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
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
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
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.
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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.
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
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
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
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
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
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
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.
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
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
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
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
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
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.
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
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.
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
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
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
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.
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
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
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
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
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
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
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
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.
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
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
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
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
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.
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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.
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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.
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
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
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, 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
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
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
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
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
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
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
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
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)
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
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
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
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
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
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
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
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
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
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
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.
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
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.