turn is altered by erosion. Our multiphase model spontaneously generates channelization and branching networks through flow and erosion. In our field studies, we find that crabs play an active role in grazing vegetation and in the bioturbation of sediments. These effects are incorporated in our model based on field and laboratory observations of crab behavior and its effects on the marsh. We find the erosional patterns and channelization are significantly altered by the faunal feedback. Crabs enhance the growth of channels, inducing the headward erosion of creeks where flow-induced stresses are weakest. They are instrumental in generating high rates of creek extension, which channelize the marsh more effectively in response to sea-level rise. This indicates that the evolution of coastal wetlands is responding to interactions between physics and ecology and highlights the importance of the faunal contribution to these feedbacks.
Modeling water droplet condensation and evaporation in DNS of turbulent channel flow
International Nuclear Information System (INIS)
In this paper a point particle model for two-way coupling in water droplet-laden incompressible turbulent flow of air is proposed. The model is based on conservation laws and semi-empirical correlations. It has been implemented and tested in a DNS code based for turbulent channel flow with an Eulerian-Lagrangian approach. The two-way coupling is investigated in terms of the effects of mass and heat transfer on the droplets distributions along the channel wall-normal direction and by comparison of the droplet temperature statistics with respect to the case without evaporation and condensation. A remarkable conclusion is that the presence of evaporating and condensing droplets results in an increase in the non-dimensional heat transfer coefficient of the channel flow represented by the Nusselt number.
Numerical modelling of channel migration with application to laboratory rivers
Institute of Scientific and Technical Information of China (English)
Jian SUN; Bin-liang LIN; Hong-wei KUANG
2015-01-01
The paper presents the development of a morphological model and its application to experimental model rivers. The model takes into account the key processes of channel migration, including bed deformation, bank failure and wetting and drying. Secondary flows in bends play an important role in lateral sediment transport, which further affects channel migration. A new formula has been derived to predict the near-bed secondary flow speed, in which the magnitude of the speed is linked to the lateral water level gradient. Since only non-cohesive sediment is considered in the current study, the bank failure is modelled based on the concept of submerged angle of repose. The wetting and drying process is modelled using an existing method. Comparisons between the numerical model predictions and experimental observations for various discharges have been made. It is found that the model predicted channel planform and cross-sectional shapes agree generally well with the laboratory observations. A scenario analysis is also carried out to investigate the impact of secondary flow on the channel migration process. It shows that if the effect of secondary flow is ignored, the channel size in the lateral direction will be seriously underestimated.
Models for probability and statistical inference theory and applications
Stapleton, James H
2007-01-01
This concise, yet thorough, book is enhanced with simulations and graphs to build the intuition of readersModels for Probability and Statistical Inference was written over a five-year period and serves as a comprehensive treatment of the fundamentals of probability and statistical inference. With detailed theoretical coverage found throughout the book, readers acquire the fundamentals needed to advance to more specialized topics, such as sampling, linear models, design of experiments, statistical computing, survival analysis, and bootstrapping.Ideal as a textbook for a two-semester sequence on probability and statistical inference, early chapters provide coverage on probability and include discussions of: discrete models and random variables; discrete distributions including binomial, hypergeometric, geometric, and Poisson; continuous, normal, gamma, and conditional distributions; and limit theory. Since limit theory is usually the most difficult topic for readers to master, the author thoroughly discusses mo...
International Nuclear Information System (INIS)
For the year 2002, part of the figures shown in the tables of the Energy Review are partly preliminary. The annual statistics of the Energy Review also includes historical time-series over a longer period (see e.g. Energiatilastot 2001, Statistics Finland, Helsinki 2002). The applied energy units and conversion coefficients are shown in the inside back cover of the Review. Explanatory notes to the statistical tables can be found after tables and figures. The figures presents: Changes in GDP, energy consumption and electricity consumption, Carbon dioxide emissions from fossile fuels use, Coal consumption, Consumption of natural gas, Peat consumption, Domestic oil deliveries, Import prices of oil, Consumer prices of principal oil products, Fuel prices in heat production, Fuel prices in electricity production, Price of electricity by type of consumer, Average monthly spot prices at the Nord pool power exchange, Total energy consumption by source and CO2-emissions, Supply and total consumption of electricity GWh, Energy imports by country of origin in January-June 2003, Energy exports by recipient country in January-June 2003, Consumer prices of liquid fuels, Consumer prices of hard coal, natural gas and indigenous fuels, Price of natural gas by type of consumer, Price of electricity by type of consumer, Price of district heating by type of consumer, Excise taxes, value added taxes and fiscal charges and fees included in consumer prices of some energy sources and Excise taxes, precautionary stock fees on oil pollution fees on energy products
International Nuclear Information System (INIS)
For the year 2003 and 2004, the figures shown in the tables of the Energy Review are partly preliminary. The annual statistics of the Energy Review also includes historical time-series over a longer period (see e.g. Energiatilastot, Statistics Finland, Helsinki 2003, ISSN 0785-3165). The applied energy units and conversion coefficients are shown in the inside back cover of the Review. Explanatory notes to the statistical tables can be found after tables and figures. The figures presents: Changes in GDP, energy consumption and electricity consumption, Carbon dioxide emissions from fossile fuels use, Coal consumption, Consumption of natural gas, Peat consumption, Domestic oil deliveries, Import prices of oil, Consumer prices of principal oil products, Fuel prices in heat production, Fuel prices in electricity production, Price of electricity by type of consumer, Average monthly spot prices at the Nord pool power exchange, Total energy consumption by source and CO2-emissions, Supplies and total consumption of electricity GWh, Energy imports by country of origin in January-March 2004, Energy exports by recipient country in January-March 2004, Consumer prices of liquid fuels, Consumer prices of hard coal, natural gas and indigenous fuels, Price of natural gas by type of consumer, Price of electricity by type of consumer, Price of district heating by type of consumer, Excise taxes, value added taxes and fiscal charges and fees included in consumer prices of some energy sources and Excise taxes, precautionary stock fees on oil pollution fees
Comparison between new thermohydraulic one-channel models and experiments
Blender, H.; Elzmann, J.
1981-11-01
Five different thermohydraulic one-channel models, COCHA, FRANCESCA, MARMITA, STASWR and THS, were tested bu experimentally checking two-phase flows along a boiling water reactor fuel element. As regards the evolution of the vapor content along the cooling channel, the agreement between all the programs and the measurements is satisfactory for small to middle entrance undercooling in the domain of undercooled boiling. For high undercooling, only the COCHA program gives satisfactory results. For the middle part of the cooling channel, all programs are satisfactory, while in the upper part, especially for increasing outlet vapor contents, the calculated values are generally too low for all programs, and especially for FRANCESCA.
Yang, Huaiyu; Gao, Zhaobing; Li, Ping; Yu, Kunqian; Yu, Ye; Xu, Tian-Le; Li, Min; Jiang, Hualiang
2012-01-01
Voltage sensing confers conversion of a change in membrane potential to signaling activities underlying the physiological processes. For an ion channel, voltage sensitivity is usually experimentally measured by fitting electrophysiological data to Boltzmann distributions. In our study, a two-state model of the ion channel and equilibrium statistical mechanics principle were used to test the hypothesis of empirically calculating the overall voltage sensitivity of an ion channel on the basis of its closed and open conformations, and determine the contribution of individual residues to the voltage sensing. We examined the theoretical paradigm by performing experimental measurements with Kv1.2 channel and a series of mutants. The correlation between the calculated values and the experimental values is at respective level, R2 = 0.73. Our report therefore provides in silico prediction of key conformations and has identified additional residues critical for voltage sensing. PMID:22768937
Dynamic Propagation Channel Characterization and Modeling for Human Body Communication
Lei Wang; Jingjing Ma; Zhicheng Li; Hong Chen; Zedong Nie
2012-01-01
This paper presents the first characterization and modeling of dynamic propagation channels for human body communication (HBC). In-situ experiments were performed using customized transceivers in an anechoic chamber. Three HBC propagation channels, i.e., from right leg to left leg, from right hand to left hand and from right hand to left leg, were investigated under thirty-three motion scenarios. Snapshots of data (2,800,000) were acquired from five volunteers. Various path gains caused by di...
Microscopic model for selective permeation in ion channels.
Wu, J.
1991-01-01
Ionic permeation in the selectivity filter of ion channels is analyzed by a microscopic model based on molecular kinetic theory. The energy and flux equations are derived by assuming that: (a) the selectivity filter is formed by a symmetrical array of carbonyl groups; (b) ion movement is near the axis of the channel; (c) a fraction of water molecules is separated from the ion while it moves across the selectivity filter; (d) the applied voltage drops linearly across the selectivity filter; (e...
Modeling Permeation Energetics in the KcsA Potassium Channel
Garofoli, S.; Jordan, P C
2003-01-01
The thermodynamics of cation permeation through the KcsA K+ channel selectivity filter is studied from the perspective of a physically transparent semimicroscopic model using Monte Carlo free energy integration. The computational approach chosen permits dissection of the separate contributions to ionic stabilization arising from different parts of the channel (selectivity filter carbonyls, single-file water, cavity water, reaction field of bulk water, inner helices, ionizable residues). All f...
Statistical detection model for eddy-current systems
International Nuclear Information System (INIS)
This chapter presents a detailed analysis of some measured noise data and the results of using those data with a probe-flaw interaction model to compute the surface-crack detection characteristics of two different air-core coil probes. The objective is to develop a statistical model for determining the probability of detecting a given flaw using an eddy-current system. The basis for developing a statistical detection model is a measurement model that relates the output voltage of the system to its various signal and noise components. Topics considered include statistics of the measured background voltage, calibration of the probe-flaw interaction model and signal-to-noise ratio (SNR) definition, the operating characteristic, and a comparison of air-core probes
A New Method of Blind Source Separation Using Single-Channel ICA Based on Higher-Order Statistics
Directory of Open Access Journals (Sweden)
Guangkuo Lu
2015-01-01
Full Text Available Methods of utilizing independent component analysis (ICA give little guidance about practical considerations for separating single-channel real-world data, in which most of them are nonlinear, nonstationary, and even chaotic in many fields. To solve this problem, a three-step method is provided in this paper. In the first step, the measured signal which is assumed to be piecewise higher order stationary time series is introduced and divided into a series of higher order stationary segments by applying a modified segmentation algorithm. Then the state space is reconstructed and the single-channel signal is transformed into a pseudo multiple input multiple output (MIMO mode using a method of nonlinear analysis based on the high order statistics (HOS. In the last step, ICA is performed on the pseudo MIMO data to decompose the single channel recording into its underlying independent components (ICs and the interested ICs are then extracted. Finally, the effectiveness and excellence of the higher order single-channel ICA (SCICA method are validated with measured data throughout experiments. Also, the proposed method in this paper is proved to be more robust under different SNR and/or embedding dimension via explicit formulae and simulations.
Ultra-Wideband Channel Modeling for Intravehicle Environment
Directory of Open Access Journals (Sweden)
Talty Timothy
2009-01-01
Full Text Available Abstract With its fine immunity to multipath fading, ultra-wideband (UWB is considered to be a potential technique in constructing intravehicle wireless sensor networks. In the UWB literature, extensive measuring and modeling work have been done for indoor or outdoor propagation, but very few measurements were performed in intravehicle environments. This paper reports our effort in measuring and modeling the UWB propagation channel in commercial vehicle environment. In our experiment, channel sounding is performed in time domain for two environments. In one environment, the transmitting and the receiving antennas are put beneath the chassis. In another environment, both antennas are located inside the engine compartment. It is observed that paths arrive in clusters in the latter environment but such clustering phenomenon does not exist in the former case. Different multipath models are used to describe the two different propagation channels. For the engine compartment environment, we describe the multipath propagation with the classical S-V model. And for the chassis environment, the channel impulse response is just represented as the sum of multiple paths. Observation reveals that the power delay profile (PDP in this environment does not start with a sharp maximum but has a rising edge. A modified S-V PDP model is used to account for this rising edge. Based on the analysis of the measured data, channel model parameters are extracted for both environments.
Ultra-Wideband Channel Modeling for Intravehicle Environment
Directory of Open Access Journals (Sweden)
Weihong Niu
2009-01-01
Full Text Available With its fine immunity to multipath fading, ultra-wideband (UWB is considered to be a potential technique in constructing intravehicle wireless sensor networks. In the UWB literature, extensive measuring and modeling work have been done for indoor or outdoor propagation, but very few measurements were performed in intravehicle environments. This paper reports our effort in measuring and modeling the UWB propagation channel in commercial vehicle environment. In our experiment, channel sounding is performed in time domain for two environments. In one environment, the transmitting and the receiving antennas are put beneath the chassis. In another environment, both antennas are located inside the engine compartment. It is observed that paths arrive in clusters in the latter environment but such clustering phenomenon does not exist in the former case. Different multipath models are used to describe the two different propagation channels. For the engine compartment environment, we describe the multipath propagation with the classical S-V model. And for the chassis environment, the channel impulse response is just represented as the sum of multiple paths. Observation reveals that the power delay profile (PDP in this environment does not start with a sharp maximum but has a rising edge. A modified S-V PDP model is used to account for this rising edge. Based on the analysis of the measured data, channel model parameters are extracted for both environments.
Attitude Estimation for In-Service Base Station Antenna Using Downlink Channel Fading Statistics
2015-01-01
A maximum-likelihood-estimation method is proposed for extracting the attitude of a sectoring base station (BS) antenna by using the received signal strengths observed by multiple user equipments (UEs) in this contribution. This method calculates the likelihood function of the antenna attitude derived by taking into account the multiscale fading statistics, that is, path loss, shadowing, and multipath fading. Depending on whether a calibration result of these fading statistics is available or...
International Nuclear Information System (INIS)
Recently, an adjustable, high-sensitivity, wide dynamic range, two-channel wavefront sensor based on moiré deflectometry was proposed by Rasouli et al (2010 Opt. Express 18 23906). In this work we have used this sensor on a telescope for measuring turbulence-induced wavefront distortions. A slightly divergent laser beam passes through turbulent ground level atmosphere and enters the telescope’s aperture. The laser beam is collimated behind the telescope’s focal point by means of a collimator and the beam enters the wavefront sensor. First, from deviations in the moiré fringes we calculate the two orthogonal components of the angle of arrival at each location across the wavefront. The deviations have been deduced in successive frames which allows evolution of the wavefront shape and Fried’s seeing parameter r0 to be determined. Mainly, statistical analysis of the reconstructed wavefront distortions are presented. The achieved accuracy in the measurements and comparison between the measurements and the theoretical models are presented. Owing to the use of the sensor on a telescope, and using sub-pixel accuracy for the measurement of the moiré fringe displacements, the sensitivity of the measurements is improved by more than one order of magnitude. In this work we have achieved a minimum measurable angle of arrival fluctuations equal to 3.7 × 10−7 rad or 0.07 arc s. Besides, because of the large area of the telescope’s aperture, a high spatial resolution is achieved in detecting the spatial perturbations of the atmospheric turbulence. (paper)
Equilibrium Statistical-Thermal Models in High-Energy Physics
Tawfik, Abdel Nasser
2014-01-01
We review some recent highlights from the applications of statistical-thermal models to different experimental measurements and lattice QCD thermodynamics, that have been made during the last decade. We start with a short review of the historical milestones on the path of constructing statistical-thermal models for heavy-ion physics. We discovered that Heinz Koppe formulated in 1948 an almost complete recipe for the statistical-thermal models. In 1950, Enrico Fermi generalized this statistical approach, in which he started with a general cross-section formula and inserted into it simplifying assumptions about the matrix element of the interaction process that likely reflects many features of the high-energy reactions dominated by density in the phase space of final states. In 1964, Hagedorn systematically analysed the high-energy phenomena using all tools of statistical physics and introduced the concept of limiting temperature based on the statistical bootstrap model. It turns to be quite often that many-par...
Model studies of dense water overflows in the Faroese Channels
Cuthbertson, Alan; Davies, Peter; Stashchuk, Nataliya; Vlasenko, Vasiliy
2014-01-01
The overflow of dense water from the Nordic Seas through the Faroese Channel system was investigated through combined laboratory experiments and numerical simulations using the Massachusetts Institute of Technology General Circulation Model. In the experimental study, a scaled, topographic representation of the Faroe-Shetland Channel, Wyville-Thomson Basin and Ridge and Faroe Bank Channel seabed bathymetry was constructed and mounted in a rotating tank. A series of parametric experiments was conducted using dye-tracing and drogue-tracking techniques to investigate deep-water overflow pathways and circulation patterns within the modelled region. In addition, the structure of the outflowing dense bottom water was investigated through density profiling along three cross-channel transects located in the Wyville-Thomson Basin and the converging, up-sloping approach to the Faroe Bank Channel. Results from the dye-tracing studies demonstrate a range of parametric conditions under which dense water overflow across the Wyville-Thomson Ridge is shown to occur, as defined by the Burger number, a non-dimensional length ratio and a dimensionless dense water volume flux parameter specified at the Faroe-Shetland Channel inlet boundary. Drogue-tracking measurements reveal the complex nature of flow paths and circulations generated in the modelled topography, particularly the development of a large anti-cyclonic gyre in the Wyville-Thompson Basin and up-sloping approach to the Faroe Bank Channel, which diverts the dense water outflow from the Faroese shelf towards the Wyville-Thomson Ridge, potentially promoting dense water spillage across the ridge itself. The presence of this circulation is also indicated by associated undulations in density isopycnals across the Wyville-Thomson Basin. Numerical simulations of parametric test cases for the main outflow pathways and density structure in a similarly-scaled Faroese Channels model domain indicate excellent qualitative agreement with
Matolak, D. W.; Apaza, Rafael; Foore, Lawrence R.
2006-01-01
We describe a recently completed wideband wireless channel characterization project for the 5 GHz Microwave Landing System (MLS) extension band, for airport surface areas. This work included mobile measurements at large and small airports, and fixed point-to-point measurements. Mobile measurements were made via transmission from the air traffic control tower (ATCT), or from an airport field site (AFS), to a receiving ground vehicle on the airport surface. The point-to-point measurements were between ATCT and AFSs. Detailed statistical channel models were developed from all these measurements. Measured quantities include propagation path loss and power delay profiles, from which we obtain delay spreads, frequency domain correlation (coherence bandwidths), fading amplitude statistics, and channel parameter correlations. In this paper we review the project motivation, measurement coordination, and illustrate measurement results. Example channel modeling results for several propagation conditions are also provided, highlighting new findings.
Complex Data Modeling and Computationally Intensive Statistical Methods
Mantovan, Pietro
2010-01-01
The last years have seen the advent and development of many devices able to record and store an always increasing amount of complex and high dimensional data; 3D images generated by medical scanners or satellite remote sensing, DNA microarrays, real time financial data, system control datasets. The analysis of this data poses new challenging problems and requires the development of novel statistical models and computational methods, fueling many fascinating and fast growing research areas of modern statistics. The book offers a wide variety of statistical methods and is addressed to statistici
In all likelihood statistical modelling and inference using likelihood
Pawitan, Yudi
2001-01-01
Based on a course in the theory of statistics this text concentrates on what can be achieved using the likelihood/Fisherian method of taking account of uncertainty when studying a statistical problem. It takes the concept ot the likelihood as providing the best methods for unifying the demands of statistical modelling and the theory of inference. Every likelihood concept is illustrated by realistic examples, which are not compromised by computational problems. Examples range from asimile comparison of two accident rates, to complex studies that require generalised linear or semiparametric mode
Statistical modelling of tropical cyclone tracks: non-normal innovations
Hall, Tim; Jewson, Stephen
2005-01-01
We present results from the sixth stage of a project to build a statistical hurricane model. Previous papers have described our modelling of the tracks, genesis, and lysis of hurricanes. In our track model we have so far employed a normal distribution for the residuals when computing innovations, even though we have demonstrated that their distribution is not normal. Here, we test to see if the track model can be improved by including more realistic non-normal innovations. The results are mix...
Advances on statistical/thermodynamical models for unpolarized structure functions
International Nuclear Information System (INIS)
During the eights and nineties many statistical/thermodynamical models were proposed to describe the nucleons’ structure functions and distribution of the quarks in the hadrons. Most of these models describe the compound quarks and gluons inside the nucleon as a Fermi / Bose gas respectively, confined in a MIT bag with continuous energy levels. Another models considers discrete spectrum. Some interesting features of the nucleons are obtained by these models, like the sea asymmetries -d/-u and -d–-u.
Speech emotion recognition based on statistical pitch model
Institute of Scientific and Technical Information of China (English)
WANG Zhiping; ZHAO Li; ZOU Cairong
2006-01-01
A modified Parzen-window method, which keep high resolution in low frequencies and keep smoothness in high frequencies, is proposed to obtain statistical model. Then, a gender classification method utilizing the statistical model is proposed, which have a 98% accuracy of gender classification while long sentence is dealt with. By separation the male voice and female voice, the mean and standard deviation of speech training samples with different emotion are used to create the corresponding emotion models. Then the Bhattacharyya distance between the test sample and statistical models of pitch, are utilized for emotion recognition in speech.The normalization of pitch for the male voice and female voice are also considered, in order to illustrate them into a uniform space. Finally, the speech emotion recognition experiment based on K Nearest Neighbor shows that, the correct rate of 81% is achieved, where it is only 73.85%if the traditional parameters are utilized.
Probabilistic Quantitative Precipitation Forecasting Using Ensemble Model Output Statistics
Scheuerer, Michael
2013-01-01
Statistical post-processing of dynamical forecast ensembles is an essential component of weather forecasting. In this article, we present a post-processing method that generates full predictive probability distributions for precipitation accumulations based on ensemble model output statistics (EMOS). We model precipitation amounts by a generalized extreme value distribution that is left-censored at zero. This distribution permits modelling precipitation on the original scale without prior transformation of the data. A closed form expression for its continuous rank probability score can be derived and permits computationally efficient model fitting. We discuss an extension of our approach that incorporates further statistics characterizing the spatial variability of precipitation amounts in the vicinity of the location of interest. The proposed EMOS method is applied to daily 18-h forecasts of 6-h accumulated precipitation over Germany in 2011 using the COSMO-DE ensemble prediction system operated by the Germa...
Linear mixed models a practical guide using statistical software
West, Brady T; Galecki, Andrzej T
2006-01-01
Simplifying the often confusing array of software programs for fitting linear mixed models (LMMs), Linear Mixed Models: A Practical Guide Using Statistical Software provides a basic introduction to primary concepts, notation, software implementation, model interpretation, and visualization of clustered and longitudinal data. This easy-to-navigate reference details the use of procedures for fitting LMMs in five popular statistical software packages: SAS, SPSS, Stata, R/S-plus, and HLM. The authors introduce basic theoretical concepts, present a heuristic approach to fitting LMMs based on bo
Asymptotic laws for disparity statistics in product multinomial models
Czech Academy of Sciences Publication Activity Database
Morales, D.; Pardo, L.; Vajda, Igor
2003-01-01
Roč. 85, č. 3 (2003), s. 335-360. ISSN 0047-259X R&D Projects: GA AV ČR IAA1075101 Grant ostatní: BMF(ES) 2000-0800 Institutional research plan: CEZ:AV0Z1075907 Keywords : Goodness-of-fit testing * product multinomial models * disparity statistics Subject RIV: BB - Applied Statistics, Operational Research Impact factor: 0.320, year: 2003
Statistical State-Space Modeling via Kalman Filtration
Czech Academy of Sciences Publication Activity Database
Brabec, Marek
New York: Nova Science Publishers, 2011 - (Gomez, J.), s. 77-110. (Mathematics Research Developments). ISBN 978-1-61761-462-0 Institutional research plan: CEZ:AV0Z10300504 Keywords : kalman filter * state-space * time-series model * prediction error decomposition * statistical estimation Subject RIV: BB - Applied Statistics, Operational Research https://www.novapublishers.com/catalog/product_info.php?products_id=28940
Quantum Statistical Physics of a Microscopic Glass Model
Thesen, Michael
2003-01-01
We investigate the quantum statistical physics of a microscopic mean-field glass model in various approximations using the replica method and effective action methods from quantum field theory. We recover results from a semiclassical treatment and find relations to quantum spherical p-spin models.
Binary and ternary fission within the statistical model
International Nuclear Information System (INIS)
The binary and ternary nuclear fission are treated within the statistical model. At the scission point we calculate the potentials as functions of the deformations of the fragments in the dinuclear model. The potentials give the mass and charge distributions of the fission fragments. The ternary fission is assumed to occur during the binary fission. (author)
Magnetic susceptibility of a two-channel Anderson model
International Nuclear Information System (INIS)
Temperature-dependent magnetic susceptibility is calculated for a two-channel Anderson model, by using the numerical renormalization group plus an interleaving procedure to recover the continuum of the conduction band. Fermi- and non-Fermi-liquid fixed points can be obtained in the low-temperature regime of the model susceptibility
Magnetic susceptibility of a two-channel Anderson model
Energy Technology Data Exchange (ETDEWEB)
Ferreira, J.V.B.; Oliveira, L.N. de; Cox, D.L.; Libero, V.L. E-mail: valter@if.sc.usp.br
2001-05-01
Temperature-dependent magnetic susceptibility is calculated for a two-channel Anderson model, by using the numerical renormalization group plus an interleaving procedure to recover the continuum of the conduction band. Fermi- and non-Fermi-liquid fixed points can be obtained in the low-temperature regime of the model susceptibility.
Map-Based Channel Model for Urban Macrocell Propagation Scenarios
Directory of Open Access Journals (Sweden)
Jose F. Monserrat
2015-01-01
Full Text Available The evolution of LTE towards 5G has started and different research projects and institutions are in the process of verifying new technology components through simulations. Coordination between groups is strongly recommended and, in this sense, a common definition of test cases and simulation models is needed. The scope of this paper is to present a realistic channel model for urban macrocell scenarios. This model is map-based and takes into account the layout of buildings situated in the area under study. A detailed description of the model is given together with a comparison with other widely used channel models. The benchmark includes a measurement campaign in which the proposed model is shown to be much closer to the actual behavior of a cellular system. Particular attention is given to the outdoor component of the model, since it is here where the proposed approach is showing main difference with other previous models.
Entanglement structure of the two-channel Kondo model
Alkurtass, Bedoor; Bayat, Abolfazl; Affleck, Ian; Bose, Sougato; Johannesson, Henrik; Sodano, Pasquale; Sørensen, Erik S.; Le Hur, Karyn
2016-02-01
Two electronic channels competing to screen a single impurity spin, as in the two-channel Kondo model, are expected to generate a ground state with a nontrivial entanglement structure. We exploit a spin-chain representation of the two-channel Kondo model to probe the ground-state block entropy, negativity, tangle, and Schmidt gap, using a density matrix renormalization group approach. In the presence of symmetric coupling to the two channels, we confirm field-theory predictions for the boundary entropy difference ln(gUV/gIR) =ln(2 ) /2 between the ultraviolet and infrared limits and the leading ln(x )/x impurity correction to the block entropy. The impurity entanglement Simp is shown to scale with the characteristic length ξ2 CK. We show that both the Schmidt gap and the entanglement of the impurity with one of the channels—as measured by the negativity—faithfully serve as order parameters for the impurity quantum phase transition appearing as a function of channel asymmetry, allowing for explicit determination of critical exponents, ν ≈2 and β ≈0.2 . Remarkably, we find the emergence of tripartite entanglement only in the vicinity of the critical channel-symmetric point.
Monte Carlo Modeling of Crystal Channeling at High Energies
Schoofs, Philippe; Cerutti, Francesco
Charged particles entering a crystal close to some preferred direction can be trapped in the electromagnetic potential well existing between consecutive planes or strings of atoms. This channeling effect can be used to extract beam particles if the crystal is bent beforehand. Crystal channeling is becoming a reliable and efficient technique for collimating beams and removing halo particles. At CERN, the installation of silicon crystals in the LHC is under scrutiny by the UA9 collaboration with the goal of investigating if they are a viable option for the collimation system upgrade. This thesis describes a new Monte Carlo model of planar channeling which has been developed from scratch in order to be implemented in the FLUKA code simulating particle transport and interactions. Crystal channels are described through the concept of continuous potential taking into account thermal motion of the lattice atoms and using Moliere screening function. The energy of the particle transverse motion determines whether or n...
A channel transmission losses model for different dryland rivers
Directory of Open Access Journals (Sweden)
A. C. Costa
2011-10-01
Full Text Available Channel transmission losses in drylands take place normally in extensive alluvial channels or streambeds underlain by fractured rocks. They can play an important role in flood prediction, groundwater recharge, freshwater supply and channel-associated ecosystems. We aim to develop a semi-distributed channel transmission losses model, a coupling of formulations which are more suitable for data-scarce dryland environments, applicable for both hydraulically disconnected losing streams and hydraulically connected losing(/gaining streams. Hence, this approach should be able to cover a large variation in climate and hydro-geologic controls, which are typically found in dryland regions of the world. Traditionally, channel transmission losses models have been developed for site specific conditions. Our model was firstly evaluated for a losing/gaining, hydraulically connected 30 km reach of the Jaguaribe River, Ceará, Brazil, which controls a catchment area of 20 000 km^{2}. Secondly, we applied it to a small losing, hydraulically disconnected 1.5 km channel reach in the Walnut Gulch Experimental Watershed (WGEW, Arizona, USA. The model based on the perceptual hydrological models of the reaches was able to predict reliably the stream flow for the both case studies. For the larger river reach, the evaluation of the hypotheses on the dominant hydrological processes was fundamental for reducing structural model uncertainties and improving the stream flow prediction, showing that both lateral stream-aquifer water fluxes and groundwater flow in the underlying alluvium parallel to the river course are necessary to predict stream flow and channel transmission losses, the former process being more relevant than the latter. The sensitivity analysis showed that even if the parameters can "potentially" produce large flow exchanges between model units in the saturated part of the modelling, large flow exchanges do not happen because they are restricted by
Statistical Design Model (SDM) of satellite thermal control subsystem
Mirshams, Mehran; Zabihian, Ehsan; Aarabi Chamalishahi, Mahdi
2016-07-01
Satellites thermal control, is a satellite subsystem that its main task is keeping the satellite components at its own survival and activity temperatures. Ability of satellite thermal control plays a key role in satisfying satellite's operational requirements and designing this subsystem is a part of satellite design. In the other hand due to the lack of information provided by companies and designers still doesn't have a specific design process while it is one of the fundamental subsystems. The aim of this paper, is to identify and extract statistical design models of spacecraft thermal control subsystem by using SDM design method. This method analyses statistical data with a particular procedure. To implement SDM method, a complete database is required. Therefore, we first collect spacecraft data and create a database, and then we extract statistical graphs using Microsoft Excel, from which we further extract mathematical models. Inputs parameters of the method are mass, mission, and life time of the satellite. For this purpose at first thermal control subsystem has been introduced and hardware using in the this subsystem and its variants has been investigated. In the next part different statistical models has been mentioned and a brief compare will be between them. Finally, this paper particular statistical model is extracted from collected statistical data. Process of testing the accuracy and verifying the method use a case study. Which by the comparisons between the specifications of thermal control subsystem of a fabricated satellite and the analyses results, the methodology in this paper was proved to be effective. Key Words: Thermal control subsystem design, Statistical design model (SDM), Satellite conceptual design, Thermal hardware
Validation of statistical models for creep rupture by parametric analysis
Energy Technology Data Exchange (ETDEWEB)
Bolton, J., E-mail: john.bolton@uwclub.net [65, Fisher Ave., Rugby, Warks CV22 5HW (United Kingdom)
2012-01-15
Statistical analysis is an efficient method for the optimisation of any candidate mathematical model of creep rupture data, and for the comparative ranking of competing models. However, when a series of candidate models has been examined and the best of the series has been identified, there is no statistical criterion to determine whether a yet more accurate model might be devised. Hence there remains some uncertainty that the best of any series examined is sufficiently accurate to be considered reliable as a basis for extrapolation. This paper proposes that models should be validated primarily by parametric graphical comparison to rupture data and rupture gradient data. It proposes that no mathematical model should be considered reliable for extrapolation unless the visible divergence between model and data is so small as to leave no apparent scope for further reduction. This study is based on the data for a 12% Cr alloy steel used in BS PD6605:1998 to exemplify its recommended statistical analysis procedure. The models considered in this paper include a) a relatively simple model, b) the PD6605 recommended model and c) a more accurate model of somewhat greater complexity. - Highlights: Black-Right-Pointing-Pointer The paper discusses the validation of creep rupture models derived from statistical analysis. Black-Right-Pointing-Pointer It demonstrates that models can be satisfactorily validated by a visual-graphic comparison of models to data. Black-Right-Pointing-Pointer The method proposed utilises test data both as conventional rupture stress and as rupture stress gradient. Black-Right-Pointing-Pointer The approach is shown to be more reliable than a well-established and widely used method (BS PD6605).
Computationally efficient statistical differential equation modeling using homogenization
Hooten, Mevin B.; Garlick, Martha J.; Powell, James A.
2013-01-01
Statistical models using partial differential equations (PDEs) to describe dynamically evolving natural systems are appearing in the scientific literature with some regularity in recent years. Often such studies seek to characterize the dynamics of temporal or spatio-temporal phenomena such as invasive species, consumer-resource interactions, community evolution, and resource selection. Specifically, in the spatial setting, data are often available at varying spatial and temporal scales. Additionally, the necessary numerical integration of a PDE may be computationally infeasible over the spatial support of interest. We present an approach to impose computationally advantageous changes of support in statistical implementations of PDE models and demonstrate its utility through simulation using a form of PDE known as “ecological diffusion.” We also apply a statistical ecological diffusion model to a data set involving the spread of mountain pine beetle (Dendroctonus ponderosae) in Idaho, USA.
Statistical Validation of Engineering and Scientific Models: Background
International Nuclear Information System (INIS)
A tutorial is presented discussing the basic issues associated with propagation of uncertainty analysis and statistical validation of engineering and scientific models. The propagation of uncertainty tutorial illustrates the use of the sensitivity method and the Monte Carlo method to evaluate the uncertainty in predictions for linear and nonlinear models. Four example applications are presented; a linear model, a model for the behavior of a damped spring-mass system, a transient thermal conduction model, and a nonlinear transient convective-diffusive model based on Burger's equation. Correlated and uncorrelated model input parameters are considered. The model validation tutorial builds on the material presented in the propagation of uncertainty tutoriaI and uses the damp spring-mass system as the example application. The validation tutorial illustrates several concepts associated with the application of statistical inference to test model predictions against experimental observations. Several validation methods are presented including error band based, multivariate, sum of squares of residuals, and optimization methods. After completion of the tutorial, a survey of statistical model validation literature is presented and recommendations for future work are made
Statistical models for nuclear decay. From evaporation to vaporization
International Nuclear Information System (INIS)
The purpose of this book is to present and discuss statistical models which are used to describe the decay of excited atomic nuclei. The subject dates from about 1937 when, building on the Bohr concept of the compound nucleus as a system in temporal equilibrium, Weisskopf first proposed a quantitatively successful statistical model to describe the 'evaporation' of neutrons from excited compound nuclei. The book is intended for use by senior undergraduates and post graduates as well as confirmed experimentalists seeking global perspective concerning the history and current status of this research domain. The book is divided into eight chapters. The first two chapters are concerned with introductions to the statistical mechanics and nuclear physics which are necessary for understanding the development of statistical models of nuclear decay. The second part of the book (chapters 3 and 4) describes the statistical models which were created to describe decay processes at low excitation energy. In chapter 3, the topics include Weisskopf theory for evaporation of neutrons, the Hauser-Feshbach evaporation theory, fusion, the Griffin, Blann-Cline and Harp-Miller-Berne approaches to pre-equilibrium particle emission, and finally, early statistical theories of low energy fission. Chapter 4, which begins with an introduction to Monte Carlo simulations, is mainly concerned with applications of the Hauser-Feshbach theory to single and multistep evaporation. The third part of the text is devoted to the description of decay processes which are 'modern' insofar as the experimental work has been mainly carried out over the last 20 years. These applications include the so-called sequential binary decay mechanism (chapter 5). Multifragmentation is discussed in chapters 6 and 7. Finally, in chapter 8 an attempt was made to draw the threads together in order to build a coherent picture of applications of statistical mechanics to nuclear decay. A few new areas of research are indicated
Statistical Validation of Normal Tissue Complication Probability Models
Energy Technology Data Exchange (ETDEWEB)
Xu Chengjian, E-mail: c.j.xu@umcg.nl [Department of Radiation Oncology, University of Groningen, University Medical Center Groningen, Groningen (Netherlands); Schaaf, Arjen van der; Veld, Aart A. van' t; Langendijk, Johannes A. [Department of Radiation Oncology, University of Groningen, University Medical Center Groningen, Groningen (Netherlands); Schilstra, Cornelis [Department of Radiation Oncology, University of Groningen, University Medical Center Groningen, Groningen (Netherlands); Radiotherapy Institute Friesland, Leeuwarden (Netherlands)
2012-09-01
Purpose: To investigate the applicability and value of double cross-validation and permutation tests as established statistical approaches in the validation of normal tissue complication probability (NTCP) models. Methods and Materials: A penalized regression method, LASSO (least absolute shrinkage and selection operator), was used to build NTCP models for xerostomia after radiation therapy treatment of head-and-neck cancer. Model assessment was based on the likelihood function and the area under the receiver operating characteristic curve. Results: Repeated double cross-validation showed the uncertainty and instability of the NTCP models and indicated that the statistical significance of model performance can be obtained by permutation testing. Conclusion: Repeated double cross-validation and permutation tests are recommended to validate NTCP models before clinical use.
Understanding and forecasting polar stratospheric variability with statistical models
Directory of Open Access Journals (Sweden)
C. Blume
2012-02-01
Full Text Available The variability of the north-polar stratospheric vortex is a prominent aspect of the middle atmosphere. This work investigates a wide class of statistical models with respect to their ability to model geopotential and temperature anomalies, representing variability in the polar stratosphere. Four partly nonstationary, nonlinear models are assessed: linear discriminant analysis (LDA; a cluster method based on finite elements (FEM-VARX; a neural network, namely a multi-layer perceptron (MLP; and support vector regression (SVR. These methods model time series by incorporating all significant external factors simultaneously, including ENSO, QBO, the solar cycle, volcanoes, etc., to then quantify their statistical importance. We show that variability in reanalysis data from 1980 to 2005 is successfully modeled. FEM-VARX and MLP even satisfactorily forecast the period from 2005 to 2011. However, internal variability remains that cannot be statistically forecasted, such as the unexpected major warming in January 2009. Finally, the statistical model with the best generalization performance is used to predict a vortex breakdown in late January, early February 2012.
A Statistical Model for Regional Tornado Climate Studies
Jagger, Thomas H.; James B. Elsner; Widen, Holly M.
2015-01-01
Tornado reports are locally rare, often clustered, and of variable quality making it difficult to use them directly to describe regional tornado climatology. Here a statistical model is demonstrated that overcomes some of these difficulties and produces a smoothed regional-scale climatology of tornado occurrences. The model is applied to data aggregated at the level of counties. These data include annual population, annual tornado counts and an index of terrain roughness. The model has a term...
The Statistical Modeling of the Trends Concerning the Romanian Population
Directory of Open Access Journals (Sweden)
Gabriela OPAIT
2014-11-01
Full Text Available This paper reflects the statistical modeling concerning the resident population in Romania, respectively the total of the romanian population, through by means of the „Least Squares Method”. Any country it develops by increasing of the population, respectively of the workforce, which is a factor of influence for the growth of the Gross Domestic Product (G.D.P.. The „Least Squares Method” represents a statistical technique for to determine the trend line of the best fit concerning a model.
Statistical Model of the 2001 Czech Census for Interactive Presentation
Czech Academy of Sciences Publication Activity Database
Grim, Jiří; Hora, Jan; Boček, Pavel; Somol, Petr; Pudil, Pavel
Vol. 26, č. 4 (2010), s. 1-23. ISSN 0282-423X R&D Projects: GA ČR GA102/07/1594; GA MŠk 1M0572 Grant ostatní: GA MŠk(CZ) 2C06019 Institutional research plan: CEZ:AV0Z10750506 Keywords : Interactive statistical model * census data presentation * distribution mixtures * data modeling * EM algorithm * incomplete data * data reproduction accuracy * data mining Subject RIV: BB - Applied Statistics, Operational Research Impact factor: 0.492, year: 2010 http://library.utia.cas.cz/separaty/2010/RO/grim-0350513.pdf
Channel network model for flow and radionuclide migration
International Nuclear Information System (INIS)
The Channel Network model has been developed for simulations of flow and solute transport in fractured rock. The model, and its computer implementation CHAN3D, has been used to simulate and analyse field experiments performed in Sweden. In the performance assessment of repositories for nuclear waste a tool was needed which could handle the release from the near field and simulate the radionuclide migration in the far field. In order to develop the tool the Channel Network model was integrated with a model which calculates the near filed release in detail. The integrated model concept which may be used for performance assessment of a nuclear repository is presented. A compartment model, NUCTRAN, is used to calculate the near field release from a damaged canister. Two main items were studied; the location of a damaged canister in relation to fracture zones, and the barrier function of the host rock. (R.P.)
A Statistical Study of Beam Centroid Oscillations in a Solenoid Transport Channel
Energy Technology Data Exchange (ETDEWEB)
Lund, S; Wootton, C; Coleman, J; Lidia, S; Seidl, P
2009-05-07
A recent theory of transverse centroid oscillations in solenoidally focused beam transport lattices presented in Ref. [1] is applied to statistically analyze properties of the centroid orbit in the Neutralized Drift Compression Experiment (NDCX) at the Lawrence Berkeley National Laboratory. Contributions to the amplitude of the centroid oscillations from mechanical misalignments and initial centroid errors exiting the injector are analyzed. Measured values of the centroid appear consistent with expected alignment tolerances. Correction of these errors is discussed.
MODELING OF VEHICULAR STEERING EFFICIENCY IN TRAFFIC DIRECTION MOTION CHANNEL
Directory of Open Access Journals (Sweden)
V. A. Ganai
2011-01-01
Full Text Available The paper formulates and solves an actual problem pertaining to vehicular steering efficiency in traffic direction motion channel. Models of operator-drivers with low, medium and high rates in motivational perception of road conditions and also a model for controlling a traffic direction motion have been taken into ccount in the paper. Modeling has been done by using MATLAB.
Directory of Open Access Journals (Sweden)
Szwast Maciej
2015-06-01
Full Text Available The paper presents the mathematical modelling of selected isothermal separation processes of gaseous mixtures, taking place in plants using membranes, in particular nonporous polymer membranes. The modelling concerns membrane modules consisting of two channels - the feeding and the permeate channels. Different shapes of the channels cross-section were taken into account. Consideration was given to co-current and counter-current flows, for feeding and permeate streams, respectively, flowing together with the inert gas receiving permeate. In the proposed mathematical model it was considered that pressure of gas changes along the length of flow channels was the result of both - the drop of pressure connected with flow resistance, and energy transfer by molecules of gas flowing in a given channel to molecules which penetrate this channel from the adjacent channel. The literature on membrane technology takes into account only the drop of pressure connected with flow resistance. Consideration given to energy transfer by molecules of gas flowing in a given channel to molecules which penetrate this channel from the adjacent channel constitute the essential novelty in the current study. The paper also presents results of calculations obtained by means of a computer program which used equations of the derived model. Physicochemical data concerning separation of the CO2/CH4 mixture with He as the sweep gas and data concerning properties of the membrane made of PDMS were assumed for calculations.
Analyzing sickness absence with statistical models for survival data
DEFF Research Database (Denmark)
Christensen, Karl Bang; Andersen, Per Kragh; Smith-Hansen, Lars; Nielsen, Martin L; Kristensen, Tage S
2007-01-01
absence data deal with events occurring over time, the use of statistical models for survival data has been reviewed, and the use of frailty models has been proposed for the analysis of such data. METHODS: Three methods for analyzing data on sickness absences were compared using a simulation study......OBJECTIVES: Sickness absence is the outcome in many epidemiologic studies and is often based on summary measures such as the number of sickness absences per year. In this study the use of modern statistical methods was examined by making better use of the available information. Since sickness...... involving the following: (i) Poisson regression using a single outcome variable (number of sickness absences), (ii) analysis of time to first event using the Cox proportional hazards model, and (iii) frailty models, which are random effects proportional hazards models. Data from a study of the relation...
Applied systems ecology: models, data, and statistical methods
Energy Technology Data Exchange (ETDEWEB)
Eberhardt, L L
1976-01-01
In this report, systems ecology is largely equated to mathematical or computer simulation modelling. The need for models in ecology stems from the necessity to have an integrative device for the diversity of ecological data, much of which is observational, rather than experimental, as well as from the present lack of a theoretical structure for ecology. Different objectives in applied studies require specialized methods. The best predictive devices may be regression equations, often non-linear in form, extracted from much more detailed models. A variety of statistical aspects of modelling, including sampling, are discussed. Several aspects of population dynamics and food-chain kinetics are described, and it is suggested that the two presently separated approaches should be combined into a single theoretical framework. It is concluded that future efforts in systems ecology should emphasize actual data and statistical methods, as well as modelling.
Statistical approaches to pharmacodynamic modeling: motivations, methods, and misperceptions.
Mick, R; Ratain, M J
1993-01-01
We have attempted to outline the fundamental statistical aspects of pharmacodynamic modeling. Unexpected yet substantial variability in effect in a group of similarly treated patients is the key motivation for pharmacodynamic investigations. Pharmacokinetic and/or pharmacodynamic factors may influence this variability. Residual variability in effect that persists after accounting for drug exposure indicates that further statistical modeling with pharmacodynamic factors is warranted. Factors that significantly predict interpatient variability in effect may then be employed to individualize the drug dose. In this paper we have emphasized the need to understand the properties of the effect measure and explanatory variables in terms of scale, distribution, and statistical relationship. The assumptions that underlie many types of statistical models have been discussed. The role of residual analysis has been stressed as a useful method to verify assumptions. We have described transformations and alternative regression methods that are employed when these assumptions are found to be in violation. Sequential selection procedures for the construction of multivariate models have been presented. The importance of assessing model performance has been underscored, most notably in terms of bias and precision. In summary, pharmacodynamic analyses are now commonly performed and reported in the oncologic literature. The content and format of these analyses has been variable. The goals of such analyses are to identify and describe pharmacodynamic relationships and, in many cases, to propose a statistical model. However, the appropriateness and performance of the proposed model are often difficult to judge. Table 1 displays suggestions (in a checklist format) for structuring the presentation of pharmacodynamic analyses, which reflect the topics reviewed in this paper. PMID:8269582
International Nuclear Information System (INIS)
Higgs mechanism, introduced in 1964, gives a satisfactory solution to a major problem of the standard model of elementary particles: the origin of the mass. It predicts the existence of the Higgs scalar boson, which mass is not defined by the theory and which has not been discovered experimentally yet (June 2012). The Tevatron, a hadron accelerator based at Fermi National Accelerator Laboratory near Chicago, took data with its two multi-purpose detectors CDF and DO since 1983 up to september 2011. Leaving about 10 fb-1 of statistics to analyze. Associated production of Higgs (H) and vector gauge boson (W) is the main search channel for a light standard Higgs boson. A light Higgs boson is expected to decay in a pair of beauty quarks. Using data collected by DO, we are looking for this production mode taking advantage of sophisticated techniques to improve the signal sensitivity like b-jet identification and multivariate discriminating factors. In the end, a statistical approach allows us to set an upper limit on the ratio between the observed (resp. expected) Higgs production and its theoretical cross section. The results obtained in the WH channel using 9.7 fb-1 at DO is 3.15 (resp. 3.96) for a 115 GeV/c2 Higgs boson. (author)
A Review of Modeling Bioelectrochemical Systems: Engineering and Statistical Aspects
Directory of Open Access Journals (Sweden)
Shuai Luo
2016-02-01
Full Text Available Bioelectrochemical systems (BES are promising technologies to convert organic compounds in wastewater to electrical energy through a series of complex physical-chemical, biological and electrochemical processes. Representative BES such as microbial fuel cells (MFCs have been studied and advanced for energy recovery. Substantial experimental and modeling efforts have been made for investigating the processes involved in electricity generation toward the improvement of the BES performance for practical applications. However, there are many parameters that will potentially affect these processes, thereby making the optimization of system performance hard to be achieved. Mathematical models, including engineering models and statistical models, are powerful tools to help understand the interactions among the parameters in BES and perform optimization of BES configuration/operation. This review paper aims to introduce and discuss the recent developments of BES modeling from engineering and statistical aspects, including analysis on the model structure, description of application cases and sensitivity analysis of various parameters. It is expected to serves as a compass for integrating the engineering and statistical modeling strategies to improve model accuracy for BES development.
Statistical modelling of tropical cyclone tracks: non-normal innovations
Hall, T; Hall, Tim; Jewson, Stephen
2005-01-01
We present results from the sixth stage of a project to build a statistical hurricane model. Previous papers have described our modelling of the tracks, genesis, and lysis of hurricanes. In our track model we have so far employed a normal distribution for the residuals when computing innovations, even though we have demonstrated that their distribution is not normal. Here, we test to see if the track model can be improved by including more realistic non-normal innovations. The results are mixed. Some features of the model improve, but others slightly worsen.
Cure Models as a Useful Statistical Tool for Analyzing Survival
Othus, Megan; Barlogie, Bart; LeBlanc, Michael L.; Crowley, John J.
2012-01-01
Cure models are a popular topic within statistical literature but are not as widely known in the clinical literature. Many patients with cancer can be long-term survivors of their disease, and cure models can be a useful tool to analyze and describe cancer survival data. The goal of this article is to review what a cure model is, explain when cure models can be used, and use cure models to describe multiple myeloma survival trends. Multiple myeloma is generally considered an incurable disease...
Single-channel speech enhancement method based on masking properties and minimum statistics
Institute of Scientific and Technical Information of China (English)
江小平; 姚天任; 傅华
2004-01-01
A single-channel speech enhancement method of noisy speech signals at very low signal-to-noise ratios is presented, which is based on masking properties of the human auditory system and power spectral density estimation of nonstationary noise. It allows for an automatic adaptation in time and frequency of the parametric enhancement system, and finds the best tradeoff among the amount of noise reduction, the speech distortion, and the levd of musicalresidual noise based on a criterion correlated with perception and SNR. This leads to a significant reduction of the unnatural structure of the residual noise. The results with several noise types show that the enhanced speech is more pleasant to a human listener.
International Nuclear Information System (INIS)
Inertial particle acceleration statistics are analyzed using DNS in the case of a turbulent channel flow. Along with effects recognized in homogeneous isotropic turbulence, an additional effect is observed due to high and low speed vortical structures aligned with the channel wall. In response to those structures, the inertial particles experience strong streamwise acceleration variations. DNS is also used in order to assess LES-SSAM (Subgrid Stochastic Acceleration Model), in which an approximation to the instantaneous non-filtered velocity field is given by simulation of both, filtered and residual, accelerations. Advantages of this approach in predicting particle dynamics in the channel flow at a high Reynolds number are shown.
Predicting lettuce canopy photosynthesis with statistical and neural network models
Frick, J.; Precetti, C.; Mitchell, C. A.
1998-01-01
An artificial neural network (NN) and a statistical regression model were developed to predict canopy photosynthetic rates (Pn) for 'Waldman's Green' leaf lettuce (Latuca sativa L.). All data used to develop and test the models were collected for crop stands grown hydroponically and under controlled-environment conditions. In the NN and regression models, canopy Pn was predicted as a function of three independent variables: shootzone CO2 concentration (600 to 1500 micromoles mol-1), photosynthetic photon flux (PPF) (600 to 1100 micromoles m-2 s-1), and canopy age (10 to 20 days after planting). The models were used to determine the combinations of CO2 and PPF setpoints required each day to maintain maximum canopy Pn. The statistical model (a third-order polynomial) predicted Pn more accurately than the simple NN (a three-layer, fully connected net). Over an 11-day validation period, average percent difference between predicted and actual Pn was 12.3% and 24.6% for the statistical and NN models, respectively. Both models lost considerable accuracy when used to determine relatively long-range Pn predictions (> or = 6 days into the future).
Statistical Properties of Downscaled CMIP3 Global Climate Model Simulations
Duffy, P.; Tyan, S.; Thrasher, B.; Maurer, E. P.; Tebaldi, C.
2009-12-01
Spatial downscaling of global climate model projections adds physically meaningful spatial detail, and brings the results down to a scale that is more relevant to human and ecological systems. Statistical/empirical downscaling methods are computationally inexpensive, and thus can be applied to large ensembles of global climate model projections. Here we examine some of the statistical properties of a large ensemble of empirically downscale global climate projections. The projections are the CMIP3 global climate model projections that were performed by modeling groups around the world and archived by the Program for Climate Model Diagnosis and Intercomparison at Lawrence Livermore National Laboratory. Downscaled versions of 112 of these simulations were created on 2007 and are archived at http://gdo-dcp.ucllnl.org/downscaled_cmip3_projections/dcpInterface.html. The downscaling methodology employed, “Bias Correction/Spatial Downscaling” (BCSD), includes a correction of GCM biases relative to observations during a historical reference period, as well as empirical downscaling to grid scale of ~12 km. We analyzed these downscaled projections and some of the original global model results to assess effects of the bias correction and downscaling on the statistical properties of the ensemble. We also assessed uncertainty in the climate response to increased greenhouse gases from initial conditions relative to the uncertainty introduced by choice of global climate model.
ABAREX: A neutron spherical optical-statistical model code
Energy Technology Data Exchange (ETDEWEB)
Lawson, R.D.
1992-06-01
The spherical optical-statistical model is briefly reviewed and the capabilities of the neutron scattering code, ABAREX, are presented. Input files for ten examples, in which neutrons are scattered by various nuclei, are given and the output of each run is discussed in detail.
ABAREX: A neutron spherical optical-statistical model code
International Nuclear Information System (INIS)
The spherical optical-statistical model is briefly reviewed and the capabilities of the neutron scattering code, ABAREX, are presented. Input files for ten examples, in which neutrons are scattered by various nuclei, are given and the output of each run is discussed in detail
Octet magnetic Moments and their sum rules in statistical model
Batra, M
2013-01-01
The statistical model is implemented to find the magnetic moments of all octet baryons. The well-known sum rules like GMO and CG sum rules has been checked in order to check the consistency of our approach. The small discrepancy between the results suggests the importance of breaking in SU(3) symmetry.
Statistical Modeling of Energy Production by Photovoltaic Farms
Czech Academy of Sciences Publication Activity Database
Brabec, Marek; Pelikán, Emil; Krč, Pavel; Eben, Kryštof; Musílek, P.
2011-01-01
Roč. 5, č. 9 (2011), s. 785-793. ISSN 1934-8975 Grant ostatní: GA AV ČR(CZ) M100300904 Institutional research plan: CEZ:AV0Z10300504 Keywords : electrical energy * solar energy * numerical weather prediction model * nonparametric regression * beta regression Subject RIV: BB - Applied Statistics, Operational Research
Confronting LHC data with the statistical hadronization model
International Nuclear Information System (INIS)
The most recent data from the CERN LHC are compared with calculations within the statistical hadronization model. The parameters temperature und baryon chemical potential are fitted to the data. The best fit yields a temperature of 156 MeV, slightly below the expectation from RHIC data. Proton yields are nearly three standard deviations below this fit and possible reasons are discussed
A Statistical Model for the Estimation of Natural Gas Consumption
Czech Academy of Sciences Publication Activity Database
Vondráček, Jiří; Pelikán, Emil; Konár, Ondřej; Čermáková, Jana; Eben, Kryštof; Malý, Marek; Brabec, Marek
2008-01-01
Roč. 85, c. 5 (2008), s. 362-370. ISSN 0306-2619 R&D Projects: GA AV ČR 1ET400300513 Institutional research plan: CEZ:AV0Z10300504 Keywords : nonlinear regression * gas consumption modeling Subject RIV: BB - Applied Statistics, Operational Research Impact factor: 1.371, year: 2008
Statistical properties of the nuclear shell-model Hamiltonian
International Nuclear Information System (INIS)
The statistical properties of realistic nuclear shell-model Hamiltonian are investigated in sd-shell nuclei. The probability distribution of the basic-vector amplitude is calculated and compared with the Porter-Thomas distribution. Relevance of the results to the calculation of the giant resonance mixing parameter is pointed out. (Author)
Hypersonic Vehicle Tracking Based on Improved Current Statistical Model
Directory of Open Access Journals (Sweden)
He Guangjun
2013-11-01
Full Text Available A new method of tracking the near space hypersonic vehicle is put forward. According to hypersonic vehicles’ characteristics, we improved current statistical model through online identification of the maneuvering frequency. A Monte Carlo simulation is used to analyze the performance of the method. The results show that the improved method exhibits very good tracking performance in comparison with the old method.
Hypersonic Vehicle Tracking Based on Improved Current Statistical Model
He Guangjun; Lv Hang; Li Baoquan; Li Yanbin
2013-01-01
A new method of tracking the near space hypersonic vehicle is put forward. According to hypersonic vehicles’ characteristics, we improved current statistical model through online identification of the maneuvering frequency. A Monte Carlo simulation is used to analyze the performance of the method. The results show that the improved method exhibits very good tracking performance in comparison with the old method.
Applying the luminosity function statistics in the fireshell model
Rangel Lemos, L. J.; Bianco, C. L.; Ruffini, R.
2015-12-01
The luminosity function (LF) statistics applied to the data of BATSE, GBM/Fermi and BAT/Swift is the theme approached in this work. The LF is a strong statistical tool to extract useful information from astrophysical samples, and the key point of this statistical analysis is in the detector sensitivity, where we have performed careful analysis. We applied the tool of the LF statistics to three GRB classes predicted by the Fireshell model. We produced, by LF statistics, predicted distributions of: peak ux N(Fph pk), redshift N(z) and peak luminosity N(Lpk) for the three GRB classes predicted by Fireshell model; we also used three GRB rates. We looked for differences among the distributions, and in fact we found. We performed a comparison between the distributions predicted and observed (with and without redshifts), where we had to build a list with 217 GRBs with known redshifts. Our goal is transform the GRBs in a standard candle, where a alternative is find a correlation between the isotropic luminosity and the Band peak spectral energy (Liso - Epk).
International Nuclear Information System (INIS)
Quantum cryptography in theory allows distributing secure keys between two users so that any performed eavesdropping attempt would be immediately discovered. However, in practice an eavesdropper can obtain key information from multi-photon states when attenuated laser radiation is used as a source. In order to overcome this possibility, it is generally suggested to implement special cryptographic protocols, like decoy states or SARG04. We present an alternative method based on monitoring photon number statistics after detection. This method can therefore be used with any existing protocol
Gaidash, A. A.; Egorov, V. I.; Gleim, A. V.
2014-10-01
Quantum cryptography in theory allows distributing secure keys between two users so that any performed eavesdropping attempt would be immediately discovered. However, in practice an eavesdropper can obtain key information from multi-photon states when attenuated laser radiation is used as a source. In order to overcome this possibility, it is generally suggested to implement special cryptographic protocols, like decoy states or SARG04. We present an alternative method based on monitoring photon number statistics after detection. This method can therefore be used with any existing protocol.
Statistical models describing the energy signature of buildings
DEFF Research Database (Denmark)
Bacher, Peder; Madsen, Henrik; Thavlov, Anders
2010-01-01
Approximately one third of the primary energy production in Denmark is used for heating in buildings. Therefore efforts to accurately describe and improve energy performance of the building mass are very important. For this purpose statistical models describing the energy signature of a building, i.......e. the heat dynamics of the building, have been developed. The models can be used to obtain rather detailed knowledge of the energy performance of the building and to optimize the control of the energy consumption for heating, which will be vital in conditions with increasing fluctuation of the energy...... supply or varying energy prices. The paper will give an overview of statistical methods and applied models based on experiments carried out in FlexHouse, which is an experimental building in SYSLAB, Risø DTU. The models are of different complexity and can provide estimates of physical quantities such as...
Statistical modelling of collocation uncertainty in atmospheric thermodynamic profiles
Directory of Open Access Journals (Sweden)
A. Fassò
2013-08-01
Full Text Available The uncertainty of important atmospheric parameters is a key factor for assessing the uncertainty of global change estimates given by numerical prediction models. One of the critical points of the uncertainty budget is related to the collocation mismatch in space and time among different observations. This is particularly important for vertical atmospheric profiles obtained by radiosondes or LIDAR. In this paper we consider a statistical modelling approach to understand at which extent collocation uncertainty is related to environmental factors, height and distance between the trajectories. To do this we introduce a new statistical approach, based on the heteroskedastic functional regression (HFR model which extends the standard functional regression approach and allows us a natural definition of uncertainty profiles. Moreover, using this modelling approach, a five-folded uncertainty decomposition is proposed. Eventually, the HFR approach is illustrated by the collocation uncertainty analysis of relative humidity from two stations involved in GCOS reference upper-air network (GRUAN.
Generalized statistical models of voids and hierarchical structure in cosmology
Mekjian, Aram Z
2007-01-01
Generalized statistical models of voids and hierarchical structure in cosmology are developed. The often quoted negative binomial model and frequently used thermodynamic model are shown to be special cases of a more general distribution which contains a parameter "a". The parameter is related to the Levy index alpha and the Fisher critical exponent tau, the latter describing the power law fall off of clumps of matter around a phase transition. The parameter"a", exponent tau, or index alpha can be obtained from properties of a void scaling function. A stochastic probability variable "p" is introduced into a statistical model which represent the adhesive growth of galaxy structure. For p1/2, an adhesive growth can go on indefinitely thereby forming an infinite supercluster. At p=1/2 a scale free power law distribution for the galaxy count distribution is present. The stochastic description also leads to consequences that have some parallels with cosmic string results, percolation theory and phase transitions.
Statistical mechanics models for motion and force planning
Rodriguez, G.
1990-01-01
The models of statistical mechanics provide an alternative to the methods of classical mechanics more traditionally used in robotics. They have a potential to: improve analysis of object collisions; handle kinematic and dynamic contact interactions within the same frmework; and reduce the need for perfect deterministic world model information. The statistical mechanics models characterize the state of the system as a probability density function (p.d.f.) whose time evolution is governed by a partial differential equation subject to boundary and initial conditions. The boundary conditions when rigid objects collide reflect the conservation of momentum. The models are being developed to embedd in remote semi-autonomous systems with a need to reason and interact with a multiobject environment.
Improved air ventilation rate estimation based on a statistical model
International Nuclear Information System (INIS)
A new approach to air ventilation rate estimation from CO measurement data is presented. The approach is based on a state-space dynamic statistical model, allowing for quick and efficient estimation. Underlying computations are based on Kalman filtering, whose practical software implementation is rather easy. The key property is the flexibility of the model, allowing various artificial regimens of CO level manipulation to be treated. The model is semi-parametric in nature and can efficiently handle time-varying ventilation rate. This is a major advantage, compared to some of the methods which are currently in practical use. After a formal introduction of the statistical model, its performance is demonstrated on real data from routine measurements. It is shown how the approach can be utilized in a more complex situation of major practical relevance, when time-varying air ventilation rate and radon entry rate are to be estimated simultaneously from concurrent radon and CO measurements
Calculation of statistical entropic measures in a model of solids
International Nuclear Information System (INIS)
In this work, a one-dimensional model of crystalline solids based on the Dirac comb limit of the Krönig–Penney model is considered. From the wave functions of the valence electrons, we calculate a statistical measure of complexity and the Fisher–Shannon information for the lower energy electronic bands appearing in the system. All these magnitudes present an extremal value for the case of solids having half-filled bands, a configuration where in general a high conductivity is attained in real solids, such as it happens with the monovalent metals. -- Highlights: ► A simplified model of solids is considered. Its electronic band structure is calculated. ► The statistical complexity and the Fisher–Shannon information are computed on this model. ► The extremal value for this indicators are taken on the configurations showing the highest conductivity.
Calculation of statistical entropic measures in a model of solids
Energy Technology Data Exchange (ETDEWEB)
Sañudo, Jaime, E-mail: jsr@unex.es [Departamento de Física, Facultad de Ciencias, Universidad de Extremadura, E-06071 Badajoz (Spain); BIFI, Universidad de Zaragoza, E-50009 Zaragoza (Spain); López-Ruiz, Ricardo, E-mail: rilopez@unizar.es [DIIS and BIFI, Facultad de Ciencias, Universidad de Zaragoza, E-50009 Zaragoza (Spain)
2012-07-09
In this work, a one-dimensional model of crystalline solids based on the Dirac comb limit of the Krönig–Penney model is considered. From the wave functions of the valence electrons, we calculate a statistical measure of complexity and the Fisher–Shannon information for the lower energy electronic bands appearing in the system. All these magnitudes present an extremal value for the case of solids having half-filled bands, a configuration where in general a high conductivity is attained in real solids, such as it happens with the monovalent metals. -- Highlights: ► A simplified model of solids is considered. Its electronic band structure is calculated. ► The statistical complexity and the Fisher–Shannon information are computed on this model. ► The extremal value for this indicators are taken on the configurations showing the highest conductivity.
Workshop on Model Uncertainty and its Statistical Implications
1988-01-01
In this book problems related to the choice of models in such diverse fields as regression, covariance structure, time series analysis and multinomial experiments are discussed. The emphasis is on the statistical implications for model assessment when the assessment is done with the same data that generated the model. This is a problem of long standing, notorious for its difficulty. Some contributors discuss this problem in an illuminating way. Others, and this is a truly novel feature, investigate systematically whether sample re-use methods like the bootstrap can be used to assess the quality of estimators or predictors in a reliable way given the initial model uncertainty. The book should prove to be valuable for advanced practitioners and statistical methodologists alike.
A channel transmission losses model for different dryland rivers
Directory of Open Access Journals (Sweden)
A. C. Costa
2012-04-01
Full Text Available Channel transmission losses in drylands take place normally in extensive alluvial channels or streambeds underlain by fractured rocks. They can play an important role in streamflow rates, groundwater recharge, freshwater supply and channel-associated ecosystems. We aim to develop a process-oriented, semi-distributed channel transmission losses model, using process formulations which are suitable for data-scarce dryland environments and applicable to both hydraulically disconnected losing streams and hydraulically connected losing(/gaining streams. This approach should be able to cover a large variation in climate and hydro-geologic controls, which are typically found in dryland regions of the Earth. Our model was first evaluated for a losing/gaining, hydraulically connected 30 km reach of the Middle Jaguaribe River (MJR, Ceará, Brazil, which drains a catchment area of 20 000 km^{2}. Secondly, we applied it to a small losing, hydraulically disconnected 1.5 km channel reach in the Walnut Gulch Experimental Watershed (WGEW, Arizona, USA. The model was able to predict reliably the streamflow volume and peak for both case studies without using any parameter calibration procedure. We have shown that the evaluation of the hypotheses on the dominant hydrological processes was fundamental for reducing structural model uncertainties and improving the streamflow prediction. For instance, in the case of the large river reach (MJR, it was shown that both lateral stream-aquifer water fluxes and groundwater flow in the underlying alluvium parallel to the river course are necessary to predict streamflow volume and channel transmission losses, the former process being more relevant than the latter. Regarding model uncertainty, it was shown that the approaches, which were applied for the unsaturated zone processes (highly nonlinear with elaborate numerical solutions, are much more sensitive to parameter variability than those approaches which were used
PARAMETRIC LINK MODELS FOR KNOWLEDGE TRANSFER IN STATISTICAL LEARNING
Beninel, Farid; Biernacki, Christophe; Bouveyron, Charles; Jacques, Julien; Lourme, Alexandre
2012-01-01
When a statistical model is designed in a prediction purpose, a major assumption is the absence of evolution in the modeled phenomenon between the training and the prediction stages. Thus, training and future data must be in the same feature space and must have the same distribution. Unfortunately, this assumption turns out to be often false in real-world applications. For instance, biological motivations could lead to classify individuals from a given species when only individuals from anoth...
Statistical and RBF NN models : providing forecasts and risk assessment
Marček, Milan
2009-01-01
Forecast accuracy of economic and financial processes is a popular measure for quantifying the risk in decision making. In this paper, we develop forecasting models based on statistical (stochastic) methods, sometimes called hard computing, and on a soft method using granular computing. We consider the accuracy of forecasting models as a measure for risk evaluation. It is found that the risk estimation process based on soft methods is simplified and less critical to the question w...
Model and Algorithm Selection in Statistical Learning and Optimization.
Bischl, Bernd
2014-01-01
Modern data-driven statistical techniques, e.g., non-linear classification and regression machine learning methods, play an increasingly important role in applied data analysis and quantitative research. For real-world we do not know a priori which methods will work best. Furthermore, most of the available models depend on so called hyper- or control parameters, which can drastically influence their performance. This leads to a vast space of potential models, which cannot be ...
Statistical modelling of collocation uncertainty in atmospheric thermodynamic profiles
A. Fassò; IGNACCOLO, R.; F. Madonna; B. B. Demoz
2013-01-01
The uncertainty of important atmospheric parameters is a key factor for assessing the uncertainty of global change estimates given by numerical prediction models. One of the critical points of the uncertainty budget is related to the collocation mismatch in space and time among different observations. This is particularly important for vertical atmospheric profiles obtained by radiosondes or LIDAR. In this paper we consider a statistical modelling approach to understand at which exte...
Statistical Equilibrium of trapped slender vortex filaments - a continuum model
Andersen, Timothy D.; Lim, Chjan C.
2006-01-01
Systems of nearly parallel, slender vortex filaments in which angular momentum is conserved are an important simplification of the Navier-Stokes equations where turbulence can be studied in statistical equilibrium. We study the canonical Gibbs distribution based on the Klein-Majda-Damodaran (KMD) model and find a divergence in the mean square vortex position from that of the point vortex model of Onsager at high temperature. We subsequently develop a free energy equation based on the non-inte...
Statistical Modeling of Energy Production by Photovoltaic Farms
Czech Academy of Sciences Publication Activity Database
Brabec, Marek; Pelikán, Emil; Krč, Pavel; Eben, Kryštof; Musílek, P.
Piscataway : IEEE, 2010, s. 1-6. ISBN 978-1-4244-8186-6. [EPEC 2010. Electrical Power and Energy Conference. Halifax (CA), 25.08.2010-27.08.2010] Institutional research plan: CEZ:AV0Z10300504 Keywords : electrical energy , solar energy * numerical weather prediction model * statistical model * nonparametric regression * inflated beta regression Subject RIV: JE - Non-nuclear Energetics, Energy Consumption ; Use
Statistical modelling of North Atlantic tropical cyclone tracks
Hall, Timothy M.; Jewson, Stephen
2007-01-01
We present a statistical model of North Atlantic tropical cyclone tracks from genesis site through lysis. To propagate tracks we use the means and variances of latitudinal and longitudinal displacements and model the remaining anomalies as autoregressive. Coefficients are determined by averaging near-neighbour historical track data, with ‘near’ determined optimally by using jackknife out-of-sample validation to maximize the likelihood of the observations. The number of cyclones in a simulated...
Modelling of the new FLNR magnetic analyzer vacuum channel
International Nuclear Information System (INIS)
The quality of any magnetic analyzer directly depends on the area of radial cross section of its volume filled with the ions trajectories. The conception of new magnetic spectrometer vacuum channel is based on computer modelling of the maximum filling of the spectrometer acceptance with given pole pieces width and the gap height of the magnetic dipole together with the maximum transmission of underflected in magnetic field emission from the target at the angle of measurements. The correct correlation of the aperture of the vacuum channel with durability, engineering and ease of handling characteristics combined with ion-optical properties of the spectrometer determines its construction in the whole
Modeling of Reverberant Radio Channels Using Propagation Graphs
DEFF Research Database (Denmark)
Pedersen, Troels; Steinböck, Gerhard; Fleury, Bernard Henri
2012-01-01
decaying power. We model the channel as a propagation graph in which vertices represent transmitters, receivers, and scatterers, while edges represent propagation conditions between vertices. The recursive structure of the graph accounts for the exponential power decay and the avalanche effect. We derive a......In measurements of in-room radio channel responses, an avalanche effect can be observed: earliest signal components, which appear well separated in delay, are followed by an avalanche of components arriving with increasing rate of occurrence, gradually merging into a diffuse tail with exponentially...... graph's recursive structure yields both an exponential power decay and an avalanche effect....
Statistical modelling of transcript profiles of differentially regulated genes
Directory of Open Access Journals (Sweden)
Sergeant Martin J
2008-07-01
Full Text Available Abstract Background The vast quantities of gene expression profiling data produced in microarray studies, and the more precise quantitative PCR, are often not statistically analysed to their full potential. Previous studies have summarised gene expression profiles using simple descriptive statistics, basic analysis of variance (ANOVA and the clustering of genes based on simple models fitted to their expression profiles over time. We report the novel application of statistical non-linear regression modelling techniques to describe the shapes of expression profiles for the fungus Agaricus bisporus, quantified by PCR, and for E. coli and Rattus norvegicus, using microarray technology. The use of parametric non-linear regression models provides a more precise description of expression profiles, reducing the "noise" of the raw data to produce a clear "signal" given by the fitted curve, and describing each profile with a small number of biologically interpretable parameters. This approach then allows the direct comparison and clustering of the shapes of response patterns between genes and potentially enables a greater exploration and interpretation of the biological processes driving gene expression. Results Quantitative reverse transcriptase PCR-derived time-course data of genes were modelled. "Split-line" or "broken-stick" regression identified the initial time of gene up-regulation, enabling the classification of genes into those with primary and secondary responses. Five-day profiles were modelled using the biologically-oriented, critical exponential curve, y(t = A + (B + CtRt + ε. This non-linear regression approach allowed the expression patterns for different genes to be compared in terms of curve shape, time of maximal transcript level and the decline and asymptotic response levels. Three distinct regulatory patterns were identified for the five genes studied. Applying the regression modelling approach to microarray-derived time course data
Measurement-Based LoS/NLoS Channel Modeling for Hot-Spot Urban Scenarios in UMTS Networks
Directory of Open Access Journals (Sweden)
Jiajing Chen
2014-01-01
Full Text Available A measurement campaign is introduced for modeling radio channels with either line-of-sight (LoS or non-line-of-sight (NLoS connection between user equipment (UE and NodeB (NB in an operating universal mobile telecommunications system. A space-alternating generalized expectation-maximization (SAGE algorithm is applied to estimate the delays and the complex attenuations of multipath components from the obtained channel impulse responses. Based on a novel LoS detection method of multipath parameter estimates, channels are classified into LoS and NLoS categories. Deterministic models which are named “channel maps” and fading statistical models have been constructed for LoS and NLoS, respectively. In addition, statistics of new parameters, such as the distance between the NB and the UE in LoS/NLoS scenarios, the life-distance of LoS channel, the LoS existence probability per location and per NB, the power variation at LoS to NLoS transition and vice versa, and the transition duration, are extracted. These models are applicable for designing and performance evaluation of transmission techniques or systems used by distinguishing the LoS and NLoS channels.
Predictive data modeling of human type II diabetes related statistics
Jaenisch, Kristina L.; Jaenisch, Holger M.; Handley, James W.; Albritton, Nathaniel G.
2009-04-01
During the course of routine Type II treatment of one of the authors, it was decided to derive predictive analytical Data Models of the daily sampled vital statistics: namely weight, blood pressure, and blood sugar, to determine if the covariance among the observed variables could yield a descriptive equation based model, or better still, a predictive analytical model that could forecast the expected future trend of the variables and possibly eliminate the number of finger stickings required to montior blood sugar levels. The personal history and analysis with resulting models are presented.
STATISTICAL MODELS FOR SEMI-RIGID NEMATIC POLYMERS
Institute of Scientific and Technical Information of China (English)
WANG Xinjiu
1995-01-01
Semi-rigid liquid crystal polymer is a class of liquid crystal polymers different from long rigid rod liquid crystal polymer to which the well-known Onsager and Flory theories are applied. In this paper, three statistical models for the semi-rigid nematic polymer were addressed. They are the elastically jointed rod model, worm-like chain model, and non-homogeneous chain model.The nematic-isotropic transition temperature was examined. The pseudo-second transition temperature is expressed analytically. Comparisons with the experiments were made and the agreements were found.
Statistical pronunciation modeling for non-native speech processing
Gruhn, Rainer E; Nakamura, Satoshi
2011-01-01
In this work, the authors present a fully statistical approach to model non--native speakers' pronunciation. Second-language speakers pronounce words in multiple different ways compared to the native speakers. Those deviations, may it be phoneme substitutions, deletions or insertions, can be modelled automatically with the new method presented here. The methods is based on a discrete hidden Markov model as a word pronunciation model, initialized on a standard pronunciation dictionary. The implementation and functionality of the methodology has been proven and verified with a test set of non-na
Stochastic geometry, spatial statistics and random fields models and algorithms
2015-01-01
Providing a graduate level introduction to various aspects of stochastic geometry, spatial statistics and random fields, this volume places a special emphasis on fundamental classes of models and algorithms as well as on their applications, for example in materials science, biology and genetics. This book has a strong focus on simulations and includes extensive codes in Matlab and R, which are widely used in the mathematical community. It can be regarded as a continuation of the recent volume 2068 of Lecture Notes in Mathematics, where other issues of stochastic geometry, spatial statistics and random fields were considered, with a focus on asymptotic methods.
Computer modelling of statistical properties of SASE FEL radiation
Saldin, E. L.; Schneidmiller, E. A.; Yurkov, M. V.
1997-06-01
The paper describes an approach to computer modelling of statistical properties of the radiation from self amplified spontaneous emission free electron laser (SASE FEL). The present approach allows one to calculate the following statistical properties of the SASE FEL radiation: time and spectral field correlation functions, distribution of the fluctuations of the instantaneous radiation power, distribution of the energy in the electron bunch, distribution of the radiation energy after monochromator installed at the FEL amplifier exit and the radiation spectrum. All numerical results presented in the paper have been calculated for the 70 nm SASE FEL at the TESLA Test Facility being under construction at DESY.
Occupation time statistics in the quenched trap model.
Burov, S; Barkai, E
2007-06-22
We investigate the distribution of the occupation time of a particle undergoing a random walk among random energy traps and in the presence of a deterministic potential field. When the distribution of energy traps is exponential with a width T(g), we find in thermal equilibrium a transition between Boltzmann statistics when T>T(g) to Lamperti statistics when T < T(g). We explain why our main results are valid for other models of quenched disorder, and discuss briefly implications on single particle experiments. PMID:17678005
Minimal sufficient statistics in location-scale parameter models
Mattner, Lutz
2000-01-01
Let f be a probability density on the real line, let n be any positive integer, and assume the condition (R) that logf is locally integrable with respect to Lebesgue measure. Then either logf is almost everywhere equal to a polynomial of degree less than n, or the order statistic of n independent and identically distributed observations from the location-scale parameter model generated by f is minimal sufficient. It follows, subject to (R) and n≥3, that a complete sufficient statistic exists ...
Thomas-Fermi Statistical Models of Finite Quark Matter
Wilcox, Walter
2008-01-01
I introduce and discuss models of finite quark matter using the formalism of the Thomas-Fermi statistical model. Similar to bag models, a vacuum energy term is introduced to model long distance confinement, but the model produces bound states from the residual color Coulomb attraction even in the absence of such a term. I discuss three baryonic applications: an equal mass nonrelativistic model with and without volume pressure, the ultra-relativistic limit confined by volume pressure, and a color-flavor locking massless model. These model may be extended to multi-meson and other mixed hadronic states. Hopefully, it can help lead to a better understanding of the phenomenology of high multi-quark states in preparation for more detailed lattice QCD calculations.
Statistical skull models from 3D X-ray images
Berar, M; Bailly, G; Payan, Y; Berar, Maxime; Desvignes, Michel; Payan, Yohan
2006-01-01
We present 2 statistical models of the skull and mandible built upon an elastic registration method of 3D meshes. The aim of this work is to relate degrees of freedom of skull anatomy, as static relations are of main interest for anthropology and legal medicine. Statistical models can effectively provide reconstructions together with statistical precision. In our applications, patient-specific meshes of the skull and the mandible are high-density meshes, extracted from 3D CT scans. All our patient-specific meshes are registrated in a subject-shared reference system using our 3D-to-3D elastic matching algorithm. Registration is based upon the minimization of a distance between the high density mesh and a shared low density mesh, defined on the vertexes, in a multi resolution approach. A Principal Component analysis is performed on the normalised registrated data to build a statistical linear model of the skull and mandible shape variation. The accuracy of the reconstruction is under the millimetre in the shape...
A Unified Channel Charges Expression for Analytic MOSFET Modeling
Hugues Murray; Patrick Martin
2012-01-01
Based on a 1D Poissons equation resolution, we present an analytic model of inversion charges allowing calculation of the drain current and transconductance in the Metal Oxide Semiconductor Field Effect Transistor. The drain current and transconductance are described by analytical functions including mobility corrections and short channel effects (CLM, DIBL). The comparison with the Pao-Sah integral shows excellent accuracy of the model in all inversion modes from strong to weak inversion in ...
International Nuclear Information System (INIS)
The complexity of mathematical models used by practicing engineers is increasing due to the growing availability of sophisticated mathematical modeling tools and ever-improving computational power. For this reason, the need to define a well-structured process for validating these models against experimental results has become a pressing issue in the engineering community. This validation process is partially characterized by the uncertainties associated with the modeling effort as well as the experimental results. The net impact of the uncertainties on the validation effort is assessed through the 'noise level of the validation procedure', which can be defined as an estimate of the 95% confidence uncertainty bounds for the comparison error between actual experimental results and model-based predictions of the same quantities of interest. Although general descriptions associated with the construction of the noise level using multivariate statistics exists in the literature, a detailed procedure outlining how to account for the systematic and random uncertainties is not available. In this paper, the methodology used to derive the covariance matrix associated with the multivariate normal pdf based on random and systematic uncertainties is examined, and a procedure used to estimate this covariance matrix using Monte Carlo analysis is presented. The covariance matrices are then used to construct approximate 95% confidence constant probability contours associated with comparison error results for a practical example. In addition, the example is used to show the drawbacks of using a first-order sensitivity analysis when nonlinear local sensitivity coefficients exist. Finally, the example is used to show the connection between the noise level of the validation exercise calculated using multivariate and univariate statistics.
Sakano, Rui; Oguri, Akira; Nisikawa, Yunori
We study non-equilibrium currents, current fluctuations and cross-correlations of the currents through Kondo-correlated quantum dots at low applied bias-voltages, using full counting statistics. To elucidate impact of dot-site interaction to these current properties in crossover between noninteracting and some Kondo states, renormalized perturbation theory or local Fermi liquid theory are employed. The exact form of the cumulant generating function up to third order of bias-voltage is derived in term of renormalized parameters. Specifically, crossover behavior of the Fano factor (ratio between noise and current) and current crosscorrelations for two-fold orbital case is discussed with using computed renormalized parameters by numerical renormalization group.
Spherical galaxy models as equilibrium configurations in nonextensive statistics
Cardone, V F; Del Popolo, A
2011-01-01
Considering galaxies as self - gravitating systems of many collisionless particles allows to use methods of statistical mechanics inferring the distribution function of these stellar systems. Actually, the long range nature of the gravitational force contrasts with the underlying assumptions of Boltzmann statistics where the interactions among particles are assumed to be short ranged. A particular generalization of the classical Boltzmann formalism is available within the nonextensive context of Tsallis q -statistics, subject to non -additivity of the entropies of sub - systems. Assuming stationarity and isotropy in the velocity space, it is possible solving the generalized collsionless Boltzmann equation to derive the galaxy distribution function and density profile. We present a particular set of nonextensive models and investigate their dynamical and observable properties. As a test of the viability of this generalized context, we fit the rotation curve of M33 showing that the proposed approach leads to da...
A Check-up for the Statistical Parton Model
Buccella, Franco
2014-01-01
We compare the parton distributions deduced in the framework of a quantum statistical approach for both the longitudinal and transverse degrees of freedom with the unpolarized distributions measured at Hera and with the polarized ones proposed in a previous paper, which have been shown to be in very good agreement also with the results of experiments performed after that proposal. The agreement with Hera data in correspondence of very similar values for the 'temperature' and the 'potentials' found in the previous work gives a robust confirm of the statistical model. The feature of describing both unpolarized and polarized parton distributions in terms of few parameters fixed by data with large statistics and small systematic errors makes very attractive the parametrization proposed here.
Distributed-Channel Bipolar Device: Experimentation, Analytical Modeling and Applications.
Jiang, Fenglai
Experimental results and theoretical modeling for four terminal distributed channel bipolar devices (DCBD) are presented. The DCBD device is comprised of an interwoven BJT and MOSFET. The device may be characterized as a MOSFET with a bipolar transistor source distributed under the MOSFET channel. Alternatively, the device may be represented as a BJT where a MOSFET channel provides the current collection function. The physical layout of the device is that of a n-channel MOSFET placed above a p-Si epitaxial base region which was grown on an n^+-Si substrate emitter. Distributed electronic behavior exhibits itself through self-biasing influences of the channel-collected current on the channel-base junction bias. For appropriate biasing, the MOSFET channel divides itself into two regions exhibiting forward active and saturation BJT behavior. Both experimental results and theoretical modeling are provided. Experimental results for "large area" rectangular gate, circular gate and trapezoidal gate DCBD are reported. The experimental results exhibit the transconductance threshold voltage, beta fall off and transconductance fall-off features reported previously by others. A "large area" trapezoidal gate structure is incorporated to illustrate the gate area influences on the electrical characteristics and to provide a model sensitive structure for evaluating the validity of the theory developed in the dissertation. An analytical model based on conventional MOSFET and bipolar theories is developed. The analytical model is applied to the large gate area devices (example: 0.127 mm rectangular gate length) and smaller dimensional gate devices down to 0.9 micron rectangular gate length. The theoretical results show good agreement with the large gate area experimental results. Application examples are provided. The use of the base current invariant transconductance threshold voltage as a reference voltage is discussed. Comparison of the transconductance threshold voltage
Statistical traffic modeling of MPEG frame size: Experiments and Analysis
Directory of Open Access Journals (Sweden)
Haniph A. Latchman
2009-12-01
Full Text Available For guaranteed quality of service (QoS and sufficient bandwidth in a communication network which provides an integrated multimedia service, it is important to obtain an analytical and tractable model of the compressed MPEG data. This paper presents a statistical approach to a group of picture (GOP MPEG frame size model to increase network traffic performance in a communication network. We extract MPEG frame data from commercial DVD movies and make probability histograms to analyze the statistical characteristics of MPEG frame data. Six candidates of probability distributions are considered here and their parameters are obtained from the empirical data using the maximum likelihood estimation (MLE. This paper shows that the lognormal distribution is the best fitting model of MPEG-2 total frame data.
Experimental, statistical, and biological models of radon carcinogenesis
International Nuclear Information System (INIS)
Risk models developed for underground miners have not been consistently validated in studies of populations exposed to indoor radon. Imprecision in risk estimates results principally from differences between exposures in mines as compared to domestic environments and from uncertainties about the interaction between cigarette-smoking and exposure to radon decay products. Uncertainties in extrapolating miner data to domestic exposures can be reduced by means of a broad-based health effects research program that addresses the interrelated issues of exposure, respiratory tract dose, carcinogenesis (molecular/cellular and animal studies, plus developing biological and statistical models), and the relationship of radon to smoking and other copollutant exposures. This article reviews experimental animal data on radon carcinogenesis observed primarily in rats at Pacific Northwest Laboratory. Recent experimental and mechanistic carcinogenesis models of exposures to radon, uranium ore dust, and cigarette smoke are presented with statistical analyses of animal data. 20 refs., 1 fig
Experimental, statistical and biological models of radon carcinogenesis
International Nuclear Information System (INIS)
Risk models developed for underground miners have not been consistently validated in studies of populations exposed to indoor radon. Imprecision in risk estimates results principally from differences between exposures in mines as compared with domestic environments and from uncertainties about the interaction between cigarette smoking and exposure to radon decay products. Uncertainties in extrapolating miner data to domestic exposures can be reduced by means of a broad-based health effects research programme that addresses the interrelated issues of exposure, respiratory tract dose, carcinogenesis (molecular/cellular and animal studies, plus developing biological and statistical models) and the relationship of radon to smoking and other co-pollutant exposures. This article reviews experimental animal data on radon carcinogenesis observed primarily in rats at Pacific Northwest Laboratory. Recent experimental and mechanistic carcinogenesis models of exposures to radon, uranium ore dust, and cigarette smoke are presented with statistical analyses of animal data. (author)
Statistical 3D damage accumulation model for ion implant simulators
Hernandez-Mangas, J M; Enriquez, L E; Bailon, L; Barbolla, J; Jaraiz, M
2003-01-01
A statistical 3D damage accumulation model, based on the modified Kinchin-Pease formula, for ion implant simulation has been included in our physically based ion implantation code. It has only one fitting parameter for electronic stopping and uses 3D electron density distributions for different types of targets including compound semiconductors. Also, a statistical noise reduction mechanism based on the dose division is used. The model has been adapted to be run under parallel execution in order to speed up the calculation in 3D structures. Sequential ion implantation has been modelled including previous damage profiles. It can also simulate the implantation of molecular and cluster projectiles. Comparisons of simulated doping profiles with experimental SIMS profiles are presented. Also comparisons between simulated amorphization and experimental RBS profiles are shown. An analysis of sequential versus parallel processing is provided.
Statistical model selection with “Big Data”
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Jurgen A. Doornik
2015-12-01
Full Text Available Big Data offer potential benefits for statistical modelling, but confront problems including an excess of false positives, mistaking correlations for causes, ignoring sampling biases and selecting by inappropriate methods. We consider the many important requirements when searching for a data-based relationship using Big Data, and the possible role of Autometrics in that context. Paramount considerations include embedding relationships in general initial models, possibly restricting the number of variables to be selected over by non-statistical criteria (the formulation problem, using good quality data on all variables, analyzed with tight significance levels by a powerful selection procedure, retaining available theory insights (the selection problem while testing for relationships being well specified and invariant to shifts in explanatory variables (the evaluation problem, using a viable approach that resolves the computational problem of immense numbers of possible models.
Spatial-temporal rainfall fields: modelling and statistical aspects
Directory of Open Access Journals (Sweden)
H. S. Wheater
2000-01-01
Full Text Available The HYREX experiment has provided a data set unique in the UK, with a dense network of raingauges available for studying the rainfall at a fine local scale and a network of radar stations allowing detailed examination of the spatial and temporal structure of rainfall at larger scales. In this paper, the properties and characteristics of the rainfall process, as measured by the HYREX recording network of rainguages and radars, are studied from a statistical perspective. The results of these analyses are used to develop various models of the rainfall process, for use in hydrological applications. Some typical results of these various modelling exercises are presented. Keywords: Rainfall statistics, rainfall models, hydrological design
SoS contract verification using statistical model checking
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Alessandro Mignogna
2013-11-01
Full Text Available Exhaustive formal verification for systems of systems (SoS is impractical and cannot be applied on a large scale. In this paper we propose to use statistical model checking for efficient verification of SoS. We address three relevant aspects for systems of systems: 1 the model of the SoS, which includes stochastic aspects; 2 the formalization of the SoS requirements in the form of contracts; 3 the tool-chain to support statistical model checking for SoS. We adapt the SMC technique for application to heterogeneous SoS. We extend the UPDM/SysML specification language to express the SoS requirements that the implemented strategies over the SoS must satisfy. The requirements are specified with a new contract language specifically designed for SoS, targeting a high-level English- pattern language, but relying on an accurate semantics given by the standard temporal logics. The contracts are verified against the UPDM/SysML specification using the Statistical Model Checker (SMC PLASMA combined with the simulation engine DESYRE, which integrates heterogeneous behavioral models through the functional mock-up interface (FMI standard. The tool-chain allows computing an estimation of the satisfiability of the contracts by the SoS. The results help the system architect to trade-off different solutions to guide the evolution of the SoS.
Organism-level models: When mechanisms and statistics fail us
International Nuclear Information System (INIS)
Purpose: To describe the unique characteristics of models that represent the entire course of radiation therapy at the organism level and to highlight the uses to which such models can be put. Methods: At the level of an organism, traditional model-building runs into severe difficulties. We do not have sufficient knowledge to devise a complete biochemistry-based model. Statistical model-building fails due to the vast number of variables and the inability to control many of them in any meaningful way. Finally, building surrogate models, such as animal-based models, can result in excluding some of the most critical variables. Bayesian probabilistic models (Bayesian networks) provide a useful alternative that have the advantages of being mathematically rigorous, incorporating the knowledge that we do have, and being practical. Results: Bayesian networks representing radiation therapy pathways for prostate cancer and head and neck cancer were used to highlight the important aspects of such models and some techniques of model-building. A more specific model representing the treatment of occult lymph nodes in head and neck cancer were provided as an example of how such a model can inform clinical decisions. A model of the possible role of PET imaging in brain cancer was used to illustrate the means by which clinical trials can be modelled in order to come up with a trial design that will have meaningful outcomes. Conclusions: Probabilistic models are currently the most useful approach to representing the entire therapy outcome process.
Mathematical model of two-phase flow in accelerator channel
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О.Ф. Нікулін
2010-01-01
Full Text Available The problem of two-phase flow composed of energy-carrier phase (Newtonian liquid and solid fine-dispersed phase (particles in counter jet mill accelerator channel is considered. The mathematical model bases goes on the supposition that the phases interact with each other like independent substances by means of aerodynamics’ forces in conditions of adiabatic flow. The mathematical model in the form of system of differential equations of order 11 is represented. Derivations of equations by base physical principles for cross-section-averaged quantity are produced. The mathematical model can be used for estimation of any kinematic and thermodynamic flow characteristics for purposely parameters optimization problem solving and transfer functions determination, that take place in counter jet mill accelerator channel design.
Spatio-temporal statistical models with applications to atmospheric processes
International Nuclear Information System (INIS)
This doctoral dissertation is presented as three self-contained papers. An introductory chapter considers traditional spatio-temporal statistical methods used in the atmospheric sciences from a statistical perspective. Although this section is primarily a review, many of the statistical issues considered have not been considered in the context of these methods and several open questions are posed. The first paper attempts to determine a means of characterizing the semiannual oscillation (SAO) spatial variation in the northern hemisphere extratropical height field. It was discovered that the midlatitude SAO in 500hPa geopotential height could be explained almost entirely as a result of spatial and temporal asymmetries in the annual variation of stationary eddies. It was concluded that the mechanism for the SAO in the northern hemisphere is a result of land-sea contrasts. The second paper examines the seasonal variability of mixed Rossby-gravity waves (MRGW) in lower stratospheric over the equatorial Pacific. Advanced cyclostationary time series techniques were used for analysis. It was found that there are significant twice-yearly peaks in MRGW activity. Analyses also suggested a convergence of horizontal momentum flux associated with these waves. In the third paper, a new spatio-temporal statistical model is proposed that attempts to consider the influence of both temporal and spatial variability. This method is mainly concerned with prediction in space and time, and provides a spatially descriptive and temporally dynamic model
An Adaptive Channel Model for VBLAST in Vehicular Networks
Directory of Open Access Journals (Sweden)
Ghassan M. T. Abdalla
2009-01-01
Full Text Available The wireless transmission environment in vehicular ad hoc systems varies from line of sight with few surroundings to rich Rayleigh fading. An efficient communication system must adapt itself to these diverse conditions. Multiple antenna systems are known to provide superior performance compared to single antenna systems in terms of capacity and reliability. The correlation between the antennas has a great effect on the performance of MIMO systems. In this paper we introduce a novel adaptive channel model for MIMO-VBLAST systems in vehicular ad hoc networks. Using the proposed model, the correlation between the antennas was investigated. Although the line of sight is ideal for single antenna systems, it severely degrades the performance of VBLAST systems since it increases the correlation between the antennas. A channel update algorithm using single tap Kalman filters for VBLAST in flat fading channels has also been derived and evaluated. At 12 dB Es/N0, the new algorithm showed 50% reduction in the mean square error (MSE between the actual channel and the corresponding updated estimate compared to the MSE without update. The computational requirement of the proposed algorithm for a p×q VBLAST is 6p×q real multiplications and 4p×q real additions.
Contribution towards statistical intercomparison of general circulation models
Energy Technology Data Exchange (ETDEWEB)
Sengupta, S.; Boyle, J.
1995-06-01
The Atmospheric Model Intercomparison Project (AMIP) of the World Climate Research Programme`s Working Group on Numerical Experimentation (WGNE) is an ambitious attempt to comprehensively intercompare atmospheric General Circulation Models (GCMs). The participants in AMIP simulate the global atmosphere for the decade 1979 to 1988 using, a common solar constant and Carbon Dioxide(CO{sub 2}) concentration and a common monthly averaged sea surface temperature (SST) and sea ice data set. In this work we attempt to present a statistical framework to address the difficult task of model intercomparison and verification.
Wen, Gezheng; Markey, Mia K.
2015-03-01
It is resource-intensive to conduct human studies for task-based assessment of medical image quality and system optimization. Thus, numerical model observers have been developed as a surrogate for human observers. The Hotelling observer (HO) is the optimal linear observer for signal-detection tasks, but the high dimensionality of imaging data results in a heavy computational burden. Channelization is often used to approximate the HO through a dimensionality reduction step, but how to produce channelized images without losing significant image information remains a key challenge. Kernel local Fisher discriminant analysis (KLFDA) uses kernel techniques to perform supervised dimensionality reduction, which finds an embedding transformation that maximizes betweenclass separability and preserves within-class local structure in the low-dimensional manifold. It is powerful for classification tasks, especially when the distribution of a class is multimodal. Such multimodality could be observed in many practical clinical tasks. For example, primary and metastatic lesions may both appear in medical imaging studies, but the distributions of their typical characteristics (e.g., size) may be very different. In this study, we propose to use KLFDA as a novel channelization method. The dimension of the embedded manifold (i.e., the result of KLFDA) is a counterpart to the number of channels in the state-of-art linear channelization. We present a simulation study to demonstrate the potential usefulness of KLFDA for building the channelized HOs (CHOs) and generating reliable decision statistics for clinical tasks. We show that the performance of the CHO with KLFDA channels is comparable to that of the benchmark CHOs.
International Nuclear Information System (INIS)
The investigation of statistical and direct aspects related to the (γ,n) and (γ,np) decay channels of 64Zn in the giant dipole resonance (GDR) and quasideuteron (QD) energy regions was performed by a trial function fitting to the respective (e,n) and (e,np) electrodisintegration yields measured by residual activity. The trial function incorporated the GDR and QD models to describe the initial photoabsorption mechanism and the geometry dependent hybrid exciton model used in the ALICE/LIVERMORE-82 code to calculate the relevant branching ratios, with the E1 virtual photon spectra being calculated in the distorted wave Born approximation. We compared our results for the (γ,n) cross section with other existing experimental measurements, and the long-standing normalization issue among different laboratories was revisited and addressed. We obtained for the first time the absolute (γ,np) cross section from threshold to 60 MeV. We succeeded in separating statistical and direct contributions of the (γ,np) process, the latter being remarkably well described by the QD model in the interval 40-60 MeV. A possible direct contribution for the (γ,n) decay in the GDR is also addressed. Finally, the total photoabsorption cross section of 64Zn was reevaluated up to 21 MeV, and the results were compared with previous estimates performed by other groups
Bayesian statistic methods and theri application in probabilistic simulation models
Directory of Open Access Journals (Sweden)
Sergio Iannazzo
2007-03-01
Full Text Available Bayesian statistic methods are facing a rapidly growing level of interest and acceptance in the field of health economics. The reasons of this success are probably to be found on the theoretical fundaments of the discipline that make these techniques more appealing to decision analysis. To this point should be added the modern IT progress that has developed different flexible and powerful statistical software framework. Among them probably one of the most noticeably is the BUGS language project and its standalone application for MS Windows WinBUGS. Scope of this paper is to introduce the subject and to show some interesting applications of WinBUGS in developing complex economical models based on Markov chains. The advantages of this approach reside on the elegance of the code produced and in its capability to easily develop probabilistic simulations. Moreover an example of the integration of bayesian inference models in a Markov model is shown. This last feature let the analyst conduce statistical analyses on the available sources of evidence and exploit them directly as inputs in the economic model.
RANDOM SYSTEMS OF HARD PARTICLES:MODELS AND STATISTICS
Institute of Scientific and Technical Information of China (English)
Dietrich Stoyan
2002-01-01
This paper surveys models and statistical properties of random systems of hard particles. Such systems appear frequently in materials science, biology and elsewhere. In mathematical - statistical investigations, simulations of such structures play an important role. In these simulations various methods and models are applied, namely the RSA model, sedimentation and collective rearrangement algorithms, molecular dynamics, and Monte Carlo methods such as the Metropolis - Hastings algorithm. The statistical description of real and simulated particle systems uses ideas of the mathematical theories of random sets and point processes. This leads to characteristics such as volume fraction or porosity, covariance,contact distribution functions, specific connectivity number from the random set approach and intensity, pair correlation function and mark correlation functions from the point process approach. Some of them can be determined stereologically using planar sections, while others can only be obtained using three - dimensional data and 3D image analysis. They are valuable tools for fitting models to empirical data and, consequently, for understanding various materials, biological structures, porous media and other practically important spatial structures.
A Statistical Model for Uplink Intercell Interference with Power Adaptation and Greedy Scheduling
Tabassum, Hina
2012-10-03
This paper deals with the statistical modeling of uplink inter-cell interference (ICI) considering greedy scheduling with power adaptation based on channel conditions. The derived model is implicitly generalized for any kind of shadowing and fading environments. More precisely, we develop a generic model for the distribution of ICI based on the locations of the allocated users and their transmit powers. The derived model is utilized to evaluate important network performance metrics such as ergodic capacity, average fairness and average power preservation numerically. Monte-Carlo simulation details are included to support the analysis and show the accuracy of the derived expressions. In parallel to the literature, we show that greedy scheduling with power adaptation reduces the ICI, average power consumption of users, and enhances the average fairness among users, compared to the case without power adaptation. © 2012 IEEE.
Statistical modelling of a new global potential vegetation distribution
Levavasseur, G.; Vrac, M.; Roche, D. M.; Paillard, D.
2012-12-01
The potential natural vegetation (PNV) distribution is required for several studies in environmental sciences. Most of the available databases are quite subjective or depend on vegetation models. We have built a new high-resolution world-wide PNV map using a objective statistical methodology based on multinomial logistic models. Our method appears as a fast and robust alternative in vegetation modelling, independent of any vegetation model. In comparison with other databases, our method provides a realistic PNV distribution in agreement with respect to BIOME 6000 data. Among several advantages, the use of probabilities allows us to estimate the uncertainty, bringing some confidence in the modelled PNV, or to highlight the regions needing some data to improve the PNV modelling. Despite our PNV map being highly dependent on the distribution of data points, it is easily updatable as soon as additional data are available and provides very useful additional information for further applications.
A statistical model of hydrogen bond networks in liquid alcohols
Sillrén, Per; Bielecki, Johan; Mattsson, Johan; Börjesson, Lars; Matic, Aleksandar
2012-03-01
We here present a statistical model of hydrogen bond induced network structures in liquid alcohols. The model generalises the Andersson-Schulz-Flory chain model to allow also for branched structures. Two bonding probabilities are assigned to each hydroxyl group oxygen, where the first is the probability of a lone pair accepting an H-bond and the second is the probability that given this bond also the second lone pair is bonded. The average hydroxyl group cluster size, cluster size distribution, and the number of branches and leaves in the tree-like network clusters are directly determined from these probabilities. The applicability of the model is tested by comparison to cluster size distributions and bonding probabilities obtained from Monte Carlo simulations of the monoalcohols methanol, propanol, butanol, and propylene glycol monomethyl ether, the di-alcohol propylene glycol, and the tri-alcohol glycerol. We find that the tree model can reproduce the cluster size distributions and the bonding probabilities for both mono- and poly-alcohols, showing the branched nature of the OH-clusters in these liquids. Thus, this statistical model is a useful tool to better understand the structure of network forming hydrogen bonded liquids. The model can be applied to experimental data, allowing the topology of the clusters to be determined from such studies.
Statistical theory of breakup reactions
International Nuclear Information System (INIS)
We propose an alternative for Coupled-Channels calculations with loosely bound exotic nuclei (CDCC), based on the the Random Matrix Model of the statistical theory of nuclear reactions. The coupled channels equations are divided into two sets. The first set, described by the CDCC, and the other set treated with RMT. The resulting theory is a Statistical CDCC (CDCCs), able in principle to take into account many pseudo channels. (author)
Statistical Theory of Breakup Reactions
Bertulani, Carlos A; Hussein, Mahir S
2014-01-01
We propose alternatives to coupled-channels calculations with loosely-bound exotic nuclei (CDCC), based on the the random matrix (RMT) and the optical background (OPM) models for the statistical theory of nuclear reactions. The coupled channels equations are divided into two sets. The first set, described by the CDCC, and the other set treated with RMT. The resulting theory is a Statistical CDCC (CDCC$_S$), able in principle to take into account many pseudo channels.
Structure functions of the nucleon in a statistical model
Cleymans, J; Joubert, J
1993-01-01
Deep inelastic scattering is considered in a statistical model of the nucleon. This incorporates certain features which are absent in the standard parton model such as quantum statistical correlations which play a role in the propagation of particles when considering Feynman diagrams containing internal lines. The inclusion of the ${\\cal O}(\\alpha_{s})$ corrections in our numerical calculations allows a good fit to the data for $x\\geq 0.25$. The fit corresponds to values of temperature and chemical potential of approximately $T=0.067$ GeV and $\\mu=0.133$ GeV. The latter values of parameters, however, give rise, for all $x$, to a large value for $R=\\sigma_{L}/\\sigma_{T}$.
Digital Image Forgery Detection by Local Statistical Models
Czech Academy of Sciences Publication Activity Database
Grim, Jiří; Somol, Petr; Pudil, Pavel
Los Alamitos, California: IEEE computer society, 2010 - (Echizen, I.; Pan, J.; Fellner, D.; Nouak, A.; Kuijper, A.; Jain, L.), s. 579-582 ISBN 978-0-7695-4222-5. [6th International Conference on Intelligent Information Hiding and Multimedia Signal Processing (IIH-MSP 2010). Darmstadt (DE), 15.10.2010-17.10.2010] R&D Projects: GA MŠk 1M0572; GA ČR GA102/08/0593; GA ČR GA102/07/1594 Grant ostatní: GA MŠk(CZ) 2C06019 Institutional research plan: CEZ:AV0Z10750506 Keywords : forgery detection * local statistical models * distribution mixtures * EM algorithm Subject RIV: IN - Informatics, Computer Science http://library.utia.cas.cz/separaty/2010/RO/grim-digital image forgery detection by local statistical models.pdf
Statistical detection of structural damage based on model reduction
Institute of Scientific and Technical Information of China (English)
Tao YIN; Heung-fai LAM; Hong-ping ZHU
2009-01-01
This paper proposes a statistical method for damage detection based on the finite element (FE) model reduction technique that utilizes measured modal data with a limited number of sensors.A deterministic damage detection process is formulated based on the model reduction technique.The probabilistic process is integrated into the deterministic damage detection process using a perturbation technique,resulting in a statistical structural damage detection method.This is achieved by deriving the firstand second-order partial derivatives of uncertain parameters,such as elasticity of the damaged member,with respect to the measurement noise,which allows expectation and covariance matrix of the uncertain parameters to be calculated.Besides the theoretical development,this paper reports numerical verification of the proposed method using a portal frame example and Monte Carlo simulation.
Statistical mechanics models for multimode lasers and random lasers
Antenucci, F; Berganza, M Ibáñez; Marruzzo, A; Leuzzi, L
2015-01-01
We review recent statistical mechanical approaches to multimode laser theory. The theory has proved very effective to describe standard lasers. We refer of the mean field theory for passive mode locking and developments based on Monte Carlo simulations and cavity method to study the role of the frequency matching condition. The status for a complete theory of multimode lasing in open and disordered cavities is discussed and the derivation of the general statistical models in this framework is presented. When light is propagating in a disordered medium, the system can be analyzed via the replica method. For high degrees of disorder and nonlinearity, a glassy behavior is expected at the lasing threshold, providing a suggestive link between glasses and photonics. We describe in details the results for the general Hamiltonian model in mean field approximation and mention an available test for replica symmetry breaking from intensity spectra measurements. Finally, we summary some perspectives still opened for such...
Passive Target Tracking Based on Current Statistical Model
Institute of Scientific and Technical Information of China (English)
DENG Xiao-long; XIE Jian-ying; YANG Yu-pu
2005-01-01
Bearing-only passive tracking is regarded as a nonlinear hard tracking problem. There are still no completely good solutions to this problem until now. Based on current statistical model, the novel solution to this problem utilizing particle filter (PF) and the unscented Kalman filter (UKF) is proposed. The new solution adopts data fusion from two observers to increase the observability of passive tracking. It applies the residual resampling step to reduce the degeneracy of PF and it introduces the Markov Chain Monte Carlo methods (MCMC) to reduce the effect of the "sample impoverish". Based on current statistical model, the EKF, the UKF and particle filter with various proposal distributions are compared in the passive tracking experiments with two observers. The simulation results demonstrate the good performance of the proposed new filtering methods with the novel techniques.
Garrido-Balsells, José María; Jurado-Navas, Antonio; Paris, José Francisco; Castillo-Vazquez, Miguel; Puerta-Notario, Antonio
2015-03-01
In this paper, a novel and deeper physical interpretation on the recently published Málaga or ℳ statistical distribution is provided. This distribution, which is having a wide acceptance by the scientific community, models the optical irradiance scintillation induced by the atmospheric turbulence. Here, the analytical expressions previously published are modified in order to express them by a mixture of the known Generalized-K and discrete Binomial and Negative Binomial distributions. In particular, the probability density function (pdf) of the ℳ model is now obtained as a linear combination of these Generalized-K pdf, in which the coefficients depend directly on the parameters of the ℳ distribution. In this way, the Málaga model can be physically interpreted as a superposition of different optical sub-channels each of them described by the corresponding Generalized-K fading model and weighted by the ℳ dependent coefficients. The expressions here proposed are simpler than the equations of the original ℳ model and are validated by means of numerical simulations by generating ℳ -distributed random sequences and their associated histogram. This novel interpretation of the Málaga statistical distribution provides a valuable tool for analyzing the performance of atmospheric optical channels for every turbulence condition. PMID:25836855
Statistical Modeling of Large-Scale Signal Path Loss in Underwater Acoustic Networks
Directory of Open Access Journals (Sweden)
Manuel Perez Malumbres
2013-02-01
Full Text Available In an underwater acoustic channel, the propagation conditions are known to vary in time, causing the deviation of the received signal strength from the nominal value predicted by a deterministic propagation model. To facilitate a large-scale system design in such conditions (e.g., power allocation, we have developed a statistical propagation model in which the transmission loss is treated as a random variable. By applying repetitive computation to the acoustic field, using ray tracing for a set of varying environmental conditions (surface height, wave activity, small node displacements around nominal locations, etc., an ensemble of transmission losses is compiled and later used to infer the statistical model parameters. A reasonable agreement is found with log-normal distribution, whose mean obeys a log-distance increases, and whose variance appears to be constant for a certain range of inter-node distances in a given deployment location. The statistical model is deemed useful for higher-level system planning, where simulation is needed to assess the performance of candidate network protocols under various resource allocation policies, i.e., to determine the transmit power and bandwidth allocation necessary to achieve a desired level of performance (connectivity, throughput, reliability, etc..
Exploring Explanations of Subglacial Bedform Sizes Using Statistical Models.
Hillier, John K; Kougioumtzoglou, Ioannis A; Stokes, Chris R; Smith, Michael J; Clark, Chris D; Spagnolo, Matteo S
2016-01-01
Sediments beneath modern ice sheets exert a key control on their flow, but are largely inaccessible except through geophysics or boreholes. In contrast, palaeo-ice sheet beds are accessible, and typically characterised by numerous bedforms. However, the interaction between bedforms and ice flow is poorly constrained and it is not clear how bedform sizes might reflect ice flow conditions. To better understand this link we present a first exploration of a variety of statistical models to explain the size distribution of some common subglacial bedforms (i.e., drumlins, ribbed moraine, MSGL). By considering a range of models, constructed to reflect key aspects of the physical processes, it is possible to infer that the size distributions are most effectively explained when the dynamics of ice-water-sediment interaction associated with bedform growth is fundamentally random. A 'stochastic instability' (SI) model, which integrates random bedform growth and shrinking through time with exponential growth, is preferred and is consistent with other observations of palaeo-bedforms and geophysical surveys of active ice sheets. Furthermore, we give a proof-of-concept demonstration that our statistical approach can bridge the gap between geomorphological observations and physical models, directly linking measurable size-frequency parameters to properties of ice sheet flow (e.g., ice velocity). Moreover, statistically developing existing models as proposed allows quantitative predictions to be made about sizes, making the models testable; a first illustration of this is given for a hypothesised repeat geophysical survey of bedforms under active ice. Thus, we further demonstrate the potential of size-frequency distributions of subglacial bedforms to assist the elucidation of subglacial processes and better constrain ice sheet models. PMID:27458921
Exploring Explanations of Subglacial Bedform Sizes Using Statistical Models.
Directory of Open Access Journals (Sweden)
John K Hillier
Full Text Available Sediments beneath modern ice sheets exert a key control on their flow, but are largely inaccessible except through geophysics or boreholes. In contrast, palaeo-ice sheet beds are accessible, and typically characterised by numerous bedforms. However, the interaction between bedforms and ice flow is poorly constrained and it is not clear how bedform sizes might reflect ice flow conditions. To better understand this link we present a first exploration of a variety of statistical models to explain the size distribution of some common subglacial bedforms (i.e., drumlins, ribbed moraine, MSGL. By considering a range of models, constructed to reflect key aspects of the physical processes, it is possible to infer that the size distributions are most effectively explained when the dynamics of ice-water-sediment interaction associated with bedform growth is fundamentally random. A 'stochastic instability' (SI model, which integrates random bedform growth and shrinking through time with exponential growth, is preferred and is consistent with other observations of palaeo-bedforms and geophysical surveys of active ice sheets. Furthermore, we give a proof-of-concept demonstration that our statistical approach can bridge the gap between geomorphological observations and physical models, directly linking measurable size-frequency parameters to properties of ice sheet flow (e.g., ice velocity. Moreover, statistically developing existing models as proposed allows quantitative predictions to be made about sizes, making the models testable; a first illustration of this is given for a hypothesised repeat geophysical survey of bedforms under active ice. Thus, we further demonstrate the potential of size-frequency distributions of subglacial bedforms to assist the elucidation of subglacial processes and better constrain ice sheet models.
Exploring Explanations of Subglacial Bedform Sizes Using Statistical Models
Kougioumtzoglou, Ioannis A.; Stokes, Chris R.; Smith, Michael J.; Clark, Chris D.; Spagnolo, Matteo S.
2016-01-01
Sediments beneath modern ice sheets exert a key control on their flow, but are largely inaccessible except through geophysics or boreholes. In contrast, palaeo-ice sheet beds are accessible, and typically characterised by numerous bedforms. However, the interaction between bedforms and ice flow is poorly constrained and it is not clear how bedform sizes might reflect ice flow conditions. To better understand this link we present a first exploration of a variety of statistical models to explain the size distribution of some common subglacial bedforms (i.e., drumlins, ribbed moraine, MSGL). By considering a range of models, constructed to reflect key aspects of the physical processes, it is possible to infer that the size distributions are most effectively explained when the dynamics of ice-water-sediment interaction associated with bedform growth is fundamentally random. A ‘stochastic instability’ (SI) model, which integrates random bedform growth and shrinking through time with exponential growth, is preferred and is consistent with other observations of palaeo-bedforms and geophysical surveys of active ice sheets. Furthermore, we give a proof-of-concept demonstration that our statistical approach can bridge the gap between geomorphological observations and physical models, directly linking measurable size-frequency parameters to properties of ice sheet flow (e.g., ice velocity). Moreover, statistically developing existing models as proposed allows quantitative predictions to be made about sizes, making the models testable; a first illustration of this is given for a hypothesised repeat geophysical survey of bedforms under active ice. Thus, we further demonstrate the potential of size-frequency distributions of subglacial bedforms to assist the elucidation of subglacial processes and better constrain ice sheet models. PMID:27458921
A statistical mechanics model of carbon nanotube macro-films
Institute of Scientific and Technical Information of China (English)
无
2011-01-01
Carbon nanotube macro-films are two-dimensional films with micrometer thickness and centimeter by centimeter in-plane dimension.These carbon nanotube macroscopic assemblies have attracted significant attention from the material and mechanics communities recently because they can be easily handled and tailored to meet specific engineering needs.This paper reports the experimental methods on the preparation and characterization of single-walled carbon nanotube macro-films,and a statistical mechanics model on ...
Multistrange Particle Production and the Statistical Hadronization Model
Petran, Michal
2009-01-01
We consider chemical freeze-out of multistrange hadrons within a Statistical Hadronization Model (SHM) inspired approach. We look at (relative) rates of Xi , \\overline\\Xi baryon and phi meson yields from the NA49 at SPS and STAR at RHIC experiments across energies and centralities in order to constrain the physical conditions present in the hot dense fireball source of strange hadrons, and to anticipate results expected at LHC.
A Statistical Model for Soliton Particle Interaction in Plasmas
DEFF Research Database (Denmark)
Dysthe, K. B.; Pécseli, Hans; Truelsen, J.
1986-01-01
A statistical model for soliton-particle interaction is presented. A master equation is derived for the time evolution of the particle velocity distribution as induced by resonant interaction with Korteweg-de Vries solitons. The detailed energy balance during the interaction subsequently determines...... the evolution of the soliton amplitude distribution. The analysis applies equally well for weakly nonlinear plasma waves in a strongly magnetized waveguide, or for ion acoustic waves propagating in one-dimensional systems....
Generalized photon and atomic statistics in Jaynes-Cummings models
International Nuclear Information System (INIS)
The interaction between a single two-level and a single mode is studied in some Jaynes-Cummings models. The coupling is supposed to depend on a function of the photon number operator. The evolution operator is calculated; then the probability distribution is obtained. Different statistical quantities are computed for the two states of the atom and different initial distributions for the radiation mode. Three modes are taken, namely, thermal, coherent and squeezed coherent light. (author)
Optimal Fuzzy Model Construction with Statistical Information using Genetic Algorithm
Bishnu Sarker; Kazuyuki Murase; Amjad Hossain; Pintu Chandra Shill
2012-01-01
Fuzzy rule based models have a capability to approximate any continuous function to any degree of accuracy on a compact domain. The majority of FLC design process relies on heuristic knowledge of experience operators. In order to make the design process automatic we present a genetic approach to learn fuzzy rules as well as membership function parameters. Moreover, several statistical information criteria such as the Akaike information criterion (AIC), the Bhansali-Downham information criteri...
Nam, Sungsik
2011-08-01
Spread spectrum receivers with generalized selection combining (GSC) RAKE reception were proposed and have been studied as alternatives to the classical two fundamental schemes: maximal ratio combining and selection combining because the number of diversity paths increases with the transmission bandwidth. Previous work on performance analyses of GSC RAKE receivers based on the signal to noise ratio focused on the development of methodologies to derive exact closed-form expressions for various performance measures. However, some open problems related to the performance evaluation of GSC RAKE receivers still remain to be solved such as the exact performance analysis of the capture probability and an exact assessment of the impact of self-interference on GSC RAKE receivers. The major difficulty in these problems is to derive some joint statistics of ordered exponential variates. With this motivation in mind, we capitalize in this paper on some new order statistics results to derive exact closed-form expressions for the capture probability and outage probability of GSC RAKE receivers subject to self-interference over independent and identically distributed Rayleigh fading channels, and compare it to that of partial RAKE receivers. © 2011 IEEE.
A statistical method for descriminating between alternative radiobiological models
International Nuclear Information System (INIS)
Radiobiological models assist understanding of the development of radiation damage, and may provide a basis for extrapolating dose-effect curves from high to low dose regions. Many models have been proposed such as multitarget and its modifications, enzymatic models, and those with a quadratic dose response relationship (i.e. αD + βD2 forms). It is difficult to distinguish between these because the statistical techniques used are almost always limited, in that one method can rarely be applied to the whole range of models. A general statistical procedure for parameter estimation (Maximum Liklihood Method) has been found applicable to a wide range of radiobiological models. The curve parameters are estimated using a computerised search that continues until the most likely set of values to fit the data is obtained. When the search is complete two procedures are carried out. First a goodness of fit test is applied which examines the applicability of an individual model to the data. Secondly an index is derived which provides an indication of the adequacy of any model compared with alternative models. Thus the models may be ranked according to how well they fit the data. For example, with one set of data, multitarget types were found to be more suitable than quadratic types (αD + βD2). This method should be of assitance is evaluating various models. It may also be profitably applied to selection of the most appropriate model to use, when it is necessary to extrapolate from high to low doses
Thermally stratified sodium channel flow: turbulence and modeling
International Nuclear Information System (INIS)
Numerical simulation of sodium stratification in open channel flow has been studied with Computational Fluid Dynamics (CFD) employing an Algebraic Heat Flux Model (AHFM) closure for the turbulent heat flux. The results are validated against experimental data and the AHFM is compared with the simplified Reynolds analogy employing a constant turbulent Pr number. Influence of buoyancy on turbulence created in the mixing layer has been evaluated and its influence on the momentum and energy transport in the vertical direction assessed. It has been found that the choice of turbulent heat flux model influences the achieved results for temperature and velocity field which might affect the flow developing and persistence of stratification in the channel. Moreover both experiment and validation show the possibility of creation of a strong stratification also for low Pr number fluids, warning the stratification problem as an existing phenomenon likely to occur in liquid metal nuclear power plants. (author)
Cascaded Network Body Channel Model for Intrabody Communication.
Wang, Hao; Tang, Xian; Choy, Chiu Sing; Sobelman, Gerald E
2016-07-01
Intrabody communication has been of great research interest in recent years. This paper proposes a novel, compact but accurate body transmission channel model based on RC distribution networks and transmission line theory. The comparison between simulation and measurement results indicates that the proposed approach accurately models the body channel characteristics. In addition, the impedance-matching networks at the transmitter output and the receiver input further maximize the power transferred to the receiver, relax the receiver complexity, and increase the transmission performance. Based on the simulation results, the power gain can be increased by up to 16 dB after matching. A binary phase-shift keying modulation scheme is also used to evaluate the bit-error-rate improvement. PMID:26111404
Mathematical and Statistical Modeling in Cancer Systems Biology
Directory of Open Access Journals (Sweden)
Rachael eHageman Blair
2012-06-01
Full Text Available Cancer is a major health problem with high mortality rates. In the post-genome era, investigators have access to massive amounts of rapidly accumulating high-throughput data in publicly available databases, some of which are exclusively devoted to housing Cancer data. However, data interpretation efforts have not kept pace with data collection, and gained knowledge is not necessarily translating into better diagnoses and treatments. A fundamental problem is to integrate and interpret data to further our understanding in Cancer Systems Biology. Viewing cancer as a network provides insights into the complex mechanisms underlying the disease. Mathematical and statistical models provide an avenue for cancer network modeling. In this article, we review two widely used modeling paradigms: deterministic metabolic models and statistical graphical models. The strength of these approaches lies in their flexibility and predictive power. Once a model has been validated, it can be used to make predictions and generate hypotheses. We describe a number of diverse applications to Cancer Biology, including, the system-wide effects of drug-treatments, disease prognosis, tumor classification, forecasting treatment outcomes, and survival predictions.
Physical-Statistical Model of Thermal Conductivity of Nanofluids
Directory of Open Access Journals (Sweden)
B. Usowicz
2014-01-01
Full Text Available A physical-statistical model for predicting the effective thermal conductivity of nanofluids is proposed. The volumetric unit of nanofluids in the model consists of solid, liquid, and gas particles and is treated as a system made up of regular geometric figures, spheres, filling the volumetric unit by layers. The model assumes that connections between layers of the spheres and between neighbouring spheres in the layer are represented by serial and parallel connections of thermal resistors, respectively. This model is expressed in terms of thermal resistance of nanoparticles and fluids and the multinomial distribution of particles in the nanofluids. The results for predicted and measured effective thermal conductivity of several nanofluids (Al2O3/ethylene glycol-based and Al2O3/water-based; CuO/ethylene glycol-based and CuO/water-based; and TiO2/ethylene glycol-based are presented. The physical-statistical model shows a reasonably good agreement with the experimental results and gives more accurate predictions for the effective thermal conductivity of nanofluids compared to existing classical models.
Statistical mechanical modeling: Computer simulations, analysis and applications
Subramanian, Balakrishna
This thesis describes the applications of statistical mechanical models and tools, especially computational techniques to the study of several problems in science. We study in chapter 2, various properties of a non-equilibrium cellular automaton model, the Toom model. We obtain numerically the exponents describing the fluctuations of the interface between the two stable phases of the model. In chapter 3, we introduce a binary alloy model with three-body potentials. Unlike the usual Ising-type models with two-body interactions, this model is not symmetric in its components. We calculate the exact low temperature phase diagram using Pirogov-Sinai theory and also find the mean-field equilibrium properties of this model. We then study the kinetics of phase segregation following a quenching in this model. We find that the results are very similar to those obtained for Ising-type models with pair interactions, indicating universality. In chapter 4, we discuss the statistical properties of "Contact Maps". These maps, are used to represent three-dimensional structures of proteins in modeling problems. We find that this representation space has particular properties that make it a convenient choice. The maps representing native folds of proteins correspond to compact structures which in turn correspond to maps with low degeneracy, making it easier to translate the map into the detailed 3-dimensional structure. The early stage of formation of a river network is described in Chapter 5 using quasi-random spanning trees on a square lattice. We observe that the statistical properties generated by these models are quite similar (better than some of the earlier models) to the empirical laws and results presented by geologists for real river networks. Finally, in chapter 6 we present a brief note on our study of the problem of progression of heterogeneous breast tumors. We investigate some of the possible pathways of progression based on the traditional notions of DCIS (Ductal
Statistical mechanics of the Huxley-Simmons model
Caruel, M
2016-01-01
The chemomechanical model of Huxley and Simmons (HS) [A. F. Huxley and R. M. Simmons, Nature 233, 533 (1971)] provides a paradigmatic description of mechanically induced collective conformational changes relevant in a variety of biological contexts, from muscles power-stroke and hair cell gating to integrin binding and hairpin unzipping. We develop a statistical mechanical perspective on the HS model by exploiting a formal analogy with a paramagnetic Ising model. We first study the equilibrium HS model with a finite number of elements and compute explicitly its mechanical and thermal properties. To model kinetics, we derive a master equation and solve it for several loading protocols. The developed formalism is applicable to a broad range of allosteric systems with mean-field interactions.
Statistical mechanics of the Huxley-Simmons model
Caruel, M.; Truskinovsky, L.
2016-06-01
The chemomechanical model of Huxley and Simmons (HS) [A. F. Huxley and R. M. Simmons, Nature 233, 533 (1971), 10.1038/233533a0] provides a paradigmatic description of mechanically induced collective conformational changes relevant in a variety of biological contexts, from muscles power stroke and hair cell gating to integrin binding and hairpin unzipping. We develop a statistical mechanical perspective on the HS model by exploiting a formal analogy with a paramagnetic Ising model. We first study the equilibrium HS model with a finite number of elements and compute explicitly its mechanical and thermal properties. To model kinetics, we derive a master equation and solve it for several loading protocols. The developed formalism is applicable to a broad range of allosteric systems with mean-field interactions.
Basic equations of channel model for underground coal gasification
Institute of Scientific and Technical Information of China (English)
无
2002-01-01
The underground coal gasification has advantages of zero rubbish, nonpollution, low cost and high safety. According to the characteristics of the gasification, the channel model of chemical fluid mechanics is used to set up the fluid equations and chemical equations by some reasonable suppositions in this paper, which lays a theoretical foundation on requirements of fluid movement rules in the process of underground coal gasification.
A statistical model for red blood cell survival.
Korell, Julia; Coulter, Carolyn V; Duffull, Stephen B
2011-01-01
A statistical model for the survival time of red blood cells (RBCs) with a continuous distribution of cell lifespans is presented. The underlying distribution of RBC lifespans is derived from a probability density function with a bathtub-shaped hazard curve, and accounts for death of RBCs due to senescence (age-dependent increasing hazard rate) and random destruction (constant hazard), as well as for death due to initial or delayed failures and neocytolysis (equivalent to early red cell mortality). The model yields survival times similar to those of previously published studies of RBC survival and is easily amenable to inclusion of drug effects and haemolytic disorders. PMID:20950630
Statistical mechanics of attractor neural network models with synaptic depression
International Nuclear Information System (INIS)
Synaptic depression is known to control gain for presynaptic inputs. Since cortical neurons receive thousands of presynaptic inputs, and their outputs are fed into thousands of other neurons, the synaptic depression should influence macroscopic properties of neural networks. We employ simple neural network models to explore the macroscopic effects of synaptic depression. Systems with the synaptic depression cannot be analyzed due to asymmetry of connections with the conventional equilibrium statistical-mechanical approach. Thus, we first propose a microscopic dynamical mean field theory. Next, we derive macroscopic steady state equations and discuss the stabilities of steady states for various types of neural network models.
Hydrological responses to dynamically and statistically downscaled climate model output
Wilby, R.L.; Hay, L.E.; Gutowski, W.J., Jr.; Arritt, R.W.; Takle, E.S.; Pan, Z.; Leavesley, G.H.; Clark, M.P.
2000-01-01
Daily rainfall and surface temperature series were simulated for the Animas River basin, Colorado using dynamically and statistically downscaled output from the National Center for Environmental Prediction/National Center for Atmospheric Research (NCEP/NCAR) re-analysis. A distributed hydrological model was then applied to the downscaled data. Relative to raw NCEP output, downscaled climate variables provided more realistic stimulations of basin scale hydrology. However, the results highlight the sensitivity of modeled processes to the choice of downscaling technique, and point to the need for caution when interpreting future hydrological scenarios.
Modeling magnetosensitive ion channels in viscoelastic environment of living cells
Goychuk, Igor
2015-01-01
We propose and study a model of hypothetical magnetosensitive ionic channels which are long thought to be a possible candidate to explain the influence of weak magnetic fields on living organisms ranging from magnetotactic bacteria to fishes, birds, rats, bats and other mammals including humans. The core of the model is provided by a short chain of magnetosomes serving as a sensor which is coupled by elastic linkers to the gating elements of ion channels forming a small cluster in the cell membrane. The magnetic sensor is fixed by one end on cytoskeleton elements attached to the membrane and is exposed to viscoelastic cytosol. Its free end can reorient stochastically and subdiffusively in viscoelastic cytosol responding to external magnetic field changes and open the gates of coupled ion channels. The sensor dynamics is generally bistable due to bistability of the gates which can be in two states with probabilities which depend on the sensor orientation. For realistic parameters, it is shown that this model c...
Statistical models for expert judgement and wear prediction
International Nuclear Information System (INIS)
This thesis studies the statistical analysis of expert judgements and prediction of wear. The point of view adopted is the one of information theory and Bayesian statistics. A general Bayesian framework for analyzing both the expert judgements and wear prediction is presented. Information theoretic interpretations are given for some averaging techniques used in the determination of consensus distributions. Further, information theoretic models are compared with a Bayesian model. The general Bayesian framework is then applied in analyzing expert judgements based on ordinal comparisons. In this context, the value of information lost in the ordinal comparison process is analyzed by applying decision theoretic concepts. As a generalization of the Bayesian framework, stochastic filtering models for wear prediction are formulated. These models utilize the information from condition monitoring measurements in updating the residual life distribution of mechanical components. Finally, the application of stochastic control models in optimizing operational strategies for inspected components are studied. Monte-Carlo simulation methods, such as the Gibbs sampler and the stochastic quasi-gradient method, are applied in the determination of posterior distributions and in the solution of stochastic optimization problems. (orig.) (57 refs., 7 figs., 1 tab.)
Non-gaussianity and Statistical Anisotropy in Cosmological Inflationary Models
Valenzuela-Toledo, Cesar A
2010-01-01
We study the statistical descriptors for some cosmological inflationary models that allow us to get large levels of non-gaussianity and violations of statistical isotropy. Basically, we study two different class of models: a model that include only scalar field perturbations, specifically a subclass of small-field slow-roll models of inflation with canonical kinetic terms, and models that admit both vector and scalar field perturbations. We study the former to show that it is possible to attain very high, including observable, values for the levels of non-gaussianity f_{NL} and \\tao_{NL} in the bispectrum B_\\zeta and trispectrum T_\\zeta of the primordial curvature perturbation \\zeta respectively. Such a result is obtained by taking care of loop corrections in the spectrum P_\\zeta, the bispectrum B_\\zeta and the trispectrum T_\\zeta . Sizeable values for f_{NL} and \\tao_{NL} arise even if \\zeta is generated during inflation. For the latter we study the spectrum P_\\zeta, bispectrum B_\\zeta and trispectrum $T_\\ze...
The Statistical Multifragmentation Model with Skyrme Effective Interactions
Carlson, B V; Donangelo, R; Lynch, W G; Steiner, A W; Tsang, M B
2010-01-01
The Statistical Multifragmentation Model is modified to incorporate Helmholtz free energies calculated in the finite temperature Thomas-Fermi approximation using Skyrme effective interactions. In this formulation, the density of the fragments at the freeze-out configuration corresponds to the equilibrium value obtained in the Thomas-Fermi approximation at the given temperature. The behavior of the nuclear caloric curve, at constant volume, is investigated in the micro-canonical ensemble and a plateau is observed for excitation energies between 8 and 10 MeV per nucleon. A small kink in the caloric curve is found at the onset of this gas transition, indicating the existence of negative heat capacity, even in this case in which the system is constrained to a fixed volume, in contrast to former statistical calculations.
A check-up for the statistical Parton model
Buccella, Franco; Sohaily, Sozha
2015-11-01
We compare the Parton distributions deduced in the framework of a quantum statistical approach for both the longitudinal and transverse degrees of freedom with the unpolarized distributions measured at HERA and with the polarized ones proposed in a previous paper, which have been shown to be in very good agreement also with the results of experiments performed after that proposal. The agreement with HERA data in correspondence to very similar values for the “temperature” and the “potentials” found in the previous work gives a robust confirm of the statistical model. The unpolarized distributions are compared also with the result of NNPDF. The free parameters are fixed mainly by data in the range (0.1, 0.5) for the x variable, where the valence Partons dominate, and in the small x region for the diffractive contribution. This feature makes the parametrization proposed here very attractive.
Statistical Inference for Partially Linear Regression Models with Measurement Errors
Institute of Scientific and Technical Information of China (English)
Jinhong YOU; Qinfeng XU; Bin ZHOU
2008-01-01
In this paper, the authors investigate three aspects of statistical inference for the partially linear regression models where some covariates are measured with errors. Firstly,a bandwidth selection procedure is proposed, which is a combination of the difference-based technique and GCV method. Secondly, a goodness-of-fit test procedure is proposed,which is an extension of the generalized likelihood technique. Thirdly, a variable selection procedure for the parametric part is provided based on the nonconcave penalization and corrected profile least squares. Same as "Variable selection via nonconcave penalized like-lihood and its oracle properties" (J. Amer. Statist. Assoc., 96, 2001, 1348-1360), it is shown that the resulting estimator has an oracle property with a proper choice of regu-larization parameters and penalty function. Simulation studies are conducted to illustrate the finite sample performances of the proposed procedures.
An Analytical Model for Vertical Profiles in Submarine Channels
Bolla Pittaluga, M.; Imran, J.
2011-12-01
Turbidity currents are the primary agents carrying sediments from the continental shelf to the deep-sea. They are the counterpart of fluvial currents in the deep-sea environment and are responsible for the shaping of submarine channels. Due to the unpredictability of events and to their ability to destroy installed monitoring instruments, only a few attempts to directly measure the properties of turbidity currents in submarine channels has proved to be successful (Xu et al., 2004; Xu, 2010). Consequently the vast majority of the studies concerning the vertical structure of turbidity currents were either laboratory experiments or numerical models. In spite of the relevance of the problem, related to the consequences of flow field on sedimentary deposits, at present an ongoing debate still exist on similarities and differences between submarine and fluvial channels related in particular to the orientation of the helical flow in channel bends. Here we expand on the above ideas and develop an analytical theory for flow and suspended sediment transport in submarine channels able to describe vertical profiles of both flow field and suspendend sediment concentration. The turbulence closure needed to account for density stratification is adapted from the model of Mellor and Yamada (1982). Solutions are found for both straight and constant curvature channels. In the latter case, in order to evaluate the secondary flow induced by curvature, we take advantage of the fact that the ratio of flow depth to radius of curvature is typically small in the field, which leads to a solution of the governing equations through an appropriate asymptotic expansion. Steady fully developed flow conditions in a bend of constant width are considered. Results for longitudinal velocity and concentration profiles in straight channels are then compared with experimental observations of Sequeiros et al. (2010) providing good agreement. We also expect to find under which values of the controlling
Statistical Process Control of a Kalman Filter Model
Directory of Open Access Journals (Sweden)
Sonja Gamse
2014-09-01
Full Text Available For the evaluation of measurement data, different functional and stochastic models can be used. In the case of time series, a Kalman filtering (KF algorithm can be implemented. In this case, a very well-known stochastic model, which includes statistical tests in the domain of measurements and in the system state domain, is used. Because the output results depend strongly on input model parameters and the normal distribution of residuals is not always fulfilled, it is very important to perform all possible tests on output results. In this contribution, we give a detailed description of the evaluation of the Kalman filter model. We describe indicators of inner confidence, such as controllability and observability, the determinant of state transition matrix and observing the properties of the a posteriori system state covariance matrix and the properties of the Kalman gain matrix. The statistical tests include the convergence of standard deviations of the system state components and normal distribution beside standard tests. Especially, computing controllability and observability matrices and controlling the normal distribution of residuals are not the standard procedures in the implementation of KF. Practical implementation is done on geodetic kinematic observations.
Statistical process control of a Kalman filter model.
Gamse, Sonja; Nobakht-Ersi, Fereydoun; Sharifi, Mohammad A
2014-01-01
For the evaluation of measurement data, different functional and stochastic models can be used. In the case of time series, a Kalman filtering (KF) algorithm can be implemented. In this case, a very well-known stochastic model, which includes statistical tests in the domain of measurements and in the system state domain, is used. Because the output results depend strongly on input model parameters and the normal distribution of residuals is not always fulfilled, it is very important to perform all possible tests on output results. In this contribution, we give a detailed description of the evaluation of the Kalman filter model. We describe indicators of inner confidence, such as controllability and observability, the determinant of state transition matrix and observing the properties of the a posteriori system state covariance matrix and the properties of the Kalman gain matrix. The statistical tests include the convergence of standard deviations of the system state components and normal distribution beside standard tests. Especially, computing controllability and observability matrices and controlling the normal distribution of residuals are not the standard procedures in the implementation of KF. Practical implementation is done on geodetic kinematic observations. PMID:25264959
Analysis of pediatric airway morphology using statistical shape modeling.
Humphries, Stephen M; Hunter, Kendall S; Shandas, Robin; Deterding, Robin R; DeBoer, Emily M
2016-06-01
Traditional studies of airway morphology typically focus on individual measurements or relatively simple lumped summary statistics. The purpose of this work was to use statistical shape modeling (SSM) to synthesize a skeleton model of the large bronchi of the pediatric airway tree and to test for overall airway shape differences between two populations. Airway tree anatomy was segmented from volumetric chest computed tomography of 20 control subjects and 20 subjects with cystic fibrosis (CF). Airway centerlines, particularly bifurcation points, provide landmarks for SSM. Multivariate linear and logistic regression was used to examine the relationships between airway shape variation, subject size, and disease state. Leave-one-out cross-validation was performed to test the ability to detect shape differences between control and CF groups. Simulation experiments, using tree shapes with known size and shape variations, were performed as a technical validation. Models were successfully created using SSM methods. Simulations demonstrated that the analysis process can detect shape differences between groups. In clinical data, CF status was discriminated with good accuracy (precision = 0.7, recall = 0.7) in leave-one-out cross-validation. Logistic regression modeling using all subjects showed a good fit (ROC AUC = 0.85) and revealed significant differences in SSM parameters between control and CF groups. The largest mode of shape variation was highly correlated with subject size (R = 0.95, p control. PMID:26718559
Modeling the statistics of image features and associated text
Barnard, Kobus; Duygulu, Pinar; Forsyth, David A.
2001-12-01
We present a methodology for modeling the statistics of image features and associated text in large datasets. The models used also serve to cluster the images, as images are modeled as being produced by sampling from a limited number of combinations of mixing components. Furthermore, because our approach models the joint occurrence image features and associated text, it can be used to predict the occurrence of either, based on observations or queries. This supports an attractive approach to image search as well as novel applications such a suggesting illustrations for blocks of text (auto-illustrate) and generating words for images outside the training set (auto-annotate). In this paper we illustrate the approach on 10,000 images of work from the Fine Arts Museum of San Francisco. The images include line drawings, paintings, and pictures of sculpture and ceramics. Many of the images have associated free text whose nature varies greatly, from physical description to interpretation and mood. We incorporate statistical natural language processing in order to deal with free text. We use WordNet to provide semantic grouping information and to help disambiguate word senses, as well as emphasize the hierarchical nature of semantic relationships.
Model output statistics applied to wind power prediction
Energy Technology Data Exchange (ETDEWEB)
Joensen, A.; Giebel, G.; Landberg, L. [Risoe National Lab., Roskilde (Denmark); Madsen, H.; Nielsen, H.A. [The Technical Univ. of Denmark, Dept. of Mathematical Modelling, Lyngby (Denmark)
1999-03-01
Being able to predict the output of a wind farm online for a day or two in advance has significant advantages for utilities, such as better possibility to schedule fossil fuelled power plants and a better position on electricity spot markets. In this paper prediction methods based on Numerical Weather Prediction (NWP) models are considered. The spatial resolution used in NWP models implies that these predictions are not valid locally at a specific wind farm. Furthermore, due to the non-stationary nature and complexity of the processes in the atmosphere, and occasional changes of NWP models, the deviation between the predicted and the measured wind will be time dependent. If observational data is available, and if the deviation between the predictions and the observations exhibits systematic behavior, this should be corrected for; if statistical methods are used, this approaches is usually referred to as MOS (Model Output Statistics). The influence of atmospheric turbulence intensity, topography, prediction horizon length and auto-correlation of wind speed and power is considered, and to take the time-variations into account, adaptive estimation methods are applied. Three estimation techniques are considered and compared, Extended Kalman Filtering, recursive least squares and a new modified recursive least squares algorithm. (au) EU-JOULE-3. 11 refs.
Generalized Statistical Models of Voids and Hierarchical Structure in Cosmology
Mekjian, Aram Z.
2007-01-01
Generalized statistical models of voids and hierarchical structure in cosmology are developed. The often quoted negative binomial model and the frequently used thermodynamic model are shown to be special cases of a more general distribution that contains a parameter a. This parameter is related to the Lévy index α and the Fisher critical exponent τ, the latter of which describes the power-law falloff of clumps of matter around a phase transition. The parameter a, exponent τ, or index α can be obtained from properties of a void scaling function. A stochastic probability variable p is introduced into a statistical model, which represents the adhesive growth of galaxy structure. The galaxy count distribution decays exponentially quickly with size for p1/2, adhesive growth can go on indefinitely, thereby forming an infinite supercluster. At p=1/2, a scale-free power-law distribution for the galaxy count distribution is present. The stochastic description also leads to consequences that have some parallels with cosmic string results, percolation theory, and phase transitions.
Statistical Model for a Complete Supernova Equation of State
Hempel, Matthias
2009-01-01
A statistical model for the equation of state (EOS) and the composition of supernova matter is presented with focus on the liquid-gas phase transition of nuclear matter. It consists of an ensemble of nuclei and interacting nucleons in nuclear statistical equilibrium. A relativistic mean field model is applied for the nucleons. The masses of the nuclei are taken from nuclear structure calculations which are based on the same nuclear Lagrangian. For known nuclei experimental data is used directly. Excluded volume effects are implemented in a thermodynamic consistent way so that the transition to uniform nuclear matter at large densities can be described. Thus the model can be applied at all densities relevant for supernova simulations, i.e. rho=10^5 - 10^15 g/cm^3, and it is possible to calculate a complete supernova EOS table. The model allows to investigate the role of shell effects, which lead to narrow-peaked distributions around the neutron magic numbers for low temperatures. At larger temperatures the dis...
Hybrid perturbation methods based on statistical time series models
San-Juan, Juan Félix; San-Martín, Montserrat; Pérez, Iván; López, Rosario
2016-04-01
In this work we present a new methodology for orbit propagation, the hybrid perturbation theory, based on the combination of an integration method and a prediction technique. The former, which can be a numerical, analytical or semianalytical theory, generates an initial approximation that contains some inaccuracies derived from the fact that, in order to simplify the expressions and subsequent computations, not all the involved forces are taken into account and only low-order terms are considered, not to mention the fact that mathematical models of perturbations not always reproduce physical phenomena with absolute precision. The prediction technique, which can be based on either statistical time series models or computational intelligence methods, is aimed at modelling and reproducing missing dynamics in the previously integrated approximation. This combination results in the precision improvement of conventional numerical, analytical and semianalytical theories for determining the position and velocity of any artificial satellite or space debris object. In order to validate this methodology, we present a family of three hybrid orbit propagators formed by the combination of three different orders of approximation of an analytical theory and a statistical time series model, and analyse their capability to process the effect produced by the flattening of the Earth. The three considered analytical components are the integration of the Kepler problem, a first-order and a second-order analytical theories, whereas the prediction technique is the same in the three cases, namely an additive Holt-Winters method.
Sketch of a Noisy Channel Model for the Translation Process
DEFF Research Database (Denmark)
Carl, Michael
The paper develops a Noisy Channel Model for the translation process that is based on actual user activity data. It builds on the monitor model and makes a distinction between early, automatic and late, conscious translation processes: while early priming processes are at the basis of a "literal...... default rendering" procedure, later conscious processes are triggered by a monitor who interferes when something goes wrong. An attempt is made to explain monitor activities with relevance theoretic concepts according to which a translator needs to ensure the similarity of explicatures and implicatures of...
A Unified Channel Charges Expression for Analytic MOSFET Modeling
Directory of Open Access Journals (Sweden)
Hugues Murray
2012-01-01
Full Text Available Based on a 1D Poissons equation resolution, we present an analytic model of inversion charges allowing calculation of the drain current and transconductance in the Metal Oxide Semiconductor Field Effect Transistor. The drain current and transconductance are described by analytical functions including mobility corrections and short channel effects (CLM, DIBL. The comparison with the Pao-Sah integral shows excellent accuracy of the model in all inversion modes from strong to weak inversion in submicronics MOSFET. All calculations are encoded with a simple C program and give instantaneous results that provide an efficient tool for microelectronics users.
Self-organized models of selectivity in calcium channels
International Nuclear Information System (INIS)
The role of flexibility in the selectivity of calcium channels is studied using a simple model with two parameters that accounts for the selectivity of calcium (and sodium) channels in many ionic solutions of different compositions and concentrations using two parameters with unchanging values. We compare the distribution of side chains (oxygens) and cations (Na+ and Ca2+) and integrated quantities. We compare the occupancies of cations Ca2+/Na+ and linearized conductance of Na+. The distributions show a strong dependence on the locations of fixed side chains and the flexibility of the side chains. Holding the side chains fixed at certain predetermined locations in the selectivity filter distorts the distribution of Ca2+ and Na+ in the selectivity filter. However, integrated quantities—occupancy and normalized conductance—are much less sensitive. Our results show that some flexibility of side chains is necessary to avoid obstruction of the ionic pathway by oxygen ions in 'unfortunate' fixed positions. When oxygen ions are mobile, they adjust 'automatically' and move 'out of the way', so they can accommodate the permeable cations in the selectivity filter. Structure is the computed consequence of the forces in this model. The structures are self-organized, at their free energy minimum. The relationship of ions and side chains varies with an ionic solution. Monte Carlo simulations are particularly well suited to compute induced-fit, self-organized structures because the simulations yield an ensemble of structures near their free energy minimum. The exact location and mobility of oxygen ions has little effect on the selectivity behavior of calcium channels. Seemingly, nature has chosen a robust mechanism to control selectivity in calcium channels: the first-order determinant of selectivity is the density of charge in the selectivity filter. The density is determined by filter volume along with the charge and excluded volume of
Coupled-channel optical model potential for rare earth nuclei
Herman, M; Palumbo, A; Dietrich, F S; Brown, D; Hoblit, S
2013-01-01
Inspired by the recent work by Dietrich et al., substantiating validity of the adiabatic assumption in coupled-channel calculations, we explore the possibility of generalizing a global spherical optical model potential (OMP) to make it usable in coupled-channel calculations on statically deformed nuclei. The generalization consists in adding the coupling of the ground state rotational band, deforming the potential by introducing appropriate quadrupole and hexadecupole deformation and correcting the OMP radius to preserve volume integral of the spherical OMP. We choose isotopes of three rare-earth elements (W, Ho, Gd), which are known to be nearly perfect rotors, to perform a consistent test of our conjecture on integrated cross sections as well as on angular distributions for elastic and inelastic neutron scattering. When doing this we employ the well-established Koning-Delaroche global spherical potential and experimentally determined deformations without any adjustments. We observe a dramatically improved a...
Rivier, Aurelie; Guillou, Nicolas; Chapalain, Georges; Gohin, Francis
2012-01-01
Concentration of near-surface suspended particulate matter (SPM) is a key parameter for the characterization of sediment dynamics and the quantification of light in the water column for hydrological and biological modeling in coastal seas. The influences of tides and wind-generated surface-gravity waves on non-algal near-surface SPM in the English Channel have recently been identified by Rivier et al. (2012) on the basis of statistical models applied to a large satellite dataset. The present ...
Evaluating statistical analysis models for RNA sequencing experiments
Directory of Open Access Journals (Sweden)
Pablo eReeb
2013-09-01
Full Text Available Validating statistical analysis methods for RNA sequencing (RNA-seq experiments is a complex task. Researcher often find themselves having to decide between competing models or assessing the reliability of results obtained with a designated analysis program. Computer simulation has been the most frequently used procedure to verify the adequacy of a model. However, datasets generated by simulations depend on the parameterization and the assumptions of the selected model. Moreover, such datasets may constitute a partial representation of reality as the complexity or RNA-seq data is hard to mimic. We present the use of plasmode datasets to complement the evaluation of statistical models for RNA-seq data. A plasmode is a dataset obtained from experimental data but for which come truth is known. Using a set of simulated scenarios of technical and biological replicates, and public available datasets, we illustrate how to design algorithms to construct plasmodes under different experimental conditions. We contrast results from two types of methods for RNA-seq: i models based on negative binomial distribution (edgeR and DESeq, and ii Gaussian models applied after transformation of data (MAANOVA. Results emphasize the fact that deciding what method to use may be experiment-specific due to the unknown distributions of expression levels. Plasmodes may contribute to choose which method to apply by using a similar pre-existing dataset. The promising results obtained from this approach, emphasize the need of promoting and improving systematic data sharing across the research community to facilitate plasmode building. Although we illustrate the use of plasmode for comparing differential expression analysis models, the flexibility of plasmode construction allows comparing upstream analysis, as normalization procedures or alignment pipelines, as well.
Lightning NOx Statistics Derived by NASA Lightning Nitrogen Oxides Model (LNOM) Data Analyses
Koshak, William; Peterson, Harold
2013-01-01
What is the LNOM? The NASA Marshall Space Flight Center (MSFC) Lightning Nitrogen Oxides Model (LNOM) [Koshak et al., 2009, 2010, 2011; Koshak and Peterson 2011, 2013] analyzes VHF Lightning Mapping Array (LMA) and National Lightning Detection Network(TradeMark) (NLDN) data to estimate the lightning nitrogen oxides (LNOx) produced by individual flashes. Figure 1 provides an overview of LNOM functionality. Benefits of LNOM: (1) Does away with unrealistic "vertical stick" lightning channel models for estimating LNOx; (2) Uses ground-based VHF data that maps out the true channel in space and time to NOx from lightning return stroke; (7) NOx computed for several other lightning discharge processes (based on Cooray et al., 2009 theory): (a) Hot core of stepped leaders and dart leaders, (b) Corona sheath of stepped leader, (c) K-change, (d) Continuing Currents, and (e) M-components; and (8) LNOM statistics (see later) can be used to parameterize LNOx production for regional air quality models (like CMAQ), and for global chemical transport models (like GEOS-Chem).
S-Channel Dark Matter Simplified Models and Unitarity
Englert, Christoph; Spannowsky, Michael
2016-01-01
The ultraviolet structure of $s$-channel mediator dark matter simplified models at hadron colliders is considered. In terms of commonly studied $s$-channel mediator simplified models it is argued that at arbitrarily high energies the perturbative description of dark matter production in high energy scattering at hadron colliders will break down in a number of cases. This is analogous to the well documented breakdown of an EFT description of dark matter collider production. With this in mind, to diagnose whether or not the use of simplified models at the LHC is valid, perturbative unitarity of the scattering amplitude in the processes relevant to LHC dark matter searches is studied. The results are as one would expect: at the LHC and future proton colliders the simplified model descriptions of dark matter production are in general valid. As a result of the general discussion, a simple new class of previously unconsidered `Fermiophobic Scalar' simplified models is proposed, in which a scalar mediator couples to...
A granular-continuum model of channelization in sedimentary layers by sub-surface flow
Yadav, Vikrant; Kudrolli, Arshad
2014-03-01
We discuss experiments where channels form in a quasi-two dimensional bed of consolidated granular particles by fluid flow. A continuum three phase model was developed recently [A. Mahadevan, A.V. Orpe, A. Kudrolli, and L. Mahadevan, EPL, 2012] which shows that channels can develop from small differences in packing in an otherwise homogeneous medium which leads to increased porosity and nonlinear feedback. To build on this model, an erodible porous medium composed of millimeter scale grains and Bentonite clay was prepared in a Hele-Shaw cell. The cohesive strength between the grains is directly proportional to the amount of clay binder. When water is pumped through this porous medium, the binder dissolves and loose beads are advected out of the erodible medium, and an initially uniform flow of water through the porous medium gets localized into channels over time. We will discuss the measured integrated rates of erosion as well as the statistical development of heterogeneity and comparison with the three-phase model as a function of binding strength and consolidation of the medium. Supported by DOE Grant No. DE-FG02-13ER16401.
A stepped leader model for lightning including charge distribution in branched channels
International Nuclear Information System (INIS)
The stepped leader process in negative cloud-to-ground lightning plays a vital role in lightning protection analysis. As lightning discharge usually presents significant branched or tortuous channels, the charge distribution along the branched channels and the stochastic feature of stepped leader propagation were investigated in this paper. The charge density along the leader channel and the charge in the leader tip for each lightning branch were approximated by introducing branch correlation coefficients. In combination with geometric characteristics of natural lightning discharge, a stochastic stepped leader propagation model was presented based on the fractal theory. By comparing simulation results with the statistics of natural lightning discharges, it was found that the fractal dimension of lightning trajectory in simulation was in the range of that observed in nature and the calculation results of electric field at ground level were in good agreement with the measurements of a negative flash, which shows the validity of this proposed model. Furthermore, a new equation to estimate the lightning striking distance to flat ground was suggested based on the present model. The striking distance obtained by this new equation is smaller than the value estimated by previous equations, which indicates that the traditional equations may somewhat overestimate the attractive effect of the ground.
Exploiting linkage disequilibrium in statistical modelling in quantitative genomics
DEFF Research Database (Denmark)
Wang, Lei
the recently proposed antedependence models, which treat neighbouring marker effects as correlated; another approach involves use of haplotype block information derived using the program Beagle. The overall conclusion is that taking LD information into account in genomic prediction models potentially......Alleles at two loci are said to be in linkage disequilibrium (LD) when they are correlated or statistically dependent. Genomic prediction and gene mapping rely on the existence of LD between gentic markers and causul variants of complex traits. In the first part of the thesis, a novel method to...... quantify and visualize local variation in LD along chromosomes in describet, and applied to characterize LD patters at the local and genome-wide scale in three Danish pig breeds. In the second part, different ways of taking LD into account in genomic prediction models are studied. One approach is to use...
Hybrid Perturbation methods based on Statistical Time Series models
San-Juan, Juan Félix; Pérez, Iván; López, Rosario
2016-01-01
In this work we present a new methodology for orbit propagation, the hybrid perturbation theory, based on the combination of an integration method and a prediction technique. The former, which can be a numerical, analytical or semianalytical theory, generates an initial approximation that contains some inaccuracies derived from the fact that, in order to simplify the expressions and subsequent computations, not all the involved forces are taken into account and only low-order terms are considered, not to mention the fact that mathematical models of perturbations not always reproduce physical phenomena with absolute precision. The prediction technique, which can be based on either statistical time series models or computational intelligence methods, is aimed at modelling and reproducing missing dynamics in the previously integrated approximation. This combination results in the precision improvement of conventional numerical, analytical and semianalytical theories for determining the position and velocity of a...
Statistical Modeling of Photovoltaic Reliability Using Accelerated Degradation Techniques (Poster)
Energy Technology Data Exchange (ETDEWEB)
Lee, J.; Elmore, R.; Jones, W.
2011-02-01
We introduce a cutting-edge life-testing technique, accelerated degradation testing (ADT), for PV reliability testing. The ADT technique is a cost-effective and flexible reliability testing method with multiple (MADT) and Step-Stress (SSADT) variants. In an environment with limited resources, including equipment (chambers), test units, and testing time, these techniques can provide statistically rigorous prediction of lifetime and other interesting parameters, such as failure rate, warranty time, mean time to failure, degradation rate, activation energy, acceleration factor, and upper limit level of stress. J-V characterization can be used for degradation data and the generalized Eyring model can be used for the thermal-humidity stress condition. The SSADT model can be constructed based on the cumulative damage model (CEM), which assumes that the remaining test united are failed according to cumulative density function of current stress level regardless of the history on previous stress levels.
Modeling, dependence, classification, united statistical science, many cultures
Parzen, Emanuel
2012-01-01
Breiman (2001) proposed to statisticians awareness of two cultures: 1. Parametric modeling culture, pioneered by R.A.Fisher and Jerzy Neyman; 2. Algorithmic predictive culture, pioneered by machine learning research. Parzen (2001), as a part of discussing Breiman (2001), proposed that researchers be aware of many cultures, including the focus of our research: 3. Nonparametric, quantile based, information theoretic modeling. Our research seeks to unify statistical problem solving in terms of comparison density, copula density, measure of dependence, correlation, information, new measures (called LP score comoments) that apply to long tailed distributions with out finite second order moments. A very important goal is to unify methods for discrete and continuous random variables. We are actively developing these ideas, which have a history of many decades, since Parzen (1979, 1983) and Eubank et al. (1987). Our research extends these methods to modern high dimensional data modeling.
Optimal Fuzzy Model Construction with Statistical Information using Genetic Algorithm
Hossain, Md Amjad; Sarker, Bishnu; Murase, Kazuyuki
2012-01-01
Fuzzy rule based models have a capability to approximate any continuous function to any degree of accuracy on a compact domain. The majority of FLC design process relies on heuristic knowledge of experience operators. In order to make the design process automatic we present a genetic approach to learn fuzzy rules as well as membership function parameters. Moreover, several statistical information criteria such as the Akaike information criterion (AIC), the Bhansali-Downham information criterion (BDIC), and the Schwarz-Rissanen information criterion (SRIC) are used to construct optimal fuzzy models by reducing fuzzy rules. A genetic scheme is used to design Takagi-Sugeno-Kang (TSK) model for identification of the antecedent rule parameters and the identification of the consequent parameters. Computer simulations are presented confirming the performance of the constructed fuzzy logic controller.
Turning statistical physics models into materials design engines.
Miskin, Marc Z; Khaira, Gurdaman; de Pablo, Juan J; Jaeger, Heinrich M
2016-01-01
Despite the success statistical physics has enjoyed at predicting the properties of materials for given parameters, the inverse problem, identifying which material parameters produce given, desired properties, is only beginning to be addressed. Recently, several methods have emerged across disciplines that draw upon optimization and simulation to create computer programs that tailor material responses to specified behaviors. However, so far the methods developed either involve black-box techniques, in which the optimizer operates without explicit knowledge of the material's configuration space, or require carefully tuned algorithms with applicability limited to a narrow subclass of materials. Here we introduce a formalism that can generate optimizers automatically by extending statistical mechanics into the realm of design. The strength of this approach lies in its capability to transform statistical models that describe materials into optimizers to tailor them. By comparing against standard black-box optimization methods, we demonstrate how optimizers generated by this formalism can be faster and more effective, while remaining straightforward to implement. The scope of our approach includes possibilities for solving a variety of complex optimization and design problems concerning materials both in and out of equilibrium. PMID:26684770
How Good Are Statistical Models at Approximating Complex Fitness Landscapes?
du Plessis, Louis; Leventhal, Gabriel E; Bonhoeffer, Sebastian
2016-09-01
Fitness landscapes determine the course of adaptation by constraining and shaping evolutionary trajectories. Knowledge of the structure of a fitness landscape can thus predict evolutionary outcomes. Empirical fitness landscapes, however, have so far only offered limited insight into real-world questions, as the high dimensionality of sequence spaces makes it impossible to exhaustively measure the fitness of all variants of biologically meaningful sequences. We must therefore revert to statistical descriptions of fitness landscapes that are based on a sparse sample of fitness measurements. It remains unclear, however, how much data are required for such statistical descriptions to be useful. Here, we assess the ability of regression models accounting for single and pairwise mutations to correctly approximate a complex quasi-empirical fitness landscape. We compare approximations based on various sampling regimes of an RNA landscape and find that the sampling regime strongly influences the quality of the regression. On the one hand it is generally impossible to generate sufficient samples to achieve a good approximation of the complete fitness landscape, and on the other hand systematic sampling schemes can only provide a good description of the immediate neighborhood of a sequence of interest. Nevertheless, we obtain a remarkably good and unbiased fit to the local landscape when using sequences from a population that has evolved under strong selection. Thus, current statistical methods can provide a good approximation to the landscape of naturally evolving populations. PMID:27189564
Statistical modelling of collocation uncertainty in atmospheric thermodynamic profiles
Fassò, A.; Ignaccolo, R.; Madonna, F.; Demoz, B. B.; Franco-Villoria, M.
2014-06-01
The quantification of measurement uncertainty of atmospheric parameters is a key factor in assessing the uncertainty of global change estimates given by numerical prediction models. One of the critical contributions to the uncertainty budget is related to the collocation mismatch in space and time among observations made at different locations. This is particularly important for vertical atmospheric profiles obtained by radiosondes or lidar. In this paper we propose a statistical modelling approach capable of explaining the relationship between collocation uncertainty and a set of environmental factors, height and distance between imperfectly collocated trajectories. The new statistical approach is based on the heteroskedastic functional regression (HFR) model which extends the standard functional regression approach and allows a natural definition of uncertainty profiles. Along this line, a five-fold decomposition of the total collocation uncertainty is proposed, giving both a profile budget and an integrated column budget. HFR is a data-driven approach valid for any atmospheric parameter, which can be assumed smooth. It is illustrated here by means of the collocation uncertainty analysis of relative humidity from two stations involved in the GCOS reference upper-air network (GRUAN). In this case, 85% of the total collocation uncertainty is ascribed to reducible environmental error, 11% to irreducible environmental error, 3.4% to adjustable bias, 0.1% to sampling error and 0.2% to measurement error.
Statistical modelling applied to the contents of waste drums - 16085
International Nuclear Information System (INIS)
Gamma spectrometry is widely used to determine the radioactive content of waste drums. However, the results of such surveys often result in large numbers of limit-of-detection (LOD) results. In this paper we will show how simple statistical methods can be used to obtain useful information on the average drum activities, even in these unfavourable circumstances. Results from measurements on 60Co, 152Eu, 154Eu activities in drums of waste from decommissioning of the GLEEP reactor suggest that these activities are log-normally distributed with geometric standard deviations (GSD) ranging from 3-4. This statistical model can be used to extract information from 235U, 234mPa and 234Th datasets which show only LOD activity results. In a repository of N drums, each with activity < L, the total activity is clearly < NL. However, we can use the lognormal model to make a much stronger statement about the total waste activity. This model is developed quantitatively in the paper. (authors)
Statistical mechanics of shell models for 2D-Turbulence
Aurell, E; Crisanti, A; Frick, P; Paladin, G; Vulpiani, A
1994-01-01
We study shell models that conserve the analogues of energy and enstrophy, hence designed to mimic fluid turbulence in 2D. The main result is that the observed state is well described as a formal statistical equilibrium, closely analogous to the approach to two-dimensional ideal hydrodynamics of Onsager, Hopf and Lee. In the presence of forcing and dissipation we observe a forward flux of enstrophy and a backward flux of energy. These fluxes can be understood as mean diffusive drifts from a source to two sinks in a system which is close to local equilibrium with Lagrange multipliers (``shell temperatures'') changing slowly with scale. The dimensional predictions on the power spectra from a supposed forward cascade of enstrophy, and from one branch of the formal statistical equilibrium, coincide in these shell models at difference to the corresponding predictions for the Navier-Stokes and Euler equations in 2D. This coincidence have previously led to the mistaken conclusion that shell models exhibit a forward ...
Symmetry Energy Effects in a Statistical Multifragmentation Model
Institute of Scientific and Technical Information of China (English)
ZHANG Lei; GAO Yuan1; ZHANG Hong-Fei; CHEN Xi-Meng; Yu Mei-Ling; LI Jun-Qing
2011-01-01
The symmetry energy effects on the nuclear disintegration mechanisms of the neutron-rich system (A0 = 200, Z0 = 78) are studied in the framework of the statistical multifragmentation model (SMM) within its micro-canonical ensemble. A modified symmetry energy term with consideration of the volume and surface asymmetry is adopted instead of the original invariable value in the standard SMM model. The results indicate that as the volume and surface asymmetries are considered, the neutron-rich system translates to a fission-like process from evaporation earlier than the original standard SMM model at lower excitation energies, and its mass distribution has larger probabilities in the medium-heavy nuclei range so that the system breaks up more averagely. When the excitation energy becomes higher, the volume and surface asymmetry lead to a smaller average multiplicity.%The symmetry energy effects on the nuclear disintegration mechanisms of the neutron-rich system (A0 =200,Z0 =78) are studied in the framework of the statistical multifragmentation model (SMM) within its micro-canonical ensemble.A modified symmetry energy term with consideration of the volume and surface asymmetry is adopted instead of the original invariable value in the standard SMM model.The results indicate that as the volume and surface asymmetries are considered,the neutron-rich system translates to a fission-like process from evaporation earlier than the original standard SMM model at lower excitation energies,and its mass distribution has larger probabilities in the medium-heavy nuclei range so that the system breaks up more averagely.When the excitation energy becomes higher,the volume and surface asymmetry lead to a smaller average multiplicity.
CHRiSM: CHance Rules induce Statistical Models
Sneyers, Jon; Meert, Wannes; Vennekens, Joost
2009-01-01
A new probabilistic-logic formalism, called CHRiSM, is introduced. CHRiSM is based on a combination of CHR and PRISM. It can be used for high-level rapid prototyping of complex statistical models by means of chance rules. The underlying PRISM system can then be used for several probabilistic inference tasks, including parameter learning. We describe a source-to-source transformation from CHRiSM rules to PRISM, via CHR(PRISM). Finally we discuss the relation between CHRiSM and probab...
Statistical properties of a two-stage model of carcinogenesis.
Portier, C J
1987-01-01
Some of the statistical properties of a simple two-stage model of carcinogenesis are explored. The implications of additive treatment effects versus independent treatment effects on the shape of the dose-response curve are considered. Response that is low-dose linear results in the cases where the mutation rates are affected by dose or in the cases where treatment changes the birth rate/death rate of initiated cells in an additive fashion. Independent treatment effects lead to non-low-dose li...
Preprocessing of Screening Mammograms Based on Local Statistical Models
Czech Academy of Sciences Publication Activity Database
Grim, Jiří
Barcelona: ACM, 2011, s. 1-5. ISBN 978-1-4503-0913-4. [4th International Symposium on Applied Sciences in Biomedical and Communication Technologies, ISABEL 2011, Barcelona. Barcelona (ES), 25.10.2011-29.10.2011] R&D Projects: GA MŠk 1M0572 Grant ostatní: GA MŠk(CZ) 2C06019 Institutional research plan: CEZ:AV0Z10750506 Keywords : Image processing software * Medical Sciences * Health Subject RIV: IN - Informatics, Computer Science http://library.utia.cas.cz/separaty/2011/RO/grim-preprocessing of screening mammograms based on local statistical models.pdf
Thermodynamical interpretation of statistical semi-inclusive model
International Nuclear Information System (INIS)
A simple picture of high-energy hadron-hadron scattering, consisting of a slight deceleration of the incoming particles followed by thermalization, allows to account for the general features of multihadron production and to derive the main parameters of the empirically developed semi-inclusive statistical model. The dependence exp(-p2T/(P2T)) is expected for pT pion distribution. The picture agrees with the universal properties of hadron production in p-p, deep inelastic and electron-positron scattering
A Quantal Response Equilibrium Model of Order Statistic Games
Yi, Kang-Oh
1999-01-01
This paper applies quantal response equilibrium (QRE) models (McKelvey and Palfrey, Games and Economic Behavior 10 (1995), 6-38) to a wide class of symmetric coordination games in which each player's best response is determined by an order statistic of all players' decisions, as in the classic experiments of Van Huyck, Battalio, and Beil (American Economic Review 80 (1990), 234-248; Quarterly Journal of Economics 106 (1991), 885-910), but players have a bounded continuum of decisions, which a...
International Nuclear Information System (INIS)
Results from the zonal model indicate quite reasonable agreement with observation in terms of the parameters and processes that influence the radiation and energy balance calculations. The model produces zonal statistics similar to those from general circulation models, and has also been shown to produce similar responses in sensitivity studies. Further studies of model performance are planned, including: comparison with July data; comparison of temperature and moisture transport and wind fields for winter and summer months; and a tabulation of atmospheric energetics. Based on these preliminary performance studies, however, it appears that the zonal model can be used in conjunction with more complex models to help unravel the problems of understanding the processes governing present climate and climate change. As can be seen in the subsequent paper on model sensitivity studies, in addition to reduced cost of computation, the zonal model facilitates analysis of feedback mechanisms and simplifies analysis of the interactions between processes
2D numerical modelling of meandering channel formation
Indian Academy of Sciences (India)
Y Xiao; G Zhou; F S Yang
2016-03-01
A 2D depth-averaged model for hydrodynamic sediment transport and river morphological adjustment was established. The sediment transport submodel takes into account the influence of non-uniform sediment with bed surface armoring and considers the impact of secondary flow in the direction of bed-loadtransport and transverse slope of the river bed. The bank erosion submodel incorporates a simple simulation method for updating bank geometry during either degradational or aggradational bed evolution. Comparison of the results obtained by the extended model with experimental and field data, and numericalpredictions validate that the proposed model can simulate grain sorting in river bends and duplicate the characteristics of meandering river and its development. The results illustrate that by using its control factors, the improved numerical model can be applied to simulate channel evolution under differentscenarios and improve understanding of patterning processes.
2D numerical modelling of meandering channel formation
XIAO, Y.; ZHOU, G.; YANG, F. S.
2016-03-01
A 2D depth-averaged model for hydrodynamic sediment transport and river morphological adjustment was established. The sediment transport submodel takes into account the influence of non-uniform sediment with bed surface armoring and considers the impact of secondary flow in the direction of bed-load transport and transverse slope of the river bed. The bank erosion submodel incorporates a simple simulation method for updating bank geometry during either degradational or aggradational bed evolution. Comparison of the results obtained by the extended model with experimental and field data, and numerical predictions validate that the proposed model can simulate grain sorting in river bends and duplicate the characteristics of meandering river and its development. The results illustrate that by using its control factors, the improved numerical model can be applied to simulate channel evolution under different scenarios and improve understanding of patterning processes.
Modeling negative ion defect migration through the gramicidin A channel.
Nemukhin, Alexander V; Kaliman, Ilya A; Moskovsky, Alexander A
2009-08-01
The results of potential of mean force (PMF) calculations for the distinct stages of proton conduction through the gramicidin A channel, including proton migration, reorientation of the water file and negative ion defect migration, are presented. The negative ion defect migration mechanism was hypothesized in experimental studies but was not considered previously in molecular dynamics simulations. The model system consisted of the peptide chains constructed on the base of the structure PDBID:1JNO, the inner file of nine water molecules and external clusters of water molecules placed at both ends of the channel. Potential energy functions were computed with the CHARMM/PM6/TIP3P parameters. The results obtained for proton migration and water file reorientation are basically consistent with those reported previously by Pómès and Roux (Biophys J 82:2304, 2002) within the similar approach. For the newly considered mechanism of negative ion defect migration from the channel center to the end of the water file we obtain the energy 3.8 kcal mol(-1) which is not considerably different from the activation energy of water reorientation, 5.4 kcal mol(-1). Therefore this mechanism may principally compete for the rate-limiting step in proton conduction in gramicidin. PMID:19198898
Modelling of flow and heat transfer in PV cooling channels
Energy Technology Data Exchange (ETDEWEB)
Diarra, D.C.; Harrison, S.J. [Queen' s Univ., Kingston, ON (Canada). Dept. of Mechanical and Materials Engineering Solar Calorimetry Lab; Akuffo, F.O. [Kwame Nkrumah Univ. of Science and Technology, Kumasi (Ghana). Dept. of Mechanical Engineering
2005-07-01
Under sunny conditions, the temperature of photovoltaic (PV) modules can be 20 to 30 degrees C above the ambient air temperature. This affects the performance of PV modules, particularly in regions with hot climates. For silicon solar cells, the maximum power decreases between 0.4 and 0.5 per cent for every degree C of temperature increase above a reference value. In an effort to address this issue, this experimental and numerical study examined an active PV panel evaporative cooling scheme that is typically used in hot arid climates. The cooling system circulated cool air behind the PV modules, extracting heat and lowering solar cell temperature. A fluid dynamic and thermal model of the combined system was developed using the EES program in order to study the configuration of the cooling channel and the characteristics of the cooling flow. Heat transfer and flow characteristics in the cooling channel were then calculated along with pressure drop and fan power associated with the air-circulation. The net power output was also calculated. The objective was to design a cost efficient cooling system and to optimize its flow and pressure drop in order to maximize power output. The study demonstrated how the performance of the PV panel is influenced by the geometry of the cooling channel, the inlet air temperature and the air flow rate. 2 refs.
Statistical shape model-based segmentation of brain MRI images.
Bailleul, Jonathan; Ruan, Su; Constans, Jean-Marc
2007-01-01
We propose a segmentation method that automatically delineates structures contours from 3D brain MRI images using a statistical shape model. We automatically build this 3D Point Distribution Model (PDM) in applying a Minimum Description Length (MDL) annotation to a training set of shapes, obtained by registration of a 3D anatomical atlas over a set of patients brain MRIs. Delineation of any structure from a new MRI image is first initialized by such registration. Then, delineation is achieved in iterating two consecutive steps until the 3D contour reaches idempotence. The first step consists in applying an intensity model to the latest shape position so as to formulate a closer guess: our model requires far less priors than standard model in aiming at direct interpretation rather than compliance to learned contexts. The second step consists in enforcing shape constraints onto previous guess so as to remove all bias induced by artifacts or low contrast on current MRI. For this, we infer the closest shape instance from the PDM shape space using a new estimation method which accuracy is significantly improved by a huge increase in the model resolution and by a depth-search in the parameter space. The delineation results we obtained are very encouraging and show the interest of the proposed framework. PMID:18003193
Ansari, Imran Shafique
2010-12-01
The introduction of new schemes that are based on the communication among nodes has motivated the use of composite fading models due to the fact that the nodes experience different multipath fading and shadowing statistics, which subsequently determines the required statistics for the performance analysis of different transceivers. The end-to-end signal-to-noise-ratio (SNR) statistics plays an essential role in the determination of the performance of cascaded digital communication systems. In this thesis, a closed-form expression for the probability density function (PDF) of the end-end SNR for independent but not necessarily identically distributed (i.n.i.d.) cascaded generalized-K (GK) composite fading channels is derived. The developed PDF expression in terms of the Meijer-G function allows the derivation of subsequent performance metrics, applicable to different modulation schemes, including outage probability, bit error rate for coherent as well as non-coherent systems, and average channel capacity that provides insights into the performance of a digital communication system operating in N cascaded GK composite fading environment. Another line of research that was motivated by the introduction of composite fading channels is the error performance. Error performance is one of the main performance measures and derivation of its closed-form expression has proved to be quite involved for certain systems. Hence, in this thesis, a unified closed-form expression, applicable to different binary modulation schemes, for the bit error rate of dual-branch selection diversity based systems undergoing i.n.i.d. GK fading is derived in terms of the extended generalized bivariate Meijer G-function.
Statistical Agent Based Modelization of the Phenomenon of Drug Abuse
di Clemente, Riccardo; Pietronero, Luciano
2012-07-01
We introduce a statistical agent based model to describe the phenomenon of drug abuse and its dynamical evolution at the individual and global level. The agents are heterogeneous with respect to their intrinsic inclination to drugs, to their budget attitude and social environment. The various levels of drug use were inspired by the professional description of the phenomenon and this permits a direct comparison with all available data. We show that certain elements have a great importance to start the use of drugs, for example the rare events in the personal experiences which permit to overcame the barrier of drug use occasionally. The analysis of how the system reacts to perturbations is very important to understand its key elements and it provides strategies for effective policy making. The present model represents the first step of a realistic description of this phenomenon and can be easily generalized in various directions.
Statistical Agent Based Modelization of the Phenomenon of Drug Abuse
Di Clemente, Riccardo; 10.1038/srep00532
2012-01-01
We introduce a statistical agent based model to describe the phenomenon of drug abuse and its dynamical evolution at the individual and global level. The agents are heterogeneous with respect to their intrinsic inclination to drugs, to their budget attitude and social environment. The various levels of drug use were inspired by the professional description of the phenomenon and this permits a direct comparison with all available data. We show that certain elements have a great importance to start the use of drugs, for example the rare events in the personal experiences which permit to overcame the barrier of drug use occasionally. The analysis of how the system reacts to perturbations is very important to understand its key elements and it provides strategies for effective policy making. The present model represents the first step of a realistic description of this phenomenon and can be easily generalized in various directions.
Role of scaling in the statistical modelling of finance
Indian Academy of Sciences (India)
Attilio L Stella; Fulvio Baldovin
2008-08-01
Modelling the evolution of a financial index as a stochastic process is a problem awaiting a full, satisfactory solution since it was first formulated by Bachelier in 1900. Here it is shown that the scaling with time of the return probability density function sampled from the historical series suggests a successful model. The resulting stochastic process is a heteroskedastic, non-Markovian martingale, which can be used to simulate index evolution on the basis of an autoregressive strategy. Results are fully consistent with volatility clustering and with the multiscaling properties of the return distribution. The idea of basing the process construction on scaling, and the construction itself, are closely inspired by the probabilistic renormalization group approach of statistical mechanics and by a recent formulation of the central limit theorem for sums of strongly correlated random variables.
Isospin dependence of nuclear multifragmentation in statistical model
Institute of Scientific and Technical Information of China (English)
ZHANG Lei; XIE Dong-Zhu; ZHANG Yan-Ping; GAO Yuan
2011-01-01
The evolution of nuclear disintegration mechanisms with increasing excitation energy, from com- pound nucleus to multifragmentation, has been studied by using the Statistical Multifragmentation Model (SMM) within a micro-canonical ensemble. We discuss the observable characteristics as functions of excitation energy in multifragmentation, concentrating on the isospin dependence of the model in its decaying mechanism and break-up fragment configuration by comparing the A = 200, Z = 78 and A = 200, Z = 100 systems. The calculations indicate that the neutron-rich system (Z = 78) translates to a fission-like process from evaporation later than the symmetric nucleus at a lower excitation energy, but gets a larger average multiplicity as the excitation energy increases above 1.0 MeV/u.
Statistical analysis and model of spread F occurrence in China
Institute of Scientific and Technical Information of China (English)
无
2010-01-01
The spread F data obtained over Lanzhou (36.1°N,103.9°E),Chongqing (29.5°N,106.4°E) and Haikou (20.0°N,110.3°E) of China during the period from 1978 to 1997 are used to analyze the occurrence characteristics.The statistical results show that the post midnight spread F occurrence is maximum during the summer solstice months of the lower solar activity period,while post sunset spread F is dominant in equinoxes of higher solar activity period over Haikou station.Over Chongqing and Lanzhou stations,spread F mostly occurs at post midnight and relates negatively with solar activity.Using regression method and Fourier expansion,the preliminary single-station model of spread F occurrence is established and the accuracy of the model is evaluated.
Texture Oriented Image Inpainting based on Local Statistical Model
Czech Academy of Sciences Publication Activity Database
Grim, Jiří; Somol, Petr; Pudil, Pavel; Míková, I.; Malec, M.
Calgary : ACTA Press, 2008 - (Cristea, P.), s. 15-20 [10th IASTED Conf. on Signal & Image Processing, SIP 2008. Kailua-Kona, HI (US), 18.08.2008-20.08.2008] R&D Projects: GA MŠk 1M0572; GA ČR GA102/08/0593; GA ČR GA102/07/1594 Grant ostatní: GA MŠk(CZ) 2C06019 Institutional research plan: CEZ:AV0Z10750506 Keywords : Image Restoration * Image Inpainting * Color Texture Prediction * Local Texture Model * Gaussian Mixtures * EM Algorithm Subject RIV: BD - Theory of Information http://library.utia.cas.cz/separaty/2008/RO/grim-texture oriented image inpainting based on local statistical model.pdf
Helicity statistics in homogeneous and isotropic turbulence and turbulence models
Sahoo, Ganapati; Biferale, Luca
2016-01-01
We study the statistical properties of helicity in direct numerical simulations of fully developed homogeneous and isotropic turbulence and in a class of turbulence shell models. We consider correlation functions based on combinations of vorticity and velocity increments that are not invariant under mirror symmetry. We also study the scaling properties of high-order structure functions based on the moments of the velocity increments projected on a subset of modes with either positive or negative helicity (chirality). We show that mirror symmetry is recovered at small-scales, i.e. chiral terms are always subleading and they are well captured by a dimensional argument plus a small anomalous correction. We confirm these findings with numerical study of helical shell models at high Reynolds numbers.
OPTIMAL FUZZY MODEL CONSTRUCTION WITH STATISTICAL INFORMATION USING GENETIC ALGORITHM
Directory of Open Access Journals (Sweden)
Bishnu Sarker
2012-01-01
Full Text Available Fuzzy rule based models have a capability to approximate any continuous function to any degree ofaccuracy on a compact domain. The majority of FLC design process relies on heuristic knowledge ofexperience operators. In order to make the design process automatic we present a genetic approach tolearn fuzzy rules as well as membership function parameters. Moreover, several statistical informationcriteria such as the Akaike information criterion (AIC, the Bhansali-Downham information criterion(BDIC, and the Schwarz-Rissanen information criterion (SRIC are used to construct optimal fuzzymodels by reducing fuzzy rules. A genetic scheme is used to design Takagi-Sugeno-Kang (TSK model foridentification of the antecedent rule parameters and the identification of the consequent parameters.Computer simulations are presented confirming the performance of the constructed fuzzy logiccontroller.
Optical wireless communications system and channel modelling with Matlab
Ghassemlooy, Z
2012-01-01
Detailing a systems approach, Optical Wireless Communications: System and Channel Modelling with MATLAB(R), is a self-contained volume that concisely and comprehensively covers the theory and technology of optical wireless communications systems (OWC) in a way that is suitable for undergraduate and graduate-level students, as well as researchers and professional engineers. Incorporating MATLAB(R) throughout, the authors highlight past and current research activities to illustrate optical sources, transmitters, detectors, receivers, and other devices used in optical wireless communications. The
Propagation model for the Land Mobile Satellite channel in urban environments
Sforza, M.; Dibernardo, G.; Cioni, R.
1993-01-01
This paper presents the major characteristics of a simulation package capable of performing a complete narrow and wideband analysis of the mobile satellite communication channel in urban environments for any given orbital configuration. The wavelength-to-average urban geometrical dimension ratio has required the use of the Geometrical Theory of Diffraction (GTD). For the RF frequency range, the model has been designed to be (1 up to 60 GHz) extended to include effects of non-perfect conductivity and surface roughness. Taking advantage of the inherent capabilities of such a high frequency method, we are able to provide a complete description of the electromagnetic field at the mobile terminal. Using the information made available at the ray-tracer and GTD solver outputs, the Land Mobile Satellite (LMS) urban model can also give a detailed description of the communication channel in terms of power delay profiles, Doppler spectra, channel scattering functions, and so forth. Statistical data, e.g. cumulative distribution functions, level crossing rates or distributions of fades are also provided. The user can access the simulation tool through a Design-CAD user-friendly interface by means of which she can effectively design her own urban layout and run consequently all the envisaged routines. The software is optimized in its execution time so that numerous runs can be achieved in a considerably short time.
Coupled channels optical model potential for rare earth nuclei
International Nuclear Information System (INIS)
The global spherical optical model by Koning and Delaroche is generalized to enable its use in coupled-channel calculations on well deformed nuclei in the rare-earth region. The generalization consists in adding the coupling of the ground state rotational band, deforming the potential by introducing appropriate quadrupole and hexadecupole deformations and correcting the optical model potential radius to preserve the volume integral of the spherical optical potential. We choose isotopes of three rare-earth elements (W, Ho, Gd), which are known to be nearly perfect rotors, to perform a consistency test of our conjecture on integrated cross sections as well as on angular distributions for elastic and inelastic neutron scattering. The only additional input are experimentally determined deformations, which we employ without any adjustments. The results are clearly superior compared to the spherical optical model calculations with dramatic improvement at low incident energies. (author)
Physics based modelling of short-channel nanowire MOSFET
Energy Technology Data Exchange (ETDEWEB)
Boerli, H; Kolberg, S; Fjeldly, T A [Department of Electronics and Telecommunication, Norwegian University of Science and Technology, and UniK, University Graduate Center, N-2021 Kjeller (Norway)], E-mail: hborli@unik.no, E-mail: kolberg@unik.no, E-mail: torfj@unik.no
2008-03-15
A modelling framework for short channel nanowire (NW) MOSFETs that covers a wide range of operating conditions is presented. The device electrostatics in the subthreshold regime is dominated by the inter-electrode capacitive coupling, which, in the case of double gate (DG) devices, is analyzed in terms of conformal mapping techniques. Previously, we have shown that these results can also be successfully applied to the NW MOSFET, by performing an appropriate mapping to compensate for the difference in gate control between the two devices. Near and above threshold, the influence of the electronic charge is taken into account in a precise, self-consistent manner by combining suitable model expressions with Poisson's equation. The models are verified by comparison with numerical device simulations.
A statistics-based pitch contour model for Mandarin speech.
Chen, Sin-Horng; Lai, Wen-Hsing; Wang, Yih-Ru
2005-02-01
A statistics-based syllable pitch contour model for Mandarin speech is proposed. This approach takes the mean and the shape of a syllable log-pitch contour as two basic modeling units and considers several affecting factors that contribute to their variations. The affecting factors include the speaker, prosodic state (which essentially represents the high-level linguistic components of F0 and will be explained more clearly in Sec. I), tone, and initial and final syllable classes. The parameters of the two modeling units were automatically estimated using the expectation-maximization (EM) algorithm. Experimental results showed that the root mean squared errors (RMSEs) obtained in the closed and open tests in the reconstructed pitch period were 0.362 and 0.373 ms, respectively. This model provides a way to separate the effects of several major factors. All of the inferred values of the affecting factors were in close agreement with our prior linguistic knowledge. It also gives a quantitative and more complete description of the coarticulation effect of neighboring tones rather than conventional qualitative descriptions of the tone sandhi rules. In addition, the model can provide useful cues to determine the prosodic phrase boundaries, including those occurring at intersyllable locations, with or without punctuation marks. PMID:15759710
Modeling Insurgent Dynamics Including Heterogeneity. A Statistical Physics Approach
Johnson, Neil F.; Manrique, Pedro; Hui, Pak Ming
2013-05-01
Despite the myriad complexities inherent in human conflict, a common pattern has been identified across a wide range of modern insurgencies and terrorist campaigns involving the severity of individual events—namely an approximate power-law x - α with exponent α≈2.5. We recently proposed a simple toy model to explain this finding, built around the reported loose and transient nature of operational cells of insurgents or terrorists. Although it reproduces the 2.5 power-law, this toy model assumes every actor is identical. Here we generalize this toy model to incorporate individual heterogeneity while retaining the model's analytic solvability. In the case of kinship or team rules guiding the cell dynamics, we find that this 2.5 analytic result persists—however an interesting new phase transition emerges whereby this cell distribution undergoes a transition to a phase in which the individuals become isolated and hence all the cells have spontaneously disintegrated. Apart from extending our understanding of the empirical 2.5 result for insurgencies and terrorism, this work illustrates how other statistical physics models of human grouping might usefully be generalized in order to explore the effect of diverse human social, cultural or behavioral traits.
Langousis, Andreas; Mamalakis, Antonios; Deidda, Roberto; Marrocu, Marino
2016-01-01
To improve the level skill of climate models (CMs) in reproducing the statistics of daily rainfall at a basin level, two types of statistical approaches have been suggested. One is statistical correction of CM rainfall outputs based on historical series of precipitation. The other, usually referred to as statistical rainfall downscaling, is the use of stochastic models to conditionally simulate rainfall series, based on large-scale atmospheric forcing from CMs. While promising, the latter approach attracted reduced attention in recent years, since the developed downscaling schemes involved complex weather identification procedures, while demonstrating limited success in reproducing several statistical features of rainfall. In a recent effort, Langousis and Kaleris () developed a statistical framework for simulation of daily rainfall intensities conditional on upper-air variables, which is simpler to implement and more accurately reproduces several statistical properties of actual rainfall records. Here we study the relative performance of: (a) direct statistical correction of CM rainfall outputs using nonparametric distribution mapping, and (b) the statistical downscaling scheme of Langousis and Kaleris (), in reproducing the historical rainfall statistics, including rainfall extremes, at a regional level. This is done for an intermediate-sized catchment in Italy, i.e., the Flumendosa catchment, using rainfall and atmospheric data from four CMs of the ENSEMBLES project. The obtained results are promising, since the proposed downscaling scheme is more accurate and robust in reproducing a number of historical rainfall statistics, independent of the CM used and the characteristics of the calibration period. This is particularly the case for yearly rainfall maxima.
Flashover of a vacuum-insulator interface: A statistical model
Stygar, W. A.; Ives, H. C.; Wagoner, T. C.; Lott, J. A.; Anaya, V.; Harjes, H. C.; Corley, J. P.; Shoup, R. W.; Fehl, D. L.; Mowrer, G. R.; Wallace, Z. R.; Anderson, R. A.; Boyes, J. D.; Douglas, J. W.; Horry, M. L.; Jaramillo, T. F.; Johnson, D. L.; Long, F. W.; Martin, T. H.; McDaniel, D. H.; Milton, O.; Mostrom, M. A.; Muirhead, D. A.; Mulville, T. D.; Ramirez, J. J.; Ramirez, L. E.; Romero, T. M.; Seamen, J. F.; Smith, J. W.; Speas, C. S.; Spielman, R. B.; Struve, K. W.; Vogtlin, G. E.; Walsh, D. E.; Walsh, E. D.; Walsh, M. D.; Yamamoto, O.
2004-07-01
We have developed a statistical model for the flashover of a 45° vacuum-insulator interface (such as would be found in an accelerator) subject to a pulsed electric field. The model assumes that the initiation of a flashover plasma is a stochastic process, that the characteristic statistical component of the flashover delay time is much greater than the plasma formative time, and that the average rate at which flashovers occur is a power-law function of the instantaneous value of the electric field. Under these conditions, we find that the flashover probability is given by 1-exp(-EβpteffC/kβ), where Ep is the peak value in time of the spatially averaged electric field E(t), teff≡∫[E(t)/Ep]βdt is the effective pulse width, C is the insulator circumference, k∝exp(λ/d), and β and λ are constants. We define E(t) as V(t)/d, where V(t) is the voltage across the insulator and d is the insulator thickness. Since the model assumes that flashovers occur at random azimuthal locations along the insulator, it does not apply to systems that have a significant defect, i.e., a location contaminated with debris or compromised by an imperfection at which flashovers repeatedly take place, and which prevents a random spatial distribution. The model is consistent with flashover measurements to within 7% for pulse widths between 0.5 ns and 10 μs, and to within a factor of 2 between 0.5 ns and 90 s (a span of over 11 orders of magnitude). For these measurements, Ep ranges from 64 to 651 kV/cm, d from 0.50 to 4.32 cm, and C from 4.96 to 95.74 cm. The model is significantly more accurate, and is valid over a wider range of parameters, than the J. C. Martin flashover relation that has been in use since 1971 [J. C. Martin on Pulsed Power, edited by T. H. Martin, A. H. Guenther, and M. Kristiansen (Plenum, New York, 1996)]. We have generalized the statistical model to estimate the total-flashover probability of an insulator stack (i.e., an assembly of insulator-electrode systems
Over-sampling basis expansion model aided channel estimation for OFDM systems with ICI
Institute of Scientific and Technical Information of China (English)
无
2008-01-01
The rapid variation of channel can induce the intercarrier interference in orthogonal frequency-division multiplexing (OFDM) systems. Intercarrier interference will significantly increase the difficulty of OFDM channel estimation because too many channel coefficients need be estimated. In this article, a novel channel estimator is proposed to resolve the above problem. This estimator consists of two parts: the channel parameter estimation unit (CPEU), which is used to estimate the number of channel taps and the multipath time delays, and the channel coefficient estimation unit (CCEU), which is used to estimate the channel coefficients by using the estimated channel parameters provided by CPEU. In CCEU, the over-sampling basis expansion model is resorted to solve the problem that a large number of channel coefficients need to be estimated. Finally, simulation results are given to scale the performance of the proposed scheme.
A Statistical Model for Regional Tornado Climate Studies.
Directory of Open Access Journals (Sweden)
Thomas H Jagger
Full Text Available Tornado reports are locally rare, often clustered, and of variable quality making it difficult to use them directly to describe regional tornado climatology. Here a statistical model is demonstrated that overcomes some of these difficulties and produces a smoothed regional-scale climatology of tornado occurrences. The model is applied to data aggregated at the level of counties. These data include annual population, annual tornado counts and an index of terrain roughness. The model has a term to capture the smoothed frequency relative to the state average. The model is used to examine whether terrain roughness is related to tornado frequency and whether there are differences in tornado activity by County Warning Area (CWA. A key finding is that tornado reports increase by 13% for a two-fold increase in population across Kansas after accounting for improvements in rating procedures. Independent of this relationship, tornadoes have been increasing at an annual rate of 1.9%. Another finding is the pattern of correlated residuals showing more Kansas tornadoes in a corridor of counties running roughly north to south across the west central part of the state consistent with the dryline climatology. The model is significantly improved by adding terrain roughness. The effect amounts to an 18% reduction in the number of tornadoes for every ten meter increase in elevation standard deviation. The model indicates that tornadoes are 51% more likely to occur in counties served by the CWAs of DDC and GID than elsewhere in the state. Flexibility of the model is illustrated by fitting it to data from Illinois, Mississippi, South Dakota, and Ohio.
Emerging Trends and Statistical Analysis in Computational Modeling in Agriculture
Directory of Open Access Journals (Sweden)
Sunil Kumar
2015-03-01
Full Text Available In this paper the authors have tried to describe emerging trend in computational modelling used in the sphere of agriculture. Agricultural computational modelling with the use of intelligence techniques for computing the agricultural output by providing minimum input data to lessen the time through cutting down the multi locational field trials and also the labours and other inputs is getting momentum. Development of locally suitable integrated farming systems (IFS is the utmost need of the day, particularly in India where about 95% farms are under small and marginal holding size. Optimization of the size and number of the various enterprises to the desired IFS model for a particular set of agro-climate is essential components of the research to sustain the agricultural productivity for not only filling the stomach of the bourgeoning population of the country, but also to enhance the nutritional security and farms return for quality life. Review of literature pertaining to emerging trends in computational modelling applied in field of agriculture is done and described below for the purpose of understanding its trends mechanism behavior and its applications. Computational modelling is increasingly effective for designing and analysis of the system. Computa-tional modelling is an important tool to analyses the effect of different scenarios of climate and management options on the farming systems and its interaction among themselves. Further, authors have also highlighted the applications of computational modeling in integrated farming system, crops, weather, soil, climate, horticulture and statistical used in agriculture which can show the path to the agriculture researcher and rural farming community to replace some of the traditional techniques.
Comparison of statistical model calculations for stable isotope neutron capture
Beard, M.; Uberseder, E.; Crowter, R.; Wiescher, M.
2014-09-01
It is a well-observed result that different nuclear input models sensitively affect Hauser-Feshbach (HF) cross-section calculations. Less well-known, however, are the effects on calculations originating from nonmodel aspects, such as experimental data truncation and transmission function energy binning, as well as code-dependent aspects, such as the definition of level-density matching energy and the inclusion of shell correction terms in the level-density parameter. To investigate these aspects, Maxwellian-averaged neutron capture cross sections (MACS) at 30 keV have been calculated using the well-established statistical Hauser-Feshbach model codes talys and non-smoker for approximately 340 nuclei. For the same nuclei, MACS predictions have also been obtained using two new HF codes, cigar and sapphire. Details of these two codes, which have been developed to contain an overlapping set of identically implemented nuclear physics input models, are presented. It is generally accepted that HF calculations are valid to within a factor of 3. It was found that this factor is dependent on both model and nonmodel details, such as the coarseness of the transmission function energy binning and data truncation, as well as variances in details regarding the implementation of level-density parameter, backshift, matching energy, and giant dipole strength function parameters.
Linear mixed models a practical guide using statistical software
West, Brady T; Galecki, Andrzej T
2014-01-01
Highly recommended by JASA, Technometrics, and other journals, the first edition of this bestseller showed how to easily perform complex linear mixed model (LMM) analyses via a variety of software programs. Linear Mixed Models: A Practical Guide Using Statistical Software, Second Edition continues to lead readers step by step through the process of fitting LMMs. This second edition covers additional topics on the application of LMMs that are valuable for data analysts in all fields. It also updates the case studies using the latest versions of the software procedures and provides up-to-date information on the options and features of the software procedures available for fitting LMMs in SAS, SPSS, Stata, R/S-plus, and HLM.New to the Second Edition A new chapter on models with crossed random effects that uses a case study to illustrate software procedures capable of fitting these models Power analysis methods for longitudinal and clustered study designs, including software options for power analyses and suggest...
Glass viscosity calculation based on a global statistical modeling approach
International Nuclear Information System (INIS)
A global statistical glass viscosity model was developed for predicting the complete viscosity curve, based on more than 2200 composition-property data of silicate glasses from the scientific literature, including soda-lime-silica container and float glasses, TV panel glasses, borosilicate fiber wool and E type glasses, low expansion borosilicate glasses, glasses for nuclear waste vitrification, lead crystal glasses, binary alkali silicates, and various further compositions from over half a century. It is shown that within a measurement series from a specific laboratory the reported viscosity values are often over-estimated at higher temperatures due to alkali and boron oxide evaporation during the measurement and glass preparation, including data by Lakatos et al. (1972) and the recently published High temperature glass melt property database for process modeling by Seward et al. (2005). Similarly, in the glass transition range many experimental data of borosilicate glasses are reported too high due to phase separation effects. The developed global model corrects those errors. The model standard error was 9-17 C, with R2 = 0.985-0.989. The prediction 95% confidence interval for glass in mass production largely depends on the glass composition of interest, the composition uncertainty, and the viscosity level. New insights in the mixed-alkali effect are provided
Glass viscosity calculation based on a global statistical modelling approach
Energy Technology Data Exchange (ETDEWEB)
Fluegel, Alex
2007-02-01
A global statistical glass viscosity model was developed for predicting the complete viscosity curve, based on more than 2200 composition-property data of silicate glasses from the scientific literature, including soda-lime-silica container and float glasses, TV panel glasses, borosilicate fiber wool and E type glasses, low expansion borosilicate glasses, glasses for nuclear waste vitrification, lead crystal glasses, binary alkali silicates, and various further compositions from over half a century. It is shown that within a measurement series from a specific laboratory the reported viscosity values are often over-estimated at higher temperatures due to alkali and boron oxide evaporation during the measurement and glass preparation, including data by Lakatos et al. (1972) and the recently published High temperature glass melt property database for process modeling by Seward et al. (2005). Similarly, in the glass transition range many experimental data of borosilicate glasses are reported too high due to phase separation effects. The developed global model corrects those errors. The model standard error was 9-17°C, with R^2 = 0.985-0.989. The prediction 95% confidence interval for glass in mass production largely depends on the glass composition of interest, the composition uncertainty, and the viscosity level. New insights in the mixed-alkali effect are provided.
Statistical mechanics of learning orthogonal signals for general covariance models
International Nuclear Information System (INIS)
Statistical mechanics techniques have proved to be useful tools in quantifying the accuracy with which signal vectors are extracted from experimental data. However, analysis has previously been limited to specific model forms for the population covariance C, which may be inappropriate for real world data sets. In this paper we obtain new statistical mechanical results for a general population covariance matrix C. For data sets consisting of p sample points in RN we use the replica method to study the accuracy of orthogonal signal vectors estimated from the sample data. In the asymptotic limit of N,p→∞ at fixed α = p/N, we derive analytical results for the signal direction learning curves. In the asymptotic limit the learning curves follow a single universal form, each displaying a retarded learning transition. An explicit formula for the location of the retarded learning transition is obtained and we find marked variation in the location of the retarded learning transition dependent on the distribution of population covariance eigenvalues. The results of the replica analysis are confirmed against simulation
STATISTICAL MECHANICS MODELING OF MESOSCALE DEFORMATION IN METALS
Energy Technology Data Exchange (ETDEWEB)
Anter El-Azab
2013-04-08
The research under this project focused on a theoretical and computational modeling of dislocation dynamics of mesoscale deformation of metal single crystals. Specifically, the work aimed to implement a continuum statistical theory of dislocations to understand strain hardening and cell structure formation under monotonic loading. These aspects of crystal deformation are manifestations of the evolution of the underlying dislocation system under mechanical loading. The project had three research tasks: 1) Investigating the statistical characteristics of dislocation systems in deformed crystals. 2) Formulating kinetic equations of dislocations and coupling these kinetics equations and crystal mechanics. 3) Computational solution of coupled crystal mechanics and dislocation kinetics. Comparison of dislocation dynamics predictions with experimental results in the area of statistical properties of dislocations and their field was also a part of the proposed effort. In the first research task, the dislocation dynamics simulation method was used to investigate the spatial, orientation, velocity, and temporal statistics of dynamical dislocation systems, and on the use of the results from this investigation to complete the kinetic description of dislocations. The second task focused on completing the formulation of a kinetic theory of dislocations that respects the discrete nature of crystallographic slip and the physics of dislocation motion and dislocation interaction in the crystal. Part of this effort also targeted the theoretical basis for establishing the connection between discrete and continuum representation of dislocations and the analysis of discrete dislocation simulation results within the continuum framework. This part of the research enables the enrichment of the kinetic description with information representing the discrete dislocation systems behavior. The third task focused on the development of physics-inspired numerical methods of solution of the coupled
The issue of statistical power for overall model fit in evaluating structural equation models
Directory of Open Access Journals (Sweden)
Richard HERMIDA
2015-06-01
Full Text Available Statistical power is an important concept for psychological research. However, examining the power of a structural equation model (SEM is rare in practice. This article provides an accessible review of the concept of statistical power for the Root Mean Square Error of Approximation (RMSEA index of overall model fit in structural equation modeling. By way of example, we examine the current state of power in the literature by reviewing studies in top Industrial-Organizational (I/O Psychology journals using SEMs. Results indicate that in many studies, power is very low, which implies acceptance of invalid models. Additionally, we examined methodological situations which may have an influence on statistical power of SEMs. Results showed that power varies significantly as a function of model type and whether or not the model is the main model for the study. Finally, results indicated that power is significantly related to model fit statistics used in evaluating SEMs. The results from this quantitative review imply that researchers should be more vigilant with respect to power in structural equation modeling. We therefore conclude by offering methodological best practices to increase confidence in the interpretation of structural equation modeling results with respect to statistical power issues.
Modelling the influence of photospheric turbulence on solar flare statistics
Mendoza, M; de Arcangelis, L; Andrade, J S; Herrmann, H J
2014-01-01
Solar flares stem from the reconnection of twisted magnetic field lines in the solar photosphere. The energy and waiting time distributions of these events follow complex patterns that have been carefully considered in the past and that bear some resemblance with earthquakes and stockmarkets. Here we explore in detail the tangling motion of interacting flux tubes anchored in the plasma and the energy ejections resulting when they recombine. The mechanism for energy accumulation and release in the flow is reminiscent of self-organized criticality. From this model we suggest the origin for two important and widely studied properties of solar flare statistics, including the time-energy correlations. We first propose that the scale-free energy distribution of solar flares is largely due to the twist exerted by the vorticity of the turbulent photosphere. Second, the long-range temporal and time-energy correlations appear to arise from the tube-tube interactions. The agreement with satellite measurements is encoura...
Statistical model on the surface elevation of waves with breaking
Institute of Scientific and Technical Information of China (English)
2008-01-01
In the surface wind drift layer with constant momentum flux, two sets of the consistent surface eleva- tion expressions with breaking and occurrence conditions for breaking are deduced from the first in- tegrals of the energy and vortex variations and the kinetic and mathematic breaking criterions, then the expression of the surface elevation with wave breaking is established by using the Heaviside function. On the basis of the form of the sea surface elevation with wave breaking and the understanding of small slope sea waves, a triple composite function of real sea waves is presented including the func- tions for the breaking, weak-nonlinear and basic waves. The expression of the triple composite func- tion and the normal distribution of basic waves are the expected theoretical model for surface elevation statistics.