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.
Bayesian Statistical Inference in Ion-Channel Models with Exact Missed Event Correction.
Epstein, Michael; Calderhead, Ben; Girolami, Mark A; Sivilotti, Lucia G
2016-07-26
The stochastic behavior of single ion channels is most often described as an aggregated continuous-time Markov process with discrete states. For ligand-gated channels each state can represent a different conformation of the channel protein or a different number of bound ligands. Single-channel recordings show only whether the channel is open or shut: states of equal conductance are aggregated, so transitions between them have to be inferred indirectly. The requirement to filter noise from the raw signal further complicates the modeling process, as it limits the time resolution of the data. The consequence of the reduced bandwidth is that openings or shuttings that are shorter than the resolution cannot be observed; these are known as missed events. Postulated models fitted using filtered data must therefore explicitly account for missed events to avoid bias in the estimation of rate parameters and therefore assess parameter identifiability accurately. In this article, we present the first, to our knowledge, Bayesian modeling of ion-channels with exact missed events correction. Bayesian analysis represents uncertain knowledge of the true value of model parameters by considering these parameters as random variables. This allows us to gain a full appreciation of parameter identifiability and uncertainty when estimating values for model parameters. However, Bayesian inference is particularly challenging in this context as the correction for missed events increases the computational complexity of the model likelihood. Nonetheless, we successfully implemented a two-step Markov chain Monte Carlo method that we called "BICME", which performs Bayesian inference in models of realistic complexity. The method is demonstrated on synthetic and real single-channel data from muscle nicotinic acetylcholine channels. We show that parameter uncertainty can be characterized more accurately than with maximum-likelihood methods. Our code for performing inference in these ion channel
Directory of Open Access Journals (Sweden)
Basile L. AGBA
2008-06-01
Full Text Available Mobile ad hoc networks (MANET are very difficult to design in terms of scenarios specification and propagation modeling. All these aspects must be taken into account when designing MANET. For cost-effective designing, powerful and accurate simulation tools are needed. Our first contribution in this paper is to provide a global approach process (GAP in channel modeling combining scenarios and propagation in order to have a better analysis of the physical layer, and finally to improve performances of the whole network. The GAP is implemented in an integrated simulation tool, Ad-SMPro. Moreover, channel statistics, throughput and delay are some key points to be considered when studying a mobile wireless networks. A carefully analysis of mobility effects over second order channel statistics and system performances is made based on our optimized simulation tool, Ad-SMProl. The channel is modeled by large scale fading and small scale fading including Doppler spectrum due to the double mobility of the nodes. Level Cross Rate and Average Duration of Fade are simulated as function of double mobility degree, a defined to be the ratio of the nodes' speeds. These results are compared to the theoretical predictions. We demonstrate that, in mobile ad hoc networks, flat fading channels and frequency-selective fading channels are differently affected. In addition, Bit Error rate is analysed as function of the ratio of the average bit energy to thermal noise density. Other performances (such as throughput, delay and routing traffic are analysed and conclusions related to the proposed simulation model and the mobility effects are drawn.
Statistical model of natural stimuli predicts edge-like pooling of spatial frequency channels in V2
Directory of Open Access Journals (Sweden)
Gutmann Michael
2005-02-01
Full Text Available Abstract Background It has been shown that the classical receptive fields of simple and complex cells in the primary visual cortex emerge from the statistical properties of natural images by forcing the cell responses to be maximally sparse or independent. We investigate how to learn features beyond the primary visual cortex from the statistical properties of modelled complex-cell outputs. In previous work, we showed that a new model, non-negative sparse coding, led to the emergence of features which code for contours of a given spatial frequency band. Results We applied ordinary independent component analysis to modelled outputs of complex cells that span different frequency bands. The analysis led to the emergence of features which pool spatially coherent across-frequency activity in the modelled primary visual cortex. Thus, the statistically optimal way of processing complex-cell outputs abandons separate frequency channels, while preserving and even enhancing orientation tuning and spatial localization. As a technical aside, we found that the non-negativity constraint is not necessary: ordinary independent component analysis produces essentially the same results as our previous work. Conclusion We propose that the pooling that emerges allows the features to code for realistic low-level image features related to step edges. Further, the results prove the viability of statistical modelling of natural images as a framework that produces quantitative predictions of visual processing.
Turbo Detection in Rayleigh flat fading channel with unknown statistics
Directory of Open Access Journals (Sweden)
Paul Fortier
2010-11-01
Full Text Available The turbo detection of turbo coded symbols over correlated Rayleigh flat fading channels generatedaccording to Jakes’ model is considered in this paper. We propose a method to estimate the channelsignal-to-noise ratio (SNR and the maximum Doppler frequency. These statistics are required bythe linear minimum mean squared error (LMMSE channel estimator. To improve the system convergence,we redefine the channel reliability factor by taking into account the channel estimationerror statistics. Simulation results for rate 1=3 turbo code and two different normalized fading ratesshow that the use of the new reliability factor greatly improves the performance. The improvementis more substantial when channel statistics are unknown.
Hatabu, Atsushi; Takeda, Koujin; Kabashima, Yoshiyuki
2009-12-01
The Kronecker channel model of wireless communication is analyzed using statistical mechanics methods. In the model, spatial proximities among transmission/reception antennas are taken into account as certain correlation matrices, which generally yield nontrivial dependence among symbols to be estimated. This prevents accurate assessment of the communication performance by naively using a previously developed analytical scheme based on a matrix integration formula. In order to resolve this difficulty, we develop a formalism that can formally handle the correlations in Kronecker models based on the known scheme. Unfortunately, direct application of the developed scheme is, in general, practically difficult. However, the formalism is still useful, indicating that the effect of the correlations generally increase after the fourth order with respect to correlation strength. Therefore, the known analytical scheme offers a good approximation in performance evaluation when the correlation strength is sufficiently small. For a class of specific correlation, we show that the performance analysis can be mapped to the problem of one-dimensional spin systems in random fields, which can be investigated without approximation by the belief propagation algorithm.
Statistical properties of chaotic scattering with one open channel
International Nuclear Information System (INIS)
The correspondence between statistical properties of decaying states and fluctuations in resonance scattering is studied in a statistical model with one open channel. The model is described by an ensemble of random nonhermitian matrices. The dependence of the correlation length on the coupling parameter both for the S-matrix and the cross-section is studied numerically. 37 refs., 7 figs
Statistical Hot Channel Analysis for the NBSR
Energy Technology Data Exchange (ETDEWEB)
Cuadra A.; Baek J.
2014-05-27
A statistical analysis of thermal limits has been carried out for the research reactor (NBSR) at the National Institute of Standards and Technology (NIST). The objective of this analysis was to update the uncertainties of the hot channel factors with respect to previous analysis for both high-enriched uranium (HEU) and low-enriched uranium (LEU) fuels. Although uncertainties in key parameters which enter into the analysis are not yet known for the LEU core, the current analysis uses reasonable approximations instead of conservative estimates based on HEU values. Cumulative distribution functions (CDFs) were obtained for critical heat flux ratio (CHFR), and onset of flow instability ratio (OFIR). As was done previously, the Sudo-Kaminaga correlation was used for CHF and the Saha-Zuber correlation was used for OFI. Results were obtained for probability levels of 90%, 95%, and 99.9%. As an example of the analysis, the results for both the existing reactor with HEU fuel and the LEU core show that CHFR would have to be above 1.39 to assure with 95% probability that there is no CHF. For the OFIR, the results show that the ratio should be above 1.40 to assure with a 95% probability that OFI is not reached.
Diffeomorphic Statistical Deformation Models
DEFF Research Database (Denmark)
Hansen, Michael Sass; Hansen, Mads/Fogtman; Larsen, Rasmus
2007-01-01
In this paper we present a new method for constructing diffeomorphic statistical deformation models in arbitrary dimensional images with a nonlinear generative model and a linear parameter space. Our deformation model is a modified version of the diffeomorphic model introduced by Cootes et al. Th...... with ground truth in form of manual expert annotations, and compared to Cootes's model. We anticipate applications in unconstrained diffeomorphic synthesis of images, e.g. for tracking, segmentation, registration or classification purposes.......In this paper we present a new method for constructing diffeomorphic statistical deformation models in arbitrary dimensional images with a nonlinear generative model and a linear parameter space. Our deformation model is a modified version of the diffeomorphic model introduced by Cootes et al...... 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...
Modeling cosmic void statistics
Hamaus, Nico; Sutter, P. M.; Wandelt, Benjamin D.
2016-10-01
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 ΛCDM 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.
Modeling cosmic void statistics
Hamaus, Nico; Wandelt, Benjamin D
2014-01-01
Understanding the internal structure and spatial distribution of cosmic voids is crucial when considering them as probes of cosmology. We present recent advances in modeling void density- and velocity-profiles in real space, as well as void two-point statistics in redshift space, by examining voids identified via the watershed transform in state-of-the-art $\\Lambda$CDM n-body simulations and mock galaxy catalogs. The simple and universal characteristics that emerge from these statistics indicate the self-similarity of large-scale structure and suggest cosmic voids to be among the most pristine objects to consider for future studies on the nature of dark energy, dark matter and modified gravity.
Institute of Scientific and Technical Information of China (English)
Wang Hui-Song; Zeng Gui-Hua
2008-01-01
In this paper,the effect of imperfect channel state information at the receiver, which is caused by noise and other interference, on the multi-access channel capacity is analysed through a statistical-mechanical approach. Replica analyses focus on analytically studying how the minimum mean square error (MMSE) channel estimation error appears in a multiuser channel capacity formula. And the relevant mathematical expressions are derived. At the same time,numerical simulation results are demonstrated to validate the Replica analyses. The simulation results show how the system parameters, such as channel estimation error, system load and signal-to-noise ratio, affect the channel capacity.
Decoding with approximate channel statistics for band-limited nonlinear satellite channels
Biederman, L.; Omura, J. K.; Jain, P. C.
1981-11-01
Expressions for the cutoff rate of memoryless channels and certain channels with memory are derived assuming decoding with approximate channel statistics. For channels with memory, two different decoding techniques are examined: conventional decoders in conjunction with ideal interleaving/deinterleaving, and maximum likelihood decoders that take advantage of the channel memory. As a practical case of interest, the cutoff rate for the band-limited nonlinear satellite channel is evaluated where the modulation is assumed to be M-ary phase shift keying (MPSK). The channel nonlinearity is introduced by a limiter in cascade with a traveling wave tube amplifier (TWTA) at the satellite repeater while the channel memory is created by channel filters in the transmission path.
Wu, Yongpeng; Wen, Chao-Kai; Xiao, Chengshan; Gao, Xiqi; Schober, Robert
2014-01-01
In this paper, we investigate the design of linear precoders for the multiple-input multiple-output (MIMO) multiple access channel (MAC). We assume that statistical channel state information (CSI) is available at the transmitters and consider the problem under the practical finite alphabet input assumption. First, we derive an asymptotic (in the large system limit) expression for the weighted sum rate (WSR) of the MIMO MAC with finite alphabet inputs and Weichselberger's MIMO channel model. S...
Channel Statistics for MIMO Handsets in Data Mode
DEFF Research Database (Denmark)
Nielsen, Jesper Ødum; Yanakiev, Boyan; Barrio, Samantha Caporal Del;
2014-01-01
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...
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.
Statistical Model for Content Extraction
DEFF Research Database (Denmark)
Qureshi, Pir Abdul Rasool; Memon, Nasrullah
2011-01-01
We present a statistical model for content extraction from HTML documents. The model operates on Document Object Model (DOM) tree of the corresponding HTML document. It evaluates each tree node and associated statistical features to predict significance of the node towards overall content...
Axial electron channeling statistical method of site occupancy determination
Institute of Scientific and Technical Information of China (English)
无
2001-01-01
Multibeams dynamical theory of electron diffraction has been used to calculate the fast electron thickness-integrated probability density on Ti and Al sites in the γ-TiAl phase as a function of the incident electron beam orientation along \\[100\\], \\[110\\] and \\[011\\] zone axes, with the effect of absorption considered. Both of the calculation and experiments show that there are big differences in electron channeling effect for different zone axes or the same axis but with different orientations, so we should choose proper zone axis and suitable incident beam tilting angles when using the axial electron channeling statistical method to determine the site occupancies of impurities. It is suggested to calculate the channeling effect map before the experiments.
Methods of statistical model estimation
Hilbe, Joseph
2013-01-01
Methods of Statistical Model Estimation examines the most important and popular methods used to estimate parameters for statistical models and provide informative model summary statistics. Designed for R users, the book is also ideal for anyone wanting to better understand the algorithms used for statistical model fitting. The text presents algorithms for the estimation of a variety of regression procedures using maximum likelihood estimation, iteratively reweighted least squares regression, the EM algorithm, and MCMC sampling. Fully developed, working R code is constructed for each method. Th
Directory of Open Access Journals (Sweden)
Justin John Finnerty
Full Text Available Cation selective channels constitute the gate for ion currents through the cell membrane. Here we present an improved statistical mechanical model based on atomistic structural information, cation hydration state and without tuned parameters that reproduces the selectivity of biological Na+ and Ca2+ ion channels. The importance of the inclusion of step-wise cation hydration in these results confirms the essential role partial dehydration plays in the bacterial Na+ channels. The model, proven reliable against experimental data, could be straightforwardly used for designing Na+ and Ca2+ selective nanopores.
Foundational Issues in Statistical Modeling: Statistical Model Specification and Validation
Directory of Open Access Journals (Sweden)
Aris Spanos
2011-01-01
Full Text Available Statistical model specification and validation raise crucial foundational problems whose pertinent resolution holds the key to learning from data by securing the reliability of frequentist inference. The paper questions the judiciousness of several current practices, including the theory-driven approach, and the Akaike-type model selection procedures, arguing that they often lead to unreliable inferences. This is primarily due to the fact that goodness-of-fit/prediction measures and other substantive and pragmatic criteria are of questionable value when the estimated model is statistically misspecified. Foisting one's favorite model on the data often yields estimated models which are both statistically and substantively misspecified, but one has no way to delineate between the two sources of error and apportion blame. The paper argues that the error statistical approach can address this Duhemian ambiguity by distinguishing between statistical and substantive premises and viewing empirical modeling in a piecemeal way with a view to delineate the various issues more effectively. It is also argued that Hendry's general to specific procedures does a much better job in model selection than the theory-driven and the Akaike-type procedures primary because of its error statistical underpinnings.
Statistical 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.
A Statistical Programme Assignment Model
DEFF Research Database (Denmark)
Rosholm, Michael; Staghøj, Jonas; Svarer, Michael
When treatment effects of active labour market programmes are heterogeneous in an observable way across the population, the allocation of the unemployed into different programmes becomes a particularly important issue. In this paper, we present a statistical model designed to improve the present...... duration of unemployment spells may result if a statistical programme assignment model is introduced. We discuss several issues regarding the plementation of such a system, especially the interplay between the statistical model and case workers....
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 $\
A Survey on Statistical Based Single Channel Speech Enhancement Techniques
Directory of Open Access Journals (Sweden)
Sunnydayal. V
2014-11-01
Full Text Available Speech enhancement is a long standing problem with various applications like hearing aids, automatic recognition and coding of speech signals. Single channel speech enhancement technique is used for enhancement of the speech degraded by additive background noises. The background noise can have an adverse impact on our ability to converse without hindrance or smoothly in very noisy environments, such as busy streets, in a car or cockpit of an airplane. Such type of noises can affect quality and intelligibility of speech. This is a survey paper and its object is to provide an overview of speech enhancement algorithms so that enhance the noisy speech signal which is corrupted by additive noise. The algorithms are mainly based on statistical based approaches. Different estimators are compared. Challenges and Opportunities of speech enhancement are also discussed. This paper helps in choosing the best statistical based technique for speech enhancement
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...
Institute of Scientific and Technical Information of China (English)
Xiao Hailin; Nie Zaiping; Yang Shiwen
2007-01-01
The novel closed-form expressions for the average channel capacity of dual selection diversity is presented, as well as, the bit-error rate (BER) of several coherent and noncoherent digital modulation schemes in the correlated Weibull fading channels with nonidentical statistics.The results are expressed in terms of Meijer's Gfunction, which can be easily evaluated numerically.The simulation results are presented to validate the proposed theoretical analysis and to examine the effects of the fading severity on the concerned quantities.
Statistical Model of Extreme Shear
DEFF Research Database (Denmark)
Larsen, Gunner Chr.; Hansen, Kurt Schaldemose
2004-01-01
In order to continue cost-optimisation of modern large wind turbines, it is important to continously increase the knowledge on wind field parameters relevant to design loads. This paper presents a general statistical model that offers site-specific prediction of the probability density function...... (PDF) of turbulence driven short-term extreme wind shear events, conditioned on the mean wind speed, for an arbitrary recurrence period. The model is based on an asymptotic expansion, and only a few and easily accessible parameters are needed as input. The model of the extreme PDF is supplemented...... by a 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...
Statistical Model of Extreme Shear
DEFF Research Database (Denmark)
Hansen, Kurt Schaldemose; Larsen, Gunner Chr.
2005-01-01
In order to continue cost-optimisation of modern large wind turbines, it is important to continuously increase the knowledge of wind field parameters relevant to design loads. This paper presents a general statistical model that offers site-specific prediction of the probability density function ...
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
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...
New Statistical Models for Copolymerization
Directory of Open Access Journals (Sweden)
Martin S. Engler
2016-06-01
Full Text Available For many years, copolymerization has been studied using mathematical and statistical models. Here, we present new Markov chain models for copolymerization kinetics: the Bernoulli and Geometric models. They model copolymer synthesis as a random process and are based on a basic reaction scheme. In contrast to previous Markov chain approaches to copolymerization, both models take variable chain lengths and time-dependent monomer probabilities into account and allow for computing sequence likelihoods and copolymer fingerprints. Fingerprints can be computed from copolymer mass spectra, potentially allowing us to estimate the model parameters from measured fingerprints. We compare both models against Monte Carlo simulations. We find that computing the models is fast and memory efficient.
Eigenvalue and Entropy Statistics for Products of Conjugate Random Quantum Channels
Directory of Open Access Journals (Sweden)
Benoît Collins
2010-06-01
Full Text Available Using the graphical calculus and integration techniques introduced by the authors, we study the statistical properties of outputs of products of random quantum channels for entangled inputs. In particular, we revisit and generalize models of relevance for the recent counterexamples to the minimum output entropy additivity problems. Our main result is a classification of regimes for which the von Neumann entropy is lower on average than the elementary bounds that can be obtained with linear algebra techniques.
Improved model for statistical alignment
Energy Technology Data Exchange (ETDEWEB)
Miklos, I.; Toroczkai, Z. (Zoltan)
2001-01-01
The statistical approach to molecular sequence evolution involves the stochastic modeling of the substitution, insertion and deletion processes. Substitution has been modeled in a reliable way for more than three decades by using finite Markov-processes. Insertion and deletion, however, seem to be more difficult to model, and thc recent approaches cannot acceptably deal with multiple insertions and deletions. A new method based on a generating function approach is introduced to describe the multiple insertion process. The presented algorithm computes the approximate joint probability of two sequences in 0(13) running time where 1 is the geometric mean of the sequence lengths.
Statistical development and validation of discharge equations for natural channels
Dingman, S. Lawrence; Sharma, Keshav P.
1997-12-01
Although the Manning equation is widely accepted as the empirical flow law for rough turbulent open-channel flow, using the equation in practical situations such as slope-area computations is fraught with uncertainty because of the difficulty in specifying the value of the reach resistance, Manning's n. Riggs (1976, J. Res. US Geol. Surv., 4: 285-291) found that n was correlated with water-surface slope, and proposed a multiple-regression equation that obviates the need for estimating n in slope-area estimates of discharge. Because his relation was developed from a relatively small sample ( N = 62), had potential flaws owing to multicollinearity, and was not thoroughly validated, we used an expanded data base ( N = 520) and objective methods to develop a new relation for the same purpose: Q = 1.564 A1.173R0.400S-0.0543log S where Q is discharge (m 3 s -1), A is cross-sectional area (m 2), R is hydraulic radius (m), and S is water-surface slope. We validated Rigg's model and our model using 100 measurements not included in model development and found that both give similar results. Riggs's model is somewhat better in terms of actual (m 3 s -1) error, but ours is better in terms of relative (log Q) error. We conclude that either Riggs's or our model can be used in place of Manning's equation in slope-area computations, but that our model is preferable because it has less bias, minimizes multicollinearity, and performs better when applied to discharge changes in individual reaches. We also found that our model performs better than those of Jarrett (1984, J. Hydraul. Eng., 110: 1519-1539) or Riggs in the range of applicability of Jarrett's equation (0.15 m ≤ R ≤ 2.13 m; 0.002 ≤ S ≤ 0.052). Both Riggs's and our models significantly overestimate Q in flows satisfying both the following conditions: Q < 3 m 3s -1 and Froude number less than 0.2. For other in-bank flows in relatively straight reaches, our model can be recommended for use in slope-area computations
Mobile Radio Channels Modeling in MATLAB
N. Kostov
2003-01-01
In this paper, a MATLAB based approach for mobile radio channels modeling is presented. Specifically, the paper introduces the basic concepts for modeling flat fading channels in MATLAB by means of user-defined m-files. Typical small-scale fading channel models are derived such as uncorrelated Rician fading channel and Rayleigh fading channel with Doppler shift. Further, simple and useful MATLAB constructions for approximation of cumulative distribution functions (CDFs) and probability densit...
Statistical bootstrap model and annihilations
Möhring, H J
1974-01-01
The statistical bootstrap model (SBM) describes the decay of single, high mass, hadronic states (fireballs, clusters) into stable particles. Coupling constants B, one for each isospin multiplet of stable particles, are the only free parameter of the model. They are related to the maximum temperature parameter T/sub 0/. The various versions of the SMB can be classified into two groups: full statistical bootstrap models and linear ones. The main results of the model are the following: i) All momentum spectra are isotropic; especially the exclusive ones are described by invariant phase space. The inclusive and semi-inclusive single-particle distributions are asymptotically of pure exponential shape; the slope is governed by T /sub 0/ only. ii) The model parameter B for pions has been obtained by fitting the multiplicity distribution in pp and pn at rest, and corresponds to T/sub 0/=0.167 GeV in the full SBM with exotics. The average pi /sup -/ multiplicity for the linear and the full SBM (both with exotics) is c...
A Survey of Fading Models for Mobile Radio Channel Characterization
Directory of Open Access Journals (Sweden)
L. D. Arya
2010-02-01
Full Text Available Future 3G and 4G mobile communication systems will be required to support wide range of data rates and quality of service matrix. For the efficient design of data link and transport protocols system designer needs knowledge of the statistical properties of physicallayer. Studies have shown that without proper characterization of the channel, blind application of existing protocols and transmission policy may results in disastrous performance unless proper measures are not being taken. Channel characterization also helps in llocation of resources, selection of transmission policy andprotocols. A feasible measure is to have an accurate and thoroughly reproducible optimum channel model which can mimic the mobile radio channel in diversities of fading error environments. Objective of channel model is to supply proper outputs for designing of upper layer protocol in such a fashion as if it were running on the actualphysical layer. The model should fit very well to the measured data and should easily handle analytically. Various approaches for characterization of fading mobile channels have appeared in iterature over last five decades. This article surveys the fading channel models for proper characterization of the radio channel andprovides approaches to classify the existing channel models. The paper also presents the contribution made by these channel models with their assumptions, suitability, applications, shortcomingsand further improvement issues. In present environment Markov Models are best suited for characterization of the fading radio channel. Inthese models radio channel is presented in terms of fading states and modeled as stochastic process. A proper constructed channel model may be valuable means to enhance the reliability and capacity of future mobile radio channel.
Statistical models for seismic magnitude
Christoffersson, Anders
1980-02-01
In this paper some statistical models in connection with seismic magnitude are presented. Two main situations are treated. The first deals with the estimation of magnitude for an event, using a fixed network of stations and taking into account the detection and bias properties of the individual stations. The second treats the problem of estimating seismicity, and detection and bias properties of individual stations. The models are applied to analyze the magnitude bias effects for an earthquake aftershock sequence from Japan, as recorded by a hypothetical network of 15 stations. It is found that network magnitudes computed by the conventional averaging technique are considerably biased, and that a maximum likelihood approach using instantaneous noise-level estimates for non-detecting stations gives the most consistent magnitude estimates. Finally, the models are applied to evaluate the detection characteristics and associated seismicity as recorded by three VELA arrays: UBO (Uinta Basin), TFO (Tonto Forest) and WMO (Wichita Mountains).
On the Second Order Statistics of the Multihop Rayleigh Fading Channel
Hadzi-Velkov, Zoran; Karagiannidis, George K; 10.1109/TCOMM.2009.06.070460
2009-01-01
Second order statistics provides a dynamic representation of a fading channel and plays an important role in the evaluation and design of the wireless communication systems. In this paper, we present a novel analytical framework for the evaluation of important second order statistical parameters, as the level crossing rate (LCR) and the average fade duration (AFD) of the amplify-and-forward multihop Rayleigh fading channel. More specifically, motivated by the fact that this channel is a cascaded one and can be modeled as the product of N fading amplitudes, we derive novel analytical expressions for the average LCR and the AFD of the product of N Rayleigh fading envelopes (or of the recently so-called N*Rayleigh channel). Furthermore, we derive simple and efficient closed-form approximations to the aforementioned parameters, using the multivariate Laplace approximation theorem. It is shown that our general results reduce to the corresponding ones of the specific dual-hop case, previously published. Numerical a...
Channel network identification from high-resolution DTM: a statistical approach
Directory of Open Access Journals (Sweden)
G. Sofia
2010-12-01
Full Text Available A statistical approach to LiDAR derived topographic attributes for the automatic extraction of channel network is presented in this paper. The basis of this approach is to use statistical descriptors to identify channel where terrain geometry denotes significant convergences. Two case study areas of different morphology and degree of organization are used with their 1 m LiDAR Digital Terrain Models (DTMs. Topographic attribute maps (curvature and openness for different window sizes are derived from the DTMs in order to detect surface convergences. For the choice of the optimum kernel size, a statistical analysis on values distributions of these maps is carried out. For the network extraction, we propose a three-step method based (a on the normalization and overlapping of openness and minimum curvature in order to highlight the more likely surface convergences, (b a weighting of the upslope area according to such normalized maps in order to identify drainage flow paths and flow accumulation consistent with terrain geometry, (c the z-score normalization of the weighted upslope area and the use of z-score values as non-subjective threshold for channel network identification. As a final step for optimal definition and representation of the whole network, a noise-filtering and connection procedure is applied. The advantage of the proposed methodology, and the efficiency and accurate localization of extracted features are demonstrated using LiDAR data of two different areas and comparing both extractions with field surveyed networks.
Statistical models for trisomic phenotypes
Energy Technology Data Exchange (ETDEWEB)
Lamb, N.E.; Sherman, S.L.; Feingold, E. [Emory Univ., Atlanta, GA (United States)
1996-01-01
Certain genetic disorders are rare in the general population but more common in individuals with specific trisomies, which suggests that the genes involved in the etiology of these disorders may be located on the trisomic chromosome. As with all aneuploid syndromes, however, a considerable degree of variation exists within each phenotype so that any given trait is present only among a subset of the trisomic population. We have previously presented a simple gene-dosage model to explain this phenotypic variation and developed a strategy to map genes for such traits. The mapping strategy does not depend on the simple model but works in theory under any model that predicts that affected individuals have an increased likelihood of disomic homozygosity at the trait locus. This paper explores the robustness of our mapping method by investigating what kinds of models give an expected increase in disomic homozygosity. We describe a number of basic statistical models for trisomic phenotypes. Some of these are logical extensions of standard models for disomic phenotypes, and some are more specific to trisomy. Where possible, we discuss genetic mechanisms applicable to each model. We investigate which models and which parameter values give an expected increase in disomic homozygosity in individuals with the trait. Finally, we determine the sample sizes required to identify the increased disomic homozygosity under each model. Most of the models we explore yield detectable increases in disomic homozygosity for some reasonable range of parameter values, usually corresponding to smaller trait frequencies. It therefore appears that our mapping method should be effective for a wide variety of moderately infrequent traits, even though the exact mode of inheritance is unlikely to be known. 21 refs., 8 figs., 1 tab.
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...
Bae, Minja; Park, Jihyun; Kim, Jongju; Xue, Dandan; Park, Kyu-Chil; Yoon, Jong Rak
2016-07-01
The bit error rate of an underwater acoustic communication system is related to multipath fading statistics, which determine the signal-to-noise ratio. The amplitude and delay of each path depend on sea surface roughness, propagation medium properties, and source-to-receiver range as a function of frequency. Therefore, received signals will show frequency-dependent fading. A shallow-water acoustic communication channel generally shows a few strong multipaths that interfere with each other and the resulting interference affects the fading statistics model. In this study, frequency-selective fading statistics are modeled on the basis of the phasor representation of the complex path amplitude. The fading statistics distribution is parameterized by the frequency-dependent constructive or destructive interference of multipaths. At a 16 m depth with a muddy bottom, a wave height of 0.2 m, and source-to-receiver ranges of 100 and 400 m, fading statistics tend to show a Rayleigh distribution at a destructive interference frequency, but a Rice distribution at a constructive interference frequency. The theoretical fading statistics well matched the experimental ones.
Degenerate RFID Channel Modeling for Positioning Applications
Directory of Open Access Journals (Sweden)
A. Povalac
2012-12-01
Full Text Available This paper introduces the theory of channel modeling for positioning applications in UHF RFID. It explains basic parameters for channel characterization from both the narrowband and wideband point of view. More details are given about ranging and direction finding. Finally, several positioning scenarios are analyzed with developed channel models. All the described models use a degenerate channel, i.e. combined signal propagation from the transmitter to the tag and from the tag to the receiver.
Modeling of weak lensing statistics. II. Configuration-space statistics
Valageas, Patrick; Nishimichi, Takahiro
2011-01-01
We investigate the performance of an analytic model of the 3D matter distribution, which combines perturbation theory with halo models, for weak lensing configuration-space statistics. We compare our predictions for the weak lensing convergence two-point and three-point correlation functions with numerical simulations and fitting formulas proposed in previous works. We also consider the second and third-order moments of the smoothed convergence and of the aperture-mass. As in our previous study of Fourier-space weak lensing statistics, we find that our model provides better agreement with simulations than published fitting formulas. Moreover, we check that we recover the dependence on cosmology of these weak lensing statistics. This approach allows us to obtain the quantitative relationship between these integrated weak lensing statistics and the various contributions to the underlying 3D density fluctuations, decomposed over perturbative, 2-halo, or 1-halo terms.
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.
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.
Institute of Scientific and Technical Information of China (English)
ZHAO Zhen-shan; XU Guo-zhi
2007-01-01
In real multiple-input multiple-output (MIMO) systems, the perfect channel state information (CSI) may be costly or impossible to acquire. But the channel statistical information can be considered relatively stationary during long-term transmission.The statistical information can be obtained at the receiver and fed back to the transmitter and do not require frequent update. By exploiting channel mean and covariance information at the transmitter simultaneously, this paper investigates the optimal transmission strategy for spatially correlated MIMO channels. An upper bound of ergodic capacity is derived and taken as the performance criterion. Simulation results are also given to show the performance improvement of the optimal transmission strategy.
Box model for channels of human migration
Vitanov, Nikolay K
2016-01-01
We discuss a mathematical model of migration channel based on the truncated Waring distribution. The truncated Waring distribution is obtained for a more general model of motion of substance through a channel containing finite number of boxes. The model is applied then for case of migrants moving through a channel consisting of finite number of countries or cities. The number of migrants in the channel strongly depends on the number of migrants that enter the channel through the country of entrance. It is shown that if the final destination country is very popular then large percentage of migrants may concentrate there.
Probing NWP model deficiencies by statistical postprocessing
DEFF Research Database (Denmark)
Rosgaard, Martin Haubjerg; Nielsen, Henrik Aalborg; Nielsen, Torben S.;
2016-01-01
The objective in this article is twofold. On one hand, a Model Output Statistics (MOS) framework for improved wind speed forecast accuracy is described and evaluated. On the other hand, the approach explored identifies unintuitive explanatory value from a diagnostic variable in an operational....... Based on the statistical model candidates inferred from the data, the lifted index NWP model diagnostic is consistently found among the NWP model predictors of the best performing statistical models across sites....
Radio propagation measurement and channel modelling
Salous, Sana
2013-01-01
While there are numerous books describing modern wireless communication systems that contain overviews of radio propagation and radio channel modelling, there are none that contain detailed information on the design, implementation and calibration of radio channel measurement equipment, the planning of experiments and the in depth analysis of measured data. The book would begin with an explanation of the fundamentals of radio wave propagation and progress through a series of topics, including the measurement of radio channel characteristics, radio channel sounders, measurement strategies
Scheduling with Rate Adaptation under Incomplete Knowledge of Channel/Estimator Statistics
Ouyang, Wenzhuo; Eryilmaz, Atilla; Shroff, Ness B
2010-01-01
In time-varying wireless networks, the state of the communication channels are subject to random variations, and hence need to be estimated for efficient rate adaptation and scheduling. The estimation mechanism possesses inaccuracies that need to be tackled in a probabilistic framework. In this work, we study scheduling with rate adaptation in single-hop queueing networks under two levels of channel uncertainty: when the channel estimates are inaccurate but complete knowledge of the channel/estimator joint statistics is available at the scheduler; and when the knowledge of the joint statistics is incomplete. In the former case, we characterize the network stability region and show that a maximum-weight type scheduling policy is throughput-optimal. In the latter case, we propose a joint channel statistics - scheduling policy. With an associated trade-off in average packet delay and convergence time, the proposed policy has a stability region arbitrarily close to the stability region of the network under full k...
Indoor MIMO Channel Measurement and Modeling
DEFF Research Database (Denmark)
Nielsen, Jesper Ødum; Andersen, Jørgen Bach
2005-01-01
Forming accurate models of the multiple input multiple output (MIMO) channel is essential both for simulation as well as understanding of the basic properties of the channel. This paper investigates different known models using measurements obtained with a 16x32 MIMO channel sounder for the 5.8GHz...... accurate model for Gaussian channels. For each of the environments different sizes of both the transmitter and receiver antenna arrays are investigated, 2x2 up to 16x32. Generally it was found that in terms of capacity cumulative distribution functions (CDFs) all models fit well for small array sizes, but...
Group statistical channel coding dimming scheme in visible light communication system
Zhuang, Kaiyu; Huang, Zhitong; Zhang, Ruqi; Li, Jianfeng; Ji, Yuefeng
2016-10-01
In this paper, we propose a group statistical channel coding (GSCC) scheme, which achieves dimming by changing the ratio of the 0-1 symbol of the original data stream through probabilistic statistics method. The simulation under various brightness conditions displays that the GSCC maintains good performance comparing to PWM dimming with half satisfice of transmission rate and a larger dimming intensity. Simulation of GSCC after combining with other channel coding schemes reflects that GSCC has good compatibility to arbitrary access coded signal.
Fermi breakup and the statistical multifragmentation model
Energy Technology Data Exchange (ETDEWEB)
Carlson, B.V., E-mail: brett@ita.br [Departamento de Fisica, Instituto Tecnologico de Aeronautica - CTA, 12228-900 Sao Jose dos Campos (Brazil); Donangelo, R. [Instituto de Fisica, Universidade Federal do Rio de Janeiro, Cidade Universitaria, CP 68528, 21941-972, Rio de Janeiro (Brazil); Instituto de Fisica, Facultad de Ingenieria, Universidad de la Republica, Julio Herrera y Reissig 565, 11.300 Montevideo (Uruguay); Souza, S.R. [Instituto de Fisica, Universidade Federal do Rio de Janeiro, Cidade Universitaria, CP 68528, 21941-972, Rio de Janeiro (Brazil); Instituto de Fisica, Universidade Federal do Rio Grande do Sul, Av. Bento Goncalves 9500, CP 15051, 91501-970, Porto Alegre (Brazil); Lynch, W.G.; Steiner, A.W.; Tsang, M.B. [Joint Institute for Nuclear Astrophysics, National Superconducting Cyclotron Laboratory and the Department of Physics and Astronomy, Michigan State University, East Lansing, MI 48824 (United States)
2012-02-15
We demonstrate the equivalence of a generalized Fermi breakup model, in which densities of excited states are taken into account, to the microcanonical statistical multifragmentation model used to describe the disintegration of highly excited fragments of nuclear reactions. We argue that such a model better fulfills the hypothesis of statistical equilibrium than the Fermi breakup model generally used to describe statistical disintegration of light mass nuclei.
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
A Semi-Deterministic Channel Model for VANETs Simulations
Directory of Open Access Journals (Sweden)
Jonathan Ledy
2012-01-01
Full Text Available Today's advanced simulators facilitate thorough studies on Vehicular Ad hoc NETworks (VANETs. However the choice of the physical layer model in such simulators is a crucial issue that impacts the results. A solution to this challenge might be found with a hybrid model. In this paper, we propose a semi-deterministic channel propagation model for VANETs called UM-CRT. It is based on CRT (Communication Ray Tracer and SCME—UM (Spatial Channel Model Extended—Urban Micro which are, respectively, a deterministic channel simulator and a statistical channel model. It uses a process which adjusts the statistical model using relevant parameters obtained from the deterministic simulator. To evaluate realistic VANET transmissions, we have integrated our hybrid model in fully compliant 802.11 p and 802.11 n physical layers. This framework is then used with the NS-2 network simulator. Our simulation results show that UM-CRT is adapted for VANETs simulations in urban areas as it gives a good approximation of realistic channel propagation mechanisms while improving significantly simulation time.
Directory of Open Access Journals (Sweden)
Muhammad Imran Akram
2012-01-01
Full Text Available This paper presents the statistical properties of the vehicle-to-vehicle Nakagami-Hoyt (Nakagami-q channel model under non-isotropic condition. The spatial time correlation function (STCF, the power spectral density (PSD, squared time autocorrelation function (SQCF, level crossing rate (LCR, and the average duration of Fade (ADF of the Nakagami-Hoyt channel have been derived under the assumption that both the transmitter and receiver are nonstationary having nonomnidirectional antennas. A simulator that uses the inverse-fast-fourier-transform- (IFFT- based computation method is designed for this model. The simulator and analytical results are compared.
Statistical Modeling of SAR Images: A Survey
Directory of Open Access Journals (Sweden)
Gui Gao
2010-01-01
Full Text Available Statistical modeling is essential to SAR (Synthetic Aperture Radar image interpretation. It aims to describe SAR images through statistical methods and reveal the characteristics of these images. Moreover, statistical modeling can provide a technical support for a comprehensive understanding of terrain scattering mechanism, which helps to develop algorithms for effective image interpretation and creditable image simulation. Numerous statistical models have been developed to describe SAR image data, and the purpose of this paper is to categorize and evaluate these models. We first summarize the development history and the current researching state of statistical modeling, then different SAR image models developed from the product model are mainly discussed in detail. Relevant issues are also discussed. Several promising directions for future research are concluded at last.
Mobile Radio Channels Modeling in MATLAB
Directory of Open Access Journals (Sweden)
N. Kostov
2003-12-01
Full Text Available In this paper, a MATLAB based approach for mobile radio channelsmodeling is presented. Specifically, the paper introduces the basicconcepts for modeling flat fading channels in MATLAB by means ofuser-defined m-files. Typical small-scale fading channel models arederived such as uncorrelated Rician fading channel and Rayleigh fadingchannel with Doppler shift. Further, simple and useful MATLABconstructions for approximation of cumulative distribution functions(CDFs and probability density functions (PDFs are also given.Finally, a MATLAB based Monte Carlo simulation example is presented,which comprises performance estimation of phase shift keying (PSKsignaling over a Rician fading channel.
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...
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
Directory of Open Access Journals (Sweden)
PRAKASH PATIL
2012-05-01
Full Text Available The future short range wireless communication in an indoor environment jncludes the nondirected Infrared (IR Wireless communication. It is essential since there is a tremendous growth of bigger residential and commercial complexes. Also, nowadays use of portable devices such as LAPTOP, PDA etc. has been increased and the connectivity to such devices is the must without any interruption. In indoor environment both the transmitter and receiver are located inside the room. An empty rectangular is considered for the simulationpurpose. The major interest in this simulation deals with the diffuse configuration (Non-directed Non-LOS of the transmitter and the receiver. The IR wireless channel modeling is performed with multipath IR signals transmitted by the IR Transmitter and received by the receiver after multiple reflections from the reflecting surfaces such as ceiling, floor walls etc.Impulse response is the fundamental predictor of IR channel modeling and it is characterized by using Monte Carlo simulation.This paper estimates the mean received power and variance for different statistical distributions such as Rician, Gamma and Nakagami derived from histograms curve fitting for various receiver heights and radii. in time domain approach.
Statistical 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,
What is the meaning of the statistical hadronization model?
Becattini, F
2005-01-01
The statistical model of hadronization succeeds in reproducing particle abundances and transverse momentum spectra in high energy collisions of elementary particles as well as of heavy ions. Despite its apparent success, the interpretation of these results is controversial and the validity of the approach very often questioned. In this paper, we would like to summarize the whole issue by first outlining a basic formulation of the model and then comment on the main criticisms and different kinds of interpretations, with special emphasis on the so-called "phase space dominance". While the ultimate answer to the question why the statistical model works should certainly be pursued, we stress that it is a priority to confirm or disprove the fundamental scheme of the statistical model by performing some detailed tests on the rates of exclusive channels at lower energy.
Statistical modelling of fish stocks
DEFF Research Database (Denmark)
Kvist, Trine
1999-01-01
for modelling the dynamics of a fish population is suggested. A new approach is introduced to analyse the sources of variation in age composition data, which is one of the most important sources of information in the cohort based models for estimation of stock abundancies and mortalities. The approach combines...... and it is argued that an approach utilising stochastic differential equations might be advantagous in fish stoch assessments....
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.
Sensometrics: Thurstonian and Statistical Models
DEFF Research Database (Denmark)
Christensen, Rune Haubo Bojesen
as ever because it enables more informed decision making in quantifying the degree to which an ingredient substitution is successful and the degree to which the perceptual properties of the product remain unchanged from end user perspectives. This thesis contributes to the field of sensometrics in general...... of human senses. Thurstonian models provide a stochastic model for the data-generating mechanism through a psychophysical model for the cognitive processes and in addition provides an independent measure for quantification of sensory differences. In the interest of cost-reduction and health......-initiative purposes, much attention is currently given to ingredient substitution. Food and beverage producing companies are consequently applying discrimination testing to control and monitor the sensory properties of evolving products and consumer response to product changes. Discrimination testing is as relevant...
Channel Measurements and Modelling for Indoor Power Line Communications
Directory of Open Access Journals (Sweden)
Zhang Peiling
2013-04-01
Full Text Available In order to obtain power line communications channel transmission characteristics, impulse responses measurements were performed on the basis of PN sequence’s excellent periodic autocorrelation properties. Meanwhile, a compensation method in frequency domain was proposed to improve the measurement precision. Then, the empirical multipath channel model of power line is presented from the measured results. The simulation and experimental measurement results not only have verified the efficiency of the proposed model, but also showed that the measurement method has fast, simple and convenient characteristic. Finally, the statistical characteristics of path amplitude and the delay spread are obtained through the analysis of measured results.
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...
Quantum Biological Channel Modeling and Capacity Calculation
Directory of Open Access Journals (Sweden)
Ivan B. Djordjevic
2012-12-01
Full Text Available Quantum mechanics has an important role in photosynthesis, magnetoreception, and evolution. There were many attempts in an effort to explain the structure of genetic code and transfer of information from DNA to protein by using the concepts of quantum mechanics. The existing biological quantum channel models are not sufficiently general to incorporate all relevant contributions responsible for imperfect protein synthesis. Moreover, the problem of determination of quantum biological channel capacity is still an open problem. To solve these problems, we construct the operator-sum representation of biological channel based on codon basekets (basis vectors, and determine the quantum channel model suitable for study of the quantum biological channel capacity and beyond. The transcription process, DNA point mutations, insertions, deletions, and translation are interpreted as the quantum noise processes. The various types of quantum errors are classified into several broad categories: (i storage errors that occur in DNA itself as it represents an imperfect storage of genetic information, (ii replication errors introduced during DNA replication process, (iii transcription errors introduced during DNA to mRNA transcription, and (iv translation errors introduced during the translation process. By using this model, we determine the biological quantum channel capacity and compare it against corresponding classical biological channel capacity. We demonstrate that the quantum biological channel capacity is higher than the classical one, for a coherent quantum channel model, suggesting that quantum effects have an important role in biological systems. The proposed model is of crucial importance towards future study of quantum DNA error correction, developing quantum mechanical model of aging, developing the quantum mechanical models for tumors/cancer, and study of intracellular dynamics in general.
Axial electron channeling statistical method of site occupancy determination
Institute of Scientific and Technical Information of China (English)
YE; Jia
2001-01-01
Karman, Th., Zur theorie der spanungszustnde in plastischen und sandartigen medion, Nachr. Gesellsch. Wissensch., Gttingen, 1909.［17］Szczepinski, W., Introduction to the Mechanics of Plastic Forming of Metals, Netherlands: Sijthoff and Noordhoff, 1979.［18］Chen, W. F., Limit Analysis and Soil Plasticity, New York: Elsevier, 1975.［19］Yu, M. H., He, L. N., A new model and theory on yield and failure of materials under complex stress state, Mechanical Behaviors of Materials～6, Oxford: Pergamon Press, 1991, 3: 841—846.［20］Yu, M. H., New System of Strength Theory (in Chinese), Xi'an: Xi'an Jiaotong Universitry Press, 1992.［21］Yu, M. H., He, L. N., Song, L. Y., Twin shear stress theory and its generalization, Scientia Sinica (Science in China), Series A, 1985, 28(11): 1174—1183.［22］Yu, M. H., Yang, S. Y. et al., Unified elasto-plastic associated and non-associated constitutive model and its engineering applications, Computers and Structures, 1999, 71: 627—636.［23］Ma, G. W., Shoji, I., Plastic limit analysis of circular plates with respect to unified yield criterion, Int. J. Mech. Sci., 1998, 40(10): 963.［24］Ma, G. W., Hao, H., Unified plastic limit analyses of circular plates under arbitrary load, Journal of Applied Mechanics, ASME, 1999, 66(2): 568.［25］Qiang, H. F., Lu, N., Liu, B. J., Unified solutions of crack tip plastic zone under small scale yielding, Chinese Journal of Mechanical Engineering, (in Chinese with English abstract), 1999, 35(1): 34—38.［26］Yang, S. Y., Yu, M. H., Constitutive descriptions of multiphase poropus media, Acta Mechanica Sinica (in Chinese with English abstract), 2000, 32(1):11—24.［27］Yang, S. Y., Yu, M. H., An elasto-plastic damage model for saturated and unsaturated geomaterials, Acta Mechanica Sinica (in Chinese with English abstract), 2000, 32(2): 198—206.［28］Cheng, H. X., Li, J. J., Zhang, G. S. et al., Finite element analysis program system HAJIF(X), Chinese Journal of
Directory of Open Access Journals (Sweden)
Mandana Samari Kermani
2016-01-01
Full Text Available The interaction of spherical solid particles with turbulent eddies in a 3-D turbulent channel flow with friction Reynolds number was studied. A generalized lattice Boltzmann equation (GLBE was used for computation of instantaneous turbulent flow field for which large eddy simulation (LES was employed. The sub-grid-scale (SGS turbulence effects were simulated through a shear-improved Smagorinsky model (SISM, which can predict turbulent near wall region without any wall function. Statistical properties of particles behavior such as root mean square (RMS velocities were studied as a function of dimensionless particle relaxation time ( by using a Lagrangian approach. Combination of SISM in GLBE with particle tracking analysis in turbulent channel flow is novelty of the present work. Both GLBE and SISM solve the flow field equations locally. This is an advantage of this method and makes it easy implementing. Comparison of the present results with previous available data indicated that SISM in GLBE is a reliable method for simulation of turbulent flows which is a key point to predict particles behavior correctly.
Sensitivity Analysis and Statistical Convergence of a Saltating Particle Model
Maldonado, S
2016-01-01
Saltation models provide considerable insight into near-bed sediment transport. This paper outlines a simple, efficient numerical model of stochastic saltation, which is validated against previously published experimental data on saltation in a channel of nearly horizontal bed. Convergence tests are systematically applied to ensure the model is free from statistical errors emanating from the number of particle hops considered. Two criteria for statistical convergence are derived; according to the first criterion, at least $10^3$ hops appear to be necessary for convergent results, whereas $10^4$ saltations seem to be the minimum required in order to achieve statistical convergence in accordance with the second criterion. Two empirical formulae for lift force are considered: one dependent on the slip (relative) velocity of the particle multiplied by the vertical gradient of the horizontal flow velocity component; the other dependent on the difference between the squares of the slip velocity components at the to...
Uncertainty the soul of modeling, probability & statistics
Briggs, William
2016-01-01
This book presents a philosophical approach to probability and probabilistic thinking, considering the underpinnings of probabilistic reasoning and modeling, which effectively underlie everything in data science. The ultimate goal is to call into question many standard tenets and lay the philosophical and probabilistic groundwork and infrastructure for statistical modeling. It is the first book devoted to the philosophy of data aimed at working scientists and calls for a new consideration in the practice of probability and statistics to eliminate what has been referred to as the "Cult of Statistical Significance". The book explains the philosophy of these ideas and not the mathematics, though there are a handful of mathematical examples. The topics are logically laid out, starting with basic philosophy as related to probability, statistics, and science, and stepping through the key probabilistic ideas and concepts, and ending with statistical models. Its jargon-free approach asserts that standard methods, suc...
Statistical Model-Based Face Pose Estimation
Institute of Scientific and Technical Information of China (English)
GE Xinliang; YANG Jie; LI Feng; WANG Huahua
2007-01-01
A robust face pose estimation approach is proposed by using face shape statistical model approach and pose parameters are represented by trigonometric functions. The face shape statistical model is firstly built by analyzing the face shapes from different people under varying poses. The shape alignment is vital in the process of building the statistical model. Then, six trigonometric functions are employed to represent the face pose parameters. Lastly, the mapping function is constructed between face image and face pose by linearly relating different parameters. The proposed approach is able to estimate different face poses using a few face training samples. Experimental results are provided to demonstrate its efficiency and accuracy.
Modeling the Noise for Indoor Power Line Channel
Directory of Open Access Journals (Sweden)
Syed Samser Ali
2013-07-01
Full Text Available Electromagnetic interference, man-made noise, and multipath effects are main causes of bit errors in power-line communication. To design an efficient powerline transmission system, the channel characterization has to be known and this paper deals with a statistical noise model (SNM for the indoor powerline channel in a frequency band from 1 MHz to 30 MHz . The SNM parameters are obtained from large-scale measurements of the noise density spectrum on a real powerline channel. All measurements are between line and neutral at different locations in the same grid. The SNM is used for simulation of the noise density spectrum and offline analysis on the powerline channel
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.
Topology for statistical modeling of petascale data.
Energy Technology Data Exchange (ETDEWEB)
Pascucci, Valerio (University of Utah, Salt Lake City, UT); Mascarenhas, Ajith Arthur; Rusek, Korben (Texas A& M University, College Station, TX); Bennett, Janine Camille; Levine, Joshua (University of Utah, Salt Lake City, UT); Pebay, Philippe Pierre; Gyulassy, Attila (University of Utah, Salt Lake City, UT); Thompson, David C.; Rojas, Joseph Maurice (Texas A& M University, College Station, TX)
2011-07-01
This document presents current technical progress and dissemination of results for the Mathematics for Analysis of Petascale Data (MAPD) project titled 'Topology for Statistical Modeling of Petascale Data', funded by the Office of Science Advanced Scientific Computing Research (ASCR) Applied Math program. Many commonly used algorithms for mathematical analysis do not scale well enough to accommodate the size or complexity of petascale data produced by computational simulations. The primary goal of this project is thus to develop new mathematical tools that address both the petascale size and uncertain nature of current data. At a high level, our approach is based on the complementary techniques of combinatorial topology and statistical modeling. In particular, we use combinatorial topology to filter out spurious data that would otherwise skew statistical modeling techniques, and we employ advanced algorithms from algebraic statistics to efficiently find globally optimal fits to statistical models. This document summarizes the technical advances we have made to date that were made possible in whole or in part by MAPD funding. These technical contributions can be divided loosely into three categories: (1) advances in the field of combinatorial topology, (2) advances in statistical modeling, and (3) new integrated topological and statistical methods.
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
UWB channel modeling for indoor line-of-sight environment
Institute of Scientific and Technical Information of China (English)
无
2007-01-01
SV/IEEE 802.15.3a model has been the standard model for Ultra-wide bandwidth (UWB) indoor non-line-of-sight (NLOS) wireless propagation, but for line-of-sight (LOS) case, it is not well defined. In this paper, a new statistical distribution model exclusively used for LOS environment is proposed based on investigation of the experimental data. By reducing the number of the visible random arriving clusters, the model itself and the parameters estimating of the corresponding model are simplified in comparison with SV/IEEE 802.15.3a model. The simulation result indicates that the proposed model is more accurate in modeling smallscale LOS environment than SV/IEEE 802.15.3a model when considering cumulative distribution functions(CDFs) for the three key channel impulse response (CIR) statistics.
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...
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.
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
Statistical physics of pairwise probability models
DEFF Research Database (Denmark)
Roudi, Yasser; Aurell, Erik; Hertz, John
2009-01-01
(dansk abstrakt findes ikke) Statistical models for describing the probability distribution over the states of biological systems are commonly used for dimensional reduction. Among these models, pairwise models are very attractive in part because they can be fit using a reasonable amount of data...
Infinite Random Graphs as Statistical Mechanical Models
DEFF Research Database (Denmark)
Durhuus, Bergfinnur Jøgvan; Napolitano, George Maria
2011-01-01
We discuss two examples of infinite random graphs obtained as limits of finite statistical mechanical systems: a model of two-dimensional dis-cretized quantum gravity defined in terms of causal triangulated surfaces, and the Ising model on generic random trees. For the former model we describe...
Statistical distribution of the S-matrix in the one-channel case
Energy Technology Data Exchange (ETDEWEB)
Lopez, G.; Mello, P.A.; Seligman, T.H.
1981-10-01
It is shown that the statistical distribution of an ensemble of one-channel S-matrices is uniquely determined by requiring that: 1) S has poles only in the lower half of the energy plane and 2) the function S(E) is ergodic in a sense to be defined. A Monte Carlo calculation was performed to illustrate numerically the above statement.
Statistical distribution of the S-matrix in the on-channel case
Energy Technology Data Exchange (ETDEWEB)
Lopez, G.; Mello, P.A.; Seligman, T.H.
1981-10-01
It is shown that the statistical distribution of an ensemble of one-channel S-matrices is uniquely determined by requiring that: 1) S has poles only in the lower half of the energy plane and 2) the function S(E) is ergodic in a sense to be defined. A Monte Carlo calculation was performed to illustrate numerically the above statement.
Directory of Open Access Journals (Sweden)
CHEN, Z.
2014-11-01
Full Text Available Impulse noise in power line communication (PLC channel seriously degrades the performance of Multiple-Input Multiple-Output (MIMO system. To remedy this problem, a MIMO detection method based on fractional lower order statistics (FLOS for PLC channel with impulse noise is proposed in this paper. The alpha stable distribution is used to model impulse noise, and FLOS is applied to construct the criteria of MIMO detection. Then the optimal detection solution is obtained by recursive least squares algorithm. Finally, the transmitted signals in PLC MIMO system are restored with the obtained detection matrix. The proposed method does not require channel estimation and has low computational complexity. The simulation results show that the proposed method has a better PLC MIMO detection performance than the existing ones under impulsive noise environment.
Discrete Stochastic Modeling of Calcium Channel Dynamics
International Nuclear Information System (INIS)
We propose a discrete stochastic model for calcium dynamics in living cells. A set of probabilities for the opening/closing of calcium channels is assumed to depend on the calcium concentration. We study this model in one dimension, analytically in the limit of a large number of channels per site N , and numerically for small N . As the number of channels per site is increased, the transition from a nonpropagating region of activity to a propagating one changes from one described by directed percolation to that of deterministic depinning in a spatially discrete system. Also, for a small number of channels a propagating calcium wave can leave behind a novel fluctuation-driven state. (c) 2000 The American Physical Society
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.
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).
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.
Simple statistical model for branched aggregates
DEFF Research Database (Denmark)
Lemarchand, Claire; Hansen, Jesper Schmidt
2015-01-01
We propose a statistical model that can reproduce the size distribution of any branched aggregate, including amylopectin, dendrimers, molecular clusters of monoalcohols, and asphaltene nanoaggregates. It is based on the conditional probability for one molecule to form a new bond with a molecule......, given that it already has bonds with others. The model is applied here to asphaltene nanoaggregates observed in molecular dynamics simulations of Cooee bitumen. The variation with temperature of the probabilities deduced from this model is discussed in terms of statistical mechanics arguments....... The relevance of the statistical model in the case of asphaltene nanoaggregates is checked by comparing the predicted value of the probability for one molecule to have exactly i bonds with the same probability directly measured in the molecular dynamics simulations. The agreement is satisfactory...
Performance modeling, loss networks, and statistical multiplexing
Mazumdar, Ravi
2009-01-01
This monograph presents a concise mathematical approach for modeling and analyzing the performance of communication networks with the aim of understanding the phenomenon of statistical multiplexing. The novelty of the monograph is the fresh approach and insights provided by a sample-path methodology for queueing models that highlights the important ideas of Palm distributions associated with traffic models and their role in performance measures. Also presented are recent ideas of large buffer, and many sources asymptotics that play an important role in understanding statistical multiplexing. I
Statistical Modeling for Radiation Hardness Assurance
Ladbury, Raymond L.
2014-01-01
We cover the models and statistics associated with single event effects (and total ionizing dose), why we need them, and how to use them: What models are used, what errors exist in real test data, and what the model allows us to say about the DUT will be discussed. In addition, how to use other sources of data such as historical, heritage, and similar part and how to apply experience, physics, and expert opinion to the analysis will be covered. Also included will be concepts of Bayesian statistics, data fitting, and bounding rates.
Advanced Concepts for Underwater Acoustic Channel Modeling
Etter, P. C.; Haas, C. H.; Ramani, D. V.
2014-12-01
This paper examines nearshore underwater-acoustic channel modeling concepts and compares channel-state information requirements against existing modeling capabilities. This process defines a subset of candidate acoustic models suitable for simulating signal propagation in underwater communications. Underwater-acoustic communications find many practical applications in coastal oceanography, and networking is the enabling technology for these applications. Such networks can be formed by establishing two-way acoustic links between autonomous underwater vehicles and moored oceanographic sensors. These networks can be connected to a surface unit for further data transfer to ships, satellites, or shore stations via a radio-frequency link. This configuration establishes an interactive environment in which researchers can extract real-time data from multiple, but distant, underwater instruments. After evaluating the obtained data, control messages can be sent back to individual instruments to adapt the networks to changing situations. Underwater networks can also be used to increase the operating ranges of autonomous underwater vehicles by hopping the control and data messages through networks that cover large areas. A model of the ocean medium between acoustic sources and receivers is called a channel model. In an oceanic channel, characteristics of the acoustic signals change as they travel from transmitters to receivers. These characteristics depend upon the acoustic frequency, the distances between sources and receivers, the paths followed by the signals, and the prevailing ocean environment in the vicinity of the paths. Properties of the received signals can be derived from those of the transmitted signals using these channel models. This study concludes that ray-theory models are best suited to the simulation of acoustic signal propagation in oceanic channels and identifies 33 such models that are eligible candidates.
Statistical Hot Spot Model for Explosive Detonation
Energy Technology Data Exchange (ETDEWEB)
Nichols, III, A L
2005-07-14
The Non-local Thermodynamic Equilibrium Statistical Hot Spot Model (NLTE SHS), a new model for explosive detonation, is described. In this model, the formation, ignition, propagation, and extinction of hot spots is explicitly modeled. The equation of state of the explosive mixture is treated with a non-local equilibrium thermodynamic assumption. A methodology for developing the parameters for the model is discussed, and applied to the detonation velocity diameter effect. Examination of these results indicates where future improvements to the model can be made.
Statistical Hot Spot Model for Explosive Detonation
Energy Technology Data Exchange (ETDEWEB)
Nichols III, A L
2004-05-10
The Non-local Thermodynamic Equilibrium Statistical Hot Spot Model (NLTE SHS), a new model for explosive detonation, is described. In this model, the formation, ignition, propagation, and extinction of hot spots is explicitly modeled. The equation of state of the explosive mixture is treated with a nonlocal equilibrium thermodynamic assumption. A methodology for developing the parameters for the model is discussed, and applied to the detonation velocity diameter effect. Examination of these results indicates where future improvements to the model can be made.
Growth curve models and statistical diagnostics
Pan, Jian-Xin
2002-01-01
Growth-curve models are generalized multivariate analysis-of-variance models. These models are especially useful for investigating growth problems on short times in economics, biology, medical research, and epidemiology. This book systematically introduces the theory of the GCM with particular emphasis on their multivariate statistical diagnostics, which are based mainly on recent developments made by the authors and their collaborators. The authors provide complete proofs of theorems as well as practical data sets and MATLAB code.
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 modelling for ship propulsion efficiency
DEFF Research Database (Denmark)
Petersen, Jóan Petur; Jacobsen, Daniel J.; Winther, Ole
2012-01-01
This paper presents a state-of-the-art systems approach to statistical modelling of fuel efficiency in ship propulsion, and also a novel and publicly available data set of high quality sensory data. Two statistical model approaches are investigated and compared: artificial neural networks and...... Gaussian processes (GP). The data presented is a publicly available full-scale data set, with a whole range of features sampled over a period of 2 months. We further discuss interpretations of the operational data in relation to the underlying physical system....
Dynamic Propagation Channel Characterization and Modeling for Human Body Communication
Directory of Open Access Journals (Sweden)
Lei Wang
2012-12-01
Full Text Available This paper presents the first characterization and modeling of dynamic propagation channels for human body communication (HBC. In-situ experiments were performed using customized transceivers in an anechoic chamber. Three HBC propagation channels, i.e., from right leg to left leg, from right hand to left hand and from right hand to left leg, were investigated under thirty-three motion scenarios. Snapshots of data (2,800,000 were acquired from five volunteers. Various path gains caused by different locations and movements were quantified and the statistical distributions were estimated. In general, for a given reference threshold è = −10 dB, the maximum average level crossing rate of the HBC was approximately 1.99 Hz, the maximum average fade time was 59.4 ms, and the percentage of bad channel duration time was less than 4.16%. The HBC exhibited a fade depth of −4 dB at 90% complementary cumulative probability. The statistical parameters were observed to be centered for each propagation channel. Subsequently a Fritchman model was implemented to estimate the burst characteristics of the on-body fading. It was concluded that the HBC is motion-insensitive, which is sufficient for reliable communication link during motions, and therefore it has great potential for body sensor/area networks.
Blind channel identication of nonlinear folding mixing model
Institute of Scientific and Technical Information of China (English)
Su Yong; Xu Shangzhi; Ye Zhongfu
2006-01-01
Signals from multi-sensor systems are often mixtures of (statistically) independent sources by unknown mixing method. Blind source separation(BSS) and independent component analysis(ICA) are the methods to identify/recover the channels and the sources. BSS/ICA of nonlinear mixing models are difficult problems. For instance, the post-nonlinear model has been studied by several authors. It is noticed that in most cases, the proposed models are always with an invertible mixing. According to this fact there is an interesting question: how about the situation of the non-invertible non-linear mixing in BSS or ICA? A new simple non-linear mixing model is proposed with a kind of non-invertible mixing, the folding mixing, and method to identify its channel, blindly.
Quiet Sun coronal heating statistical model
Krasnoselskikh, V V; Lefebvre, B; Vilmer, N
2002-01-01
To describe statistical properties of solar coronal heating by microflares, nanoflares, and even smaller events, we consider a cellular automata model subject to uniform small scale driving and dissipation. The model consists of two elements, the magnetic field source supposed to be associated with the small scale hydrodynamic turbulence convected from the photosphere and local dissipation of small scale currents. The dissipation is assumed to be provided by either anomalous resistivity, when the current density exceeds a certain threshold value, or by the magnetic reconnection. The main problem considered is how the statistical characteristics of dissipated energy flow depend upon characteristics of the magnetic field source and on physical mechanism responsible for the magnetic field dissipation. As the threshold value of current is increased, we observe the transition from Gaussian statistics to power-law type. In addition, we find that the dissipation provided by reconnection results in stronger deviation...
Energy Technology Data Exchange (ETDEWEB)
Mello, P.A.; Pereyra, P.; Seligman, T.H.
1985-05-01
Ensembles of scattering S-matrices have been used in the past to describe the statistical fluctuations exhibited by many nuclear-reaction cross sections as a function of energy. In recent years, there have been attempts to construct these ensembles explicitly in terms of S, by directly proposinng a statistical law for S. In the present paper, it is shown that, for an arbitrary number of channels, one can incorporate, in the ensemble of S-matrices, the conditions of flux conservation, time-reversal invariance, causality, ergodicity, and the requirement that the ensemble average coincide with the optical scattering matrix. Since these conditions do not specify the ensemble uniquely, the ensemble that has maximum information-entropy is dealt with among those that satisfy the above requirements. Some applications to few-channel problems and comparisons to Monte-Carlo calculations are presented.
International Nuclear Information System (INIS)
We describe a method for computing linear observer statistics for maximum a posteriori (MAP) reconstructions of PET images. The method is based on a theoretical approximation for the mean and covariance of MAP reconstructions. In particular, we derive here a closed form for the channelized Hotelling observer (CHO) statistic applied to 2D MAP images. We show reasonably good correspondence between these theoretical results and Monte Carlo studies. The accuracy and low computational cost of the approximation allow us to analyze the observer performance over a wide range of operating conditions and parameter settings for the MAP reconstruction algorithm
Statistical analysis of the factors induced defect formation during welding tubes for fuel channels
International Nuclear Information System (INIS)
Using as an example the welding of the mounting joints of 160x10mm 08Kh18N10T steel tubes for fuel channels of the RBM-K-1000 reactor, considered is the effect of the three main factors, causing formation of the defects in welded joints: constructional, technological and organizational. Emperic equations of the defectiveness and the above mentioned factors for the statistical analysis of the welding quality during the mounting of nuclear power stations are suggested
Topology for Statistical Modeling of Petascale Data
Energy Technology Data Exchange (ETDEWEB)
Bennett, Janine Camille [Sandia National Lab. (SNL-CA), Livermore, CA (United States); Pebay, Philippe Pierre [Sandia National Lab. (SNL-CA), Livermore, CA (United States); Pascucci, Valerio [Univ. of Utah, Salt Lake City, UT (United States); Levine, Joshua [Univ. of Utah, Salt Lake City, UT (United States); Gyulassy, Attila [Univ. of Utah, Salt Lake City, UT (United States); Rojas, Maurice [Texas A & M Univ., College Station, TX (United States)
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 Modeling Efforts for Headspace Gas
Energy Technology Data Exchange (ETDEWEB)
Weaver, Brian Phillip [Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
2016-03-17
The purpose of this document is to describe the statistical modeling effort for gas concentrations in WIPP storage containers. The concentration (in ppm) of CO_{2} in the headspace volume of standard waste box (SWB) 68685 is shown. A Bayesian approach and an adaptive Metropolis-Hastings algorithm were used.
Topology for Statistical Modeling of Petascale Data.
Energy Technology Data Exchange (ETDEWEB)
Bennett, Janine Camille; Pebay, Philippe Pierre; Pascucci, Valerio; Levine, Joshua; Gyulassy, Attila; Rojas, Joseph Maurice
2014-07-01
This document presents current technical progress and dissemination of results for the Mathematics for Analysis of Petascale Data (MAPD) project titled "Topology for Statistical Modeling of Petascale Data", funded by the Office of Science Advanced Scientific Computing Research (ASCR) Applied Math program.
Statistical model semiquantitatively approximates arabinoxylooligosaccharides' structural diversity
DEFF Research Database (Denmark)
Dotsenko, Gleb; Nielsen, Michael Krogsgaard; Lange, Lene
2016-01-01
A statistical model describing the random distribution of substituted xylopyranosyl residues in arabinoxylooligosaccharides is suggested and compared with existing experimental data. Structural diversity of arabinoxylooligosaccharides of various length, originating from different arabinoxylans...... only for prediction and quantification of arabinoxylooligosaccharides' structural diversity, but also for estimate of yield and selection of the optimal source of arabinoxylan for production of arabinoxylooligosaccharides with desired structural features....
STATISTICAL MODELS OF REPRESENTING INTELLECTUAL CAPITAL
Directory of Open Access Journals (Sweden)
Andreea Feraru
2016-07-01
Full Text Available This article entitled Statistical Models of Representing Intellectual Capital approaches and analyses the concept of intellectual capital, as well as the main models which can support enterprisers/managers in evaluating and quantifying the advantages of intellectual capital. Most authors examine intellectual capital from a static perspective and focus on the development of its various evaluation models. In this chapter we surveyed the classical static models: Sveiby, Edvisson, Balanced Scorecard, as well as the canonical model of intellectual capital. Among the group of static models for evaluating organisational intellectual capital the canonical model stands out. This model enables the structuring of organisational intellectual capital in: human capital, structural capital and relational capital. Although the model is widely spread, it is a static one and can thus create a series of errors in the process of evaluation, because all the three entities mentioned above are not independent from the viewpoint of their contents, as any logic of structuring complex entities requires.
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
NUMERICAL MODELING OF COMPOUND CHANNEL FLOWS
Institute of Scientific and Technical Information of China (English)
无
2002-01-01
A numerical model capable of predicting flow characteristics in a compound channel was established with the 3-D steady continuity and momentum equations along with the transport equations for turbulence kinetic energy and dissipation rate. Closure was achieved with the aid of algebraic relations for turbulent shear stresses. The above equations were discretized with implicit difference approach and solved with a step method along the flow direction. The computational results showing the lateral distribution of vertical average velocities and the latio of total flow in the compound channel agree well with the available experimental data.
Pitfalls in statistical landslide susceptibility modelling
Schröder, Boris; Vorpahl, Peter; Märker, Michael; Elsenbeer, Helmut
2010-05-01
The use of statistical methods is a well-established approach to predict landslide occurrence probabilities and to assess landslide susceptibility. This is achieved by applying statistical methods relating historical landslide inventories to topographic indices as predictor variables. In our contribution, we compare several new and powerful methods developed in machine learning and well-established in landscape ecology and macroecology for predicting the distribution of shallow landslides in tropical mountain rainforests in southern Ecuador (among others: boosted regression trees, multivariate adaptive regression splines, maximum entropy). Although these methods are powerful, we think it is necessary to follow a basic set of guidelines to avoid some pitfalls regarding data sampling, predictor selection, and model quality assessment, especially if a comparison of different models is contemplated. We therefore suggest to apply a novel toolbox to evaluate approaches to the statistical modelling of landslide susceptibility. Additionally, we propose some methods to open the "black box" as an inherent part of machine learning methods in order to achieve further explanatory insights into preparatory factors that control landslides. Sampling of training data should be guided by hypotheses regarding processes that lead to slope failure taking into account their respective spatial scales. This approach leads to the selection of a set of candidate predictor variables considered on adequate spatial scales. This set should be checked for multicollinearity in order to facilitate model response curve interpretation. Model quality assesses how well a model is able to reproduce independent observations of its response variable. This includes criteria to evaluate different aspects of model performance, i.e. model discrimination, model calibration, and model refinement. In order to assess a possible violation of the assumption of independency in the training samples or a possible
Statistical shape and appearance models of bones.
Sarkalkan, Nazli; Weinans, Harrie; Zadpoor, Amir A
2014-03-01
When applied to bones, statistical shape models (SSM) and statistical appearance models (SAM) respectively describe the mean shape and mean density distribution of bones within a certain population as well as the main modes of variations of shape and density distribution from their mean values. The availability of this quantitative information regarding the detailed anatomy of bones provides new opportunities for diagnosis, evaluation, and treatment of skeletal diseases. The potential of SSM and SAM has been recently recognized within the bone research community. For example, these models have been applied for studying the effects of bone shape on the etiology of osteoarthritis, improving the accuracy of clinical osteoporotic fracture prediction techniques, design of orthopedic implants, and surgery planning. This paper reviews the main concepts, methods, and applications of SSM and SAM as applied to bone.
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...
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.
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 ...
Statistical Modelling of Wind Proles - Data Analysis and Modelling
DEFF Research Database (Denmark)
Jónsson, Tryggvi; Pinson, Pierre
The aim of the analysis presented in this document is to investigate whether statistical models can be used to make very short-term predictions of wind profiles.......The aim of the analysis presented in this document is to investigate whether statistical models can be used to make very short-term predictions of wind profiles....
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 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...
Modelling debris flows down general channels
Directory of Open Access Journals (Sweden)
S. P. Pudasaini
2005-01-01
Full Text Available This paper is an extension of the single-phase cohesionless dry granular avalanche model over curved and twisted channels proposed by Pudasaini and Hutter (2003. It is a generalisation of the Savage and Hutter (1989, 1991 equations based on simple channel topography to a two-phase fluid-solid mixture of debris material. Important terms emerging from the correct treatment of the kinematic and dynamic boundary condition, and the variable basal topography are systematically taken into account. For vanishing fluid contribution and torsion-free channel topography our new model equations exactly degenerate to the previous Savage-Hutter model equations while such a degeneration was not possible by the Iverson and Denlinger (2001 model, which, in fact, also aimed to extend the Savage and Hutter model. The model equations of this paper have been rigorously derived; they include the effects of the curvature and torsion of the topography, generally for arbitrarily curved and twisted channels of variable channel width. The equations are put into a standard conservative form of partial differential equations. From these one can easily infer the importance and influence of the pore-fluid-pressure distribution in debris flow dynamics. The solid-phase is modelled by applying a Coulomb dry friction law whereas the fluid phase is assumed to be an incompressible Newtonian fluid. Input parameters of the equations are the internal and bed friction angles of the solid particles, the viscosity and volume fraction of the fluid, the total mixture density and the pore pressure distribution of the fluid at the bed. Given the bed topography and initial geometry and the initial velocity profile of the debris mixture, the model equations are able to describe the dynamics of the depth profile and bed parallel depth-averaged velocity distribution from the initial position to the final deposit. A shock capturing, total variation diminishing numerical scheme is implemented to
Statistical Language Model for Chinese Text Proofreading
Institute of Scientific and Technical Information of China (English)
张仰森; 曹元大
2003-01-01
Statistical language modeling techniques are investigated so as to construct a language model for Chinese text proofreading. After the defects of n-gram model are analyzed, a novel statistical language model for Chinese text proofreading is proposed. This model takes full account of the information located before and after the target word wi, and the relationship between un-neighboring words wi and wj in linguistic environment(LE). First, the word association degree between wi and wj is defined by using the distance-weighted factor, wj is l words apart from wi in the LE, then Bayes formula is used to calculate the LE related degree of word wi, and lastly, the LE related degree is taken as criterion to predict the reasonability of word wi that appears in context. Comparing the proposed model with the traditional n-gram in a Chinese text automatic error detection system, the experiments results show that the error detection recall rate and precision rate of the system have been improved.
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.
Institute of Scientific and Technical Information of China (English)
Zhao Zhi-Jin; Zheng Shi-Lian; Xu Chun-Yun; Kong Xian-Zheng
2007-01-01
Hidden Markov models (HMMs) have been used to model burst error sources of wireless channels. This paper proposes a hybrid method of using genetic algorithm (GA) and simulated annealing (SA) to train HMM for discrete channel modelling. The proposed method is compared with pure GA, and experimental results show that the HMMs trained by the hybrid method can better describe the error sequences due to SA's ability of facilitating hill-climbing at the later stage of the search. The burst error statistics of the HMMs trained by the proposed method and the corresponding error sequences are also presented to validate the proposed method.
Strings, Integrable Systems, Geometry and Statistical Models
Marshakov, A
2004-01-01
The role of integrable systems in string theory is discussed. We remind old examples of the correspondence between stringy partition functions or effective actions and integrable equations, based on effective application of the matrix model technique. Then we turn to a new example, coming from the Nekrasov deformation of the Seiberg-Witten prepotential. In the last case the deformed theory is described by a different statistical model, which becomes equivalent to a partition function of a topological string. The full partition function of string theory arises therefore always as a certain "quantization" of its quasiclassical geometry.
A Wideband Channel Model for Intravehicular Nomadic Systems
Directory of Open Access Journals (Sweden)
François Bellens
2011-01-01
Full Text Available The increase in electronic entertainment equipments within vehicles has rendered the idea of replacing the wired links with intra-vehicle personal area networks. Ultra-wideband (UWB seems an appropriate candidate technology to meet the required data rates for interconnecting such devices. In particular, the multiband OFDM (MB-OFDM is able to provide very high transfer rates (up to 480 MBps over relatively short distances and low transmit power. In order to evaluate the performances of UWB systems within vehicles, a reliable channel model is needed. In this paper, a nomadic system where a base station placed in the center of the dashboard wants to communicate with fixed devices placed at the rear seat is investigated. A single-input single-output (SISO channel model for intra-vehicular communication (IVC systems is proposed, based on reverberation chamber theory. The model is based on measurements conducted in real traffic conditions, with a varying number of passengers in the car. Temporal variations of the wireless channels are also characterized and parametrized. The proposed model is validated by comparing model-independent statistics with the measurements.
A 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...
Statistical Analysis of Multipath Fading Channels Using Generalizations of Shot Noise
Directory of Open Access Journals (Sweden)
Djouadi SeddikM
2008-01-01
Full Text Available Abstract This paper provides a connection between the shot-noise analysis of Rice and the statistical analysis of multipath fading wireless channels when the received signals are a low-pass signal and a bandpass signal. Under certain conditions, explicit expressions are obtained for autocorrelation functions, power spectral densities, and moment-generating functions. In addition, a central limit theorem is derived identifying the mean and covariance of the received signals, which is a generalization of Campbell_s theorem. The results are easily applicable to transmitted signals which are random and to CDMA signals.
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.
Effects of roughness on density-weighted particle statistics in turbulent channel flows
Energy Technology Data Exchange (ETDEWEB)
Milici, Barbara [Faculty of Engineering and Architecture, Cittadella Universitaria - 94100 - Enna (Italy)
2015-12-31
The distribution of inertial particles in turbulent flows is strongly influenced by the characteristics of the coherent turbulent structures which develop in the carrier flow field. In wall-bounded flows, these turbulent structures, which control the turbulent regeneration cycles, are strongly affected by the roughness of the wall, nevertheless its effects on the particle transport in two-phase turbulent flows has been still poorly investigated. The issue is discussed here by addressing DNS combined with LPT to obtain statistics of velocity and preferential accumulation of a dilute dispersion of heavy particles in a turbulent channel flow, bounded by irregular two-dimensional rough surfaces, in the one-way coupling regime.
Does the choice of the forcing term affect flow statistics in DNS of turbulent channel flow?
Quadrio, Maurizio; Frohnapfel, Bettina; Hasegawa, Yosuke
2016-01-01
We seek possible statistical consequences of the way a forcing term is added to the Navier--Stokes equations in the Direct Numerical Simulation (DNS) of incompressible channel flow. Simulations driven by constant flow rate, constant pressure gradient and constant power input are used to build large databases, and in particular to store the complete temporal trace of the wall-shear stress for later analysis. As these approaches correspond to different dynamical systems, it can in principle be envisaged that these differences are reflect by certain statistics of the turbulent flow field. The instantaneous realizations of the flow in the various simulations are obviously different, but, as expected, the usual one-point, one-time statistics do not show any appreciable difference. However, the PDF for the fluctuations of the streamwise component of wall friction reveals that the simulation with constant flow rate presents lower probabilities for extreme events of large positive friction. The low probability value of such events explains their negligible contribution to the commonly computed statistics; however, the very existence of a difference in the PDF demonstrates that the forcing term is not entirely uninfluential. Other statistics for wall-based quantities (the two components of friction and pressure) are examined; in particular spatio-temporal autocorrelations show small differences at large temporal separations, where unfortunately the residual statistical uncertainty is still of the same order of the observed difference. Hence we suggest that the specific choice of the forcing term does not produce important statistical consequences, unless one is interested in the strongest events of high wall friction, that are underestimated by a simulation run at constant flow rate.
Directory of Open Access Journals (Sweden)
G. Sofia
2011-05-01
Full Text Available A statistical approach to LiDAR derived topographic attributes for the automatic extraction of channel network and for the choice of the scale to apply for parameter evaluation is presented in this paper. The basis of this approach is to use distribution analysis and statistical descriptors to identify channels where terrain geometry denotes significant convergences. Two case study areas with different morphology and degree of organization are used with their 1 m LiDAR Digital Terrain Models (DTMs. Topographic attribute maps (curvature and openness for various window sizes are derived from the DTMs in order to detect surface convergences. A statistical analysis on value distributions considering each window size is carried out for the choice of the optimum kernel. We propose a three-step method to extract the network based (a on the normalization and overlapping of openness and minimum curvature to highlight the more likely surface convergences, (b a weighting of the upslope area according to these normalized maps to identify drainage flow paths and flow accumulation consistent with terrain geometry, (c the standard score normalization of the weighted upslope area and the use of standard score values as non subjective threshold for channel network identification. As a final step for optimal definition and representation of the whole network, a noise-filtering and connection procedure is applied. The advantage of the proposed methodology, and the efficiency and accurate localization of extracted features are demonstrated using LiDAR data of two different areas and comparing both extractions with field surveyed networks.
Modelling of meander migration in an incised channel
Institute of Scientific and Technical Information of China (English)
Jianchun HUANG; Blair P GREIMANN; Timothy J RANDLE
2014-01-01
An updated linear computer model for meandering rivers with incision has been developed. The model simulates the bed topography, flow field, and bank erosion rate in an incised meandering channel. In a scenario where the upstream sediment load decreases (e.g., after dam closure or soil conservation), alluvial river experiences cross section deepening and slope flattening. The channel migration rate might be affected in two ways:decreased channel slope and steeped bank height. The proposed numerical model combines the traditional one-dimensional (1D) sediment transport model in simulating the channel erosion and the linear model for channel meandering. A non-equilibrium sediment transport model is used to update the channel bed elevation and gradations. A linear meandering model was used to calculate the channel alignment and bank erosion/accretion, which in turn was used by the 1D sediment transport model. In the 1D sediment transport model, the channel bed elevation and gradations are represented in each channel cross section. In the meandering model, the bed elevation and gradations are stored in two dimensional (2D) cells to represent the channel and terrain properties (elevation and gradation). A new method is proposed to exchange information regarding bed elevations and bed material fractions between 1D river geometry and 2D channel and terrain. The ability of the model is demonstrated using the simulation of the laboratory channel migration of Friedkin in which channel incision occurs at the upstream end.
Electronic noise modeling in statistical iterative reconstruction.
Xu, Jingyan; Tsui, Benjamin M W
2009-06-01
We consider electronic noise modeling in tomographic image reconstruction when the measured signal is the sum of a Gaussian distributed electronic noise component and another random variable whose log-likelihood function satisfies a certain linearity condition. Examples of such likelihood functions include the Poisson distribution and an exponential dispersion (ED) model that can approximate the signal statistics in integration mode X-ray detectors. We formulate the image reconstruction problem as a maximum-likelihood estimation problem. Using an expectation-maximization approach, we demonstrate that a reconstruction algorithm can be obtained following a simple substitution rule from the one previously derived without electronic noise considerations. To illustrate the applicability of the substitution rule, we present examples of a fully iterative reconstruction algorithm and a sinogram smoothing algorithm both in transmission CT reconstruction when the measured signal contains additive electronic noise. Our simulation studies show the potential usefulness of accurate electronic noise modeling in low-dose CT applications.
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 ...
Statistical Model Checking for Biological Systems
DEFF Research Database (Denmark)
David, Alexandre; Larsen, Kim Guldstrand; Legay, Axel;
2014-01-01
Statistical Model Checking (SMC) is a highly scalable simulation-based verification approach for testing and estimating the probability that a stochastic system satisfies a given linear temporal property. The technique has been applied to (discrete and continuous time) Markov chains, stochastic...... timed automata and most recently hybrid systems using the tool Uppaal SMC. In this paper we enable the application of SMC to complex biological systems, by combining Uppaal SMC with ANIMO, a plugin of the tool Cytoscape used by biologists, as well as with SimBiology®, a plugin of Matlab to simulate...
Turbulent structures and statistics in turbulent channel flow with two-dimensional slits
Energy Technology Data Exchange (ETDEWEB)
Makino, Soichiro [Department of Mechanical Engineering, Tokyo University of Science, Noda-shi, Chiba 278-8510 (Japan)], E-mail: a7502126@rs.noda.tus.ac.jp; Iwamoto, Kaoru; Kawamura, Hiroshi [Department of Mechanical Engineering, Tokyo University of Science, Noda-shi, Chiba 278-8510 (Japan)
2008-06-15
Direct numerical simulation (DNS, hereafter) of turbulent channel flow with periodic two-dimensional slits has been performed in order to investigate the turbulent statistics and the turbulent structures behind the slits. The Reynolds numbers based on the friction velocity and the channel half width are 10-1500. In the wake region, the mean flow becomes asymmetric with respect to the centerline of the geometry through the Coanda effect. Large-scale vortices are generated at the height of the slit edges. These vortices become deformed in various scenarios and break up into disordered small-scale structures in the shear layers behind the slit. The small-scale vortices are convected toward the channel center. The budgets of the Reynolds stresses have been computed. The significant differences are found between the budgets in this study and those in a backward-facing step turbulence. The positive Reynolds shear stress u'v'-bar is observed owing to the flow contraction just behind the slit. The wake region was classified into several categories based upon the budgets of the Reynolds stresses and turbulent structures.
Projecting Policy Effects with Statistical Models Projecting Policy Effects with Statistical Models
Directory of Open Access Journals (Sweden)
Christopher Sims
1988-03-01
Full Text Available This paper attempts to briefly discus the current frontiers in quantitative modeling for forecastina and policy analvsis. It does so by summarizing some recent developmenrs in three areas: reduced form forecasting models; theoretical models including elements of stochastic optimization; and identification. In the process, the paper tries to provide some remarks on the direction we seem to be headed. Projecting Policy Effects with Statistical Models
Irshad, Humayun; Roux, Ludovic; Racoceanu, Daniel
2013-01-01
Accurate counting of mitosis in breast cancer histopathology plays a critical role in the grading process. Manual counting of mitosis is tedious and subject to considerable inter- and intra-reader variations. This work aims at improving the accuracy of mitosis detection by selecting the color channels that better capture the statistical and morphological features having mitosis discrimination from other objects. The proposed framework includes comprehensive analysis of first and second order statistical features together with morphological features in selected color channels and a study on balancing the skewed dataset using SMOTE method for increasing the predictive accuracy of mitosis classification. The proposed framework has been evaluated on MITOS data set during an ICPR 2012 contest and ranked second from 17 finalists. The proposed framework achieved 74% detection rate, 70% precision and 72% F-Measure. In future work, we plan to apply our mitosis detection tool to images produced by different types of slide scanners, including multi-spectral and multi-focal microscopy.
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...
Capecelatro, Jesse; Desjardins, Olivier; Fox, Rodney O.
2016-03-01
Simulations of strongly coupled (i.e., high-mass-loading) fluid-particle flows in vertical channels are performed with the purpose of understanding the fundamental physics of wall-bounded multiphase turbulence. The exact Reynolds-averaged (RA) equations for high-mass-loading suspensions are presented, and the unclosed terms that are retained in the context of fully developed channel flow are evaluated in an Eulerian-Lagrangian (EL) framework for the first time. A key distinction between the RA formulation presented in the current work and previous derivations of multiphase turbulence models is the partitioning of the particle velocity fluctuations into spatially correlated and uncorrelated components, used to define the components of the particle-phase turbulent kinetic energy (TKE) and granular temperature, respectively. The adaptive spatial filtering technique developed in our previous work for homogeneous flows [J. Capecelatro, O. Desjardins, and R. O. Fox, "Numerical study of collisional particle dynamics in cluster-induced turbulence," J. Fluid Mech. 747, R2 (2014)] is shown to accurately partition the particle velocity fluctuations at all distances from the wall. Strong segregation in the components of granular energy is observed, with the largest values of particle-phase TKE associated with clusters falling near the channel wall, while maximum granular temperature is observed at the center of the channel. The anisotropy of the Reynolds stresses both near the wall and far away is found to be a crucial component for understanding the distribution of the particle-phase volume fraction. In Part II of this paper, results from the EL simulations are used to validate a multiphase Reynolds-stress turbulence model that correctly predicts the wall-normal distribution of the two-phase turbulence statistics.
Physical-statistical modeling in geophysics
Berliner, L. Mark
2003-12-01
Two powerful formulas have been available to scientists for more than two centuries: Newton's second law, providing a foundation for classical physics, and Bayes's theorem, prescribing probabilistic learning about unknown quantities based on observations. For the most part the use of these formulas has been separated, with Newton being the more dominant in geophysics. This separation is arguably surprising since numerous sources of uncertainty arise in the application of classical physics in complex situations. One explanation for the separation is the difficulty in implementing Bayesian analysis in complex settings. However, recent advances in both modeling strategies and computational tools have contributed to a significant change in the scope and feasibility of Bayesian analysis. This paradigm provides opportunities for the combination of physical reasoning and observational data in a coherent analysis framework but in a fashion which manages the uncertainties in both information sources. A key to the modeling is the hierarchical viewpoint, in which separate statistical models are developed for the process variables studied and for the observations conditional on those variables. Modeling process variables in this way enables the incorporation of physics across a spectrum of levels of intensity, ranging from a qualitative use of physical reasoning to a strong reliance on numerical models. Selected examples from this spectrum are reviewed. So far as the laws of mathematics refer to reality, they are not certain. And so far as they are certain, they do not refer to reality.Albert Einstein (1921)
Atmospheric corrosion: statistical validation of models
International Nuclear Information System (INIS)
In this paper we discuss two different methods for validation of regression models, applied to corrosion data. One of them is based on the correlation coefficient and the other one is the statistical test of lack of fit. Both methods are used here to analyse fitting of bi logarithmic model in order to predict corrosion for very low carbon steel substrates in rural and urban-industrial atmospheres in Uruguay. Results for parameters A and n of the bi logarithmic model are reported here. For this purpose, all repeated values were used instead of using average values as usual. Modelling is carried out using experimental data corresponding to steel substrates under the same initial meteorological conditions ( in fact, they are put in the rack at the same time). Results of correlation coefficient are compared with the lack of it tested at two different signification levels (α=0.01 and α=0.05). Unexpected differences between them are explained and finally, it is possible to conclude, at least in the studied atmospheres, that the bi logarithmic model does not fit properly the experimental data. (Author) 18 refs
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
Integrated statistical modelling of spatial landslide probability
Mergili, M.; Chu, H.-J.
2015-09-01
Statistical methods are commonly employed to estimate spatial probabilities of landslide release at the catchment or regional scale. Travel distances and impact areas are often computed by means of conceptual mass point models. The present work introduces a fully automated procedure extending and combining both concepts to compute an integrated spatial landslide probability: (i) the landslide inventory is subset into release and deposition zones. (ii) We employ a simple statistical approach to estimate the pixel-based landslide release probability. (iii) We use the cumulative probability density function of the angle of reach of the observed landslide pixels to assign an impact probability to each pixel. (iv) We introduce the zonal probability i.e. the spatial probability that at least one landslide pixel occurs within a zone of defined size. We quantify this relationship by a set of empirical curves. (v) The integrated spatial landslide probability is defined as the maximum of the release probability and the product of the impact probability and the zonal release probability relevant for each pixel. We demonstrate the approach with a 637 km2 study area in southern Taiwan, using an inventory of 1399 landslides triggered by the typhoon Morakot in 2009. We observe that (i) the average integrated spatial landslide probability over the entire study area corresponds reasonably well to the fraction of the observed landside area; (ii) the model performs moderately well in predicting the observed spatial landslide distribution; (iii) the size of the release zone (or any other zone of spatial aggregation) influences the integrated spatial landslide probability to a much higher degree than the pixel-based release probability; (iv) removing the largest landslides from the analysis leads to an enhanced model performance.
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.
Thermonuclear reaction rates from statistical model calculations
International Nuclear Information System (INIS)
The quality of statistical model predictions for thermonuclear reaction rates is based on the accuracy of theoretical determinations of particle and photon transmission coefficients as well as of level densities of excited states in nuclei. The square well potentials for neutrons, protons and alpha particles, used in previous approaches, have been replaced in this work by realistic optical potentials which reproduce nicely experimental data, e.g. the neutron strength functions. E1 γ-transitions are calculated in the framework of the Giant Dipole Resonance model. The width ΓGDR(A.Z) is based on a macroscopic-microscopic model which results in a good agreement with the observed shell structure. The nuclear level densities are still computed with the aid of the back-shifted Fermi-gas model. The relation between the level density parameters a and δ and the shell correction term of nuclear mass formulae is obtained by using the most recent experimental level densities at the neutron separation energy. Cross sections predictions obtained within this framework are expected to lie safety within a factor of 2 of experimental values
Statistical Shape Modeling of Cam Femoroacetabular Impingement
Energy Technology Data Exchange (ETDEWEB)
Harris, Michael D.; Dater, Manasi; Whitaker, Ross; Jurrus, Elizabeth R.; Peters, Christopher L.; Anderson, Andrew E.
2013-10-01
In this study, statistical shape modeling (SSM) was used to quantify three-dimensional (3D) variation and morphologic differences between femurs with and without cam femoroacetabular impingement (FAI). 3D surfaces were generated from CT scans of femurs from 41 controls and 30 cam FAI patients. SSM correspondence particles were optimally positioned on each surface using a gradient descent energy function. Mean shapes for control and patient groups were defined from the resulting particle configurations. Morphological differences between group mean shapes and between the control mean and individual patients were calculated. Principal component analysis was used to describe anatomical variation present in both groups. The first 6 modes (or principal components) captured statistically significant shape variations, which comprised 84% of cumulative variation among the femurs. Shape variation was greatest in femoral offset, greater trochanter height, and the head-neck junction. The mean cam femur shape protruded above the control mean by a maximum of 3.3 mm with sustained protrusions of 2.5-3.0 mm along the anterolateral head-neck junction and distally along the anterior neck, corresponding well with reported cam lesion locations and soft-tissue damage. This study provides initial evidence that SSM can describe variations in femoral morphology in both controls and cam FAI patients and may be useful for developing new measurements of pathological anatomy. SSM may also be applied to characterize cam FAI severity and provide templates to guide patient-specific surgical resection of bone.
Physical and Statistical Modeling of Saturn's Troposphere
Yanamandra-Fisher, Padmavati A.; Braverman, Amy J.; Orton, Glenn S.
2002-12-01
The 5.2-μm atmospheric window on Saturn is dominated by thermal radiation and weak gaseous absorption, with a 20% contribution from sunlight reflected from clouds. The striking variability displayed by Saturn's clouds at 5.2 μm and the detection of PH3 (an atmospheric tracer) variability near or below the 2-bar level and possibly at lower pressures provide salient constraints on the dynamical organization of Saturn's atmosphere by constraining the strength of vertical motions at two levels across the disk. We analyse the 5.2-μm spectra of Saturn by utilising two independent methods: (a) physical models based on the relevant atmospheric parameters and (b) statistical analysis, based on principal components analysis (PCA), to determine the influence of the variation of phosphine and the opacity of clouds deep within Saturn's atmosphere to understand the dynamics in its atmosphere.
Facial Expression Biometrics Using Statistical Shape Models
Quan, Wei; Matuszewski, Bogdan J.; Shark, Lik-Kwan; Ait-Boudaoud, Djamel
2009-12-01
This paper describes a novel method for representing different facial expressions based on the shape space vector (SSV) of the statistical shape model (SSM) built from 3D facial data. The method relies only on the 3D shape, with texture information not being used in any part of the algorithm, that makes it inherently invariant to changes in the background, illumination, and to some extent viewing angle variations. To evaluate the proposed method, two comprehensive 3D facial data sets have been used for the testing. The experimental results show that the SSV not only controls the shape variations but also captures the expressive characteristic of the faces and can be used as a significant feature for facial expression recognition. Finally the paper suggests improvements of the SSV discriminatory characteristics by using 3D facial sequences rather than 3D stills.
Facial Expression Biometrics Using Statistical Shape Models
Directory of Open Access Journals (Sweden)
Djamel Ait-Boudaoud
2009-01-01
Full Text Available This paper describes a novel method for representing different facial expressions based on the shape space vector (SSV of the statistical shape model (SSM built from 3D facial data. The method relies only on the 3D shape, with texture information not being used in any part of the algorithm, that makes it inherently invariant to changes in the background, illumination, and to some extent viewing angle variations. To evaluate the proposed method, two comprehensive 3D facial data sets have been used for the testing. The experimental results show that the SSV not only controls the shape variations but also captures the expressive characteristic of the faces and can be used as a significant feature for facial expression recognition. Finally the paper suggests improvements of the SSV discriminatory characteristics by using 3D facial sequences rather than 3D stills.
Global precedence, spatial frequency channels, and the statistics of natural images.
Hughes, H C; Nozawa, G; Kitterle, F
1996-01-01
that assume the channels are independent. In view of previous work showing that global precedence depends upon the low frequency content of the stimuli, we suggest that low spatial frequencies represent the sine qua non for the dominance of configurational cues in human pattern perception, and that this configurational dominance reflects the microgenesis of visual pattern perception. This general view of the temporal dynamics of visual pattern recognition is discussed, is considered from an evolutionary perspective, and is related to certain statistical regularities in natural scenes. Potential adaptive advantages of an interactive parallel architecture that confers an initial processing advantage to low resolution information are explored.
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.
Baroclinic Channel Model in Fluid Dynamics
Directory of Open Access Journals (Sweden)
Kharatti Lal
2016-02-01
Full Text Available A complex flow structure is studied using a 2-dimentional baroclinic channel model Unsteady Navier - stokes equation coupled with equation of thermal energy ,salinity and the equation of state are implemented .System closure is achieved through a modified Prandtl, s mixing length formulation of turbulence dissipation The model is applied in a region where the fluid flow is effected by various forcing equation .In this case ,flow is estuarine region affected by diurnal tide and the fresh water inflow in to the estuary and a submerged structure is considered giving possible insight in to stress effects on submerged structure .the result show that in the time evolution of the vertical velocity along downstream edge changes sign from negative to positive .as the dike length increases the primary cell splits and flow becomes turbulent du e to the non-linear effect caused by the dike .these are found to agree favourably with result published in the open literature.
Mathematical Modeling on Open Limestone Channel
Bandstra, Joel; Wu, Naiyi
2014-01-01
Acid mine drainage (AMD) is the outflow of acidic water from metal mines or coal mines. When exposed to air and water, metal sulfides from the deposits of the mines are oxidized and produce acid, metal ions and sulfate, which lower the pH value of the water. An open limestone channel (OLC) is a passive and low cost way to neutralize AMD. The dissolution of calcium into the water increases the pH value of the solution. A differential equation model is numerically solved to predict the variation of concentration of each species in the OLC solution. The diffusion of Calcium due to iron precipitates is modeled by a linear equation. The results give the variation of pH value and the concentration of Calcium.
Modeling of channel erosion downstream spillway dams
Directory of Open Access Journals (Sweden)
M.A. Mikhalev
2013-03-01
Full Text Available The channel erosion downstream spillway dams in non-cohesive materials has been analyzed from the viewpoint of methods of similarity and dimension theory. The obtained criterion equation connects the maximum depth of the local erosion with its determining parameters: length of concrete lining of bed in the down water of the spillway dam; Froude number at the contracted cross section; Archimedes and Reynolds criterions; submergence factor of hydraulic jump. The problem may be formulated as follows: the geometric size of the structure, kinematics and dynamics of the flows in the model are similar to that in the prototype. Conditions under which the characteristic depth of the local erosion in the model would be recomputed into the prototype, like any geometric size, are being discussed.
On Cooperative Beamforming Based on Second-Order Statistics of Channel State Information
Li, Jiangyuan; Poor, H Vincent
2010-01-01
Cooperative beamforming in relay networks is considered, in which a source transmits to its destination with the help of a set of cooperating nodes. The source first transmits locally. The cooperating nodes that receive the source signal retransmit a weighted version of it in an amplify-and-forward (AF) fashion. Assuming knowledge of the second-order statistics of the channel state information, beamforming weights are determined so that the signal-to-noise ratio (SNR) at the destination is maximized subject to two different power constraints, i.e., a total (source and relay) power constraint, and individual relay power constraints. For the former constraint, the original problem is transformed into a problem of one variable, which can be solved via Newton's method. For the latter constraint, the original problem is transformed into a homogeneous quadratically constrained quadratic programming (QCQP) problem. In this case, it is shown that when the number of relays does not exceed three the global solution can...
RooStatsCms: a tool for analysis modelling, combination and statistical studies
Piparo, Danilo; Quast, Gunter
2009-01-01
RooStatsCms is an object oriented statistical framework based on the RooFit technology. Its scope is to allow the modelling, statistical analysis and combination of multiple search channels for new phenomena in High Energy Physics. It provides a variety of methods described in literature implemented as classes, whose design is oriented to the execution of multiple CPU intensive jobs on batch systems or on the Grid.
Pathway Model and Nonextensive Statistical Mechanics
Mathai, A. M.; Haubold, H. J.; Tsallis, C.
2015-12-01
The established technique of eliminating upper or lower parameters in a general hypergeometric series is profitably exploited to create pathways among confluent hypergeometric functions, binomial functions, Bessel functions, and exponential series. One such pathway, from the mathematical statistics point of view, results in distributions which naturally emerge within nonextensive statistical mechanics and Beck-Cohen superstatistics, as pursued in generalizations of Boltzmann-Gibbs statistics.
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.
Channel Modelling for Multiprobe Over-the-Air MIMO Testing
Directory of Open Access Journals (Sweden)
Pekka Kyösti
2012-01-01
a fading emulator, an anechoic chamber, and multiple probes. Creation of a propagation environment inside an anechoic chamber requires unconventional radio channel modelling, namely, a specific mapping of the original models onto the probe antennas. We introduce two novel methods to generate fading emulator channel coefficients; the prefaded signals synthesis and the plane wave synthesis. To verify both methods we present a set of simulation results. We also show that the geometric description is a prerequisite for the original channel model.
Statistical model evaluation of (n,xn) and (n,xnf) cross sections for heavy nuclei
International Nuclear Information System (INIS)
A method for a statistical model evaluation of fission, (n,2n) and (n,3n) cross sections from 2MeV to 20MeV neutrons on 237U, 238U, 239U and 239Pu is presented. It consists of the determination of fission width parameters by a fit to known fission cross-sections. This method makes use of neutron transmission coefficients from an adapted coupled channel model. The neutron, fission and radiative widths are calculated by the statistical model including Fermi gas model level densities. Results are given for 237U, 238U, 239U and 239Pu nuclei
Hahn, Y. K.
2016-09-01
A statistical density model for composite system scattering is formulated, by incorporating the ensemble density functional approach in describing the correlation dynamics during the collision. The principal difficulty of non-integrable propagating waves is first resolved by treating the open and closed channels separately; only the closed channel part does allow a density description. The unique open/closed channel separation adopted here allows not only the closed channel Hamiltonian MQ to support integrable densities, but also to establish the important bounds on the scattering amplitude. A modified ensemble energy functional for the MQ is constructed, and the statistical densities ρmtQ for the closed channels are generated. The scattering amplitude is then formulated in terms of the ρmtQ and the coefficients of variation that connect the closed channels to the asymptotic source. Evaluation of the amplitude integrals requires the determinantal functions deduced from the ρmtQ, which also leads to a coupled channel approach. The bound property of the amplitude allows variational optimization of the coefficients. Approximate procedures for securing the orthogonality of the MQ and for evaluation of the source term itself are discussed, including a judicious choice of configurations with zero and one inner-shell holes. Validity of the several critical modifications introduced is assessed.
A model for the distribution channels planning process
Neves, M.F.; Zuurbier, P.; Campomar, M.C.
2001-01-01
Research of existing literature reveals some models (sequence of steps) for companies that want to plan distribution channels. None of these models uses strong contributions from transaction cost economics, bringing a possibility to elaborate on a "distribution channels planning model", with these c
[Model of the selective calcium channel of characean algae].
Lunevskiĭ, V Z; Zherelova, O M; Aleksandrov, A A; Vinokurov, M G; Berestovskiĭ, G N
1980-01-01
The present work was intended to further investigate the selective filter of calcium channel on both a cell membrane and reconstructed channels. For the studies on cell membranes, an inhibitor of chloride channels was chosen (ethacrynic acid) to pass currents only through the calcium channels. On both the cells and reconstructed channels, permeability of ions of different crystal radii and valencies was investigated. The obtained results suggest that the channel represents a wide water pore with a diameter larger than 8 A into which ions go together with the nearest water shell. The values of the maximal currents are given by electrostatic interaction of the ions with the anion center of the channel. A phenomenological two-barrier model of the channel is given which describes the movement of all the ions studied. PMID:6251921
Dividing Streamline Formation Channel Confluences by Physical Modeling
Directory of Open Access Journals (Sweden)
Minarni Nur Trilita
2010-02-01
Full Text Available Confluence channels are often found in open channel network system and is the most important element. The incoming flow from the branch channel to the main cause various forms and cause vortex flow. Phenomenon can cause erosion of the side wall of the channel, the bed channel scour and sedimentation in the downstream confluence channel. To control these problems needed research into the current width of the branch channel. The incoming flow from the branch channel to the main channel flow bounded by a line distributors (dividing streamline. In this paper, the wide dividing streamline observed in the laboratory using a physical model of two open channels, a square that formed an angle of 30º. Observations were made with a variety of flow coming from each channel. The results obtained in the laboratory observation that the width of dividing streamline flow is influenced by the discharge ratio between the channel branch with the main channel. While the results of a comparison with previous studies showing that the observation in the laboratory is smaller than the results of previous research.
Dynamical Properties of Potassium Ion Channels with a Hierarchical Model
Institute of Scientific and Technical Information of China (English)
ZHAN Yong; AN Hai-Long; YU Hui; ZHANG Su-Hua; HAN Ying-Rong
2006-01-01
@@ It is well known that potassium ion channels have higher permeability than K ions, and the permeable rate of a single K ion channel is about 108 ions per second. We develop a hierarchical model of potassium ion channel permeation involving ab initio quantum calculations and Brownian dynamics simulations, which can consistently explain a range of channel dynamics. The results show that the average velocity of K ions, the mean permeable time of K ions and the permeable rate of single channel are about 0.92nm/ns, 4.35ns and 2.30×108 ions/s,respectively.
Integer Set Compression and Statistical Modeling
DEFF Research Database (Denmark)
Larsson, N. Jesper
2014-01-01
enumeration of elements may be arbitrary or random, but where statistics is kept in order to estimate probabilities of elements. We present a recursive subset-size encoding method that is able to benefit from statistics, explore the effects of permuting the enumeration order based on element probabilities......Compression of integer sets and sequences has been extensively studied for settings where elements follow a uniform probability distribution. In addition, methods exist that exploit clustering of elements in order to achieve higher compression performance. In this work, we address the case where...
A model study in hadron statistical bootstrap
Hagedorn, Rolf
1973-01-01
In the framework of the statistical bootstrap the decay of a fireball is considered as an exact inverse of its statistical composition. This assumption leads to a bootstrap formulated in terms of integral equations for all kinds of distributions of the fireball's decay products. Solutions of the equations are obtained in terms of power series and of K-transforms and determine in the general case their asymptotic behaviour for large fireball mass. Relations to a thermodynamical description are established and illustrated by effective temperatures. The approach to the asymptotic limits is easy to investigate in a simplified linear bootstrap where the K-transforms can be more explicitly calculated. (30 refs).
Modeling the morphogenesis of brine channels in sea ice
Kutschan, B; gemming, S
2009-01-01
Brine channels are formed in sea ice under certain constraints and represent a habitat of different microorganisms. The complex system depends on a number of various quantities as salinity, density, pH-value or temperature. Each quantity governs the process of brine channel formation. There exists a strong link between bulk salinity and the presence of brine drainage channels in growing ice with respect to both the horizontal and vertical planes. We develop a suitable phenomenological model for the formation of brine channels both referring to the Ginzburg-Landau-theory of phase transitions as well as to the chemical basis of morphogenesis according to Turing. It is possible to conclude from the critical wavenumber on the size of the structure and the critical parameters. The theoretically deduced transition rates have the same magnitude as the experimental values. The model creates channels of similar size as observed experimentally. An extension of the model towards channels with different sizes is possible...
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…
A 0-Memory Model for Single Ion Channel
Institute of Scientific and Technical Information of China (English)
Zhou Wenqing; Fan Jiqian; Guan Yongyuan
1998-01-01
This paper discusses a 0-memory model for a single ion channel. The renewal rates of the open-class and the close-class are proposed to deseribe kinetic properties of a single ion channel. Further more, a procedure to estimate the parameters in the model is suggested and illustrated with examples in pharmacology.
Comparison of Statistical Models for Regional Crop Trial Analysis
Institute of Scientific and Technical Information of China (English)
ZHANG Qun-yuan; KONG Fan-ling
2002-01-01
Based on the review and comparison of main statistical analysis models for estimating varietyenvironment cell means in regional crop trials, a new statistical model, LR-PCA composite model was proposed, and the predictive precision of these models were compared by cross validation of an example data. Results showed that the order of model precision was LR-PCA model ＞ AMMI model ＞ PCA model ＞ Treatment Means (TM) model ＞ Linear Regression (LR) model ＞ Additive Main Effects ANOVA model. The precision gain factor of LR-PCA model was 1.55, increasing by 8.4% compared with AMMI.
A 3D Geometry-based Stochastic Model for 5G Massive MIMO Channels
Directory of Open Access Journals (Sweden)
Yi Xie
2015-09-01
Full Text Available Massive MIMO is one of the most promising technologies for the fifth generation (5G mobile communication systems. In order to better assess the system performance, it is essential to build a corresponding channel model accurately. In this paper, a three-dimension (3D two-cylinder regular-shaped geometry-based stochastic model (GBSM for non-isotropic scattering massive MIMO channels is proposed. Based on geometric method, all the scatters are distributed on the surface of a cylinder as equivalent scatters. Non-stationary property is that one antenna has its own visible area of scatters by using a virtual sphere. The proposed channel model is evaluated by comparing with the 3GPP 3D channel model [1]. The statistical properties are investigated. Simulation results show that close agreements are achieved between the characteristics of the proposed channel model and those of the 3GPP channel model, which justify the correctness of the proposed model. The model has advantages such as good applicability.
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.
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.
Transport properties in network models with perfectly conducting channels
International Nuclear Information System (INIS)
We study the transport properties of disordered electron systems that contain perfectly conducting channels. Two quantum network models that belong to different universality classes, unitary and symplectic, are simulated numerically. The perfectly conducting channel in the unitary class can be realized in zigzag graphene nano-ribbons and that in the symplectic class is known to appear in metallic carbon nanotubes. The existence of a perfectly conducting channel leads to novel conductance distribution functions and a shortening of the conductance decay length.
Transport properties in network models with perfectly conducting channels
Energy Technology Data Exchange (ETDEWEB)
Kobayashi, K; Hirose, K; Ohtsuki, T [Department of Physics, Sophia University, 102-8554 Tokyo (Japan); Obuse, H [Department of Physics, Kyoto University, 606-8501 Kyoto (Japan); Slevin, K [Department of Physics, Osaka University, 560-0043 Osaka (Japan)], E-mail: k-koji@sophia.ac.jp
2009-02-01
We study the transport properties of disordered electron systems that contain perfectly conducting channels. Two quantum network models that belong to different universality classes, unitary and symplectic, are simulated numerically. The perfectly conducting channel in the unitary class can be realized in zigzag graphene nano-ribbons and that in the symplectic class is known to appear in metallic carbon nanotubes. The existence of a perfectly conducting channel leads to novel conductance distribution functions and a shortening of the conductance decay length.
Transport properties in network models with perfectly conducting channels
Kobayashi, Koji; Hirose, Kosuke; Obuse, Hideaki; Ohtsuki, Tomi; Slevin, Keith
2008-01-01
We study the transport properties of disordered electron systems that contain perfectly conducting channels. Two quantum network models that belong to different universality classes, unitary and symplectic, are simulated numerically. The perfectly conducting channel in the unitary class can be realized in zigzag graphene nano-ribbons and that in the symplectic class is known to appear in metallic carbon nanotubes. The existence of a perfectly conducting channel leads to novel conductance dist...
Yu, Yang; Bing-Zhong, Wang; Shuai, Ding
2016-05-01
Utilizing channel reciprocity, time reversal (TR) technique increases the signal-to-noise ratio (SNR) at the receiver with very low transmitter complexity in complex multipath environment. Present research works about TR multiple-input multiple-output (MIMO) communication all focus on the system implementation and network building. The aim of this work is to analyze the influence of antenna coupling on the capacity of wideband TR MIMO system, which is a realistic question in designing a practical communication system. It turns out that antenna coupling stabilizes the capacity in a small variation range with statistical wideband channel response. Meanwhile, antenna coupling only causes a slight detriment to the channel capacity in a wideband TR MIMO system. Comparatively, uncorrelated stochastic channels without coupling exhibit a wider range of random capacity distribution which greatly depends on the statistical channel. The conclusions drawn from information difference entropy theory provide a guideline for designing better high-performance wideband TR MIMO communication systems. Project supported by the National Natural Science Foundation of China (Grant Nos. 61331007, 61361166008, and 61401065) and the Specialized Research Fund for the Doctoral Program of Higher Education of China (Grant No. 20120185130001).
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
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
A Noise Robust Statistical Texture Model
DEFF Research Database (Denmark)
Hilger, Klaus Baggesen; Stegmann, Mikkel Bille; Larsen, Rasmus
2002-01-01
Appearance Models segmentation framework. This is accomplished by augmenting the model with an estimate of the covariance of the noise present in the training data. This results in a more compact model maximising the signal-to-noise ratio, thus favouring subspaces rich on signal, but low on noise...
Modeling two-phase flow in PEM fuel cell channels
Wang, Yun; Basu, Suman; Wang, Chao-Yang
2008-05-01
This paper is concerned with the simultaneous flow of liquid water and gaseous reactants in mini-channels of a proton exchange membrane (PEM) fuel cell. Envisaging the mini-channels as structured and ordered porous media, we develop a continuum model of two-phase channel flow based on two-phase Darcy's law and the M2 formalism, which allow estimate of the parameters key to fuel cell operation such as overall pressure drop and liquid saturation profiles along the axial flow direction. Analytical solutions of liquid water saturation and species concentrations along the channel are derived to explore the dependences of these physical variables vital to cell performance on operating parameters such as flow stoichiometric ratio and relative humility. The two-phase channel model is further implemented for three-dimensional numerical simulations of two-phase, multi-component transport in a single fuel-cell channel. Three issues critical to optimizing channel design and mitigating channel flooding in PEM fuel cells are fully discussed: liquid water buildup towards the fuel cell outlet, saturation spike in the vicinity of flow cross-sectional heterogeneity, and two-phase pressure drop. Both the two-phase model and analytical solutions presented in this paper may be applicable to more general two-phase flow phenomena through mini- and micro-channels.
Modeling two-phase flow in PEM fuel cell channels
Energy Technology Data Exchange (ETDEWEB)
Wang, Yun; Basu, Suman; Wang, Chao-Yang [Electrochemical Engine Center (ECEC), and Department of Mechanical and Nuclear Engineering, The Pennsylvania State University, University Park, PA 16802 (United States)
2008-05-01
This paper is concerned with the simultaneous flow of liquid water and gaseous reactants in mini-channels of a proton exchange membrane (PEM) fuel cell. Envisaging the mini-channels as structured and ordered porous media, we develop a continuum model of two-phase channel flow based on two-phase Darcy's law and the M{sup 2} formalism, which allow estimate of the parameters key to fuel cell operation such as overall pressure drop and liquid saturation profiles along the axial flow direction. Analytical solutions of liquid water saturation and species concentrations along the channel are derived to explore the dependences of these physical variables vital to cell performance on operating parameters such as flow stoichiometric ratio and relative humility. The two-phase channel model is further implemented for three-dimensional numerical simulations of two-phase, multi-component transport in a single fuel-cell channel. Three issues critical to optimizing channel design and mitigating channel flooding in PEM fuel cells are fully discussed: liquid water buildup towards the fuel cell outlet, saturation spike in the vicinity of flow cross-sectional heterogeneity, and two-phase pressure drop. Both the two-phase model and analytical solutions presented in this paper may be applicable to more general two-phase flow phenomena through mini- and micro-channels. (author)
12th Workshop on Stochastic Models, Statistics and Their Applications
Rafajłowicz, Ewaryst; Szajowski, Krzysztof
2015-01-01
This volume presents the latest advances and trends in stochastic models and related statistical procedures. Selected peer-reviewed contributions focus on statistical inference, quality control, change-point analysis and detection, empirical processes, time series analysis, survival analysis and reliability, statistics for stochastic processes, big data in technology and the sciences, statistical genetics, experiment design, and stochastic models in engineering. Stochastic models and related statistical procedures play an important part in furthering our understanding of the challenging problems currently arising in areas of application such as the natural sciences, information technology, engineering, image analysis, genetics, energy and finance, to name but a few. This collection arises from the 12th Workshop on Stochastic Models, Statistics and Their Applications, Wroclaw, Poland.
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
Zhong, Qiang; Chen, Qigang; Wang, Hao; Li, Danxun; Wang, Xingkui
2016-05-01
Long streamwise-elongated high- and low-speed streaks are repeatedly observed near the free surface in open channel flows in natural rivers and lab experiments. Super-streamwise vortex model has been proposed to explain this widespread phenomenon for quite some time. However, statistical evidence of the existence of the super-streamwise vortices as one type of coherent structures is still insufficient. Correlation and proper orthogonal decomposition (POD) analysis based on PIV experimental data in the streamwise-spanwise plane near the free surface in a smooth open channel flow are employed to investigate this topic. Correlation analysis revealed that the streaky structures appear frequently near the free surface and their occurrence probability at any spanwise position is equal. The spanwise velocity fluctuation usually flows from low-speed streaks toward high-speed streaks. The average spanwise width and spacing between neighboring low (or high) speed streaks are approximately h and 2h respectively. POD analysis reveals that there are streaks with different spanwise width in the instantaneous flow fields. Typical streamwise rotational movement can be sketched out directly based on the results from statistical analyses. Point-by-point analysis indicates that this pattern is consistent everywhere in the measurement window and is without any inhomogeneity in the spanwise direction, which reveals the essential difference between coherent structures and secondary flow cells. The pattern found by statistical analysis is consistent with the notion that the super-streamwise vortices exist universally as one type of coherent structure in open channel flows.
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 modeling and extrapolation of carcinogenesis data
International Nuclear Information System (INIS)
Mathematical models of carcinogenesis are reviewed, including pharmacokinetic models for metabolic activation of carcinogenic substances. Maximum likelihood procedures for fitting these models to epidemiological data are discussed, including situations where the time to tumor occurrence is unobservable. The plausibility of different possible shapes of the dose response curve at low doses is examined, and a robust method for linear extrapolation to low doses is proposed and applied to epidemiological data on radiation carcinogenesis
Infinite statistics condensate as a model of dark matter
Energy Technology Data Exchange (ETDEWEB)
Ebadi, Zahra; Mirza, Behrouz [Department of Physics, Isfahan University of Technology, Isfahan, 84156–83111 (Iran, Islamic Republic of); Mohammadzadeh, Hosein, E-mail: z.ebadi@ph.iut.ac.ir, E-mail: b.mirza@cc.iut.ac.ir, E-mail: mohammadzadeh@uma.ac.ir [Department of Physics, University of Mohaghegh Ardabili, P.O. Box 179, Ardabil (Iran, Islamic Republic of)
2013-11-01
In some models, dark matter is considered as a condensate bosonic system. In this paper, we prove that condensation is also possible for particles that obey infinite statistics and derive the critical condensation temperature. We argue that a condensed state of a gas of very weakly interacting particles obeying infinite statistics could be considered as a consistent model of dark matter.
Fluctuations of offshore wind generation: Statistical modelling
DEFF Research Database (Denmark)
Pinson, Pierre; Christensen, Lasse E.A.; Madsen, Henrik;
2007-01-01
production averaged at a 1, 5, and 10-minute rate. The exercise consists in one-step ahead forecasting of these time-series with the various regime-switching models. It is shown that the MSAR model, for which the succession of regimes is represented by a hidden Markov chain, significantly outperforms......) and Markov-Switching AutoRegressive (MSAR) models are considered. The particularities of these models are presented, as well as methods for the estimation of their parameters. Simulation results are given for the case of the Horns Rev and Nysted offshore wind farms in Denmark, for time-series of power...
Statistical modelling of traffic safety development
DEFF Research Database (Denmark)
Christens, Peter
2004-01-01
Road safety is a major concern for society and individuals. Although road safety has improved in recent years, the number of road fatalities is still unacceptably high. In 2000, road accidents killed over 40,000 people in the European Union and injured more than 1.7 million. In 2001 in Denmark...... 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...
A channel-based coordination model for component composition
Arbab, F.
2002-01-01
In this paper, we present $P epsilon omega$, a paradigm for composition of software components based on the notion of mobile channels. $P repsilon omega$ is a channel-based exogenous coordination model wherein complex coordinators, called {em connectors are compositionally built out of simpler ones.
Reo: A Channel-based Coordination Model for Component Composition
Arbab, F.
2004-01-01
In this paper, we present Reo, which forms a paradigm for composition of software components based on the notion of mobile channels. Reo is a channel-based exogenous coordination model in which complex coordinators, called connectors, are compositionally built out of simpler ones. The simplest conne
Molecular modeling of mechanosensory ion channel structural and functional features.
Gessmann, Renate; Kourtis, Nikos; Petratos, Kyriacos; Tavernarakis, Nektarios
2010-09-16
The DEG/ENaC (Degenerin/Epithelial Sodium Channel) protein family comprises related ion channel subunits from all metazoans, including humans. Members of this protein family play roles in several important biological processes such as transduction of mechanical stimuli, sodium re-absorption and blood pressure regulation. Several blocks of amino acid sequence are conserved in DEG/ENaC proteins, but structure/function relations in this channel class are poorly understood. Given the considerable experimental limitations associated with the crystallization of integral membrane proteins, knowledge-based modeling is often the only route towards obtaining reliable structural information. To gain insight into the structural characteristics of DEG/ENaC ion channels, we derived three-dimensional models of MEC-4 and UNC-8, based on the available crystal structures of ASIC1 (Acid Sensing Ion Channel 1). MEC-4 and UNC-8 are two DEG/ENaC family members involved in mechanosensation and proprioception respectively, in the nematode Caenorhabditis elegans. We used these models to examine the structural effects of specific mutations that alter channel function in vivo. The trimeric MEC-4 model provides insight into the mechanism by which gain-of-function mutations cause structural alterations that result in increased channel permeability, which trigger cell degeneration. Our analysis provides an introductory framework to further investigate the multimeric organization of the DEG/ENaC ion channel complex.
Molecular modeling of mechanosensory ion channel structural and functional features.
Directory of Open Access Journals (Sweden)
Renate Gessmann
Full Text Available The DEG/ENaC (Degenerin/Epithelial Sodium Channel protein family comprises related ion channel subunits from all metazoans, including humans. Members of this protein family play roles in several important biological processes such as transduction of mechanical stimuli, sodium re-absorption and blood pressure regulation. Several blocks of amino acid sequence are conserved in DEG/ENaC proteins, but structure/function relations in this channel class are poorly understood. Given the considerable experimental limitations associated with the crystallization of integral membrane proteins, knowledge-based modeling is often the only route towards obtaining reliable structural information. To gain insight into the structural characteristics of DEG/ENaC ion channels, we derived three-dimensional models of MEC-4 and UNC-8, based on the available crystal structures of ASIC1 (Acid Sensing Ion Channel 1. MEC-4 and UNC-8 are two DEG/ENaC family members involved in mechanosensation and proprioception respectively, in the nematode Caenorhabditis elegans. We used these models to examine the structural effects of specific mutations that alter channel function in vivo. The trimeric MEC-4 model provides insight into the mechanism by which gain-of-function mutations cause structural alterations that result in increased channel permeability, which trigger cell degeneration. Our analysis provides an introductory framework to further investigate the multimeric organization of the DEG/ENaC ion channel complex.
Model validation of channel zapping quality
Kooij, R.E.; Nicolai, F.; Ahmed, O.K.; Brunnström, K.
2009-01-01
In an earlier paper we showed, that perceived quality of channel zapping is related to the perceived quality of download time of web browsing, as suggested by ITU-T Rec.G.1030. We showed this by performing subjective tests resulting in an excellent fit with a 0.99 correlation. This was what we call
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
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 Model of the 3-D Braided Composites Strength
Institute of Scientific and Technical Information of China (English)
XIAO Laiyuan; ZUO Weiwei; CAI Ganwei; LIAO Daoxun
2007-01-01
Based on the statistical model for the tensile statistical strength of unidirectional composite materials and the stress analysis of 3-D braided composites, a new method is proposed to calculate the tensile statistical strength of the 3-D braided composites. With this method, the strength of 3-D braided composites can be calculated with very large accuracy, and the statistical parameters of 3-D braided composites can be determined. The numerical result shows that the tensile statistical strength of 3-D braided composites can be predicted using this method.
A numerical model for meltwater channel evolution in glaciers
Directory of Open Access Journals (Sweden)
A. H. Jarosch
2011-10-01
Full Text Available Meltwater channels form an integral part of the hydrological system of a glacier. Better understanding of how meltwater channels develop and evolve is required to fully comprehend supraglacial and englacial meltwater drainage. Incision of supraglacial stream channels and subsequent roof closure by ice deformation has been proposed in recent literature as a possible englacial conduit formation process. Field evidence for supraglacial stream incision has been found in Svalbard and Nepal. In Iceland, where volcanic activity provides meltwater with temperatures above 0 °C, rapid enlargement of supraglacial channels has been observed. By coupling, for the first time, a numerical ice dynamic model to a hydraulic model which includes heat transfer, we investigate the evolution of meltwater channels and their incision behaviour. We present results for different, constant meltwater fluxes, different channel slopes, different meltwater temperatures as well as temporal variations in meltwater flux. The key parameters governing incision rate and depth are the channel slope and the meltwater temperature loss to the ice. Meltwater flux controls channel width and to a lesser degree incision behaviour. Calculated Nusselt numbers suggest that turbulent forced convection is the main heat transfer mechanism in the studied meltwater channels.
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 ...
Statistical Modeling of Large-Scale Scientific Simulation Data
Energy Technology Data Exchange (ETDEWEB)
Eliassi-Rad, T; Baldwin, C; Abdulla, G; Critchlow, T
2003-11-15
With the advent of massively parallel computer systems, scientists are now able to simulate complex phenomena (e.g., explosions of a stars). Such scientific simulations typically generate large-scale data sets over the spatio-temporal space. Unfortunately, the sheer sizes of the generated data sets make efficient exploration of them impossible. Constructing queriable statistical models is an essential step in helping scientists glean new insight from their computer simulations. We define queriable statistical models to be descriptive statistics that (1) summarize and describe the data within a user-defined modeling error, and (2) are able to answer complex range-based queries over the spatiotemporal dimensions. In this chapter, we describe systems that build queriable statistical models for large-scale scientific simulation data sets. In particular, we present our Ad-hoc Queries for Simulation (AQSim) infrastructure, which reduces the data storage requirements and query access times by (1) creating and storing queriable statistical models of the data at multiple resolutions, and (2) evaluating queries on these models of the data instead of the entire data set. Within AQSim, we focus on three simple but effective statistical modeling techniques. AQSim's first modeling technique (called univariate mean modeler) computes the ''true'' (unbiased) mean of systematic partitions of the data. AQSim's second statistical modeling technique (called univariate goodness-of-fit modeler) uses the Andersen-Darling goodness-of-fit method on systematic partitions of the data. Finally, AQSim's third statistical modeling technique (called multivariate clusterer) utilizes the cosine similarity measure to cluster the data into similar groups. Our experimental evaluations on several scientific simulation data sets illustrate the value of using these statistical models on large-scale simulation data sets.
Modeling and Simulation of MIMO Mobile-to-Mobile Wireless Fading Channels
Directory of Open Access Journals (Sweden)
Gholamreza Bakhshi
2012-01-01
Full Text Available Analysis and design of multielement antenna systems in mobile fading channels require a model for the space-time cross-correlation among the links of the underlying multipleinput multiple-output (MIMO Mobile-to-Mobile (M-to-M communication channels. In this paper, we propose the modified geometrical two-ring model, a MIMO channel reference model for M-to-M communication systems. This model is based on the extension of single-bounce two-ring scattering model for flat fading channel under the assumption that the transmitter and the receiver are moving. Assuming single-bounce scattering model in both isotropic and nonisotropic environment, a closed-form expression for the space-time cross-correlation function (CCF between any two subchannels is derived. The proposed model provides an important framework in M-to-M system design, where includes many existing correlation models as special cases. Also, two realizable statistical simulation models are proposed for simulating both isotropic and nonisotropic reference model. The realizable simulation models are based on Sum-of-Sinusoids (SoS simulation model. Finally, the correctness of the proposed simulation models is shown via different simulation scenarios.
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...
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.
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.
Beta decay properties from a statistical model
International Nuclear Information System (INIS)
The present work assumes that any intrinsic structure in the nuclei involved is not important. Only spin, parity, and energy are considered. Quantities such as half-life, average beta energy, or average gamma energy can be obtained by integrals over the beta strength function weighted by kinematic and other factors. The beta strength function is proportional to the level density multiplied by a reduced transition probability. Delayed neutron emission is calculated by assuming that the daughter is a compound nucleus which then statistically decays as in the Hauser-Feshbach approach. Using the ENDF/B-V fission product file which contains 877 nuclei, energy-dependent reduced transition probabilities were found for allowed 0+ → 1+ transitions (50 cases) and for other allowed transitions (over 600 cases), corresponding to log ft values of 4.3 and 5.6 respectively. No dependence on either transition energy or on mass was found. A reduced transition probability corresponding to log ft of 7.1 was used for first forbidden transitions. Some results are presented and discussed
Statistics-based investigation on typhoon transition modeling
DEFF Research Database (Denmark)
Zhang, Shuoyun; Nishijima, Kazuyoshi
The present study revisits the statistical modeling of typhoon transition. The objective of the study is to provide insights on plausible statistical typhoon transition models based on extensive statistical analysis. First, the correlation structures of the typhoon transition are estimated in terms...... of autocorrelation function (ACF) and partial autocorrelation function (PACF). This facilitates to specify a set of plausible models for further investigation. Then, the corrected Akaike Information Criterion (cAIC) is applied to investigate the relative goodness of fit of these models. The spatial inhomogeneity...
NUMERICAL MODELING OF SUSPENDED SEDIMENT TRANSPORT IN CHANNEL BENDS
Institute of Scientific and Technical Information of China (English)
HUANG Sui-liang; JIA Y. F.; WANG Sam S. Y.
2006-01-01
An algorithm to compute three-dimensional sediment transport effect was proposed in this paper to enhance the capability of depth-averaged numerical models. This algorithm took into account of non-uniform distributions of flow velocities and suspended sediment concentrations along water depth, it significantly enhanced the applicability of 2D models in simulating open channel flows, especially in channel bends. Preliminary numerical experiments in a U-shaped and a sine-generated experimental channel indicate that the proposed method performs quite well in predicting the change of bed-deformation in channel bends due to suspended sediment transport. This method provides an effective alternative for the simulations of channel morphodynamic changes.
Contributions in Radio Channel Sounding, Modeling, and Estimation
DEFF Research Database (Denmark)
Pedersen, Troels
2009-01-01
This thesis spans over three strongly related topics in wireless communication: channel-sounding, -modeling, and -estimation. Three main problems are addressed: optimization of spatio-temporal apertures for channel sounding; estimation of per-path power spectral densities (psds); and modeling of...... reverberant channels. We develop a theory for optimization of spatio-temporal apertures used in multiple-input multiple-output (MIMO) channel sounding. Initially, we focus on joint estimation of bi-direction and Doppler frequency from time-division multiplexing (TDM) MIMO measurements. We introduce and...... analyze a bi-spatio-temporal ambiguity function for spatio-temporal channel sounding. The analysis reveals that by proper design of the spatio-temporal aperture, the maximum estimable Doppler frequency of a TDM-MIMO sounder is as high as that of a traditional single-input single-output sounder. We give...
Statistics of Certain Models of Evolution
Standish, R K
1999-01-01
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. I would argue that this mechanism should be described as self-organised critical. In this paper, I have also implemented Newman's model using the Ecolab software, removing the restriction that the number of species remains constant. It turns out that the requirement of constant species number is non-trivial, leading to a global coupling between species that is similar in effect to the species interactions seen in Ecolab. In fact, the model must self-organise to a state where the long time average of speciations balances that of the extinctions, otherwise the system either collapses o...
A statistical model of facial attractiveness.
Said, Christopher P; Todorov, Alexander
2011-09-01
Previous research has identified facial averageness and sexual dimorphism as important factors in facial attractiveness. The averageness and sexual dimorphism accounts provide important first steps in understanding what makes faces attractive, and should be valued for their parsimony. However, we show that they explain relatively little of the variance in facial attractiveness, particularly for male faces. As an alternative to these accounts, we built a regression model that defines attractiveness as a function of a face's position in a multidimensional face space. The model provides much more predictive power than the averageness and sexual dimorphism accounts and reveals previously unreported components of attractiveness. The model shows that averageness is attractive in some dimensions but not in others and resolves previous contradictory reports about the effects of sexual dimorphism on the attractiveness of male faces.
Lightning NOx Statistics Derived by NASA Lightning Nitrogen Oxides Model (LNOM) Data Analyses
Koshak, William; Peterson, Harold
2013-01-01
What is the LNOM? The NASA Marshall Space Flight Center (MSFC) Lightning Nitrogen Oxides Model (LNOM) [Koshak et al., 2009, 2010, 2011; Koshak and Peterson 2011, 2013] analyzes VHF Lightning Mapping Array (LMA) and National Lightning Detection Network(TradeMark) (NLDN) data to estimate the lightning nitrogen oxides (LNOx) produced by individual flashes. Figure 1 provides an overview of LNOM functionality. Benefits of LNOM: (1) Does away with unrealistic "vertical stick" lightning channel models for estimating LNOx; (2) Uses ground-based VHF data that maps out the true channel in space and time to < 100 m accuracy; (3) Therefore, true channel segment height (ambient air density) is used to compute LNOx; (4) True channel length is used! (typically tens of kilometers since channel has many branches and "wiggles"); (5) Distinction between ground and cloud flashes are made; (6) For ground flashes, actual peak current from NLDN used to compute NOx from lightning return stroke; (7) NOx computed for several other lightning discharge processes (based on Cooray et al., 2009 theory): (a) Hot core of stepped leaders and dart leaders, (b) Corona sheath of stepped leader, (c) K-change, (d) Continuing Currents, and (e) M-components; and (8) LNOM statistics (see later) can be used to parameterize LNOx production for regional air quality models (like CMAQ), and for global chemical transport models (like GEOS-Chem).
Editorial to: Six papers on Dynamic Statistical Models
DEFF Research Database (Denmark)
2014-01-01
statistical methodology and theory for large and complex data sets that included biostatisticians and mathematical statisticians from three faculties at the University of Copenhagen. The satellite meeting took place August 17–19, 2011. Its purpose was to bring together researchers in statistics and related...... was organized around the theme “Dynamic Statistical Models” as a part of the Program of Excellence at the University of Copenhagen on “Statistical methods for complex and high dimensional models” (http://statistics.ku.dk/). The Excellence Program in Statistics was a research project to develop and investigate...... areas working with frontier research topics in statistics for dynamic models. This issue of SJS contains a quite diverse collection of six papers from the conference: Spectral Estimation of Covolatility from Noisy Observations Using Local Weights Markus Bibinger and Markus Reiß One-Way Anova...
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.
Improved virtual channel noise model for transform domain Wyner-Ziv video coding
DEFF Research Database (Denmark)
Huang, Xin; Forchhammer, Søren
2009-01-01
Distributed video coding (DVC) has been proposed as a new video coding paradigm to deal with lossy source coding using side information to exploit the statistics at the decoder to reduce computational demands at the encoder. A virtual channel noise model is utilized at the decoder to estimate the...... coding is proposed, which utilizes cross-band correlation to estimate the Laplacian parameters more accurately. Experimental results show that the proposed noise model can improve the rate-distortion (RD) performance....
A Statistical Model for Energy Intensity
Directory of Open Access Journals (Sweden)
Marjaneh Issapour
2012-12-01
Full Text Available A promising approach to improve scientific literacy in regards to global warming and climate change is using a simulation as part of a science education course. The simulation needs to employ scientific analysis of actual data from internationally accepted and reputable databases to demonstrate the reality of the current climate change situation. One of the most important criteria for using a simulation in a science education course is the fidelity of the model. The realism of the events and consequences modeled in the simulation is significant as well. Therefore, all underlying equations and algorithms used in the simulation must have real-world scientific basis. The "Energy Choices" simulation is one such simulation. The focus of this paper is the development of a mathematical model for "Energy Intensity" as a part of the overall system dynamics in "Energy Choices" simulation. This model will define the "Energy Intensity" as a function of other independent variables that can be manipulated by users of the simulation. The relationship discovered by this research will be applied to an algorithm in the "Energy Choices" simulation.
Functional summary statistics for the Johnson-Mehl model
DEFF Research Database (Denmark)
Møller, Jesper; Ghorbani, Mohammad
The Johnson-Mehl germination-growth model is a spatio-temporal point process model which among other things have been used for the description of neurotransmitters datasets. However, for such datasets parametric Johnson-Mehl models fitted by maximum likelihood have yet not been evaluated by means...... of functional summary statistics. This paper therefore invents four functional summary statistics adapted to the Johnson-Mehl model, with two of them based on the second-order properties and the other two on the nuclei-boundary distances for the associated Johnson-Mehl tessellation. The functional summary...... statistics theoretical properties are investigated, non-parametric estimators are suggested, and their usefulness for model checking is examined in a simulation study. The functional summary statistics are also used for checking fitted parametric Johnson-Mehl models for a neurotransmitters dataset....
Statistical modelling in biostatistics and bioinformatics selected papers
Peng, Defen
2014-01-01
This book presents selected papers on statistical model development related mainly to the fields of Biostatistics and Bioinformatics. The coverage of the material falls squarely into the following categories: (a) Survival analysis and multivariate survival analysis, (b) Time series and longitudinal data analysis, (c) Statistical model development and (d) Applied statistical modelling. Innovations in statistical modelling are presented throughout each of the four areas, with some intriguing new ideas on hierarchical generalized non-linear models and on frailty models with structural dispersion, just to mention two examples. The contributors include distinguished international statisticians such as Philip Hougaard, John Hinde, Il Do Ha, Roger Payne and Alessandra Durio, among others, as well as promising newcomers. Some of the contributions have come from researchers working in the BIO-SI research programme on Biostatistics and Bioinformatics, centred on the Universities of Limerick and Galway in Ireland and fu...
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. ...
Daisy Models Semi-Poisson statistics and beyond
Hernández-Saldaña, H; Seligman, T H
1999-01-01
Semi-Poisson statistics are shown to be obtained by removing every other number from a random sequence. Retaining every (r+1)th level we obtain a family of secuences which we call daisy models. Their statistical properties coincide with those of Bogomolny's nearest-neighbour interaction Coulomb gas if the inverse temperature coincides with the integer r. In particular the case r=2 reproduces closely the statistics of quasi-optimal solutions of the traveling salesman problem.
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 ...
Statistics in the landscape of intersecting brane models
Energy Technology Data Exchange (ETDEWEB)
Gmeiner, Florian [NIKHEF, Amsterdam (Netherlands)
2008-08-15
An approach towards a statistical survey of four-dimensional supersymmetric vacua in the string theory landscape is described and illustrated with three examples of ensembles of intersecting D-brane models. The question whether it is conceivable to make predictions based on statistical distributions is discussed. Especially interesting in this context are possible correlations between low energy observables. As an example we look at correlations between properties of the gauge sector of intersecting D-brane models and Gepner model constructions. (orig.)
Modeling statistical properties of written text.
Directory of Open Access Journals (Sweden)
M Angeles Serrano
Full Text Available Written text is one of the fundamental manifestations of human language, and the study of its universal regularities can give clues about how our brains process information and how we, as a society, organize and share it. Among these regularities, only Zipf's law has been explored in depth. Other basic properties, such as the existence of bursts of rare words in specific documents, have only been studied independently of each other and mainly by descriptive models. As a consequence, there is a lack of understanding of linguistic processes as complex emergent phenomena. Beyond Zipf's law for word frequencies, here we focus on burstiness, Heaps' law describing the sublinear growth of vocabulary size with the length of a document, and the topicality of document collections, which encode correlations within and across documents absent in random null models. We introduce and validate a generative model that explains the simultaneous emergence of all these patterns from simple rules. As a result, we find a connection between the bursty nature of rare words and the topical organization of texts and identify dynamic word ranking and memory across documents as key mechanisms explaining the non trivial organization of written text. Our research can have broad implications and practical applications in computer science, cognitive science and linguistics.
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.
Modeling Statistical and Dynamic Features of Earthquakes
Rydelek, P. A.; Suyehiro, K.; Sacks, S. I.; Smith, D. E.; Takanami, T.; Hatano, T.
2015-12-01
The cellular automaton earthquake model by Sacks and Rydelek (1995) is extended to explain spatio-temporal change in seismicity with the regional tectonic stress buildup. Our approach is to apply a simple Coulomb failure law to our model space of discrete cells, which successfully reproduces empirical laws (e.g. Gutenberg-Richter law) and dynamic failure characteristics (e.g. stress drop vs. magnitude and asperities) of earthquakes. Once the stress condition supersedes the Coulomb threshold on a discrete cell, its accumulated stress is transferred to only neighboring cells, which cascades to more neighboring cells to create various size ruptures. A fundamental point here is the cellular view of the continuous earth. We suggest the cell size varies regionally with the maturity of the faults of the region. Seismic gaps (e.g. Mogi, 1979) and changes in seismicity such as indicated by b-values have been known but poorly understood. There have been reports of magnitude dependent seismic quiescence before large event at plate boundaries and intraplate (Smith et al., 2013). Recently, decreases in b-value for large earthquakes have been reported (Nanjo et al., 2012) as anticipated from lab experiments (Mogi, 1963). Our model reproduces the b-value decrease towards eventual large earthquake (increasing tectonic stress and its heterogeneous distribution). We succeeded in reproducing the cut-off of larger events above some threshold magnitude (M3-4) by slightly increasing the Coulomb failure level for only 2 % or more of the highly stressed cells. This is equivalent to reducing the pore pressure in these distributed cells. We are working on the model to introduce the recovery of pore pressure incorporating the observed orders of magnitude higher permeability fault zones than the surrounding rock (Lockner, 2009) allowing for a large earthquake to be generated. Our interpretation requires interactions of pores and fluids. We suggest heterogeneously distributed patches hardened
Behavioral and Statistical Models of Educational Inequality
DEFF Research Database (Denmark)
Holm, Anders; Breen, Richard
2016-01-01
This paper addresses the question of how students and their families make educational decisions. We describe three types of behavioral model that might underlie decision-making and we show that they have consequences for what decisions are made. Our study thus has policy implications if we wish...... to encourage students and their families to make better educational choices. We also establish the conditions under which empirical analysis can distinguish between the three sorts of decision-making and we illustrate our arguments using data from the National Educational Longitudinal Study....
Impact of Clustering in Indoor MIMO Propagation Using a Hybrid Channel Model
Directory of Open Access Journals (Sweden)
Tang Zhongwei
2005-01-01
Full Text Available The clustering of propagating signals in indoor environments can influence the performance of multiple-input multiple-output (MIMO systems that employ multiple-element antennas at the transmitter and receiver. In order to clarify the effect of clustering propagation on the performance of indoor MIMO systems, we propose a simple and efficient indoor MIMO channel model. The proposed model, which is validated with on-site measurements, combines the statistical characteristics of signal clusters with deterministic ray tracing approach. Using the proposed model, the effect of signal clusters and the presence of the line-of-sight component in indoor Ricean channels are studied. Simulation results on channel efficiency and the angular sensitivity for different antenna array topologies inside a specified indoor scenario are also provided. Our investigations confirm that the clustering of signals significantly affects the spatial correlation, and hence, the achievable indoor MIMO capacity.
Channel Modeling for Air-to-Ground Wireless Communication
Institute of Scientific and Technical Information of China (English)
Yingcheng Shi; Di He; Bin Li; Jianwu Dou
2015-01-01
In this paper, we discuss several large⁃scale fading models for different environments. The COST231⁃Hata model is adapted for air⁃to⁃ground modeling. We propose two criteria for air⁃to⁃ground channel modelling based on test data derived from field testing in Beijing. We develop a new propagation model that is more suitable for air⁃to⁃ground communication that pre⁃vious models. We focus on improving this propagation model using the field test data.
Statistical Analysis and Modeling of Elastic Functions
Srivastava, Anuj; Kurtek, Sebastian; Klassen, Eric; Marron, J S
2011-01-01
We introduce a novel geometric framework for separating, analyzing and modeling the $x$ (or horizontal) and the $y$ (or vertical) variability in time-warped functional data of the type frequently studied in growth curve analysis. This framework is based on the use of the Fisher-Rao Riemannian metric that provides a proper distance for: (1) aligning, comparing and modeling functions and (2) analyzing the warping functions. A convenient square-root velocity function (SRVF) representation transforms the Fisher-Rao metric to the standard $\\ltwo$ metric, a tool that is applied twice in this framework. Firstly, it is applied to the given functions where it leads to a parametric family of penalized-$\\ltwo$ distances in SRVF space. The parameter controls the levels of elasticity of the individual functions. These distances are then used to define Karcher means and the individual functions are optimally warped to align them to the Karcher means to extract the $y$ variability. Secondly, the resulting warping functions,...
Effects of subfilter velocity modelling on dispersed phase in LES of heated channel flow
International Nuclear Information System (INIS)
A non-isothermal turbulent flow with the dispersed phase is modelled using the Large Eddy Simulation (LES) approach for fluid, one-way coupled with the equations of point-particle evolution. The channel is heated at both walls and isoflux boundary conditions are applied for fluid. Particle velocity and thermal statistics are computed. Of particular interest are the r.m.s. profiles and the probability density function of particle temperature in the near-wall region. We compare our findings with available reference data for particle-laden, heated channel flow. Moreover, an open issue in LES is the influence of non-resolved (residual) scales of fluid velocity and temperature fields on particles. In the present contribution, we apply a stochastic model for subfilter fluid velocity at the particle positions that aims at reconstructing the effects of the smallest scales of turbulence on particle dynamics. We analyse the impact of this model on particle thermal statistics.
Effects of subfilter velocity modelling on dispersed phase in LES of heated channel flow
Pozorski, Jacek; Knorps, Maria; Łuniewski, Mirosław
2011-12-01
A non-isothermal turbulent flow with the dispersed phase is modelled using the Large Eddy Simulation (LES) approach for fluid, one-way coupled with the equations of point-particle evolution. The channel is heated at both walls and isoflux boundary conditions are applied for fluid. Particle velocity and thermal statistics are computed. Of particular interest are the r.m.s. profiles and the probability density function of particle temperature in the near-wall region. We compare our findings with available reference data for particle-laden, heated channel flow. Moreover, an open issue in LES is the influence of non-resolved (residual) scales of fluid velocity and temperature fields on particles. In the present contribution, we apply a stochastic model for subfilter fluid velocity at the particle positions that aims at reconstructing the effects of the smallest scales of turbulence on particle dynamics. We analyse the impact of this model on particle thermal statistics.
Statistical properties of several models of fractional random point processes
Bendjaballah, C.
2011-08-01
Statistical properties of several models of fractional random point processes have been analyzed from the counting and time interval statistics points of view. Based on the criterion of the reduced variance, it is seen that such processes exhibit nonclassical properties. The conditions for these processes to be treated as conditional Poisson processes are examined. Numerical simulations illustrate part of the theoretical calculations.
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..
3D Massive MIMO Systems: Channel Modeling and Performance Analysis
Nadeem, Qurrat-Ul-Ain
2015-03-01
Multiple-input-multiple-output (MIMO) systems of current LTE releases are capable of adaptation in the azimuth only. More recently, the trend is to enhance the system performance by exploiting the channel\\'s degrees of freedom in the elevation through the dynamic adaptation of the vertical antenna beam pattern. This necessitates the derivation and characterization of three-dimensional (3D) channels. Over the years, channel models have evolved to address the challenges of wireless communication technologies. In parallel to theoretical studies on channel modeling, many standardized channel models like COST-based models, 3GPP SCM, WINNER, ITU have emerged that act as references for industries and telecommunication companies to assess system-level and link-level performances of advanced signal processing techniques over real-like channels. Given the existing channels are only two dimensional (2D) in nature; a large effort in channel modeling is needed to study the impact of the channel component in the elevation direction. The first part of this work sheds light on the current 3GPP activity around 3D channel modeling and beamforming, an aspect that to our knowledge has not been extensively covered by a research publication. The standardized MIMO channel model is presented, that incorporates both the propagation effects of the environment and the radio effects of the antennas. In order to facilitate future studies on the use of 3D beamforming, the main features of the proposed 3D channel model are discussed. A brief overview of the future 3GPP 3D channel model being outlined for the next generation of wireless networks is also provided. In the subsequent part of this work, we present an information-theoretic channel model for MIMO systems that supports the elevation dimension. The model is based on the principle of maximum entropy, which enables us to determine the distribution of the channel matrix consistent with the prior information on the angles of departure and
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.
CHANNEL MORPHOLOGY TOOL (CMT): A GIS-BASED AUTOMATED EXTRACTION MODEL FOR CHANNEL GEOMETRY
Energy Technology Data Exchange (ETDEWEB)
JUDI, DAVID [Los Alamos National Laboratory; KALYANAPU, ALFRED [Los Alamos National Laboratory; MCPHERSON, TIMOTHY [Los Alamos National Laboratory; BERSCHEID, ALAN [Los Alamos National Laboratory
2007-01-17
This paper describes an automated Channel Morphology Tool (CMT) developed in ArcGIS 9.1 environment. The CMT creates cross-sections along a stream centerline and uses a digital elevation model (DEM) to create station points with elevations along each of the cross-sections. The generated cross-sections may then be exported into a hydraulic model. Along with the rapid cross-section generation the CMT also eliminates any cross-section overlaps that might occur due to the sinuosity of the channels using the Cross-section Overlap Correction Algorithm (COCoA). The CMT was tested by extracting cross-sections from a 5-m DEM for a 50-km channel length in Houston, Texas. The extracted cross-sections were compared directly with surveyed cross-sections in terms of the cross-section area. Results indicated that the CMT-generated cross-sections satisfactorily matched the surveyed data.
A novel statistical generative model dedicated to face recognition
Heusch, Guillaume; Marcel, Sébastien
2009-01-01
In this paper, a novel statistical generative model to describe a face is presented, and is applied to the face authentication task. Classical generative models used so far in face recognition, such as Gaussian Mixture Models (GMMs) and Hidden Markov Models (HMMs) for instance, are making strong assumptions on the observations derived from a face image. Indeed, such models usually assume that local observations are independent, which is obviously not the case in a face. The presented model he...
Statistical Physics and Dynamical Systems: Models of Phase Transitions
Patwardhan, Ajay
2007-01-01
This paper explores the connection between dynamical system properties and statistical physics of ensembles of such systems. Simple models are used to give novel phase transitions; particularly for finite N particle systems with many physically interesting examples.
Statistical modeling of a considering work-piece
Directory of Open Access Journals (Sweden)
Cornelia Victoria Anghel
2008-10-01
Full Text Available In this article are presented the stochastic predictive models for controlling properly the independent variables of the drilling operation a combined approach of statistical design and Response Surface Methodology (RSM.
MODELING OF VEHICULAR STEERING EFFICIENCY IN TRAFFIC DIRECTION MOTION CHANNEL
V. A. Ganai; S. A. O. Diab Abdullah
2011-01-01
The paper formulates and solves an actual problem pertaining to vehicular steering efficiency in traffic direction motion channel. Models of operator-drivers with low, medium and high rates in motivational perception of road conditions and also a model for controlling a traffic direction motion have been taken into ccount in the paper. Modeling has been done by using MATLAB.
Model of risk assessment under ballistic statistical tests
Gabrovski, Ivan; Karakaneva, Juliana
The material presents the application of a mathematical method for risk assessment under statistical determination of the ballistic limits of the protection equipment. The authors have implemented a mathematical model based on Pierson's criteria. The software accomplishment of the model allows to evaluate the V50 indicator and to assess the statistical hypothesis' reliability. The results supply the specialists with information about the interval valuations of the probability determined during the testing process.
A no extensive statistical model for the nucleon structure function
Trevisan, Luis A.; Mirez, Carlos
2013-03-01
We studied an application of nonextensive thermodynamics to describe the structure function of nucleon, in a model where the usual Fermi-Dirac and Bose-Einstein energy distribution were replaced by the equivalent functions of the q-statistical. The parameters of the model are given by an effective temperature T, the q parameter (from Tsallis statistics), and two chemical potentials given by the corresponding up (u) and down (d) quark normalization in the nucleon.
a Nonextensive Statistical Model for the Nucleon Structure Function
Trevisan, Luis Augusto; Mirez, Carlos
2013-07-01
We studied an application of nonextensive thermodynamics to describe the structure function of nucleon, in a model where the usual Fermi-Dirac and Bose-Einstein energy distribution were replaced by the equivalent functions of the q-statistical. The parameters of the model are given by an effective temperature T, the q parameter (from Tsallis statistics), and two chemical potentials given by the corresponding up (u) and down (d) quark normalizations in the nucleon.
FLOOD ROUTING MODELS IN CONFLUENT AND DIVIDING CHANNELS
Institute of Scientific and Technical Information of China (English)
范平; 李家春; 刘青泉
2004-01-01
By introducing a water depth connecting formula, the hydraulic equations in the dividing channel system were coupled and the relation of discharge distribution between the branches of the dividing channels can be yielded. In this manner, a numerical model for the confluent channels was established to study the variation of backwater effects with the parameters in the channel junction. The meeting of flood peaks in the mainstream and tributary can be analyzed with this model. The flood peak meeting is found to be a major factor for the extremely high water level in the mainstream during the 1998 Yangtze River flood. Subsequently the variations of discharge distribution and water level with channel parameters between each branch in this system were studied as well. As a result, flood evolution caused by Jingjiang River shortcut and sediment deposition in the entrance of dividing channels of the Yangtze River may be qualitatively elucidated. It is suggested to be an effective measure for flood mitigation to enhance regulation capability of reservoirs available upstream of the tributaries and harness branch entrance channels.
A simple statistical signal loss model for deep underground garage
DEFF Research Database (Denmark)
Nguyen, Huan Cong; Gimenez, Lucas Chavarria; Kovacs, Istvan;
2016-01-01
In this paper we address the channel modeling aspects for a deep-indoor scenario with extreme coverage conditions in terms of signal losses, namely underground garage areas. We provide an in-depth analysis in terms of path loss (gain) and large scale signal shadowing, and a propose simple propaga...
Modeling Channelization in Coastal Wetlands with Ecological Feedbacks
Hughes, Z. J.; Mahadevan, A.; Pennings, S.; FitzGerald, D.
2014-12-01
In coastal wetlands in Georgia and South Carolina, dendritic channel networks are actively incising headward at the rate of nearly 2 m/yr. The future geomorphic evolution of these marshes remains in question as rates of relative sea-level rise increase. Our objective is to understand the mechanisms that lead to the evolution of these channel networks through field observations and modeling. We model the geomorphological evolution of tidal creeks by viewing the wetland as a permeable medium. The porosity of the medium affects its hydraulic conductivity, which in turn is altered by erosion. Our multiphase model spontaneously generates channelization and branching networks through flow and erosion. In our field studies, we find that crabs play an active role in grazing vegetation and in the bioturbation of sediments. These effects are incorporated in our model based on field and laboratory observations of crab behavior and its effects on the marsh. We find the erosional patterns and channelization are significantly altered by the faunal feedback. Crabs enhance the growth of channels, inducing the headward erosion of creeks where flow-induced stresses are weakest. They are instrumental in generating high rates of creek extension, which channelize the marsh more effectively in response to sea-level rise. This indicates that the evolution of coastal wetlands is responding to interactions between physics and ecology and highlights the importance of the faunal contribution to these feedbacks.
An empirical conceptual gully evolution model for channelled sea cliffs
Leyland, Julian; Darby, Stephen E.
2008-12-01
Incised coastal channels are a specific form of incised channel that are found in locations where stream channels flowing to cliffed coasts have the excess energy required to cut down through the cliff to reach the outlet water body. The southern coast of the Isle of Wight, southern England, comprises soft cliffs that vary in height between 15 and 100 m and which are retreating at rates ≤ 1.5 m a - 1 , due to a combination of wave erosion and landslides. In several locations, river channels have cut through the cliffs to create deeply (≤ 45 m) incised gullies, known locally as 'Chines'. The Chines are unusual in that their formation is associated with dynamic shoreline encroachment during a period of rising sea-level, whereas existing models of incised channel evolution emphasise the significance of base level lowering. This paper develops a conceptual model of Chine evolution by applying space for time substitution methods using empirical data gathered from Chine channel surveys and remotely sensed data. The model identifies a sequence of evolutionary stages, which are classified based on a suite of morphometric indices and associated processes. The extent to which individual Chines are in a state of growth or decay is estimated by determining the relative rates of shoreline retreat and knickpoint recession, the former via analysis of historical aerial images and the latter through the use of a stream power erosion model.
Numerical modelling of channel migration with application to laboratory rivers
Institute of Scientific and Technical Information of China (English)
Jian SUN; Bin-liang LIN; Hong-wei KUANG
2015-01-01
The paper presents the development of a morphological model and its application to experimental model rivers. The model takes into account the key processes of channel migration, including bed deformation, bank failure and wetting and drying. Secondary flows in bends play an important role in lateral sediment transport, which further affects channel migration. A new formula has been derived to predict the near-bed secondary flow speed, in which the magnitude of the speed is linked to the lateral water level gradient. Since only non-cohesive sediment is considered in the current study, the bank failure is modelled based on the concept of submerged angle of repose. The wetting and drying process is modelled using an existing method. Comparisons between the numerical model predictions and experimental observations for various discharges have been made. It is found that the model predicted channel planform and cross-sectional shapes agree generally well with the laboratory observations. A scenario analysis is also carried out to investigate the impact of secondary flow on the channel migration process. It shows that if the effect of secondary flow is ignored, the channel size in the lateral direction will be seriously underestimated.
Statistical models and NMR analysis of polymer microstructure
Statistical models can be used in conjunction with NMR spectroscopy to study polymer microstructure and polymerization mechanisms. Thus, Bernoullian, Markovian, and enantiomorphic-site models are well known. Many additional models have been formulated over the years for additional situations. Typica...
Statistical Research for Probabilistic Model of Distortions of Remote Sensing
Ayman, Iskakova
2016-08-01
In this work the new multivariate discrete probability model of distribution of processes distortion of radiation from remote sensing data is proposed and studied. Research was performed on a full cycle adopted in mathematical statistics, namely, the model was constructed and investigated, various methods for estimating the parameters was proposed and test the hypothesis that the model adequacy observations, was considered.
Modeling water droplet condensation and evaporation in DNS of turbulent channel flow
International Nuclear Information System (INIS)
In this paper a point particle model for two-way coupling in water droplet-laden incompressible turbulent flow of air is proposed. The model is based on conservation laws and semi-empirical correlations. It has been implemented and tested in a DNS code based for turbulent channel flow with an Eulerian-Lagrangian approach. The two-way coupling is investigated in terms of the effects of mass and heat transfer on the droplets distributions along the channel wall-normal direction and by comparison of the droplet temperature statistics with respect to the case without evaporation and condensation. A remarkable conclusion is that the presence of evaporating and condensing droplets results in an increase in the non-dimensional heat transfer coefficient of the channel flow represented by the Nusselt number.
A New Method of Blind Source Separation Using Single-Channel ICA Based on Higher-Order Statistics
Directory of Open Access Journals (Sweden)
Guangkuo Lu
2015-01-01
Full Text Available Methods of utilizing independent component analysis (ICA give little guidance about practical considerations for separating single-channel real-world data, in which most of them are nonlinear, nonstationary, and even chaotic in many fields. To solve this problem, a three-step method is provided in this paper. In the first step, the measured signal which is assumed to be piecewise higher order stationary time series is introduced and divided into a series of higher order stationary segments by applying a modified segmentation algorithm. Then the state space is reconstructed and the single-channel signal is transformed into a pseudo multiple input multiple output (MIMO mode using a method of nonlinear analysis based on the high order statistics (HOS. In the last step, ICA is performed on the pseudo MIMO data to decompose the single channel recording into its underlying independent components (ICs and the interested ICs are then extracted. Finally, the effectiveness and excellence of the higher order single-channel ICA (SCICA method are validated with measured data throughout experiments. Also, the proposed method in this paper is proved to be more robust under different SNR and/or embedding dimension via explicit formulae and simulations.
Dynamic Propagation Channel Characterization and Modeling for Human Body Communication
Lei Wang; Jingjing Ma; Zhicheng Li; Hong Chen; Zedong Nie
2012-01-01
This paper presents the first characterization and modeling of dynamic propagation channels for human body communication (HBC). In-situ experiments were performed using customized transceivers in an anechoic chamber. Three HBC propagation channels, i.e., from right leg to left leg, from right hand to left hand and from right hand to left leg, were investigated under thirty-three motion scenarios. Snapshots of data (2,800,000) were acquired from five volunteers. Various path gains caused by di...
Models for probability and statistical inference theory and applications
Stapleton, James H
2007-01-01
This concise, yet thorough, book is enhanced with simulations and graphs to build the intuition of readersModels for Probability and Statistical Inference was written over a five-year period and serves as a comprehensive treatment of the fundamentals of probability and statistical inference. With detailed theoretical coverage found throughout the book, readers acquire the fundamentals needed to advance to more specialized topics, such as sampling, linear models, design of experiments, statistical computing, survival analysis, and bootstrapping.Ideal as a textbook for a two-semester sequence on probability and statistical inference, early chapters provide coverage on probability and include discussions of: discrete models and random variables; discrete distributions including binomial, hypergeometric, geometric, and Poisson; continuous, normal, gamma, and conditional distributions; and limit theory. Since limit theory is usually the most difficult topic for readers to master, the author thoroughly discusses mo...
Yang, Huaiyu; Gao, Zhaobing; Li, Ping; Yu, Kunqian; Yu, Ye; Xu, Tian-Le; Li, Min; Jiang, Hualiang
2012-01-01
Voltage sensing confers conversion of a change in membrane potential to signaling activities underlying the physiological processes. For an ion channel, voltage sensitivity is usually experimentally measured by fitting electrophysiological data to Boltzmann distributions. In our study, a two-state model of the ion channel and equilibrium statistical mechanics principle were used to test the hypothesis of empirically calculating the overall voltage sensitivity of an ion channel on the basis of its closed and open conformations, and determine the contribution of individual residues to the voltage sensing. We examined the theoretical paradigm by performing experimental measurements with Kv1.2 channel and a series of mutants. The correlation between the calculated values and the experimental values is at respective level, R2 = 0.73. Our report therefore provides in silico prediction of key conformations and has identified additional residues critical for voltage sensing. PMID:22768937
International Nuclear Information System (INIS)
Recently, an adjustable, high-sensitivity, wide dynamic range, two-channel wavefront sensor based on moiré deflectometry was proposed by Rasouli et al (2010 Opt. Express 18 23906). In this work we have used this sensor on a telescope for measuring turbulence-induced wavefront distortions. A slightly divergent laser beam passes through turbulent ground level atmosphere and enters the telescope’s aperture. The laser beam is collimated behind the telescope’s focal point by means of a collimator and the beam enters the wavefront sensor. First, from deviations in the moiré fringes we calculate the two orthogonal components of the angle of arrival at each location across the wavefront. The deviations have been deduced in successive frames which allows evolution of the wavefront shape and Fried’s seeing parameter r0 to be determined. Mainly, statistical analysis of the reconstructed wavefront distortions are presented. The achieved accuracy in the measurements and comparison between the measurements and the theoretical models are presented. Owing to the use of the sensor on a telescope, and using sub-pixel accuracy for the measurement of the moiré fringe displacements, the sensitivity of the measurements is improved by more than one order of magnitude. In this work we have achieved a minimum measurable angle of arrival fluctuations equal to 3.7 × 10−7 rad or 0.07 arc s. Besides, because of the large area of the telescope’s aperture, a high spatial resolution is achieved in detecting the spatial perturbations of the atmospheric turbulence. (paper)
Model studies of dense water overflows in the Faroese Channels
Cuthbertson, Alan; Davies, Peter; Stashchuk, Nataliya; Vlasenko, Vasiliy
2014-01-01
The overflow of dense water from the Nordic Seas through the Faroese Channel system was investigated through combined laboratory experiments and numerical simulations using the Massachusetts Institute of Technology General Circulation Model. In the experimental study, a scaled, topographic representation of the Faroe-Shetland Channel, Wyville-Thomson Basin and Ridge and Faroe Bank Channel seabed bathymetry was constructed and mounted in a rotating tank. A series of parametric experiments was conducted using dye-tracing and drogue-tracking techniques to investigate deep-water overflow pathways and circulation patterns within the modelled region. In addition, the structure of the outflowing dense bottom water was investigated through density profiling along three cross-channel transects located in the Wyville-Thomson Basin and the converging, up-sloping approach to the Faroe Bank Channel. Results from the dye-tracing studies demonstrate a range of parametric conditions under which dense water overflow across the Wyville-Thomson Ridge is shown to occur, as defined by the Burger number, a non-dimensional length ratio and a dimensionless dense water volume flux parameter specified at the Faroe-Shetland Channel inlet boundary. Drogue-tracking measurements reveal the complex nature of flow paths and circulations generated in the modelled topography, particularly the development of a large anti-cyclonic gyre in the Wyville-Thompson Basin and up-sloping approach to the Faroe Bank Channel, which diverts the dense water outflow from the Faroese shelf towards the Wyville-Thomson Ridge, potentially promoting dense water spillage across the ridge itself. The presence of this circulation is also indicated by associated undulations in density isopycnals across the Wyville-Thomson Basin. Numerical simulations of parametric test cases for the main outflow pathways and density structure in a similarly-scaled Faroese Channels model domain indicate excellent qualitative agreement with
Ferroelectric active models of ion channels in biomembranes.
Bystrov, V S; Lakhno, V D; Molchanov, M
1994-06-21
Ferroactive models of ion channels in the theory of biological membranes are presented. The main equations are derived and their possible solutions are shown. The estimates of some experimentally measured parameters are given. Possible physical consequences of the suggested models are listed and the possibility of their experimental finding is discussed. The functioning of the biomembrane's ion channel is qualitatively described on the basis of the suggested ferroactive models. The main directions and prospects for development of the ferroactive approach to the theory of biological membranes and their structures are indicated.
Equilibrium Statistical-Thermal Models in High-Energy Physics
Tawfik, Abdel Nasser
2014-01-01
We review some recent highlights from the applications of statistical-thermal models to different experimental measurements and lattice QCD thermodynamics, that have been made during the last decade. We start with a short review of the historical milestones on the path of constructing statistical-thermal models for heavy-ion physics. We discovered that Heinz Koppe formulated in 1948 an almost complete recipe for the statistical-thermal models. In 1950, Enrico Fermi generalized this statistical approach, in which he started with a general cross-section formula and inserted into it simplifying assumptions about the matrix element of the interaction process that likely reflects many features of the high-energy reactions dominated by density in the phase space of final states. In 1964, Hagedorn systematically analysed the high-energy phenomena using all tools of statistical physics and introduced the concept of limiting temperature based on the statistical bootstrap model. It turns to be quite often that many-par...
Matolak, D. W.; Apaza, Rafael; Foore, Lawrence R.
2006-01-01
We describe a recently completed wideband wireless channel characterization project for the 5 GHz Microwave Landing System (MLS) extension band, for airport surface areas. This work included mobile measurements at large and small airports, and fixed point-to-point measurements. Mobile measurements were made via transmission from the air traffic control tower (ATCT), or from an airport field site (AFS), to a receiving ground vehicle on the airport surface. The point-to-point measurements were between ATCT and AFSs. Detailed statistical channel models were developed from all these measurements. Measured quantities include propagation path loss and power delay profiles, from which we obtain delay spreads, frequency domain correlation (coherence bandwidths), fading amplitude statistics, and channel parameter correlations. In this paper we review the project motivation, measurement coordination, and illustrate measurement results. Example channel modeling results for several propagation conditions are also provided, highlighting new findings.
Monte Carlo Modeling of Crystal Channeling at High Energies
Schoofs, Philippe; Cerutti, Francesco
Charged particles entering a crystal close to some preferred direction can be trapped in the electromagnetic potential well existing between consecutive planes or strings of atoms. This channeling effect can be used to extract beam particles if the crystal is bent beforehand. Crystal channeling is becoming a reliable and efficient technique for collimating beams and removing halo particles. At CERN, the installation of silicon crystals in the LHC is under scrutiny by the UA9 collaboration with the goal of investigating if they are a viable option for the collimation system upgrade. This thesis describes a new Monte Carlo model of planar channeling which has been developed from scratch in order to be implemented in the FLUKA code simulating particle transport and interactions. Crystal channels are described through the concept of continuous potential taking into account thermal motion of the lattice atoms and using Moliere screening function. The energy of the particle transverse motion determines whether or n...
Map-Based Channel Model for Urban Macrocell Propagation Scenarios
Directory of Open Access Journals (Sweden)
Jose F. Monserrat
2015-01-01
Full Text Available The evolution of LTE towards 5G has started and different research projects and institutions are in the process of verifying new technology components through simulations. Coordination between groups is strongly recommended and, in this sense, a common definition of test cases and simulation models is needed. The scope of this paper is to present a realistic channel model for urban macrocell scenarios. This model is map-based and takes into account the layout of buildings situated in the area under study. A detailed description of the model is given together with a comparison with other widely used channel models. The benchmark includes a measurement campaign in which the proposed model is shown to be much closer to the actual behavior of a cellular system. Particular attention is given to the outdoor component of the model, since it is here where the proposed approach is showing main difference with other previous models.
Advances on statistical/thermodynamical models for unpolarized structure functions
International Nuclear Information System (INIS)
During the eights and nineties many statistical/thermodynamical models were proposed to describe the nucleons’ structure functions and distribution of the quarks in the hadrons. Most of these models describe the compound quarks and gluons inside the nucleon as a Fermi / Bose gas respectively, confined in a MIT bag with continuous energy levels. Another models considers discrete spectrum. Some interesting features of the nucleons are obtained by these models, like the sea asymmetries -d/-u and -d–-u.
In all likelihood statistical modelling and inference using likelihood
Pawitan, Yudi
2001-01-01
Based on a course in the theory of statistics this text concentrates on what can be achieved using the likelihood/Fisherian method of taking account of uncertainty when studying a statistical problem. It takes the concept ot the likelihood as providing the best methods for unifying the demands of statistical modelling and the theory of inference. Every likelihood concept is illustrated by realistic examples, which are not compromised by computational problems. Examples range from asimile comparison of two accident rates, to complex studies that require generalised linear or semiparametric mode
Complex Data Modeling and Computationally Intensive Statistical Methods
Mantovan, Pietro
2010-01-01
The last years have seen the advent and development of many devices able to record and store an always increasing amount of complex and high dimensional data; 3D images generated by medical scanners or satellite remote sensing, DNA microarrays, real time financial data, system control datasets. The analysis of this data poses new challenging problems and requires the development of novel statistical models and computational methods, fueling many fascinating and fast growing research areas of modern statistics. The book offers a wide variety of statistical methods and is addressed to statistici
A channel transmission losses model for different dryland rivers
Directory of Open Access Journals (Sweden)
A. C. Costa
2011-10-01
Full Text Available Channel transmission losses in drylands take place normally in extensive alluvial channels or streambeds underlain by fractured rocks. They can play an important role in flood prediction, groundwater recharge, freshwater supply and channel-associated ecosystems. We aim to develop a semi-distributed channel transmission losses model, a coupling of formulations which are more suitable for data-scarce dryland environments, applicable for both hydraulically disconnected losing streams and hydraulically connected losing(/gaining streams. Hence, this approach should be able to cover a large variation in climate and hydro-geologic controls, which are typically found in dryland regions of the world. Traditionally, channel transmission losses models have been developed for site specific conditions. Our model was firstly evaluated for a losing/gaining, hydraulically connected 30 km reach of the Jaguaribe River, Ceará, Brazil, which controls a catchment area of 20 000 km^{2}. Secondly, we applied it to a small losing, hydraulically disconnected 1.5 km channel reach in the Walnut Gulch Experimental Watershed (WGEW, Arizona, USA. The model based on the perceptual hydrological models of the reaches was able to predict reliably the stream flow for the both case studies. For the larger river reach, the evaluation of the hypotheses on the dominant hydrological processes was fundamental for reducing structural model uncertainties and improving the stream flow prediction, showing that both lateral stream-aquifer water fluxes and groundwater flow in the underlying alluvium parallel to the river course are necessary to predict stream flow and channel transmission losses, the former process being more relevant than the latter. The sensitivity analysis showed that even if the parameters can "potentially" produce large flow exchanges between model units in the saturated part of the modelling, large flow exchanges do not happen because they are restricted by
Speech emotion recognition based on statistical pitch model
Institute of Scientific and Technical Information of China (English)
WANG Zhiping; ZHAO Li; ZOU Cairong
2006-01-01
A modified Parzen-window method, which keep high resolution in low frequencies and keep smoothness in high frequencies, is proposed to obtain statistical model. Then, a gender classification method utilizing the statistical model is proposed, which have a 98% accuracy of gender classification while long sentence is dealt with. By separation the male voice and female voice, the mean and standard deviation of speech training samples with different emotion are used to create the corresponding emotion models. Then the Bhattacharyya distance between the test sample and statistical models of pitch, are utilized for emotion recognition in speech.The normalization of pitch for the male voice and female voice are also considered, in order to illustrate them into a uniform space. Finally, the speech emotion recognition experiment based on K Nearest Neighbor shows that, the correct rate of 81% is achieved, where it is only 73.85%if the traditional parameters are utilized.
Probabilistic Quantitative Precipitation Forecasting Using Ensemble Model Output Statistics
Scheuerer, Michael
2013-01-01
Statistical post-processing of dynamical forecast ensembles is an essential component of weather forecasting. In this article, we present a post-processing method that generates full predictive probability distributions for precipitation accumulations based on ensemble model output statistics (EMOS). We model precipitation amounts by a generalized extreme value distribution that is left-censored at zero. This distribution permits modelling precipitation on the original scale without prior transformation of the data. A closed form expression for its continuous rank probability score can be derived and permits computationally efficient model fitting. We discuss an extension of our approach that incorporates further statistics characterizing the spatial variability of precipitation amounts in the vicinity of the location of interest. The proposed EMOS method is applied to daily 18-h forecasts of 6-h accumulated precipitation over Germany in 2011 using the COSMO-DE ensemble prediction system operated by the Germa...
A statistical model for the excitation of cavities through apertures
Gradoni, Gabriele; Anlage, Steven M; Ott, Edward
2015-01-01
In this paper, a statistical model for the coupling of electromagnetic radiation into enclosures through apertures is presented. The model gives a unified picture bridging deterministic theories of aperture radiation, and statistical models necessary for capturing the properties of irregular shaped enclosures. A Monte Carlo technique based on random matrix theory is used to predict and study the power transmitted through the aperture into the enclosure. Universal behavior of the net power entering the aperture is found. Results are of interest for predicting the coupling of external radiation through openings in irregular enclosures and reverberation chambers.
Linear mixed models a practical guide using statistical software
West, Brady T; Galecki, Andrzej T
2006-01-01
Simplifying the often confusing array of software programs for fitting linear mixed models (LMMs), Linear Mixed Models: A Practical Guide Using Statistical Software provides a basic introduction to primary concepts, notation, software implementation, model interpretation, and visualization of clustered and longitudinal data. This easy-to-navigate reference details the use of procedures for fitting LMMs in five popular statistical software packages: SAS, SPSS, Stata, R/S-plus, and HLM. The authors introduce basic theoretical concepts, present a heuristic approach to fitting LMMs based on bo
General Linear Models: An Integrated Approach to Statistics
Andrew Faulkner; Sylvain Chartier
2008-01-01
Generally, in psychology, the various statistical analyses are taught independently from each other. As a consequence, students struggle to learn new statistical analyses, in contexts that differ from their textbooks. This paper gives a short introduction to the general linear model (GLM), in which it is showed that ANOVA (one-way, factorial, repeated measure and analysis of covariance) is simply a multiple correlation/regression analysis (MCRA). Generalizations to other cases, such as multiv...
Error Bounds in the Phased Array Antenna. A statistical Model
Vellekoop, A.R.; Snoeij, P.; Koomen, P.J.
1991-01-01
Expressions are generated for the probabilistic analysis of phased-array antenna-pattern degradation subject to random errors in the excitation coefficients and angle measurement errors by means of a model based upon a statistical coefficient of variation model. The expressions are exercised and com
Quantum Statistical Physics of a Microscopic Glass Model
Thesen, Michael
2003-01-01
We investigate the quantum statistical physics of a microscopic mean-field glass model in various approximations using the replica method and effective action methods from quantum field theory. We recover results from a semiclassical treatment and find relations to quantum spherical p-spin models.
Multi-region Statistical Shape Model for Cochlear Implantation
DEFF Research Database (Denmark)
Romera, Jordi; Kjer, H. Martin; Piella, Gemma;
2016-01-01
Statistical shape models are commonly used to analyze the variability between similar anatomical structures and their use is established as a tool for analysis and segmentation of medical images. However, using a global model to capture the variability of complex structures is not enough to achie...
Statistical Design Model (SDM) of satellite thermal control subsystem
Mirshams, Mehran; Zabihian, Ehsan; Aarabi Chamalishahi, Mahdi
2016-07-01
Satellites thermal control, is a satellite subsystem that its main task is keeping the satellite components at its own survival and activity temperatures. Ability of satellite thermal control plays a key role in satisfying satellite's operational requirements and designing this subsystem is a part of satellite design. In the other hand due to the lack of information provided by companies and designers still doesn't have a specific design process while it is one of the fundamental subsystems. The aim of this paper, is to identify and extract statistical design models of spacecraft thermal control subsystem by using SDM design method. This method analyses statistical data with a particular procedure. To implement SDM method, a complete database is required. Therefore, we first collect spacecraft data and create a database, and then we extract statistical graphs using Microsoft Excel, from which we further extract mathematical models. Inputs parameters of the method are mass, mission, and life time of the satellite. For this purpose at first thermal control subsystem has been introduced and hardware using in the this subsystem and its variants has been investigated. In the next part different statistical models has been mentioned and a brief compare will be between them. Finally, this paper particular statistical model is extracted from collected statistical data. Process of testing the accuracy and verifying the method use a case study. Which by the comparisons between the specifications of thermal control subsystem of a fabricated satellite and the analyses results, the methodology in this paper was proved to be effective. Key Words: Thermal control subsystem design, Statistical design model (SDM), Satellite conceptual design, Thermal hardware
Validation of statistical models for creep rupture by parametric analysis
Energy Technology Data Exchange (ETDEWEB)
Bolton, J., E-mail: john.bolton@uwclub.net [65, Fisher Ave., Rugby, Warks CV22 5HW (United Kingdom)
2012-01-15
Statistical analysis is an efficient method for the optimisation of any candidate mathematical model of creep rupture data, and for the comparative ranking of competing models. However, when a series of candidate models has been examined and the best of the series has been identified, there is no statistical criterion to determine whether a yet more accurate model might be devised. Hence there remains some uncertainty that the best of any series examined is sufficiently accurate to be considered reliable as a basis for extrapolation. This paper proposes that models should be validated primarily by parametric graphical comparison to rupture data and rupture gradient data. It proposes that no mathematical model should be considered reliable for extrapolation unless the visible divergence between model and data is so small as to leave no apparent scope for further reduction. This study is based on the data for a 12% Cr alloy steel used in BS PD6605:1998 to exemplify its recommended statistical analysis procedure. The models considered in this paper include a) a relatively simple model, b) the PD6605 recommended model and c) a more accurate model of somewhat greater complexity. - Highlights: Black-Right-Pointing-Pointer The paper discusses the validation of creep rupture models derived from statistical analysis. Black-Right-Pointing-Pointer It demonstrates that models can be satisfactorily validated by a visual-graphic comparison of models to data. Black-Right-Pointing-Pointer The method proposed utilises test data both as conventional rupture stress and as rupture stress gradient. Black-Right-Pointing-Pointer The approach is shown to be more reliable than a well-established and widely used method (BS PD6605).
The Large Office Environment - Measurement and Modeling of the Wideband Radio Channel
DEFF Research Database (Denmark)
Andersen, Jørgen Bach; Nielsen, Jesper Ødum; Bauch, Gerhard;
2006-01-01
In a future 4G or WLAN wideband application we can imagine multiple users in a large office environment con-sisting of a single room with partitions. Up to now, indoor radio channel measurement and modelling has mainly concentrated on scenarios with several office rooms and corridors. We present...... here measurements at 5.8GHz for 100 MHz bandwidth and a novel modelling approach for the wideband radio channel in a large office room envi-ronment. An acoustic like reverberation theory is pro-posed that allows to specify a tapped delay line model just from the room dimensions and an average...... absorption co-efficient of the delimiting walls. The proposed model agrees amazingly well with the measurements, showing that the diffuse part is uniformly spread over the room with a constant energy level and a constant temporal de-cay slope. Furthermore, we analyze fading statistics and capacities...
Statistical Modeling for Wind-Temperature Meteorological Elements in Troposphere
Virtser, A; Golbraikh, E
2010-01-01
A comprehensive statistical model for vertical profiles of the horizontal wind and temperature throughout the troposphere is presented. The model is based on radiosonde measurements of wind and temperature during several years. The profiles measured under quite different atmospheric conditions exhibit qualitative similarity, and a proper choice of the reference scales for the wind, temperature and altitude levels allows to consider the measurement data as realizations of a random process with universal characteristics: means, the basic functions and parameters of standard distributions for transform coefficients of the Principal Component Analysis. The features of the atmospheric conditions are described by statistical characteristics of the wind-temperature ensemble of dimensional reference scales. The high effectiveness of the proposed approach is provided by a similarity of wind - temperature vertical profiles, which allow to carry out the statistical modeling in the low-dimension space of the dimensional ...
Computationally efficient statistical differential equation modeling using homogenization
Hooten, Mevin B.; Garlick, Martha J.; Powell, James A.
2013-01-01
Statistical models using partial differential equations (PDEs) to describe dynamically evolving natural systems are appearing in the scientific literature with some regularity in recent years. Often such studies seek to characterize the dynamics of temporal or spatio-temporal phenomena such as invasive species, consumer-resource interactions, community evolution, and resource selection. Specifically, in the spatial setting, data are often available at varying spatial and temporal scales. Additionally, the necessary numerical integration of a PDE may be computationally infeasible over the spatial support of interest. We present an approach to impose computationally advantageous changes of support in statistical implementations of PDE models and demonstrate its utility through simulation using a form of PDE known as “ecological diffusion.” We also apply a statistical ecological diffusion model to a data set involving the spread of mountain pine beetle (Dendroctonus ponderosae) in Idaho, USA.
Analyzing sickness absence with statistical models for survival data
DEFF Research Database (Denmark)
Christensen, Karl Bang; Andersen, Per Kragh; Smith-Hansen, Lars;
2007-01-01
absence data deal with events occurring over time, the use of statistical models for survival data has been reviewed, and the use of frailty models has been proposed for the analysis of such data. METHODS: Three methods for analyzing data on sickness absences were compared using a simulation study...... involving the following: (i) Poisson regression using a single outcome variable (number of sickness absences), (ii) analysis of time to first event using the Cox proportional hazards model, and (iii) frailty models, which are random effects proportional hazards models. Data from a study of the relation...... between the psychosocial work environment and sickness absence were used to illustrate the results. RESULTS: Standard methods were found to underestimate true effect sizes by approximately one-tenth [method i] and one-third [method ii] and to have lower statistical power than frailty models. CONCLUSIONS...
Statistical Validation of Normal Tissue Complication Probability Models
Energy Technology Data Exchange (ETDEWEB)
Xu Chengjian, E-mail: c.j.xu@umcg.nl [Department of Radiation Oncology, University of Groningen, University Medical Center Groningen, Groningen (Netherlands); Schaaf, Arjen van der; Veld, Aart A. van' t; Langendijk, Johannes A. [Department of Radiation Oncology, University of Groningen, University Medical Center Groningen, Groningen (Netherlands); Schilstra, Cornelis [Department of Radiation Oncology, University of Groningen, University Medical Center Groningen, Groningen (Netherlands); Radiotherapy Institute Friesland, Leeuwarden (Netherlands)
2012-09-01
Purpose: To investigate the applicability and value of double cross-validation and permutation tests as established statistical approaches in the validation of normal tissue complication probability (NTCP) models. Methods and Materials: A penalized regression method, LASSO (least absolute shrinkage and selection operator), was used to build NTCP models for xerostomia after radiation therapy treatment of head-and-neck cancer. Model assessment was based on the likelihood function and the area under the receiver operating characteristic curve. Results: Repeated double cross-validation showed the uncertainty and instability of the NTCP models and indicated that the statistical significance of model performance can be obtained by permutation testing. Conclusion: Repeated double cross-validation and permutation tests are recommended to validate NTCP models before clinical use.
Statistical models for nuclear decay. From evaporation to vaporization
International Nuclear Information System (INIS)
The purpose of this book is to present and discuss statistical models which are used to describe the decay of excited atomic nuclei. The subject dates from about 1937 when, building on the Bohr concept of the compound nucleus as a system in temporal equilibrium, Weisskopf first proposed a quantitatively successful statistical model to describe the 'evaporation' of neutrons from excited compound nuclei. The book is intended for use by senior undergraduates and post graduates as well as confirmed experimentalists seeking global perspective concerning the history and current status of this research domain. The book is divided into eight chapters. The first two chapters are concerned with introductions to the statistical mechanics and nuclear physics which are necessary for understanding the development of statistical models of nuclear decay. The second part of the book (chapters 3 and 4) describes the statistical models which were created to describe decay processes at low excitation energy. In chapter 3, the topics include Weisskopf theory for evaporation of neutrons, the Hauser-Feshbach evaporation theory, fusion, the Griffin, Blann-Cline and Harp-Miller-Berne approaches to pre-equilibrium particle emission, and finally, early statistical theories of low energy fission. Chapter 4, which begins with an introduction to Monte Carlo simulations, is mainly concerned with applications of the Hauser-Feshbach theory to single and multistep evaporation. The third part of the text is devoted to the description of decay processes which are 'modern' insofar as the experimental work has been mainly carried out over the last 20 years. These applications include the so-called sequential binary decay mechanism (chapter 5). Multifragmentation is discussed in chapters 6 and 7. Finally, in chapter 8 an attempt was made to draw the threads together in order to build a coherent picture of applications of statistical mechanics to nuclear decay. A few new areas of research are indicated
A Statistical Study of Beam Centroid Oscillations in a Solenoid Transport Channel
Energy Technology Data Exchange (ETDEWEB)
Lund, S; Wootton, C; Coleman, J; Lidia, S; Seidl, P
2009-05-07
A recent theory of transverse centroid oscillations in solenoidally focused beam transport lattices presented in Ref. [1] is applied to statistically analyze properties of the centroid orbit in the Neutralized Drift Compression Experiment (NDCX) at the Lawrence Berkeley National Laboratory. Contributions to the amplitude of the centroid oscillations from mechanical misalignments and initial centroid errors exiting the injector are analyzed. Measured values of the centroid appear consistent with expected alignment tolerances. Correction of these errors is discussed.
Understanding and forecasting polar stratospheric variability with statistical models
Directory of Open Access Journals (Sweden)
C. Blume
2012-02-01
Full Text Available The variability of the north-polar stratospheric vortex is a prominent aspect of the middle atmosphere. This work investigates a wide class of statistical models with respect to their ability to model geopotential and temperature anomalies, representing variability in the polar stratosphere. Four partly nonstationary, nonlinear models are assessed: linear discriminant analysis (LDA; a cluster method based on finite elements (FEM-VARX; a neural network, namely a multi-layer perceptron (MLP; and support vector regression (SVR. These methods model time series by incorporating all significant external factors simultaneously, including ENSO, QBO, the solar cycle, volcanoes, etc., to then quantify their statistical importance. We show that variability in reanalysis data from 1980 to 2005 is successfully modeled. FEM-VARX and MLP even satisfactorily forecast the period from 2005 to 2011. However, internal variability remains that cannot be statistically forecasted, such as the unexpected major warming in January 2009. Finally, the statistical model with the best generalization performance is used to predict a vortex breakdown in late January, early February 2012.
LETTER: Statistical physics of the Schelling model of segregation
Dall'Asta, L.; Castellano, C.; Marsili, M.
2008-07-01
We investigate the static and dynamic properties of a celebrated model of social segregation, providing a complete explanation of the mechanisms leading to segregation both in one- and two-dimensional systems. Standard statistical physics methods shed light on the rich phenomenology of this simple model, exhibiting static phase transitions typical of kinetic constrained models, non-trivial coarsening like in driven-particle systems and percolation-related phenomena.
Enhanced surrogate models for statistical design exploiting space mapping technology
DEFF Research Database (Denmark)
Koziel, Slawek; Bandler, John W.; Mohamed, Achmed S.;
2005-01-01
We present advances in microwave and RF device modeling exploiting Space Mapping (SM) technology. We propose new SM modeling formulations utilizing input mappings, output mappings, frequency scaling and quadratic approximations. Our aim is to enhance circuit models for statistical analysis...... and yield-driven design. We illustrate our results using a capacitively-loaded two-section impedance transformer, a single-resonator waveguide filter and a six-section H-plane waveguide filter....
A Statistical Model for Regional Tornado Climate Studies
Jagger, Thomas H.; James B. Elsner; Widen, Holly M.
2015-01-01
Tornado reports are locally rare, often clustered, and of variable quality making it difficult to use them directly to describe regional tornado climatology. Here a statistical model is demonstrated that overcomes some of these difficulties and produces a smoothed regional-scale climatology of tornado occurrences. The model is applied to data aggregated at the level of counties. These data include annual population, annual tornado counts and an index of terrain roughness. The model has a term...
Directory of Open Access Journals (Sweden)
Szwast Maciej
2015-06-01
Full Text Available The paper presents the mathematical modelling of selected isothermal separation processes of gaseous mixtures, taking place in plants using membranes, in particular nonporous polymer membranes. The modelling concerns membrane modules consisting of two channels - the feeding and the permeate channels. Different shapes of the channels cross-section were taken into account. Consideration was given to co-current and counter-current flows, for feeding and permeate streams, respectively, flowing together with the inert gas receiving permeate. In the proposed mathematical model it was considered that pressure of gas changes along the length of flow channels was the result of both - the drop of pressure connected with flow resistance, and energy transfer by molecules of gas flowing in a given channel to molecules which penetrate this channel from the adjacent channel. The literature on membrane technology takes into account only the drop of pressure connected with flow resistance. Consideration given to energy transfer by molecules of gas flowing in a given channel to molecules which penetrate this channel from the adjacent channel constitute the essential novelty in the current study. The paper also presents results of calculations obtained by means of a computer program which used equations of the derived model. Physicochemical data concerning separation of the CO2/CH4 mixture with He as the sweep gas and data concerning properties of the membrane made of PDMS were assumed for calculations.
The Statistical Modeling of the Trends Concerning the Romanian Population
Directory of Open Access Journals (Sweden)
Gabriela OPAIT
2014-11-01
Full Text Available This paper reflects the statistical modeling concerning the resident population in Romania, respectively the total of the romanian population, through by means of the „Least Squares Method”. Any country it develops by increasing of the population, respectively of the workforce, which is a factor of influence for the growth of the Gross Domestic Product (G.D.P.. The „Least Squares Method” represents a statistical technique for to determine the trend line of the best fit concerning a model.
MODELING OF VEHICULAR STEERING EFFICIENCY IN TRAFFIC DIRECTION MOTION CHANNEL
Directory of Open Access Journals (Sweden)
V. A. Ganai
2011-01-01
Full Text Available The paper formulates and solves an actual problem pertaining to vehicular steering efficiency in traffic direction motion channel. Models of operator-drivers with low, medium and high rates in motivational perception of road conditions and also a model for controlling a traffic direction motion have been taken into ccount in the paper. Modeling has been done by using MATLAB.
Single-channel speech enhancement method based on masking properties and minimum statistics
Institute of Scientific and Technical Information of China (English)
江小平; 姚天任; 傅华
2004-01-01
A single-channel speech enhancement method of noisy speech signals at very low signal-to-noise ratios is presented, which is based on masking properties of the human auditory system and power spectral density estimation of nonstationary noise. It allows for an automatic adaptation in time and frequency of the parametric enhancement system, and finds the best tradeoff among the amount of noise reduction, the speech distortion, and the levd of musicalresidual noise based on a criterion correlated with perception and SNR. This leads to a significant reduction of the unnatural structure of the residual noise. The results with several noise types show that the enhanced speech is more pleasant to a human listener.
International Nuclear Information System (INIS)
Higgs mechanism, introduced in 1964, gives a satisfactory solution to a major problem of the standard model of elementary particles: the origin of the mass. It predicts the existence of the Higgs scalar boson, which mass is not defined by the theory and which has not been discovered experimentally yet (June 2012). The Tevatron, a hadron accelerator based at Fermi National Accelerator Laboratory near Chicago, took data with its two multi-purpose detectors CDF and DO since 1983 up to september 2011. Leaving about 10 fb-1 of statistics to analyze. Associated production of Higgs (H) and vector gauge boson (W) is the main search channel for a light standard Higgs boson. A light Higgs boson is expected to decay in a pair of beauty quarks. Using data collected by DO, we are looking for this production mode taking advantage of sophisticated techniques to improve the signal sensitivity like b-jet identification and multivariate discriminating factors. In the end, a statistical approach allows us to set an upper limit on the ratio between the observed (resp. expected) Higgs production and its theoretical cross section. The results obtained in the WH channel using 9.7 fb-1 at DO is 3.15 (resp. 3.96) for a 115 GeV/c2 Higgs boson. (author)
Applied systems ecology: models, data, and statistical methods
Energy Technology Data Exchange (ETDEWEB)
Eberhardt, L L
1976-01-01
In this report, systems ecology is largely equated to mathematical or computer simulation modelling. The need for models in ecology stems from the necessity to have an integrative device for the diversity of ecological data, much of which is observational, rather than experimental, as well as from the present lack of a theoretical structure for ecology. Different objectives in applied studies require specialized methods. The best predictive devices may be regression equations, often non-linear in form, extracted from much more detailed models. A variety of statistical aspects of modelling, including sampling, are discussed. Several aspects of population dynamics and food-chain kinetics are described, and it is suggested that the two presently separated approaches should be combined into a single theoretical framework. It is concluded that future efforts in systems ecology should emphasize actual data and statistical methods, as well as modelling.
Statistical approaches to pharmacodynamic modeling: motivations, methods, and misperceptions.
Mick, R; Ratain, M J
1993-01-01
We have attempted to outline the fundamental statistical aspects of pharmacodynamic modeling. Unexpected yet substantial variability in effect in a group of similarly treated patients is the key motivation for pharmacodynamic investigations. Pharmacokinetic and/or pharmacodynamic factors may influence this variability. Residual variability in effect that persists after accounting for drug exposure indicates that further statistical modeling with pharmacodynamic factors is warranted. Factors that significantly predict interpatient variability in effect may then be employed to individualize the drug dose. In this paper we have emphasized the need to understand the properties of the effect measure and explanatory variables in terms of scale, distribution, and statistical relationship. The assumptions that underlie many types of statistical models have been discussed. The role of residual analysis has been stressed as a useful method to verify assumptions. We have described transformations and alternative regression methods that are employed when these assumptions are found to be in violation. Sequential selection procedures for the construction of multivariate models have been presented. The importance of assessing model performance has been underscored, most notably in terms of bias and precision. In summary, pharmacodynamic analyses are now commonly performed and reported in the oncologic literature. The content and format of these analyses has been variable. The goals of such analyses are to identify and describe pharmacodynamic relationships and, in many cases, to propose a statistical model. However, the appropriateness and performance of the proposed model are often difficult to judge. Table 1 displays suggestions (in a checklist format) for structuring the presentation of pharmacodynamic analyses, which reflect the topics reviewed in this paper. PMID:8269582
A Review of Modeling Bioelectrochemical Systems: Engineering and Statistical Aspects
Directory of Open Access Journals (Sweden)
Shuai Luo
2016-02-01
Full Text Available Bioelectrochemical systems (BES are promising technologies to convert organic compounds in wastewater to electrical energy through a series of complex physical-chemical, biological and electrochemical processes. Representative BES such as microbial fuel cells (MFCs have been studied and advanced for energy recovery. Substantial experimental and modeling efforts have been made for investigating the processes involved in electricity generation toward the improvement of the BES performance for practical applications. However, there are many parameters that will potentially affect these processes, thereby making the optimization of system performance hard to be achieved. Mathematical models, including engineering models and statistical models, are powerful tools to help understand the interactions among the parameters in BES and perform optimization of BES configuration/operation. This review paper aims to introduce and discuss the recent developments of BES modeling from engineering and statistical aspects, including analysis on the model structure, description of application cases and sensitivity analysis of various parameters. It is expected to serves as a compass for integrating the engineering and statistical modeling strategies to improve model accuracy for BES development.
Statistical modelling of tropical cyclone tracks: non-normal innovations
Hall, T; Hall, Tim; Jewson, Stephen
2005-01-01
We present results from the sixth stage of a project to build a statistical hurricane model. Previous papers have described our modelling of the tracks, genesis, and lysis of hurricanes. In our track model we have so far employed a normal distribution for the residuals when computing innovations, even though we have demonstrated that their distribution is not normal. Here, we test to see if the track model can be improved by including more realistic non-normal innovations. The results are mixed. Some features of the model improve, but others slightly worsen.
Application of Bayesian Hierarchical Prior Modeling to Sparse Channel Estimation
DEFF Research Database (Denmark)
Pedersen, Niels Lovmand; Manchón, Carles Navarro; Shutin, Dmitriy;
2012-01-01
Existing methods for sparse channel estimation typically provide an estimate computed as the solution maximizing an objective function defined as the sum of the log-likelihood function and a penalization term proportional to the l1-norm of the parameter of interest. However, other penalization...... terms have proven to have strong sparsity-inducing properties. In this work, we design pilot assisted channel estimators for OFDM wireless receivers within the framework of sparse Bayesian learning by defining hierarchical Bayesian prior models that lead to sparsity-inducing penalization terms...
Modelling of the new FLNR magnetic analyzer vacuum channel
International Nuclear Information System (INIS)
The quality of any magnetic analyzer directly depends on the area of radial cross section of its volume filled with the ions trajectories. The conception of new magnetic spectrometer vacuum channel is based on computer modelling of the maximum filling of the spectrometer acceptance with given pole pieces width and the gap height of the magnetic dipole together with the maximum transmission of underflected in magnetic field emission from the target at the angle of measurements. The correct correlation of the aperture of the vacuum channel with durability, engineering and ease of handling characteristics combined with ion-optical properties of the spectrometer determines its construction in the whole
STATISTICAL BASED NON-LINEAR MODEL UPDATING USING FEATURE EXTRACTION
Energy Technology Data Exchange (ETDEWEB)
Schultz, J.F.; Hemez, F.M. [and others
2000-10-01
This research presents a new method to improve analytical model fidelity for non-linear systems. The approach investigates several mechanisms to assist the analyst in updating an analytical model based on experimental data and statistical analysis of parameter effects. The first is a new approach at data reduction called feature extraction. This is an expansion of the update metrics to include specific phenomena or character of the response that is critical to model application. This is an extension of the classical linear updating paradigm of utilizing the eigen-parameters or FRFs to include such devices as peak acceleration, time of arrival or standard deviation of model error. The next expansion of the updating process is the inclusion of statistical based parameter analysis to quantify the effects of uncertain or significant effect parameters in the construction of a meta-model. This provides indicators of the statistical variation associated with parameters as well as confidence intervals on the coefficients of the resulting meta-model, Also included in this method is the investigation of linear parameter effect screening using a partial factorial variable array for simulation. This is intended to aid the analyst in eliminating from the investigation the parameters that do not have a significant variation effect on the feature metric, Finally an investigation of the model to replicate the measured response variation is examined.
Predicting lettuce canopy photosynthesis with statistical and neural network models
Frick, J.; Precetti, C.; Mitchell, C. A.
1998-01-01
An artificial neural network (NN) and a statistical regression model were developed to predict canopy photosynthetic rates (Pn) for 'Waldman's Green' leaf lettuce (Latuca sativa L.). All data used to develop and test the models were collected for crop stands grown hydroponically and under controlled-environment conditions. In the NN and regression models, canopy Pn was predicted as a function of three independent variables: shootzone CO2 concentration (600 to 1500 micromoles mol-1), photosynthetic photon flux (PPF) (600 to 1100 micromoles m-2 s-1), and canopy age (10 to 20 days after planting). The models were used to determine the combinations of CO2 and PPF setpoints required each day to maintain maximum canopy Pn. The statistical model (a third-order polynomial) predicted Pn more accurately than the simple NN (a three-layer, fully connected net). Over an 11-day validation period, average percent difference between predicted and actual Pn was 12.3% and 24.6% for the statistical and NN models, respectively. Both models lost considerable accuracy when used to determine relatively long-range Pn predictions (> or = 6 days into the future).
Hypersonic Vehicle Tracking Based on Improved Current Statistical Model
Directory of Open Access Journals (Sweden)
He Guangjun
2013-11-01
Full Text Available A new method of tracking the near space hypersonic vehicle is put forward. According to hypersonic vehicles’ characteristics, we improved current statistical model through online identification of the maneuvering frequency. A Monte Carlo simulation is used to analyze the performance of the method. The results show that the improved method exhibits very good tracking performance in comparison with the old method.
Hypersonic Vehicle Tracking Based on Improved Current Statistical Model
He Guangjun; Lv Hang; Li Baoquan; Li Yanbin
2013-01-01
A new method of tracking the near space hypersonic vehicle is put forward. According to hypersonic vehicles’ characteristics, we improved current statistical model through online identification of the maneuvering frequency. A Monte Carlo simulation is used to analyze the performance of the method. The results show that the improved method exhibits very good tracking performance in comparison with the old method.
Modelling geographical graduate job search using circular statistics
Faggian, Alessandra; Corcoran, Jonathan; McCann, Philip
2013-01-01
Theory suggests that the spatial patterns of migration flows are contingent both on individual human capital and underlying geographical structures. Here we demonstrate these features by using circular statistics in an econometric modelling framework applied to the flows of UK university graduates.
Environmental Concern and Sociodemographic Variables: A Study of Statistical Models
Xiao, Chenyang; McCright, Aaron M.
2007-01-01
Studies of the social bases of environmental concern over the past 30 years have produced somewhat inconsistent results regarding the effects of sociodemographic variables, such as gender, income, and place of residence. The authors argue that model specification errors resulting from violation of two statistical assumptions (interval-level…
ABAREX: A neutron spherical optical-statistical model code
International Nuclear Information System (INIS)
The spherical optical-statistical model is briefly reviewed and the capabilities of the neutron scattering code, ABAREX, are presented. Input files for ten examples, in which neutrons are scattered by various nuclei, are given and the output of each run is discussed in detail
Octet magnetic Moments and their sum rules in statistical model
Batra, M
2013-01-01
The statistical model is implemented to find the magnetic moments of all octet baryons. The well-known sum rules like GMO and CG sum rules has been checked in order to check the consistency of our approach. The small discrepancy between the results suggests the importance of breaking in SU(3) symmetry.
Statistical sampling and modelling for cork oak and eucalyptus stands
Paulo, M.J.
2002-01-01
This thesis focuses on the use of modern statistical methods to solve problems on sampling, optimal cutting time and agricultural modelling in Portuguese cork oak and eucalyptus stands. The results are contained in five chapters that have been submitted for publication as scientific manuscripts.The
A review of the kinetic statistical strength model
Energy Technology Data Exchange (ETDEWEB)
Attia, A.V.
1996-03-11
This is a review of the Kinetic-Statistical Strength (KSS) model described in the report ``Models of Material Strength, Fracture and Failure`` by V. Kuropatenko and V. Bychenkov. The models for metals subjected to high strain rates (explosions) are focussed on. Model implementation appears possible in a hydrocode. Applying the model to the shock response of metals will require a data source for the Weibull parameter {alpha}{sub u}, short of measuing the strength of specimens of various sizes. Model validation will require more detail on the experiments successfully calculated by SPRUT. Evaluation of the KSS model is needed against other existing rate-dependent models for metals such as the Steinberg-Lund or MTS model on other shock experiments.
Applying the luminosity function statistics in the fireshell model
Rangel Lemos, L. J.; Bianco, C. L.; Ruffini, R.
2015-12-01
The luminosity function (LF) statistics applied to the data of BATSE, GBM/Fermi and BAT/Swift is the theme approached in this work. The LF is a strong statistical tool to extract useful information from astrophysical samples, and the key point of this statistical analysis is in the detector sensitivity, where we have performed careful analysis. We applied the tool of the LF statistics to three GRB classes predicted by the Fireshell model. We produced, by LF statistics, predicted distributions of: peak ux N(Fph pk), redshift N(z) and peak luminosity N(Lpk) for the three GRB classes predicted by Fireshell model; we also used three GRB rates. We looked for differences among the distributions, and in fact we found. We performed a comparison between the distributions predicted and observed (with and without redshifts), where we had to build a list with 217 GRBs with known redshifts. Our goal is transform the GRBs in a standard candle, where a alternative is find a correlation between the isotropic luminosity and the Band peak spectral energy (Liso - Epk).
A Statistical model for estimating software testing defects
Directory of Open Access Journals (Sweden)
Dr Shaik Nafeez Umar
2013-07-01
Full Text Available Typically, a software defect plays critical role in software product. The estimation of defects can determine in the product, using advanced statistical techniques based on the historical data, obtained the testing phases. The purpose of this paper is to study and estimate the statistical model, using Rayleigh function in to estimates number of defects passed to the customer. The present study offers to decide how many defects creep in to production and determine the effort spent in months. The estimation model was used on STLC complete product. The accuracy of the model explains 80.47% and 77% of the variation in spent efforts in months associated with number of defects. The model helps in senior management to estimate defects, schedule, cost and effort.
Workshop on Model Uncertainty and its Statistical Implications
1988-01-01
In this book problems related to the choice of models in such diverse fields as regression, covariance structure, time series analysis and multinomial experiments are discussed. The emphasis is on the statistical implications for model assessment when the assessment is done with the same data that generated the model. This is a problem of long standing, notorious for its difficulty. Some contributors discuss this problem in an illuminating way. Others, and this is a truly novel feature, investigate systematically whether sample re-use methods like the bootstrap can be used to assess the quality of estimators or predictors in a reliable way given the initial model uncertainty. The book should prove to be valuable for advanced practitioners and statistical methodologists alike.
Statistical modelling of collocation uncertainty in atmospheric thermodynamic profiles
Directory of Open Access Journals (Sweden)
A. Fassò
2013-08-01
Full Text Available The uncertainty of important atmospheric parameters is a key factor for assessing the uncertainty of global change estimates given by numerical prediction models. One of the critical points of the uncertainty budget is related to the collocation mismatch in space and time among different observations. This is particularly important for vertical atmospheric profiles obtained by radiosondes or LIDAR. In this paper we consider a statistical modelling approach to understand at which extent collocation uncertainty is related to environmental factors, height and distance between the trajectories. To do this we introduce a new statistical approach, based on the heteroskedastic functional regression (HFR model which extends the standard functional regression approach and allows us a natural definition of uncertainty profiles. Moreover, using this modelling approach, a five-folded uncertainty decomposition is proposed. Eventually, the HFR approach is illustrated by the collocation uncertainty analysis of relative humidity from two stations involved in GCOS reference upper-air network (GRUAN.
Calculation of statistical entropic measures in a model of solids
International Nuclear Information System (INIS)
In this work, a one-dimensional model of crystalline solids based on the Dirac comb limit of the Krönig–Penney model is considered. From the wave functions of the valence electrons, we calculate a statistical measure of complexity and the Fisher–Shannon information for the lower energy electronic bands appearing in the system. All these magnitudes present an extremal value for the case of solids having half-filled bands, a configuration where in general a high conductivity is attained in real solids, such as it happens with the monovalent metals. -- Highlights: ► A simplified model of solids is considered. Its electronic band structure is calculated. ► The statistical complexity and the Fisher–Shannon information are computed on this model. ► The extremal value for this indicators are taken on the configurations showing the highest conductivity.
Calculation of statistical entropic measures in a model of solids
Energy Technology Data Exchange (ETDEWEB)
Sañudo, Jaime, E-mail: jsr@unex.es [Departamento de Física, Facultad de Ciencias, Universidad de Extremadura, E-06071 Badajoz (Spain); BIFI, Universidad de Zaragoza, E-50009 Zaragoza (Spain); López-Ruiz, Ricardo, E-mail: rilopez@unizar.es [DIIS and BIFI, Facultad de Ciencias, Universidad de Zaragoza, E-50009 Zaragoza (Spain)
2012-07-09
In this work, a one-dimensional model of crystalline solids based on the Dirac comb limit of the Krönig–Penney model is considered. From the wave functions of the valence electrons, we calculate a statistical measure of complexity and the Fisher–Shannon information for the lower energy electronic bands appearing in the system. All these magnitudes present an extremal value for the case of solids having half-filled bands, a configuration where in general a high conductivity is attained in real solids, such as it happens with the monovalent metals. -- Highlights: ► A simplified model of solids is considered. Its electronic band structure is calculated. ► The statistical complexity and the Fisher–Shannon information are computed on this model. ► The extremal value for this indicators are taken on the configurations showing the highest conductivity.
Statistical models describing the energy signature of buildings
DEFF Research Database (Denmark)
Bacher, Peder; Madsen, Henrik; Thavlov, Anders
2010-01-01
Approximately one third of the primary energy production in Denmark is used for heating in buildings. Therefore efforts to accurately describe and improve energy performance of the building mass are very important. For this purpose statistical models describing the energy signature of a building, i.......e. the heat dynamics of the building, have been developed. The models can be used to obtain rather detailed knowledge of the energy performance of the building and to optimize the control of the energy consumption for heating, which will be vital in conditions with increasing fluctuation of the energy supply...... or varying energy prices. The paper will give an overview of statistical methods and applied models based on experiments carried out in FlexHouse, which is an experimental building in SYSLAB, Risø DTU. The models are of different complexity and can provide estimates of physical quantities such as UA...
Generalized statistical models of voids and hierarchical structure in cosmology
Mekjian, Aram Z
2007-01-01
Generalized statistical models of voids and hierarchical structure in cosmology are developed. The often quoted negative binomial model and frequently used thermodynamic model are shown to be special cases of a more general distribution which contains a parameter "a". The parameter is related to the Levy index alpha and the Fisher critical exponent tau, the latter describing the power law fall off of clumps of matter around a phase transition. The parameter"a", exponent tau, or index alpha can be obtained from properties of a void scaling function. A stochastic probability variable "p" is introduced into a statistical model which represent the adhesive growth of galaxy structure. For p1/2, an adhesive growth can go on indefinitely thereby forming an infinite supercluster. At p=1/2 a scale free power law distribution for the galaxy count distribution is present. The stochastic description also leads to consequences that have some parallels with cosmic string results, percolation theory and phase transitions.
An Order Statistics Approach to the Halo Model for Galaxies
Paul, Niladri; Sheth, Ravi K
2016-01-01
We use the Halo Model to explore the implications of assuming that galaxy luminosities in groups are randomly drawn from an underlying luminosity function. We show that even the simplest of such order statistics models -- one in which this luminosity function $p(L)$ is universal -- naturally produces a number of features associated with previous analyses based on the `central plus Poisson satellites' hypothesis. These include the monotonic relation of mean central luminosity with halo mass, the Lognormal distribution around this mean, and the tight relation between the central and satellite mass scales. In stark contrast to observations of galaxy clustering, however, this model predicts $\\textit{no}$ luminosity dependence of large scale clustering. We then show that an extended version of this model, based on the order statistics of a $\\textit{halo mass dependent}$ luminosity function $p(L|m)$, is in much better agreement with the clustering data as well as satellite luminosities, but systematically under-pre...
Statistical Characterization for L and X-Band Meteorological Satellite Channel%L与X波段气象卫星信道概率统计特性
Institute of Scientific and Technical Information of China (English)
张秀再; 郭业才; 陈金立; 杨昌军
2012-01-01
covering clouds in the cloudy weather, which form part of the shadow block over a certain range spread above the ground station. In this case, the signals received by ground station may have two situations. One circumstance, the received signals are composed of the line of sight and a certain intensity of multipath scattering signals that are diffracted, refracted and scattered, and PDF obeys the statistical characterizations of Rice. The other circumstance, the received signals are composed of the line of sight obscured by clouds, and PDF o-beys the statistical characterizations of Lognormal. There are a few thin clouds in the clear sky and good visibility in the high atmosphere layer, when the signals received by ground station are composed of very weak multipath scattering signals and the line of sight, and PDF obeys the statistical characterizations of Gauss.According to theoretical analysis, the simulation models of Rayleigh, Rice, Lognormal and Gauss probability distribution are established. Through the computer calculation, the results of the simulation models show that the signals received by ground station with different composition lead to different statistical characterizations because meteorological satellite signal pass through different physical state of the atmosphere. The multipath scattering signals both exist in the Rice channel and the Rayleigh channel, however, the line of sight only exists in the Rice channel. Gauss channel model and the Rice channel model have the same structure, but the received signals in both channels have different intensity of the multipath scattering components. That explains the cause why the variety of the received signals envelope brings out different statistical characterizations in different channels. The probability density curve of the simulation model and the theoretical model match quite well, verifying the correctness and validity of the theoretical analysis, providing a theoretical guidance to calculate the data error
Development of 3D statistical mandible models for cephalometric measurements
Energy Technology Data Exchange (ETDEWEB)
Kim, Sung Goo; Yi, Won Jin; Hwang, Soon Jung; Choi, Soon Chul; Lee, Sam Sun; Heo, Min Suk; Huh, Kyung Hoe; Kim, Tae Il [School of Dentistry, Seoul National University, Seoul (Korea, Republic of); Hong, Helen; Yoo, Ji Hyun [Division of Multimedia Engineering, Seoul Women' s University, Seoul (Korea, Republic of)
2012-09-15
The aim of this study was to provide sex-matched three-dimensional (3D) statistical shape models of the mandible, which would provide cephalometric parameters for 3D treatment planning and cephalometric measurements in orthognathic surgery. The subjects used to create the 3D shape models of the mandible included 23 males and 23 females. The mandibles were segmented semi-automatically from 3D facial CT images. Each individual mandible shape was reconstructed as a 3D surface model, which was parameterized to establish correspondence between different individual surfaces. The principal component analysis (PCA) applied to all mandible shapes produced a mean model and characteristic models of variation. The cephalometric parameters were measured directly from the mean models to evaluate the 3D shape models. The means of the measured parameters were compared with those from other conventional studies. The male and female 3D statistical mean models were developed from 23 individual mandibles, respectively. The male and female characteristic shapes of variation produced by PCA showed a large variability included in the individual mandibles. The cephalometric measurements from the developed models were very close to those from some conventional studies. We described the construction of 3D mandibular shape models and presented the application of the 3D mandibular template in cephalometric measurements. Optimal reference models determined from variations produced by PCA could be used for craniofacial patients with various types of skeletal shape.
Statistical approach for uncertainty quantification of experimental modal model parameters
DEFF Research Database (Denmark)
Luczak, M.; Peeters, B.; Kahsin, M.;
2014-01-01
estimates obtained from vibration experiments. Modal testing results are influenced by numerous factors introducing uncertainty to the measurement results. Different experimental techniques applied to the same test item or testing numerous nominally identical specimens yields different test results....... This paper aims at a systematic approach for uncertainty quantification of the parameters of the modal models estimated from experimentally obtained data. Statistical analysis of modal parameters is implemented to derive an assessment of the entire modal model uncertainty measure. Investigated structures...
Statistical Equilibrium of trapped slender vortex filaments - a continuum model
Andersen, Timothy D.; Lim, Chjan C.
2006-01-01
Systems of nearly parallel, slender vortex filaments in which angular momentum is conserved are an important simplification of the Navier-Stokes equations where turbulence can be studied in statistical equilibrium. We study the canonical Gibbs distribution based on the Klein-Majda-Damodaran (KMD) model and find a divergence in the mean square vortex position from that of the point vortex model of Onsager at high temperature. We subsequently develop a free energy equation based on the non-inte...
Statistical and RBF NN models : providing forecasts and risk assessment
Marček, Milan
2009-01-01
Forecast accuracy of economic and financial processes is a popular measure for quantifying the risk in decision making. In this paper, we develop forecasting models based on statistical (stochastic) methods, sometimes called hard computing, and on a soft method using granular computing. We consider the accuracy of forecasting models as a measure for risk evaluation. It is found that the risk estimation process based on soft methods is simplified and less critical to the question w...
Measurement and Modeling of Narrowband Channels for Ultrasonic Underwater Communications
Cañete, Francisco J.; López-Fernández, Jesús; García-Corrales, Celia; Sánchez, Antonio; Robles, Encarnación; Rodrigo, Francisco J.; Paris, José F.
2016-01-01
Underwater acoustic sensor networks are a promising technology that allow real-time data collection in seas and oceans for a wide variety of applications. Smaller size and weight sensors can be achieved with working frequencies shifted from audio to the ultrasonic band. At these frequencies, the fading phenomena has a significant presence in the channel behavior, and the design of a reliable communication link between the network sensors will require a precise characterization of it. Fading in underwater channels has been previously measured and modeled in the audio band. However, there have been few attempts to study it at ultrasonic frequencies. In this paper, a campaign of measurements of ultrasonic underwater acoustic channels in Mediterranean shallow waters conducted by the authors is presented. These measurements are used to determine the parameters of the so-called κ-μ shadowed distribution, a fading model with a direct connection to the underlying physical mechanisms. The model is then used to evaluate the capacity of the measured channels with a closed-form expression. PMID:26907281
Measurement and Modeling of Narrowband Channels for Ultrasonic Underwater Communications
Directory of Open Access Journals (Sweden)
Francisco J. Cañete
2016-02-01
Full Text Available Underwater acoustic sensor networks are a promising technology that allow real-time data collection in seas and oceans for a wide variety of applications. Smaller size and weight sensors can be achieved with working frequencies shifted from audio to the ultrasonic band. At these frequencies, the fading phenomena has a significant presence in the channel behavior, and the design of a reliable communication link between the network sensors will require a precise characterization of it. Fading in underwater channels has been previously measured and modeled in the audio band. However, there have been few attempts to study it at ultrasonic frequencies. In this paper, a campaign of measurements of ultrasonic underwater acoustic channels in Mediterranean shallow waters conducted by the authors is presented. These measurements are used to determine the parameters of the so-called κ-μ shadowed distribution, a fading model with a direct connection to the underlying physical mechanisms. The model is then used to evaluate the capacity of the measured channels with a closed-form expression.
Measurement and Modeling of Narrowband Channels for Ultrasonic Underwater Communications.
Cañete, Francisco J; López-Fernández, Jesús; García-Corrales, Celia; Sánchez, Antonio; Robles, Encarnación; Rodrigo, Francisco J; Paris, José F
2016-01-01
Underwater acoustic sensor networks are a promising technology that allow real-time data collection in seas and oceans for a wide variety of applications. Smaller size and weight sensors can be achieved with working frequencies shifted from audio to the ultrasonic band. At these frequencies, the fading phenomena has a significant presence in the channel behavior, and the design of a reliable communication link between the network sensors will require a precise characterization of it. Fading in underwater channels has been previously measured and modeled in the audio band. However, there have been few attempts to study it at ultrasonic frequencies. In this paper, a campaign of measurements of ultrasonic underwater acoustic channels in Mediterranean shallow waters conducted by the authors is presented. These measurements are used to determine the parameters of the so-called κ-μ shadowed distribution, a fading model with a direct connection to the underlying physical mechanisms. The model is then used to evaluate the capacity of the measured channels with a closed-form expression.
The FPGA Implementation of Short—Wave Channel Model
Institute of Scientific and Technical Information of China (English)
GANLiangcai; LIYuanyuan
2003-01-01
Based on the characteristic of timevariance,short-wave channel can be modeled as a real-time tors of fllter in frequency domain,the model can simulate short-wave channel exactly,such as delay spread,Doppler shift and Doppler spread.In the design,the bandwidth of short-wave channel model is 768kHz,and the frequency interval is 3kHz.A kind of Overlap-Discard algorithm based on the fast Fourier transform (FFT)is utilized to design the real-time FIR filter,and an architectural design structure based on Field Programmable Gate Arrays(FPGA)chip is adopted to implement 512-point FFT.The channel transfer function and the noise and interference function are periodically updated in real-time,which are stored in ROM in advance.The simulation result shows that the hardware implementation is simple and feasible and the wideband short-wave systems,such as frequency-hopping,direct sequence spread spectrum systems.
Statistical modelling of transcript profiles of differentially regulated genes
Directory of Open Access Journals (Sweden)
Sergeant Martin J
2008-07-01
Full Text Available Abstract Background The vast quantities of gene expression profiling data produced in microarray studies, and the more precise quantitative PCR, are often not statistically analysed to their full potential. Previous studies have summarised gene expression profiles using simple descriptive statistics, basic analysis of variance (ANOVA and the clustering of genes based on simple models fitted to their expression profiles over time. We report the novel application of statistical non-linear regression modelling techniques to describe the shapes of expression profiles for the fungus Agaricus bisporus, quantified by PCR, and for E. coli and Rattus norvegicus, using microarray technology. The use of parametric non-linear regression models provides a more precise description of expression profiles, reducing the "noise" of the raw data to produce a clear "signal" given by the fitted curve, and describing each profile with a small number of biologically interpretable parameters. This approach then allows the direct comparison and clustering of the shapes of response patterns between genes and potentially enables a greater exploration and interpretation of the biological processes driving gene expression. Results Quantitative reverse transcriptase PCR-derived time-course data of genes were modelled. "Split-line" or "broken-stick" regression identified the initial time of gene up-regulation, enabling the classification of genes into those with primary and secondary responses. Five-day profiles were modelled using the biologically-oriented, critical exponential curve, y(t = A + (B + CtRt + ε. This non-linear regression approach allowed the expression patterns for different genes to be compared in terms of curve shape, time of maximal transcript level and the decline and asymptotic response levels. Three distinct regulatory patterns were identified for the five genes studied. Applying the regression modelling approach to microarray-derived time course data
Sakano, Rui; Oguri, Akira; Nisikawa, Yunori
We study non-equilibrium currents, current fluctuations and cross-correlations of the currents through Kondo-correlated quantum dots at low applied bias-voltages, using full counting statistics. To elucidate impact of dot-site interaction to these current properties in crossover between noninteracting and some Kondo states, renormalized perturbation theory or local Fermi liquid theory are employed. The exact form of the cumulant generating function up to third order of bias-voltage is derived in term of renormalized parameters. Specifically, crossover behavior of the Fano factor (ratio between noise and current) and current crosscorrelations for two-fold orbital case is discussed with using computed renormalized parameters by numerical renormalization group.
A Unified Channel Charges Expression for Analytic MOSFET Modeling
Hugues Murray; Patrick Martin
2012-01-01
Based on a 1D Poissons equation resolution, we present an analytic model of inversion charges allowing calculation of the drain current and transconductance in the Metal Oxide Semiconductor Field Effect Transistor. The drain current and transconductance are described by analytical functions including mobility corrections and short channel effects (CLM, DIBL). The comparison with the Pao-Sah integral shows excellent accuracy of the model in all inversion modes from strong to weak inversion in ...
Measurement-Based LoS/NLoS Channel Modeling for Hot-Spot Urban Scenarios in UMTS Networks
Directory of Open Access Journals (Sweden)
Jiajing Chen
2014-01-01
Full Text Available A measurement campaign is introduced for modeling radio channels with either line-of-sight (LoS or non-line-of-sight (NLoS connection between user equipment (UE and NodeB (NB in an operating universal mobile telecommunications system. A space-alternating generalized expectation-maximization (SAGE algorithm is applied to estimate the delays and the complex attenuations of multipath components from the obtained channel impulse responses. Based on a novel LoS detection method of multipath parameter estimates, channels are classified into LoS and NLoS categories. Deterministic models which are named “channel maps” and fading statistical models have been constructed for LoS and NLoS, respectively. In addition, statistics of new parameters, such as the distance between the NB and the UE in LoS/NLoS scenarios, the life-distance of LoS channel, the LoS existence probability per location and per NB, the power variation at LoS to NLoS transition and vice versa, and the transition duration, are extracted. These models are applicable for designing and performance evaluation of transmission techniques or systems used by distinguishing the LoS and NLoS channels.
The estimation of yearly probability gain for seismic statistical model
Institute of Scientific and Technical Information of China (English)
无
2000-01-01
Based on the calculation method of information gain in the stochastic process presented by Vere-Jones, the relation between information gain and probability gain is studied, which is very common in earthquake prediction, and the yearly probability gain for seismic statistical model is proposed. The method is applied to the non-stationary Poisson model with whole-process exponential increase and stress release model. In addition, the prediction method of stress release model is obtained based on the inverse function simulation method of stochastic variable.
Predictive data modeling of human type II diabetes related statistics
Jaenisch, Kristina L.; Jaenisch, Holger M.; Handley, James W.; Albritton, Nathaniel G.
2009-04-01
During the course of routine Type II treatment of one of the authors, it was decided to derive predictive analytical Data Models of the daily sampled vital statistics: namely weight, blood pressure, and blood sugar, to determine if the covariance among the observed variables could yield a descriptive equation based model, or better still, a predictive analytical model that could forecast the expected future trend of the variables and possibly eliminate the number of finger stickings required to montior blood sugar levels. The personal history and analysis with resulting models are presented.
STATISTICAL MODELS FOR SEMI-RIGID NEMATIC POLYMERS
Institute of Scientific and Technical Information of China (English)
WANG Xinjiu
1995-01-01
Semi-rigid liquid crystal polymer is a class of liquid crystal polymers different from long rigid rod liquid crystal polymer to which the well-known Onsager and Flory theories are applied. In this paper, three statistical models for the semi-rigid nematic polymer were addressed. They are the elastically jointed rod model, worm-like chain model, and non-homogeneous chain model.The nematic-isotropic transition temperature was examined. The pseudo-second transition temperature is expressed analytically. Comparisons with the experiments were made and the agreements were found.
Stochastic geometry, spatial statistics and random fields models and algorithms
2015-01-01
Providing a graduate level introduction to various aspects of stochastic geometry, spatial statistics and random fields, this volume places a special emphasis on fundamental classes of models and algorithms as well as on their applications, for example in materials science, biology and genetics. This book has a strong focus on simulations and includes extensive codes in Matlab and R, which are widely used in the mathematical community. It can be regarded as a continuation of the recent volume 2068 of Lecture Notes in Mathematics, where other issues of stochastic geometry, spatial statistics and random fields were considered, with a focus on asymptotic methods.
General Linear Models: An Integrated Approach to Statistics
Directory of Open Access Journals (Sweden)
Andrew Faulkner
2008-09-01
Full Text Available Generally, in psychology, the various statistical analyses are taught independently from each other. As a consequence, students struggle to learn new statistical analyses, in contexts that differ from their textbooks. This paper gives a short introduction to the general linear model (GLM, in which it is showed that ANOVA (one-way, factorial, repeated measure and analysis of covariance is simply a multiple correlation/regression analysis (MCRA. Generalizations to other cases, such as multivariate and nonlinear analysis, are also discussed. It can easily be shown that every popular linear analysis can be derived from understanding MCRA.
Minimal sufficient statistics in location-scale parameter models
Mattner, Lutz
2000-01-01
Let f be a probability density on the real line, let n be any positive integer, and assume the condition (R) that logf is locally integrable with respect to Lebesgue measure. Then either logf is almost everywhere equal to a polynomial of degree less than n, or the order statistic of n independent and identically distributed observations from the location-scale parameter model generated by f is minimal sufficient. It follows, subject to (R) and n≥3, that a complete sufficient statistic exists ...
Statistical skull models from 3D X-ray images
Berar, M; Bailly, G; Payan, Y; Berar, Maxime; Desvignes, Michel; Payan, Yohan
2006-01-01
We present 2 statistical models of the skull and mandible built upon an elastic registration method of 3D meshes. The aim of this work is to relate degrees of freedom of skull anatomy, as static relations are of main interest for anthropology and legal medicine. Statistical models can effectively provide reconstructions together with statistical precision. In our applications, patient-specific meshes of the skull and the mandible are high-density meshes, extracted from 3D CT scans. All our patient-specific meshes are registrated in a subject-shared reference system using our 3D-to-3D elastic matching algorithm. Registration is based upon the minimization of a distance between the high density mesh and a shared low density mesh, defined on the vertexes, in a multi resolution approach. A Principal Component analysis is performed on the normalised registrated data to build a statistical linear model of the skull and mandible shape variation. The accuracy of the reconstruction is under the millimetre in the shape...
On Wiener filtering and the physics behind statistical modeling.
Marbach, Ralf
2002-01-01
The closed-form solution of the so-called statistical multivariate calibration model is given in terms of the pure component spectral signal, the spectral noise, and the signal and noise of the reference method. The "statistical" calibration model is shown to be as much grounded on the physics of the pure component spectra as any of the "physical" models. There are no fundamental differences between the two approaches since both are merely different attempts to realize the same basic idea, viz., the spectrometric Wiener filter. The concept of the application-specific signal-to-noise ratio (SNR) is introduced, which is a combination of the two SNRs from the reference and the spectral data. Both are defined and the central importance of the latter for the assessment and development of spectroscopic instruments and methods is explained. Other statistics like the correlation coefficient, prediction error, slope deficiency, etc., are functions of the SNR. Spurious correlations and other practically important issues are discussed in quantitative terms. Most important, it is shown how to use a priori information about the pure component spectra and the spectral noise in an optimal way, thereby making the distinction between statistical and physical calibrations obsolete and combining the best of both worlds. Companies and research groups can use this article to realize significant savings in cost and time for development efforts.
Spherical galaxy models as equilibrium configurations in nonextensive statistics
Cardone, V F; Del Popolo, A
2011-01-01
Considering galaxies as self - gravitating systems of many collisionless particles allows to use methods of statistical mechanics inferring the distribution function of these stellar systems. Actually, the long range nature of the gravitational force contrasts with the underlying assumptions of Boltzmann statistics where the interactions among particles are assumed to be short ranged. A particular generalization of the classical Boltzmann formalism is available within the nonextensive context of Tsallis q -statistics, subject to non -additivity of the entropies of sub - systems. Assuming stationarity and isotropy in the velocity space, it is possible solving the generalized collsionless Boltzmann equation to derive the galaxy distribution function and density profile. We present a particular set of nonextensive models and investigate their dynamical and observable properties. As a test of the viability of this generalized context, we fit the rotation curve of M33 showing that the proposed approach leads to da...
Multi-region statistical shape model for cochlear implantation
Romera, Jordi; Kjer, H. Martin; Piella, Gemma; Ceresa, Mario; González Ballester, Miguel A.
2016-03-01
Statistical shape models are commonly used to analyze the variability between similar anatomical structures and their use is established as a tool for analysis and segmentation of medical images. However, using a global model to capture the variability of complex structures is not enough to achieve the best results. The complexity of a proper global model increases even more when the amount of data available is limited to a small number of datasets. Typically, the anatomical variability between structures is associated to the variability of their physiological regions. In this paper, a complete pipeline is proposed for building a multi-region statistical shape model to study the entire variability from locally identified physiological regions of the inner ear. The proposed model, which is based on an extension of the Point Distribution Model (PDM), is built for a training set of 17 high-resolution images (24.5 μm voxels) of the inner ear. The model is evaluated according to its generalization ability and specificity. The results are compared with the ones of a global model built directly using the standard PDM approach. The evaluation results suggest that better accuracy can be achieved using a regional modeling of the inner ear.
A statistical model for characterization of histopathology images
Álvarez, Pablo; Castro, Guatizalema; Corredor, Germán.; Romero, Eduardo
2015-01-01
Accessing information of interest in collections of histopathology images is a challenging task. To address such issue, previous works have designed searching strategies based on the use of keywords and low-level features. However, those methods have demonstrated to not be enough or practical for this purpose. Alternative low-level features such as cell area, distance among cells and cell density are directly associated to simple histological concepts and could serve as good descriptors for this purpose. In this paper, a statistical model is adapted to represent the distribution of the areas occupied by cells for its use in whole histopathology image characterization. This novel descriptor facilitates the design of metrics based on distribution parameters and also provides new elements for a better image understanding. The proposed model was validated using image processing and statistical techniques. Results showed low error rates, demonstrating the accuracy of the model.
Experimental, statistical, and biological models of radon carcinogenesis
International Nuclear Information System (INIS)
Risk models developed for underground miners have not been consistently validated in studies of populations exposed to indoor radon. Imprecision in risk estimates results principally from differences between exposures in mines as compared to domestic environments and from uncertainties about the interaction between cigarette-smoking and exposure to radon decay products. Uncertainties in extrapolating miner data to domestic exposures can be reduced by means of a broad-based health effects research program that addresses the interrelated issues of exposure, respiratory tract dose, carcinogenesis (molecular/cellular and animal studies, plus developing biological and statistical models), and the relationship of radon to smoking and other copollutant exposures. This article reviews experimental animal data on radon carcinogenesis observed primarily in rats at Pacific Northwest Laboratory. Recent experimental and mechanistic carcinogenesis models of exposures to radon, uranium ore dust, and cigarette smoke are presented with statistical analyses of animal data. 20 refs., 1 fig
Experimental, statistical and biological models of radon carcinogenesis
International Nuclear Information System (INIS)
Risk models developed for underground miners have not been consistently validated in studies of populations exposed to indoor radon. Imprecision in risk estimates results principally from differences between exposures in mines as compared with domestic environments and from uncertainties about the interaction between cigarette smoking and exposure to radon decay products. Uncertainties in extrapolating miner data to domestic exposures can be reduced by means of a broad-based health effects research programme that addresses the interrelated issues of exposure, respiratory tract dose, carcinogenesis (molecular/cellular and animal studies, plus developing biological and statistical models) and the relationship of radon to smoking and other co-pollutant exposures. This article reviews experimental animal data on radon carcinogenesis observed primarily in rats at Pacific Northwest Laboratory. Recent experimental and mechanistic carcinogenesis models of exposures to radon, uranium ore dust, and cigarette smoke are presented with statistical analyses of animal data. (author)
Statistical traffic modeling of MPEG frame size: Experiments and Analysis
Directory of Open Access Journals (Sweden)
Haniph A. Latchman
2009-12-01
Full Text Available For guaranteed quality of service (QoS and sufficient bandwidth in a communication network which provides an integrated multimedia service, it is important to obtain an analytical and tractable model of the compressed MPEG data. This paper presents a statistical approach to a group of picture (GOP MPEG frame size model to increase network traffic performance in a communication network. We extract MPEG frame data from commercial DVD movies and make probability histograms to analyze the statistical characteristics of MPEG frame data. Six candidates of probability distributions are considered here and their parameters are obtained from the empirical data using the maximum likelihood estimation (MLE. This paper shows that the lognormal distribution is the best fitting model of MPEG-2 total frame data.
Statistical 3D damage accumulation model for ion implant simulators
Hernandez-Mangas, J M; Enriquez, L E; Bailon, L; Barbolla, J; Jaraiz, M
2003-01-01
A statistical 3D damage accumulation model, based on the modified Kinchin-Pease formula, for ion implant simulation has been included in our physically based ion implantation code. It has only one fitting parameter for electronic stopping and uses 3D electron density distributions for different types of targets including compound semiconductors. Also, a statistical noise reduction mechanism based on the dose division is used. The model has been adapted to be run under parallel execution in order to speed up the calculation in 3D structures. Sequential ion implantation has been modelled including previous damage profiles. It can also simulate the implantation of molecular and cluster projectiles. Comparisons of simulated doping profiles with experimental SIMS profiles are presented. Also comparisons between simulated amorphization and experimental RBS profiles are shown. An analysis of sequential versus parallel processing is provided.
Statistical model selection with “Big Data”
Directory of Open Access Journals (Sweden)
Jurgen A. Doornik
2015-12-01
Full Text Available Big Data offer potential benefits for statistical modelling, but confront problems including an excess of false positives, mistaking correlations for causes, ignoring sampling biases and selecting by inappropriate methods. We consider the many important requirements when searching for a data-based relationship using Big Data, and the possible role of Autometrics in that context. Paramount considerations include embedding relationships in general initial models, possibly restricting the number of variables to be selected over by non-statistical criteria (the formulation problem, using good quality data on all variables, analyzed with tight significance levels by a powerful selection procedure, retaining available theory insights (the selection problem while testing for relationships being well specified and invariant to shifts in explanatory variables (the evaluation problem, using a viable approach that resolves the computational problem of immense numbers of possible models.
Improved head-driven statistical models for natural language parsing
Institute of Scientific and Technical Information of China (English)
袁里驰
2013-01-01
Head-driven statistical models for natural language parsing are the most representative lexicalized syntactic parsing models, but they only utilize semantic dependency between words, and do not incorporate other semantic information such as semantic collocation and semantic category. Some improvements on this distinctive parser are presented. Firstly, "valency" is an essential semantic feature of words. Once the valency of word is determined, the collocation of the word is clear, and the sentence structure can be directly derived. Thus, a syntactic parsing model combining valence structure with semantic dependency is purposed on the base of head-driven statistical syntactic parsing models. Secondly, semantic role labeling(SRL) is very necessary for deep natural language processing. An integrated parsing approach is proposed to integrate semantic parsing into the syntactic parsing process. Experiments are conducted for the refined statistical parser. The results show that 87.12% precision and 85.04% recall are obtained, and F measure is improved by 5.68% compared with the head-driven parsing model introduced by Collins.
SoS contract verification using statistical model checking
Directory of Open Access Journals (Sweden)
Alessandro Mignogna
2013-11-01
Full Text Available Exhaustive formal verification for systems of systems (SoS is impractical and cannot be applied on a large scale. In this paper we propose to use statistical model checking for efficient verification of SoS. We address three relevant aspects for systems of systems: 1 the model of the SoS, which includes stochastic aspects; 2 the formalization of the SoS requirements in the form of contracts; 3 the tool-chain to support statistical model checking for SoS. We adapt the SMC technique for application to heterogeneous SoS. We extend the UPDM/SysML specification language to express the SoS requirements that the implemented strategies over the SoS must satisfy. The requirements are specified with a new contract language specifically designed for SoS, targeting a high-level English- pattern language, but relying on an accurate semantics given by the standard temporal logics. The contracts are verified against the UPDM/SysML specification using the Statistical Model Checker (SMC PLASMA combined with the simulation engine DESYRE, which integrates heterogeneous behavioral models through the functional mock-up interface (FMI standard. The tool-chain allows computing an estimation of the satisfiability of the contracts by the SoS. The results help the system architect to trade-off different solutions to guide the evolution of the SoS.
Explicit Numerical Modeling of Heat Transfer in Glacial Channels
Jarosch, A. H.; Zwinger, T.
2015-12-01
Turbulent flow and heat transfer of water in englacial channels is explicitly modelelled and the numerical results are compared to the most commonly used heat transfer parameterization in glaciology, i.e. the Dittus-Boelter equation. The three-dimensional flow is simulated by solving the incompressible Navier-Stokes equations utilizing a variational multiscale method (VMS) turbulence model and the finite-element method (i.e. Elmer-FEM software), which also solves the heat equation. By studying a wide range of key parameters of the system, e.g. channel diameter, Reynolds number, water flux, water temperature and Darcy-Weisbach wall roughness (which is explicitly represented on the wall geometry), it is found that the Dittus-Boelter equation is inadequate for glaciological applications and a new, highly suitable heat transfer parameterization for englacial/subglacial channels will be presented. This new parameterization utilizes a standard combination of dimensionless numbers describing the flow and channel (i.e. Reynolds number, Prandtl number and Darcy-Weisbach roughness) to predict a suitable Nusselt number describing the effective heat transfer and thus can be readily used in existing englacial/subglacial hydrology models.
Institute of Scientific and Technical Information of China (English)
仲峰泉; 刘难生; 陆夕云; 庄礼贤
2002-01-01
In the present paper, a new dynamic subgrid-scale (SGS) model of turbulent stress and heat flux for stratified shear flow is proposed. Based on our calculated results of stratified channel flow, the dynamic subgrid-scale model developed in this paper is shown to be effective for large eddy simulation (LES) of stratified turbulent shear flows. The new SGS model is then applied to the LES of the stratified turbulent channel flow to investigate the coupled shear and buoyancy effects on the behavior of turbulent statistics, turbulent heat transfer and flow structures at different Richardson numbers.
Wen, Gezheng; Markey, Mia K.
2015-03-01
It is resource-intensive to conduct human studies for task-based assessment of medical image quality and system optimization. Thus, numerical model observers have been developed as a surrogate for human observers. The Hotelling observer (HO) is the optimal linear observer for signal-detection tasks, but the high dimensionality of imaging data results in a heavy computational burden. Channelization is often used to approximate the HO through a dimensionality reduction step, but how to produce channelized images without losing significant image information remains a key challenge. Kernel local Fisher discriminant analysis (KLFDA) uses kernel techniques to perform supervised dimensionality reduction, which finds an embedding transformation that maximizes betweenclass separability and preserves within-class local structure in the low-dimensional manifold. It is powerful for classification tasks, especially when the distribution of a class is multimodal. Such multimodality could be observed in many practical clinical tasks. For example, primary and metastatic lesions may both appear in medical imaging studies, but the distributions of their typical characteristics (e.g., size) may be very different. In this study, we propose to use KLFDA as a novel channelization method. The dimension of the embedded manifold (i.e., the result of KLFDA) is a counterpart to the number of channels in the state-of-art linear channelization. We present a simulation study to demonstrate the potential usefulness of KLFDA for building the channelized HOs (CHOs) and generating reliable decision statistics for clinical tasks. We show that the performance of the CHO with KLFDA channels is comparable to that of the benchmark CHOs.
Physics-based statistical learning approach to mesoscopic model selection
Taverniers, Søren; Haut, Terry S.; Barros, Kipton; Alexander, Francis J.; Lookman, Turab
2015-11-01
In materials science and many other research areas, models are frequently inferred without considering their generalization to unseen data. We apply statistical learning using cross-validation to obtain an optimally predictive coarse-grained description of a two-dimensional kinetic nearest-neighbor Ising model with Glauber dynamics (GD) based on the stochastic Ginzburg-Landau equation (sGLE). The latter is learned from GD "training" data using a log-likelihood analysis, and its predictive ability for various complexities of the model is tested on GD "test" data independent of the data used to train the model on. Using two different error metrics, we perform a detailed analysis of the error between magnetization time trajectories simulated using the learned sGLE coarse-grained description and those obtained using the GD model. We show that both for equilibrium and out-of-equilibrium GD training trajectories, the standard phenomenological description using a quartic free energy does not always yield the most predictive coarse-grained model. Moreover, increasing the amount of training data can shift the optimal model complexity to higher values. Our results are promising in that they pave the way for the use of statistical learning as a general tool for materials modeling and discovery.
Think continuous: Markovian Gaussian models in spatial statistics
Simpson, Daniel; Rue, Håvard
2011-01-01
Gaussian Markov random fields (GMRFs) are frequently used as computationally efficient models in spatial statistics. Unfortunately, it has traditionally been difficult to link GMRFs with the more traditional Gaussian random field models as the Markov property is difficult to deploy in continuous space. Following the pioneering work of Lindgren et al. (2011), we expound on the link between Markovian Gaussian random fields and GMRFs. In particular, we discuss the theoretical and practical aspects of fast computation with continuously specified Markovian Gaussian random fields, as well as the clear advantages they offer in terms of clear, parsimonious and interpretable models of anisotropy and non-stationarity.
Contribution towards statistical intercomparison of general circulation models
Energy Technology Data Exchange (ETDEWEB)
Sengupta, S.; Boyle, J.
1995-06-01
The Atmospheric Model Intercomparison Project (AMIP) of the World Climate Research Programme`s Working Group on Numerical Experimentation (WGNE) is an ambitious attempt to comprehensively intercompare atmospheric General Circulation Models (GCMs). The participants in AMIP simulate the global atmosphere for the decade 1979 to 1988 using, a common solar constant and Carbon Dioxide(CO{sub 2}) concentration and a common monthly averaged sea surface temperature (SST) and sea ice data set. In this work we attempt to present a statistical framework to address the difficult task of model intercomparison and verification.
Statistical Characteristics of the Received Signal for Stochastic Surface Models
Institute of Scientific and Technical Information of China (English)
无
2002-01-01
This paper describes the stochastic model of the scattered electromagnetic field.Unlike common-used functional-determined models the proposed is characterised by amplitude/phase fluctuation of the received signal.This paper derives the statistical characteristic of the input signal and describes algorithm for its estimation in post-processing and real-time processing modes.Achieved characteristics allow the mapping and estimation of the surface models more accurate,moreover,such processing increase space resolution of synthetic aperture radar.
Spatio-temporal statistical models with applications to atmospheric processes
International Nuclear Information System (INIS)
This doctoral dissertation is presented as three self-contained papers. An introductory chapter considers traditional spatio-temporal statistical methods used in the atmospheric sciences from a statistical perspective. Although this section is primarily a review, many of the statistical issues considered have not been considered in the context of these methods and several open questions are posed. The first paper attempts to determine a means of characterizing the semiannual oscillation (SAO) spatial variation in the northern hemisphere extratropical height field. It was discovered that the midlatitude SAO in 500hPa geopotential height could be explained almost entirely as a result of spatial and temporal asymmetries in the annual variation of stationary eddies. It was concluded that the mechanism for the SAO in the northern hemisphere is a result of land-sea contrasts. The second paper examines the seasonal variability of mixed Rossby-gravity waves (MRGW) in lower stratospheric over the equatorial Pacific. Advanced cyclostationary time series techniques were used for analysis. It was found that there are significant twice-yearly peaks in MRGW activity. Analyses also suggested a convergence of horizontal momentum flux associated with these waves. In the third paper, a new spatio-temporal statistical model is proposed that attempts to consider the influence of both temporal and spatial variability. This method is mainly concerned with prediction in space and time, and provides a spatially descriptive and temporally dynamic model
Spatio-temporal statistical models with applications to atmospheric processes
Energy Technology Data Exchange (ETDEWEB)
Wikle, C.K.
1996-12-31
This doctoral dissertation is presented as three self-contained papers. An introductory chapter considers traditional spatio-temporal statistical methods used in the atmospheric sciences from a statistical perspective. Although this section is primarily a review, many of the statistical issues considered have not been considered in the context of these methods and several open questions are posed. The first paper attempts to determine a means of characterizing the semiannual oscillation (SAO) spatial variation in the northern hemisphere extratropical height field. It was discovered that the midlatitude SAO in 500hPa geopotential height could be explained almost entirely as a result of spatial and temporal asymmetries in the annual variation of stationary eddies. It was concluded that the mechanism for the SAO in the northern hemisphere is a result of land-sea contrasts. The second paper examines the seasonal variability of mixed Rossby-gravity waves (MRGW) in lower stratospheric over the equatorial Pacific. Advanced cyclostationary time series techniques were used for analysis. It was found that there are significant twice-yearly peaks in MRGW activity. Analyses also suggested a convergence of horizontal momentum flux associated with these waves. In the third paper, a new spatio-temporal statistical model is proposed that attempts to consider the influence of both temporal and spatial variability. This method is mainly concerned with prediction in space and time, and provides a spatially descriptive and temporally dynamic model.
RANDOM SYSTEMS OF HARD PARTICLES:MODELS AND STATISTICS
Institute of Scientific and Technical Information of China (English)
Dietrich Stoyan
2002-01-01
This paper surveys models and statistical properties of random systems of hard particles. Such systems appear frequently in materials science, biology and elsewhere. In mathematical - statistical investigations, simulations of such structures play an important role. In these simulations various methods and models are applied, namely the RSA model, sedimentation and collective rearrangement algorithms, molecular dynamics, and Monte Carlo methods such as the Metropolis - Hastings algorithm. The statistical description of real and simulated particle systems uses ideas of the mathematical theories of random sets and point processes. This leads to characteristics such as volume fraction or porosity, covariance,contact distribution functions, specific connectivity number from the random set approach and intensity, pair correlation function and mark correlation functions from the point process approach. Some of them can be determined stereologically using planar sections, while others can only be obtained using three - dimensional data and 3D image analysis. They are valuable tools for fitting models to empirical data and, consequently, for understanding various materials, biological structures, porous media and other practically important spatial structures.
Bayesian statistic methods and theri application in probabilistic simulation models
Directory of Open Access Journals (Sweden)
Sergio Iannazzo
2007-03-01
Full Text Available Bayesian statistic methods are facing a rapidly growing level of interest and acceptance in the field of health economics. The reasons of this success are probably to be found on the theoretical fundaments of the discipline that make these techniques more appealing to decision analysis. To this point should be added the modern IT progress that has developed different flexible and powerful statistical software framework. Among them probably one of the most noticeably is the BUGS language project and its standalone application for MS Windows WinBUGS. Scope of this paper is to introduce the subject and to show some interesting applications of WinBUGS in developing complex economical models based on Markov chains. The advantages of this approach reside on the elegance of the code produced and in its capability to easily develop probabilistic simulations. Moreover an example of the integration of bayesian inference models in a Markov model is shown. This last feature let the analyst conduce statistical analyses on the available sources of evidence and exploit them directly as inputs in the economic model.
A Statistical Model for Uplink Intercell Interference with Power Adaptation and Greedy Scheduling
Tabassum, Hina
2012-10-03
This paper deals with the statistical modeling of uplink inter-cell interference (ICI) considering greedy scheduling with power adaptation based on channel conditions. The derived model is implicitly generalized for any kind of shadowing and fading environments. More precisely, we develop a generic model for the distribution of ICI based on the locations of the allocated users and their transmit powers. The derived model is utilized to evaluate important network performance metrics such as ergodic capacity, average fairness and average power preservation numerically. Monte-Carlo simulation details are included to support the analysis and show the accuracy of the derived expressions. In parallel to the literature, we show that greedy scheduling with power adaptation reduces the ICI, average power consumption of users, and enhances the average fairness among users, compared to the case without power adaptation. © 2012 IEEE.
Statistical Model Checking of Rich Models and Properties
DEFF Research Database (Denmark)
Poulsen, Danny Bøgsted
Software is in increasing fashion embedded within safety- and business critical processes of society. Errors in these embedded systems can lead to human casualties or severe monetary loss. Model checking technology has proven formal methods capable of finding and correcting errors in software...... 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....... However, software is approaching the boundary in terms of the complexity and size that model checking can handle. Furthermore, software systems are nowadays more frequently interacting with their environment hence accurately modelling such systems requires modelling the environment as well - resulting...
Directory of Open Access Journals (Sweden)
Angela Heck
Full Text Available Despite the current progress in high-throughput, dense genome scans, a major portion of complex traits' heritability still remains unexplained, a phenomenon commonly termed "missing heritability." The negligence of analytical approaches accounting for gene-gene interaction effects, such as statistical epistasis, is probably central to this phenomenon. Here we performed a comprehensive two-way SNP interaction analysis of human episodic memory, which is a heritable complex trait, and focused on 120 genes known to show differential, memory-related expression patterns in rat hippocampus. Functional magnetic resonance imaging was also used to capture genotype-dependent differences in memory-related brain activity. A significant, episodic memory-related interaction between two markers located in potassium channel genes (KCNB2 and KCNH5 was observed (P(nominal combined=0.000001. The epistatic interaction was robust, as it was significant in a screening (P(nominal=0.0000012 and in a replication sample (P(nominal=0.01. Finally, we found genotype-dependent activity differences in the parahippocampal gyrus (P(nominal=0.001 supporting the behavioral genetics finding. Our results demonstrate the importance of analytical approaches that go beyond single marker statistics of complex traits.
Nam, Sungsik
2011-08-01
Spread spectrum receivers with generalized selection combining (GSC) RAKE reception were proposed and have been studied as alternatives to the classical two fundamental schemes: maximal ratio combining and selection combining because the number of diversity paths increases with the transmission bandwidth. Previous work on performance analyses of GSC RAKE receivers based on the signal to noise ratio focused on the development of methodologies to derive exact closed-form expressions for various performance measures. However, some open problems related to the performance evaluation of GSC RAKE receivers still remain to be solved such as the exact performance analysis of the capture probability and an exact assessment of the impact of self-interference on GSC RAKE receivers. The major difficulty in these problems is to derive some joint statistics of ordered exponential variates. With this motivation in mind, we capitalize in this paper on some new order statistics results to derive exact closed-form expressions for the capture probability and outage probability of GSC RAKE receivers subject to self-interference over independent and identically distributed Rayleigh fading channels, and compare it to that of partial RAKE receivers. © 2011 IEEE.
Statistical mechanics models for multimode lasers and random lasers
Antenucci, F; Berganza, M Ibáñez; Marruzzo, A; Leuzzi, L
2015-01-01
We review recent statistical mechanical approaches to multimode laser theory. The theory has proved very effective to describe standard lasers. We refer of the mean field theory for passive mode locking and developments based on Monte Carlo simulations and cavity method to study the role of the frequency matching condition. The status for a complete theory of multimode lasing in open and disordered cavities is discussed and the derivation of the general statistical models in this framework is presented. When light is propagating in a disordered medium, the system can be analyzed via the replica method. For high degrees of disorder and nonlinearity, a glassy behavior is expected at the lasing threshold, providing a suggestive link between glasses and photonics. We describe in details the results for the general Hamiltonian model in mean field approximation and mention an available test for replica symmetry breaking from intensity spectra measurements. Finally, we summary some perspectives still opened for such...
Passive Target Tracking Based on Current Statistical Model
Institute of Scientific and Technical Information of China (English)
DENG Xiao-long; XIE Jian-ying; YANG Yu-pu
2005-01-01
Bearing-only passive tracking is regarded as a nonlinear hard tracking problem. There are still no completely good solutions to this problem until now. Based on current statistical model, the novel solution to this problem utilizing particle filter (PF) and the unscented Kalman filter (UKF) is proposed. The new solution adopts data fusion from two observers to increase the observability of passive tracking. It applies the residual resampling step to reduce the degeneracy of PF and it introduces the Markov Chain Monte Carlo methods (MCMC) to reduce the effect of the "sample impoverish". Based on current statistical model, the EKF, the UKF and particle filter with various proposal distributions are compared in the passive tracking experiments with two observers. The simulation results demonstrate the good performance of the proposed new filtering methods with the novel techniques.
Statistical detection of structural damage based on model reduction
Institute of Scientific and Technical Information of China (English)
Tao YIN; Heung-fai LAM; Hong-ping ZHU
2009-01-01
This paper proposes a statistical method for damage detection based on the finite element (FE) model reduction technique that utilizes measured modal data with a limited number of sensors.A deterministic damage detection process is formulated based on the model reduction technique.The probabilistic process is integrated into the deterministic damage detection process using a perturbation technique,resulting in a statistical structural damage detection method.This is achieved by deriving the firstand second-order partial derivatives of uncertain parameters,such as elasticity of the damaged member,with respect to the measurement noise,which allows expectation and covariance matrix of the uncertain parameters to be calculated.Besides the theoretical development,this paper reports numerical verification of the proposed method using a portal frame example and Monte Carlo simulation.
Sequence-Based Pronunciation Variation Modeling for Spontaneous ASR Using a Noisy Channel Approach
Hofmann, Hansjörg; Sakti, Sakriani; Hori, Chiori; Kashioka, Hideki; Nakamura, Satoshi; Minker, Wolfgang
The performance of English automatic speech recognition systems decreases when recognizing spontaneous speech mainly due to multiple pronunciation variants in the utterances. Previous approaches address this problem by modeling the alteration of the pronunciation on a phoneme to phoneme level. However, the phonetic transformation effects induced by the pronunciation of the whole sentence have not yet been considered. In this article, the sequence-based pronunciation variation is modeled using a noisy channel approach where the spontaneous phoneme sequence is considered as a “noisy” string and the goal is to recover the “clean” string of the word sequence. Hereby, the whole word sequence and its effect on the alternation of the phonemes will be taken into consideration. Moreover, the system not only learns the phoneme transformation but also the mapping from the phoneme to the word directly. In this study, first the phonemes will be recognized with the present recognition system and afterwards the pronunciation variation model based on the noisy channel approach will map from the phoneme to the word level. Two well-known natural language processing approaches are adopted and derived from the noisy channel model theory: Joint-sequence models and statistical machine translation. Both of them are applied and various experiments are conducted using microphone and telephone of spontaneous speech.
Thermally stratified sodium channel flow: turbulence and modeling
International Nuclear Information System (INIS)
Numerical simulation of sodium stratification in open channel flow has been studied with Computational Fluid Dynamics (CFD) employing an Algebraic Heat Flux Model (AHFM) closure for the turbulent heat flux. The results are validated against experimental data and the AHFM is compared with the simplified Reynolds analogy employing a constant turbulent Pr number. Influence of buoyancy on turbulence created in the mixing layer has been evaluated and its influence on the momentum and energy transport in the vertical direction assessed. It has been found that the choice of turbulent heat flux model influences the achieved results for temperature and velocity field which might affect the flow developing and persistence of stratification in the channel. Moreover both experiment and validation show the possibility of creation of a strong stratification also for low Pr number fluids, warning the stratification problem as an existing phenomenon likely to occur in liquid metal nuclear power plants. (author)
Cascaded Network Body Channel Model for Intrabody Communication.
Wang, Hao; Tang, Xian; Choy, Chiu Sing; Sobelman, Gerald E
2016-07-01
Intrabody communication has been of great research interest in recent years. This paper proposes a novel, compact but accurate body transmission channel model based on RC distribution networks and transmission line theory. The comparison between simulation and measurement results indicates that the proposed approach accurately models the body channel characteristics. In addition, the impedance-matching networks at the transmitter output and the receiver input further maximize the power transferred to the receiver, relax the receiver complexity, and increase the transmission performance. Based on the simulation results, the power gain can be increased by up to 16 dB after matching. A binary phase-shift keying modulation scheme is also used to evaluate the bit-error-rate improvement. PMID:26111404
Cascaded Network Body Channel Model for Intrabody Communication.
Wang, Hao; Tang, Xian; Choy, Chiu Sing; Sobelman, Gerald E
2016-07-01
Intrabody communication has been of great research interest in recent years. This paper proposes a novel, compact but accurate body transmission channel model based on RC distribution networks and transmission line theory. The comparison between simulation and measurement results indicates that the proposed approach accurately models the body channel characteristics. In addition, the impedance-matching networks at the transmitter output and the receiver input further maximize the power transferred to the receiver, relax the receiver complexity, and increase the transmission performance. Based on the simulation results, the power gain can be increased by up to 16 dB after matching. A binary phase-shift keying modulation scheme is also used to evaluate the bit-error-rate improvement.
Exploring Explanations of Subglacial Bedform Sizes Using Statistical Models.
Directory of Open Access Journals (Sweden)
John K Hillier
Full Text Available Sediments beneath modern ice sheets exert a key control on their flow, but are largely inaccessible except through geophysics or boreholes. In contrast, palaeo-ice sheet beds are accessible, and typically characterised by numerous bedforms. However, the interaction between bedforms and ice flow is poorly constrained and it is not clear how bedform sizes might reflect ice flow conditions. To better understand this link we present a first exploration of a variety of statistical models to explain the size distribution of some common subglacial bedforms (i.e., drumlins, ribbed moraine, MSGL. By considering a range of models, constructed to reflect key aspects of the physical processes, it is possible to infer that the size distributions are most effectively explained when the dynamics of ice-water-sediment interaction associated with bedform growth is fundamentally random. A 'stochastic instability' (SI model, which integrates random bedform growth and shrinking through time with exponential growth, is preferred and is consistent with other observations of palaeo-bedforms and geophysical surveys of active ice sheets. Furthermore, we give a proof-of-concept demonstration that our statistical approach can bridge the gap between geomorphological observations and physical models, directly linking measurable size-frequency parameters to properties of ice sheet flow (e.g., ice velocity. Moreover, statistically developing existing models as proposed allows quantitative predictions to be made about sizes, making the models testable; a first illustration of this is given for a hypothesised repeat geophysical survey of bedforms under active ice. Thus, we further demonstrate the potential of size-frequency distributions of subglacial bedforms to assist the elucidation of subglacial processes and better constrain ice sheet models.
Exploring Explanations of Subglacial Bedform Sizes Using Statistical Models.
Hillier, John K; Kougioumtzoglou, Ioannis A; Stokes, Chris R; Smith, Michael J; Clark, Chris D; Spagnolo, Matteo S
2016-01-01
Sediments beneath modern ice sheets exert a key control on their flow, but are largely inaccessible except through geophysics or boreholes. In contrast, palaeo-ice sheet beds are accessible, and typically characterised by numerous bedforms. However, the interaction between bedforms and ice flow is poorly constrained and it is not clear how bedform sizes might reflect ice flow conditions. To better understand this link we present a first exploration of a variety of statistical models to explain the size distribution of some common subglacial bedforms (i.e., drumlins, ribbed moraine, MSGL). By considering a range of models, constructed to reflect key aspects of the physical processes, it is possible to infer that the size distributions are most effectively explained when the dynamics of ice-water-sediment interaction associated with bedform growth is fundamentally random. A 'stochastic instability' (SI) model, which integrates random bedform growth and shrinking through time with exponential growth, is preferred and is consistent with other observations of palaeo-bedforms and geophysical surveys of active ice sheets. Furthermore, we give a proof-of-concept demonstration that our statistical approach can bridge the gap between geomorphological observations and physical models, directly linking measurable size-frequency parameters to properties of ice sheet flow (e.g., ice velocity). Moreover, statistically developing existing models as proposed allows quantitative predictions to be made about sizes, making the models testable; a first illustration of this is given for a hypothesised repeat geophysical survey of bedforms under active ice. Thus, we further demonstrate the potential of size-frequency distributions of subglacial bedforms to assist the elucidation of subglacial processes and better constrain ice sheet models. PMID:27458921
Exploring Explanations of Subglacial Bedform Sizes Using Statistical Models
Kougioumtzoglou, Ioannis A.; Stokes, Chris R.; Smith, Michael J.; Clark, Chris D.; Spagnolo, Matteo S.
2016-01-01
Sediments beneath modern ice sheets exert a key control on their flow, but are largely inaccessible except through geophysics or boreholes. In contrast, palaeo-ice sheet beds are accessible, and typically characterised by numerous bedforms. However, the interaction between bedforms and ice flow is poorly constrained and it is not clear how bedform sizes might reflect ice flow conditions. To better understand this link we present a first exploration of a variety of statistical models to explain the size distribution of some common subglacial bedforms (i.e., drumlins, ribbed moraine, MSGL). By considering a range of models, constructed to reflect key aspects of the physical processes, it is possible to infer that the size distributions are most effectively explained when the dynamics of ice-water-sediment interaction associated with bedform growth is fundamentally random. A ‘stochastic instability’ (SI) model, which integrates random bedform growth and shrinking through time with exponential growth, is preferred and is consistent with other observations of palaeo-bedforms and geophysical surveys of active ice sheets. Furthermore, we give a proof-of-concept demonstration that our statistical approach can bridge the gap between geomorphological observations and physical models, directly linking measurable size-frequency parameters to properties of ice sheet flow (e.g., ice velocity). Moreover, statistically developing existing models as proposed allows quantitative predictions to be made about sizes, making the models testable; a first illustration of this is given for a hypothesised repeat geophysical survey of bedforms under active ice. Thus, we further demonstrate the potential of size-frequency distributions of subglacial bedforms to assist the elucidation of subglacial processes and better constrain ice sheet models. PMID:27458921
Garrido-Balsells, José María; Jurado-Navas, Antonio; Paris, José Francisco; Castillo-Vazquez, Miguel; Puerta-Notario, Antonio
2015-03-01
In this paper, a novel and deeper physical interpretation on the recently published Málaga or ℳ statistical distribution is provided. This distribution, which is having a wide acceptance by the scientific community, models the optical irradiance scintillation induced by the atmospheric turbulence. Here, the analytical expressions previously published are modified in order to express them by a mixture of the known Generalized-K and discrete Binomial and Negative Binomial distributions. In particular, the probability density function (pdf) of the ℳ model is now obtained as a linear combination of these Generalized-K pdf, in which the coefficients depend directly on the parameters of the ℳ distribution. In this way, the Málaga model can be physically interpreted as a superposition of different optical sub-channels each of them described by the corresponding Generalized-K fading model and weighted by the ℳ dependent coefficients. The expressions here proposed are simpler than the equations of the original ℳ model and are validated by means of numerical simulations by generating ℳ -distributed random sequences and their associated histogram. This novel interpretation of the Málaga statistical distribution provides a valuable tool for analyzing the performance of atmospheric optical channels for every turbulence condition. PMID:25836855
A Statistical Model for Soliton Particle Interaction in Plasmas
DEFF Research Database (Denmark)
Dysthe, K. B.; Pécseli, Hans; Truelsen, J.
1986-01-01
A statistical model for soliton-particle interaction is presented. A master equation is derived for the time evolution of the particle velocity distribution as induced by resonant interaction with Korteweg-de Vries solitons. The detailed energy balance during the interaction subsequently determines...... the evolution of the soliton amplitude distribution. The analysis applies equally well for weakly nonlinear plasma waves in a strongly magnetized waveguide, or for ion acoustic waves propagating in one-dimensional systems....
Optimal Fuzzy Model Construction with Statistical Information using Genetic Algorithm
Bishnu Sarker; Kazuyuki Murase; Amjad Hossain; Pintu Chandra Shill
2012-01-01
Fuzzy rule based models have a capability to approximate any continuous function to any degree of accuracy on a compact domain. The majority of FLC design process relies on heuristic knowledge of experience operators. In order to make the design process automatic we present a genetic approach to learn fuzzy rules as well as membership function parameters. Moreover, several statistical information criteria such as the Akaike information criterion (AIC), the Bhansali-Downham information criteri...
A statistical mechanics model of carbon nanotube macro-films
Institute of Scientific and Technical Information of China (English)
无
2011-01-01
Carbon nanotube macro-films are two-dimensional films with micrometer thickness and centimeter by centimeter in-plane dimension.These carbon nanotube macroscopic assemblies have attracted significant attention from the material and mechanics communities recently because they can be easily handled and tailored to meet specific engineering needs.This paper reports the experimental methods on the preparation and characterization of single-walled carbon nanotube macro-films,and a statistical mechanics model on ...
Statistical Modeling of Large-Scale Signal Path Loss in Underwater Acoustic Networks
Directory of Open Access Journals (Sweden)
Manuel Perez Malumbres
2013-02-01
Full Text Available In an underwater acoustic channel, the propagation conditions are known to vary in time, causing the deviation of the received signal strength from the nominal value predicted by a deterministic propagation model. To facilitate a large-scale system design in such conditions (e.g., power allocation, we have developed a statistical propagation model in which the transmission loss is treated as a random variable. By applying repetitive computation to the acoustic field, using ray tracing for a set of varying environmental conditions (surface height, wave activity, small node displacements around nominal locations, etc., an ensemble of transmission losses is compiled and later used to infer the statistical model parameters. A reasonable agreement is found with log-normal distribution, whose mean obeys a log-distance increases, and whose variance appears to be constant for a certain range of inter-node distances in a given deployment location. The statistical model is deemed useful for higher-level system planning, where simulation is needed to assess the performance of candidate network protocols under various resource allocation policies, i.e., to determine the transmit power and bandwidth allocation necessary to achieve a desired level of performance (connectivity, throughput, reliability, etc..
Basic equations of channel model for underground coal gasification
Institute of Scientific and Technical Information of China (English)
无
2002-01-01
The underground coal gasification has advantages of zero rubbish, nonpollution, low cost and high safety. According to the characteristics of the gasification, the channel model of chemical fluid mechanics is used to set up the fluid equations and chemical equations by some reasonable suppositions in this paper, which lays a theoretical foundation on requirements of fluid movement rules in the process of underground coal gasification.
A statistical method for descriminating between alternative radiobiological models
International Nuclear Information System (INIS)
Radiobiological models assist understanding of the development of radiation damage, and may provide a basis for extrapolating dose-effect curves from high to low dose regions. Many models have been proposed such as multitarget and its modifications, enzymatic models, and those with a quadratic dose response relationship (i.e. αD + βD2 forms). It is difficult to distinguish between these because the statistical techniques used are almost always limited, in that one method can rarely be applied to the whole range of models. A general statistical procedure for parameter estimation (Maximum Liklihood Method) has been found applicable to a wide range of radiobiological models. The curve parameters are estimated using a computerised search that continues until the most likely set of values to fit the data is obtained. When the search is complete two procedures are carried out. First a goodness of fit test is applied which examines the applicability of an individual model to the data. Secondly an index is derived which provides an indication of the adequacy of any model compared with alternative models. Thus the models may be ranked according to how well they fit the data. For example, with one set of data, multitarget types were found to be more suitable than quadratic types (αD + βD2). This method should be of assitance is evaluating various models. It may also be profitably applied to selection of the most appropriate model to use, when it is necessary to extrapolate from high to low doses
Physical-Statistical Model of Thermal Conductivity of Nanofluids
Directory of Open Access Journals (Sweden)
B. Usowicz
2014-01-01
Full Text Available A physical-statistical model for predicting the effective thermal conductivity of nanofluids is proposed. The volumetric unit of nanofluids in the model consists of solid, liquid, and gas particles and is treated as a system made up of regular geometric figures, spheres, filling the volumetric unit by layers. The model assumes that connections between layers of the spheres and between neighbouring spheres in the layer are represented by serial and parallel connections of thermal resistors, respectively. This model is expressed in terms of thermal resistance of nanoparticles and fluids and the multinomial distribution of particles in the nanofluids. The results for predicted and measured effective thermal conductivity of several nanofluids (Al2O3/ethylene glycol-based and Al2O3/water-based; CuO/ethylene glycol-based and CuO/water-based; and TiO2/ethylene glycol-based are presented. The physical-statistical model shows a reasonably good agreement with the experimental results and gives more accurate predictions for the effective thermal conductivity of nanofluids compared to existing classical models.
Mathematical and Statistical Modeling in Cancer Systems Biology
Directory of Open Access Journals (Sweden)
Rachael eHageman Blair
2012-06-01
Full Text Available Cancer is a major health problem with high mortality rates. In the post-genome era, investigators have access to massive amounts of rapidly accumulating high-throughput data in publicly available databases, some of which are exclusively devoted to housing Cancer data. However, data interpretation efforts have not kept pace with data collection, and gained knowledge is not necessarily translating into better diagnoses and treatments. A fundamental problem is to integrate and interpret data to further our understanding in Cancer Systems Biology. Viewing cancer as a network provides insights into the complex mechanisms underlying the disease. Mathematical and statistical models provide an avenue for cancer network modeling. In this article, we review two widely used modeling paradigms: deterministic metabolic models and statistical graphical models. The strength of these approaches lies in their flexibility and predictive power. Once a model has been validated, it can be used to make predictions and generate hypotheses. We describe a number of diverse applications to Cancer Biology, including, the system-wide effects of drug-treatments, disease prognosis, tumor classification, forecasting treatment outcomes, and survival predictions.
The Ising model in physics and statistical genetics.
Majewski, J; Li, H; Ott, J
2001-10-01
Interdisciplinary communication is becoming a crucial component of the present scientific environment. Theoretical models developed in diverse disciplines often may be successfully employed in solving seemingly unrelated problems that can be reduced to similar mathematical formulation. The Ising model has been proposed in statistical physics as a simplified model for analysis of magnetic interactions and structures of ferromagnetic substances. Here, we present an application of the one-dimensional, linear Ising model to affected-sib-pair (ASP) analysis in genetics. By analyzing simulated genetics data, we show that the simplified Ising model with only nearest-neighbor interactions between genetic markers has statistical properties comparable to much more complex algorithms from genetics analysis, such as those implemented in the Allegro and Mapmaker-Sibs programs. We also adapt the model to include epistatic interactions and to demonstrate its usefulness in detecting modifier loci with weak individual genetic contributions. A reanalysis of data on type 1 diabetes detects several susceptibility loci not previously found by other methods of analysis.
Modeling magnetosensitive ion channels in viscoelastic environment of living cells
Goychuk, Igor
2015-01-01
We propose and study a model of hypothetical magnetosensitive ionic channels which are long thought to be a possible candidate to explain the influence of weak magnetic fields on living organisms ranging from magnetotactic bacteria to fishes, birds, rats, bats and other mammals including humans. The core of the model is provided by a short chain of magnetosomes serving as a sensor which is coupled by elastic linkers to the gating elements of ion channels forming a small cluster in the cell membrane. The magnetic sensor is fixed by one end on cytoskeleton elements attached to the membrane and is exposed to viscoelastic cytosol. Its free end can reorient stochastically and subdiffusively in viscoelastic cytosol responding to external magnetic field changes and open the gates of coupled ion channels. The sensor dynamics is generally bistable due to bistability of the gates which can be in two states with probabilities which depend on the sensor orientation. For realistic parameters, it is shown that this model c...
Statistical mechanics of the Huxley-Simmons model
Caruel, M.; Truskinovsky, L.
2016-06-01
The chemomechanical model of Huxley and Simmons (HS) [A. F. Huxley and R. M. Simmons, Nature 233, 533 (1971), 10.1038/233533a0] provides a paradigmatic description of mechanically induced collective conformational changes relevant in a variety of biological contexts, from muscles power stroke and hair cell gating to integrin binding and hairpin unzipping. We develop a statistical mechanical perspective on the HS model by exploiting a formal analogy with a paramagnetic Ising model. We first study the equilibrium HS model with a finite number of elements and compute explicitly its mechanical and thermal properties. To model kinetics, we derive a master equation and solve it for several loading protocols. The developed formalism is applicable to a broad range of allosteric systems with mean-field interactions.
Statistical mechanics of the Huxley-Simmons model
Caruel, M
2016-01-01
The chemomechanical model of Huxley and Simmons (HS) [A. F. Huxley and R. M. Simmons, Nature 233, 533 (1971)] provides a paradigmatic description of mechanically induced collective conformational changes relevant in a variety of biological contexts, from muscles power-stroke and hair cell gating to integrin binding and hairpin unzipping. We develop a statistical mechanical perspective on the HS model by exploiting a formal analogy with a paramagnetic Ising model. We first study the equilibrium HS model with a finite number of elements and compute explicitly its mechanical and thermal properties. To model kinetics, we derive a master equation and solve it for several loading protocols. The developed formalism is applicable to a broad range of allosteric systems with mean-field interactions.
Spatial Statistical Procedures to Validate Input Data in Energy Models
Energy Technology Data Exchange (ETDEWEB)
Johannesson, G.; Stewart, J.; Barr, C.; Brady Sabeff, L.; George, R.; Heimiller, D.; Milbrandt, A.
2006-01-01
Energy modeling and analysis often relies on data collected for other purposes such as census counts, atmospheric and air quality observations, economic trends, and other primarily non-energy related uses. Systematic collection of empirical data solely for regional, national, and global energy modeling has not been established as in the abovementioned fields. Empirical and modeled data relevant to energy modeling is reported and available at various spatial and temporal scales that might or might not be those needed and used by the energy modeling community. The incorrect representation of spatial and temporal components of these data sets can result in energy models producing misleading conclusions, especially in cases of newly evolving technologies with spatial and temporal operating characteristics different from the dominant fossil and nuclear technologies that powered the energy economy over the last two hundred years. Increased private and government research and development and public interest in alternative technologies that have a benign effect on the climate and the environment have spurred interest in wind, solar, hydrogen, and other alternative energy sources and energy carriers. Many of these technologies require much finer spatial and temporal detail to determine optimal engineering designs, resource availability, and market potential. This paper presents exploratory and modeling techniques in spatial statistics that can improve the usefulness of empirical and modeled data sets that do not initially meet the spatial and/or temporal requirements of energy models. In particular, we focus on (1) aggregation and disaggregation of spatial data, (2) predicting missing data, and (3) merging spatial data sets. In addition, we introduce relevant statistical software models commonly used in the field for various sizes and types of data sets.
Spatial Statistical Procedures to Validate Input Data in Energy Models
Energy Technology Data Exchange (ETDEWEB)
Lawrence Livermore National Laboratory
2006-01-27
Energy modeling and analysis often relies on data collected for other purposes such as census counts, atmospheric and air quality observations, economic trends, and other primarily non-energy-related uses. Systematic collection of empirical data solely for regional, national, and global energy modeling has not been established as in the above-mentioned fields. Empirical and modeled data relevant to energy modeling is reported and available at various spatial and temporal scales that might or might not be those needed and used by the energy modeling community. The incorrect representation of spatial and temporal components of these data sets can result in energy models producing misleading conclusions, especially in cases of newly evolving technologies with spatial and temporal operating characteristics different from the dominant fossil and nuclear technologies that powered the energy economy over the last two hundred years. Increased private and government research and development and public interest in alternative technologies that have a benign effect on the climate and the environment have spurred interest in wind, solar, hydrogen, and other alternative energy sources and energy carriers. Many of these technologies require much finer spatial and temporal detail to determine optimal engineering designs, resource availability, and market potential. This paper presents exploratory and modeling techniques in spatial statistics that can improve the usefulness of empirical and modeled data sets that do not initially meet the spatial and/or temporal requirements of energy models. In particular, we focus on (1) aggregation and disaggregation of spatial data, (2) predicting missing data, and (3) merging spatial data sets. In addition, we introduce relevant statistical software models commonly used in the field for various sizes and types of data sets.
Von Neumann's growth model: Statistical mechanics and biological applications
De Martino, A.; Marinari, E.; Romualdi, A.
2012-09-01
We review recent work on the statistical mechanics of Von Neumann's growth model and discuss its application to cellular metabolic networks. In this context, we present a detailed analysis of the physiological scenario underlying optimality à la Von Neumann in the metabolism of the bacterium E. coli, showing that optimal solutions are characterized by a considerable microscopic flexibility accompanied by a robust emergent picture for the key physiological functions. This suggests that the ideas behind optimal economic growth in Von Neumann's model can be helpful in uncovering functional organization principles of cell energetics.
A statistical model for red blood cell survival.
Korell, Julia; Coulter, Carolyn V; Duffull, Stephen B
2011-01-01
A statistical model for the survival time of red blood cells (RBCs) with a continuous distribution of cell lifespans is presented. The underlying distribution of RBC lifespans is derived from a probability density function with a bathtub-shaped hazard curve, and accounts for death of RBCs due to senescence (age-dependent increasing hazard rate) and random destruction (constant hazard), as well as for death due to initial or delayed failures and neocytolysis (equivalent to early red cell mortality). The model yields survival times similar to those of previously published studies of RBC survival and is easily amenable to inclusion of drug effects and haemolytic disorders. PMID:20950630
UPPAAL-SMC: Statistical Model Checking for Priced Timed Automata
DEFF Research Database (Denmark)
Bulychev, Petr; David, Alexandre; Larsen, Kim Guldstrand;
2012-01-01
in the form of probability distributions and compare probabilities to analyze performance aspects of systems. The focus of the survey is on the evolution of the tool – including modeling and specification formalisms as well as techniques applied – together with applications of the tool to case studies....... on a series of extensions of the statistical model checking approach generalized to handle real-time systems and estimate undecidable problems. U PPAAL - SMC comes together with a friendly user interface that allows a user to specify complex problems in an efficient manner as well as to get feedback...
Calculation of statistical entropic measures in a model of solids
Sanudo, Jaime
2012-01-01
In this work, a one-dimensional model of crystalline solids based on the Dirac comb limit of the Kronig-Penney model is considered. From the wave functions of the valence electrons, we calculate a statistical measure of complexity and the Fisher-Shannon information for the lower energy electronic bands appearing in the system. All these magnitudes present an extremal value for the case of solids having half-filled bands, a configuration where in general a high conductivity is attained in real solids, such as it happens with the monovalent metals.
Non-gaussianity and Statistical Anisotropy in Cosmological Inflationary Models
Valenzuela-Toledo, Cesar A
2010-01-01
We study the statistical descriptors for some cosmological inflationary models that allow us to get large levels of non-gaussianity and violations of statistical isotropy. Basically, we study two different class of models: a model that include only scalar field perturbations, specifically a subclass of small-field slow-roll models of inflation with canonical kinetic terms, and models that admit both vector and scalar field perturbations. We study the former to show that it is possible to attain very high, including observable, values for the levels of non-gaussianity f_{NL} and \\tao_{NL} in the bispectrum B_\\zeta and trispectrum T_\\zeta of the primordial curvature perturbation \\zeta respectively. Such a result is obtained by taking care of loop corrections in the spectrum P_\\zeta, the bispectrum B_\\zeta and the trispectrum T_\\zeta . Sizeable values for f_{NL} and \\tao_{NL} arise even if \\zeta is generated during inflation. For the latter we study the spectrum P_\\zeta, bispectrum B_\\zeta and trispectrum $T_\\ze...
Anyonic behavior of an intermediate-statistics fermion gas model.
Algin, Abdullah; Irk, Dursun; Topcu, Gozde
2015-06-01
We study the high-temperature behavior of an intermediate-statistics fermionic gas model whose quantum statistical properties enable us to effectively deduce the details about both the interaction among deformed (quasi)particles and their anyonic behavior. Starting with a deformed fermionic grand partition function, we calculate, in the thermodynamical limit, several thermostatistical functions of the model such as the internal energy and the entropy by means of a formalism of the fermionic q calculus. For high temperatures, a virial expansion of the equation of state for the system is obtained in two and three dimensions and the first five virial coefficients are derived in terms of the model deformation parameter q. From the results obtained by the effect of fermionic deformation, it is found that the model parameter q interpolates completely between bosonlike and fermionic systems via the behaviors of the third and fifth virial coefficients in both two and three spatial dimensions and in addition it characterizes effectively the interaction among quasifermions. Our results reveal that the present deformed (quasi)fermion model could be very efficient and effective in accounting for the nonlinear behaviors in interacting composite particle systems.
A statistical permafrost distribution model for the European Alps
Directory of Open Access Journals (Sweden)
L. Boeckli
2011-05-01
Full Text Available Permafrost distribution modeling in densely populated mountain regions is an important task to support the construction of infrastructure and for the assessment of climate change effects on permafrost and related natural systems. In order to analyze permafrost distribution and evolution on an Alpine-wide scale, one consistent model for the entire domain is needed.
We present a statistical permafrost model for the entire Alps based on rock glacier inventories and rock surface temperatures. Starting from an integrated model framework, two different sub-models were developed, one for debris covered areas (debris model and one for steep rock faces (rock model. For the debris model a generalized linear mixed-effect model (GLMM was used to predict the probability of a rock glacier being intact as opposed to relict. The model is based on the explanatory variables mean annual air temperature (MAAT, potential incoming solar radiation (PISR and the mean annual sum of precipitation (PRECIP, and achieves an excellent discrimination (area under the receiver-operating characteristic, AUROC = 0.91. Surprisingly, the probability of a rock glacier being intact is positively associated with increasing PRECIP for given MAAT and PISR conditions. The rock model was calibrated with mean annual rock surface temperatures (MARST and is based on MAAT and PISR. The linear regression achieves a root mean square error (RMSE of 1.6 °C. The final model combines the two sub-models and accounts for the different scales used for model calibration. Further steps to transfer this model into a map-based product are outlined.
Statistical models of video structure for content analysis and characterization.
Vasconcelos, N; Lippman, A
2000-01-01
Content structure plays an important role in the understanding of video. In this paper, we argue that knowledge about structure can be used both as a means to improve the performance of content analysis and to extract features that convey semantic information about the content. We introduce statistical models for two important components of this structure, shot duration and activity, and demonstrate the usefulness of these models with two practical applications. First, we develop a Bayesian formulation for the shot segmentation problem that is shown to extend the standard thresholding model in an adaptive and intuitive way, leading to improved segmentation accuracy. Second, by applying the transformation into the shot duration/activity feature space to a database of movie clips, we also illustrate how the Bayesian model captures semantic properties of the content. We suggest ways in which these properties can be used as a basis for intuitive content-based access to movie libraries.
Liver recognition based on statistical shape model in CT images
Xiang, Dehui; Jiang, Xueqing; Shi, Fei; Zhu, Weifang; Chen, Xinjian
2016-03-01
In this paper, an automatic method is proposed to recognize the liver on clinical 3D CT images. The proposed method effectively use statistical shape model of the liver. Our approach consist of three main parts: (1) model training, in which shape variability is detected using principal component analysis from the manual annotation; (2) model localization, in which a fast Euclidean distance transformation based method is able to localize the liver in CT images; (3) liver recognition, the initial mesh is locally and iteratively adapted to the liver boundary, which is constrained with the trained shape model. We validate our algorithm on a dataset which consists of 20 3D CT images obtained from different patients. The average ARVD was 8.99%, the average ASSD was 2.69mm, the average RMSD was 4.92mm, the average MSD was 28.841mm, and the average MSD was 13.31%.
Statistical Inference for Partially Linear Regression Models with Measurement Errors
Institute of Scientific and Technical Information of China (English)
Jinhong YOU; Qinfeng XU; Bin ZHOU
2008-01-01
In this paper, the authors investigate three aspects of statistical inference for the partially linear regression models where some covariates are measured with errors. Firstly,a bandwidth selection procedure is proposed, which is a combination of the difference-based technique and GCV method. Secondly, a goodness-of-fit test procedure is proposed,which is an extension of the generalized likelihood technique. Thirdly, a variable selection procedure for the parametric part is provided based on the nonconcave penalization and corrected profile least squares. Same as "Variable selection via nonconcave penalized like-lihood and its oracle properties" (J. Amer. Statist. Assoc., 96, 2001, 1348-1360), it is shown that the resulting estimator has an oracle property with a proper choice of regu-larization parameters and penalty function. Simulation studies are conducted to illustrate the finite sample performances of the proposed procedures.
Sketch of a Noisy Channel Model for the Translation Process
DEFF Research Database (Denmark)
Carl, Michael
The paper develops a Noisy Channel Model for the translation process that is based on actual user activity data. It builds on the monitor model and makes a distinction between early, automatic and late, conscious translation processes: while early priming processes are at the basis of a "literal...... default rendering" procedure, later conscious processes are triggered by a monitor who interferes when something goes wrong. An attempt is made to explain monitor activities with relevance theoretic concepts according to which a translator needs to ensure the similarity of explicatures and implicatures of...
A Unified Channel Charges Expression for Analytic MOSFET Modeling
Directory of Open Access Journals (Sweden)
Hugues Murray
2012-01-01
Full Text Available Based on a 1D Poissons equation resolution, we present an analytic model of inversion charges allowing calculation of the drain current and transconductance in the Metal Oxide Semiconductor Field Effect Transistor. The drain current and transconductance are described by analytical functions including mobility corrections and short channel effects (CLM, DIBL. The comparison with the Pao-Sah integral shows excellent accuracy of the model in all inversion modes from strong to weak inversion in submicronics MOSFET. All calculations are encoded with a simple C program and give instantaneous results that provide an efficient tool for microelectronics users.
Self-organized models of selectivity in calcium channels
International Nuclear Information System (INIS)
The role of flexibility in the selectivity of calcium channels is studied using a simple model with two parameters that accounts for the selectivity of calcium (and sodium) channels in many ionic solutions of different compositions and concentrations using two parameters with unchanging values. We compare the distribution of side chains (oxygens) and cations (Na+ and Ca2+) and integrated quantities. We compare the occupancies of cations Ca2+/Na+ and linearized conductance of Na+. The distributions show a strong dependence on the locations of fixed side chains and the flexibility of the side chains. Holding the side chains fixed at certain predetermined locations in the selectivity filter distorts the distribution of Ca2+ and Na+ in the selectivity filter. However, integrated quantities—occupancy and normalized conductance—are much less sensitive. Our results show that some flexibility of side chains is necessary to avoid obstruction of the ionic pathway by oxygen ions in 'unfortunate' fixed positions. When oxygen ions are mobile, they adjust 'automatically' and move 'out of the way', so they can accommodate the permeable cations in the selectivity filter. Structure is the computed consequence of the forces in this model. The structures are self-organized, at their free energy minimum. The relationship of ions and side chains varies with an ionic solution. Monte Carlo simulations are particularly well suited to compute induced-fit, self-organized structures because the simulations yield an ensemble of structures near their free energy minimum. The exact location and mobility of oxygen ions has little effect on the selectivity behavior of calcium channels. Seemingly, nature has chosen a robust mechanism to control selectivity in calcium channels: the first-order determinant of selectivity is the density of charge in the selectivity filter. The density is determined by filter volume along with the charge and excluded volume of
Coupled-channel optical model potential for rare earth nuclei
Herman, M; Palumbo, A; Dietrich, F S; Brown, D; Hoblit, S
2013-01-01
Inspired by the recent work by Dietrich et al., substantiating validity of the adiabatic assumption in coupled-channel calculations, we explore the possibility of generalizing a global spherical optical model potential (OMP) to make it usable in coupled-channel calculations on statically deformed nuclei. The generalization consists in adding the coupling of the ground state rotational band, deforming the potential by introducing appropriate quadrupole and hexadecupole deformation and correcting the OMP radius to preserve volume integral of the spherical OMP. We choose isotopes of three rare-earth elements (W, Ho, Gd), which are known to be nearly perfect rotors, to perform a consistent test of our conjecture on integrated cross sections as well as on angular distributions for elastic and inelastic neutron scattering. When doing this we employ the well-established Koning-Delaroche global spherical potential and experimentally determined deformations without any adjustments. We observe a dramatically improved a...
Estimating Predictive Variance for Statistical Gas Distribution Modelling
Lilienthal, Achim J.; Asadi, Sahar; Reggente, Matteo
2009-05-01
Recent publications in statistical gas distribution modelling have proposed algorithms that model mean and variance of a distribution. This paper argues that estimating the predictive concentration variance entails not only a gradual improvement but is rather a significant step to advance the field. This is, first, since the models much better fit the particular structure of gas distributions, which exhibit strong fluctuations with considerable spatial variations as a result of the intermittent character of gas dispersal. Second, because estimating the predictive variance allows to evaluate the model quality in terms of the data likelihood. This offers a solution to the problem of ground truth evaluation, which has always been a critical issue for gas distribution modelling. It also enables solid comparisons of different modelling approaches, and provides the means to learn meta parameters of the model, to determine when the model should be updated or re-initialised, or to suggest new measurement locations based on the current model. We also point out directions of related ongoing or potential future research work.
Hybrid perturbation methods based on statistical time series models
San-Juan, Juan Félix; San-Martín, Montserrat; Pérez, Iván; López, Rosario
2016-04-01
In this work we present a new methodology for orbit propagation, the hybrid perturbation theory, based on the combination of an integration method and a prediction technique. The former, which can be a numerical, analytical or semianalytical theory, generates an initial approximation that contains some inaccuracies derived from the fact that, in order to simplify the expressions and subsequent computations, not all the involved forces are taken into account and only low-order terms are considered, not to mention the fact that mathematical models of perturbations not always reproduce physical phenomena with absolute precision. The prediction technique, which can be based on either statistical time series models or computational intelligence methods, is aimed at modelling and reproducing missing dynamics in the previously integrated approximation. This combination results in the precision improvement of conventional numerical, analytical and semianalytical theories for determining the position and velocity of any artificial satellite or space debris object. In order to validate this methodology, we present a family of three hybrid orbit propagators formed by the combination of three different orders of approximation of an analytical theory and a statistical time series model, and analyse their capability to process the effect produced by the flattening of the Earth. The three considered analytical components are the integration of the Kepler problem, a first-order and a second-order analytical theories, whereas the prediction technique is the same in the three cases, namely an additive Holt-Winters method.
Model output statistics applied to wind power prediction
Energy Technology Data Exchange (ETDEWEB)
Joensen, A.; Giebel, G.; Landberg, L. [Risoe National Lab., Roskilde (Denmark); Madsen, H.; Nielsen, H.A. [The Technical Univ. of Denmark, Dept. of Mathematical Modelling, Lyngby (Denmark)
1999-03-01
Being able to predict the output of a wind farm online for a day or two in advance has significant advantages for utilities, such as better possibility to schedule fossil fuelled power plants and a better position on electricity spot markets. In this paper prediction methods based on Numerical Weather Prediction (NWP) models are considered. The spatial resolution used in NWP models implies that these predictions are not valid locally at a specific wind farm. Furthermore, due to the non-stationary nature and complexity of the processes in the atmosphere, and occasional changes of NWP models, the deviation between the predicted and the measured wind will be time dependent. If observational data is available, and if the deviation between the predictions and the observations exhibits systematic behavior, this should be corrected for; if statistical methods are used, this approaches is usually referred to as MOS (Model Output Statistics). The influence of atmospheric turbulence intensity, topography, prediction horizon length and auto-correlation of wind speed and power is considered, and to take the time-variations into account, adaptive estimation methods are applied. Three estimation techniques are considered and compared, Extended Kalman Filtering, recursive least squares and a new modified recursive least squares algorithm. (au) EU-JOULE-3. 11 refs.
A Statistical Quality Model for Data-Driven Speech Animation.
Ma, Xiaohan; Deng, Zhigang
2012-11-01
In recent years, data-driven speech animation approaches have achieved significant successes in terms of animation quality. However, how to automatically evaluate the realism of novel synthesized speech animations has been an important yet unsolved research problem. In this paper, we propose a novel statistical model (called SAQP) to automatically predict the quality of on-the-fly synthesized speech animations by various data-driven techniques. Its essential idea is to construct a phoneme-based, Speech Animation Trajectory Fitting (SATF) metric to describe speech animation synthesis errors and then build a statistical regression model to learn the association between the obtained SATF metric and the objective speech animation synthesis quality. Through delicately designed user studies, we evaluate the effectiveness and robustness of the proposed SAQP model. To the best of our knowledge, this work is the first-of-its-kind, quantitative quality model for data-driven speech animation. We believe it is the important first step to remove a critical technical barrier for applying data-driven speech animation techniques to numerous online or interactive talking avatar applications.
Statistical process control of a Kalman filter model.
Gamse, Sonja; Nobakht-Ersi, Fereydoun; Sharifi, Mohammad A
2014-01-01
For the evaluation of measurement data, different functional and stochastic models can be used. In the case of time series, a Kalman filtering (KF) algorithm can be implemented. In this case, a very well-known stochastic model, which includes statistical tests in the domain of measurements and in the system state domain, is used. Because the output results depend strongly on input model parameters and the normal distribution of residuals is not always fulfilled, it is very important to perform all possible tests on output results. In this contribution, we give a detailed description of the evaluation of the Kalman filter model. We describe indicators of inner confidence, such as controllability and observability, the determinant of state transition matrix and observing the properties of the a posteriori system state covariance matrix and the properties of the Kalman gain matrix. The statistical tests include the convergence of standard deviations of the system state components and normal distribution beside standard tests. Especially, computing controllability and observability matrices and controlling the normal distribution of residuals are not the standard procedures in the implementation of KF. Practical implementation is done on geodetic kinematic observations. PMID:25264959
Statistical Process Control of a Kalman Filter Model
Directory of Open Access Journals (Sweden)
Sonja Gamse
2014-09-01
Full Text Available For the evaluation of measurement data, different functional and stochastic models can be used. In the case of time series, a Kalman filtering (KF algorithm can be implemented. In this case, a very well-known stochastic model, which includes statistical tests in the domain of measurements and in the system state domain, is used. Because the output results depend strongly on input model parameters and the normal distribution of residuals is not always fulfilled, it is very important to perform all possible tests on output results. In this contribution, we give a detailed description of the evaluation of the Kalman filter model. We describe indicators of inner confidence, such as controllability and observability, the determinant of state transition matrix and observing the properties of the a posteriori system state covariance matrix and the properties of the Kalman gain matrix. The statistical tests include the convergence of standard deviations of the system state components and normal distribution beside standard tests. Especially, computing controllability and observability matrices and controlling the normal distribution of residuals are not the standard procedures in the implementation of KF. Practical implementation is done on geodetic kinematic observations.
Generalized Statistical Models of Voids and Hierarchical Structure in Cosmology
Mekjian, Aram Z.
2007-01-01
Generalized statistical models of voids and hierarchical structure in cosmology are developed. The often quoted negative binomial model and the frequently used thermodynamic model are shown to be special cases of a more general distribution that contains a parameter a. This parameter is related to the Lévy index α and the Fisher critical exponent τ, the latter of which describes the power-law falloff of clumps of matter around a phase transition. The parameter a, exponent τ, or index α can be obtained from properties of a void scaling function. A stochastic probability variable p is introduced into a statistical model, which represents the adhesive growth of galaxy structure. The galaxy count distribution decays exponentially quickly with size for p1/2, adhesive growth can go on indefinitely, thereby forming an infinite supercluster. At p=1/2, a scale-free power-law distribution for the galaxy count distribution is present. The stochastic description also leads to consequences that have some parallels with cosmic string results, percolation theory, and phase transitions.
S-Channel Dark Matter Simplified Models and Unitarity
Englert, Christoph; Spannowsky, Michael
2016-01-01
The ultraviolet structure of $s$-channel mediator dark matter simplified models at hadron colliders is considered. In terms of commonly studied $s$-channel mediator simplified models it is argued that at arbitrarily high energies the perturbative description of dark matter production in high energy scattering at hadron colliders will break down in a number of cases. This is analogous to the well documented breakdown of an EFT description of dark matter collider production. With this in mind, to diagnose whether or not the use of simplified models at the LHC is valid, perturbative unitarity of the scattering amplitude in the processes relevant to LHC dark matter searches is studied. The results are as one would expect: at the LHC and future proton colliders the simplified model descriptions of dark matter production are in general valid. As a result of the general discussion, a simple new class of previously unconsidered `Fermiophobic Scalar' simplified models is proposed, in which a scalar mediator couples to...
Evaluating statistical analysis models for RNA sequencing experiments
Directory of Open Access Journals (Sweden)
Pablo eReeb
2013-09-01
Full Text Available Validating statistical analysis methods for RNA sequencing (RNA-seq experiments is a complex task. Researcher often find themselves having to decide between competing models or assessing the reliability of results obtained with a designated analysis program. Computer simulation has been the most frequently used procedure to verify the adequacy of a model. However, datasets generated by simulations depend on the parameterization and the assumptions of the selected model. Moreover, such datasets may constitute a partial representation of reality as the complexity or RNA-seq data is hard to mimic. We present the use of plasmode datasets to complement the evaluation of statistical models for RNA-seq data. A plasmode is a dataset obtained from experimental data but for which come truth is known. Using a set of simulated scenarios of technical and biological replicates, and public available datasets, we illustrate how to design algorithms to construct plasmodes under different experimental conditions. We contrast results from two types of methods for RNA-seq: i models based on negative binomial distribution (edgeR and DESeq, and ii Gaussian models applied after transformation of data (MAANOVA. Results emphasize the fact that deciding what method to use may be experiment-specific due to the unknown distributions of expression levels. Plasmodes may contribute to choose which method to apply by using a similar pre-existing dataset. The promising results obtained from this approach, emphasize the need of promoting and improving systematic data sharing across the research community to facilitate plasmode building. Although we illustrate the use of plasmode for comparing differential expression analysis models, the flexibility of plasmode construction allows comparing upstream analysis, as normalization procedures or alignment pipelines, as well.
A granular-continuum model of channelization in sedimentary layers by sub-surface flow
Yadav, Vikrant; Kudrolli, Arshad
2014-03-01
We discuss experiments where channels form in a quasi-two dimensional bed of consolidated granular particles by fluid flow. A continuum three phase model was developed recently [A. Mahadevan, A.V. Orpe, A. Kudrolli, and L. Mahadevan, EPL, 2012] which shows that channels can develop from small differences in packing in an otherwise homogeneous medium which leads to increased porosity and nonlinear feedback. To build on this model, an erodible porous medium composed of millimeter scale grains and Bentonite clay was prepared in a Hele-Shaw cell. The cohesive strength between the grains is directly proportional to the amount of clay binder. When water is pumped through this porous medium, the binder dissolves and loose beads are advected out of the erodible medium, and an initially uniform flow of water through the porous medium gets localized into channels over time. We will discuss the measured integrated rates of erosion as well as the statistical development of heterogeneity and comparison with the three-phase model as a function of binding strength and consolidation of the medium. Supported by DOE Grant No. DE-FG02-13ER16401.
Rivier, Aurelie; Guillou, Nicolas; Chapalain, Georges; Gohin, Francis
2012-01-01
Concentration of near-surface suspended particulate matter (SPM) is a key parameter for the characterization of sediment dynamics and the quantification of light in the water column for hydrological and biological modeling in coastal seas. The influences of tides and wind-generated surface-gravity waves on non-algal near-surface SPM in the English Channel have recently been identified by Rivier et al. (2012) on the basis of statistical models applied to a large satellite dataset. The present ...
Hybrid Perturbation methods based on Statistical Time Series models
San-Juan, Juan Félix; Pérez, Iván; López, Rosario
2016-01-01
In this work we present a new methodology for orbit propagation, the hybrid perturbation theory, based on the combination of an integration method and a prediction technique. The former, which can be a numerical, analytical or semianalytical theory, generates an initial approximation that contains some inaccuracies derived from the fact that, in order to simplify the expressions and subsequent computations, not all the involved forces are taken into account and only low-order terms are considered, not to mention the fact that mathematical models of perturbations not always reproduce physical phenomena with absolute precision. The prediction technique, which can be based on either statistical time series models or computational intelligence methods, is aimed at modelling and reproducing missing dynamics in the previously integrated approximation. This combination results in the precision improvement of conventional numerical, analytical and semianalytical theories for determining the position and velocity of a...
Statistical Modeling of Photovoltaic Reliability Using Accelerated Degradation Techniques (Poster)
Energy Technology Data Exchange (ETDEWEB)
Lee, J.; Elmore, R.; Jones, W.
2011-02-01
We introduce a cutting-edge life-testing technique, accelerated degradation testing (ADT), for PV reliability testing. The ADT technique is a cost-effective and flexible reliability testing method with multiple (MADT) and Step-Stress (SSADT) variants. In an environment with limited resources, including equipment (chambers), test units, and testing time, these techniques can provide statistically rigorous prediction of lifetime and other interesting parameters, such as failure rate, warranty time, mean time to failure, degradation rate, activation energy, acceleration factor, and upper limit level of stress. J-V characterization can be used for degradation data and the generalized Eyring model can be used for the thermal-humidity stress condition. The SSADT model can be constructed based on the cumulative damage model (CEM), which assumes that the remaining test united are failed according to cumulative density function of current stress level regardless of the history on previous stress levels.
Exploiting linkage disequilibrium in statistical modelling in quantitative genomics
DEFF Research Database (Denmark)
Wang, Lei
the recently proposed antedependence models, which treat neighbouring marker effects as correlated; another approach involves use of haplotype block information derived using the program Beagle. The overall conclusion is that taking LD information into account in genomic prediction models potentially......Alleles at two loci are said to be in linkage disequilibrium (LD) when they are correlated or statistically dependent. Genomic prediction and gene mapping rely on the existence of LD between gentic markers and causul variants of complex traits. In the first part of the thesis, a novel method to...... quantify and visualize local variation in LD along chromosomes in describet, and applied to characterize LD patters at the local and genome-wide scale in three Danish pig breeds. In the second part, different ways of taking LD into account in genomic prediction models are studied. One approach is to use...
Dynamic statistical models of biological cognition: insights from communications theory
Wallace, Rodrick
2014-10-01
Maturana's cognitive perspective on the living state, Dretske's insight on how information theory constrains cognition, the Atlan/Cohen cognitive paradigm, and models of intelligence without representation, permit construction of a spectrum of dynamic necessary conditions statistical models of signal transduction, regulation, and metabolism at and across the many scales and levels of organisation of an organism and its context. Nonequilibrium critical phenomena analogous to physical phase transitions, driven by crosstalk, will be ubiquitous, representing not only signal switching, but the recruitment of underlying cognitive modules into tunable dynamic coalitions that address changing patterns of need and opportunity at all scales and levels of organisation. The models proposed here, while certainly providing much conceptual insight, should be most useful in the analysis of empirical data, much as are fitted regression equations.
Optimal Fuzzy Model Construction with Statistical Information using Genetic Algorithm
Hossain, Md Amjad; Sarker, Bishnu; Murase, Kazuyuki
2012-01-01
Fuzzy rule based models have a capability to approximate any continuous function to any degree of accuracy on a compact domain. The majority of FLC design process relies on heuristic knowledge of experience operators. In order to make the design process automatic we present a genetic approach to learn fuzzy rules as well as membership function parameters. Moreover, several statistical information criteria such as the Akaike information criterion (AIC), the Bhansali-Downham information criterion (BDIC), and the Schwarz-Rissanen information criterion (SRIC) are used to construct optimal fuzzy models by reducing fuzzy rules. A genetic scheme is used to design Takagi-Sugeno-Kang (TSK) model for identification of the antecedent rule parameters and the identification of the consequent parameters. Computer simulations are presented confirming the performance of the constructed fuzzy logic controller.
RM-structure alignment based statistical machine translation model
Institute of Scientific and Technical Information of China (English)
Sun Jiadong; Zhao Tiejun
2008-01-01
A novel model based on structure alignments is proposed for statistical machine translation in this paper.Meta-structure and sequence of meta-structure for a parse tree are defined.During the translation process, a parse tree is decomposed to deal with the structure divergence and the alignments can be constructed at different levels of recombination of meta-structure (RM).This method can perform the structure mapping across the sub-tree structure between languages.As a result, we get not only the translation for the target language, but sequence of meta-structure of its parse tree at the same time.Experiments show that the model in the framework of log-linear model has better generative ability and significantly outperforms Pharaoh, a phrase-based system.
A review of radio channel models for body centric communications
Cotton, Simon L.; D'Errico, Raffaele; Oestges, Claude
2014-06-01
The human body is an extremely challenging environment for the operation of wireless communications systems, not least because of the complex antenna-body electromagnetic interaction effects which can occur. This is further compounded by the impact of movement and the propagation characteristics of the local environment which all have an effect upon body centric communications channels. As the successful design of body area networks (BANs) and other types of body centric system is inextricably linked to a thorough understanding of these factors, the aim of this paper is to conduct a survey of the current state of the art in relation to propagation and channel models primarily for BANs but also considering other types of body centric communications. We initially discuss some of the standardization efforts performed by the Institute of Electrical and Electronics Engineers 802.15.6 task group before focusing on the two most popular types of technologies currently being considered for BANs, namely narrowband and Ultrawideband (UWB) communications. For narrowband communications the applicability of a generic path loss model is contended, before presenting some of the scenario specific models which have proven successful. The impacts of human body shadowing and small-scale fading are also presented alongside some of the most recent research into the Doppler and time dependencies of BANs. For UWB BAN communications, we again consider the path loss as well as empirical tap delay line models developed from a number of extensive channel measurement campaigns conducted by research institutions around the world. Ongoing efforts within collaborative projects such as Committee on Science and Technology Action IC1004 are also described. Finally, recent years have also seen significant developments in other areas of body centric communications such as off-body and body-to-body communications. We highlight some of the newest relevant research in these areas as well as discussing
Turning statistical physics models into materials design engines.
Miskin, Marc Z; Khaira, Gurdaman; de Pablo, Juan J; Jaeger, Heinrich M
2016-01-01
Despite the success statistical physics has enjoyed at predicting the properties of materials for given parameters, the inverse problem, identifying which material parameters produce given, desired properties, is only beginning to be addressed. Recently, several methods have emerged across disciplines that draw upon optimization and simulation to create computer programs that tailor material responses to specified behaviors. However, so far the methods developed either involve black-box techniques, in which the optimizer operates without explicit knowledge of the material's configuration space, or require carefully tuned algorithms with applicability limited to a narrow subclass of materials. Here we introduce a formalism that can generate optimizers automatically by extending statistical mechanics into the realm of design. The strength of this approach lies in its capability to transform statistical models that describe materials into optimizers to tailor them. By comparing against standard black-box optimization methods, we demonstrate how optimizers generated by this formalism can be faster and more effective, while remaining straightforward to implement. The scope of our approach includes possibilities for solving a variety of complex optimization and design problems concerning materials both in and out of equilibrium. PMID:26684770
How Good Are Statistical Models at Approximating Complex Fitness Landscapes?
du Plessis, Louis; Leventhal, Gabriel E; Bonhoeffer, Sebastian
2016-09-01
Fitness landscapes determine the course of adaptation by constraining and shaping evolutionary trajectories. Knowledge of the structure of a fitness landscape can thus predict evolutionary outcomes. Empirical fitness landscapes, however, have so far only offered limited insight into real-world questions, as the high dimensionality of sequence spaces makes it impossible to exhaustively measure the fitness of all variants of biologically meaningful sequences. We must therefore revert to statistical descriptions of fitness landscapes that are based on a sparse sample of fitness measurements. It remains unclear, however, how much data are required for such statistical descriptions to be useful. Here, we assess the ability of regression models accounting for single and pairwise mutations to correctly approximate a complex quasi-empirical fitness landscape. We compare approximations based on various sampling regimes of an RNA landscape and find that the sampling regime strongly influences the quality of the regression. On the one hand it is generally impossible to generate sufficient samples to achieve a good approximation of the complete fitness landscape, and on the other hand systematic sampling schemes can only provide a good description of the immediate neighborhood of a sequence of interest. Nevertheless, we obtain a remarkably good and unbiased fit to the local landscape when using sequences from a population that has evolved under strong selection. Thus, current statistical methods can provide a good approximation to the landscape of naturally evolving populations. PMID:27189564
How Good Are Statistical Models at Approximating Complex Fitness Landscapes?
du Plessis, Louis; Leventhal, Gabriel E.; Bonhoeffer, Sebastian
2016-01-01
Fitness landscapes determine the course of adaptation by constraining and shaping evolutionary trajectories. Knowledge of the structure of a fitness landscape can thus predict evolutionary outcomes. Empirical fitness landscapes, however, have so far only offered limited insight into real-world questions, as the high dimensionality of sequence spaces makes it impossible to exhaustively measure the fitness of all variants of biologically meaningful sequences. We must therefore revert to statistical descriptions of fitness landscapes that are based on a sparse sample of fitness measurements. It remains unclear, however, how much data are required for such statistical descriptions to be useful. Here, we assess the ability of regression models accounting for single and pairwise mutations to correctly approximate a complex quasi-empirical fitness landscape. We compare approximations based on various sampling regimes of an RNA landscape and find that the sampling regime strongly influences the quality of the regression. On the one hand it is generally impossible to generate sufficient samples to achieve a good approximation of the complete fitness landscape, and on the other hand systematic sampling schemes can only provide a good description of the immediate neighborhood of a sequence of interest. Nevertheless, we obtain a remarkably good and unbiased fit to the local landscape when using sequences from a population that has evolved under strong selection. Thus, current statistical methods can provide a good approximation to the landscape of naturally evolving populations. PMID:27189564
How Good Are Statistical Models at Approximating Complex Fitness Landscapes?
du Plessis, Louis; Leventhal, Gabriel E; Bonhoeffer, Sebastian
2016-09-01
Fitness landscapes determine the course of adaptation by constraining and shaping evolutionary trajectories. Knowledge of the structure of a fitness landscape can thus predict evolutionary outcomes. Empirical fitness landscapes, however, have so far only offered limited insight into real-world questions, as the high dimensionality of sequence spaces makes it impossible to exhaustively measure the fitness of all variants of biologically meaningful sequences. We must therefore revert to statistical descriptions of fitness landscapes that are based on a sparse sample of fitness measurements. It remains unclear, however, how much data are required for such statistical descriptions to be useful. Here, we assess the ability of regression models accounting for single and pairwise mutations to correctly approximate a complex quasi-empirical fitness landscape. We compare approximations based on various sampling regimes of an RNA landscape and find that the sampling regime strongly influences the quality of the regression. On the one hand it is generally impossible to generate sufficient samples to achieve a good approximation of the complete fitness landscape, and on the other hand systematic sampling schemes can only provide a good description of the immediate neighborhood of a sequence of interest. Nevertheless, we obtain a remarkably good and unbiased fit to the local landscape when using sequences from a population that has evolved under strong selection. Thus, current statistical methods can provide a good approximation to the landscape of naturally evolving populations.
Statistical mechanics of shell models for 2D-Turbulence
Aurell, E; Crisanti, A; Frick, P; Paladin, G; Vulpiani, A
1994-01-01
We study shell models that conserve the analogues of energy and enstrophy, hence designed to mimic fluid turbulence in 2D. The main result is that the observed state is well described as a formal statistical equilibrium, closely analogous to the approach to two-dimensional ideal hydrodynamics of Onsager, Hopf and Lee. In the presence of forcing and dissipation we observe a forward flux of enstrophy and a backward flux of energy. These fluxes can be understood as mean diffusive drifts from a source to two sinks in a system which is close to local equilibrium with Lagrange multipliers (``shell temperatures'') changing slowly with scale. The dimensional predictions on the power spectra from a supposed forward cascade of enstrophy, and from one branch of the formal statistical equilibrium, coincide in these shell models at difference to the corresponding predictions for the Navier-Stokes and Euler equations in 2D. This coincidence have previously led to the mistaken conclusion that shell models exhibit a forward ...
Symmetry Energy Effects in a Statistical Multifragmentation Model
Institute of Scientific and Technical Information of China (English)
ZHANG Lei; GAO Yuan1; ZHANG Hong-Fei; CHEN Xi-Meng; Yu Mei-Ling; LI Jun-Qing
2011-01-01
The symmetry energy effects on the nuclear disintegration mechanisms of the neutron-rich system (A0 = 200, Z0 = 78) are studied in the framework of the statistical multifragmentation model (SMM) within its micro-canonical ensemble. A modified symmetry energy term with consideration of the volume and surface asymmetry is adopted instead of the original invariable value in the standard SMM model. The results indicate that as the volume and surface asymmetries are considered, the neutron-rich system translates to a fission-like process from evaporation earlier than the original standard SMM model at lower excitation energies, and its mass distribution has larger probabilities in the medium-heavy nuclei range so that the system breaks up more averagely. When the excitation energy becomes higher, the volume and surface asymmetry lead to a smaller average multiplicity.%The symmetry energy effects on the nuclear disintegration mechanisms of the neutron-rich system (A0 =200,Z0 =78) are studied in the framework of the statistical multifragmentation model (SMM) within its micro-canonical ensemble.A modified symmetry energy term with consideration of the volume and surface asymmetry is adopted instead of the original invariable value in the standard SMM model.The results indicate that as the volume and surface asymmetries are considered,the neutron-rich system translates to a fission-like process from evaporation earlier than the original standard SMM model at lower excitation energies,and its mass distribution has larger probabilities in the medium-heavy nuclei range so that the system breaks up more averagely.When the excitation energy becomes higher,the volume and surface asymmetry lead to a smaller average multiplicity.
Random matrices as models for the statistics of quantum mechanics
Casati, Giulio; Guarneri, Italo; Mantica, Giorgio
1986-05-01
Random matrices from the Gaussian unitary ensemble generate in a natural way unitary groups of evolution in finite-dimensional spaces. The statistical properties of this time evolution can be investigated by studying the time autocorrelation functions of dynamical variables. We prove general results on the decay properties of such autocorrelation functions in the limit of infinite-dimensional matrices. We discuss the relevance of random matrices as models for the dynamics of quantum systems that are chaotic in the classical limit. Permanent address: Dipartimento di Fisica, Via Celoria 16, 20133 Milano, Italy.
CHRiSM: CHance Rules induce Statistical Models
Sneyers, Jon; Meert, Wannes; Vennekens, Joost
2009-01-01
A new probabilistic-logic formalism, called CHRiSM, is introduced. CHRiSM is based on a combination of CHR and PRISM. It can be used for high-level rapid prototyping of complex statistical models by means of chance rules. The underlying PRISM system can then be used for several probabilistic inference tasks, including parameter learning. We describe a source-to-source transformation from CHRiSM rules to PRISM, via CHR(PRISM). Finally we discuss the relation between CHRiSM and probab...
Statistical properties of a two-stage model of carcinogenesis.
Portier, C J
1987-01-01
Some of the statistical properties of a simple two-stage model of carcinogenesis are explored. The implications of additive treatment effects versus independent treatment effects on the shape of the dose-response curve are considered. Response that is low-dose linear results in the cases where the mutation rates are affected by dose or in the cases where treatment changes the birth rate/death rate of initiated cells in an additive fashion. Independent treatment effects lead to non-low-dose li...
A Quantal Response Equilibrium Model of Order Statistic Games
Yi, Kang-Oh
1999-01-01
This paper applies quantal response equilibrium (QRE) models (McKelvey and Palfrey, Games and Economic Behavior 10 (1995), 6-38) to a wide class of symmetric coordination games in which each player's best response is determined by an order statistic of all players' decisions, as in the classic experiments of Van Huyck, Battalio, and Beil (American Economic Review 80 (1990), 234-248; Quarterly Journal of Economics 106 (1991), 885-910), but players have a bounded continuum of decisions, which a...
Modeling negative ion defect migration through the gramicidin A channel.
Nemukhin, Alexander V; Kaliman, Ilya A; Moskovsky, Alexander A
2009-08-01
The results of potential of mean force (PMF) calculations for the distinct stages of proton conduction through the gramicidin A channel, including proton migration, reorientation of the water file and negative ion defect migration, are presented. The negative ion defect migration mechanism was hypothesized in experimental studies but was not considered previously in molecular dynamics simulations. The model system consisted of the peptide chains constructed on the base of the structure PDBID:1JNO, the inner file of nine water molecules and external clusters of water molecules placed at both ends of the channel. Potential energy functions were computed with the CHARMM/PM6/TIP3P parameters. The results obtained for proton migration and water file reorientation are basically consistent with those reported previously by Pómès and Roux (Biophys J 82:2304, 2002) within the similar approach. For the newly considered mechanism of negative ion defect migration from the channel center to the end of the water file we obtain the energy 3.8 kcal mol(-1) which is not considerably different from the activation energy of water reorientation, 5.4 kcal mol(-1). Therefore this mechanism may principally compete for the rate-limiting step in proton conduction in gramicidin. PMID:19198898
Modelling of flow and heat transfer in PV cooling channels
Energy Technology Data Exchange (ETDEWEB)
Diarra, D.C.; Harrison, S.J. [Queen' s Univ., Kingston, ON (Canada). Dept. of Mechanical and Materials Engineering Solar Calorimetry Lab; Akuffo, F.O. [Kwame Nkrumah Univ. of Science and Technology, Kumasi (Ghana). Dept. of Mechanical Engineering
2005-07-01
Under sunny conditions, the temperature of photovoltaic (PV) modules can be 20 to 30 degrees C above the ambient air temperature. This affects the performance of PV modules, particularly in regions with hot climates. For silicon solar cells, the maximum power decreases between 0.4 and 0.5 per cent for every degree C of temperature increase above a reference value. In an effort to address this issue, this experimental and numerical study examined an active PV panel evaporative cooling scheme that is typically used in hot arid climates. The cooling system circulated cool air behind the PV modules, extracting heat and lowering solar cell temperature. A fluid dynamic and thermal model of the combined system was developed using the EES program in order to study the configuration of the cooling channel and the characteristics of the cooling flow. Heat transfer and flow characteristics in the cooling channel were then calculated along with pressure drop and fan power associated with the air-circulation. The net power output was also calculated. The objective was to design a cost efficient cooling system and to optimize its flow and pressure drop in order to maximize power output. The study demonstrated how the performance of the PV panel is influenced by the geometry of the cooling channel, the inlet air temperature and the air flow rate. 2 refs.
2D numerical modelling of meandering channel formation
Indian Academy of Sciences (India)
Y Xiao; G Zhou; F S Yang
2016-03-01
A 2D depth-averaged model for hydrodynamic sediment transport and river morphological adjustment was established. The sediment transport submodel takes into account the influence of non-uniform sediment with bed surface armoring and considers the impact of secondary flow in the direction of bed-loadtransport and transverse slope of the river bed. The bank erosion submodel incorporates a simple simulation method for updating bank geometry during either degradational or aggradational bed evolution. Comparison of the results obtained by the extended model with experimental and field data, and numericalpredictions validate that the proposed model can simulate grain sorting in river bends and duplicate the characteristics of meandering river and its development. The results illustrate that by using its control factors, the improved numerical model can be applied to simulate channel evolution under differentscenarios and improve understanding of patterning processes.
A statistical model of FM-TV spectra for satellite interference and distortion prediction
Boeck, A. M.; Carpenter, D. C.; Gallois, A. P.
1990-04-01
The requirement for a model of FM-TV spectra in the planning procedure of satellite communication systems is introduced. Based on long-term measurements of live TV channels, statistical properties of video spectra are examined and probability distributions for the luminance and chrominance components are proposed. The spectrum of the frequency-modulated signal is then derived, and signal distortion due to bandlimiting is calculated. Adjacent and cochannel interference effects are also investigated, with example cases illustrating influences of subcarrier loading and energy dispersion. The proposed model, which describes FM-TV spectra in terms of random variables, makes it possible to examine relative effects of system parameters, and will, therefore, be of benefit in the planning of new satellite services.
River channel's predisposition to ice jams: a geospatial model
De Munck, S.; Gauthier, Y.; Bernier, M.; Légaré, S.
2012-04-01
When dynamic breakup occurs on rivers, ice moving downstream may eventually stop at an obstacle when the volume of moving ice exceeds the transport capacity of the river, resulting into an ice jam. The suddenness and unpredictability of these ice jams are a constant danger to local population. Therefore forecasting methods are necessary to provide an early warning to these population. Nonetheless the morphological and hydrological factors controlling where and how the ice will jam are numerous and complex. Existing studies which exist on this topic are highly site specific. Therefore, the goal of this work is to develop a simplified geospatial model that would estimate the predisposition of any river channel to ice jams. The question here is not to predict when the ice will break up but rather to know where the released ice would be susceptible to jam. This paper presents the developments and preliminary results of the proposed approach. The initial step was to document the main factors identified in the literature, as potential cause for an ice jam. First, several main factors identified in the literature as potential cause for an ice jam have been selected: presence of an island, narrowing of the channel, sinuosity, presence of a bridge, confluence of rivers and slope break. The second step was to spatially represent, in 2D, the physical characteristics of the channel and to translate these characteristics into potential ice jamming factors. The Chaudiere River, south of Quebec City (Canada), was chosen as a test site. Tools from the GIS-based FRAZIL system have been used to generate these factors from readily available geospatial data and calcutate an "ice jam predisposition index" over regular-spaced segments along the entire channel. The resulting map was validated upon historical observations and local knowledge, collected in relationship with the Minister of Public Security.
Statistical shape model-based segmentation of brain MRI images.
Bailleul, Jonathan; Ruan, Su; Constans, Jean-Marc
2007-01-01
We propose a segmentation method that automatically delineates structures contours from 3D brain MRI images using a statistical shape model. We automatically build this 3D Point Distribution Model (PDM) in applying a Minimum Description Length (MDL) annotation to a training set of shapes, obtained by registration of a 3D anatomical atlas over a set of patients brain MRIs. Delineation of any structure from a new MRI image is first initialized by such registration. Then, delineation is achieved in iterating two consecutive steps until the 3D contour reaches idempotence. The first step consists in applying an intensity model to the latest shape position so as to formulate a closer guess: our model requires far less priors than standard model in aiming at direct interpretation rather than compliance to learned contexts. The second step consists in enforcing shape constraints onto previous guess so as to remove all bias induced by artifacts or low contrast on current MRI. For this, we infer the closest shape instance from the PDM shape space using a new estimation method which accuracy is significantly improved by a huge increase in the model resolution and by a depth-search in the parameter space. The delineation results we obtained are very encouraging and show the interest of the proposed framework. PMID:18003193
Optical wireless communications system and channel modelling with Matlab
Ghassemlooy, Z
2012-01-01
Detailing a systems approach, Optical Wireless Communications: System and Channel Modelling with MATLAB(R), is a self-contained volume that concisely and comprehensively covers the theory and technology of optical wireless communications systems (OWC) in a way that is suitable for undergraduate and graduate-level students, as well as researchers and professional engineers. Incorporating MATLAB(R) throughout, the authors highlight past and current research activities to illustrate optical sources, transmitters, detectors, receivers, and other devices used in optical wireless communications. The
A combined statistical model for multiple motifs search
Institute of Scientific and Technical Information of China (English)
Gao Li-Feng; Liu Xin; Guan Shan
2008-01-01
Transcription factor binding sites (TFBS) play key roles in genebior 6.8 wavelet expression and regulation. They are short sequence segments with definite structure and can be recognized by the corresponding transcription factors correctly. From the viewpoint of statistics, the candidates of TFBS should be quite different from the segments that are randomly combined together by nucleotide. This paper proposes a combined statistical model for finding overrepresented short sequence segments in different kinds of data set. While the over-represented short sequence segment is described by position weight matrix, the nucleotide distribution at most sites of the segment should be far from the background nucleotide distribution. The central idea of this approach is to search for such kind of signals. This algorithm is tested on 3 data sets, including binding sites data set of cyclic AMP receptor protein in E.coli, PlantProm DB which is a non-redundant collection of proximal promoter sequences from different species, collection of the intergenic sequences of the whole genome of E.Coli. Even though the complexity of these three data sets is quite different, the results show that this model is rather general and sensible.
Energy Level Statistics in Particle—Rotor Model
Institute of Scientific and Technical Information of China (English)
ZHOUXian－Rong; MENGJie; 等
2002-01-01
Energy level statistics of a system consisting of six particles interacting by delta force in a two-j model coupled with a deformed core is studied in particle-rotor model.For single-j shell (i13/2) and two-j shell (g7/2+d5/2) the exact energies for our statistical analysis are obtained from a full diagonalization of the Hamiltonian,whilt in two-j case (i13/2+g9/2) the configuration truncation is used.The nearest-neighbor distribution of energy levels and spectral rigidity are studied as the function of spin.The results of single-j shell are compared with those in two-j case.It is showed that the system becomes more regular when single-j space (i13/2) is replaced by two-j shell (g7/2+d5/2) although the basis size of the configuration space is unchanged.The degree of chaoticity of the system,however,changes slightly when configuration space is enlarged by extending single-j shell (i13/2) to two-j shell (i13/2+g9/2).
A derivation of the NS-alpha model and preliminary application to plane channel flow
Scott, K Andrea
2010-01-01
In this paper we consider the Navier-Stokes-$\\alpha$ (NS-$\\alpha$) model within a large-eddy simulation framework. An investigation is carried out using fully-developed turbulent channel flow at a fairly low Reynolds number. This is a flow where diffusion plays a prominent role, and presents a challenge to the nonlinear model investigated here. It is found that when $\\alpha^{2}_{k}$ is based on the mesh spacing, the NS-$\\alpha$ model has a tendency to tilt spanwise vorticity in the streamwise direction, leading to high skin friction. This is due to interaction between the spanwise vorticity, the model, and the streamwise streaks. To overcome this problem $\\alpha^{2}_{k}$ is damped in the streak affected region. Results overall demonstrate the potential of the model to reproduce some features of the DNS (helicity statistics and small-scale features), but more work is required before the full potential of the model can be achieved. In addition to the channel flow investigation, a derivation of the governing usi...
Role of scaling in the statistical modelling of finance
Indian Academy of Sciences (India)
Attilio L Stella; Fulvio Baldovin
2008-08-01
Modelling the evolution of a financial index as a stochastic process is a problem awaiting a full, satisfactory solution since it was first formulated by Bachelier in 1900. Here it is shown that the scaling with time of the return probability density function sampled from the historical series suggests a successful model. The resulting stochastic process is a heteroskedastic, non-Markovian martingale, which can be used to simulate index evolution on the basis of an autoregressive strategy. Results are fully consistent with volatility clustering and with the multiscaling properties of the return distribution. The idea of basing the process construction on scaling, and the construction itself, are closely inspired by the probabilistic renormalization group approach of statistical mechanics and by a recent formulation of the central limit theorem for sums of strongly correlated random variables.
Helicity statistics in homogeneous and isotropic turbulence and turbulence models
Sahoo, Ganapati; Biferale, Luca
2016-01-01
We study the statistical properties of helicity in direct numerical simulations of fully developed homogeneous and isotropic turbulence and in a class of turbulence shell models. We consider correlation functions based on combinations of vorticity and velocity increments that are not invariant under mirror symmetry. We also study the scaling properties of high-order structure functions based on the moments of the velocity increments projected on a subset of modes with either positive or negative helicity (chirality). We show that mirror symmetry is recovered at small-scales, i.e. chiral terms are always subleading and they are well captured by a dimensional argument plus a small anomalous correction. We confirm these findings with numerical study of helical shell models at high Reynolds numbers.
Isospin dependence of nuclear multifragmentation in statistical model
Institute of Scientific and Technical Information of China (English)
ZHANG Lei; XIE Dong-Zhu; ZHANG Yan-Ping; GAO Yuan
2011-01-01
The evolution of nuclear disintegration mechanisms with increasing excitation energy, from com- pound nucleus to multifragmentation, has been studied by using the Statistical Multifragmentation Model (SMM) within a micro-canonical ensemble. We discuss the observable characteristics as functions of excitation energy in multifragmentation, concentrating on the isospin dependence of the model in its decaying mechanism and break-up fragment configuration by comparing the A = 200, Z = 78 and A = 200, Z = 100 systems. The calculations indicate that the neutron-rich system (Z = 78) translates to a fission-like process from evaporation later than the symmetric nucleus at a lower excitation energy, but gets a larger average multiplicity as the excitation energy increases above 1.0 MeV/u.
OPTIMAL FUZZY MODEL CONSTRUCTION WITH STATISTICAL INFORMATION USING GENETIC ALGORITHM
Directory of Open Access Journals (Sweden)
Bishnu Sarker
2012-01-01
Full Text Available Fuzzy rule based models have a capability to approximate any continuous function to any degree ofaccuracy on a compact domain. The majority of FLC design process relies on heuristic knowledge ofexperience operators. In order to make the design process automatic we present a genetic approach tolearn fuzzy rules as well as membership function parameters. Moreover, several statistical informationcriteria such as the Akaike information criterion (AIC, the Bhansali-Downham information criterion(BDIC, and the Schwarz-Rissanen information criterion (SRIC are used to construct optimal fuzzymodels by reducing fuzzy rules. A genetic scheme is used to design Takagi-Sugeno-Kang (TSK model foridentification of the antecedent rule parameters and the identification of the consequent parameters.Computer simulations are presented confirming the performance of the constructed fuzzy logiccontroller.
Statistical analysis and model of spread F occurrence in China
Institute of Scientific and Technical Information of China (English)
无
2010-01-01
The spread F data obtained over Lanzhou (36.1°N,103.9°E),Chongqing (29.5°N,106.4°E) and Haikou (20.0°N,110.3°E) of China during the period from 1978 to 1997 are used to analyze the occurrence characteristics.The statistical results show that the post midnight spread F occurrence is maximum during the summer solstice months of the lower solar activity period,while post sunset spread F is dominant in equinoxes of higher solar activity period over Haikou station.Over Chongqing and Lanzhou stations,spread F mostly occurs at post midnight and relates negatively with solar activity.Using regression method and Fourier expansion,the preliminary single-station model of spread F occurrence is established and the accuracy of the model is evaluated.
Statistical Agent Based Modelization of the Phenomenon of Drug Abuse
di Clemente, Riccardo; Pietronero, Luciano
2012-07-01
We introduce a statistical agent based model to describe the phenomenon of drug abuse and its dynamical evolution at the individual and global level. The agents are heterogeneous with respect to their intrinsic inclination to drugs, to their budget attitude and social environment. The various levels of drug use were inspired by the professional description of the phenomenon and this permits a direct comparison with all available data. We show that certain elements have a great importance to start the use of drugs, for example the rare events in the personal experiences which permit to overcame the barrier of drug use occasionally. The analysis of how the system reacts to perturbations is very important to understand its key elements and it provides strategies for effective policy making. The present model represents the first step of a realistic description of this phenomenon and can be easily generalized in various directions.
Statistical Agent Based Modelization of the Phenomenon of Drug Abuse
Di Clemente, Riccardo; 10.1038/srep00532
2012-01-01
We introduce a statistical agent based model to describe the phenomenon of drug abuse and its dynamical evolution at the individual and global level. The agents are heterogeneous with respect to their intrinsic inclination to drugs, to their budget attitude and social environment. The various levels of drug use were inspired by the professional description of the phenomenon and this permits a direct comparison with all available data. We show that certain elements have a great importance to start the use of drugs, for example the rare events in the personal experiences which permit to overcame the barrier of drug use occasionally. The analysis of how the system reacts to perturbations is very important to understand its key elements and it provides strategies for effective policy making. The present model represents the first step of a realistic description of this phenomenon and can be easily generalized in various directions.
Ansari, Imran Shafique
2010-12-01
The introduction of new schemes that are based on the communication among nodes has motivated the use of composite fading models due to the fact that the nodes experience different multipath fading and shadowing statistics, which subsequently determines the required statistics for the performance analysis of different transceivers. The end-to-end signal-to-noise-ratio (SNR) statistics plays an essential role in the determination of the performance of cascaded digital communication systems. In this thesis, a closed-form expression for the probability density function (PDF) of the end-end SNR for independent but not necessarily identically distributed (i.n.i.d.) cascaded generalized-K (GK) composite fading channels is derived. The developed PDF expression in terms of the Meijer-G function allows the derivation of subsequent performance metrics, applicable to different modulation schemes, including outage probability, bit error rate for coherent as well as non-coherent systems, and average channel capacity that provides insights into the performance of a digital communication system operating in N cascaded GK composite fading environment. Another line of research that was motivated by the introduction of composite fading channels is the error performance. Error performance is one of the main performance measures and derivation of its closed-form expression has proved to be quite involved for certain systems. Hence, in this thesis, a unified closed-form expression, applicable to different binary modulation schemes, for the bit error rate of dual-branch selection diversity based systems undergoing i.n.i.d. GK fading is derived in terms of the extended generalized bivariate Meijer G-function.
Physics based modelling of short-channel nanowire MOSFET
Energy Technology Data Exchange (ETDEWEB)
Boerli, H; Kolberg, S; Fjeldly, T A [Department of Electronics and Telecommunication, Norwegian University of Science and Technology, and UniK, University Graduate Center, N-2021 Kjeller (Norway)], E-mail: hborli@unik.no, E-mail: kolberg@unik.no, E-mail: torfj@unik.no
2008-03-15
A modelling framework for short channel nanowire (NW) MOSFETs that covers a wide range of operating conditions is presented. The device electrostatics in the subthreshold regime is dominated by the inter-electrode capacitive coupling, which, in the case of double gate (DG) devices, is analyzed in terms of conformal mapping techniques. Previously, we have shown that these results can also be successfully applied to the NW MOSFET, by performing an appropriate mapping to compensate for the difference in gate control between the two devices. Near and above threshold, the influence of the electronic charge is taken into account in a precise, self-consistent manner by combining suitable model expressions with Poisson's equation. The models are verified by comparison with numerical device simulations.
A statistics-based pitch contour model for Mandarin speech.
Chen, Sin-Horng; Lai, Wen-Hsing; Wang, Yih-Ru
2005-02-01
A statistics-based syllable pitch contour model for Mandarin speech is proposed. This approach takes the mean and the shape of a syllable log-pitch contour as two basic modeling units and considers several affecting factors that contribute to their variations. The affecting factors include the speaker, prosodic state (which essentially represents the high-level linguistic components of F0 and will be explained more clearly in Sec. I), tone, and initial and final syllable classes. The parameters of the two modeling units were automatically estimated using the expectation-maximization (EM) algorithm. Experimental results showed that the root mean squared errors (RMSEs) obtained in the closed and open tests in the reconstructed pitch period were 0.362 and 0.373 ms, respectively. This model provides a way to separate the effects of several major factors. All of the inferred values of the affecting factors were in close agreement with our prior linguistic knowledge. It also gives a quantitative and more complete description of the coarticulation effect of neighboring tones rather than conventional qualitative descriptions of the tone sandhi rules. In addition, the model can provide useful cues to determine the prosodic phrase boundaries, including those occurring at intersyllable locations, with or without punctuation marks. PMID:15759710
Miyazawa, N.
2011-12-01
River-channel changes are a key factor affecting physical, ecological and management issues in the fluvial environment. In this study, long-term channel changes in the Mekong River were assessed using remote sensing and a channel-evolution model. A channel-evolution model for calculating long-term channel changes of a measndering river was developed using a previous fluid-dynamic model [Zolezzi and Seminara, 2001], and was applied in order to quantify channel changes of two meandering reaches in the Mekong River. Quite few attempts have been made so far to combine remote sensing observation of meandering planform change with the application of channel evolution models within relatively small-scale gravel-bed systems in humid temperate regions. The novel point of the present work is to link state-of-art meandering planform evolution model with observed morphological changes within large-scale sand-bed rivers with higher bank height in tropical monsoonal climate regions, which are the highly dynamic system, and assess the performance. Unstable extents of the reaches could be historically identified using remote-sensing technique. The instability caused i) bank erosion and accretion of meander bends and ii) movement or development of bars and changes in the flow around the bars. The remote sensing measurements indicate that maximum erosion occurred downstream of the maximum curvature of the river-center line in both reaches. The model simulations indicates that under the mean annual peak discharge the maximum of excess longitudinal velocity near the banks occurs downstream of the maximum curvature in both reaches. The channel migration coefficients of the reaches were calibrated by comparing remote-sensing measurements and model simulations. The diffrence in the migration coefficients between both reaches depends on the diffrence in bank height rather than the geotechnical properties of floodplain sediments. Possible eroded floodplain areas and accreted floodplain
Over-sampling basis expansion model aided channel estimation for OFDM systems with ICI
Institute of Scientific and Technical Information of China (English)
无
2008-01-01
The rapid variation of channel can induce the intercarrier interference in orthogonal frequency-division multiplexing (OFDM) systems. Intercarrier interference will significantly increase the difficulty of OFDM channel estimation because too many channel coefficients need be estimated. In this article, a novel channel estimator is proposed to resolve the above problem. This estimator consists of two parts: the channel parameter estimation unit (CPEU), which is used to estimate the number of channel taps and the multipath time delays, and the channel coefficient estimation unit (CCEU), which is used to estimate the channel coefficients by using the estimated channel parameters provided by CPEU. In CCEU, the over-sampling basis expansion model is resorted to solve the problem that a large number of channel coefficients need to be estimated. Finally, simulation results are given to scale the performance of the proposed scheme.
Langousis, Andreas; Mamalakis, Antonios; Deidda, Roberto; Marrocu, Marino
2016-01-01
To improve the level skill of climate models (CMs) in reproducing the statistics of daily rainfall at a basin level, two types of statistical approaches have been suggested. One is statistical correction of CM rainfall outputs based on historical series of precipitation. The other, usually referred to as statistical rainfall downscaling, is the use of stochastic models to conditionally simulate rainfall series, based on large-scale atmospheric forcing from CMs. While promising, the latter approach attracted reduced attention in recent years, since the developed downscaling schemes involved complex weather identification procedures, while demonstrating limited success in reproducing several statistical features of rainfall. In a recent effort, Langousis and Kaleris () developed a statistical framework for simulation of daily rainfall intensities conditional on upper-air variables, which is simpler to implement and more accurately reproduces several statistical properties of actual rainfall records. Here we study the relative performance of: (a) direct statistical correction of CM rainfall outputs using nonparametric distribution mapping, and (b) the statistical downscaling scheme of Langousis and Kaleris (), in reproducing the historical rainfall statistics, including rainfall extremes, at a regional level. This is done for an intermediate-sized catchment in Italy, i.e., the Flumendosa catchment, using rainfall and atmospheric data from four CMs of the ENSEMBLES project. The obtained results are promising, since the proposed downscaling scheme is more accurate and robust in reproducing a number of historical rainfall statistics, independent of the CM used and the characteristics of the calibration period. This is particularly the case for yearly rainfall maxima.
Emerging Trends and Statistical Analysis in Computational Modeling in Agriculture
Directory of Open Access Journals (Sweden)
Sunil Kumar
2015-03-01
Full Text Available In this paper the authors have tried to describe emerging trend in computational modelling used in the sphere of agriculture. Agricultural computational modelling with the use of intelligence techniques for computing the agricultural output by providing minimum input data to lessen the time through cutting down the multi locational field trials and also the labours and other inputs is getting momentum. Development of locally suitable integrated farming systems (IFS is the utmost need of the day, particularly in India where about 95% farms are under small and marginal holding size. Optimization of the size and number of the various enterprises to the desired IFS model for a particular set of agro-climate is essential components of the research to sustain the agricultural productivity for not only filling the stomach of the bourgeoning population of the country, but also to enhance the nutritional security and farms return for quality life. Review of literature pertaining to emerging trends in computational modelling applied in field of agriculture is done and described below for the purpose of understanding its trends mechanism behavior and its applications. Computational modelling is increasingly effective for designing and analysis of the system. Computa-tional modelling is an important tool to analyses the effect of different scenarios of climate and management options on the farming systems and its interaction among themselves. Further, authors have also highlighted the applications of computational modeling in integrated farming system, crops, weather, soil, climate, horticulture and statistical used in agriculture which can show the path to the agriculture researcher and rural farming community to replace some of the traditional techniques.
A Statistical Model for Regional Tornado Climate Studies.
Directory of Open Access Journals (Sweden)
Thomas H Jagger
Full Text Available Tornado reports are locally rare, often clustered, and of variable quality making it difficult to use them directly to describe regional tornado climatology. Here a statistical model is demonstrated that overcomes some of these difficulties and produces a smoothed regional-scale climatology of tornado occurrences. The model is applied to data aggregated at the level of counties. These data include annual population, annual tornado counts and an index of terrain roughness. The model has a term to capture the smoothed frequency relative to the state average. The model is used to examine whether terrain roughness is related to tornado frequency and whether there are differences in tornado activity by County Warning Area (CWA. A key finding is that tornado reports increase by 13% for a two-fold increase in population across Kansas after accounting for improvements in rating procedures. Independent of this relationship, tornadoes have been increasing at an annual rate of 1.9%. Another finding is the pattern of correlated residuals showing more Kansas tornadoes in a corridor of counties running roughly north to south across the west central part of the state consistent with the dryline climatology. The model is significantly improved by adding terrain roughness. The effect amounts to an 18% reduction in the number of tornadoes for every ten meter increase in elevation standard deviation. The model indicates that tornadoes are 51% more likely to occur in counties served by the CWAs of DDC and GID than elsewhere in the state. Flexibility of the model is illustrated by fitting it to data from Illinois, Mississippi, South Dakota, and Ohio.
A Generalized Statistical Uncertainty Model for Satellite Precipitation Products
Sarachi, S.
2013-12-01
A mixture model of Generalized Normal Distribution and Gamma distribution (GND-G) is used to model the joint probability distribution of satellite-based and stage IV radar rainfall under a given spatial and temporal resolution (e.g. 1°x1° and daily rainfall). The distribution parameters of GND-G are extended across various rainfall rates and spatial and temporal resolutions. In the study, GND-G is used to describe the uncertainty of the estimates from Precipitation Estimation from Remote Sensing Information using Artificial Neural Network algorithm (PERSIANN). The stage IV-based multi-sensor precipitation estimates (MPE) are used as reference measurements .The study area for constructing the uncertainty model covers a 15°×15°box of 0.25°×0.25° cells over the eastern United States for summer 2004 to 2009. Cells are aggregated in space and time to obtain data with different resolutions for the construction of the model's parameter space. Result shows that comparing to the other statistical uncertainty models, GND-G fits better than the other models, such as Gaussian and Gamma distributions, to the reference precipitation data. The impact of precipitation uncertainty to the stream flow is further demonstrated by Monte Carlo simulation of precipitation forcing in the hydrologic model. The NWS DMIP2 basins over Illinois River basin south of Siloam is selected in this case study. The data covers the time period of 2006 to 2008.The uncertainty range of stream flow from precipitation of GND-G distributions calculated and will be discussed.
Linear mixed models a practical guide using statistical software
West, Brady T; Galecki, Andrzej T
2014-01-01
Highly recommended by JASA, Technometrics, and other journals, the first edition of this bestseller showed how to easily perform complex linear mixed model (LMM) analyses via a variety of software programs. Linear Mixed Models: A Practical Guide Using Statistical Software, Second Edition continues to lead readers step by step through the process of fitting LMMs. This second edition covers additional topics on the application of LMMs that are valuable for data analysts in all fields. It also updates the case studies using the latest versions of the software procedures and provides up-to-date information on the options and features of the software procedures available for fitting LMMs in SAS, SPSS, Stata, R/S-plus, and HLM.New to the Second Edition A new chapter on models with crossed random effects that uses a case study to illustrate software procedures capable of fitting these models Power analysis methods for longitudinal and clustered study designs, including software options for power analyses and suggest...
Energy Level Statistics in Particle-Rotor Model
Institute of Scientific and Technical Information of China (English)
ZHOU Xian-Rong; GUO Lu; MENG Jie; ZHAO En-Guang
2002-01-01
Energy level statistics of a system consisting of six particles interacting by delta force in a two-j modelcoupled with a deformed core is studied in particle-rotor model. For single-j shell (i13/2) and two-j shell (g7/2 + d5/2)the exact energies for our statistical analysis are obtained from a full diagonalization of the Hamiltonian, while in two-jcase (i13/2 + g9/2) the configuration truncation is used. The nearest-neighbor distribution of energy levels and spectralrigidity are studied as the function of spin. The results of single-j shell are compared with those in two-j case. It isshowed that the system becomes more regular when single-j space (i13/2) is replaced by two-j shell (g7/2 +d5/2) althoughthe basis size of the configuration space is unchanged. The degree of chaoticity of the system, however, changes slightlywhen configuration space is enlarged by extending single-j shell (i13/2) to two-j shell (i13/2 + g9/2).
Channel selection in e-commerce age: a strategic analysis of co-op advertising models
Yongmei Liu; Yuhua Sun; Junhua Hu
2013-01-01
Purpose: The purpose of this paper is to develop and compare two co-op advertising models: advertising model under traditional channel and co-op advertising model under dual channel, to select optimal channel structure to sell products for manufacturer and to derive optimal co-op advertising strategies for the manufacturer and the retailer.Design/methodology/approach: Stackelberg game theoretical is used to develop two co-op advertising models: co-op advertising model under traditional channe...
STATISTICAL MECHANICS MODELING OF MESOSCALE DEFORMATION IN METALS
Energy Technology Data Exchange (ETDEWEB)
Anter El-Azab
2013-04-08
The research under this project focused on a theoretical and computational modeling of dislocation dynamics of mesoscale deformation of metal single crystals. Specifically, the work aimed to implement a continuum statistical theory of dislocations to understand strain hardening and cell structure formation under monotonic loading. These aspects of crystal deformation are manifestations of the evolution of the underlying dislocation system under mechanical loading. The project had three research tasks: 1) Investigating the statistical characteristics of dislocation systems in deformed crystals. 2) Formulating kinetic equations of dislocations and coupling these kinetics equations and crystal mechanics. 3) Computational solution of coupled crystal mechanics and dislocation kinetics. Comparison of dislocation dynamics predictions with experimental results in the area of statistical properties of dislocations and their field was also a part of the proposed effort. In the first research task, the dislocation dynamics simulation method was used to investigate the spatial, orientation, velocity, and temporal statistics of dynamical dislocation systems, and on the use of the results from this investigation to complete the kinetic description of dislocations. The second task focused on completing the formulation of a kinetic theory of dislocations that respects the discrete nature of crystallographic slip and the physics of dislocation motion and dislocation interaction in the crystal. Part of this effort also targeted the theoretical basis for establishing the connection between discrete and continuum representation of dislocations and the analysis of discrete dislocation simulation results within the continuum framework. This part of the research enables the enrichment of the kinetic description with information representing the discrete dislocation systems behavior. The third task focused on the development of physics-inspired numerical methods of solution of the coupled
Modeling of optical wireless scattering communication channels over broad spectra.
Liu, Weihao; Zou, Difan; Xu, Zhengyuan
2015-03-01
The air molecules and suspended aerosols help to build non-line-of-sight (NLOS) optical scattering communication links using carriers from near infrared to visible light and ultraviolet bands. This paper proposes channel models over such broad spectra. Wavelength dependent Rayleigh and Mie scattering and absorption coefficients of particles are analytically obtained first. They are applied to the ray tracing based Monte Carlo method, which models the photon scattering angle from the scatterer and propagation distance between two consecutive scatterers. Communication link path loss is studied under different operation conditions, including visibility, particle density, wavelength, and communication range. It is observed that optimum communication performances exist across the wavelength under specific atmospheric conditions. Infrared, visible light and ultraviolet bands show their respective features as conditions vary. PMID:26366662
Channel Measurement and Modeling for 5G Urban Microcellular Scenarios
Directory of Open Access Journals (Sweden)
Michael Peter
2016-08-01
Full Text Available In order to support the development of channel models for higher frequency bands, multiple urban microcellular measurement campaigns have been carried out in Berlin, Germany, at 60 and 10 GHz. In this paper, the collected data is uniformly analyzed with focus on the path loss (PL and the delay spread (DS. It reveals that the ground reflection has a dominant impact on the fading behavior. For line-of-sight conditions, the PL exponents are close to free space propagation at 60 GHz, but slightly smaller (1.62 for the street canyon at 10 GHz. The DS shows a clear dependence on the scenario (median values between 16 and 38 ns and a strong distance dependence for the open square and the wide street canyon. The dependence is less distinct for the narrow street canyon with residential buildings. This behavior is consistent with complementary ray tracing simulations, though the simplified model tends to overestimate the DS.
Fermionic Dark Matter in a simple $t$-channel model
Goyal, Ashok
2016-01-01
We consider a fermionic dark matter (DM) particle in renormalizable Standard Model (SM) gauge interactions in a simple $t$-channel model. The DM particle interactions with SM fermions is through the exchange of scalar and vector mediators which carry colour or lepton number. In the case of coloured mediators considered in this study, we find that if the DM is thermally produced and accounts for the observed relic density almost the entire parameter space is ruled out by the direct detection observations. The bounds from the monojet plus missing energy searches at the Large Hadron Collider are less stringent in this case. In contrast for the case of Majorana DM, we obtain strong bounds from the monojet searches which rule out DM particles of mass less than about a few hundred GeV for both the scalar and vector mediators.
Channel Measurement and Modeling for 5G Urban Microcellular Scenarios.
Peter, Michael; Weiler, Richard J; Göktepe, Barış; Keusgen, Wilhelm; Sakaguchi, Kei
2016-01-01
In order to support the development of channel models for higher frequency bands, multiple urban microcellular measurement campaigns have been carried out in Berlin, Germany, at 60 and 10 GHz. In this paper, the collected data is uniformly analyzed with focus on the path loss (PL) and the delay spread (DS). It reveals that the ground reflection has a dominant impact on the fading behavior. For line-of-sight conditions, the PL exponents are close to free space propagation at 60 GHz, but slightly smaller (1.62) for the street canyon at 10 GHz. The DS shows a clear dependence on the scenario (median values between 16 and 38 ns) and a strong distance dependence for the open square and the wide street canyon. The dependence is less distinct for the narrow street canyon with residential buildings. This behavior is consistent with complementary ray tracing simulations, though the simplified model tends to overestimate the DS. PMID:27556462
DEFF Research Database (Denmark)
Pedersen, Morten Gram; Cortese, Giuliana; Eliasson, Lena
2011-01-01
on depolarization-evoked Ca2+-currents and corresponding capacitance measurements. Using a statistical mixed-effects model, we show that the data indicate that pool depletion is negligible in response to short depolarizations in mouse ß-cells. We then review mathematical models of granule dynamics and exocytosis...... in rodent ß-cells and present a mathematical description of Ca2+-evoked exocytosis in human ß-cells, which show clear differences to their rodent counterparts. The model suggests that L- and P/Q-type Ca2+-channels are involved to a similar degree in exocytosis during electrical activity in human ß-cells....
MIMO capacity for deterministic channel models: sublinear growth
DEFF Research Database (Denmark)
Bentosela, Francois; Cornean, Horia; Marchetti, Nicola
2013-01-01
This is the second paper by the authors in a series concerned with the development of a deterministic model for the transfer matrix of a MIMO system. In our previous paper, we started from the Maxwell equations and described the generic structure of such a deterministic transfer matrix...... some generic assumptions, we prove that the capacity grows much more slowly than linearly with the number of antennas. These results reinforce previous heuristic results obtained from statistical models of the transfer matrix, which also predict a sublinear behavior....
A statistical downscaling model for summer rainfall over Pakistan
Kazmi, Dildar Hussain; Li, Jianping; Ruan, Chengqing; Zhao, Sen; Li, Yanjie
2016-10-01
A statistical approach is utilized to construct an interannual model for summer (July-August) rainfall over the western parts of South Asian Monsoon. Observed monthly rainfall data for selected stations of Pakistan for the last 55 years (1960-2014) is taken as predictand. Recommended climate indices along with the oceanic and atmospheric data on global scales, for the period April-June are employed as predictors. First 40 years data has been taken as training period and the rest as validation period. Cross-validation stepwise regression approach adopted to select the robust predictors. Upper tropospheric zonal wind at 200 hPa over the northeastern Atlantic is finally selected as the best predictor for interannual model. Besides, the next possible candidate `geopotential height at upper troposphere' is taken as the indirect predictor for being a source of energy transportation from core region (northeast Atlantic/western Europe) to the study area. The model performed well for both the training as well as validation period with correlation coefficient of 0.71 and tolerable root mean square errors. Cross-validation of the model has been processed by incorporating JRA-55 data for potential predictors in addition to NCEP and fragmentation of study period to five non-overlapping test samples. Subsequently, to verify the outcome of the model on physical grounds, observational analyses as well as the model simulations are incorporated. It is revealed that originating from the jet exit region through large vorticity gradients, zonally dominating waves may transport energy and momentum to the downstream areas of west-central Asia, that ultimately affect interannual variability of the specific rainfall. It has been detected that both the circumglobal teleconnection and Rossby wave propagation play vital roles in modulating the proposed mechanism.
A statistical downscaling model for summer rainfall over Pakistan
Kazmi, Dildar Hussain; Li, Jianping; Ruan, Chengqing; Sen, Zhao; Li, Yanjie
2016-02-01
A statistical approach is utilized to construct an interannual model for summer (July-August) rainfall over the western parts of South Asian Monsoon. Observed monthly rainfall data for selected stations of Pakistan for the last 55 years (1960-2014) is taken as predictand. Recommended climate indices along with the oceanic and atmospheric data on global scales, for the period April-June are employed as predictors. First 40 years data has been taken as training period and the rest as validation period. Cross-validation stepwise regression approach adopted to select the robust predictors. Upper tropospheric zonal wind at 200 hPa over the northeastern Atlantic is finally selected as the best predictor for interannual model. Besides, the next possible candidate `geopotential height at upper troposphere' is taken as the indirect predictor for being a source of energy transportation from core region (northeast Atlantic/western Europe) to the study area. The model performed well for both the training as well as validation period with correlation coefficient of 0.71 and tolerable root mean square errors. Cross-validation of the model has been processed by incorporating JRA-55 data for potential predictors in addition to NCEP and fragmentation of study period to five non-overlapping test samples. Subsequently, to verify the outcome of the model on physical grounds, observational analyses as well as the model simulations are incorporated. It is revealed that originating from the jet exit region through large vorticity gradients, zonally dominating waves may transport energy and momentum to the downstream areas of west-central Asia, that ultimately affect interannual variability of the specific rainfall. It has been detected that both the circumglobal teleconnection and Rossby wave propagation play vital roles in modulating the proposed mechanism.
A Parallel Markov Cerebrovascular Segmentation Algorithm Based on Statistical Model
Institute of Scientific and Technical Information of China (English)
Rong-Fei Cao; Xing-Ce Wang; Zhong-Ke Wu; Ming-Quan Zhou; Xin-Yu Liu
2016-01-01
For segmenting cerebral blood vessels from the time-of-flight magnetic resonance angiography (TOF-MRA) images accurately, we propose a parallel segmentation algorithm based on statistical model with Markov random field (MRF). Firstly, we improve traditional non-local means filter with patch-based Fourier transformation to preprocess the TOF-MRA images. In this step, we mainly utilize the sparseness and self-similarity of the MRA brain images sequence. Secondly, we add the MRF information to the finite mixture mode (FMM) to fit the intensity distribution of medical images. We make use of the MRF in image sequence to estimate the proportion of cerebral tissues. Finally, we choose the particle swarm optimization (PSO) algorithm to parallelize the parameter estimation of FMM. A large number of experiments verify the high accuracy and robustness of our approach especially for narrow vessels. The work will offer significant assistance for physicians on the prevention and diagnosis of cerebrovascular diseases.
Vibroacoustic optimization using a statistical energy analysis model
Culla, Antonio; D`Ambrogio, Walter; Fregolent, Annalisa; Milana, Silvia
2016-08-01
In this paper, an optimization technique for medium-high frequency dynamic problems based on Statistical Energy Analysis (SEA) method is presented. Using a SEA model, the subsystem energies are controlled by internal loss factors (ILF) and coupling loss factors (CLF), which in turn depend on the physical parameters of the subsystems. A preliminary sensitivity analysis of subsystem energy to CLF's is performed to select CLF's that are most effective on subsystem energies. Since the injected power depends not only on the external loads but on the physical parameters of the subsystems as well, it must be taken into account under certain conditions. This is accomplished in the optimization procedure, where approximate relationships between CLF's, injected power and physical parameters are derived. The approach is applied on a typical aeronautical structure: the cabin of a helicopter.
Velocity statistics of the Nagel-Schreckenberg model
Bain, Nicolas; Emig, Thorsten; Ulm, Franz-Josef; Schreckenberg, Michael
2016-02-01
The statistics of velocities in the cellular automaton model of Nagel and Schreckenberg for traffic are studied. From numerical simulations, we obtain the probability distribution function (PDF) for vehicle velocities and the velocity-velocity (vv) covariance function. We identify the probability to find a standing vehicle as a potential order parameter that signals nicely the transition between free congested flow for a sufficiently large number of velocity states. Our results for the vv covariance function resemble features of a second-order phase transition. We develop a 3-body approximation that allows us to relate the PDFs for velocities and headways. Using this relation, an approximation to the velocity PDF is obtained from the headway PDF observed in simulations. We find a remarkable agreement between this approximation and the velocity PDF obtained from simulations.
Statistical model on the surface elevation of waves with breaking
Institute of Scientific and Technical Information of China (English)
2008-01-01
In the surface wind drift layer with constant momentum flux, two sets of the consistent surface eleva- tion expressions with breaking and occurrence conditions for breaking are deduced from the first in- tegrals of the energy and vortex variations and the kinetic and mathematic breaking criterions, then the expression of the surface elevation with wave breaking is established by using the Heaviside function. On the basis of the form of the sea surface elevation with wave breaking and the understanding of small slope sea waves, a triple composite function of real sea waves is presented including the func- tions for the breaking, weak-nonlinear and basic waves. The expression of the triple composite func- tion and the normal distribution of basic waves are the expected theoretical model for surface elevation statistics.
A context dependent pair hidden Markov model for statistical alignment
Arribas-Gil, Ana
2011-01-01
This article proposes a novel approach to statistical alignment of nucleotide sequences by introducing a context dependent structure on the substitution process in the underlying evolutionary model. We propose to estimate alignments and context dependent mutation rates relying on the observation of two homologous sequences. The procedure is based on a generalized pair-hidden Markov structure, where conditional on the alignment path, the nucleotide sequences follow a Markov distribution. We use a stochastic approximation expectation maximization (saem) algorithm to give accurate estimators of parameters and alignments. We provide results both on simulated data and vertebrate genomes, which are known to have a high mutation rate from CG dinucleotide. In particular, we establish that the method improves the accuracy of the alignment of a human pseudogene and its functional gene.
A reciprocating twin-channel model for ABC transporters.
Jones, Peter M; George, Anthony M
2014-08-01
ABC transporters comprise a large, diverse, and ubiquitous superfamily of membrane active transporters. Their core architecture is a dimer of dimers, comprising two transmembrane (TM) domains that bind substrate, and two ATP-binding cassettes, which use the cell's energy currency to couple substrate translocation to ATP hydrolysis. Despite the availability of over a dozen resolved structures and a wealth of biochemical and biophysical data, this field is bedeviled by controversy and long-standing mechanistic questions remain unresolved. The prevailing paradigm for the ABC transport mechanism is the Switch Model, in which the ATP-binding cassettes dimerize upon binding two ATP molecules, and thence dissociate upon sequential ATP hydrolysis. This cycle of nucleotide-binding domain (NBD) dimerization and dissociation is coupled to a switch between inward- or outward facing conformations of a single TM channel; this alternating access enables substrate binding on one face of the membrane and its release at the other. Notwithstanding widespread acceptance of the Switch Model, there is substantial evidence that the NBDs do not separate very much, if at all, and thus physical separation of the ATP cassettes observed in crystallographic structures may be an artefact. An alternative Constant Contact Model has been proposed, in which ATP hydrolysis occurs alternately at the two ATP-binding sites, with one of the sites remaining closed and containing occluded nucleotide at all times. In this model, the cassettes remain in contact and the active sites swing open in an alternately seesawing motion. Whilst the concept of NBD association/dissociation in the Switch Model is naturally compatible with a single alternating-access channel, the asymmetric functioning proposed by the Constant Contact model suggests an alternating or reciprocating function in the TMDs. Here, a new model for the function of ABC transporters is proposed in which the sequence of ATP binding, hydrolysis, and
The issue of statistical power for overall model fit in evaluating structural equation models
Directory of Open Access Journals (Sweden)
Richard HERMIDA
2015-06-01
Full Text Available Statistical power is an important concept for psychological research. However, examining the power of a structural equation model (SEM is rare in practice. This article provides an accessible review of the concept of statistical power for the Root Mean Square Error of Approximation (RMSEA index of overall model fit in structural equation modeling. By way of example, we examine the current state of power in the literature by reviewing studies in top Industrial-Organizational (I/O Psychology journals using SEMs. Results indicate that in many studies, power is very low, which implies acceptance of invalid models. Additionally, we examined methodological situations which may have an influence on statistical power of SEMs. Results showed that power varies significantly as a function of model type and whether or not the model is the main model for the study. Finally, results indicated that power is significantly related to model fit statistics used in evaluating SEMs. The results from this quantitative review imply that researchers should be more vigilant with respect to power in structural equation modeling. We therefore conclude by offering methodological best practices to increase confidence in the interpretation of structural equation modeling results with respect to statistical power issues.
The statistical multifragmentation model: Origins and recent advances
Donangelo, R.; Souza, S. R.
2016-07-01
We review the Statistical Multifragmentation Model (SMM) which considers a generalization of the liquid-drop model for hot nuclei and allows one to calculate thermodynamic quantities characterizing the nuclear ensemble at the disassembly stage. We show how to determine probabilities of definite partitions of finite nuclei and how to determine, through Monte Carlo calculations, observables such as the caloric curve, multiplicity distributions, heat capacity, among others. Some experimental measurements of the caloric curve confirmed the SMM predictions of over 10 years before, leading to a surge in the interest in the model. However, the experimental determination of the fragmentation temperatures relies on the yields of different isotopic species, which were not correctly calculated in the schematic, liquid-drop picture, employed in the SMM. This led to a series of improvements in the SMM, in particular to the more careful choice of nuclear masses and energy densities, specially for the lighter nuclei. With these improvements the SMM is able to make quantitative determinations of isotope production. We show the application of SMM to the production of exotic nuclei through multifragmentation. These preliminary calculations demonstrate the need for a careful choice of the system size and excitation energy to attain maximum yields.
The Role of Atmospheric Measurements in Wind Power Statistical Models
Wharton, S.; Bulaevskaya, V.; Irons, Z.; Newman, J. F.; Clifton, A.
2015-12-01
The simplest wind power generation curves model power only as a function of the wind speed at turbine hub-height. While the latter is an essential predictor of power output, it is widely accepted that wind speed information in other parts of the vertical profile, as well as additional atmospheric variables including atmospheric stability, wind veer, and hub-height turbulence are also important factors. The goal of this work is to determine the gain in predictive ability afforded by adding additional atmospheric measurements to the power prediction model. In particular, we are interested in quantifying any gain in predictive ability afforded by measurements taken from a laser detection and ranging (lidar) instrument, as lidar provides high spatial and temporal resolution measurements of wind speed and direction at 10 or more levels throughout the rotor-disk and at heights well above. Co-located lidar and meteorological tower data as well as SCADA power data from a wind farm in Northern Oklahoma will be used to train a set of statistical models. In practice, most wind farms continue to rely on atmospheric measurements taken from less expensive, in situ instruments mounted on meteorological towers to assess turbine power response to a changing atmospheric environment. Here, we compare a large suite of atmospheric variables derived from tower measurements to those taken from lidar to determine if remote sensing devices add any competitive advantage over tower measurements alone to predict turbine power response.
Critical, statistical, and thermodynamical properties of lattice models
Energy Technology Data Exchange (ETDEWEB)
Varma, Vipin Kerala
2013-10-15
In this thesis we investigate zero temperature and low temperature properties - critical, statistical and thermodynamical - of lattice models in the contexts of bosonic cold atom systems, magnetic materials, and non-interacting particles on various lattice geometries. We study quantum phase transitions in the Bose-Hubbard model with higher body interactions, as relevant for optical lattice experiments of strongly interacting bosons, in one and two dimensions; the universality of the Mott insulator to superfluid transition is found to remain unchanged for even large three body interaction strengths. A systematic renormalization procedure is formulated to fully re-sum these higher (three and four) body interactions into the two body terms. In the strongly repulsive limit, we analyse the zero and low temperature physics of interacting hard-core bosons on the kagome lattice at various fillings. Evidence for a disordered phase in the Ising limit of the model is presented; in the strong coupling limit, the transition between the valence bond solid and the superfluid is argued to be first order at the tip of the solid lobe.
Multivariate Statistical Modelling of Drought and Heat Wave Events
Manning, Colin; Widmann, Martin; Vrac, Mathieu; Maraun, Douglas; Bevaqua, Emanuele
2016-04-01
Multivariate Statistical Modelling of Drought and Heat Wave Events C. Manning1,2, M. Widmann1, M. Vrac2, D. Maraun3, E. Bevaqua2,3 1. School of Geography, Earth and Environmental Sciences, University of Birmingham, Edgbaston, Birmingham, UK 2. Laboratoire des Sciences du Climat et de l'Environnement, (LSCE-IPSL), Centre d'Etudes de Saclay, Gif-sur-Yvette, France 3. Wegener Center for Climate and Global Change, University of Graz, Brandhofgasse 5, 8010 Graz, Austria Compound extreme events are a combination of two or more contributing events which in themselves may not be extreme but through their joint occurrence produce an extreme impact. Compound events are noted in the latest IPCC report as an important type of extreme event that have been given little attention so far. As part of the CE:LLO project (Compound Events: muLtivariate statisticaL mOdelling) we are developing a multivariate statistical model to gain an understanding of the dependence structure of certain compound events. One focus of this project is on the interaction between drought and heat wave events. Soil moisture has both a local and non-local effect on the occurrence of heat waves where it strongly controls the latent heat flux affecting the transfer of sensible heat to the atmosphere. These processes can create a feedback whereby a heat wave maybe amplified or suppressed by the soil moisture preconditioning, and vice versa, the heat wave may in turn have an effect on soil conditions. An aim of this project is to capture this dependence in order to correctly describe the joint probabilities of these conditions and the resulting probability of their compound impact. We will show an application of Pair Copula Constructions (PCCs) to study the aforementioned compound event. PCCs allow in theory for the formulation of multivariate dependence structures in any dimension where the PCC is a decomposition of a multivariate distribution into a product of bivariate components modelled using copulas. A
MoCha, a model for distributed mobile channels
Guillen Scholten, Juan
2004-01-01
A mobile channel is a link that provides an asynchronous and anonymous means of communication between components in a distributed system. A channel is called mobile if either of its (channel-)ends can be moved from one component to another without the knowledge of the component at its other end. Such mobility allows dynamic reconfiguration of channel connections among the components in a system, a property that is very useful and even crucial in systems where the components themselves are mob...
Modelling customer behaviour in multi-channel service distribution
D. Heinhuis; E.J. de Vries
2008-01-01
Financial service providers are innovating their distribution strategy into multi-channel strategies. The success of a multi-channel approach and the high investments made in information systems and enterprise architectures depends on the adoption and multi-channel usage behaviour of consumers. We b
Feature and Statistical Model Development in Structural Health Monitoring
Kim, Inho
All structures suffer wear and tear because of impact, excessive load, fatigue, corrosion, etc. in addition to inherent defects during their manufacturing processes and their exposure to various environmental effects. These structural degradations are often imperceptible, but they can severely affect the structural performance of a component, thereby severely decreasing its service life. Although previous studies of Structural Health Monitoring (SHM) have revealed extensive prior knowledge on the parts of SHM processes, such as the operational evaluation, data processing, and feature extraction, few studies have been conducted from a systematical perspective, the statistical model development. The first part of this dissertation, the characteristics of inverse scattering problems, such as ill-posedness and nonlinearity, reviews ultrasonic guided wave-based structural health monitoring problems. The distinctive features and the selection of the domain analysis are investigated by analytically searching the conditions of the uniqueness solutions for ill-posedness and are validated experimentally. Based on the distinctive features, a novel wave packet tracing (WPT) method for damage localization and size quantification is presented. This method involves creating time-space representations of the guided Lamb waves (GLWs), collected at a series of locations, with a spatially dense distribution along paths at pre-selected angles with respect to the direction, normal to the direction of wave propagation. The fringe patterns due to wave dispersion, which depends on the phase velocity, are selected as the primary features that carry information, regarding the wave propagation and scattering. The following part of this dissertation presents a novel damage-localization framework, using a fully automated process. In order to construct the statistical model for autonomous damage localization deep-learning techniques, such as restricted Boltzmann machine and deep belief network
Analytical models of calcium binding in a calcium channel
International Nuclear Information System (INIS)
The anomalous mole fraction effect of L-type calcium channels is analyzed using a Fermi like distribution with the experimental data of Almers and McCleskey [J. Physiol. 353, 585 (1984)] and the atomic resolution model of Lipkind and Fozzard [Biochemistry 40, 6786 (2001)] of the selectivity filter of the channel. Much of the analysis is algebraic, independent of differential equations. The Fermi distribution is derived from the configuration entropy of ions and water molecules with different sizes, different valences, and interstitial voids between particles. It allows us to calculate potentials and distances (between the binding ion and the oxygen ions of the glutamate side chains) directly from the experimental data using algebraic formulas. The spatial resolution of these results is comparable with those of molecular models, but of course the accuracy is no better than that implied by the experimental data. The glutamate side chains in our model are flexible enough to accommodate different types of binding ions in different bath conditions. The binding curves of Na+ and Ca2+ for [CaCl2] ranging from 10−8 to 10−2 M with a fixed 32 mM background [NaCl] are shown to agree with published Monte Carlo simulations. The Poisson-Fermi differential equation—that includes both steric and correlation effects—is then used to obtain the spatial profiles of energy, concentration, and dielectric coefficient from the solvent region to the filter. The energy profiles of ions are shown to depend sensitively on the steric energy that is not taken into account in the classical rate theory. We improve the rate theory by introducing a steric energy that lumps the effects of excluded volumes of all ions and water molecules and empty spaces between particles created by Lennard-Jones type and electrostatic forces. We show that the energy landscape varies significantly with bath concentrations. The energy landscape is not constant
Institute of Scientific and Technical Information of China (English)
Nguyen ThanhSon; Guo Shuxu; Chen Haipeng
2013-01-01
Multipath arrivals in an Ultra-WideBand (UWB) channel have a long time intervals between clusters and rays where the signal takes on zero or negligible values.It is precisely the signal sparsity of the impulse response of the UWB channel that is exploited in this work aiming at UWB channel estimation based on Compressed Sensing (CS).However,these multipath arrivals mainly depend on the channel environments that generate different sparse levels (low-sparse or high-sparse) of the UWB channels.According to this basis,we have analyzed the two most basic recovery algorithms,one based on linear programming Basis Pursuit (BP),another using greedy method Orthogonal Matching Pursuit (OMP),and chosen the best recovery algorithm which are suitable to the sparse level for each type of channel environment.Besides,the results of this work is an open topic for further research aimed at creating a optimal algorithm specially for application of CS based UWB systems.
Patch-Based Generative Shape Model and MDL Model Selection for Statistical Analysis of Archipelagos
DEFF Research Database (Denmark)
Ganz, Melanie; Nielsen, Mads; Brandt, Sami
2010-01-01
We propose a statistical generative shape model for archipelago-like structures. These kind of structures occur, for instance, in medical images, where our intention is to model the appearance and shapes of calcifications in x-ray radio graphs. The generative model is constructed by (1) learning...... a patch-based dictionary for possible shapes, (2) building up a time-homogeneous Markov model to model the neighbourhood correlations between the patches, and (3) automatic selection of the model complexity by the minimum description length principle. The generative shape model is proposed...... as a probability distribution of a binary image where the model is intended to facilitate sequential simulation. Our results show that a relatively simple model is able to generate structures visually similar to calcifications. Furthermore, we used the shape model as a shape prior in the statistical segmentation...