Discovering Ecosystem Models from Time-Series Data
Langley, Pat
Discovering Ecosystem Models from Time-Series Data Dileep George, 1 Kazumi Saito, 2 Pat Langley, 1. Ecosystem models are used to interpret and predict the in- teractions of species and their environment. In this paper, we address the task of inducing ecosystem models from background knowledge and time- series data
Modeling Time Series of Real Systems using Genetic Programming
Dilip P. Ahalpara; Jitendra C. Parikh
2006-07-14T23:59:59.000Z
Analytic models of two computer generated time series (Logistic map and Rossler system) and two real time series (ion saturation current in Aditya Tokamak plasma and NASDAQ composite index) are constructed using Genetic Programming (GP) framework. In each case, the optimal map that results from fitting part of the data set also provides a very good description of rest of the data. Predictions made using the map iteratively range from being very good to fair.
Functional Coefficient Regression Models for Non-linear Time Series: A Polynomial
Shen, Haipeng
Functional Coefficient Regression Models for Non-linear Time Series: A Polynomial Spline Approach of functional coefficient regression models for non-linear time series. Consistency and rate of convergence regression model extends several familiar non-linear time series models such as the exponential
Time series modeling of autonomous hybrid power systems
Quinlan, P.J.; Beckman, W.A.; Mitchell, J.W.; Klein, S.A.; Blair, N.J. [Univ. of Wisconsin, Madison, WI (United States). Solar Energy Lab.
1997-12-31T23:59:59.000Z
The Solar Energy Laboratory (SEL) has developed a wind diesel PV hybrid systems simulator, UW-HYBRID 1.0, as an application of the TRNSYS 14.2 time-series simulation environment. The simulator provides a customizable user interface. The simulation provides an AC/DC buss, diesel generators, wind turbines, PV modules, a battery bank, and power converter. PV system simulations include solar angle and peak power tracking options. Diesel simulations include estimated fuel-use and waste heat output, and are dispatched using a least-cost of fuel strategy. Wind system simulations include varying air density, wind shear and wake effects. Time step duration is user-selectable. This paper provides a description of the simulation models and example output.
Two problems with variational expectation maximisation for time-series models
Ghahramani, Zoubin
optimisation of a free-energy, are widely used in time-series modelling. Here, we investigate the success of v as a variational optimisation of a free-energy (Hathaway, 1986; Neal and Hinton, 1998). Consider observationsChapter 1 Two problems with variational expectation maximisation for time-series models Richard
Discrimination and Classification of Nonstationary Time Series Using the SLEX Model
Discrimination and Classification of Nonstationary Time Series Using the SLEX Model Hsiao-Yun HUANG a discriminant scheme based on the SLEX (smooth localized complex exponential) library. The SLEX library forms domains. Thus, the SLEX library has the ability to extract local spectral features of the time series
Discrimination and Classification of Nonstationary Time Series using the SLEX Model
Discrimination and Classification of Nonstationary Time Series using the SLEX Model Hsiao-Yun Huang scheme based on the SLEX (Smooth Localized Complex EXponential) library. The SLEX library forms domains. Thus, the SLEX library has the ability to extract local spectral features of the time series
Modeling Gene Regulatory Networks from Time Series Data using Particle Filtering
Noor, Amina
2012-10-19T23:59:59.000Z
This thesis considers the problem of learning the structure of gene regulatory networks using gene expression time series data. A more realistic scenario where the state space model representing a gene network evolves nonlinearly is considered while...
Essays on empirical time series modeling with causality and structural change
Kim, Jin Woong
2006-10-30T23:59:59.000Z
In this dissertation, three related issues of building empirical time series models for financial markets are investigated with respect to contemporaneous causality, dynamics, and structural change. In the first essay, ...
Modelling signal interactions with application to financial time series
Jain, Bonny
2014-01-01T23:59:59.000Z
In this thesis, we concern ourselves with the problem of reasoning over a set of objects evolving over time that are coupled through interaction structures that are themselves changing over time. We focus on inferring ...
A FAST MODEL-BUILDING METHOD FOR TIME SERIES USING GENETIC PROGRAMMING
Fernandez, Thomas
generation, initial values of the parameters in an model (offspring) are inherited from the parents. step-2 series and applied it to lots of time series: (1) computer generated chaos e.g. Logistic, Loessler is made by using a set of finite number of past values measured from the system )x,,x,(xfx~ n-t2-t1-tt
IMPROVED SEMI-PARAMETRIC TIME SERIES MODELS OF AIR POLLUTION AND MORTALITY
Dominici, Francesca
IMPROVED SEMI-PARAMETRIC TIME SERIES MODELS OF AIR POLLUTION AND MORTALITY Francesca Dominici series analyses of air pollution and health attracted the attention of the scientific community, policy makers, the press, and the diverse stakeholders con- cerned with air pollution. As the Environmental
Self-organizing Time Series Model Tomoyuki Higuchi
Higuchi, Tomoyuki
.1) observation model yt r( jxt obs) (1.2) where xt is an nx 1 vector of unobserved sate variables, and yt R) (1.6) where F G, and H are nx nx, nx nv , and ny nx matrices, respectively. Q and R enormously with respect to the state dimension nx (Carlin, Polson and Sto er 1992, Fahrmeir 1992, Fruhwirth
Aalborg Universitet ARIMA-Based Time Series Model of Stochastic Wind Power Generation
Bak-Jensen, Birgitte
power measurement of one year from the Nysted offshore wind farm in Denmark. The proposed limitedAalborg Universitet ARIMA-Based Time Series Model of Stochastic Wind Power Generation Chen, Peiyuan Model of Stochastic Wind Power Generation. IEEE Transactions on Power Systems, 25(2), 667-676. 10
Chattopadhyay, Goutami; 10.1140/epjp/i2012-12043-9
2012-01-01T23:59:59.000Z
This study reports a statistical analysis of monthly sunspot number time series and observes non homogeneity and asymmetry within it. Using Mann-Kendall test a linear trend is revealed. After identifying stationarity within the time series we generate autoregressive AR(p) and autoregressive moving average (ARMA(p,q)). Based on minimization of AIC we find 3 and 1 as the best values of p and q respectively. In the next phase, autoregressive neural network (AR-NN(3)) is generated by training a generalized feedforward neural network (GFNN). Assessing the model performances by means of Willmott's index of second order and coefficient of determination, the performance of AR-NN(3) is identified to be better than AR(3) and ARMA(3,1).
Goutami Chattopadhyay; Surajit Chattopadhyay
2012-04-18T23:59:59.000Z
This study reports a statistical analysis of monthly sunspot number time series and observes non homogeneity and asymmetry within it. Using Mann-Kendall test a linear trend is revealed. After identifying stationarity within the time series we generate autoregressive AR(p) and autoregressive moving average (ARMA(p,q)). Based on minimization of AIC we find 3 and 1 as the best values of p and q respectively. In the next phase, autoregressive neural network (AR-NN(3)) is generated by training a generalized feedforward neural network (GFNN). Assessing the model performances by means of Willmott's index of second order and coefficient of determination, the performance of AR-NN(3) is identified to be better than AR(3) and ARMA(3,1).
Denoising Deterministic Time Series
Steven P. Lalley; Andrew B. Nobel
2006-04-21T23:59:59.000Z
This paper is concerned with the problem of recovering a finite, deterministic time series from observations that are corrupted by additive, independent noise. A distinctive feature of this problem is that the available data exhibit long-range dependence and, as a consequence, existing statistical theory and methods are not readily applicable. This paper gives an analysis of the denoising problem that extends recent work of Lalley, but begins from first principles. Both positive and negative results are established. The positive results show that denoising is possible under somewhat restrictive conditions on the additive noise. The negative results show that, under more general conditions on the noise, no procedure can recover the underlying deterministic series.
Chandra, Kavitha
THOMPSON Center for Advanced Computation and Telecommunications University of Massachusetts Lowell One, nonlinear time-series Corresponding author: Charles Thompson; charles_thompson2@uml.edu 1 INTRODUCTION
Siracusa, Michael Richard, 1980-
2009-01-01T23:59:59.000Z
In this dissertation we investigate the problem of reasoning over evolving structures which describe the dependence among multiple, possibly vector-valued, time-series. Such problems arise naturally in variety of settings. ...
A regression model with a hidden logistic process for feature extraction from time series
Chamroukhi, Faicel
operation. The switch operations signals can be seen as time series presenting non-linearities and various changes in regime. Basic linear regression can not be adopted for this type of sig- nals because a constant linear relationship is not adapted. As alternative to linear regression, some authors use
Financial time series forecasting with a bio-inspired fuzzy model Jos Luis Aznarte a,
Granada, Universidad de
Alcalá-Fdez b , Antonio Arauzo-Azofra c , José Manuel Benítez b a Center for Energy and Processes (CEP series, as stock prices or level of indices, is a controversial issue which has been questioned nature, the most salient of which is the well-known ARMA model by Box and Jenkins (1970). However, due
Statistical criteria for characterizing irradiance time series.
Stein, Joshua S.; Ellis, Abraham; Hansen, Clifford W.
2010-10-01T23:59:59.000Z
We propose and examine several statistical criteria for characterizing time series of solar irradiance. Time series of irradiance are used in analyses that seek to quantify the performance of photovoltaic (PV) power systems over time. Time series of irradiance are either measured or are simulated using models. Simulations of irradiance are often calibrated to or generated from statistics for observed irradiance and simulations are validated by comparing the simulation output to the observed irradiance. Criteria used in this comparison should derive from the context of the analyses in which the simulated irradiance is to be used. We examine three statistics that characterize time series and their use as criteria for comparing time series. We demonstrate these statistics using observed irradiance data recorded in August 2007 in Las Vegas, Nevada, and in June 2009 in Albuquerque, New Mexico.
Fernandez, Thomas
Comparative application of artificial neural networks and genetic algorithms for multivariate time of artificial neural networks and genetic algorithms in terms of forecasting and understanding of algal blooms-a, Microcystis, short-term prediction, artificial neural network model, genetic algorithm model, rule sets
Time Series Analysis 1 Time series in astronomy
Babu, G. Jogesh
(supernovae, gamma-ray bursts) Difficulties in astronomical time series Gapped data streams: Diurnal & monthly phenomena: thermonuclear (novae, X-ray bursts), magnetic reconnection (solar/stellar flares), star death); pulsation (helioseismology, Cepheids) Stochastic phenomena: accretion (CVs, X-ray binaries, Seyfert gals
Maximum likelihood parameter estimation in time series models using sequential Monte Carlo
Yildirim, Sinan
2013-06-11T23:59:59.000Z
, respectively. This approach is useful to handle the case where the columns of Y are generated sequentially in time, such as in audio signal processing. Usually very large number of columns in Y leads to the necessity of online algorithms to learn the model... .6 (dashed lines). For illustrative purposes, every 1000th estimate is shown . . . . . . . . . . . . . . . . . . . . . . . 130 6.1 Histograms of Monte Carlo estimates of gradients of log p?,?,?? (Y ?,?,?) w.r.t. the parameters of the ?-stable distribution...
Regression quantiles for time series
Cai, Zongwu
2002-02-01T23:59:59.000Z
~see, e+g+, Ibragimov and Linnik, 1971, p+ 316!+ Namely, partition REGRESSION QUANTILES FOR TIME SERIES 187 $1, + + + , n% into 2qn 1 1 subsets with large block of size r 5 rn and small block of size s 5 sn+ Set q 5 qn 5 ? n rn 1 sn? , (A.7) where {x...! are the standard Lindeberg–Feller conditions for asymptotic normality of Qn,1 for the independent setup+ Let us first establish ~A+8!+ To this effect, we define the large-block size rn by rn 5 {~nhn!102} and the small-block size sn 5 {~nhn!1020log n}+ Then, as n r...
Marzouk, Youssef; Fast P. (Lawrence Livermore National Laboratory, Livermore, CA); Kraus, M. (Peterson AFB, CO); Ray, J. P.
2006-01-01T23:59:59.000Z
Terrorist attacks using an aerosolized pathogen preparation have gained credibility as a national security concern after the anthrax attacks of 2001. The ability to characterize such attacks, i.e., to estimate the number of people infected, the time of infection, and the average dose received, is important when planning a medical response. We address this question of characterization by formulating a Bayesian inverse problem predicated on a short time-series of diagnosed patients exhibiting symptoms. To be of relevance to response planning, we limit ourselves to 3-5 days of data. In tests performed with anthrax as the pathogen, we find that these data are usually sufficient, especially if the model of the outbreak used in the inverse problem is an accurate one. In some cases the scarcity of data may initially support outbreak characterizations at odds with the true one, but with sufficient data the correct inferences are recovered; in other words, the inverse problem posed and its solution methodology are consistent. We also explore the effect of model error-situations for which the model used in the inverse problem is only a partially accurate representation of the outbreak; here, the model predictions and the observations differ by more than a random noise. We find that while there is a consistent discrepancy between the inferred and the true characterizations, they are also close enough to be of relevance when planning a response.
Detection Methods for Astronomical Time Series
Coehlo, Nathan Kirk
2010-01-01T23:59:59.000Z
Time Series by Nathan Kirk Coehlo A dissertation submittedCopyright 2010 by Nathan Kirk Coehlo Abstract DetectionTime Series by Nathan Kirk Coehlo Doctor of Philosophy in
Chen, Wei-Chen [ORNL; Maitra, Ranjan [Iowa State University
2011-01-01T23:59:59.000Z
We propose a model-based approach for clustering time series regression data in an unsupervised machine learning framework to identify groups under the assumption that each mixture component follows a Gaussian autoregressive regression model of order p. Given the number of groups, the traditional maximum likelihood approach of estimating the parameters using the expectation-maximization (EM) algorithm can be employed, although it is computationally demanding. The somewhat fast tune to the EM folk song provided by the Alternating Expectation Conditional Maximization (AECM) algorithm can alleviate the problem to some extent. In this article, we develop an alternative partial expectation conditional maximization algorithm (APECM) that uses an additional data augmentation storage step to efficiently implement AECM for finite mixture models. Results on our simulation experiments show improved performance in both fewer numbers of iterations and computation time. The methodology is applied to the problem of clustering mutual funds data on the basis of their average annual per cent returns and in the presence of economic indicators.
Inverting multispectral thermal time series images of volcanic eruptions for lava emplacement models
Barnie, T. D.; Oppenheimer, C.
2015-06-04T23:59:59.000Z
is small – this can be 434 considered to model a situation in which there is a lot of ‘churn’ at the hot surface and most 435 material is removed in some way. In Figure 10 the NAE has a the same support at high temperatures 436 as the previous ‘complex...
Normalizing the causality between time series
Liang, X San
2015-01-01T23:59:59.000Z
Recently, a rigorous yet concise formula has been derived to evaluate the information flow, and hence the causality in a quantitative sense, between time series. To assess the importance of a resulting causality, it needs to be normalized. The normalization is achieved through distinguishing three types of fundamental mechanisms that govern the marginal entropy change of the flow recipient. A normalized or relative flow measures its importance relative to other mechanisms. In analyzing realistic series, both absolute and relative information flows need to be taken into account, since the normalizers for a pair of reverse flows belong to two different entropy balances; it is quite normal that two identical flows may differ a lot in relative importance in their respective balances. We have reproduced these results with several autoregressive models. We have also shown applications to a climate change problem and a financial analysis problem. For the former, reconfirmed is the role of the Indian Ocean Dipole as ...
Multivariate Time Series Forecasting in Incomplete Environments
Roberts, Stephen
Multivariate Time Series Forecasting in Incomplete Environments Technical Report PARG 08-03 Seung of Oxford December 2008 #12;Seung Min Lee and Stephen J. Roberts Technical Report PARG 08-03 Multivariate missing observations and forecasting future values in incomplete multivariate time series data. We study
14.384 Time Series Analysis, Fall 2007
Mikusheva, Anna, 1976-
The course provides a survey of the theory and application of time series methods in econometrics. Topics covered will include univariate stationary and non-stationary models, vector autoregressions, frequency domain ...
14.384 Time Series Analysis, Fall 2008
Schrimpf, Paul
The course provides a survey of the theory and application of time series methods in econometrics. Topics covered will include univariate stationary and non-stationary models, vector autoregressions, frequency domain ...
Wavelet analysis and scaling properties of time series
P. Manimaran; Prasanta K. Panigrahi; Jitendra C. Parikh
2005-08-30T23:59:59.000Z
We propose a wavelet based method for the characterization of the scaling behavior of non-stationary time series. It makes use of the built-in ability of the wavelets for capturing the trends in a data set, in variable window sizes. Discrete wavelets from the Daubechies family are used to illustrate the efficacy of this procedure. After studying binomial multifractal time series with the present and earlier approaches of detrending for comparison, we analyze the time series of averaged spin density in the 2D Ising model at the critical temperature, along with several experimental data sets possessing multi-fractal behavior.
Integrated method for chaotic time series analysis
Hively, Lee M. (Philadelphia, TN); Ng, Esmond G. (Concord, TN)
1998-01-01T23:59:59.000Z
Methods and apparatus for automatically detecting differences between similar but different states in a nonlinear process monitor nonlinear data. Steps include: acquiring the data; digitizing the data; obtaining nonlinear measures of the data via chaotic time series analysis; obtaining time serial trends in the nonlinear measures; and determining by comparison whether differences between similar but different states are indicated.
Integrated method for chaotic time series analysis
Hively, L.M.; Ng, E.G.
1998-09-29T23:59:59.000Z
Methods and apparatus for automatically detecting differences between similar but different states in a nonlinear process monitor nonlinear data are disclosed. Steps include: acquiring the data; digitizing the data; obtaining nonlinear measures of the data via chaotic time series analysis; obtaining time serial trends in the nonlinear measures; and determining by comparison whether differences between similar but different states are indicated. 8 figs.
Chaotic time series prediction using artificial neural networks
Bartlett, E.B.
1991-12-31T23:59:59.000Z
This paper describes the use of artificial neural networks to model the complex oscillations defined by a chaotic Verhuist animal population dynamic. A predictive artificial neural network model is developed and tested, and results of computer simulations are given. These results show that the artificial neural network model predicts the chaotic time series with various initial conditions, growth parameters, or noise.
Chaotic time series prediction using artificial neural networks
Bartlett, E.B.
1991-01-01T23:59:59.000Z
This paper describes the use of artificial neural networks to model the complex oscillations defined by a chaotic Verhuist animal population dynamic. A predictive artificial neural network model is developed and tested, and results of computer simulations are given. These results show that the artificial neural network model predicts the chaotic time series with various initial conditions, growth parameters, or noise.
Can biomass time series be reliably assessed from CPUE time series data Francis Lalo1
Hawai'i at Manoa, University of
1 Can biomass time series be reliably assessed from CPUE time series data only? Francis Laloë1 to abundance. This means (i) that catchability is constant and (ii) that all the biomass is catchable. If so, relative variations in CPUE indicate the same relative variations in biomass. Myers and Worm consider
Nonlinear time-series analysis revisited
Elizabeth Bradley; Holger Kantz
2015-03-25T23:59:59.000Z
In 1980 and 1981, two pioneering papers laid the foundation for what became known as nonlinear time-series analysis: the analysis of observed data---typically univariate---via dynamical systems theory. Based on the concept of state-space reconstruction, this set of methods allows us to compute characteristic quantities such as Lyapunov exponents and fractal dimensions, to predict the future course of the time series, and even to reconstruct the equations of motion in some cases. In practice, however, there are a number of issues that restrict the power of this approach: whether the signal accurately and thoroughly samples the dynamics, for instance, and whether it contains noise. Moreover, the numerical algorithms that we use to instantiate these ideas are not perfect; they involve approximations, scale parameters, and finite-precision arithmetic, among other things. Even so, nonlinear time-series analysis has been used to great advantage on thousands of real and synthetic data sets from a wide variety of systems ranging from roulette wheels to lasers to the human heart. Even in cases where the data do not meet the mathematical or algorithmic requirements to assure full topological conjugacy, the results of nonlinear time-series analysis can be helpful in understanding, characterizing, and predicting dynamical systems.
Segmenting Time Series for Weather Forecasting
Sripada, Yaji
for generating textual summaries. Our algorithm has been implemented in a weather forecast generation system. 1 presentation, aid human understanding of the underlying data sets. SUMTIME is a research project aiming turbines. In the domain of meteorology, time series data produced by numerical weather prediction (NWP
Wang, Ruofan; Wang, Jiang; Deng, Bin, E-mail: dengbin@tju.edu.cn; Liu, Chen; Wei, Xile [Department of Electrical and Automation Engineering, Tianjin University, Tianjin (China)] [Department of Electrical and Automation Engineering, Tianjin University, Tianjin (China); Tsang, K. M.; Chan, W. L. [Department of Electrical Engineering, The Hong Kong Polytechnic University, Kowloon (Hong Kong)] [Department of Electrical Engineering, The Hong Kong Polytechnic University, Kowloon (Hong Kong)
2014-03-15T23:59:59.000Z
A combined method composing of the unscented Kalman filter (UKF) and the synchronization-based method is proposed for estimating electrophysiological variables and parameters of a thalamocortical (TC) neuron model, which is commonly used for studying Parkinson's disease for its relay role of connecting the basal ganglia and the cortex. In this work, we take into account the condition when only the time series of action potential with heavy noise are available. Numerical results demonstrate that not only this method can estimate model parameters from the extracted time series of action potential successfully but also the effect of its estimation is much better than the only use of the UKF or synchronization-based method, with a higher accuracy and a better robustness against noise, especially under the severe noise conditions. Considering the rather important role of TC neuron in the normal and pathological brain functions, the exploration of the method to estimate the critical parameters could have important implications for the study of its nonlinear dynamics and further treatment of Parkinson's disease.
Some results of analysis of source position time series
Malkin, Zinovy
2015-01-01T23:59:59.000Z
Source position time series produced by International VLBI Service for Geodesy and astrometry (IVS) Analysis Centers were analyzed. These series was computed using different software and analysis strategy. Comparison of this series showed that they have considerably different scatter and systematic behavior. Based on the inspection of all the series, new sources were identified as sources with irregular (non-random) position variations. Two statistics used to estimate the noise level in the time series, namely RMS and ADEV were compared.
Abstract--We present a method to integrate environmental time series
89 Abstract--We present a method to integrate environmental time series into stock assessment). A general framework for integrating environmental time series into stock assessment models: model models and to test the significance of correlations between population processes and the environmental
Nonlinear chaos in temperature time series: Part I: Case studies
Yaron Rosenstein; Gal Zahavi
2012-11-27T23:59:59.000Z
In this work we present 3 case studies of local temperature time series obtained from stations in Europe and Israel. The nonlinear nature of the series is presented along with model based forecasting. Data is nonlinearly filtered using high dimensional projection and analysis is performed on the filtered data. A lorenz type model of 3 first order ODEs is then fitted. Forecasts are shown for periods of 100 days ahead, outperforming any existing forecast method known today. While other models fail at forecasting periods above 11 days, ours shows remarkable stability 100 days ahead. Thus finally a local dynamical system if found for local temperature forecasting not requiring solution of Navier-Stokes equations. Thus saving computational costs.
Burra G. Sidharth
2008-09-03T23:59:59.000Z
We briefly review two concepts of time - the usual time associated with "being" and more recent ideas, answering to the description of "becoming". The approximation involved in the former is examined. Finally we argue that it is (unpredictable) fluctuations that underlie time.
Exact Primitives for Time Series Data Mining
Mueen, Abdullah Al
2012-01-01T23:59:59.000Z
G. Silva, and Rui M. M. Brito. Mining approximate motifs intime series. In Data Mining, 2001. ICDM 2001, Proceedingson Knowledge discovery and data mining, KDD, pages 947–956,
A Framework for Comparison of Spatiotemporal and Time Series...
Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)
Framework for Comparison of Spatiotemporal and Time Series Datasets NREL is a national laboratory of the U.S. Department of Energy, Office of Energy Efficiency & Renewable Energy,...
14.384 Time Series Analysis, Fall 2002
Kuersteiner, Guido M.
Theory and application of time series methods in econometrics, including representation theorems, decomposition theorems, prediction, spectral analysis, estimation with stationary and nonstationary processes, VARs, unit ...
A Multivariate Approach to Estimate Complexity of FMRI Time Series
A Multivariate Approach to Estimate Complexity of FMRI Time Series Henry SchÂ¨utze1,2 , Thomas (MPSE), a multivariate entropy ap- proach that estimates spatio-temporal complexity of fMRI time series. In a temporally sliding window, MPSE measures the differential entropy of an assumed multivariate Gaussian density
Efficient Mining of Partial Periodic Patterns in Time Series Database
Dong, Guozhu
Efficient Mining of Partial Periodic Patterns in Time Series Database In ICDE 99 Jiawei Han \\Lambda peri odic patterns in timeseries databases, is an interesting data mining problem. Previous studies several algorithms for efficient mining of par tial periodic patterns, by exploring some interesting
A METHOD FOR IDENTIFYING REPETITION STRUCTURE IN MUSICAL AUDIO BASED ON TIME SERIES PREDICTION
Dixon, Simon
A METHOD FOR IDENTIFYING REPETITION STRUCTURE IN MUSICAL AUDIO BASED ON TIME SERIES PREDICTION This paper investigates techniques for determining the repeti- tion structure of musical audio. In particular. To this end, we propose a novel approach based on multivari- ate time series modelling of audio features
The moving blocks bootstrap versus parametric time series Richard M. Vogel
Vogel, Richard M.
The moving blocks bootstrap versus parametric time series models Richard M. Vogel Department adding uncertainty to the analysis. The moving blocks bootstrap is a simple resampling algorithm which of the moving block length. The moving blocks bootstrap resamples the observed time series using approximately
COMPOSITIONAL TIME SERIES ANALYSIS OF MORTALITY PROPORTIONS
Ravishanker, Nalini
models based on the Dirichlet distribution for modeling within the simplex. In this article, we describe to inaccurate estimation and prediction. In this article, a regression model with vector autoregressive moving lies on a simplex induced by the unit sum constraint. In general, a composition x of G parts is a G
Estimation of connectivity measures in gappy time series
Papadopoulos, G
2015-01-01T23:59:59.000Z
A new method is proposed to compute connectivity measures on multivariate time series with gaps. Rather than removing or filling the gaps, the rows of the joint data matrix containing empty entries are removed and the calculations are done on the remainder matrix. The method, called measure adapted gap removal (MAGR), can be applied to any connectivity measure that uses a joint data matrix, such as cross correlation, cross mutual information and transfer entropy. MAGR is favorably compared using these three measures to a number of known gap-filling techniques, as well as the gap closure. The superiority of MAGR is illustrated on time series from synthetic systems and financial time series.
Text Queries on Document Time Series
Baeza-Yates, Ricardo
Retrieved for Query "iraq war" #12;Smoothed Timeline for "iraq war" #12;Temporal Models Goal: Estimate;Documents Retrieved for Query "iraq war" #12;Weighted by Document Relevance #12;Smoothed with Background
Applications of Time Series in Finance and Macroeconomics
Ibarra Ramirez, Raul
2011-08-08T23:59:59.000Z
This dissertation contains three applications of time series in finance and macroeconomics. The first essay compares the cumulative returns for stocks and bonds at investment horizons from one to ten years by using a test ...
Nonparametric estimation of additive nonlinear ARX time series: Local Linear Fitting and Projections
Cai, Zongwu; Masry, Elias
2000-08-01T23:59:59.000Z
We consider the estimation and identification of the components (endogenous and exogenous) of additive nonlinear ARX time series models. We employ a local polynomial fitting scheme coupled with projections. We establish ...
Generalized Volterra-Wiener and surrogate data methods for complex time series analysis
Shashidhar, Akhil
2006-01-01T23:59:59.000Z
This thesis describes the current state-of-the-art in nonlinear time series analysis, bringing together approaches from a broad range of disciplines including the non-linear dynamical systems, nonlinear modeling theory, ...
Predictive Mining of Time Series Data in Astronomy
E. Perlman; A. Java
2002-12-18T23:59:59.000Z
We discuss the development of a Java toolbox for astronomical time series data. Rather than using methods conventional in astronomy (e.g., power spectrum and cross-correlation analysis) we employ rule discovery techniques commonly used in analyzing stock-market data. By clustering patterns found within the data, rule discovery allows one to build predictive models, allowing one to forecast when a given event might occur or whether the occurrence of one event will trigger a second. We have tested the toolbox and accompanying display tool on datasets (representing several classes of objects) from the RXTE All Sky Monitor. We use these datasets to illustrate the methods and functionality of the toolbox. We also discuss issues that can come up in data analysis as well as the possible future development of the package.
2001, Applied Statistics, 50, 143-154. Nonlinear autoregressive time series with multivariate
Glasbey, Chris
2001, Applied Statistics, 50, 143-154. Nonlinear autoregressive time series with multivariate's Buildings, Edinburgh, EH9 3JZ, Scotland July 27, 2000 Abstract A new form of nonlinear autoregressive time to be multivariate Gaussian mixtures. The model is also a type of multiprocess dynamic linear model
Feature-preserving interpolation and filtering of environmental time series
Mariethoz, Gregoire; Jougnot, Damien; Rezaee, Hassan
2015-01-01T23:59:59.000Z
We propose a method for filling gaps and removing interferences in time series for applications involving continuous monitoring of environmental variables. The approach is non-parametric and based on an iterative pattern-matching between the affected and the valid parts of the time series. It considers several variables jointly in the pattern matching process and allows preserving linear or non-linear dependences between variables. The uncertainty in the reconstructed time series is quantified through multiple realizations. The method is tested on self-potential data that are affected by strong interferences as well as data gaps, and the results show that our approach allows reproducing the spectral features of the original signal. Even in the presence of intense signal perturbations, it significantly improves the signal and corrects bias introduced by asymmetrical interferences. Potential applications are wide-ranging, including geophysics, meteorology and hydrology.
Iterative prediction of chaotic time series using a recurrent neural network
Essawy, M.A.; Bodruzzaman, M. [Tennessee State Univ., Nashville, TN (United States). Dept. of Electrical and Computer Engineering; Shamsi, A.; Noel, S. [USDOE Morgantown Energy Technology Center, WV (United States)
1996-12-31T23:59:59.000Z
Chaotic systems are known for their unpredictability due to their sensitive dependence on initial conditions. When only time series measurements from such systems are available, neural network based models are preferred due to their simplicity, availability, and robustness. However, the type of neutral network used should be capable of modeling the highly non-linear behavior and the multi-attractor nature of such systems. In this paper the authors use a special type of recurrent neural network called the ``Dynamic System Imitator (DSI)``, that has been proven to be capable of modeling very complex dynamic behaviors. The DSI is a fully recurrent neural network that is specially designed to model a wide variety of dynamic systems. The prediction method presented in this paper is based upon predicting one step ahead in the time series, and using that predicted value to iteratively predict the following steps. This method was applied to chaotic time series generated from the logistic, Henon, and the cubic equations, in addition to experimental pressure drop time series measured from a Fluidized Bed Reactor (FBR), which is known to exhibit chaotic behavior. The time behavior and state space attractor of the actual and network synthetic chaotic time series were analyzed and compared. The correlation dimension and the Kolmogorov entropy for both the original and network synthetic data were computed. They were found to resemble each other, confirming the success of the DSI based chaotic system modeling.
NONLINEAR MULTIVARIATE AND TIME SERIES ANALYSIS BY NEURAL NETWORK METHODS
Hsieh, William
NONLINEAR MULTIVARIATE AND TIME SERIES ANALYSIS BY NEURAL NETWORK METHODS William W. Hsieh] Methods in multivariate statistical analysis are essential for working with large amounts of geophysical multivariate statistical analysis, there is a hierarchy of methods, starting with linear regression at the base
Fast and Flexible Multivariate Time Series Subsequence Search Kanishka Bhaduri
Oza, Nikunj C.
search algorithm capable of subsequence search on any subset of variables. Moreover, MTS subsequence approach" may include searching on parameters such as speed, descent rate, vertical flight pathFast and Flexible Multivariate Time Series Subsequence Search Kanishka Bhaduri MCT Inc., NASA ARC
Mining Deviants in Time Series Data Streams S. Muthukrishnan
Shah, Rahul
outliers. There is a long history of study of various outliers in statistics and databases, and a recent aberrations. Deviants are known to be of great mining value in time series databases. We present first (highway, telephone, internet, web click), Supported by National Science foundation grants EIA 0087022
Wavelet Methods for Time Series Analysis Don Percival
Percival, Don
Wavelet Methods for Time Series Analysis Don Percival Applied Physics Laboratory Box 355640 in the morning and two in the afternoon, each about 45 minutes long) Â· Monday 1: introduction to wavelets and wavelet transforms (Part I) 2: introduction to the discrete wavelet transform (Part II) 3 & 4: basic
Resampling Methodology in Spatial Prediction and Repeated Measures Time Series
Rister, Krista Dianne
2012-02-14T23:59:59.000Z
- series representation given by ?(x) = ?? k=0 dk(x? ?(s0))k, x ? R (E.19) for some d0, d1, . . . ? R. Further, supppose that E [ Z?n(s0) ]2 = O(1) and that for some k1 ? (0,?), ?? k=1 ?? j=1 kj|dkdj|2 (k+j?2)/2? ( k + j ? 1 2 )[ ?j+k?2... December 2010 Major Subject: Statistics iii ABSTRACT Resampling Methodology in Spatial Prediction and Repeated Measures Time Series. (December 2010) Krista Dianne Rister, B.S., Texas A&M University; M.S., Texas A&M University Chair of Advisory...
SUPPLEMENT Figure 5. Wavelet time series analysis for yearly LBM outbreaks. a) The normalized time-series. b) Temporally-local wavelet power spectrum (dark red indicates the strongest periodicity while white indicates the weakest periodicity). c) Spatiotemporally-global wavelet spectrum. d) Time-series plot
Donges, Jonathan F; Beronov, Boyan; Wiedermann, Marc; Runge, Jakob; Feng, Qing Yi; Tupikina, Liubov; Stolbova, Veronika; Donner, Reik V; Marwan, Norbert; Dijkstra, Henk A; Kurths, Jürgen
2015-01-01T23:59:59.000Z
We introduce the pyunicorn (Pythonic unified complex network and recurrence analysis toolbox) open source software package for applying and combining modern methods of data analysis and modeling from complex network theory and nonlinear time series analysis. pyunicorn is a fully object-oriented and easily parallelizable package written in the language Python. It allows for the construction of functional networks such as climate networks in climatology or functional brain networks in neuroscience representing the structure of statistical interrelationships in large data sets of time series and, subsequently, investigating this structure using advanced methods of complex network theory such as measures and models for spatial networks, networks of interacting networks, node-weighted statistics or network surrogates. Additionally, pyunicorn provides insights into the nonlinear dynamics of complex systems as recorded in uni- and multivariate time series from a non-traditional perspective by means of recurrence qua...
Mesoscale variability in time series data: Satellite-based estimates for the U.S. JGOFS Bermuda TOPEX/PoseidonERS-1/2) are used to characterize, statistically, the mesoscale variability about the U to better understand the contribution of mesoscale eddies to the time series record and the model- data
Integrated Mathematical Modeling Software Series of Vehicle Propulsion...
Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site
Mathematical Modeling Software Series of Vehicle Propulsion System: (1) Tractive Effort (T sub ew) of Vehicle Road WheelTrack Sprocket Integrated Mathematical Modeling Software...
Bayesian classification of partially observed outbreaks using time-series data.
Safta, Cosmin; Ray, Jaideep; Crary, David (Applied Research Associates, Inc, Arlington, VA); Cheng, Karen (Applied Research Associates, Inc, Arlington, VA)
2010-05-01T23:59:59.000Z
Results show that a time-series based classification may be possible. For the test cases considered, the correct model can be selected and the number of index case can be captured within {+-} {sigma} with 5-10 days of data. The low signal-to-noise ratio makes the classification difficult for small epidemics. The problem statement is: (1) Create Bayesian techniques to classify and characterize epidemics from a time-series of ICD-9 codes (will call this time-series a 'morbidity stream'); and (2) It is assumed the morbidity stream has already set off an alarm (through a Kalman filter anomaly detector) Starting with a set of putative diseases: Identify which disease or set of diseases 'fit the data best' and, Infer associated information about it, i.e. number of index cases, start time of the epidemic, spread rate, etc.
Characterizing Weak Chaos using Time Series of Lyapunov Exponents
R. M. da Silva; C. Manchein; M. W. Beims; E. G. Altmann
2015-06-13T23:59:59.000Z
We investigate chaos in mixed-phase-space Hamiltonian systems using time series of the finite- time Lyapunov exponents. The methodology we propose uses the number of Lyapunov exponents close to zero to define regimes of ordered (stickiness), semi-ordered (or semi-chaotic), and strongly chaotic motion. The dynamics is then investigated looking at the consecutive time spent in each regime, the transition between different regimes, and the regions in the phase-space associated to them. Applying our methodology to a chain of coupled standard maps we obtain: (i) that it allows for an improved numerical characterization of stickiness in high-dimensional Hamiltonian systems, when compared to the previous analyses based on the distribution of recurrence times; (ii) that the transition probabilities between different regimes are determined by the phase-space volume associated to the corresponding regions; (iii) the dependence of the Lyapunov exponents with the coupling strength.
Time series power flow analysis for distribution connected PV generation.
Broderick, Robert Joseph; Quiroz, Jimmy Edward; Ellis, Abraham; Reno, Matthew J. [Georgia Institute of Technology, Atlanta, GA; Smith, Jeff [Electric Power Research Institute, Knoxville, TN; Dugan, Roger [Electric Power Research Institute, Knoxville, TN
2013-01-01T23:59:59.000Z
Distributed photovoltaic (PV) projects must go through an interconnection study process before connecting to the distribution grid. These studies are intended to identify the likely impacts and mitigation alternatives. In the majority of the cases, system impacts can be ruled out or mitigation can be identified without an involved study, through a screening process or a simple supplemental review study. For some proposed projects, expensive and time-consuming interconnection studies are required. The challenges to performing the studies are twofold. First, every study scenario is potentially unique, as the studies are often highly specific to the amount of PV generation capacity that varies greatly from feeder to feeder and is often unevenly distributed along the same feeder. This can cause location-specific impacts and mitigations. The second challenge is the inherent variability in PV power output which can interact with feeder operation in complex ways, by affecting the operation of voltage regulation and protection devices. The typical simulation tools and methods in use today for distribution system planning are often not adequate to accurately assess these potential impacts. This report demonstrates how quasi-static time series (QSTS) simulation and high time-resolution data can be used to assess the potential impacts in a more comprehensive manner. The QSTS simulations are applied to a set of sample feeders with high PV deployment to illustrate the usefulness of the approach. The report describes methods that can help determine how PV affects distribution system operations. The simulation results are focused on enhancing the understanding of the underlying technical issues. The examples also highlight the steps needed to perform QSTS simulation and describe the data needed to drive the simulations. The goal of this report is to make the methodology of time series power flow analysis readily accessible to utilities and others responsible for evaluating potential PV impacts.
TQuEST: Threshold Query Execution for Large Sets of Time Series
Kriegel, Hans-Peter
TQuEST: Threshold Query Execution for Large Sets of Time Series Johannes AÃ?falg, Hans-Peter Kriegel TQuEST, a powerful query processor for time series databases. TQuEST supports a novel but very useful times. 1 Introduction In this paper, we present TQuEST, a powerful analysis tool for time series
Analysis of Geophysical Time Series Using Discrete Wavelet Transforms: An Overview
Percival, Don
Analysis of Geophysical Time Series Using Discrete Wavelet Transforms: An Overview Donald B geophysical time series. The basic idea is to transform a time series into coefficients describing how in geophysical data analysis. The intent of this article is to give an overview of how DWTs can be used
New Problems for an Old Design: Time-Series Analyses of Air Pollution and Health
Dominici, Francesca
New Problems for an Old Design: Time-Series Analyses of Air Pollution and Health Jonathan M. Samet1 of particulate air pollution on the same or recent days (1;2). Studies of similar time-series design of morbidity for adverse effects of particulate air pollution on the public's health. The daily time-series studies of air
Exposure Measurement Error in Time-Series Studies of Air Pollution: Concepts and Consequences
Dominici, Francesca
1 Exposure Measurement Error in Time-Series Studies of Air Pollution: Concepts and Consequences S in time-series studies 1 11/11/99 Keywords: measurement error, air pollution, time series, exposure of air pollution and health. Because measurement error may have substantial implications for interpreting
Ray, Asok
February 8, 2015 16:49 World Scientific Review Volume - 9in x 6in "time-series classification" page:49 World Scientific Review Volume - 9in x 6in "time-series classification" page 2 2 S. Bahrampour and N. M
Detecting and interpreting distortions in hierarchical organization of complex time series
Dro?d?, Stanis?aw
2015-01-01T23:59:59.000Z
Hierarchical organization is a cornerstone of complexity and multifractality constitutes its central quantifying concept. For model uniform cascades the corresponding singularity spectra are symmetric while those extracted from empirical data are often asymmetric. Using the selected time series representing such diverse phenomena like price changes and inter-transaction times in the financial markets, sentence length variability in the narrative texts, Missouri River discharge and Sunspot Number variability as examples, we show that the resulting singularity spectra appear strongly asymmetric, more often left-sided but in some cases also right-sided. We present a unified view on the origin of such effects and indicate that they may be crucially informative for identifying composition of the time series. One particularly intriguing case of this later kind of asymmetry is detected in the daily reported Sunspot Number variability. This signals that either the commonly used famous Wolf formula distorts the real d...
Bodruzzaman, M.; Essawy, M.A.
1996-03-31T23:59:59.000Z
Chaotic systems are known for their unpredictability due to their sensitive dependence on initial conditions. When only time series measurements from such systems are available, neural network based models are preferred due to their simplicity, availability, and robustness. However, the type of neural network used should be capable of modeling the highly non-linear behavior and the multi- attractor nature of such systems. In this paper we use a special type of recurrent neural network called the ``Dynamic System Imitator (DSI)``, that has been proven to be capable of modeling very complex dynamic behaviors. The DSI is a fully recurrent neural network that is specially designed to model a wide variety of dynamic systems. The prediction method presented in this paper is based upon predicting one step ahead in the time series, and using that predicted value to iteratively predict the following steps. This method was applied to chaotic time series generated from the logistic, Henon, and the cubic equations, in addition to experimental pressure drop time series measured from a Fluidized Bed Reactor (FBR), which is known to exhibit chaotic behavior. The time behavior and state space attractor of the actual and network synthetic chaotic time series were analyzed and compared. The correlation dimension and the Kolmogorov entropy for both the original and network synthetic data were computed. They were found to resemble each other, confirming the success of the DSI based chaotic system modeling.
Time series analysis of ionization waves in dc neon glow discharge
Hassouba, M. A.; Al-Naggar, H. I.; Al-Naggar, N. M.; Wilke, C. [Department of Physics, Faculty of Science, Benha University (Egypt); Institute of Physics, E. M. A. University, Domstrasse 10a, 17489 Greifswald (Germany)
2006-07-15T23:59:59.000Z
The dynamics of dc neon glow discharge is examined by calculating a Lyapunov exponent spectrum (LES) and correlation dimension (D{sub corr}) from experimental time series. The embedding theory is used to reconstruct an attractor with the delay coordinate method. The analysis refers to periodic, chaotic, and quasi-periodic attractors. The results obtained are confirmed by a comparison with other methods of time series analysis such as the Fourier power spectrum and autocorrelation function. The main object of the present work is the positive column of a dc neon glow discharge. The positive column is an excellent model for the study of a non-linearity plasma system because it is nonisothermal plasma far from equilibrium.
SumTime-Turbine: A Knowledge-Based System to Communicate Gas Turbine Time-Series Data
Reiter, Ehud
SumTime-Turbine: A Knowledge-Based System to Communicate Gas Turbine Time-Series Data Jin Yu produces textual summaries of archived time- series data from gas turbines. These summaries should help evaluated. 1 Introduction In order to get the most out of gas turbines, TIGER [2] has been developed
Fliess, Michel
2008-01-01T23:59:59.000Z
New fast estimation methods stemming from control theory lead to a fresh look at time series, which bears some resemblance to "technical analysis". The results are applied to a typical object of financial engineering, namely the forecast of foreign exchange rates, via a "model-free" setting, i.e., via repeated identifications of low order linear difference equations on sliding short time windows. Several convincing computer simulations, including the prediction of the position and of the volatility with respect to the forecasted trendline, are provided. $\\mathcal{Z}$-transform and differential algebra are the main mathematical tools.
On the long-term correlations and multifractal properties of electric arc furnace time series
Livi, Lorenzo; Rizzi, Antonello; Sadeghian, Alireza
2015-01-01T23:59:59.000Z
In this paper, we study long-term correlations and multifractal properties elaborated from time series of three-phase current signals coming from an industrial electric arc furnace plant. Implicit sinusoidal trends are suitably detected in the scaling of the fluctuation function of such time series. Time series are then initially filtered via a Fourier based analysis, removing hence such strong periodicities. In the filtered time series we detected long-term, positive correlations. The presence of persistent correlations is in agreement with the typical V--I characteristic (hysteresis) of the electric arc furnace, justifying thus the memory effects found in the current time series. The multifractal signature is strong enough in the filtered time series to be effectively classified as multifractal.
The level crossing analysis of German stock market index (DAX) and daily oil price time series
Shayeganfar, F; Peinke, J; Tabar, M Reza Rahimi
2010-01-01T23:59:59.000Z
The level crossing analysis of DAX and oil price time series are given. We determine the average frequency of positive-slope crossings, $\
Tataw, Oben Moses
2013-01-01T23:59:59.000Z
International Conference on Data Mining (2001). Khairy, K. ,and Eamonn Keogh (2011). Mining Historical Documents forWang, E. J. Keogh. Querying and mining of time series data.
Lean Blow-Out Prediction in Gas Turbine Combustors Using Symbolic Time Series Analysis
Ray, Asok
Lean Blow-Out Prediction in Gas Turbine Combustors Using Symbolic Time Series Analysis Achintya of lean blowout in gas turbine combustors based on symbolic analysis of time series data from optical. For the purpose of detecting lean blowout in gas turbine combustors, the state probability vector obtained
Detecting Climate Change in Multivariate Time Series Data by Novel Clustering and Cluster Tracing Aachen University, Germany {kremer, guennemann, seidl}@cs.rwth-aachen.de Abstract--Climate change can series, and trace the clusters over time. A climate pattern is categorized as a changing pattern
Wavelet Methods for Time Series Analysis Half-Day Workshop Presented at UNSW
Percival, Don
Wavelet Methods for Time Series Analysis Half-Day Workshop Presented at UNSW Don Percival Visiting://faculty.washington.edu/dbp Overview of Workshop Â· two sessions, each 1 hour and 45 minutes long I: introduction to wavelets and wavelet transforms II: wavelet-based statistical analysis of time series - wavelet variance (also known
Wavelet Methods for Time Series Analysis Half-Day Workshop Presented at UQ St Lucia Campus
Percival, Don
Wavelet Methods for Time Series Analysis Half-Day Workshop Presented at UQ St Lucia Campus Don://faculty.washington.edu/dbp Overview of Workshop Â· two sessions, each 1 hour and 45 minutes long I: introduction to wavelets and wavelet transforms II: wavelet-based statistical analysis of time series - wavelet variance (also known
Fast Bootstrap applied to LS-SVM for Long Term Prediction of Time Series
Verleysen, Michel
Fast Bootstrap applied to LS-SVM for Long Term Prediction of Time Series Amaury Lendasse HUT, CIS the Fast Bootstrap methodology introduced in previous works. I. INTRODUCTION Time series forecasting are based on resampling, as k-fold cross-validation, leave-one-out, and bootstrap [4]. Although they differ
A test for second order stationarity of a time series based on the Discrete Fourier Transform
Subba Rao, Suhasini
A test for second order stationarity of a time series based on the Discrete Fourier Transform property, we construct a Portmanteau type test statistic for testing stationarity of the time series. It is shown that under the null of stationarity, the test statistic is approximately a chi square distribution
Engine Control Improvement through Application of Chaotic Time Series Analysis
Green, J.B., Jr.; Daw, C.S.
2003-07-15T23:59:59.000Z
The objective of this program was to investigate cyclic variations in spark-ignition (SI) engines under lean fueling conditions and to develop options to reduce emissions of nitrogen oxides (NOx) and particulate matter (PM) in compression-ignition direct-injection (CIDI) engines at high exhaust gas recirculation (EGR) rates. The CIDI activity builds upon an earlier collaboration between ORNL and Ford examining combustion instabilities in SI engines. Under the original CRADA, the principal objective was to understand the fundamental causes of combustion instability in spark-ignition engines operating with lean fueling. The results of this earlier activity demonstrated that such combustion instabilities are dominated by the effects of residual gas remaining in each cylinder from one cycle to the next. A very simple, low-order model was developed that explained the observed combustion instability as a noisy nonlinear dynamical process. The model concept lead to development of a real-time control strategy that could be employed to significantly reduce cyclic variations in real engines using existing sensors and engine control systems. This collaboration led to the issuance of a joint patent for spark-ignition engine control. After a few years, the CRADA was modified to focus more on EGR and CIDI engines. The modified CRADA examined relationships between EGR, combustion, and emissions in CIDI engines. Information from CIDI engine experiments, data analysis, and modeling were employed to identify and characterize new combustion regimes where it is possible to simultaneously achieve significant reductions in NOx and PM emissions. These results were also used to develop an on-line combustion diagnostic (virtual sensor) to make cycle-resolved combustion quality assessments for active feedback control. Extensive experiments on engines at Ford and ORNL led to the development of the virtual sensor concept that may be able to detect simultaneous reductions in NOx and PM emissions under low temperature combustion (LTC) regimes. An invention disclosure was submitted to ORNL for the virtual sensor under the CRADA. Industrial in-kind support was available throughout the project period. Review of the research results were carried out on a regular basis (annual reports and meetings) followed by suggestions for improvement in ongoing work and direction for future work. A significant portion of the industrial support was in the form of experimentation, data analysis, data exchange, and technical consultation.
iSAX: disk-aware mining and indexing of massive time series datasets
Shieh, Jin; Keogh, Eamonn
2009-01-01T23:59:59.000Z
on both indexing and data mining problems. Finally, in Sect.0125-6 iSAX: disk-aware mining and indexing of massive timeCurrent research in indexing and mining time series data has
BIOINFORMATICS Inferring Gene Regulatory Networks from Time Series
Babu, M. Madan
model regulatory relations in terms of Boolean relationships and combinatorial logic circuits (Kauffman the model (Shmulevich et al., 2002), the immediate extension of PBNs to any finite quantization (also. As opposed to PBNs, where gene interactions are modeled explicitly in terms of binary or multi-valued logical
Lightweight Time Modeling in Timed Creol
Bjørk, Joakim; Owe, Olaf; Schlatte, Rudolf; 10.4204/EPTCS.36.4
2010-01-01T23:59:59.000Z
Creol is an object-oriented modeling language in which inherently concurrent objects exchange asynchronous method calls. The operational semantics of Creol is written in an actor-based style, formulated in rewriting logic. The operational semantics yields a language interpreter in the Maude system, which can be used to analyze models. Recently, Creol has been applied to the modeling of systems with radio communication, such as sensor systems. With radio communication, messages expire and, if sent simultaneously, they may collide in the air. In order to capture these and other properties of distributed systems, we extended Creol's operational semantics with a notion of time. We exploit the framework of a language interpreter to use a lightweight notion of time, in contrast to that needed for a general purpose specification language. This paper presents a timed extension of Creol, including the semantics and the implementation strategy, and discusses its properties using an extended example. The approach can be...
A New Architecture for Summarising Time Series Data
Sripada, Yaji
of the systems developed in the SumTime Project2 ) summarises sensor data from gas turbines. This is challenging because of the large amount of data being summarised; a typical gas turbine has 250 ana- logue data generation techniques to produce summaries of such data. A short extract from SumTime-Turbine's input data
Simulation of wind-speed time series for wind-energy conversion analysis.
Corotis, R.B.
1982-06-01T23:59:59.000Z
In order to investigate operating characteristics of a wind energy conversion system it is often desirable to have a sequential record of wind speeds. Sometimes a long enough actual data record is not available at the time an analysis is needed. This may be the case if, e.g., data are recorded three times a day at a candidate wind turbine site, and then the hourly performance of generated power is desired. In such cases it is often possible to use statistical characteristics of the wind speed data to calibrate a stochastic model and then generate a simulated wind speed time series. Any length of record may be simulated by this method, and desired system characteristics may be studied. A simple wind speed simulation model, WEISIM, is developed based on the Weibull probability distribution for wind speeds with a correction based on the lag-one autocorrelation value. The model can simulate at rates from one a second to one an hour, and wind speeds can represent short-term averages (e.g., 1-sec averages) or longer-term averages (e.g., 1-min or 1 hr averages). The validity of the model is verified with PNL data for both histogram characteristics and persistance characteristics.
ENERGY SERIES "CFD Modeling and its Application in Steam Condenser
Bergman, Keren
SEMINAR: ENERGY SERIES "CFD Modeling and its Application in Steam Condenser Performance Improvement will discuss the application of CFD to steam condensers, an area where both of the above mentioned limitations of computational fluid dynamics, having applied these techniques extensively in the design large heat exchangers
Studying accreting black holes and neutron stars with time series: beyond the power spectrum
S. Vaughan; P. Uttley
2008-02-04T23:59:59.000Z
The fluctuating brightness of cosmic X-ray sources, particularly accreting black holes and neutron star systems, has enabled enormous progress in understanding the physics of turbulent accretion flows, the behaviour of matter on the surfaces of neutron stars and improving the evidence for black holes. Most of this progress has been made by analysing and modelling time series data in terms of their power and cross spectra, as will be discussed in other articles in this volume. Recently, attempts have been made to make use of other aspects of the data, by testing for non-linearity, non-Gaussianity, time asymmetry and by examination of higher order Fourier spectra. These projects, which have been made possible by the vast increase in data quality and quantity over the past decade, are the subject of this article.
Topic Time Series Analysis of Microblogs ellai@uci.edu
Bertozzi, Andrea L.
-worthy phenomena. However, transforming raw, free-form, real time text into meaningful in- formation remains spatially, temporally or both might be of interest to analysts, marketers, researchers, law enforcement of microblog topics, where edges represent the predictive power of one topic for another. Recovery
RESULTS Greenhouse Gas Time Series SUMMARY AND CONCLUSIONS
for soil respiration is 5.1 at 3 C and 4.2 at 5 C. · Figure 5b shows that CO2 residual fluxes are water - Sampling location vs. soil temperature and water content CO2 model residuals. The variables on the x fitting method2 . · Soil temperature at 5 cm taken concurrently with chambers · Soil water content of top
Analysis of MODIS 250 m NDVI Using Different Time-Series Data for Crop Type Separability
Lee, Eunmok
2014-08-31T23:59:59.000Z
The primary objectives of this research were to: (1) investigate the use of different compositing periods of NDVI values of time-series MODIS 250 m data for distinguishing major crop types on the central Great Plains of ...
Time-Series Classification of High-Temporal Resolution AVHRR NDVI Imagery of Mexico
Egbert, Stephen L.; Ortega-Huerta, Miguel; Martí nez-Meyer, Enrique; Price, Kevin P.; Peterson, A. Townsend
2000-01-01T23:59:59.000Z
Time-series data from wide-field sensors, acquired for the period of a growing season or longer, capitalize on phenological changes in vegetation and make it possible to identify vegetated land cover types in greater detail. ...
Mining Time Series Data: Moving from Toy Problems to Realistic Deployments
Hu, Bing
2013-01-01T23:59:59.000Z
Conference on Data Mining, 2010 V. Chandola, A. Banerjee,and E. Keogh. “ Querying and Mining of Time Series Data:2 nd Workshop on Temporal Data Mining, 2002 K. Malatesta, S.
The application of complex network time series analysis in turbulent heated jets
Charakopoulos, A. K.; Karakasidis, T. E., E-mail: thkarak@uth.gr; Liakopoulos, A. [Laboratory of Hydromechanics and Environmental Engineering, Department of Civil Engineering, University of Thessaly, 38334 Volos (Greece)] [Laboratory of Hydromechanics and Environmental Engineering, Department of Civil Engineering, University of Thessaly, 38334 Volos (Greece); Papanicolaou, P. N. [School of Civil Engineering, Department of Water Resources and Environmental Engineering, National Technical University of Athens, 5 Heroon Polytechniou St., 15780 Zografos (Greece)] [School of Civil Engineering, Department of Water Resources and Environmental Engineering, National Technical University of Athens, 5 Heroon Polytechniou St., 15780 Zografos (Greece)
2014-06-15T23:59:59.000Z
In the present study, we applied the methodology of the complex network-based time series analysis to experimental temperature time series from a vertical turbulent heated jet. More specifically, we approach the hydrodynamic problem of discriminating time series corresponding to various regions relative to the jet axis, i.e., time series corresponding to regions that are close to the jet axis from time series originating at regions with a different dynamical regime based on the constructed network properties. Applying the transformation phase space method (k nearest neighbors) and also the visibility algorithm, we transformed time series into networks and evaluated the topological properties of the networks such as degree distribution, average path length, diameter, modularity, and clustering coefficient. The results show that the complex network approach allows distinguishing, identifying, and exploring in detail various dynamical regions of the jet flow, and associate it to the corresponding physical behavior. In addition, in order to reject the hypothesis that the studied networks originate from a stochastic process, we generated random network and we compared their statistical properties with that originating from the experimental data. As far as the efficiency of the two methods for network construction is concerned, we conclude that both methodologies lead to network properties that present almost the same qualitative behavior and allow us to reveal the underlying system dynamics.
Andresen, Gorm Bruun; Greiner, Martin
2014-01-01T23:59:59.000Z
We present a new global high-resolution renewable energy atlas (REatlas) that can be used to calculate customised hourly time series of wind and solar PV power generation. In this paper, the atlas is applied to produce 32-year-long hourly model wind power time series for Denmark for each historical and future year between 1980 and 2035. These are calibrated and validated against real production data from the period 2000 to 2010. The high number of years allows us to discuss how the characteristics of Danish wind power generation varies between individual weather years. As an example, the annual energy production is found to vary by $\\pm10\\%$ from the average. Furthermore, we show how the production pattern change as small onshore turbines are gradually replaced by large onshore and offshore turbines. In most energy system analysis tools, fixed hourly time series of wind power generation are used to model future power systems with high penetrations of wind energy. Here, we compare the wind power time series fo...
Hsu, P. J.; Lai, S. K., E-mail: sklai@coll.phy.ncu.edu.tw [Complex Liquids Laboratory, Department of Physics, National Central University, Chungli 320 Taiwan (China); Molecular Science and Technology Program, Taiwan International Graduate Program, Academia Sinica, Taipei 115, Taiwan (China); Cheong, S. A. [Division of Physics and Applied Physics, School of Physical and Mathematical Sciences, Nanyang Technological University, 21 Nanyang Link, Singapore 637371 (Singapore)
2014-05-28T23:59:59.000Z
Folded conformations of proteins in thermodynamically stable states have long lifetimes. Before it folds into a stable conformation, or after unfolding from a stable conformation, the protein will generally stray from one random conformation to another leading thus to rapid fluctuations. Brief structural changes therefore occur before folding and unfolding events. These short-lived movements are easily overlooked in studies of folding/unfolding for they represent momentary excursions of the protein to explore conformations in the neighborhood of the stable conformation. The present study looks for precursory signatures of protein folding/unfolding within these rapid fluctuations through a combination of three techniques: (1) ultrafast shape recognition, (2) time series segmentation, and (3) time series correlation analysis. The first procedure measures the differences between statistical distance distributions of atoms in different conformations by calculating shape similarity indices from molecular dynamics simulation trajectories. The second procedure is used to discover the times at which the protein makes transitions from one conformation to another. Finally, we employ the third technique to exploit spatial fingerprints of the stable conformations; this procedure is to map out the sequences of changes preceding the actual folding and unfolding events, since strongly correlated atoms in different conformations are different due to bond and steric constraints. The aforementioned high-frequency fluctuations are therefore characterized by distinct correlational and structural changes that are associated with rate-limiting precursors that translate into brief segments. Guided by these technical procedures, we choose a model system, a fragment of the protein transthyretin, for identifying in this system not only the precursory signatures of transitions associated with ? helix and ? hairpin, but also the important role played by weaker correlations in such protein folding dynamics.
Anomaly detection in thermal pulse combustors using symbolic time series analysis
Ray, Asok
pulse combustor. Results are presented to exemplify early detection of combustion instability due339 Anomaly detection in thermal pulse combustors using symbolic time series analysis S Gupta1 for anomaly detection in thermal pulse combustors. The anomaly detection method has been tested on the time
Forecasting of preprocessed daily solar radiation time series using neural networks
Boyer, Edmond
Forecasting of preprocessed daily solar radiation time series using neural networks Christophe prediction of global solar radiation on a horizontal surface. First results are promising with nRMSE ~ 21 t or at day d and year y d H0 Extraterrestrial solar radiation coefficient for day d [MJ/m²] xt, xd,y Time
Applications of Universal Source Coding to Statistical Analysis of Time Series
Ryabko, Boris
2008-01-01T23:59:59.000Z
We show how universal codes can be used for solving some of the most important statistical problems for time series. By definition, a universal code (or a universal lossless data compressor) can compress any sequence generated by a stationary and ergodic source asymptotically to the Shannon entropy, which, in turn, is the best achievable ratio for lossless data compressors. We consider finite-alphabet and real-valued time series and the following problems: estimation of the limiting probabilities for finite-alphabet time series and estimation of the density for real-valued time series, the on-line prediction, regression, classification (or problems with side information) for both types of the time series and the following problems of hypothesis testing: goodness-of-fit testing, or identity testing, and testing of serial independence. It is important to note that all problems are considered in the framework of classical mathematical statistics and, on the other hand, everyday methods of data compression (or ar...
Forecasting of preprocessed daily solar radiation time series using neural networks
Paoli, Christophe; Muselli, Marc; Nivet, Marie-Laure [University of Corsica, CNRS UMR SPE, Corte (France); Voyant, Cyril [University of Corsica, CNRS UMR SPE, Corte (France); Hospital of Castelluccio, Radiotherapy Unit, Ajaccio (France)
2010-12-15T23:59:59.000Z
In this paper, we present an application of Artificial Neural Networks (ANNs) in the renewable energy domain. We particularly look at the Multi-Layer Perceptron (MLP) network which has been the most used of ANNs architectures both in the renewable energy domain and in the time series forecasting. We have used a MLP and an ad hoc time series pre-processing to develop a methodology for the daily prediction of global solar radiation on a horizontal surface. First results are promising with nRMSE {proportional_to} 21% and RMSE {proportional_to} 3.59 MJ/m{sup 2}. The optimized MLP presents predictions similar to or even better than conventional and reference methods such as ARIMA techniques, Bayesian inference, Markov chains and k-Nearest-Neighbors. Moreover we found that the data pre-processing approach proposed can reduce significantly forecasting errors of about 6% compared to conventional prediction methods such as Markov chains or Bayesian inference. The simulator proposed has been obtained using 19 years of available data from the meteorological station of Ajaccio (Corsica Island, France, 41 55'N, 8 44'E, 4 m above mean sea level). The predicted whole methodology has been validated on a 1.175 kWc mono-Si PV power grid. Six prediction methods (ANN, clear sky model, combination..) allow to predict the best daily DC PV power production at horizon d + 1. The cumulated DC PV energy on a 6-months period shows a great agreement between simulated and measured data (R{sup 2} > 0.99 and nRMSE < 2%). (author)
A non subjective approach to the GP algorithm for analysing noisy time series
K. P. Harikrishnan; R. Misra; G. Ambika; A. K. Kembhavi
2006-03-11T23:59:59.000Z
We present an adaptation of the standard Grassberger-Proccacia (GP) algorithm for estimating the Correlation Dimension of a time series in a non subjective manner. The validity and accuracy of this approach is tested using different types of time series, such as, those from standard chaotic systems, pure white and colored noise and chaotic systems added with noise. The effectiveness of the scheme in analysing noisy time series, particularly those involving colored noise, is investigated. An interesting result we have obtained is that, for the same percentage of noise addition, data with colored noise is more distinguishable from the corresponding surrogates, than data with white noise. As examples for real life applications, analysis of data from an astrophysical X-ray object and human brain EEG, are presented.
Detrended partial cross-correlation analysis of two time series influenced by common external forces
Qian, Xi-Yuan; Jiang, Zhi-Qiang; Podobnik, Boris; Zhou, Wei-Xing; Stanley, H Eugene
2015-01-01T23:59:59.000Z
We propose a new method, detrended partial cross-correlation analysis (DPXA), to uncover the intrinsic power-law cross-correlations between two simultaneously recorded time series in the presence of nonstationarity after removing the effects of other time series acting as common forces. The DPXA method is a generalization of the detrended cross-correlation analysis by taking into account the partial correlation analysis. We illustrate the performance of the method using bivariate fractional Brownian motions and multifractal binomial measures with analytical expressions and apply it to extract the intrinsic cross-correlation between crude oil and gold futures by considering the impact of the US dollar index.
Nonlinear analysis of time series of vibration data from a friction brake: SSA, PCA, and MFDFA
Nikolay K. Vitanov; Norbert P. Hoffmann; Boris Wernitz
2014-10-23T23:59:59.000Z
We use the methodology of singular spectrum analysis (SSA), principal component analysis (PCA), and multi-fractal detrended fluctuation analysis (MFDFA), for investigating characteristics of vibration time series data from a friction brake. SSA and PCA are used to study the long time-scale characteristics of the time series. MFDFA is applied for investigating all time scales up to the smallest recorded one. It turns out that the majority of the long time-scale dynamics, that is presumably dominated by the structural dynamics of the brake system, is dominated by very few active dimensions only and can well be understood in terms of low dimensional chaotic attractors. The multi-fractal analysis shows that the fast dynamical processes originating in the friction interface are in turn truly multi-scale in nature.
Likelihood scan of the Super-Kamiokande I time series data
Gioacchino Ranucci
2006-05-12T23:59:59.000Z
In this work a detailed spectral analysis of the time series of the 8B solar neutrino flux published by the Super-Kamiokande Collaboration is presented, performed through a likelihood scan approach. Preliminarily a careful review of the analysis methodology is given, showing that the traditional periodicity search via the Lomb-Scargle periodogram is a special case of a more general likelihood based method. Since the data are published together with the relevant asymmetric errors, it is then shown how the likelihood analysis can be performed either with or without a prior error averaging. A key point of this work is the detailed illustration of the mathematical model describing the statistical properties of the estimated spectra obtained in the various cases, which is also validated through extensive Monte Carlo computations; the model includes a calculation for the prediction of the possible alias effects. In the successive investigation of the data, such a model is used to derive objective, mathematical predictions which are quantitatively compared with the features observed in the experimental spectra. This article clearly demonstrates that the handling of the errors is the origin of the discrepancy between published null observations and claimed significant periodicity in the same SK-I data sample. Moreover, the comprehensive likelihood analysis with asymmetric errors developed in this work provides results which cannot exclude the null hypothesis of constant rate, even though some indications stemming from the model at odd with such conclusion point towards the desirability of additional investigations with alternative methods to shed further light on the characteristics of the data.
A new measure of phase synchronization for a pair of time series and seizure focus localization
Kaushik Majumdar
2006-12-22T23:59:59.000Z
Defining and measuring phase synchronization in a pair of nonlinear time series are highly nontrivial. This can be done with the help of Fourier transform, when it exists, for a pair of stored (hence stationary) signals. In a time series instantaneous phase is often defined with the help of Hilbert transform. In this paper phase of a time series has been defined with the help of Fourier transform. This gives rise to a deterministic method to detect phase synchronization in its most general form between a pair of time series. Since this is a stricter method than the statistical methods based on instantaneous phase, this can be used for lateralization and source localization of epileptic seizures with greater accuracy. Based on this method a novel measure of phase synchronization, called syn function, has been defined, which is capable of quantifying neural phase synchronization and asynchronization as important parameters of epileptic seizure dynamics. It has been shown that such a strict measure of phase synchronization has potential application in seizure focus localization from scalp electroencephalogram (EEG) data, without any knowledge of electrical conductivity of the head.
OUTPUT-ONLY STATISTICAL TIME SERIES METHODS FOR STRUCTURAL HEALTH MONITORING: A COMPARATIVE STUDY
Paris-Sud XI, Université de
OUTPUT-ONLY STATISTICAL TIME SERIES METHODS FOR STRUCTURAL HEALTH MONITORING: A COMPARATIVE STUDY-STSMs) for Structural Health Monitoring (SHM) is presented via damage de- tection and identification in a GARTEUR type for Structural Health Monitoring (SHM). Their use is of high importance for structures such as bridges, aircraft
Efficient Time Series Matching by Wavelets Kinpong Chan and Ada Waichee Fu
Fu, Ada Waichee
since the effectiveness of power concentration of a particÂ ular transformation depends on the nature to other problems. While large pieces reduce the power of multiÂresolution, small pieces has weaknessÂTrees for fast retrieval. Due to the dimensionality curse problem, transformations are applied to time series
Mining Markov chain transition matrix from wind speed time series data Zhe Song a,
Kusiak, Andrew
Ltd. All rights reserved. 1. Introduction The US and China wind power market is rapidly expanding Wind speed time series Wind power Evolutionary algorithms Markov chain Optimization a b s t r a c transforming the first order transition matrix into its higher order counterparts. The evolutionary search
Indexing of Time Series by Major Minima and Maxima Eugene Fink
Fink, Eugene
sets: stock prices, air and sea temperatures, and wind speeds. Keywords: Compression, indexing.ics.uci.edu). Wind speeds: We have used daily wind speeds at twelve sites in Ireland, from 1961 to 1978, ob- tained. Indexing: The indexing of a time-series database is based on the notion of major inclines, illustrated
Indexing of Time Series by Major Minima and Maxima Eugene Fink
Fink, Eugene
sets: stock prices, air and sea temperatures, and wind speeds. Keywords: Compression, indexing.ics.uci.edu). Wind speeds: We have used daily wind speeds at twelve sites in Ireland, from 1961 to 1978, ob tained. Indexing: The indexing of a timeseries database is based on the notion of major inclines, illustrated
Monitoring water stress using time series of observed to unstressed surface temperature difference
Gentine, Pierre
Monitoring water stress using time series of observed to unstressed surface temperature difference to monitor stress have shifted from establishing empirical relationships between combined vegetation cover/temperature surface temperature as a baseline to monitor water stress. The unstressed temperature is the equilibrium
Weiss, Gary
Utility based Data Mining for Time Series Analysis - Cost-sensitive Learning for Neural Network@bis-lab.com ABSTRACT In corporate data mining applications, cost-sensitive learning is firmly established Mining General Terms Algorithms, Management, Economics Keywords Data Mining, cost-sensitive learning
Recognising Visual Patterns to Communicate Gas Turbine Time-Series Data
Reiter, Ehud
Recognising Visual Patterns to Communicate Gas Turbine Time-Series Data Jin Yu, Jim Hunter, Ehud analogue channels are sampled once per second and archived by the Tiger system for monitoring gas turbines is the generation of textual summaries. We are developing a knowledge-based system to summarise such data in the gas
Bispectral-Based Methods for Clustering Time Series Jane L. Harvill
Ravishanker, Nalini
the ratios. As an example, we apply the method to a set of time series of intensities of gamma-ray bursts, some of which exhibit nonlinear behavior; this enables us to identify gamma-ray bursts that may. As an example, we apply the bispectral-based clustering technique to a set of gamma-ray burst (GRB) intensity
Time Series Analysis with R A. Ian McLeod, Hao Yu, Esam Mahdi
McLeod, Ian
it is built on a solid foundation of core statistical and numerical algorithms. The R programming languageTime Series Analysis with R A. Ian McLeod, Hao Yu, Esam Mahdi Department of Statistical out some other key features of this quantitative programming environment (QPE). R is an open source
Time Series Measurements of Temperature, Current Velocity, and Sediment Resuspension in Saginaw Bay
Time Series Measurements of Temperature, Current Velocity, and Sediment Resuspension in Saginaw Bay and verification. These measurements will be made as part of this project. Measurements of sediment resuspension sediment resuspension in the bay during the spring. Measurements of sediment resuspension are important
Time-series validation of MODIS land biophysical products in a Kalahari woodland, Africa
Myneni, Ranga B.
Time-series validation of MODIS land biophysical products in a Kalahari woodland, Africa K. F MODIS variables are produced from the same algorithm. Solar zenith angle effects, differences between the two sides of the leaves are not symmetrical; 3. horizontally projected LAI is the area of `shadow
Time Series Methods for ForecastingElectricityMarket Pricing Zoran Obradovic Kevin Tomsovic
Obradovic, Zoran
Time Series Methods for ForecastingElectricityMarket Pricing Zoran Obradovic Kevin Tomsovic PO Box the predictability of electricity price under new market regulations and the engineering aspects of large scale of traditional commodities, such as,oil or agricultural products. Clearly, assessing the effectiveness
Closing the carbon budget of estuarine wetlands with tower-based measurements and MODIS time series
Chen, Jiquan
Closing the carbon budget of estuarine wetlands with tower-based measurements and MODIS time series, Institute of Biodiversity Science, Fudan University, Shanghai 200433, China, wDepartment of Environmental have distinct carbon flux dynamics the lateral carbon flux incurred by tidal activities, and methane
Creating and Using Geospatial Ontology Time Series in a Semantic Cultural Heritage Portal
Hyvönen, Eero
Creating and Using Geospatial Ontology Time Series in a Semantic Cultural Heritage Portal Tomi annotations in semantic cultural heritage portals commonly make spatiotemporal references to historical heritage portal CULTURESAMPO to sup- port faceted semantic search of contents and to visualize historical
Ultrasound radio-frequency time series for finding malignant breast lesions
de Freitas, Nando
-based solutions for breast lesion characterization to reduce the patient recall rate after mammography screening. In this work, ultrasound radio frequency time series analysis is performed for sepa- rating benign framework can help in differentiating malignant from benign breast lesions. 1 Introduction In the United
EOF analysis of a time series with application to tsunami detection
Tolkova, Elena
EOF analysis of a time series with application to tsunami detection Elena Tolkova a, a. Decomposition of a tsunami buoy record in a functional space of tidal EOFs presents an efficient tool for a short-term tidal forecast, as well as for an accu- rate tidal removal needed for early tsunami detection
INHERENT WATER OPTICAL PROPERTIES AT THE CARIBBEAN TIME SERIES STATION (CaTS)
Gilbes, Fernando
INHERENT WATER OPTICAL PROPERTIES AT THE CARIBBEAN TIME SERIES STATION (CaTS) Fernando Gilbes Rico 00681 ABSTRACT The temporal variability of the inherent water optical properties at the Caribbean wavelengths, but in all cases, the values were less than one. The correlation between bio-optical properties
1.2000-2009 time-series return information for Snake River: a. Fall Chinook Salmon
#12;Content: 1.2000-2009 time-series return information for Snake River: a. Fall Chinook Salmon b Natural 2000 2009 Estimated Return Of #12;Species: Run: Origin: Period: Chinook Salmon Fall Natural and Hatchery 2000 2009 Estimated Return Of #12;#12;Species: Run: Origin: Period: Sockeye Salmon Wild
Neural networks as a tool for constructing continuous NDVI time series from AVHRR and MODIS
Neural networks as a tool for constructing continuous NDVI time series from AVHRR and MODIS M. E-stationary aspect of NDVI, we use an artificial neural network (ANN) to map the NDVI indices from AVHRR to those the AVHRR record. Four years of overlap between the two sensors is used to train a neural network to remove
Global SunFarm Data Acquisition Network, Energy CRADLE, and Time Series Analysis
Rollins, Andrew M.
outdoor test beds across the world. Energy CRADLE is an ontology driven database acquisition tool which for Energy Technology workshop[1], the topic of photovoltaics(PV) lifetime and degradation science (LGlobal SunFarm Data Acquisition Network, Energy CRADLE, and Time Series Analysis Yang Hu, Mohammad
Evolving Neural Network Weights for Time-Series Prediction of General Aviation Flight Data
Hu, Wen-Chen
and predictive maintenance systems, reducing accident rates and saving lives. Keywords: Time-Series Prediction and lucrative industry, it has the highest accident rates within civil aviation [21]. For many years between 0.08% for altitude to 2% for roll. Cross validation of the best neural networks indicate
Two-Sample Testing in High Dimension and a Smooth Block Bootstrap for Time Series
Gregory, Karl Bruce
2014-06-12T23:59:59.000Z
This document contains three sections. The first two present new methods for two-sample testing where there are many variables of interest and the third presents a new methodology for time series bootstrapping. In the first section we develop a...
Time-varying Spectral Analysis in Neurophysiological Time Series Using Hilbert
Whitcher, Brandon
ability to detect time-varying coherence and phase properties. Key words: Coherence, electromyographic
High and Low Temperature Series Estimates for the Critical Temperature of the 3D Ising Model
Adler, Joan
High and Low Temperature Series Estimates for the Critical Temperature of the 3D Ising Model Zaher Abstract We have analysed low and high temperature series expansions for the threedimensional Ising model on the simple cubic lattice. Our analysis of Butera and Comi's new 32 term high temperature series yields K c
PRECISE HIGH-CADENCE TIME SERIES OBSERVATIONS OF FIVE VARIABLE YOUNG STARS IN AURIGA WITH MOST
Cody, Ann Marie; Tayar, Jamie; Hillenbrand, Lynne A. [Department of Astrophysics, California Institute of Technology, MC 249-17, Pasadena, CA 91125 (United States); Matthews, Jaymie M. [Department of Physics and Astronomy, University of British Columbia, 6224 Agricultural Road, Vancouver, British Columbia V6T 1Z1 (Canada); Kallinger, Thomas, E-mail: amc@ipac.caltech.edu [Institut fuer Astronomie, Universitaet Wien, Tuerkenschanzstrasse 17, A-1180 Vienna (Austria)
2013-03-15T23:59:59.000Z
To explore young star variability on a large range of timescales, we have used the MOST satellite to obtain 24 days of continuous, sub-minute cadence, high-precision optical photometry on a field of classical and weak-lined T Tauri stars (TTSs) in the Taurus-Auriga star formation complex. Observations of AB Aurigae, SU Aurigae, V396 Aurigae, V397 Aurigae, and HD 31305 reveal brightness fluctuations at the 1%-10% level on timescales of hours to weeks. We have further assessed the variability properties with Fourier, wavelet, and autocorrelation techniques, identifying one significant period per star. We present spot models in an attempt to fit the periodicities, but find that we cannot fully account for the observed variability. Rather, all stars exhibit a mixture of periodic and aperiodic behavior, with the latter dominating stochastically on timescales less than several days. After removal of the main periodicity, periodograms for each light curve display power-law trends consistent with those seen for other young accreting stars. Several of our targets exhibited unusual variability patterns not anticipated by prior studies, and we propose that this behavior originates with the circumstellar disks. The MOST observations underscore the need for investigation of TTS light variations on a wide range of timescales in order to elucidate the physical processes responsible; we provide guidelines for future time series observations.
Tse, Chi K. "Michael"
IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS--I: FUNDAMENTAL THEORY AND APPLICATIONS, VOL. 50, NO. 5 that may be applied to determine whether an observed time series is inconsis- tent with a specific class to the residuals of nonlinear models is equiv- alent to fitting that model subject to an information theoretic
Martin, Luis; Marchante, Ruth; Cony, Marco [Investigaciones y Recursos Solares Avanzados (IrSOLaV), Tres Cantos 2 8045 (Spain); Zarzalejo, Luis F.; Polo, Jesus; Navarro, Ana [Energy Department, CIEMAT, Madrid 28040 (Spain)
2010-10-15T23:59:59.000Z
Due to strong increase of solar power generation, the predictions of incoming solar energy are acquiring more importance. Photovoltaic and solar thermal are the main sources of electricity generation from solar energy. In the case of solar thermal energy plants with storage energy system, its management and operation need reliable predictions of solar irradiance with the same temporal resolution as the temporal capacity of the back-up system. These plants can work like a conventional power plant and compete in the energy stock market avoiding intermittence in electricity production. This work presents a comparisons of statistical models based on time series applied to predict half daily values of global solar irradiance with a temporal horizon of 3 days. Half daily values consist of accumulated hourly global solar irradiance from solar raise to solar noon and from noon until dawn for each day. The dataset of ground solar radiation used belongs to stations of Spanish National Weather Service (AEMet). The models tested are autoregressive, neural networks and fuzzy logic models. Due to the fact that half daily solar irradiance time series is non-stationary, it has been necessary to transform it to two new stationary variables (clearness index and lost component) which are used as input of the predictive models. Improvement in terms of RMSD of the models essayed is compared against the model based on persistence. The validation process shows that all models essayed improve persistence. The best approach to forecast half daily values of solar irradiance is neural network models with lost component as input, except Lerida station where models based on clearness index have less uncertainty because this magnitude has a linear behaviour and it is easier to simulate by models. (author)
Subba Rao, Suhasini
A test for second order stationarity of a time series based on the Discrete Fourier Transform stationary. Exploiting this important property, we construct a Portmanteau type test statistic for testing stationarity of the time series. It is shown that under the null of stationarity, the test statistic has
MODEL-DRIVEN ENGINEERING FOR IMPLEMENTING THE ISO 19100 SERIES OF INTERNATIONAL STANDARDS
Paris-Sud XI, Université de
MODEL-DRIVEN ENGINEERING FOR IMPLEMENTING THE ISO 19100 SERIES OF INTERNATIONAL STANDARDS CYRIL of the ISO 19100 series of standards with use of Model-Driven Engineering (MDE) techniques. We expose how MDE to use ISO 19109, 19110 and 19117 models in order to generate a rich client application. Our work takes
Time cartogram series to explore differences in the level of railway services: a case, population or travelling-time. A time cartogram is a type of cartogram in which the geographic-distance between locations is replaced by a time-related attribute (e.g., travelling-time) and the geography
Plotkin, S.; Stephens, T.; McManus, W.
2013-03-01T23:59:59.000Z
Scenarios of new vehicle technology deployment serve various purposes; some will seek to establish plausibility. This report proposes two reality checks for scenarios: (1) implications of manufacturing constraints on timing of vehicle deployment and (2) investment decisions required to bring new vehicle technologies to market. An estimated timeline of 12 to more than 22 years from initial market introduction to saturation is supported by historical examples and based on the product development process. Researchers also consider the series of investment decisions to develop and build the vehicles and their associated fueling infrastructure. A proposed decision tree analysis structure could be used to systematically examine investors' decisions and the potential outcomes, including consideration of cash flow and return on investment. This method requires data or assumptions about capital cost, variable cost, revenue, timing, and probability of success/failure, and would result in a detailed consideration of the value proposition of large investments and long lead times. This is one of a series of reports produced as a result of the Transportation Energy Futures (TEF) project, a Department of Energy-sponsored multi-agency effort to pinpoint underexplored strategies for abating GHGs and reducing petroleum dependence related to transportation.
Fast detection of nonlinearity and nonstationarity in short and noisy time series
M. De Domenico; V. Latora
2010-07-07T23:59:59.000Z
We introduce a statistical method to detect nonlinearity and nonstationarity in time series, that works even for short sequences and in presence of noise. The method has a discrimination power similar to that of the most advanced estimators on the market, yet it depends only on one parameter, is easier to implement and faster. Applications to real data sets reject the null hypothesis of an underlying stationary linear stochastic process with a higher confidence interval than the best known nonlinear discriminators up to date.
Interpretation of engine cycle-to-cycle variation by chaotic time series analysis
Daw, C.S.; Kahl, W.K.
1990-01-01T23:59:59.000Z
In this paper we summarize preliminary results from applying a new mathematical technique -- chaotic time series analysis (CTSA) -- to cylinder pressure data from a spark-ignition (SI) four-stroke engine fueled with both methanol and iso-octane. Our objective is to look for the presence of deterministic chaos'' dynamics in peak pressure variations and to investigate the potential usefulness of CTSA as a diagnostic tool. Our results suggest that sequential peak cylinder pressures exhibit some characteristic features of deterministic chaos and that CTSA can extract previously unrecognized information from such data. 18 refs., 11 figs., 2 tabs.
Perpinan, O. [Electrical Engineering Department, EUITI-UPM, Ronda de Valencia 3, 28012 Madrid (Spain); Lorenzo, E. [Instituto de Energia Solar, UPM, Ciudad Universitaria s/n, 28040 Madrid (Spain)
2011-01-15T23:59:59.000Z
The irradiance fluctuations and the subsequent variability of the power output of a PV system are analysed with some mathematical tools based on the wavelet transform. It can be shown that the irradiance and power time series are nonstationary process whose behaviour resembles that of a long memory process. Besides, the long memory spectral exponent {alpha} is a useful indicator of the fluctuation level of a irradiance time series. On the other side, a time series of global irradiance on the horizontal plane can be simulated by means of the wavestrapping technique on the clearness index and the fluctuation behaviour of this simulated time series correctly resembles the original series. Moreover, a time series of global irradiance on the inclined plane can be simulated with the wavestrapping procedure applied over a signal previously detrended by a partial reconstruction with a wavelet multiresolution analysis, and, once again, the fluctuation behaviour of this simulated time series is correct. This procedure is a suitable tool for the simulation of irradiance incident over a group of distant PV plants. Finally, a wavelet variance analysis and the long memory spectral exponent show that a PV plant behaves as a low-pass filter. (author)
Carter, Joshua A.; Winn, Joshua N., E-mail: carterja@mit.ed, E-mail: jwinn@mit.ed [Department of Physics and Kavli Institute for Astrophysics and Space Research, Massachusetts Institute of Technology, Cambridge, MA 02139 (United States)
2009-10-10T23:59:59.000Z
We consider the problem of fitting a parametric model to time-series data that are afflicted by correlated noise. The noise is represented by a sum of two stationary Gaussian processes: one that is uncorrelated in time, and another that has a power spectral density varying as 1/f{sup g}amma. We present an accurate and fast [O(N)] algorithm for parameter estimation based on computing the likelihood in a wavelet basis. The method is illustrated and tested using simulated time-series photometry of exoplanetary transits, with particular attention to estimating the mid-transit time. We compare our method to two other methods that have been used in the literature, the time-averaging method and the residual-permutation method. For noise processes that obey our assumptions, the algorithm presented here gives more accurate results for mid-transit times and truer estimates of their uncertainties.
Barr, R.A. [Electric Power Consulting Pty Ltd., Culburra Beach, New South Wales (Australia)] [Electric Power Consulting Pty Ltd., Culburra Beach, New South Wales (Australia); Platt, D. [Univ. of Wollongong, New South Wales (Australia). Dept. of Electrical and Computer Engineering] [Univ. of Wollongong, New South Wales (Australia). Dept. of Electrical and Computer Engineering
1996-04-01T23:59:59.000Z
Series capacitors can increase the power carrying capacity of subtransmission and distribution lines by reducing voltage regulation. The potential exists in selected locations for utilities to both improve the customer quality of supply and increase the supply capacity. The possibility of ferroresonance and effective countermeasures to ferroresonance are important issues that need to be carefully considered at the design stage. Other design issues are capacitor location, ohmic reactive value, transient behavior, short circuit withstand and capacitor protection. Ferroresonance can cause severe overvoltages and heavy currents resulting in damage to power system equipment and customer installations. This paper describes a ferroresonance model incorporating both time domain and frequency domain techniques. The ferroresonance model is used to map the possible ferroresonant states. A small scale laboratory non-linear ferroresonant circuit was constructed with the experimental results comparing favorably with the predicted model behavior. For series compensated lines and other circuit arrangements, the ferroresonance model allows the prediction of ferroresonant states and the examination of counter measures.
Time series models with an EGB2 conditional distribution
Harvey, Andrew; Caivano, Michele
2013-07-17T23:59:59.000Z
function; see Kleiber4 and Kotz (2003, ch6). The GB2 distribution contains many important distributions as special cases, including the Burr (#24; = 1) and log-logistic (#24; = 1; & = 1). GB2 distributions are fat tailed for ?nite #24; and & with upper... and lower tail indices of #17; = and #17; = #24;#23; respectively. The absolute value5 of a tf variate is GB2(f 1=2'; 2; 1=2; f=2) with tail index is #17; = #17; = f: 4Note that Kleiber and Kotz (2003) have #11; and #23; in reverse order, ie they write...
Modeling of ECM Controlled Series Fan-powered VAV Terminal Units
Yin, Peng
2011-10-21T23:59:59.000Z
Semi-empirical models for series fan-powered variable air volume terminal units (FPTUs) were developed based on models of the primary, plenum, fan airflow and the fan power consumption. The experimental setups and test procedures were developed...
Time Series Analysis Methods Applied to the Super-Kamiokande I Data
Gioacchino Ranucci
2005-05-25T23:59:59.000Z
The need to unravel modulations hidden in noisy time series of experimental data is a well known problem, traditionally attacked through a variety of methods, among which a popular tool is the so called Lomb-Scargle periodogram. Recently, for a class of problems in the solar neutrino field, it has been proposed an alternative maximum likelihood based approach, intended to overcome some intrinsic limitations affecting the Lomb-Scargle implementation. This work is focused to highlight the features of the likelihood methodology, introducing in particular an analytical approach to assess the quantitative significance of the potential modulation signals. As an example, the proposed method is applied to the time series of the measured values of the 8B neutrino flux released by the Super-Kamiokande collaboration, and the results compared with those of previous analysis performed on the same data sets. It is also examined in detail the comparison between the Lomb-Scargle and the likelihood methods, giving in the appendix the complete demonstration of their close relationship.
Jensen, Deborah Larkey
2005-02-17T23:59:59.000Z
. The mean and standard deviation of observable decision-action rates on teacher-identified ?teaching days? were higher than the rates on ?guiding? days. Bivariate time series analysis of decision-action rates and physiological response rates showed a...
Spectral fluctuations of billiards with mixed dynamics: from time series to superstatistics
A. Y. Abul-Magd; B. Dietz; T. Friedrich; A. Richter
2008-03-22T23:59:59.000Z
A statistical analysis of the eigenfrequencies of two sets of superconducting microwave billiards, one with mushroom-like shape and the other from the familiy of the Limacon billiards, is presented. These billiards have mixed regular-chaotic dynamics but different structures in their classical phase spaces. The spectrum of each billiard is represented as a time series where the level order plays the role of time. Two most important findings follow from the time-series analysis. First, the spectra can be characterized by two distinct relaxation lengths. This is a prerequisite for the validity of the superstatistical approach which is based on the folding of two distribution functions. Second, the shape of the resulting probability density function of the so-called superstatistical parameter is reasonably approximated by an inverse chi-square distribution. This distribution is used to compute nearest-neighbor spacing distributions and compare them with those of the resonance frequencies of billiards with mixed dynamics within the framework of superstatistics. The obtained spacing distribution is found to present a good description of the experimental ones and is of the same or even better quality as a number of other spacing distributions, including the one from Berry and Robnik. However, in contrast to other approaches towards a theoretical description of spectral properties of systems with mixed dynamics, superstatistics also provides a description of properties of the eigenfunctions. Indeed, the inverse chi-square parameter distribution is found suitable for the analysis of experimental resonance strengths in the Limacon billiards within the framework of superstatistics.
Modeling Timed Concurrent Systems using Generalized Ultrametrics
Modeling Timed Concurrent Systems using Generalized Ultrametrics Xiaojun Liu Eleftherios Matsikoudis Edward A. Lee Electrical Engineering and Computer Sciences University of California at Berkeley to lists, requires prior specific permission. #12;Modeling Timed Concurrent Systems using Generalized
Time series of high resolution spectra of SN 2014J observed with the TIGRE telescope
Jack, D; Schroder, K -P; Schmitt, J H M M; Hempelmann, A; Gonzalez-Perez, J N; Trinidad, M A; Rauw, G; Sixto, J M Cabrera
2015-01-01T23:59:59.000Z
We present a time series of high resolution spectra of the Type Ia supernova 2014J, which exploded in the nearby galaxy M82. The spectra were obtained with the HEROS echelle spectrograph installed at the 1.2 m TIGRE telescope. We present a series of 33 spectra with a resolution of R = 20, 000, which covers the important bright phases in the evolution of SN 2014J during the period from January 24 to April 1 of 2014. The spectral evolution of SN 2014J is derived empirically. The expansion velocities of the Si II P-Cygni features were measured and show the expected decreasing behaviour, beginning with a high velocity of 14,000 km/s on January 24. The Ca II infrared triplet feature shows a high velocity component with expansion velocities of > 20, 000 km/s during the early evolution apart from the normal component showing similar velocities as Si II. Further broad P-Cygni profiles are exhibited by the principal lines of Ca II, Mg II and Fe II. The TIGRE SN 2014J spectra also resolve several very sharp Na I D doub...
WAVELETS WITH RIDGES: A HIGH-RESOLUTION REPRESENTATION OF CATACLYSMIC VARIABLE TIME SERIES
Blackman, Claire, E-mail: claire.blackman@rhul.ac.u [Department of Economics, Royal Holloway, University of London, Egham, Surrey TW20 0EX (United Kingdom)
2010-11-15T23:59:59.000Z
Quasi-periodic oscillations (QPO) and dwarf nova oscillations (DNOs) occur in dwarf novae and nova-like variables during outburst and occasionally during quiescence, and have analogs in high-mass X-ray binaries and black-hole candidates. The frequent low coherence of quasi-period oscillations and DNOs can make detection with standard time-series tools such as periodograms problematic. This paper develops tools to analyze quasi-periodic brightness oscillations. We review the use of time-frequency representations (TFRs) in the astronomical literature, and show that representations such as the Choi-Williams distribution and Zhao-Atlas-Marks representation, which are best suited to high signal-to-noise data, cannot be assumed a priori to be the best techniques for our data, which have a much higher noise level and lower coherence. This leads us to a detailed analysis of the time-frequency resolution and statistical properties of six TFRs. We conclude that the wavelet scalogram, with the addition of wavelet ridges and maxima points, is the most effective TFR for analyzing quasi-periodicities in low signal-to-noise data, as it has high time-frequency resolution, and is a minimum variance estimator. We use the wavelet ridges method to re-analyze archival data from VW Hyi, and find 62 new QPOs and 7 new long-period DNOs. Relative to previous analyses, our method substantially improves the detection rate for QPOs.
Development of models for series and parallel fan variable air volume terminal units
Furr, James C., Jr
2007-09-17T23:59:59.000Z
Empirical models of airflow output and power consumption were developed for series and parallel fan powered variable air volume terminal units at typical design pressure conditions. A testing procedure and experimental setup were developed to test...
Series evaluation of Tweedie exponential dispersion model densities
Smyth, Gordon K.
of Mathematics and Computing University of Southern Queensland Toowoomba, Qld 4350, Australia Gordon K. Smyth 3052, Australia smyth@wehi.edu.au 23 February 2005 Abstract Exponential dispersion models, which for generalized linear models. The Tweedie families are those exponential dispersion models with power mean
F2010-B-107 MODELING OF THE THS-II SERIES/PARALLEL POWER TRAIN AND
Paris-Sud XI, Université de
F2010-B-107 MODELING OF THE THS-II SERIES/PARALLEL POWER TRAIN AND ITS ENERGY MANAGEMENT SYSTEM Hybrid power train, power-split eCVT, rule-based control strategy, Toyota Hybrid System, driver-based engineering intuition controller. The model encloses the modeling of the vehicle dynamics, the power train
Constant time algorithms in sparse graph model
Nguyen, Huy Ngoc, Ph. D. Massachusetts Institute of Technology
2010-01-01T23:59:59.000Z
We focus on constant-time algorithms for graph problems in bounded degree model. We introduce several techniques to design constant-time approximation algorithms for problems such as Vertex Cover, Maximum Matching, Maximum ...
Mazzaccaro, Anthony Peter
1974-01-01T23:59:59.000Z
TIME -SERIES ANAI, YSIS OI' PARTICIPATION IN NQiIRESI DEN I. ' HUNTING: Tl-;E EFFECTS OI LICENSE COST ANI3 QUANTITATIVE I LUC fUWTIONS IN SVPPI. Y A lil*sis by ANTHONY PETER MAZZACCARO Subrnittc. d to the Gracluate College of Teresa ARM Unic... AND QUANTITATIVE Fl UCTUATIONS IN SUPPLY A Thesis by ANTHONY PETER IvlAZZACCARO Approved as to style and content: (Chairman of Conrrnittee) ead of Department) ( ivl e rnb e g ~. , 8! (Member) +~eg ~+ ABSTRACT Time-Series Analysis of Participation...
A Scientific Data Processing Framework for Time Series NetCDF Data
Gaustad, Krista L.; Shippert, Timothy R.; Ermold, Brian D.; Beus, Sherman J.; Daily, Jeffrey A.; Borsholm, Atle; Fox, Kevin M.
2014-10-01T23:59:59.000Z
ARM Data Integrator (ADI) is a framework to streamline the development of scientific algorithms that analyze time-series NetCDF data, and to improve the content and consistency of the output data products produced by these algorithms. ADI achieves these goals by automating the process of retrieving and preparing data for analysis, supporting the definition of output data products through a graphical interface, and providing a modular, flexible software development architecture. The input data, preprocessing, and output data specifications are defined through a graphical interface and stored in a database. ADI also includes a workflow for data integration, a library of software modules to support the workflow, and a source code generator that produces C, IDL and Python templates. Data preparation support includes automated retrieval of data from input files, merging the retrieved data into appropriately sized chunks, and transformation of the data onto a common coordinate system grid. Through the graphical interface, users can view the details of both their data products and those in the ARM catalog. The variable and attribute definitions of the existing data products can be used to build new output data products. In addition, the rules that make up the ARM archive’s data standards are laid on top of the view of the new data product providing the user with a visual cue indicating where their output violates an archive standard. The necessary configurations are stored in a database that is accessed by the ADI libraries. This paper discusses the ADI framework, its supporting components, and how ADI can significantly decrease the time and cost of implementing scientific algorithms while improving the ability of scientists to disseminate their results.
Iriarte, Jose Luis
1994-01-01T23:59:59.000Z
Micro-phytoplankton (>20 gm cell size) was sampled in the upper 200 m of the water column at the Pacific equator, 140'W, during two JGOFS EqPac Time Series Studies, in order to determine the changes in the micro-phytoplanlcton ...
Abolmaesumi, Purang
Finding Statistics & Data at Queen's Sept/08 STATISTICS Facts & figures in tables, charts, time series, graphs, etc. 1. Statistics Canada www.statcan.ca English use the search box... REMEMBER: Don't Pay Contact madgic@queensu.ca to get statistics for free if faced with a fee! 2. Social
Pazzani, Michael J.
An Indexing Scheme for Fast Similarity Search in Large Time Series Databases Eamonn J. Keogh, California 92697 USA {eamonn,pazzani}@ics.uci.edu Abstract We address the problem of similarity search similar element of the bin. This bound allows us to search the bins in best first order, and to prune some
Time Series, Load Profiles, Temperature Sensitivity, Weather Adjustment 1 Introduction The quantitative, it is required to use indirect techniques to assess the type of demand they face [10, 11] in order to support their long-term investment planning. In this context, categories of residential, business and in- dustrial
Kirchner, James W.
January 2004; accepted 29 January 2004 Abstract Catchment-scale chemical transport is jointly controlledMeasuring catchment-scale chemical retardation using spectral analysis of reactive and passive chemical tracer time series Xiahong Fenga,*, James W. Kirchnerb , Colin Nealc a Department of Earth
ON MACHINE-LEARNED CLASSIFICATION OF VARIABLE STARS WITH SPARSE AND NOISY TIME-SERIES DATA
Richards, Joseph W.; Starr, Dan L.; Butler, Nathaniel R.; Bloom, Joshua S.; Crellin-Quick, Arien; Higgins, Justin; Kennedy, Rachel; Rischard, Maxime [Astronomy Department, University of California, Berkeley, CA 94720-7450 (United States); Brewer, John M., E-mail: jwrichar@stat.berkeley.edu [Astronomy Department, Yale University, New Haven, CT 06520-8101 (United States)
2011-05-20T23:59:59.000Z
With the coming data deluge from synoptic surveys, there is a need for frameworks that can quickly and automatically produce calibrated classification probabilities for newly observed variables based on small numbers of time-series measurements. In this paper, we introduce a methodology for variable-star classification, drawing from modern machine-learning techniques. We describe how to homogenize the information gleaned from light curves by selection and computation of real-numbered metrics (features), detail methods to robustly estimate periodic features, introduce tree-ensemble methods for accurate variable-star classification, and show how to rigorously evaluate a classifier using cross validation. On a 25-class data set of 1542 well-studied variable stars, we achieve a 22.8% error rate using the random forest (RF) classifier; this represents a 24% improvement over the best previous classifier on these data. This methodology is effective for identifying samples of specific science classes: for pulsational variables used in Milky Way tomography we obtain a discovery efficiency of 98.2% and for eclipsing systems we find an efficiency of 99.1%, both at 95% purity. The RF classifier is superior to other methods in terms of accuracy, speed, and relative immunity to irrelevant features; the RF can also be used to estimate the importance of each feature in classification. Additionally, we present the first astronomical use of hierarchical classification methods to incorporate a known class taxonomy in the classifier, which reduces the catastrophic error rate from 8% to 7.8%. Excluding low-amplitude sources, the overall error rate improves to 14%, with a catastrophic error rate of 3.5%.
Time reversal symmetry and collapse models
Daniel Bedingham; Owen Maroney
2015-02-24T23:59:59.000Z
Collapse models are modifications of quantum theory where the wave function is treated as physically real and the collapse of the wave function is a physical process. This appears to introduce a time reversal asymmetry into the dynamics of the wave function since the collapses affect only the future state. This paper challenges this conclusion, showing that in three different examples of time asymmetries associated with collapse models, if the physically real part of the model can be reduced to the locations in space and time about which collapses occur, then such a model works both forward and backward in time, in each case satisfying the Born rule. Despite the apparent asymmetry of the collapse process, these models in fact have time reversal symmetry. Any physically observed time asymmetries that arise in such models are due to the asymmetric imposition of initial or final time boundary conditions, rather than from an inherent asymmetry in the dynamical law. This is the standard explanation of time asymmetric behaviour resulting from time symmetric laws.
Nonlinear Time Domain Modeling and Simulation of Surface and...
Office of Environmental Management (EM)
Nonlinear Time Domain Modeling and Simulation of Surface and Embedded NPPS Nonlinear Time Domain Modeling and Simulation of Surface and Embedded NPPS Nonlinear Time Domain Modeling...
Time symmetry in wave function collapse models
Daniel Bedingham
2015-02-25T23:59:59.000Z
A framework for wave function collapse models that is symmetric under time reversal is presented. Within this framework there are equivalent pictures of collapsing wave functions evolving in both time directions. The backwards-in-time Born rule can be broken by an initial condition on the Universe resulting in asymmetric behaviour. Similarly the forwards-in-time Born rule can in principle be broken by a final condition on the Universe.
IGR For GR/M76881/01: Generating Summaries of Time-Series Data (SumTime) Background/Context
Sripada, Yaji
of numerical time-series data. The modern world is being flooded with such data. For example, a typical gas-turbine worked in three domains: weather forecasts, summaries of gas-turbine sensor data, and summaries of sensor number of input data values; this meant it could not be used in our hospital and gas-turbine domains
A Time Series Analysis of Food Price and Its Input Prices
Routh, Kari 1988-
2012-11-27T23:59:59.000Z
of crude oil, gasoline, corn, and ethanol prices, as well as, the relative foreign exchange rate of the U.S. dollar and producer price indexes for food manufacturing and fuel products on domestic food prices are examined. Because the data series are non...
Turova, Varvara
International Series of Numerical Mathematics, Vol. 160, 521540 Freezing of Living Cells, stresses arising due to non-simultaneous freezing of water in- side and outside of cells are modeled and outside of living cells during freezing is derived by applying an appropriate averaging technique
Ryabko, Boris
2007-01-01T23:59:59.000Z
We address the problem of nonparametric estimation of characteristics for stationary and ergodic time series. We consider finite-alphabet time series and real-valued ones and the following four problems: i) estimation of the (limiting) probability (or estimation of the density for real-valued time series), ii) on-line prediction, iii) regression and iv) classification (or so-called problems with side information). We show that so-called archivers (or data compressors) can be used as a tool for solving these problems. In particular, firstly, it is proven that any so-called universal code (or universal data compressor) can be used as a basis for constructing asymptotically optimal methods for the above problems. (By definition, a universal code can "compress" any sequence generated by a stationary and ergodic source asymptotically till the Shannon entropy of the source.) And, secondly, we show experimentally that estimates, which are based on practically used methods of data compression, have a reasonable preci...
Sripada, Yaji
An Approach to Generating Summaries of Time Series Data in the Gas Turbine Domain Jin Yu and Jim an approach to generating summaries of time series data in the gas turbine domain using AI techniques. Through the production of textual summaries. We extend KBTA framework to the gas turbine domain and propose to generate
Martinez, L.T.
1997-05-01T23:59:59.000Z
The objective of this study was to determine the effect of nonrandom sampling over time may have on the estimation of variability, namely the geometric standard deviation, using time series of personal exposure data.
A quantum defect model for the s, p, d, and f Rydberg series of CaF
Kay, Jeffrey J.
We present an improved quantum defect theory model for the “s,” “p,” “d,” and “f” Rydberg series of CaF. The model, which is the result of an exhaustive fit of high-resolution spectroscopic data, parameterizes the electronic ...
Time-series investigation of anomalous thermocouple responses in a liquid-metal-cooled reactor
Gross, K.C.; Planchon, H.P.; Poloncsik, J.
1988-03-24T23:59:59.000Z
A study was undertaken using SAS software to investigate the origin of anomalous temperature measurements recorded by thermocouples (TCs) in an instrumented fuel assembly in a liquid-metal-cooled nuclear reactor. SAS macros that implement univariate and bivariate spectral decomposition techniques were employed to analyze data recorded during a series of experiments conducted at full reactor power. For each experiment, data from physical sensors in the tests assembly were digitized at a sampling rate of 2/s and recorded on magnetic tapes for subsequent interactive processing with CMS SAS. Results from spectral and cross-correlation analyses led to the identification of a flow rate-dependent electromotive force (EMF) phenomenon as the origin of the anomalous TC readings. Knowledge of the physical mechanism responsible for the discrepant TC signals enabled us to device and justify a simple correction factor to be applied to future readings.
Six-Week Time Series Of Eddy Covariance CO2 Flux At Mammoth Mountain...
CO2 fluxes and the atmospheric parameters over a comparable time period. Energy balance closure was assessed by statistical regression of EC energy fluxes (sensible and...
Savran, Darko; Blesic, Suzana; Miljkovic, Vladimir
2014-01-01T23:59:59.000Z
In this paper we have analyzed scaling properties of time series of stock market indices (SMIs) of developing economies of Western Balkans, and have compared the results we have obtained with the results from more developed economies. We have used three different techniques of data analysis to obtain and verify our findings: Detrended Fluctuation Analysis (DFA) method, Detrended Moving Average (DMA) method, and Wavelet Transformation (WT) analysis. We have found scaling behavior in all SMI data sets that we have analyzed. The scaling of our SMI series changes from long-range correlated to slightly anti-correlated behavior with the change in growth or maturity of the economy the stock market is embedded in. We also report the presence of effects of potential periodic-like influences on the SMI data that we have analyzed. One such influence is visible in all our SMI series, and appears at a period $T_{p}\\approx 90$ days. We propose that the existence of various periodic-like influences on SMI data may partially...
Exploratory Spectral Analysis of Hydrological Time Series A.I. McLeod
McLeod, Ian
of Systems Design Engineering University of Waterloo Waterloo, Ontario, Canada N2L 3C5 December 1994 #12 previ- ously to these datasets adequately describe the low frequency component. The software and data are prewhitened by fitting either trend models or simple parametric models such as autore- gressive
TIME SERIES ANALYSIS FOR THE CF SOURCE IN SUDBURY NEUTRINO OBSERVATORY
Analysis . . . . . . . . . . . . . . . . . . . . . . . . 4 2 The Theory Leading to the Californium Time . . . . . . . . . . . . . 10 2.1.3 A Typical Event Chronology . . . . . . . . . . . . . . . . . . . 13 2.2 The Survival Function . . . . . . . . . . . . . . . . . . . . . . . . . . 15 2.2.1 The Survival Function for a Single
Time series analysis of the lead-lag relationship of freight futures and spot market prices
Gavriilidis, Nikolaos
2008-01-01T23:59:59.000Z
This thesis analyzes the relationship between the physical and paper shipping markets. The main objective is to find if one market leads the other by a specific time period so that market players can take advantage from ...
Looking for granulation and periodicity imprints in the sunspot time series
Lopes, Ilidio
2015-01-01T23:59:59.000Z
The sunspot activity is the end result of the cyclic destruction and regeneration of magnetic fields by the dynamo action. We propose a new method to analyze the daily sunspot areas data recorded since 1874. By computing the power spectral density of daily data series using the Mexican hat wavelet, we found a power spectrum with a well-defined shape, characterized by three features. The first term is the 22 yr solar magnetic cycle, estimated in our work to be of 18.43 yr. The second term is related to the daily volatility of sunspots. This term is most likely produced by the turbulent motions linked to the solar granulation. The last term corresponds to a periodic source associated with the solar magnetic activity, for which the maximum of power spectral density occurs at 22.67 days. This value is part of the 22-27 day periodicity region that shows an above-average intensity in the power spectra. The origin of this 22.67 day periodic process is not clearly identified, and there is a possibility that it can be...
Performance of VAV Fan Powered Terminal Units: Experimental Results and Models for Series Units
Furr, J.; O'Neal, D.; Davis, M.; Bryant, J.; Cramlet, A.
©2008 ASHRAE 91 ABSTRACT Empirical models of airflow output and power consump- tion were developed for series fan powered variable air volume terminal units at typical operating pressures. Terminal units with 8 in. (203 mm) and 12 in. (304 mm... pressures of 0.25 w.g. (63 Pa). Upstream static pressures ranged from 0.1 to 2.0 in w.g. (25 to 498 Pa). Data were collected at four different primary air damper positions and at four terminal unit fan speeds. Model variables included the RMS voltage...
2001, Applied Statistics, 50, 143-154. Nonlinear autoregressive time series with multivariate
Stone, J. V.
and Collares Pereira, 1992; Beyer et al., 1995, models for mean instantaneous sky luminance distribution have a value greater than unity when the sky is clear and a value less than unity when the sky is cloudy. Its
DePaolo, Donald J.; Maher, Kate; Christensen, John N.; McManus,Jerry
2006-06-05T23:59:59.000Z
High precision uranium isotope measurements of marineclastic sediments are used to measure the transport and storage time ofsediment from source to site of deposition. The approach is demonstratedon fine-grained, late Pleistocene deep-sea sediments from Ocean DrillingProgram Site 984A on the Bjorn Drift in the North Atlantic. The sedimentsare siliciclastic with up to 30 percent carbonate, and dated by sigma 18Oof benthic foraminifera. Nd and Sr isotopes indicate that provenance hasoscillated between a proximal source during the last three interglacialperiods volcanic rocks from Iceland and a distal continental sourceduring glacial periods. An unexpected finding is that the 234U/238Uratios of the silicate portion of the sediment, isolated by leaching withhydrochloric acid, are significantly less than the secular equilibriumvalue and show large and systematic variations that are correlated withglacial cycles and sediment provenance. The 234U depletions are inferredto be due to alpha-recoil loss of234Th, and are used to calculate"comminution ages" of the sediment -- the time elapsed between thegeneration of the small (<_ 50 mu-m) sediment grains in the sourceareas by comminution of bedrock, and the time of deposition on theseafloor. Transport times, the difference between comminution ages anddepositional ages, vary from less than 10 ky to about 300 to 400 ky forthe Site 984A sediments. Long transport times may reflect prior storagein soils, on continental shelves, or elsewhere on the seafloor. Transporttime may also be a measure of bottom current strength. During the mostrecent interglacial periods the detritus from distal continental sourcesis diluted with sediment from Iceland that is rapidly transported to thesite of deposition. The comminution age approach could be used to dateQuaternary non-marine sediments, soils, and atmospheric dust, and may beenhanced by concomitant measurement of 226Ra/230Th, 230Th/234U, andcosmogenic nuclides.
Ghosh, Sayantan; Panigrahi, Prasanta K
2010-01-01T23:59:59.000Z
We make use of wavelet transform to study the multi-scale, self similar behavior and deviations thereof, in the stock prices of large companies, belonging to different economic sectors. The stock market returns exhibit multi-fractal characteristics, with some of the companies showing deviations at small and large scales. The fact that, the wavelets belonging to the Daubechies' (Db) basis enables one to isolate local polynomial trends of different degrees, plays the key role in isolating fluctuations at different scales. We make use of Db4 and Db6 basis sets to respectively isolate local linear and quadratic trends at different scales in order to study the statistical characteristics of these financial time series. The fluctuations reveal fat tail non-Gaussian behavior, unstable periodic modulations, at finer scales, from which the characteristic $k^{-3}$ power law behavior emerges at sufficiently large scales. We further identify stable periodic behavior through the continuous Morlet wavelet.
Time series association learning
Papcun, George J. (Santa Fe, NM)
1995-01-01T23:59:59.000Z
An acoustic input is recognized from inferred articulatory movements output by a learned relationship between training acoustic waveforms and articulatory movements. The inferred movements are compared with template patterns prepared from training movements when the relationship was learned to regenerate an acoustic recognition. In a preferred embodiment, the acoustic articulatory relationships are learned by a neural network. Subsequent input acoustic patterns then generate the inferred articulatory movements for use with the templates. Articulatory movement data may be supplemented with characteristic acoustic information, e.g. relative power and high frequency data, to improve template recognition.
Sripada, Yaji
generates summaries of sensor data from a gas turbine. Table 1. Part of a sample of time series data describe and evaluate SumTime-Turbine, a prototype system which uses this architecture to generate textual summaries of sensor data from gas turbines. 1 Introduction It is often said in the NLP community
High and Low Temperature Series Estimates for the Critical Temperature of the 3D Ising Model
Adler, Joan
High and Low Temperature Series Estimates for the Critical Temperature Abstract We have analysed low and high temperature series expansions for the three high temperature series yields Kc = 0.221659 +0.000002-0.000005and from the 32 term low
Concurrency Theory Lecture 22: Timed Modelling & Conclusions
ÃbrahÃ¡m, Erika
Systems Example 22.1 (Real-time reactive systems) brake systems and airbags in cars plant controls mobile.1 (Real-time reactive systems) brake systems and airbags in cars plant controls mobile phones ... Real-Time Reactive Systems Example 22.1 (Real-time reactive systems) brake systems and airbags in cars plant controls
Verifying Hybrid Systems Modeled as Timed Automata: A Case Study?
-Vaandrager timed automata model, of the Steam Boiler Controller problem, a hybrid systems benchmark. This pa- per
On the Probabilistic Modeling of Runway Inter-departure Times
Balakrishnan, Hamsa
This paperr examines the validity of the Erlang distribution for runway service times. It uses high-fidelity surface surveillance data, for the first time, to model the probability distributions of runway service times and ...
Rabatel, Antoine
Using remote-sensing data to determine equilibrium-line altitude and mass-balance time series to calculate glacier mass balance using remote-sensing data. Snowline measurements from remotely sensed images by ground measurements and remote sensing are compared and show excellent correlation (r2 > 0.89), both
International Association for Cryptologic Research (IACR)
analysis, machine learning, time series classification. 1 Introduction Embedded devices such as smart cards operations allowing to secure, for example, bank transfers, buildings and cars. A modern bank card embeds securely a secret information allowing in fine to transfer cash. This operation is allowed by the smart
Introduction to Ocean Station Time Series CD-ROM The National Oceanographic Data Center (NODC) and the World Data Center for Oceanography (WDC) have compiled from the NODC Oceanographic Station Data File a set of oceanographic data having repetitive samples along ocean sections or at fixed locations
Unified Modeling of Complex Real-Time Control Systems
Hai, He; Chi-Lan, Cai
2011-01-01T23:59:59.000Z
Complex real-time control system is a software dense and algorithms dense system, which needs modern software engineering techniques to design. UML is an object-oriented industrial standard modeling language, used more and more in real-time domain. This paper first analyses the advantages and problems of using UML for real-time control systems design. Then, it proposes an extension of UML-RT to support time-continuous subsystems modeling. So we can unify modeling of complex real-time control systems on UML-RT platform, from requirement analysis, model design, simulation, until generation code.
Hierarchical Bayesian models for space-time air pollution data
Sahu, Sujit K
Hierarchical Bayesian models for space-time air pollution data Sujit K. Sahu June 14, 2011 sets have led to a step change in the analysis of space-time air pollution data. Accurate predictions-time air pollution data and illustrate the benefits of modeling with a real data example on monitoring
Statistical Model Checking for Networks of Priced Timed Automata
David, Alexandre
Statistical Model Checking for Networks of Priced Timed Automata Alexandre David1 , Kim G. Larsen1- and cost-bounded properties. A second contribution of the paper is the application of Statistical Model-time and hybrid systems with quantitative constraints on time, energy or more general continuous aspects [1
Time representation in reinforcement learning models of the basal ganglia
Gershman, Samuel J.
Reinforcement learning (RL) models have been influential in understanding many aspects of basal ganglia function, from reward prediction to action selection. Time plays an important role in these models, but there is still ...
Model Reference Adaptive Control Framework for Real Time Traffic
Minnesota, University of
Adaptive Control #12;12 Prescriptive Dynamic Traffic Assignment A Prediction Model and the Reference ModelModel Reference Adaptive Control Framework for Real Time Traffic Management Under Emergency Movement Volume Adaptive Controller Model Reference Adaptive Control (MRAC) Assumptions Super Zone Concept
Springer Series in Statistics Springer Series in Statistics
Cappé, Olivier
Springer Series in Statistics Springer Series in Statistics Inference in Hidden Markov Models class of statistical models with applications in diverse areas such as communications engineering models, including both algo- rithms and statistical theory. Topics range from filtering and smoothing
Continuous time random walk models for fractional space-time diffusion equations
Sabir Umarov
2014-09-14T23:59:59.000Z
In this paper continuous time random walk models approximating fractional space-time diffusion processes are studied. Stochastic processes associated with the considered equations represent time-changed processes, where the time-change process is a L\\'evy's stable subordinator with the stability index $\\beta \\in (0,1).$ In the parer the convergence of constructed CTRWs to time-changed processes associated with the corresponding fractional diffusion equations are proved using a new analytic method.
Estimating transition times for a model of
Mitchener, W. Garrett
= mean usage rate of G2 dm dt = birth q(m) - death m 0.0 0.2 0.4 0.6 0.8 1.0 0.2 0.4 0.6 0.8 1.0 Mean at a rate k K Simplify K = 1: Each agent uses G1 (state 0) or G2 (state 1) @ Ck = number youth in state kD = death rate: each time step each adult dies with prob- ability pD = rD N , replaced by sampling from
A Real-time Framework for Model Predictive Control of Continuous-Time Nonlinear Systems
Sontag, Eduardo
for piecewise constant NMPC of continuous-time processes. Index Terms-- nonlinear model predictive control, real-time optimization, optimal control, piecewise constant control I. INTRODUCTION Model predictive control (MPC horizon, open-loop optimal control problem. The unprecedented industrial success of MPC ap- proaches based
Model checking Timed CSP Philip Armstrong Gavin Lowe Joel Ouaknine
Ouaknine, JoÃ«l
Model checking Timed CSP Philip Armstrong Gavin Lowe JoÂ¨el Ouaknine A.W. Roscoe Oxford University Department of Computer Science Abstract Though Timed CSP was developed 25 years ago and the CSP for Timed CSP. In this paper we report on the creation of such a version, based on the digitisation results
Development of a probabilistic timing model for the ingestion of tap water.
Davis, M. J.; Janke, R.; Environmental Science Division; EPA
2009-01-01T23:59:59.000Z
A contamination event in a water distribution system can result in adverse health impacts to individuals consuming contaminated water from the system. Assessing impacts to such consumers requires accounting for the timing of exposures of individuals to tap-water contaminants that have time-varying concentrations. Here we present a probabilistic model for the timing of ingestion of tap water that we developed for use in the U.S. Environmental Protection Agency's Threat Ensemble Vulnerability Assessment and Sensor Placement Tool, which is designed to perform consequence assessments for contamination events in water distribution systems. We also present a statistical analysis of the timing of ingestion activity using data collected by the American Time Use Survey. The results of the analysis provide the basis for our model, which accounts for individual variability in ingestion timing and provides a series of potential ingestion times for tap water. It can be combined with a model for ingestion volume to perform exposure assessments and applied in cases for which the use of characteristics typical of the United States is appropriate.
Ray, Nige
â??ole for products and reciprocals. Several of the underlying ideas are rooted in algebraic combinatorics, especially] in algebraic topology. Our project has been stimulated by growing interest amongst combinatorialists and conventions for formal power series, basing our treatment on that of Henrici [9]. We assume given
Data Tools & Models - Time Series - U.S. Energy Information Administration
Annual Energy Outlook 2013 [U.S. Energy Information Administration (EIA)]
AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level:5 TablesExports to3,1,50022,3,,0,,6,1,Separation 23 362 334 318 706Production% of41.1 381.7DecemberGlobalInformation Administration(EIA) The
Modeling Gene Regulatory Networks from Time Series Data using Particle Filtering
Noor, Amina
2012-10-19T23:59:59.000Z
the National University of Sciences & Technology, Islamabad, Pakistan, in 2006 and 2008, respectively. Her research interests include genomic signal processing, pattern recognition, and algorithm design. Ms. Noor may be reached at Department of Electrical...
Multivariate and Time Series Models for Circular Data with Applications to Protein
Stone, J. V.
, University of Leeds) for his helpful comments at annual reviews. As mentioned in the abstract, bioinformatics The University of Leeds Department of Statistics January 2007 The candidate confirms that the work submitted involved is exemplified by the Leeds Annual Statistical Research (LASR) workshops (www.maths.leeds
Desertification of high latitude ecosystems: conceptual models, time-series analyses and experiments
Thorsson, Johann
2009-05-15T23:59:59.000Z
, representing state 5 where land degradation and erosion has resulted in loss of much of the mineral soil and nutrients, leaving a frost-heaved, gravely, oligotrophic substrate behind... exhibiting signs of frost damage on three dates............................................... 83 4.10 Percentage of birch seedling in control and 25% and 75% defoliation treatments exhibiting signs of frost damage in June of 2001, 2002 and 2003...
Ling, Shiqing
Heteroscedasticity Author(s): Shiqing Ling and W. K. Li Source: Journal of the American Statistical Association, Vol. 92, No. 439 (Sep., 1997), pp. 1184- 1194 Published by: American Statistical Association Stable URL contact support@jstor.org. . American Statistical Association is collaborating with JSTOR to digitize
Boyer, Edmond
Health Monitoring of operating wind turbines is challenging, as those structures are characterized, analyzed and compared within the problem of vibration based fault detection on operating wind turbines. The particular case of operating wind turbines is challeng- ing, as those structures are characterized by complex
Desertification of high latitude ecosystems: conceptual models, time-series analyses and experiments
Thorsson, Johann
2009-05-15T23:59:59.000Z
, representing state 5 where land degradation and erosion has resulted in loss of much of the mineral soil and nutrients, leaving a frost-heaved, gravely, oligotrophic substrate behind... exhibiting signs of frost damage on three dates............................................... 83 4.10 Percentage of birch seedling in control and 25% and 75% defoliation treatments exhibiting signs of frost damage in June of 2001, 2002 and 2003...
A supply forecasting model for Zimbabwe's corn sector: a time series and structural analysis
Makaudze, Ephias
1993-01-01T23:59:59.000Z
in the rural areas, (f) contribute to the improvement of the balance of payments both through increasing export earnings and generating import savings and (g) produce and supply raw materials for the manufacturing industry (Government of Zimbabwe National... about 70 percent of Zimbabwe's cereal calorie requirement (F. A. O. , 1985). Because of its primary importance as a national foodcrop, corn became controlled by the government as early as the Great Depression of the 1930s. The marketing of corn...
Essays on empirical time series modeling with causality and structural change
Kim, Jin Woong
2006-10-30T23:59:59.000Z
/dynamic causal relationships among variables. These characteristics will likely be helpful in generating accurate forecasts. v To my beloved brother vi ACKNOWLEDGEMENTS I would like to express special thanks to Dr. David Leatham, one... of my committee co-chairs for introducing me to research ideas with his excellent economic intuition, his careful insights, and thoughtful consideration. In addition to research, I really enjoyed working for Dr. David Leatham as a teaching assistant...
Statistical testing and estimation in continuous time interest rate models
Kim, Myung Suk
2006-10-30T23:59:59.000Z
The shape of drift function in continuous time interest rate models has been investigated by many authors during the past decade. The main concerns have been whether the drift function is linear or nonlinear, but no convincing conclusions have been...
On the modeling of time-varying delays
Shah, Chirag Laxmikant
2004-09-30T23:59:59.000Z
different characteristics, making the development of easy to use models a difficult endeavor. First an algorithm is developed to predict the actual input-output behavior when the input signal is directly fed into a device that characterizes the time...
Pulse combustor modeling demonstration of the importance of characteristic times
Barr, P.K.; Keller, J.O.; Bramlette, T.T.; Dec, J.E. (Combustion Research Facility, Sandia National Lab., Livermore, CA (US)); Westbrook, C.K. (Lawrence Livermore National Lab., Univ. of California, Livermore, CA (US))
1990-12-01T23:59:59.000Z
A numerical model has been developed to study the sensitivity of a pulse combustor's performance to changes in the relative timing between several of the dominant physical processes. The model is used to demonstrate the importance of the characteristic times associated with acoustics, fluid mixing, and chemical kinetics, which have been identified from both theoretical and experimental evidence. The combination of submodels for acoustics, injection, and combustion produces a pulse combustor model that is dynamic in that it fully couples the injection and mixing processes to the acoustic waves. Comparisons of simulations with experimental results show good agreement, verifying the model over a wide range of operating conditions. Because the model provides more control of the dominant processes than can be obtained in experiments, the parametric study establishes the cause-effect relations between the characteristic times and the resulting combustor performance.
Bird, R.E.; Riordan, C.J.; Myers, D.R.
1987-06-01T23:59:59.000Z
This report summarizes the investigation of a cloud-cover modification to SPCTRAL2, SERI's simple model for cloudless-sky, spectral solar irradiance. Our approach was to develop a modifier that relies on commonly acquired meteorological and broadband-irradiance data rather than detailed cloud properties that are generally not available. The method was to normalize modeled, cloudless-sky spectral irradiance to a measured broadband-irradiance value under cloudy skies, and then to compare the normalized, modeled data with measured spectral-irradiance data to empirically derive spectral modifiers that improve the agreement between modeled and measured data. Results indicate the possible form of the spectral corrections; however, we must analyze additional data to develop a spectral transmission function for cloudy-sky conditions.
Timed CTL Model Checking Lecture #16 of Advanced Model Checking
ÃbrahÃ¡m, Erika
= , if either: Â· for all x C: (x) > cx and (x) > cx, or Â· for any x, y C with (x) cx and (x) cx, and (y) cy(TA) is defined by: [s] = , [] = { s, | [] } c JPK 9 #12;Advanced model checking Example cx=2, cy=1 c JPK 10 from below and above by: |C|! xC cx Eval(C)/= number of regions |C|! 2|C|-1 xC (2cx + 2) where
Short-term time step convergence in a climate model
DOE Public Access Gateway for Energy & Science Beta (PAGES Beta)
Wan, Hui; Rasch, Philip J.; Taylor, Mark A.; Jablonowski, Christiane
2015-03-01T23:59:59.000Z
This paper evaluates the numerical convergence of very short (1 h) simulations carried out with a spectral-element (SE) configuration of the Community Atmosphere Model version 5 (CAM5). While the horizontal grid spacing is fixed at approximately 110 km, the process-coupling time step is varied between 1800 and 1 s to reveal the convergence rate with respect to the temporal resolution. Special attention is paid to the behavior of the parameterized subgrid-scale physics. First, a dynamical core test with reduced dynamics time steps is presented. The results demonstrate that the experimental setup is able to correctly assess the convergence rate ofmore »the discrete solutions to the adiabatic equations of atmospheric motion. Second, results from full-physics CAM5 simulations with reduced physics and dynamics time steps are discussed. It is shown that the convergence rate is 0.4—considerably slower than the expected rate of 1.0. Sensitivity experiments indicate that, among the various subgrid-scale physical parameterizations, the stratiform cloud schemes are associated with the largest time-stepping errors, and are the primary cause of slow time step convergence. While the details of our findings are model specific, the general test procedure is applicable to any atmospheric general circulation model. The need for more accurate numerical treatments of physical parameterizations, especially the representation of stratiform clouds, is likely common in many models. The suggested test technique can help quantify the time-stepping errors and identify the related model sensitivities.« less
Grzegorz Litak; Rodolfo Taccani; Krzysztof Urbanowicz; Janusz A. Holyst; Miroslaw Wendeker; Alessandro Giadrossi
2004-05-22T23:59:59.000Z
We report our results on non-periodic experimental time series of pressure in a single cylinder spark ignition engine. The experiments were performed for different levels of loading. We estimate the noise level in internal pressure calculating the coarse-grained entropy from variations of maximal pressures in successive cycles. The results show that the dynamics of the combustion is a nonlinear multidimensional process mediated by noise. Our results show that so defined level of noise in internal pressure is not monotonous function of loading.
Jensen, Deborah Larkey
2005-02-17T23:59:59.000Z
The purpose of this exploratory case study was to describe an expert teacher?s decision-making system during interactive instruction using teacher self-report information, classroom observation data, and physiological recordings. Timed recordings...
A Series Solution Framework for Finite-time Optimal Feedback Control, H-infinity Control and Games
Sharma, Rajnish
2010-01-14T23:59:59.000Z
The Bolza-form of the finite-time constrained optimal control problem leads to the Hamilton-Jacobi-Bellman (HJB) equation with terminal boundary conditions and tobe- determined parameters. In general, it is a formidable ...
Time Scales in Probabilistic Models of Wireless Sensor Networks
Anatoly Manita
2013-02-28T23:59:59.000Z
We consider a stochastic model of clock synchronization in a wireless network consisting of N sensors interacting with one dedicated accurate time server. For large N we find an estimate of the final time sychronization error for global and relative synchronization. Main results concern a behavior of the network on different time scales $t=t_N \\to \\infty$, $N \\to \\infty$. We discuss existence of phase transitions and find exact time scales on which an effective clock synchronization of the system takes place.
Neutrino flavor instabilities in a time-dependent supernova model
Abbar, Sajad
2015-01-01T23:59:59.000Z
A dense neutrino medium such as that inside a core-collapse supernova can experience collective flavor conversion or oscillations because of the neutral-current weak interaction among the neutrinos. This phenomenon has been studied in a restricted, stationary supernova model which possesses the (spatial) spherical symmetry about the center of the supernova and the (directional) axial symmetry around the radial direction. Recently it has been shown that these spatial and directional symmetries can be broken spontaneously by collective neutrino oscillations. In this paper we analyze the neutrino flavor instabilities in a time-dependent supernova model. Our results show that collective neutrino oscillations start at approximately the same radius in both the stationary and time-dependent supernova models unless there exist very rapid variations in local physical conditions on timescales of a few microseconds or shorter. Our results also suggest that collective neutrino oscillations can vary rapidly with time in t...
Modeling Time in Computing: A Taxonomy and a Comparative Survey
Carlo A. Furia; Dino Mandrioli; Angelo Morzenti; Matteo Rossi
2010-10-11T23:59:59.000Z
The increasing relevance of areas such as real-time and embedded systems, pervasive computing, hybrid systems control, and biological and social systems modeling is bringing a growing attention to the temporal aspects of computing, not only in the computer science domain, but also in more traditional fields of engineering. This article surveys various approaches to the formal modeling and analysis of the temporal features of computer-based systems, with a level of detail that is suitable also for non-specialists. In doing so, it provides a unifying framework, rather than just a comprehensive list of formalisms. The paper first lays out some key dimensions along which the various formalisms can be evaluated and compared. Then, a significant sample of formalisms for time modeling in computing are presented and discussed according to these dimensions. The adopted perspective is, to some extent, historical, going from "traditional" models and formalisms to more modern ones.
Modeling Space-Time Dynamics of Aerosols Using Satellite Data and Atmospheric Transport Model Output
Shi, Tao
Modeling Space-Time Dynamics of Aerosols Using Satellite Data and Atmospheric Transport Model of aerosol optical depth across mainland Southeast Asia. We include a cross validation study to assess
Mitchell, Christopher J [Los Alamos National Laboratory; Ahrens, James P [Los Alamos National Laboratory; Wang, Jun [UCF
2010-10-15T23:59:59.000Z
Petascale simulations compute at resolutions ranging into billions of cells and write terabytes of data for visualization and analysis. Interactive visuaUzation of this time series is a desired step before starting a new run. The I/O subsystem and associated network often are a significant impediment to interactive visualization of time-varying data; as they are not configured or provisioned to provide necessary I/O read rates. In this paper, we propose a new I/O library for visualization applications: VisIO. Visualization applications commonly use N-to-N reads within their parallel enabled readers which provides an incentive for a shared-nothing approach to I/O, similar to other data-intensive approaches such as Hadoop. However, unlike other data-intensive applications, visualization requires: (1) interactive performance for large data volumes, (2) compatibility with MPI and POSIX file system semantics for compatibility with existing infrastructure, and (3) use of existing file formats and their stipulated data partitioning rules. VisIO, provides a mechanism for using a non-POSIX distributed file system to provide linear scaling of 110 bandwidth. In addition, we introduce a novel scheduling algorithm that helps to co-locate visualization processes on nodes with the requested data. Testing using VisIO integrated into Para View was conducted using the Hadoop Distributed File System (HDFS) on TACC's Longhorn cluster. A representative dataset, VPIC, across 128 nodes showed a 64.4% read performance improvement compared to the provided Lustre installation. Also tested, was a dataset representing a global ocean salinity simulation that showed a 51.4% improvement in read performance over Lustre when using our VisIO system. VisIO, provides powerful high-performance I/O services to visualization applications, allowing for interactive performance with ultra-scale, time-series data.
Model Predictive Control based Real Time Power System Protection Schemes
Kumar, Ratnesh
1 Model Predictive Control based Real Time Power System Protection Schemes Licheng Jin, Member by controlling the production, absorption as well as flow of reactive power at various locations in the system predictive control, trajectory sensitivity, voltage stabilization, switching control, power system I
Real-time Modelling of Tsunami Data Applied Physics Laboratory
Percival, Don
Real-time Modelling of Tsunami Data Applied Physics Laboratory Department of Statistics University for Tsunami Research #12;Background - I · even before disasterous Sumatra tsunami in December 2004, de- structive potential of earthquake-generated tsunamis was well- known · due to rate at which a tsunami
Continuous time Markov chain models for chemical reaction networks
Kurtz, Tom
Continuous time Markov chain models for chemical reaction networks David F. Anderson Departments Abstract A reaction network is a chemical system involving multiple reactions and chemical species exploit the representation of the stochastic equation for chemical reaction networks and, under what
CONTINUOUS TIME MARKOV CHAIN MODELS FOR CHEMICAL REACTION NETWORKS
Anderson, David F.
Chapter 1 CONTINUOUS TIME MARKOV CHAIN MODELS FOR CHEMICAL REACTION NETWORKS David F. Anderson@math.wisc.edu Abstract A reaction network is a chemical system involving multiple reactions and chemical species-05793 #12;2 the representation of the stochastic equation for chemical reaction net- works and, under what
Short-term time step convergence in a climate model
DOE Public Access Gateway for Energy & Science Beta (PAGES Beta)
Wan, Hui; Rasch, Philip J.; Taylor, Mark; Jablonowski, Christiane
2015-02-11T23:59:59.000Z
A testing procedure is designed to assess the convergence property of a global climate model with respect to time step size, based on evaluation of the root-mean-square temperature difference at the end of very short (1 h) simulations with time step sizes ranging from 1 s to 1800 s. A set of validation tests conducted without sub-grid scale parameterizations confirmed that the method was able to correctly assess the convergence rate of the dynamical core under various configurations. The testing procedure was then applied to the full model, and revealed a slow convergence of order 0.4 in contrast to themore »expected first-order convergence. Sensitivity experiments showed without ambiguity that the time stepping errors in the model were dominated by those from the stratiform cloud parameterizations, in particular the cloud microphysics. This provides a clear guidance for future work on the design of more accurate numerical methods for time stepping and process coupling in the model.« less
Modeling Combined Time-and Event-Driven Dynamic Systems
Baclawski, Kenneth B.
such as logistical systems, distributed sensor sys- tems and intelligent highway vehicle systems, are complex dynamic. In this approach, future behaviors are generated through quantitative simulation which "executes" a simulation model, typically at fixed time steps, to obtain quantitative values of state and/or output variables. 1
Simulation analysis of moored fluorometer time series from the Mid-Atlantic Bight during 1987--1990
Walsh, J.J.
1990-01-01T23:59:59.000Z
The goal of the previous research during 1987-1990 within the DOE (Department of Energy) Shelf Edge Exchange Processes (SEEP) program in the Mid-Atlantic Bight was to understand the physical and biogeochemical processes effecting the diffusive exchange of the proxies of energy-related, by-products associated with particulate matter between estuarine, shelf, and slope waters on this continental margin. As originally envisioned in the SEEP program plan, SEEP-III would take place at Cape Hatteras to study the advective exchange of materials by a major boundary current. One problem of continuing interest is the determination of the local assimilative capacity of slope waters and sediments off the eastern seaboard of the US to lengthen the pathway between potentially harmful energy by-products and man. At basin scales, realistic specification of the lateral transport by western boundary currents of particulate matter is a necessary input to global models of carbon/nitrogen cycling. Finally, at these global scales, the generic role of continental margins in cycling greenhouse gases, e.g. CO{sub 2}, CH{sub 4}, and N{sub 2}O, is now of equal interest. This continuing research of model construction and evaluation within the SEEP program focuses on all three questions at local, regional, and basin scales. Results from SEEP-I and II are discussed as well as plans for SEEP-III. 14 figs., 3 tabs.
Development of models for series and parallel fan variable air volume terminal units
Furr, James C., Jr
2007-09-17T23:59:59.000Z
collected at four different primary air damper positions. Data were also collected at four different terminal unit fan speeds, controlled by a silicon controlled rectifier (SCR). The models utilized the RMS voltage entering the terminal unit fan, the 'rake...
Emergent Semiclassical Time in Quantum Gravity. I. Mechanical Models
Edward Anderson
2007-11-04T23:59:59.000Z
Strategies intended to resolve the problem of time in quantum gravity by means of emergent or hidden timefunctions are considered in the arena of relational particle toy models. In situations with `heavy' and `light' degrees of freedom, two notions of emergent semiclassical WKB time emerge; these are furthermore equivalent to two notions of emergent classical `Leibniz--Mach--Barbour' time. I futhermore study the semiclassical approach, in a geometric phase formalism, extended to include linear constraints, and with particular care to make explicit those approximations and assumptions used. I propose a new iterative scheme for this in the cosmologically-motivated case with one heavy degree of freedom. I find that the usual semiclassical quantum cosmology emergence of time comes hand in hand with the emergence of other qualitatively significant terms, including back-reactions on the heavy subsystem and second time derivatives. I illustrate my analysis by taking it further for relational particle models with linearly-coupled harmonic oscillator potentials. As these examples are exactly soluble by means outside the semiclassical approach, they are additionally useful for testing the justifiability of some of the approximations and assumptions habitually made in the semiclassical approach to quantum cosmology. Finally, I contrast the emergent semiclassical timefunction with its hidden dilational Euler time counterpart.
Barker, Erin I.; Choi, Kyoo Sil; Sun, Xin; Deda, Erin; Allison, John; Li, Mei; Forsmark, Joy; Zindel, Jacob; Godlewski, Larry
2014-09-30T23:59:59.000Z
Magnesium alloys have become popular alternatives to aluminums and steels for the purpose of vehicle light-weighting. However, Mg alloys are hindered from wider application due to limited ductility as well as poor creep and corrosion performance. Understanding the impact of microstructural features on bulk response is key to improving Mg alloys for more widespread use and for moving towards truly predicting modeling capabilities. This study focuses on modeling the intrinsic features, particularly volume fraction and morphology of beta phase present, of cast Mg alloy microstructure and quantifying their impact on bulk performance. Computational results are compared to experimental measurements of cast plates of Mg alloy with varying aluminum content.
Distinguishing causal time from Minkowski time and a model for the black hole quantum eigenstates
G. 't Hooft
1997-11-18T23:59:59.000Z
A discussion is presented of the principle of black hole com- plementarity. It is argued that this principle could be viewed as a breakdown of general relativity, or alternatively, as the introduction of a time variable with multiple `sheets' or `branches' A consequence of the theory is that the stress-energy tensor as viewed by an outside observer is not simply the Lorentz-transform of the tensor viewed by an ingoing observer. This can serve as a justification of a new model for the black hole atmosphere, recently re-introduced. It is discussed how such a model may lead to a dynamical description of the black hole quantum states.
Daily Time Step Simulation with a Priority Order Based Surface Water Allocation Model
Hoffpauir, Richard James
2011-02-22T23:59:59.000Z
Surface water availability models often use monthly simulation time steps for reasons of data availability, model parameter parsimony, and reduced computational time. Representing realistic streamflow variability, ...
Discrete-Time ARMAv Model-Based Optimal Sensor Placement
Song Wei; Dyke, Shirley J. [Washington University in St. Louis, St. Louis, MO 63130 (United States)
2008-07-08T23:59:59.000Z
This paper concentrates on the optimal sensor placement problem in ambient vibration based structural health monitoring. More specifically, the paper examines the covariance of estimated parameters during system identification using auto-regressive and moving average vector (ARMAv) model. By utilizing the discrete-time steady state Kalman filter, this paper realizes the structure's finite element (FE) model under broad-band white noise excitations using an ARMAv model. Based on the asymptotic distribution of the parameter estimates of the ARMAv model, both a theoretical closed form and a numerical estimate form of the covariance of the estimates are obtained. Introducing the information entropy (differential entropy) measure, as well as various matrix norms, this paper attempts to find a reasonable measure to the uncertainties embedded in the ARMAv model estimates. Thus, it is possible to select the optimal sensor placement that would lead to the smallest uncertainties during the ARMAv identification process. Two numerical examples are provided to demonstrate the methodology and compare the sensor placement results upon various measures.
Multiple-relaxation-time lattice Boltzmann kinetic model for combustion
Xu, Aiguo; Zhang, Guangcai; Li, Yingjun
2014-01-01T23:59:59.000Z
To probe both the Mechanical Non-Equilibrium (MNE) and Thermodynamic Non-Equilibrium (TNE) in the combustion procedure, a two-dimensional Multiple-Relaxation-Time (MRT) version of the Lattice Boltzmann Kinetic Model(LBKM) for combustion phenomena is presented. The chemical energy released in the progress of combustion is dynamically coupled into the system by adding a chemical term to the LB kinetic equation. The LB model is required to recover the Navier-Stokes equations with chemical reaction in the hydrodynamic limit. To that aim, we construct a discrete velocity model with $24$ velocities divided into $3$ groups. In each group a flexible parameter is used to control the size of discrete velocities and a second parameter is used to describe the contribution of the extra degrees of freedom. The current model works for both subsonic and supersonic flows with or without chemical reaction. In this model both the specific-heat ratio and the Prandtl number are flexible, the TNE effects are naturally presented in...
Analysis of real-time reservoir monitoring : reservoirs, strategies, & modeling.
Mani, Seethambal S.; van Bloemen Waanders, Bart Gustaaf; Cooper, Scott Patrick; Jakaboski, Blake Elaine; Normann, Randy Allen; Jennings, Jim (University of Texas at Austin, Austin, TX); Gilbert, Bob (University of Texas at Austin, Austin, TX); Lake, Larry W. (University of Texas at Austin, Austin, TX); Weiss, Chester Joseph; Lorenz, John Clay; Elbring, Gregory Jay; Wheeler, Mary Fanett (University of Texas at Austin, Austin, TX); Thomas, Sunil G. (University of Texas at Austin, Austin, TX); Rightley, Michael J.; Rodriguez, Adolfo (University of Texas at Austin, Austin, TX); Klie, Hector (University of Texas at Austin, Austin, TX); Banchs, Rafael (University of Texas at Austin, Austin, TX); Nunez, Emilio J. (University of Texas at Austin, Austin, TX); Jablonowski, Chris (University of Texas at Austin, Austin, TX)
2006-11-01T23:59:59.000Z
The project objective was to detail better ways to assess and exploit intelligent oil and gas field information through improved modeling, sensor technology, and process control to increase ultimate recovery of domestic hydrocarbons. To meet this objective we investigated the use of permanent downhole sensors systems (Smart Wells) whose data is fed real-time into computational reservoir models that are integrated with optimized production control systems. The project utilized a three-pronged approach (1) a value of information analysis to address the economic advantages, (2) reservoir simulation modeling and control optimization to prove the capability, and (3) evaluation of new generation sensor packaging to survive the borehole environment for long periods of time. The Value of Information (VOI) decision tree method was developed and used to assess the economic advantage of using the proposed technology; the VOI demonstrated the increased subsurface resolution through additional sensor data. Our findings show that the VOI studies are a practical means of ascertaining the value associated with a technology, in this case application of sensors to production. The procedure acknowledges the uncertainty in predictions but nevertheless assigns monetary value to the predictions. The best aspect of the procedure is that it builds consensus within interdisciplinary teams The reservoir simulation and modeling aspect of the project was developed to show the capability of exploiting sensor information both for reservoir characterization and to optimize control of the production system. Our findings indicate history matching is improved as more information is added to the objective function, clearly indicating that sensor information can help in reducing the uncertainty associated with reservoir characterization. Additional findings and approaches used are described in detail within the report. The next generation sensors aspect of the project evaluated sensors and packaging survivability issues. Our findings indicate that packaging represents the most significant technical challenge associated with application of sensors in the downhole environment for long periods (5+ years) of time. These issues are described in detail within the report. The impact of successful reservoir monitoring programs and coincident improved reservoir management is measured by the production of additional oil and gas volumes from existing reservoirs, revitalization of nearly depleted reservoirs, possible re-establishment of already abandoned reservoirs, and improved economics for all cases. Smart Well monitoring provides the means to understand how a reservoir process is developing and to provide active reservoir management. At the same time it also provides data for developing high-fidelity simulation models. This work has been a joint effort with Sandia National Laboratories and UT-Austin's Bureau of Economic Geology, Department of Petroleum and Geosystems Engineering, and the Institute of Computational and Engineering Mathematics.
Spectral Models for Early Time SN 2011fe Observations
Baron, E; Sullivan, M; Hsiao, E; Ellis, R S; Gal-Yam, A; Howell, D A; Nugent, P E; Dominguez, I; Krisciunas, K; Phillips, M M; Suntzeff, N; Wang, L; Thomas, R C
2015-01-01T23:59:59.000Z
We use observed UV through near IR spectra to examine whether SN 2011fe can be understood in the framework of Branch-normal SNe Ia and to examine its individual peculiarities. As a benchmark, we use a delayed-detonation model with a progenitor metallicity of Z_solar/20. We study the sensitivity of features to variations in progenitor metallicity, the outer density profile, and the distribution of radioactive nickel. The effect of metallicity variations in the progenitor have a relatively small effect on the synthetic spectra. We also find that the abundance stratification of SN 2011fe resembles closely that of a delayed detonation model with a transition density that has been fit to other Branch-normal Type Ia supernovae. At early times, the model photosphere is formed in material with velocities that are too high, indicating that the photosphere recedes too slowly or that SN 2011fe has a lower specific energy in the outer ~0.1 M_sun than does the model. We discuss several explanations for the discrepancies. ...
Frolov, Vladimir [Moscow Inst. of Physics and Technology (MIPT), Moscow (Russian Federation); Backhaus, Scott N. [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Chertkov, Michael [Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
2014-01-14T23:59:59.000Z
We explore optimization methods for planning the placement, sizing and operations of Flexible Alternating Current Transmission System (FACTS) devices installed to relieve transmission grid congestion. We limit our selection of FACTS devices to Series Compensation (SC) devices that can be represented by modification of the inductance of transmission lines. Our master optimization problem minimizes the l_{1} norm of the inductance modification subject to the usual line thermal-limit constraints. We develop heuristics that reduce this non-convex optimization to a succession of Linear Programs (LP) which are accelerated further using cutting plane methods. The algorithm solves an instance of the MatPower Polish Grid model (3299 lines and 2746 nodes) in 40 seconds per iteration on a standard laptop—a speed up that allows the sizing and placement of a family of SC devices to correct a large set of anticipated congestions. We observe that our algorithm finds feasible solutions that are always sparse, i.e., SC devices are placed on only a few lines. In a companion manuscript, we demonstrate our approach on realistically-sized networks that suffer congestion from a range of causes including generator retirement. In this manuscript, we focus on the development of our approach, investigate its structure on a small test system subject to congestion from uniform load growth, and demonstrate computational efficiency on a realistically-sized network.
Multiple-relaxation-time lattice Boltzmann kinetic model for combustion
Aiguo Xu; Chuandong Lin; Guangcai Zhang; Yingjun Li
2015-03-13T23:59:59.000Z
To probe both the Hydrodynamic Non-Equilibrium (HNE) and Thermodynamic Non-Equilibrium (TNE) in the combustion process, a two-dimensional Multiple-Relaxation-Time (MRT) version of Lattice Boltzmann Kinetic Model(LBKM) for combustion phenomena is presented. The chemical energy released in the progress of combustion is dynamically coupled into the system by adding a chemical term to the LB kinetic equation. Beside describing the evolutions of the conserved quantities, the density, momentum and energy, which are what the Navier-Stokes model describes, the MRT-LBKM presents also a coarse-grained description on the evolutions of some non-conserved quantities. The current model works for both subsonic and supersonic flows with or without chemical reaction. In this model both the specific-heat ratio and the Prandtl number are flexible, the TNE effects are naturally presented in each simulation step. The model is verified and validated via well-known benchmark tests. As an initial application, various non-equilibrium behaviours, including the complex interplays between various HNEs, between various TNEs and between the HNE and TNE, around the detonation wave in the unsteady and steady one-dimensional detonation processes are preliminarily probed. It is found that the system viscosity (or heat conductivity) decreases the local TNE, but increase the global TNE around the detonation wave, that even locally, the system viscosity (or heat conductivity) results in two kinds of competing trends, to increase and to decrease the TNE effects. The physical reason is that the viscosity (or heat conductivity) takes part in both the thermodynamic and hydrodynamic responses.
Contreras, R. [INAF-Osservatorio Astronomico di Bologna, via Ranzani 1, 40127, Bologna (Italy); Catelan, M. [Departamento de AstronomIa y Astrofisica, Pontificia Universidad Catolica de Chile, Av. Vicuna Mackenna 4860, 782-0436 Macul, Santiago (Chile); Smith, H. A.; Kuehn, C. A. [Department of Physics and Astronomy, Michigan State University, East Lansing, MI 48824 (United States); Pritzl, B. J. [Department of Physics and Astronomy, University of Wisconsin, Oshkosh, WI 54901 (United States); Borissova, J. [Departamento de Fisica y AstronomIa, Facultad de Ciencias, Universidad de ValparaIso, Ave. Gran Bretana 1111, Playa Ancha, Casilla 5030, ValparaIso (Chile)
2010-12-15T23:59:59.000Z
We present new time-series CCD photometry, in the B and V bands, for the moderately metal-rich ([Fe/H] {approx_equal} -1.3) Galactic globular cluster M62 (NGC 6266). The present data set is the largest obtained so far for this cluster and consists of 168 images per filter, obtained with the Warsaw 1.3 m telescope at the Las Campanas Observatory and the 1.3 m telescope of the Cerro Tololo Inter-American Observatory, in two separate runs over the time span of 3 months. The procedure adopted to detect the variable stars was the optimal image subtraction method (ISIS v2.2), as implemented by Alard. The photometry was performed using both ISIS and Stetson's DAOPHOT/ALLFRAME package. We have identified 245 variable stars in the cluster fields that have been analyzed so far, of which 179 are new discoveries. Of these variables, 133 are fundamental mode RR Lyrae stars (RRab), 76 are first overtone (RRc) pulsators, 4 are type II Cepheids, 25 are long-period variables (LPVs), 1 is an eclipsing binary, and 6 are not yet well classified. Such a large number of RR Lyrae stars places M62 among the top two most RR Lyrae-rich (in the sense of total number of RR Lyrae stars present) globular clusters known in the Galaxy, second only to M3 (NGC 5272) with a total of 230 known RR Lyrae stars. Since this study covers most but not all of the cluster area, it is not unlikely that M62 is in fact the most RR Lyrae-rich globular cluster in the Galaxy. In like vein, thanks to the time coverage of our data sets, we were also able to detect the largest sample of LPVs known so far in a Galactic globular cluster. We analyze a variety of Oosterhoff type indicators for the cluster, including mean periods, period distribution, Bailey diagrams, and Fourier decomposition parameters (as well as the physical parameters derived therefrom). All of these indicators clearly show that M62 is an Oosterhoff type I system. This is in good agreement with the moderately high metallicity of the cluster, in spite of its predominantly blue horizontal branch morphology-which is more typical of Oosterhoff type II systems. We thus conclude that metallicity plays a key role in defining Oosterhoff type. Finally, based on an application of the 'A-method', we conclude that the cluster RR Lyrae stars have a similar He abundance as M3, although more work on the temperatures of the M62 RR Lyrae is needed before this result can be conclusively established.
G. Konisi; T. Saito; Z. Maki; M. Nakahara
1998-12-08T23:59:59.000Z
The left-right symmetric model (LRSM) with gauge group $SU(2)_{L} \\times SU(2)_{R} \\times U(1)_{B-L}$ is reconstructed from the geometric formulation of gauge theory in $M_4 \\times Z_2 \\times Z_2$ where $M_4$ is the four-dimensional Minkowski space and $Z_2 \\times Z_2$ the discrete space with four points. The geometrical structure of this model becomes clearer compared with other works based on noncommutative geometry. As a result, the Yukawa coupling terms and the Higgs potential are derived in more restricted forms than in the standard LRSM.
Showalter, Kenneth
developments and experimental applications of feedback control to nonlinear dynamical systems [211]. Recent of Dynamical Systems from Time Series Valery Petrov and Kenneth Showalter* Department of Chemistry, West of multidimensional, nonlinear single-input single-output systems is formulated in terms of an invariant hypersurface
The "Supercritical Pile" Model of GRB: Thresholds, Polarization, Time Lags
Demosthenes Kazanas; Markos Georganopoulos; Apostolos Mastichiadis
2003-11-21T23:59:59.000Z
The essence of the ``Supercritical Pile'' model is a process for converting the energy stored in the relativistic protons of a Relativistic Blast Wave (RBW) of Lorentz factor $\\Gamma$ into electron -- positron pairs of similar Lorentz factor, while at the same time emitting most of the GRB luminosity at an energy $E_p \\simeq 1$ MeV. This is achieved by scattering the synchrotron radiation emitted by the RBW in an upstream located ``mirror'' and then re-intercepting it by the RBW. The repeated scatterings of radiation between the RBW and the ``mirror'', along with the threshold of the pair production reaction $p \\gamma \\to p e^-e^+$, lead to a maximum in the GRB luminosity at an energy $E_p \\simeq 1$ MeV, {\\sl independent of the value of $\\Gamma$}. Furthermore, the same threshold implies that the prompt $\\gamma-$ray emission is only possible for $\\Gamma$ larger than a minimum value, thereby providing a ``natural'' account for the termination of this stage of the GRB as the RBW slows down. Within this model the $\\gamma-$ray ($E \\sim 100$ keV -- 1 MeV) emission process is due to Inverse Compton scattering and it is thus expected to be highly polarized if viewed at angles $\\theta \\simeq 1/\\Gamma$ to the RBW's direction of motion. Finally, the model also predicts lags in the light curves of the lower energy photons with respect to those of higher energy; these are of purely kinematic origin and of magnitude $\\Delta t \\simeq 10^{-2}$ s, in agreement with observation.
Abdelgawad, Marwa
2012-07-16T23:59:59.000Z
are based on a linear model, therefore, the nonlinear model is linearized using the perturbation method. The linear model is validated by comparing its performance with the nonlinear model about a suitable operating point. The control of ignition timing can...
Modeling Metal Fatigue As a Key Step in PV Module Life Time Prediction (Presentation)
Bosco, N.
2012-02-01T23:59:59.000Z
This presentation covers modeling metal fatigue as a key step in photovoltaic (PV) module lifetime predictions. Described are time-dependent and time-independent case studies.
MODELING REAL-TIME HUMAN-AUTOMATION COLLABORATIVE SCHEDULING OF UNMANNED VEHICLES
Cummings, Mary "Missy"
MODELING REAL-TIME HUMAN-AUTOMATION COLLABORATIVE SCHEDULING OF UNMANNED VEHICLES by ANDREW S, Humans and Automation Laboratory Certified by;3 MODELING REAL-TIME HUMAN-AUTOMATION COLLABORATIVE SCHEDULING OF UNMANNED VEHICLES by Andrew S. Clare
Dhar, A. [Enron Corp., Houston, TX (United States); Reddy, T.A. [Drexel Univ., Philadelphia, PA (United States). Civil and Architectural Engineering Dept.; Claridge, D.E. [Texas A and M Univ., College Station, TX (United States). Energy Systems Lab.
1999-02-01T23:59:59.000Z
Accurate modeling of hourly heating and cooling energy use in commercial buildings can be achieved by a Generalized Fourier Series (GFS) approach involving weather variables such as dry-bulb temperature, specific humidity and horizontal solar flux. However, there are situations when only temperature data is available. The objective of this paper is to (i) describe development of a variant of the GFS approach which allows modeling both heating and cooling hourly energy use in commercial buildings with outdoor temperature as the only weather variable and (ii) illustrate its application with monitored hourly data from several buildings in Texas. It is found that the new Temperature based Fourier Series (TFS) approach (1) provides better approximation to heating energy use than the existing GFS approach, (ii) can indirectly account for humidity and solar effects in the cooling energy use, (iii) offers physical insight into the operating pattern of a building HVAC system and (iv) can be used for diagnostic purposes.
Kent, University of
are driving modern real-time control systems from centralized to decentralized architec- tures for the validation and verification of real- time control systems. This paper introduces an algorith- mic methodology to translate the state space visualization of a centralized real-time control system to a decentralized one
Kalman Filter in the Real Time URBIS model Date June 2010
Vuik, Kees
2010-06-03 Kalman Filter in the Real Time URBIS model Date June 2010 Author(s) R. Kranenburg Keywords NOx, Real Time URBIS, Uncertainty, Rijnmond, Kalman filter, Screening process Target Master Thesis Analysis of the uncertainty of the Real Time URBIS model with a Kalman filter 7 1 Introduction 9 2 Model
Invariance and homogenization of an adaptive time gap car-following model
Monneau, Régis
Invariance and homogenization of an adaptive time gap car-following model R. Monneau , M called the adaptive time gap car- following model. This is a system of ODEs which describes the interactions between cars moving on a single line. The time gap is the time that a car needs to reach
C. Tannous; A. Fessant
2001-01-07T23:59:59.000Z
Combustion reaction kinetics models are used for the description of a special class of bursty Financial Time Series. The small number of parameters they depend upon enable financial analysts to predict the time as well as the magnitude of the jump of the value of the portfolio. Several Financial Time Series are analysed within this framework and applications are given.
Modeling and Verification for Timing Satisfaction of Fault-Tolerant Systems with Finiteness
Cheng, Chih-Hong; Esparza, Javier; Knoll, Alois
2009-01-01T23:59:59.000Z
The increasing use of model-based tools enables further use of formal verification techniques in the context of distributed real-time systems. To avoid state explosion, it is necessary to construct a verification model that focuses on the aspects under consideration. In this paper, we discuss how we construct a verification model for timing analysis in distributed real-time systems. We (1) give observations concerning restrictions of timed automata to model these systems, (2) formulate mathematical representations how to perform model-to-model transformation to derive verification models from system models, and (3) propose some theoretical criteria how to reduce the model size. The latter is in particular important, as for the verification of complex systems, an efficient model reflecting the properties of the system under consideration is equally important to the verification algorithm itself. Finally, we present an extension of the model-based development tool FTOS, designed to develop fault-tolerant system...
Time-critical collision handling for deformable modeling
Teschner, Matthias
or surgical simula- tors, where a pre-defined response time should be guaranteed for each simulation step. We- quent simulation step. If an exact response can- not be computed in a given time frame, the algo- rithm forces. Detection, penetration depth estimation and response are di- vided into atomic tasks. In case
Using response times to model student disengagement Joseph E. Beck
Mostow, Jack
for learning a skill. However, learners must be focused on the learning for the time invested to be productive.25 with student learning gains. The novel aspect of this work is that it requires only data normally collected/motivation 1 Introduction Time on task is an important predictor of how well students learn a skill. However
Numerical modeling of fluid flow and time-lapse seismograms ...
gabriela
1. Inst. del Gas y del Petr´oleo - FI, Univ. de Buenos Aires, ARGENTINA. 2 .... 1 + i??s ). (9) where ?e > ?s are relaxation times and Mr = KG,µm. Numerical ...
Unfolding time : a projective model for the moving image
Watkins, Elizabeth Anne
2012-01-01T23:59:59.000Z
Humanity's desire to record events happening in time has spawned a lineage of moving-image transcription systems, from early cinematographs to contemporary digital camcorder equipment. These technologies have arisen, ...
Analyzing California's GHG Reduction Paths using CA-TIMES Energy System Model
California at Davis, University of
@ucdavis.edu NextSTEPS (Sustainable Transportation Energy Pathways) #12;CA-TIMES Model Overview · CA-TIMES helps us understand the role of technologies, resources and policies in California's future energyAnalyzing California's GHG Reduction Paths using CA-TIMES Energy System Model Christopher Yang
Analysis of Competitive Electricity Markets under a New Model of Real-Time Retail Pricing with
Bhatia, Sangeeta
Analysis of Competitive Electricity Markets under a New Model of Real-Time Retail Pricing with Ex@tum.de Abstract--In this paper, we propose a new real-time retail pricing model characterized by ex and robustness properties than pure exant´e pricing. Index Terms--Real-Time Pricing, Market Stability, Economic
Application of time reverse modeling on ultrasonic non-destructive testing of concrete
Application of time reverse modeling on ultrasonic non-destructive testing of concrete Erik H-differences Wave propagation Source localization Non-destructive testing a b s t r a c t Time reverse modeling (TRM is to transform a method within exploration geo- physics to non-destructive testing. In contrast to previous time
Dominici, Francesca
of the mortality and morbidity air pollution effects are 0.42 (95% interval 0.05, 1.18), and 0.31 (95% interval 0 relative rate, Air pollution. Francesca Dominici, Scott L. Zeger, Department of Biostatistics, Jonathan M The potential for air pollution at high concentrations to cause excess deaths and morbidity was firmly establis
A MODEL FOR THE FLEET SIZING OF DEMAND RESPONSIVE TRANSPORTATION SERVICES WITH TIME WINDOWS
Dessouky, Maged
A MODEL FOR THE FLEET SIZING OF DEMAND RESPONSIVE TRANSPORTATION SERVICES WITH TIME WINDOWS Marco a demand responsive transit service with a predetermined quality for the user in terms of waiting time models; Continuous approximation models; Paratransit services; Demand responsive transit systems. #12;3 1
Time consistency and risk averse dynamic decision models ...
2013-05-02T23:59:59.000Z
sistent models as we provide practitioners with an intuitive economic inter- pretation for the ... ning and financial engineering problems. Based on ... consistency is shown to be one basic requirement to get suitable optimal de- cisions, in ...
Dating Concurrent Objects: Real-Time Modeling and Schedulability Analysis
Johnsen, Einar Broch
. This research is partly funded by the EU projects IST-33826 CREDO: Modeling and Analysis of Evolutionary Structures for Distributed Services (http://credo.cwi.nl) and FP7-231620 HATS: Highly Adaptable and Trust
Development of a real-time quantitative hydrologic forecasting model
Bell, John Frank
1986-01-01T23:59:59.000Z
data made in each domain. Fit3ur e 1. Lieatner Radar Carr ection Procedures (by drtmatni ( Bussel I et a 1 . , (97EI ) (Weeks and Hebbert, 1980) and the Boughton Model (Weeks and Hebbert, 1980) are but a few. Models range from sophisticated... of hydroelectric power with existing facilities, $73 million, e) benefits to navigation, $2 million and f) more efFective use of recreational facilities and wildlife habitat, $3 million. Total $485 million The resulting expected benefits in 1983 dollars...
EXPERIMENTS IN MODELING THE SPACE-TIME INDOOR WIRELESS COMMUNICATION CHANNEL
Swindlehurst, A. Lee
include only time of arrival characteris- tics. However, in order to use statistical models in simu to know the statis- tics of the angle of arrival and its correlation with time of arrival. Inthis paper
Modeling genome-wide replication kinetics reveals a mechanism for regulation of replication timing
Bechhoefer, John
Modeling genome-wide replication kinetics reveals a mechanism for regulation of replication timing, University of Massachusetts Medical School, Worcester, MA, USA * Corresponding author. Department of Physics, testable, biochemically plausible mechanism for the regulation of replication timing in eukaryotes
TIME-VARYING CHANNEL MODEL EFFICIENCY Scott Rickard
Drakakis, Konstantinos
with constant radial velocity relative to one an- other. For ease of presentation, we consider in this work the derivation of the Doppler effect, although the resulting channel for elec- tromagnetic waves has a similar path Doppler effect non- relativistic channel. In Section 3 we derive the continuous time
Mining, Modeling, and Analyzing Real-Time Social Trails
Kamath, Krishna Y
2013-05-28T23:59:59.000Z
Real-time social systems are the fastest growing phenomena on the web, enabling millions of users to generate, share, and consume content on a massive scale. These systems are manifestations of a larger trend toward the global sharing of the real...
Space and Time: Wind in an Investment Planning Model
Neuhoff, Karsten; Ehrenmann, A; Butler, Lucy; Cust, J; Hoexter, Harriet; Keats, Kim; Kreczko, Adam; Sinden, Graham
2006-03-14T23:59:59.000Z
in different regions. Given the stock of existing capacity and the new investment the model then solves for the cheapest way to dispatch the system to satisfy demand. This could also involve demand side response, which we currently model to be avail- able... an hourly demand profile for each of the regions of the entire week. To address computational con- straints, we then aggregate the hours of the week into 20 load segments based on the electricity de- mand. We then calculate the average wind output for a...
Lewicki, Jennifer; Lewicki, J.L.; Fischer, M.L.; Hilley, G.E.
2007-10-15T23:59:59.000Z
CO{sub 2} and heat fluxes were measured over a six-week period (09/08/2006 to 10/24/2006) by the eddy covariance (EC) technique at the Horseshoe Lake tree kill (HLTK), Mammoth Mountain, CA, a site with complex terrain and high, spatially heterogeneous CO{sub 2} emission rates. EC CO{sub 2} fluxes ranged from 218 to 3500 g m{sup -2} d{sup -1} (mean = 1346 g m{sup -2} d{sup -1}). Using footprint modeling, EC CO{sub 2} fluxes were compared to CO{sub 2} fluxes measured by the chamber method on a grid repeatedly over a 10-day period. Half-hour EC CO{sub 2} fluxes were moderately correlated (R{sup 2} = 0.42) with chamber fluxes, whereas average-daily EC CO{sub 2} fluxes were well correlated (R{sup 2} = 0.70) with chamber measurements. Average daily EC CO{sub 2} fluxes were correlated with both average daily wind speed and atmospheric pressure; relationships were similar to those observed between chamber CO{sub 2} fluxes and the atmospheric parameters over a comparable time period. Energy balance closure was assessed by statistical regression of EC energy fluxes (sensible and latent heat) against available energy (net radiation, less soil heat flux). While incomplete (R{sup 2} = 0.77 for 1:1 line), the degree of energy balance closure fell within the range observed in many investigations conducted in contrasting ecosystems and climates. Results indicate that despite complexities presented by the HLTK, EC can be reliably used to monitor background variations in volcanic CO{sub 2} fluxes associated with meteorological forcing, and presumably changes related to deeply derived processes such as volcanic activity.
About model of the Universe with accelerated movement of the time
W. B. Belayev
1999-03-30T23:59:59.000Z
Cosmological model based on metric of Fridmann-Robertson-Walker with permanent size and acceleration of time is considered. The problem of the dark matter is analyzed within this model .
Oracle Circuits for Branching-Time Model Checking
Doyen, Laurent
is at least exponen- tially more succinct than its pure-future fragment [LMS02b]. 2 There is a similar model checking problem [LMS01,LMS02a]. However, for some remaining logics, the techniques used in [LMS01,LMS02a] for proving p 2-hardness do not apply. The difficulty here is that, if these prob- lems
Synchronous Closing of Timed SDL Systems for Model Checking
Sidorova, Natalia
the model from a piece of software? additional techniques: 1. abstraction: (a) data abstraction: replace concrete domains by finite, abstract ones (b) control abstraction, i.e., add non-determinism 2. system solutions 1. one-valued data abstraction ¢¡ no external data 2. three-valued timer abstraction 3
REAL-TIME SYSTEMS AND NETWORKS Aspect-based methodology and model-driven tool for real-time embedded
Baudoin, Geneviève
to handle model transformation complexities, improve consistency between control design and its: K. Perko. Real-time embedded control system (RTECS) design follows usually a V-process composed of three major steps: system control analysis (control law design), system specification (software design
Open Universe Modeling: Information Layer and Time Dilation
Baris Baykant Alagoz
2010-11-10T23:59:59.000Z
In this paper, we suppose that the universe has an information processing layer, which coveys the informational contents accompanying the physical events. In this manner, universe is considered to be composed of several associative layers such that one rises on the other layer. Preliminary, we present a method for the analytical treatment of the amount of information processed by universe itself, and then we try to show its correspondence with theories developed for the time dilation and gravitational forces.
Method of modeling transmissions for real-time simulation
Hebbale, Kumaraswamy V.
2012-09-25T23:59:59.000Z
A transmission modeling system includes an in-gear module that determines an in-gear acceleration when a vehicle is in gear. A shift module determines a shift acceleration based on a clutch torque when the vehicle is shifting between gears. A shaft acceleration determination module determines a shaft acceleration based on at least one of the in-gear acceleration and the shift acceleration.
Space-time complexity in solid state models
Bishop, A.R.
1985-01-01T23:59:59.000Z
In this Workshop on symmetry-breaking it is appropriate to include the evolving fields of nonlinear-nonequilibrium systems in which transitions to and between various degrees of ''complexity'' (including ''chaos'') occur in time or space or both. These notions naturally bring together phenomena of pattern formation and chaos and therefore have ramifications for a huge array of natural sciences - astrophysics, plasmas and lasers, hydrodynamics, field theory, materials and solid state theory, optics and electronics, biology, pattern recognition and evolution, etc. Our particular concerns here are with examples from solid state and condensed matter.
First-time measurements will advance turbulence models
Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)
AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level:5 TablesExports(Journal Article)41clothThe Bonneville Power AdministrationHawaiiEnergyFlorida July 9,Department of Energy First-GenerationorderFirst-time
Offin, Dan
Math 421 Fourier Series Autumn 2006 Text: Fourier Series, by Rajendra Bhatia, Math. Assoc. of America, 2005. Topics Covered: Â Ch. 1, Fourier series and the heat equation Â Ch. 2, Convergence of Fourier series Â Ch. 3, Sine and cosine series, arbitrary pe- riods, sin(x)/x, Gibbs's phenomenon Â Ch. 4
Real-time capable first principle based modelling of tokamak turbulent transport
Breton, S; Felici, F; Imbeaux, F; Aniel, T; Artaud, J F; Baiocchi, B; Bourdelle, C; Camenen, Y; Garcia, J
2015-01-01T23:59:59.000Z
A real-time capable core turbulence tokamak transport model is developed. This model is constructed from the regularized nonlinear regression of quasilinear gyrokinetic transport code output. The regression is performed with a multilayer perceptron neural network. The transport code input for the neural network training set consists of five dimensions, and is limited to adiabatic electrons. The neural network model successfully reproduces transport fluxes predicted by the original quasilinear model, while gaining five orders of magnitude in computation time. The model is implemented in a real-time capable tokamak simulator, and simulates a 300s ITER discharge in 10s. This proof-of-principle for regression based transport models anticipates a significant widening of input space dimensionality and physics realism for future training sets. This aims to provide unprecedented computational speed coupled with first-principle based physics for real-time control and integrated modelling applications.
El Nino duration time (month) Dynamic coupling of an ENSO model to the
Goelzer, Heiko
El Nino duration time (month) Dynamic coupling of an ENSO model to the global coupled climate model changes in the thermohaline circulation and changes in the El Nino/Southern Oscillation (ENSO), the Zebiak distribution El Nino event interval (month) · Interval between ENSO events shifted towards longer times
NUMERICAL SOLUTION OF RESERVOIR FLOW MODELS BASED ON LARGE TIME STEP OPERATOR SPLITTING ALGORITHMS
NUMERICAL SOLUTION OF RESERVOIR FLOW MODELS BASED ON LARGE TIME STEP OPERATOR SPLITTING ALGORITHMS and analysis of large time step operator splitting algorithms for the numerical simulation of multiphase flow the main ideas behind these novel operator splitting algorithms for a basic twophase flow model. Special
Discrete-Time, Cyclostationary Phase-Locked Loop Model for Jitter Analysis
Nikolic, Borivoje
Discrete-Time, Cyclostationary Phase-Locked Loop Model for Jitter Analysis Socrates D. Vamvakos Sciences, Berkeley, CA 94720 USA Abstract Â Timing jitter is one of the most significant phase- locked loop to develop the tools necessary to study and predict PLL jitter performance at design time. In this paper
Time delay for dispersive systems in quantum scattering theory. I. The Friedrichs model
Rafael Tiedra de Aldecoa
2008-04-08T23:59:59.000Z
We present a method for proving the existence of time delay (defined in terms of sojourn times) as well as its identity with Eisenbud-Wigner time delay in the case of the Friedrichs model. We show that this method applies to scattering by finite rank potentials.
A Tactical Planning Model for a Production Network with Continuous-Time Control
Graves, Stephen C.
1 A Tactical Planning Model for a Production Network with Continuous-Time Control Chee-Chong Teo1 for production planning, the time period needs to be long enough to coincide with the underlying time buckets network. Subject classifications: Inventory/production: tactical planning that considers tradeoffs between
Real-time system verification techniques based on abstraction/deduction and model checking
Paris-Sud XI, Université de
Real-time system verification techniques based on abstraction/deduction and model checking Eun in or- der to obtain a powerful and highly automatic verification environment for real-time systems. One-Young.Kang@loria.fr Abstract. Our research focuses on verification techniques for real-time systems based on predicate
Ris DTU 09-06-08 Waste-to-energy technologies in TIMES models
(focusing on Denmark) Long tradition for waste incineration for district heating · How to model waste that supply base-load district heating. #12;Risø DTU 09-06-08 13 Modelling new Waste for Energy Technologies-to-energy technologies in the Pan-European NEEDS- TIMES model Waste incineration for electricity and heat, landfill gas
A Time-coherent Model for the Steering of Parallel Simulations
Paris-Sud XI, Université de
A Time-coherent Model for the Steering of Parallel Simulations Aur´elien Esnard, Micha¨el Dussere data. Only VASE [3] proposes a high-level model of simulations based on a control-flow graph (CFG an efficient steering envi- ronment which combines both the temporal coherence and a precise model of parallel
Optimization of Pacing Strategies for Cycling Time Trials Using a Smooth 6-Parameter Endurance Model
Deussen, Oliver
.1. The mechanical - -model As established by [1], the relationship between pedalling power (control variable time trials can be formulated as an optimal control problem, where a mechanical model review approaches that use the 3-parameter critical power model to compute optimal pacing strategies
Modeling and Analysis of Stage Machinery Control Systems by Timed Colored Petri Nets
Paris-Sud XI, Université de
Modeling and Analysis of Stage Machinery Control Systems by Timed Colored Petri Nets Hehua Zhang, is critical to the correctness of a system. Petri nets (PN) have been proven to be a powerful modeling tool Nets (TCPN) are proposed to model and analyze a PLC-based stage machinery control system1
Specific Heat Exponent for the 3-d Ising Model from a 24-th Order High Temperature Series
G. Bhanot; M. Creutz; U. Glaessner; K. Schilling
1993-12-10T23:59:59.000Z
We compute high temperature expansions of the 3-d Ising model using a recursive transfer-matrix algorithm and extend the expansion of the free energy to 24th order. Using ID-Pade and ratio methods, we extract the critical exponent of the specific heat to be alpha=0.104(4).
Modelling and Formal Verification of Timing Aspects in Large PLC Programs
Fernandez Adiego, B; Blanco Vinuela, E; Tournier, J-C; Gonzalez Suarez, V M; Blech, J O
2014-01-01T23:59:59.000Z
One of the main obstacle that prevents model checking from being widely used in industrial control systems is the complexity of building formal models out of PLC programs, especially when timing aspects need to be integrated. This paper brings an answer to this obstacle by proposing a methodology to model and verify timing aspects of PLC programs. Two approaches are proposed to allow the users to balance the trade-off between the complexity of the model, i.e. its number of states, and the set of specifications possible to be verified. A tool supporting the methodology which allows to produce models for different model checkers directly from PLC programs has been developed. Verification of timing aspects for real-life PLC programs are presented in this paper using NuSMV.
Vickers, James
Power Series 16.4 Introduction In this section we consider power series. These are examples of infinite series where each term contains a variable, x, raised to a positive integer power. We use the ratio test to obtain the radius of convergence R, of the power series and state the important result
Duong, Thien Chi
2011-02-22T23:59:59.000Z
. The reason for choosing these applications is that they introduce more control challenges than non-real-time services. One promising flow control strategy was proposed by Bhattacharya and it was based on Model Predictive Control (MPC). The controller...
A Nonlinear Continuous Time Optimal Control Model of Dynamic Pricing and Inventory Control with no
Adida, Elodie
time optimal control model for studying a dynamic pricing and inventory control problem for a make-to-stock of not introducing any approximation to the real setting: it provides the exact solution of the system. When taking
A time-delay approach for the modeling and control of plasma instabilities in thermonuclear fusion
Paris-Sud XI, Université de
1 A time-delay approach for the modeling and control of plasma instabilities in thermonuclear for thermonuclear fusion plasmas. Indeed, advanced plasma confinement scenarios, such as the ones considered
Limited Model Information Control Design for Linear Discrete-Time Systems with Stochastic Parameters
Johansson, Karl Henrik
Limited Model Information Control Design for Linear Discrete-Time Systems with Stochastic systems with stochastically varying parameters. Recently, there have been studies in optimal control subsystems' parameters. There have been many studies in optimal control design for linear discrete
3D weak-dispersion reverse time migration using a stereo-modeling operator
Li, Jingshuang
Reliable 3D imaging is a required tool for developing models of complex geologic structures. Reverse time migration (RTM), as the most powerful depth imaging method, has become the preferred imaging tool because of its ...
Effectiveness of 4D construction modeling in detecting time-space conflicts of construction sites
Nigudkar, Narendra Shriniwas
2005-11-01T23:59:59.000Z
. Reinschmidt Committee Member, Neil N. Eldin Head of Department, James W. Craig August 2005 Major Subject: Construction Management iii ABSTRACT Effectiveness of 4D Construction Modeling in Detecting Time-Space Conflicts...
Duong, Thien Chi
2011-02-22T23:59:59.000Z
FLOW CONTROL OF REAL TIME MULTIMEDIA APPLICATIONS USING MODEL PREDICTIVE CONTROL WITH A FEED FORWARD TERM A Thesis by THIEN CHI DUONG Submitted to the Office of Graduate Studies of Texas A&M University in partial fulfillment... of the requirements for the degree of MASTER OF SCIENCE December 2010 Major Subject: Mechanical Engineering Flow Control of Real Time Multimedia Applications Using Model Predictive Control with Feed Forward Term...
QGP time formation in holographic shock waves model of heavy ion collisions
Aref'eva, Irina Ya
2015-01-01T23:59:59.000Z
We estimate the thermalization time in two colliding shock waves holographic model of heavy-ion collisions. For this purpose we model the process by the Vaidya metric with a horizon defined by the trapped surface location. We consider two bottom-up AdS/QCD models that give, within the colliding shock waves approach, the dependence of multiplicity on the energy compatible with RHIC and LHC results. One model is a bottom-up AdS/QCD confining model and the other is related to an anisotropic thermalization. We estimate the thermalization time and show that increasing the confining potential decreases the thermalization time as well as an anisotropy accelerates the thermalization.
QGP time formation in holographic shock waves model of heavy ion collisions
Irina Ya. Aref'eva
2015-03-07T23:59:59.000Z
We estimate the thermalization time in two colliding shock waves holographic model of heavy-ion collisions. For this purpose we model the process by the Vaidya metric with a horizon defined by the trapped surface location. We consider two bottom-up AdS/QCD models that give, within the colliding shock waves approach, the dependence of multiplicity on the energy compatible with RHIC and LHC results. One model is a bottom-up AdS/QCD confining model and the other is related to an anisotropic thermalization. We estimate the thermalization time and show that increasing the confining potential decreases the thermalization time as well as an anisotropy accelerates the thermalization.
From calls to communities: a model for time varying social networks
Laurent, Guillaume; Karsai, Márton
2015-01-01T23:59:59.000Z
Social interactions vary in time and appear to be driven by intrinsic mechanisms, which in turn shape the emerging structure of the social network. Large-scale empirical observations of social interaction structure have become possible only recently, and modelling their dynamics is an actual challenge. Here we propose a temporal network model which builds on the framework of activity-driven time-varying networks with memory. The model also integrates key mechanisms that drive the formation of social ties - social reinforcement, focal closure and cyclic closure, which have been shown to give rise to community structure and the global connectedness of the network. We compare the proposed model with a real-world time-varying network of mobile phone communication and show that they share several characteristics from heterogeneous degrees and weights to rich community structure. Further, the strong and weak ties that emerge from the model follow similar weight-topology correlations as real-world social networks, i...
space/time and modeling formalisms; extensions: Multilevel modeling in CA
Utrecht, Universiteit
expectation (attractors, mesoscale patterns) · Exploration what happens if we assume.... emergent behaviour MESOSCALE ENTITIES: - discovery and description - modeling these entities -'beyond' dynamical systems (IBM models) PREDEFINED MULTIPLE LEVEL - e.g. predefined cells as mesoscale - multiple timescales
Computer representation of the model covariance function resulting from travel-time tomography
Cerveny, Vlastislav
Computer representation of the model covariance function resulting from travel-time tomography Lud a supplement to the paper by Klime#20;s (2002b) on the stochastic travel{time tomography. It contains brief covariance function is a function of 6 coordinates with pro- nounced singularities. The computer
ForPeerReview Time-varying autoregressive conditional duration model
Morettin, Pedro A.
-stationary processes without preliminary data transformations. The time-varying ACD model estimation was done Introduction As computation power and data storage capacity grows, it becomes possible to gather and analyze, in other words, longer times between transactions indicate less activity of the market. The behavior
Linear Compositional Delay Model for the Timing Analysis of Sub-Powered Combinational Circuits
Linear Compositional Delay Model for the Timing Analysis of Sub-Powered Combinational Circuits the propagation delay through nanometer CMOS circuits is highly desirable. Statistical Static Timing Analysis to accurately capture the circuit behaviour. In view of this we introduce an Inverse Gaussian Distribution (IGD
Modeling and identification of continuous-time system for RF amplifiers
Boyer, Edmond
Modeling and identification of continuous-time system for RF amplifiers Mourad Djamai 1 , Smail present a new identification proce- dure for radio frequency Power Amplifier (PA) in the presence signals in time domain. I. INTRODUCTION Numerous approaches in Power Amplifier identification area have
An Approach of Modeling, Monitoring and Managing Business Operations for Just-In-Time Manufacturing
Li, Haifei
An Approach of Modeling, Monitoring and Managing Business Operations for Just-In-Time Manufacturing execution and monitoring for the JIT (Just In Time) schedule execution. JIT is a manufacturing method to change their manufacturing orders. When a manufacturer receives an order change request, the manufacturer
Discrete-Time Model of an IPMSM Based on Variational Integrators
Noé, Reinhold
implemented on a digital platform, a discrete-time motor model is needed. With respect to the calculation space e.g. in the automotive industry. Hence, the IPMSM is often used as a traction drive in today of the art to realize motor control and motor related functions on a digital platform. Thus, discrete- time
Ferreira, Márcia M. C.
QSPR models of boiling point, octanolwater partition coefficient and retention time index StructureProperty Relationship (QSPR) analysis and study of polycyclic aromatic hydrocarbons (PAHs (bp), octanol water partition coefficient ðlog KowÞ and retention time index (RI) for reversed
Tentzeris, Manos
Modeling and Optimization of RF-MEMS Reconfigurable Tuners with Computationally Efficient Time of Technology, Atlanta, GA 30332 2 Raytheon Company, Tucson AZ, 85734 Abstract -- Modern RF-MEMS device design methods in which the FDTD technique can be used to model a reconfigurable RF-MEMS tuner. A new method
TIME-VARYING LINEAR MODEL APPROXIMATION: APPLICATION TO THERMAL AND AIRFLOW BUILDING SIMULATION
Paris-Sud XI, Université de
TIME-VARYING LINEAR MODEL APPROXIMATION: APPLICATION TO THERMAL AND AIRFLOW BUILDING SIMULATION Nowadays, most of the numerical tools dedicated to simulating the thermal behavior of buildings, consider is demonstrated by its application to the simulation of a multi-zones building. THERMAL AND AIRFLOW MODELS
Carlin, Bradley P.
benefits to patient-reported outcomes (PROs) may add value to the traditional biomedical clinical trial longitudinal PRO measurements and survival outcomes. Model development is motivated by a clinical trialMultilevel Bayesian Models for Survival Times and Longitudinal Patient-Reported Outcomes with Many
Toward Real-Time Simulation of Physics Based Lithium-Ion Battery Models
Subramanian, Venkat
Toward Real-Time Simulation of Physics Based Lithium-Ion Battery Models Venkat R. Subramanian Technological University, Cookeville, Tennessee 38505, USA Recent interest in lithium-ion batteries for electric on the computational efficiency of lithium-ion battery models. This paper presents an effective approach to simulate
A comparative study of continuous-time modelings for scheduling of crude oil operations
Grossmann, Ignacio E.
on its efficient performance for industrial problems. Keywords: Crude oil scheduling; event-based model problem is the first and critical stage of the crude oil refining process. The problem involves crude oilA comparative study of continuous-time modelings for scheduling of crude oil operations Xuan Chena
Modeling and Control for Balanced Timed and Weighted Event Graphs in Dioids
Paris-Sud XI, Université de
1 Modeling and Control for Balanced Timed and Weighted Event Graphs in Dioids Bertrand Cottenceau for which some model matching control problems have been solved. In the context of manufacturing applications, the controllers obtained by these approaches have the effect of regulating material flows
Run-time Modeling and Estimation of Operating System Power Consumption
John, Lizy Kurian
Run-time Modeling and Estimation of Operating System Power Consumption Tao Li Department computing systems point to the need for power modeling and estimation for all components of a system software power evaluation, as well as power management (e.g. dynamic thermal control and equal energy
Long-time integration methods for mesoscopic models of pattern-forming systems
Abukhdeir, Nasser Mohieddin [Department of Chemical Engineering, University of Delaware, Newark, DE (United States); Vlachos, Dionisios G., E-mail: vlachos@udel.ed [Department of Chemical Engineering, University of Delaware, Newark, DE (United States); Katsoulakis, Markos [Department of Mathematics and Statistics, University of Massachusetts, Amherst, MA (United States); Department of Applied Mathematics, University of Crete, Heraklion (Greece); Institute of Applied and Computational Mathematics, Foundation for Research and Technology Hellas, Heraklion (Greece); Plexousakis, Michael [Department of Applied Mathematics, University of Crete, Heraklion (Greece); Institute of Applied and Computational Mathematics, Foundation for Research and Technology Hellas, Heraklion (Greece)
2011-06-20T23:59:59.000Z
Spectral methods for simulation of a mesoscopic diffusion model of surface pattern formation are evaluated for long simulation times. Backwards-differencing time-integration, coupled with an underlying Newton-Krylov nonlinear solver (SUNDIALS-CVODE), is found to substantially accelerate simulations, without the typical requirement of preconditioning. Quasi-equilibrium simulations of patterned phases predicted by the model are shown to agree well with linear stability analysis. Simulation results of the effect of repulsive particle-particle interactions on pattern relaxation time and short/long-range order are discussed.
The IAU Resolutions on Astronomical Reference Systems, Time Scales, and Earth Rotation Models
George H. Kaplan
2006-02-03T23:59:59.000Z
Recent resolutions passed by the International Astronomical Union (IAU) on astronomical reference systems, time scales, and Earth rotation models are the most significant set of international agreements in positional astronomy in several decades. These resolutions, the result of over ten years of international research and study, provide a coherent set of foundational standards for the treatment of astrometric data and the modeling of dynamics in the solar system. This circular explains these resolutions and provides a complete set of practical formulas for their implementation. The six main chapters cover relativity, time scales, the fundamental celestial reference system, ephemerides of solar system bodies, precession and nutation, and modeling the Earth's rotation.
Time-variability of alpha from realistic models of Oklo reactors
C. R. Gould; E. I. Sharapov; S. K. Lamoreaux
2007-04-30T23:59:59.000Z
We reanalyze Oklo $^{149}$Sm data using realistic models of the natural nuclear reactors. Disagreements among recent Oklo determinations of the time evolution of $\\alpha$, the electromagnetic fine structure constant, are shown to be due to different reactor models, which led to different neutron spectra used in the calculations. We use known Oklo reactor epithermal spectral indices as criteria for selecting realistic reactor models. Two Oklo reactors, RZ2 and RZ10, were modeled with MCNP. The resulting neutron spectra were used to calculate the change in the $^{149}$Sm effective neutron capture cross section as a function of a possible shift in the energy of the 97.3-meV resonance. We independently deduce ancient $^{149}$Sm effective cross sections, and use these values to set limits on the time-variation of $\\alpha$. Our study resolves a contradictory situation with previous Oklo $\\alpha$-results. Our suggested $2 \\sigma$ bound on a possible time variation of $\\alpha$ over two billion years is stringent: $ -0.24 \\times 10^{-7} \\le \\frac{\\Delta \\alpha}{\\alpha} \\le 0.11 \\times 10^{-7}$, but model dependent in that it assumes only $\\alpha$ has varied over time.
Kim, Hee-Kyung
2008-01-01T23:59:59.000Z
production function, the optimal allocation of time tofunction, the structural model of household resource allocationfunction. Domestic production model The optimal allocation
Arnold, Jonathan
Series Packages MASTERWORKS · Atlanta Symphony Orchestra and Chorus September 20 · Atlanta PACKAGE · Includes all of the concerts on both the Masterworks and Classics series. Ten performances · This package includes all of the events on the Show Biz and Celebrity Evenings series. Ten performances in all
Exact Primitives for Time Series Data Mining
Mueen, Abdullah Al
2012-01-01T23:59:59.000Z
on Knowledge discovery and data mining, KDD, pages 947–956,on Knowledge discovery and data mining, KDD ’11, pages [15]on Knowledge discovery and data mining, KDD ’03, pages 493–
ADVANCED SPECTRAL METHODS FOR CLIMATIC TIME SERIES
Ide, Kayo
of Atmospheric Sciences and Institute of Geophysics and Planetary Physics, University of California, Los Angeles, Los Angeles, California, USA. 2 Also at De´partement Terre-Atmosphe`re-Oce´an and Labo- ratoire de Me´te´orologie Dynamique, Ecole Normale Su- pe´rieure, Paris, France. 3 Space Science and Technology Department, Rutherford
Time Series Evaluation of Portal Monitor Data
Robinson, Sean M.; Bender, Sarah E.; Lopresti, Charles A.; Woodring, Mitchell L.
2008-12-08T23:59:59.000Z
Radiation portal monitors screen cargo and personal vehicle traffic at international border crossings to detect and interdict illicit sources which may be present in the commerce stream. One difficulty faced by RPM systems is the prospect of false alarms, or undesired alarms due to background fluctuation, or Naturally-Occurring Radioactive Material (NORM) sources in the commerce stream. In general, NORM alarms represent a significant fraction of the nuisance alarms at international border crossings, particularly with Polyvinyl-Toluene (PVT) RPM detectors, which have only very weak spectral differentiation capability. With PVT detectors, the majority of detected photon events fall within the Compton continuum of the material, allowing for very little spectral information to be preserved [1]. Previous work has shown that these detectors can be used for limited spectroscopy, utilizing around 8 spectral bins to further differentiate some NORM and other nuisance sources [2]. NaI based systems achieve much more detailed spectral resolution from each measurement of a source, but still combine all measurements over a vehicle's occupancy in order to arrive at a spectrum to be analyzed.
From time series to superstatistics Christian Beck
Texas at Austin. University of
, a changing mass parameter, a changing amplitude of Gaussian white noise, the fluctuating energy dissipation 18 , solar flares 19 , random networks 20,21 , and mathematical finance 22,23 . In this paper we address a problem that is of great interest in experimental applications. Given an experimentally mea
Learning connections in financial time series
Gartheeban, Ganeshapillai
2014-01-01T23:59:59.000Z
Much of modern financial theory is based upon the assumption that a portfolio containing a diversified set of equities can be used to control risk while achieving a good rate of return. The basic idea is to choose equities ...
Bootstrap Prediction Intervals for Time Series /
Pan, Li
2013-01-01T23:59:59.000Z
Local Bootstrap . . . . . . . . . . . . . . . . . . . . .1.6 Generalized Bootstrap predictionSieve/PRR Bootstrap . . . . . . . . . . . . . . . . . . .
Controlling the coherence in a pure dephasing model for an arbitrarily prescribed time span
Lucio Fassarella
2014-07-12T23:59:59.000Z
We present an open-loop unitary strategy to control the coherence in a pure dephasing model (related to the phase-flip channel) that is able to recover, for whatever prescribed time span, the initial coherence at the end of the control process. The strategy's key idea is to steer the quantum state to the subset of invariant states and keep it there the necessary time, using a fine tuned control Hamiltonian.
Real time assimilation of HF radar currents into a coastal ocean model
Breivik, Øyvind; 10.1016/S0924-7963(01)00002-1
2012-01-01T23:59:59.000Z
A real time assimilation and forecasting system for coastal currents is presented. The purpose of the system is to deliver current analyses and forecasts based on assimilation of high frequency radar surface current measurements. The local Vessel Traffic Service monitoring the ship traffic to two oil terminals on the coast of Norway received the analyses and forecasts in real time. A new assimilation method based on optimal interpolation is presented where spatial covariances derived from an ocean model are used instead of simplified mathematical formulations. An array of high frequency radar antennae provide the current measurements. A suite of nested ocean models comprise the model system. The observing system is found to yield good analyses and short range forecasts that are significantly improved compared to a model twin without assimilation. The system is fast; analysis and six hour forecasts are ready at the Vessel Traffic Service 45 minutes after acquisition of radar measurements.
Fourier series notes and examples
2014-10-14T23:59:59.000Z
The Fourier series are useful for describing periodic phenomena. The advantage that the Fourier series has over Taylor series is that the function itself does not ...
Experiments with a time-dependent, zonally averaged, seasonal, enery balance climatic model
Thompson, Starley Lee
1977-01-01T23:59:59.000Z
EXPERIMENTS WITH A TI&E-DEPENDENT, ZONALLY AVERAGED, SEASONAL, ENERGY BALANCE CLIMATIC MODEL A Thesis by STARLEY LEE THOMPSON Submitted to the Graduate College of Texas ASM University in partial fulfillment of the requirement for the decree... of MASTER OF SCIENCE December 1977 Major Subject: Meteorology EXPERIMENTS WITH A TIME DEPENDENT~ ZONALLY AVERAGED~ SEASONAL, ENERGY BALANCE CLIMATIC MODEL A Thesis by STARLEY LEE THOMPSON Approved as to style and content by: (Chairman of Committee...
Experiments with a time-dependent, zonally averaged, seasonal, enery balance climatic model
Thompson, Starley Lee
1977-01-01T23:59:59.000Z
EXPERIMENTS WITH A TI&E-DEPENDENT, ZONALLY AVERAGED, SEASONAL, ENERGY BALANCE CLIMATIC MODEL A Thesis by STARLEY LEE THOMPSON Submitted to the Graduate College of Texas ASM University in partial fulfillment of the requirement for the decree... of MASTER OF SCIENCE December 1977 Major Subject: Meteorology EXPERIMENTS WITH A TIME DEPENDENT~ ZONALLY AVERAGED~ SEASONAL, ENERGY BALANCE CLIMATIC MODEL A Thesis by STARLEY LEE THOMPSON Approved as to style and content by: (Chairman of Committee...
time algorithm for d-dimensional protein folding in the HP-model
Istrail, Sorin
A 2O(n 1-1 d log n) time algorithm for d-dimensional protein folding in the HP-model Bin Fu Wei Wang Abstract The protein folding problem in the HP-model is NP-hard in both 2D and 3D [4, 6 structure. By studying how proteins fold, their functions can be better understood. The study of protein
Real-time characterization of partially observed epidemics using surrogate models.
Safta, Cosmin; Ray, Jaideep; Lefantzi, Sophia; Crary, David (Applied Research Associates, Arlington, VA); Sargsyan, Khachik; Cheng, Karen (Applied Research Associates, Arlington, VA)
2011-09-01T23:59:59.000Z
We present a statistical method, predicated on the use of surrogate models, for the 'real-time' characterization of partially observed epidemics. Observations consist of counts of symptomatic patients, diagnosed with the disease, that may be available in the early epoch of an ongoing outbreak. Characterization, in this context, refers to estimation of epidemiological parameters that can be used to provide short-term forecasts of the ongoing epidemic, as well as to provide gross information on the dynamics of the etiologic agent in the affected population e.g., the time-dependent infection rate. The characterization problem is formulated as a Bayesian inverse problem, and epidemiological parameters are estimated as distributions using a Markov chain Monte Carlo (MCMC) method, thus quantifying the uncertainty in the estimates. In some cases, the inverse problem can be computationally expensive, primarily due to the epidemic simulator used inside the inversion algorithm. We present a method, based on replacing the epidemiological model with computationally inexpensive surrogates, that can reduce the computational time to minutes, without a significant loss of accuracy. The surrogates are created by projecting the output of an epidemiological model on a set of polynomial chaos bases; thereafter, computations involving the surrogate model reduce to evaluations of a polynomial. We find that the epidemic characterizations obtained with the surrogate models is very close to that obtained with the original model. We also find that the number of projections required to construct a surrogate model is O(10)-O(10{sup 2}) less than the number of samples required by the MCMC to construct a stationary posterior distribution; thus, depending upon the epidemiological models in question, it may be possible to omit the offline creation and caching of surrogate models, prior to their use in an inverse problem. The technique is demonstrated on synthetic data as well as observations from the 1918 influenza pandemic collected at Camp Custer, Michigan.
PERFORMANCE ANALYSIS OF INDUSTRIAL ETHERNET NETWORKS BY MEANS OF TIMED MODEL-CHECKING
Paris-Sud XI, Université de
technologies in manufacturing automation but they have not been specifically intended for industrial controlPERFORMANCE ANALYSIS OF INDUSTRIAL ETHERNET NETWORKS BY MEANS OF TIMED MODEL-CHECKING Daniel Witsch networks are promising for the harmonization of the communication technologies in manufacturing automation
A time-delay approach for the modeling and control of plasma instabilities in thermonuclear fusion
Sipahi, Rifat
for thermonuclear fusion plasmas. Indeed, advanced plasma confinement scenarios, such as the ones considered1 A time-delay approach for the modeling and control of plasma instabilities in thermonuclear fusion Emmanuel WITRANT, Erik OLOFSSON, Silviu-Iulian NICULESCU, March 13, 2009. Abstract This letter
Modeling of Large Scale RF-MEMS Circuits Using Efficient Time-Domain Techniques
Tentzeris, Manos
Modeling of Large Scale RF-MEMS Circuits Using Efficient Time-Domain Techniques N. Bushyager, E Engineering Georgia Institute of Technology Atlanta, GA 30332-0250, USA Abstract RF-MEMS design is made difficult due to the lack of tools capable of simulating both MEMS devices and their surrounding circuits
Climate Projections Using Bayesian Model Averaging and Space-Time Dependence
Haran, Murali
Climate Projections Using Bayesian Model Averaging and Space-Time Dependence K. Sham Bhat, Murali Haran, Adam Terando, and Klaus Keller. Abstract Projections of future climatic changes are a key input to the design of climate change mitiga- tion and adaptation strategies. Current climate change projections
A Real-Time Opponent Modeling System for Rush Football Kennard Laviers
Sukthankar, Gita Reese
A Real-Time Opponent Modeling System for Rush Football Kennard Laviers Department of EECS football game (Rush 2008) to create an au- tonomous offensive team capable of responding to unexpected a popular domain where planning is crucial and accurate plan recognition is possible--American football
Coupling time decoding and trajectory decoding using a target-included model in the motor cortex
Wu, Wei
Coupling time decoding and trajectory decoding using a target-included model in the motor cortex Communicated by D. Erdogmus Available online 27 December 2011 Keywords: Neural decoding Motor cortex Target made within the last decade in motor cortical decoding that predicts movement behaviors from population
Ris-R-1174(EN) RTMOD: Real-Time MODel Evaluation
Risø-R-1174(EN) RTMOD: Real-Time MODel Evaluation Giovanni Graziani and Stefano Galmarini JRC January 2000 #12;Abstract. The 1998 - 1999 RTMOD project is a system based on an automated statistical-friendly interface for data submission and an interactive program module for displaying, intercomparison and analysis
Energy-Aware Modeling and Scheduling of Real-Time Tasks for Dynamic Voltage Scaling
Xu, Cheng-Zhong
scaling (DVS) is an effective approach to power reduction by scaling the processor voltage and frequency the voltage accordingly. On the other hand, a reduction of the operating frequency leads to an increaseEnergy-Aware Modeling and Scheduling of Real-Time Tasks for Dynamic Voltage Scaling Xiliang Zhong
Carlin, Bradley P.
Bayesian hierarchical joint models for longitudinal patient-reported outcomes and survival times in clinical trials Background In many studies of medical treatments, symptoms are measured repeatedly over of a clinical event, called survival observations. One such treatment study provides our motivating data set
Mohaghegh, Shahab
SPE 132643 Intelligent Time Successive Production Modeling Y. Khazaeni, SPE, S. D. Mohaghegh, SPE, West Virginia University Copyright 2010, Society of Petroleum Engineers This paper was prepared of Petroleum Engineers and are subject to correction by the author(s). The material does not necessarily
Control-Oriented Model of a Dual Equal Variable Cam Timing Spark Ignition Engine
Stefanopoulou, Anna
control 1 Introduction. Modern automobile engines must satisfy the challenging and often con icting goals) 248-3611, Phone: (313) 322-1977 y Control Systems Laboratory, Department of Electrical EngineeringControl-Oriented Model of a Dual Equal Variable Cam Timing Spark Ignition Engine A. G
deYoung, Brad
Modelling the distribution, sustainability and diapause emergence timing of the copepod Calanus of population sustainability. We are able to simulate reasonably well the temporal and spatial patterns, however, are dependent upon ships of opportunity, which rarely venture into the mid- and northern Labrador
MODELING SPACE-TIME DEPENDENT HELIUM BUBBLE EVOLUTION IN TUNGSTEN ARMOR UNDER IFE CONDITIONS
Ghoniem, Nasr M.
dependent Helium transport in finite geometries, including the simultaneous transient production of defects of Helium bubbles. I. INTRODUCTION Helium production and helium bubble evolution in neutronMODELING SPACE-TIME DEPENDENT HELIUM BUBBLE EVOLUTION IN TUNGSTEN ARMOR UNDER IFE CONDITIONS Qiyang
TIMES model for the Reunion Island: addressing reliability of electricity supply
Paris-Sud XI, Université de
- sults obtained with a TIMES model dedicated to the supply and power sectors of the Reunion Island. We energy, wind energy, geothermal, or marine power. However, achieving such a wide integration of renewable of the integration of renew- able energy sources on power systems are not adequately assessed. Indeed
Qiu, Qinru
Binghamton University, State University of New York Binghamton, New York, USA {jlu5, sliu5, qwu, qqiuAccurate Modeling and Prediction of Energy Availability in Energy Harvesting Real-Time Embedded}@binghamton.edu Abstract -- Energy availability is the primary subject that drives the research innovations in energy
Boyer, Edmond
Time-dependent model for diluted magnetic semiconductors including band structure and confinement dynamics in confined diluted magnetic semiconductors induced by laser. The hole-spin relaxation process light-induced magnetization dynamics in ferro- magnetic films and in diluted magnetic semiconductors DMS
A Performance Model to Estimate Execution Time of Scientific Workflows on the Cloud
Sakellariou, Rizos
. In the evaluation, three real-world scientific workflows are used to compare the estimated makespan calculatedA Performance Model to Estimate Execution Time of Scientific Workflows on the Cloud Ilia Pietri.K Information Sciences Institute, University of Southern California, USA Abstract--Scientific workflows, which
A TIME DELAY MODEL FOR SOLAR AND STELLAR DYNAMOS A. L. Wilmot-Smith
Dundee, University of
A TIME DELAY MODEL FOR SOLAR AND STELLAR DYNAMOS A. L. Wilmot-Smith School of Mathematics of Dundee, 23 Perth Road, Dundee, DD1 4HN, UK and P. C. H. Martens Department of Physics, Montana State dynamos operating in stellar interiors produce the diverse range of magnetic activity ob- served in solar
Paris-Sud XI, Université de
Parameter identification of nonlinear time-dependent rubber bushings models towards^atenay-Malabry, France Abstract Rubber bushings are extensively-used linking parts in a vehicle chassis that allow of the rubber bushings is useful to describe the significant characteristics of the vehicle's steering behaviour
Multiple-relaxation-time lattice Boltzmann modeling of incompressible flows in porous media
Qing Liu; Ya-Ling He; Chao He
2014-09-20T23:59:59.000Z
In this paper, a two-dimensional eight-velocity (D2Q8) multiple-relaxation-time (MRT) lattice Boltzmann (LB) model is proposed for incompressible porous flows at the representative elementary volume scale based on the Brinkman-Forchheimer-extended Darcy formulation. In the model, the porosity is included into the pressure-based equilibrium moments, and the linear and nonlinear drag forces of the porous media are incorporated into the model by adding a forcing term to the MRT-LB equation in the moment space. Through the Chapman-Enskog analysis, the generalized Navier-Stokes equations can be recovered exactly without artificial compressible errors. Numerical simulations of several typical two-dimensional porous flows are carried out to validate the present MRT-LB model. The numerical results of the present MRT-LB model are in good agreement with the analytical solutions and/or other numerical solutions reported in the literature.
Series Transmission Line Transformer
Buckles, Robert A. (Livermore, CA); Booth, Rex (Livermore, CA); Yen, Boris T. (El Cerrito, CA)
2004-06-29T23:59:59.000Z
A series transmission line transformer is set forth which includes two or more of impedance matched sets of at least two transmissions lines such as shielded cables, connected in parallel at one end ans series at the other in a cascading fashion. The cables are wound about a magnetic core. The series transmission line transformer (STLT) which can provide for higher impedance ratios and bandwidths, which is scalable, and which is of simpler design and construction.
A New Model for Timing Jitter Caused by Device Noise in Current-Mode Logic Frequency Dividers
Oklobdzija, Vojin G.
A New Model for Timing Jitter Caused by Device Noise in Current-Mode Logic Frequency Dividers Marko for predicting timing jitter caused by device noise in current-mode logic (CML) frequency dividers is presented. Device noise transformation into jitter is modeled as a linear time-varying (LTV) process, as opposed
Late time acceleration in a non-commutative model of modified cosmology
B. Malekolkalami; K. Atazadeh; B. Vakili
2014-11-25T23:59:59.000Z
We investigate the effects of noncommutativity between the position-position, position-momentum and momentum-momentum of a phase space corresponding to a modified cosmological model. We show that the existence of such noncommutativity results in a Moyal Poisson algebra between the phase space variables in which the product law between the functions is of the kind of an $\\alpha$-deformed product. We then transform the variables in such a way that the Poisson brackets between the dynamical variables take the form of a usual Poisson bracket but this time with a noncommutative structure. For a power law expression for the function of the Ricci scalar with which the action of the gravity model is modified, the exact solutions in the commutative and noncommutative cases are presented and compared. In terms of these solutions we address the issue of the late time acceleration in cosmic evolution.
Time-dependent models of two-phase accretion discs around black holes
M. Mayer; J. E. Pringle
2006-12-28T23:59:59.000Z
We present time-dependent simulations of a two-phase accretion flow around a black hole. The accretion flow initially is composed of an optically thick and cool disc close to the midplane, while on top and below the disc there is a hot and optically thin corona. We consider several interaction mechanisms as heating of the disc by the corona and Compton cooling of the corona by the soft photons of the disc. Mass and energy can be exchanged between the disc and the corona due to thermal conduction. For the course of this more exploratory work, we limit ourselves to one particular model for a stellar mass black hole accreting at a low accretion rate. We confirm earlier both theoretical and observational results which show that at low accretion rates the disc close to the black hole cannot survive and is evaporated. Given the framework of this model, we now can follow through this phase of disc evaporation time dependently.
Generalized Uncertainty Relations and Long Time Limits for Quantum Brownian Motion Models
C. Anastopoulos; J. J. Halliwell
1994-07-27T23:59:59.000Z
We study the time evolution of the reduced Wigner function for a class of quantum Brownian motion models. We derive two generalized uncertainty relations. The first consists of a sharp lower bound on the uncertainty function, $U = (\\Delta p)^2 (\\Delta q)^2 $, after evolution for time $t$ in the presence of an environment. The second, a stronger and simpler result, consists of a lower bound at time $t$ on a modified uncertainty function, essentially the area enclosed by the $1-\\sigma$ contour of the Wigner function. In both cases the minimizing initial state is a non-minimal Gaussian pure state. These generalized uncertainty relations supply a measure of the comparative size of quantum and thermal fluctuations. We prove two simple inequalites, relating uncertainty to von Neumann entropy, and the von Neumann entropy to linear entropy. We also prove some results on the long-time limit of the Wigner function for arbitrary initial states. For the harmonic oscillator the Wigner function for all initial states becomes a Gaussian at large times (often, but not always, a thermal state). We derive the explicit forms of the long-time limit for the free particle (which does not in general go to a Gaussian), and also for more general potentials in the approximation of high temperature.
Model for Correlating Real-Time Survey Results to Contaminant Concentrations - 12183
Walker, Stuart A. [U.S. Environmental Protection Agency, Washington, DC. 20460 (United States)
2012-07-01T23:59:59.000Z
The U.S. Environmental Protection Agency (EPA) Superfund program is developing a new Counts Per Minute (CPM) calculator to correlate real-time survey results, which are often expressed as counts per minute, to contaminant concentrations that are more typically provided in risk assessments or for cleanup levels, usually expressed in pCi/g or pCi/m{sup 2}. Currently there is no EPA guidance for Superfund sites on correlating count per minute field survey readings back to risk, dose, or other ARAR based concentrations. The CPM calculator is a web-based model that estimates a gamma detector response for a given level of contamination. The intent of the CPM calculator is to facilitate more real-time measurements within a Superfund response framework. The draft of the CPM calculator is still undergoing internal EPA review. This will be followed by external peer review. It is expected that the CPM calculator will at least be in peer review by the time of WM2012 and possibly finalized at that time. The CPM calculator should facilitate greater use of real-time measurement at Superfund sites. The CPM calculator may also standardize the process of converting lab data to real time measurements. It will thus lessen the amount of lab sampling that is needed for site characterization and confirmation surveys, but it will not remove the need for sampling. (authors)
Li, C.; Su, W.; Fang, C. [School of Astronomy and Space Science, Nanjing University, Nanjing 210093 (China); Zhong, S. J. [Department of Mathematics, Southeast University, Nanjing 210096 (China); Wang, L., E-mail: lic@nju.edu.cn [Institute of Space Physics and Applied Technology, Peking University, Beijing 100871 (China)
2014-09-10T23:59:59.000Z
We present a study of the waiting time distributions (WTDs) of solar energetic particle (SEP) events observed with the spacecraft WIND and GOES. The WTDs of both solar electron events (SEEs) and solar proton events (SPEs) display a power-law tail of ??t {sup –?}. The SEEs display a broken power-law WTD. The power-law index is ?{sub 1} = 0.99 for the short waiting times (<70 hr) and ?{sub 2} = 1.92 for large waiting times (>100 hr). The break of the WTD of SEEs is probably due to the modulation of the corotating interaction regions. The power-law index, ? ? 1.82, is derived for the WTD of the SPEs which is consistent with the WTD of type II radio bursts, indicating a close relationship between the shock wave and the production of energetic protons. The WTDs of SEP events can be modeled with a non-stationary Poisson process, which was proposed to understand the waiting time statistics of solar flares. We generalize the method and find that, if the SEP event rate ? = 1/?t varies as the time distribution of event rate f(?) = A?{sup –?}exp (– ??), the time-dependent Poisson distribution can produce a power-law tail WTD of ??t {sup ?} {sup –3}, where 0 ? ? < 2.
Fourier Series and Integrals Fourier Series
Mehta, Pankaj
(x) can be expanded in a Fourier series f(x) = a0 2 + n=1 an cos nx L + bn sin nx L , (1a) or expansion, multiply Eq. (1) by cos nx L or sin nx L and integrate over the interval. For this calculation, we need the basic orthogonality relation of the basis functions: L -L cos nx L cos mx L dx = mnL, (3
Real-Time Multi-Sensor Multi-Source Network Data Fusion Using Dynamic Traffic Assignment Models
Ben-Akiva, Moshe E.
This paper presents a model-based data fusion framework that allows systematic fusing of multi-sensor multi-source traffic network data at real-time. Using simulation-based Dynamic Traffic Assignment (DTA) models, the ...
Estimating Reaction Rate Coefficients Within a Travel-Time Modeling Framework
Gong, R [Georgia Institute of Technology; Lu, C [Georgia Institute of Technology; Luo, Jian [Georgia Institute of Technology; Wu, Wei-min [Stanford University; Cheng, H. [Stanford University; Criddle, Craig [Stanford University; Kitanidis, Peter K. [Stanford University; Gu, Baohua [ORNL; Watson, David B [ORNL; Jardine, Philip M [ORNL; Brooks, Scott C [ORNL
2011-03-01T23:59:59.000Z
A generalized, efficient, and practical approach based on the travel-time modeling framework is developed to estimate in situ reaction rate coefficients for groundwater remediation in heterogeneous aquifers. The required information for this approach can be obtained by conducting tracer tests with injection of a mixture of conservative and reactive tracers and measurements of both breakthrough curves (BTCs). The conservative BTC is used to infer the travel-time distribution from the injection point to the observation point. For advection-dominant reactive transport with well-mixed reactive species and a constant travel-time distribution, the reactive BTC is obtained by integrating the solutions to advective-reactive transport over the entire travel-time distribution, and then is used in optimization to determine the in situ reaction rate coefficients. By directly working on the conservative and reactive BTCs, this approach avoids costly aquifer characterization and improves the estimation for transport in heterogeneous aquifers which may not be sufficiently described by traditional mechanistic transport models with constant transport parameters. Simplified schemes are proposed for reactive transport with zero-, first-, nth-order, and Michaelis-Menten reactions. The proposed approach is validated by a reactive transport case in a two-dimensional synthetic heterogeneous aquifer and a field-scale bioremediation experiment conducted at Oak Ridge, Tennessee. The field application indicates that ethanol degradation for U(VI)-bioremediation is better approximated by zero-order reaction kinetics than first-order reaction kinetics.
Salvaggio, Carl
images representing what an airborne or satellite thermal infrared imaging sensor would record. The scene sensors to a point where the model can be usedas a research tool to evaluate the limitations in our infrared (TIR) imagery generated by midwave (3-5 Rm) and longwave (8-14 pm) sensors is being increasingly
Jackson, Robert B.
decomposition data with process-based biogeochemical models is essential to quantify the turnover of organic to model multiple cohort decomposition, unifying both types of experimental data in one theory. Based models with a single time-dependent decay rate, and two models based on a continuous distribution
Model-independent plotting of the cosmological scale factor as a function of lookback time
Ringermacher, H. I.; Mead, L. R., E-mail: ringerha@gmail.com, E-mail: Lawrence.mead@usm.edu [Department of Physics and Astronomy, University of Southern Mississippi, Hattiesburg, MS 39406 (United States)
2014-11-01T23:59:59.000Z
In this work we describe a model-independent method of developing a plot of scale factor a(t) versus lookback time t{sub L} from the usual Hubble diagram of modulus data against redshift. This is the first plot of this type. We follow the model-independent methodology of Daly and Djorgovski used for their radio-galaxy data. Once the a(t)data plot is completed, any model can be applied and will display as described in the standard literature. We then compile an extensive data set to z = 1.8 by combining Type Ia supernovae (SNe Ia) data from SNLS3 of Conley et al., high-z SNe data of Riess et al., and radio-galaxy data of Daly and Djorgovski to validate the new plot. We first display these data on a standard Hubble diagram to confirm the best fit for ?CDM cosmology, and thus validate the joined data set. The scale factor plot is then developed from the data and the ?CDM model is again displayed from a least-squares fit. The fit parameters are in agreement with the Hubble diagram fit confirming the validity of the new plot. Of special interest is the transition time of the universe, which in the scale factor plot will appear as an inflection point in the data set. Noise is more visible in this presentation, which is particularly sensitive to inflection points of any model displayed in the plot, unlike on a modulus-z diagram, where there are no inflection points and the transition-z is not at all obvious by inspection. We obtain a lower limit of z ? 0.6. It is evident from this presentation that there is a dearth of SNe data in the range z = 1-2, exactly the range necessary to confirm a ?CDM transition-z around z = 0.76. We then compare a 'toy model' wherein dark matter is represented as a perfect fluid with an equation of state p = –(1/3) ? to demonstrate the plot sensitivity to model choice. Its density varies as 1/t {sup 2} and it enters the Friedmann equations as ?{sub dark}/t {sup 2}, replacing only the ?{sub dark}/a {sup 3} term. The toy model is a close match to ?CDM, but separates from it on the scale factor plot for similar ?CDM density parameters. It is described in the Appendix. A more complete transition time analysis will be presented in a future paper.
Skolski, J. Z. P., E-mail: j.z.p.skolski@utwente.nl; Vincenc Obona, J. [Materials innovation institute M2i, Faculty of Engineering Technology, Chair of Applied Laser Technology, University of Twente, P.O. Box 217, 7500 AE Enschede (Netherlands); Römer, G. R. B. E.; Huis in 't Veld, A. J. [Faculty of Engineering Technology, Chair of Applied Laser Technology, University of Twente, P.O. Box 217, 7500 AE Enschede (Netherlands)
2014-03-14T23:59:59.000Z
A model predicting the formation of laser-induced periodic surface structures (LIPSSs) is presented. That is, the finite-difference time domain method is used to study the interaction of electromagnetic fields with rough surfaces. In this approach, the rough surface is modified by “ablation after each laser pulse,” according to the absorbed energy profile, in order to account for inter-pulse feedback mechanisms. LIPSSs with a periodicity significantly smaller than the laser wavelength are found to “grow” either parallel or orthogonal to the laser polarization. The change in orientation and periodicity follow from the model. LIPSSs with a periodicity larger than the wavelength of the laser radiation and complex superimposed LIPSS patterns are also predicted by the model.
A cyclic time-dependent Markov process to model daily patterns in wind turbine power production
Scholz, Teresa; Estanqueiro, Ana
2013-01-01T23:59:59.000Z
Wind energy is becoming a top contributor to the renewable energy mix, which raises potential reliability issues for the grid due to the fluctuating nature of its source. To achieve adequate reserve commitment and to promote market participation, it is necessary to provide models that can capture daily patterns in wind power production. This paper presents a cyclic inhomogeneous Markov process, which is based on a three-dimensional state-space (wind power, speed and direction). Each time-dependent transition probability is expressed as a Bernstein polynomial. The model parameters are estimated by solving a constrained optimization problem: The objective function combines two maximum likelihood estimators, one to ensure that the Markov process long-term behavior reproduces the data accurately and another to capture daily fluctuations. A convex formulation for the overall optimization problem is presented and its applicability demonstrated through the analysis of a case-study. The proposed model is capable of r...
Test Cases for Wind Power Plant Dynamic Models on Real-Time Digital Simulator: Preprint
Singh, M.; Muljadi, E.; Gevorgian, V.
2012-06-01T23:59:59.000Z
The objective of this paper is to present test cases for wind turbine generator and wind power plant models commonly used during commissioning of wind power plants to ensure grid integration compatibility. In this paper, different types of wind power plant models based on the Western Electricity Coordinating Council Wind Generator Modeling Group's standardization efforts are implemented on a real-time digital simulator, and different test cases are used to gauge their grid integration capability. The low-voltage ride through and reactive power support capability and limitations of wind turbine generators under different grid conditions are explored. Several types of transient events (e.g., symmetrical and unsymmetrical faults, frequency dips) are included in the test cases. The differences in responses from different types of wind turbine are discussed in detail.
The time evolution of cosmological redshift in non-standard dark energy models
Balbi, A
2007-01-01T23:59:59.000Z
The variation of the expansion rate of the universe with time produces an evolution in the cosmological redshift of distant sources (for example quasars), that might be directly observed (over a decade or so) by future ultra stable, high-resolution spectrographs (such as CODEX) coupled to extremely large telescopes (such as ESO's ELT). This would open a new window to explore the physical mechanism responsible for the current acceleration of the universe. We investigate the evolution of cosmological redshift from a variety of non-standard dark energy models, and compare it with simulated data based on realistic assumptions. We perform a Fisher matrix analysis, in order to estimate the expected constraints on the parameters of the models. We find that there are interesting prospects for constraining the parameters of non-standard dark energy models and for discriminating among competing candidates.
Kalueff, Allan V.
adaptation, computer software, or by similar or dissimilar methodology now known or hereafter developed + Business Media made a renewed commitment to this series. The new program will focus on methods
Kalueff, Allan V.
analysis. Use in connection with any form of information storage and retrieval, electronic adaptation Science + Business Media made a renewed commitment to this series. The new program will focus on methods
Fourier series and periodicity
Donal F. Connon
2014-12-07T23:59:59.000Z
A large number of the classical texts dealing with Fourier series more or less state that the hypothesis of periodicity is required for pointwise convergence. In this paper, we highlight the fact that this condition is not necessary.
Introduction to Fourier Series
2014-10-15T23:59:59.000Z
Oct 15, 2014 ... The Basics. Fourier series. Examples. Even and odd functions. Definition. A function f(x) is said to be even if f(-x) = f(x). The function f(x) is said ...
A multiscale MDCT image-based breathing lung model with time-varying regional ventilation
Yin, Youbing, E-mail: youbing-yin@uiowa.edu [Department of Mechanical and Industrial Engineering, The University of Iowa, Iowa City, IA 52242 (United States) [Department of Mechanical and Industrial Engineering, The University of Iowa, Iowa City, IA 52242 (United States); IIHR-Hydroscience and Engineering, The University of Iowa, Iowa City, IA 52242 (United States); Department of Radiology, The University of Iowa, Iowa City, IA 52242 (United States); Choi, Jiwoong, E-mail: jiwoong-choi@uiowa.edu [Department of Mechanical and Industrial Engineering, The University of Iowa, Iowa City, IA 52242 (United States) [Department of Mechanical and Industrial Engineering, The University of Iowa, Iowa City, IA 52242 (United States); IIHR-Hydroscience and Engineering, The University of Iowa, Iowa City, IA 52242 (United States); Hoffman, Eric A., E-mail: eric-hoffman@uiowa.edu [Department of Radiology, The University of Iowa, Iowa City, IA 52242 (United States); Department of Biomedical Engineering, The University of Iowa, Iowa City, IA 52242 (United States); Department of Internal Medicine, The University of Iowa, Iowa City, IA 52242 (United States); Tawhai, Merryn H., E-mail: m.tawhai@auckland.ac.nz [Auckland Bioengineering Institute, The University of Auckland, Auckland (New Zealand); Lin, Ching-Long, E-mail: ching-long-lin@uiowa.edu [Department of Mechanical and Industrial Engineering, The University of Iowa, Iowa City, IA 52242 (United States) [Department of Mechanical and Industrial Engineering, The University of Iowa, Iowa City, IA 52242 (United States); IIHR-Hydroscience and Engineering, The University of Iowa, Iowa City, IA 52242 (United States)
2013-07-01T23:59:59.000Z
A novel algorithm is presented that links local structural variables (regional ventilation and deforming central airways) to global function (total lung volume) in the lung over three imaged lung volumes, to derive a breathing lung model for computational fluid dynamics simulation. The algorithm constitutes the core of an integrative, image-based computational framework for subject-specific simulation of the breathing lung. For the first time, the algorithm is applied to three multi-detector row computed tomography (MDCT) volumetric lung images of the same individual. A key technique in linking global and local variables over multiple images is an in-house mass-preserving image registration method. Throughout breathing cycles, cubic interpolation is employed to ensure C{sub 1} continuity in constructing time-varying regional ventilation at the whole lung level, flow rate fractions exiting the terminal airways, and airway deformation. The imaged exit airway flow rate fractions are derived from regional ventilation with the aid of a three-dimensional (3D) and one-dimensional (1D) coupled airway tree that connects the airways to the alveolar tissue. An in-house parallel large-eddy simulation (LES) technique is adopted to capture turbulent-transitional-laminar flows in both normal and deep breathing conditions. The results obtained by the proposed algorithm when using three lung volume images are compared with those using only one or two volume images. The three-volume-based lung model produces physiologically-consistent time-varying pressure and ventilation distribution. The one-volume-based lung model under-predicts pressure drop and yields un-physiological lobar ventilation. The two-volume-based model can account for airway deformation and non-uniform regional ventilation to some extent, but does not capture the non-linear features of the lung.
Photon and neutrino spectra of time-dependent photospheric models of gamma-ray bursts
Asano, K. [Institute for Cosmic Ray Research, The University of Tokyo, 5-1-5 Kashiwanoha, Kashiwa, Chiba 277-8582 (Japan); Mészáros, P., E-mail: asanok@icrr.u-tokyo.ac.jp, E-mail: nnp@astro.psu.edu [Department of Astronomy and Astrophysics, Department of Physics, Center for Particle and Gravitational Astrophysics, Pennsylvania State University, University Park, PA 16802 (United States)
2013-09-01T23:59:59.000Z
Thermal photons from the photosphere may be the primary source of the observed prompt emission of gamma-ray bursts (GRBs). In order to produce the observed non-thermal spectra, some kind of dissipation mechanism near the photosphere is required. In this paper we numerically simulate the evolution of the photon spectrum in a relativistically expanding shell with a time-dependent numerical code. We consider two basic models. One is a leptonic model, where a dissipation mechanism heats the thermal electrons maintaining their high temperature. The other model involves a cascade process induced by pp(pn)-collisions which produce high-energy electrons, modify the thermal spectrum, and emit neutrinos. The qualitative properties of the photon spectra are mainly determined by the optical depth at which the dissipation mechanism sets in. Too large optical depths lead to a broad and curved spectrum contradicting the observations, while for optical depths smaller than unity the spectral hardness becomes softer than observed. A significant shift of the spectral peak energy to higher energies due to a large energy injection can lead to an overly broad spectral shape. We show ideal parameter ranges for which these models are able to reproduce the observed spectra. For the pn-collision model, the neutrino fluence in the 10–100 GeV range is well above the atmospheric neutrino fluence, but its detection is challenging for presently available detectors.
Stochastic Modeling and Power Control of Time-Varying Wireless Communication Networks
Olama, Mohammed M [ORNL; Djouadi, Seddik M [ORNL; Charalambous, Prof. Charalambos [University of Cyprus
2014-01-01T23:59:59.000Z
Wireless networks are characterized by nodes mobility, which makes the propagation environment time-varying and subject to fading. As a consequence, the statistical characteristics of the received signal vary continuously, giving rise to a Doppler power spectral density (DPSD) that varies from one observation instant to the next. This paper is concerned with dynamical modeling of time-varying wireless fading channels, their estimation and parameter identification, and optimal power control from received signal measurement data. The wireless channel is characterized using a stochastic state-space form and derived by approximating the time-varying DPSD of the channel. The expected maximization and Kalman filter are employed to recursively identify and estimate the channel parameters and states, respectively, from online received signal strength measured data. Moreover, we investigate a centralized optimal power control algorithm based on predictable strategies and employing the estimated channel parameters and states. The proposed models together with the estimation and power control algorithms are tested using experimental measurement data and the results are presented.
Analysis Of Residence Time Distribution Of Fluid Flow By Axial Dispersion Model
Sugiharto [Department of Physics, Faculty of Mathematics and Natural Sciences, Bandung Institute of Technology, Jl. Ganesha 10, Bandung 40132 (Indonesia); Centre for Applications of Isotopes and Radiation Technology-National Nuclear Energy Agency, Jl. Lebak Bulus Raya No. 49, Jakarta 12440 (Indonesia); Su'ud, Zaki; Kurniadi, Rizal; Waris, Abdul [Centre for Applications of Isotopes and Radiation Technology-National Nuclear Energy Agency, Jl. Lebak Bulus Raya No. 49, Jakarta 12440 (Indonesia); Abidin, Zainal [Department of Physics, Faculty of Mathematics and Natural Sciences, Bandung Institute of Technology, Jl. Ganesha 10, Bandung 40132 (Indonesia)
2010-12-23T23:59:59.000Z
Radioactive tracer {sup 82}Br in the form of KBr-82 with activity {+-} 1 mCi has been injected into steel pipeline to qualify the extent dispersion of water flowing inside it. Internal diameter of the pipe is 3 in. The water source was originated from water tank through which the water flow gravitically into the pipeline. Two collimated sodium iodide detectors were used in this experiment each of which was placed on the top of the pipeline at the distance of 8 and 11 m from injection point respectively. Residence time distribution (RTD) curves obtained from injection of tracer are elaborated numerically to find information of the fluid flow properties. The transit time of tracer calculated from the mean residence time (MRT) of each RTD curves is 14.9 s, therefore the flow velocity of the water is 0.2 m/s. The dispersion number, D/uL, for each RTD curve estimated by using axial dispersion model are 0.055 and 0.06 respectively. These calculations are performed after fitting the simulated axial dispersion model on the experiment curves. These results indicated that the extent of dispersion of water flowing in the pipeline is in the category of intermediate.
Paris-Sud XI, Université de
/Simulink simulations. Key words: power system harmonics, power electronic, linear time periodic modeling, PWM, control1 POWER ELECTRONICS HARMONIC ANALYSIS BASED ON THE LINEAR TIME PERIODIC MODELING. APPLICATIONS in power electronic systems. The considered system is described by a set of differential equations, which
A late time accelerated FRW model with scalar and vector fields via Noether symmetry
Babak Vakili
2014-10-22T23:59:59.000Z
We study the evolution of a three-dimensional minisuperspace cosmological model by the Noether symmetry approach. The phase space variables turn out to correspond to the scale factor of a flat Friedmann-Robertson-Walker (FRW) model, a scalar field with potential function $V(\\phi)$ with which the gravity part of the action is minimally coupled and a vector field of its kinetic energy is coupled with the scalar field by a coupling function $f(\\phi)$. Then, the Noether symmetry of such a cosmological model is investigated by utilizing the behavior of the corresponding Lagrangian under the infinitesimal generator of the desired symmetry. We explicitly calculate the form of the coupling function between the scalar and the vector fields and also the scalar field potential function for which such symmetry exists. Finally, by means of the corresponding Noether current, we integrate the equations of motion and obtain exact solutions for the scale factor, scalar and vector fields. It is shown that the resulting cosmology is an accelerated expansion universe for which its expansion is due to the presence of the vector field in the early times, while the scalar field is responsible of its late time expansion.
Frontiers in Computational and Information Sciences Seminar Series
Frontiers in Computational and Information Sciences Seminar Series Programming Models in the Exascale Era Presented by... Professor Barbara Chapman Department of Computer Science University of Houston
SQUARE SUMMABLE POWER SERIES Louis de Branges Preface ...
1911-01-10T23:59:59.000Z
The construction of the space Q and the verification of its properties are ..... model of the linear system is constructed in a Hilbert space of power series with ...
The shortest time and/or the shortest path strategies in a CA FF pedestrian dynamics model
Ekaterina Kirik; Tat'yana Yurgel'yan; Dmitriy Krouglov
2009-06-23T23:59:59.000Z
This paper deals with a mathematical model of a pedestrian movement. A stochastic cellular automata (CA) approach is used here. The Floor Field (FF) model is a basis model. FF models imply that virtual people follow the shortest path strategy. But people are followed by a strategy of the shortest time as well. This paper is focused on how to mathematically formalize and implement to a model these features of the pedestrian movement. Some results of a simulation are presented.
Time-dependent modeling of radiative processes in hot magnetized plasmas
Indrek Vurm; Juri Poutanen
2009-03-03T23:59:59.000Z
Numerical simulations of radiative processes in magnetized compact sources such as hot accretion disks around black holes, relativistic jets in active galaxies and gamma-ray bursts are complicated because the particle and photon distributions span many orders of magnitude in energy, they also strongly depend on each other, the radiative processes behave significantly differently depending on the energy regime, and finally due to the enormous difference in the time-scales of the processes. We have developed a novel computer code for the time-dependent simulations that overcomes these problems. The processes taken into account are Compton scattering, electron-positron pair production and annihilation, Coulomb scattering as well as synchrotron emission and absorption. No approximation has been made on the corresponding rates. For the first time, we solve coupled integro-differential kinetic equations for photons and electrons/positrons without any limitations on the photon and lepton energies. A numerical scheme is proposed to guarantee energy conservation when dealing with synchrotron processes in electron and photon equations. We apply the code to model non-thermal pair cascades in the blackbody radiation field, to study the synchrotron self-absorption as particle thermalization mechanism, and to simulate time evolution of stochastically heated pairs and corresponding synchrotron self-Compton photon spectra which might be responsible for the prompt emission of gamma-ray bursts. Good agreement with previous works is found in the parameter regimes where comparison is feasible, with the differences attributable to our improved treatment of the microphysics.
Fission time-scale in experiments and in multiple initiation model
Karamian, S. A., E-mail: karamian@nrmail.jinr.ru [Joint Institute for Nuclear Research (Russian Federation)
2011-12-15T23:59:59.000Z
Rate of fission for highly-excited nuclei is affected by the viscose character of the systemmotion in deformation coordinates as was reported for very heavy nuclei with Z{sub C} > 90. The long time-scale of fission can be described in a model of 'fission by diffusion' that includes an assumption of the overdamped diabatic motion. The fission-to-spallation ratio at intermediate proton energy could be influenced by the viscosity, as well. Within a novel approach of the present work, the cross examination of the fission probability, time-scales, and pre-fission neutron multiplicities is resulted in the consistent interpretation of a whole set of the observables. Earlier, different aspects could be reproduced in partial simulations without careful coordination.
RodrÃguez, Rodolfo
Analysis of a FEM-BEM model posed on the conducting domain for the time-dependent eddy currentÂ´atica, Universidad de ConcepciÂ´on, Casilla 160-C, Concepcion, Chile. Abstract The three-dimensional eddy current time. Keywords: Boundary elements; eddy current problem; finite elements; time-dependent electromagnetic problem
Stringy models of modified gravity: space-time defects and structure formation
Mavromatos, Nick E.; Sakellariadou, Mairi; Yusaf, Muhammad Furqaan, E-mail: nikolaos.mavromatos@kcl.ac.uk, E-mail: mairi.sakellariadou@kcl.ac.uk, E-mail: muhammad.yusaf@kcl.ac.uk [King's College London, Department of Physics, Strand, London WC2R 2LS (United Kingdom)
2013-03-01T23:59:59.000Z
Starting from microscopic models of space-time foam, based on brane universes propagating in bulk space-times populated by D0-brane defects (''D-particles''), we arrive at effective actions used by a low-energy observer on the brane world to describe his/her observations of the Universe. These actions include, apart from the metric tensor field, also scalar (dilaton) and vector fields, the latter describing the interactions of low-energy matter on the brane world with the recoiling point-like space-time defect (D-particle). The vector field is proportional to the recoil velocity of the D-particle and as such it satisfies a certain constraint. The vector breaks locally Lorentz invariance, which however is assumed to be conserved on average in a space-time foam situation, involving the interaction of matter with populations of D-particle defects. In this paper we clarify the role of fluctuations of the vector field on structure formation and galactic growth. In particular we demonstrate that, already at the end of the radiation era, the (constrained) vector field associated with the recoil of the defects provides the seeds for a growing mode in the evolution of the Universe. Such a growing mode survives during the matter dominated era, provided the variance of the D-particle recoil velocities on the brane is larger than a critical value. We note that in this model, as a result of specific properties of D-brane dynamics in the bulk, there is no issue of overclosing the brane Universe for large defect densities. Thus, in these models, the presence of defects may be associated with large-structure formation. Although our string inspired models do have (conventional, from a particle physics point of view) dark matter components, nevertheless it is interesting that the role of ''extra'' dark matter is also provided by the population of massive defects. This is consistent with the weakly interacting character of the D-particle defects, which predominantly interact only gravitationally.
Nonlinear Time Domain Modeling and Simulation of Surface and Embedded NPPS
Office of Environmental Management (EM)
AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level:5 TablesExports to3,1,50022,3,,0,,6,1,Separation 23 362 of Thomas P.Oil,J. B. CardellConverDyn| Department of Energy Nonlinear Time Domain Modeling
Modeling, Real-Time Estimation, and Identification of UWB Indoor Wireless Channels
Olama, Mohammed M [ORNL] [ORNL; Djouadi, Seddik M [ORNL] [ORNL; Li, Yanyan [ORNL] [ORNL; Fathy, Aly [University of Tennessee (UT)] [University of Tennessee (UT)
2013-01-01T23:59:59.000Z
In this paper, stochastic differential equations (SDEs) are used to model ultrawideband (UWB) indoor wireless channels. We show that the impulse responses for time-varying indoor wireless channels can be approximated in a mean square sense as close as desired by impulse responses that can be realized by SDEs. The state variables represent the inphase and quadrature components of the UWB channel. The expected maximization and extended Kalman filter are employed to recursively identify and estimate the channel parameters and states, respectively, from online received signal strength measured data. Both resolvable and non-resolvable multipath received signals are considered and represented as small-scaled Nakagami fading. The proposed models together with the estimation algorithm are tested using UWB indoor measurement data demonstrating the method s viability and the results are presented.
A symbolic model approach to the digital control of nonlinear time-delay systems
Pola, Giordano; Di Benedetto, Maria D; Tabuada, Paulo
2009-01-01T23:59:59.000Z
Time-delay systems are an important class of dynamical systems which provide a solid mathematical framework to deal with many application domains of interest ranging from biology, chemical, electrical, and mechanical engineering, to economics. However, the inherent complexity of such systems poses serious difficulties to control design, when control objectives depart from the standard ones investigated in the current literature, e.g. stabilization, regulation, and etc. In this paper we propose one approach to control design, which is based on the construction of symbolic models, where each symbolic state and each symbolic label correspond to an aggregate of continuous states and to an aggregate of input signals in the original system. The use of symbolic models offers a systematic methodology for control design in which constraints coming from software and hardware, interacting with the physical world, can be integrated. The main contribution of this paper is in showing that incrementally input-to-state stabl...
Models of the Time Variability of BHC: Light Curves, PSD, Lags
Demosthenes Kazanas
2000-01-13T23:59:59.000Z
We present a model for the aperiodic variablity of accreting Black Hole Candidates (BHC) along with model light curves. According to the model this variability is the combined outcome of random (Poisson) injection of soft photons near the center of an extended {\\sl inhomogeneous} distribution of hot electrons (similar to those advocated by the ADAF or ADIOS flows) and the stochastic nature of Compton scattering which converts these soft photons into the observed high energy radiation. Thus, the timing properties (PSD, lags, coherence) of the BHC light curves reflect, to a large extent, the properties of the scattering medium (which in this approximation acts as a combination of a {\\sl linear} amplifier/filter) and they can be used to probe its structure, most notably the density profile of the scattering medium. The model accounts well for the observed PSDs and lags and also the reduction in the RMS variability and the increase in the characteristic PSD frequencies with increasing source luminosity. The electron density profiles obtained to date are consistent mainly with those of ADIOS but also with pure ADAF flows.
Scheichl, Robert
2013-01-01T23:59:59.000Z
shed light on the rich phenomenology of both the original and extended adaptive voter models, includingRogers, T. C. and Gross, T. (2013) Consensus time and conformity in the adaptive voter model in the adaptive voter model Tim Rogers Centre for Networks and Collective Behaviour, Department of Mathematical
Liberzon, Daniel
International Conference on FormalInternational Conference on Formal ModellingModelling andand, SwedenFORMATS 2005, Uppsala, Sweden #12;International Conference on FormalInternational Conference on the specification language Interface to Theorem Provers Simulator Model checking #12;International Conference
John Ondov; Gregory Beachley
2007-07-05T23:59:59.000Z
In previous studies, 11 elements (Al, As, Cd, Cr, Cu, Fe, Mn, Ni, Pb, Se, and Zn) were determined in 30-minute aerosol samples collected with the University of Maryland Semicontinuous Elements in Aerosol Sampler (SEAS; Kidwell and Ondov, 2001, 2004; SEAS-II) in several locations in which air quality is influenced by emissions from coal- or oil-fired power plants. At this time resolution, plumes from stationary high temperature combustion sources are readily detected as large excursions in ambient concentrations of elements emitted by these sources (Pancras et al. ). Moreover, the time-series data contain intrinsic information on the lateral diffusion of the plume (e.g., {sigma}{sub y}), which Park et al. (2005 and 2006) have exploited in their Pseudo-Deterministic Receptor Model (PDRM), to calculate emission rates of SO{sub 2} and 11 elements (mentioned above) from four individual coal- and oil-fired power plants in the Tampa Bay area. In the current project, we proposed that the resolving power of source apportionment methods might be improved by expanding the set of maker species and that there exist some optimum set of marker species that could be used. The ultimate goal was to determine the utility of using additional elements to better identify and isolate contributions of individual power plants to ambient levels of PM and its constituents. And, having achieved better resolution, achieve, also, better emission rate estimates. In this study, we optimized sample preparation and instrumental protocols for simultaneous analysis of 28 elements in dilute slurry samples collected with the SEAS with a new state-of-the-art Thermo-Systems, Inc., X-series II, Inductively Coupled Plasma Mass Spectroscopy (ICP-MS), and reanalyzed the samples previously collected in Tampa during the modeling period studied by Park et al. (2005) in which emission rates from four coal- and oil-fired power plants affected air quality at the sampling site. In the original model, Park et al. (2005), included 6 sources. Herein, we reassessed the number of contributing sources in light of the new data. A comprehensive list of sources was prepared and both our Gaussian Plume model and PMF were used to identify and predict the relative strengths of source contributions at the receptor sites. Additionally, PDRM was modified to apply National Inventory Emissions, Toxic Release Inventory, and Chemical Mass Balance source profile data to further constrain solutions. Both the original Tampa data set (SO{sub 2} plus 11 elements) and the new expanded data set (SO{sub 2} plus 23 elements) were used to resolve the contributions of particle constituents and PM to sources using Positive Matrix Factorization (PMF) and PDRM.
DOE Public Access Gateway for Energy & Science Beta (PAGES Beta)
Lowe, Douglas; Archer-Nicholls, Scott; Morgan, Will; Allan, James D.; Utembe, Steve; Ouyang, Bin; Aruffo, Eleonora; Le Breton, Michael; Zaveri, Rahul A.; di Carlo, Piero; et al
2015-01-01T23:59:59.000Z
Chemical modelling studies have been conducted over north-western Europe in summer conditions, showing that night-time dinitrogen pentoxide (N2O5) heterogeneous reactive uptake is important regionally in modulating particulate nitrate and has a~modest influence on oxidative chemistry. Results from Weather Research and Forecasting model with Chemistry (WRF-Chem) model simulations, run with a detailed volatile organic compound (VOC) gas-phase chemistry scheme and the Model for Simulating Aerosol Interactions and Chemistry (MOSAIC) sectional aerosol scheme, were compared with a series of airborne gas and particulate measurements made over the UK in July 2010. Modelled mixing ratios of key gas-phase species were reasonably accurate (correlationsmore »with measurements of 0.7–0.9 for NO2 and O3). However modelled loadings of particulate species were less accurate (correlation with measurements for particulate sulfate and ammonium were between 0.0 and 0.6). Sulfate mass loadings were particularly low (modelled means of 0.5–0.7 ?g kg?1air, compared with measurements of 1.0–1.5 ?g kg?1air). Two flights from the campaign were used as test cases – one with low relative humidity (RH) (60–70%), the other with high RH (80–90%). N2O5 heterogeneous chemistry was found to not be important in the low-RH test case; but in the high-RH test case it had a strong effect and significantly improved the agreement between modelled and measured NO3 and N2O5. When the model failed to capture atmospheric RH correctly, the modelled NO3 and N2O5 mixing ratios for these flights differed significantly from the measurements. This demonstrates that, for regional modelling which involves heterogeneous processes, it is essential to capture the ambient temperature and water vapour profiles. The night-time NO3 oxidation of VOCs across the whole region was found to be 100–300 times slower than the daytime OH oxidation of these compounds. The difference in contribution was less for alkenes (× 80) and comparable for dimethylsulfide (DMS). However the suppression of NO3 mixing ratios across the domain by N2O5 heterogeneous chemistry has only a very slight, negative, influence on this oxidative capacity. The influence on regional particulate nitrate mass loadings is stronger. Night-time N2O5 heterogeneous chemistry maintains the production of particulate nitrate within polluted regions: when this process is taken into consideration, the daytime peak (for the 95th percentile) of PM10 nitrate mass loadings remains around 5.6 ?g kg?1air, but the night-time minimum increases from 3.5 to 4.6 ?g kg?1air. The sustaining of higher particulate mass loadings through the night by this process improves model skill at matching measured aerosol nitrate diurnal cycles and will negatively impact on regional air quality, requiring this process to be included in regional models.« less
Decoherence Models for Discrete-Time Quantum Walks and their Application to Neutral Atom Experiments
Andrea Alberti; Wolfgang Alt; Reinhard Werner; Dieter Meschede
2014-12-26T23:59:59.000Z
We discuss decoherence in discrete-time quantum walks in terms of a phenomenological model that distinguishes spin and spatial decoherence. We identify the dominating mechanisms that affect quantum walk experiments realized with neutral atoms walking in an optical lattice. From the measured spatial distributions, we determine with good precision the amount of decoherence per step, which provides a quantitative indication of the quality of our quantum walks. In particular, we find that spin decoherence is the main mechanism responsible for the loss of coherence in our experiment. We also find that the sole observation of ballistic instead of diffusive expansion in position space is not a good indicator for the range of coherent delocalization. We provide further physical insight by distinguishing the effects of short and long time spin dephasing mechanisms. We introduce the concept of coherence length in the discrete-time quantum walk, which quantifies the range of spatial coherences. Unexpectedly, we find that quasi-stationary dephasing does not modify the local properties of the quantum walk, but instead affects spatial coherences. For a visual representation of decoherence phenomena in phase space, we have developed a formalism based on a discrete analogue of the Wigner function. We show that the effects of spin and spatial decoherence differ dramatically in momentum space.
Multi-fluid transport code modeling of time-dependent recycling in ELMy H-mode
Pigarov, A. Yu.; Krasheninnikov, S. I.; Hollmann, E. M. [University of California at San Diego, La Jolla, California 92093 (United States); Rognlien, T. D.; Lasnier, C. J. [Lawrence Livermore National Laboratory, Livermore, California 94551 (United States); Unterberg, E. [Oak Ridge National Laboratory, Oak Ridge, Tennessee 37831 (United States)
2014-06-15T23:59:59.000Z
Simulations of a high-confinement-mode (H-mode) tokamak discharge with infrequent giant type-I ELMs are performed by the multi-fluid, multi-species, two-dimensional transport code UEDGE-MB, which incorporates the Macro-Blob approach for intermittent non-diffusive transport due to filamentary coherent structures observed during the Edge Localized Modes (ELMs) and simple time-dependent multi-parametric models for cross-field plasma transport coefficients and working gas inventory in material surfaces. Temporal evolutions of pedestal plasma profiles, divertor recycling, and wall inventory in a sequence of ELMs are studied and compared to the experimental time-dependent data. Short- and long-time-scale variations of the pedestal and divertor plasmas where the ELM is described as a sequence of macro-blobs are discussed. It is shown that the ELM recovery includes the phase of relatively dense and cold post-ELM divertor plasma evolving on a several ms scale, which is set by the transport properties of H-mode barrier. The global gas balance in the discharge is also analyzed. The calculated rates of working gas deposition during each ELM and wall outgassing between ELMs are compared to the ELM particle losses from the pedestal and neutral-beam-injection fueling rate, correspondingly. A sensitivity study of the pedestal and divertor plasmas to model assumptions for gas deposition and release on material surfaces is presented. The performed simulations show that the dynamics of pedestal particle inventory is dominated by the transient intense gas deposition into the wall during each ELM followed by continuous gas release between ELMs at roughly a constant rate.
Multi-fluid transport code modeling of time-dependent recycling in ELMy H-mode
Pigarov, A. Yu. [University of California, San Diego; Krasheninnikov, S. I. [University of California, La Jolla; Rognlien, T. D. [Lawrence Livermore National Laboratory (LLNL); Hollmann, E. M. [University of California, San Diego; Lasnier, C. J. [Lawrence Livermore National Laboratory (LLNL); Unterberg, Ezekial A [ORNL
2014-01-01T23:59:59.000Z
Simulations of a high-confinement-mode (H-mode) tokamak discharge with infrequent giant type-I ELMs are performed by the multi-fluid, multi-species, two-dimensional transport code UEDGE-MB, which incorporates the Macro-Blob approach for intermittent non-diffusive transport due to filamentary coherent structures observed during the Edge Localized Modes (ELMs) and simple time-dependent multi-parametric models for cross-field plasma transport coefficients and working gas inventory in material surfaces. Temporal evolutions of pedestal plasma profiles, divertor recycling, and wall inventory in a sequence of ELMs are studied and compared to the experimental time-dependent data. Short- and long-time-scale variations of the pedestal and divertor plasmas where the ELM is described as a sequence of macro-blobs are discussed. It is shown that the ELM recovery includes the phase of relatively dense and cold post-ELM divertor plasma evolving on a several ms scale, which is set by the transport properties of H-mode barrier. The global gas balance in the discharge is also analyzed. The calculated rates of working gas deposition during each ELM and wall outgassing between ELMs are compared to the ELM particle losses from the pedestal and neutral-beam-injection fueling rate, correspondingly. A sensitivity study of the pedestal and divertor plasmas to model assumptions for gas deposition and release on material surfaces is presented. The performed simulations show that the dynamics of pedestal particle inventory is dominated by the transient intense gas deposition into the wall during each ELM followed by continuous gas release between ELMs at roughly a constant rate.
Time-Dependent Modeling of Gamma-ray Flares in Blazar PKS1510-089
Saito, Shinya; Tanaka, Yasuyuki; Takahashi, Tadayuki; Sikora, Marek; Moderski, Rafal
2015-01-01T23:59:59.000Z
Here we present a new approach for constraining luminous blazars, incorporating fully time-dependent and self-consistent modeling of bright gamma-ray flares of PKS1510-089 resolved with Fermi-LAT, in the framework of the internal shock scenario. The results of our modeling imply the location of the gamma-ray flaring zone outside of the broad-line region, namely around 0.3pc from the core for a free-expanding jet with the opening angle Gamma, \\theta_\\mathrm{jet} \\simeq 1 (where Gamma is the jet bulk Lorentz factor), up to \\simeq 3pc for a collimated outflow with Gamma, \\theta_\\mathrm{jet} \\simeq 0.1. Moreover, under the Gamma, \\theta_\\mathrm{jet} \\simeq 1 condition, our modeling indicates the maximum efficiency of the jet production during the flares, with the total jet energy flux strongly dominated by protons and exceeding the available accretion power in the source. This is in contrast to the quiescence states of the blazar, characterized by lower jet kinetic power and an approximate energy equipartition be...
Briceno, Luis Diego [Colorado State University, Fort Collins; Khemka, Bhavesh [Colorado State University, Fort Collins; Siegel, Howard Jay [Colorado State University, Fort Collins; Maciejewski, Anthony A [ORNL; Groer, Christopher S [ORNL; Koenig, Gregory A [ORNL; Okonski, Gene D [ORNL; Poole, Stephen W [ORNL
2011-01-01T23:59:59.000Z
This study considers a heterogeneous computing system and corresponding workload being investigated by the Extreme Scale Systems Center (ESSC) at Oak Ridge National Laboratory (ORNL). The ESSC is part of a collaborative effort between the Department of Energy (DOE) and the Department of Defense (DoD) to deliver research, tools, software, and technologies that can be integrated, deployed, and used in both DOE and DoD environments. The heterogeneous system and workload described here are representative of a prototypical computing environment being studied as part of this collaboration. Each task can exhibit a time-varying importance or utility to the overall enterprise. In this system, an arriving task has an associated priority and precedence. The priority is used to describe the importance of a task, and precedence is used to describe how soon the task must be executed. These two metrics are combined to create a utility function curve that indicates how valuable it is for the system to complete a task at any given moment. This research focuses on using time-utility functions to generate a metric that can be used to compare the performance of different resource schedulers in a heterogeneous computing system. The contributions of this paper are: (a) a mathematical model of a heterogeneous computing system where tasks arrive dynamically and need to be assigned based on their priority, precedence, utility characteristic class, and task execution type, (b) the use of priority and precedence to generate time-utility functions that describe the value a task has at any given time, (c) the derivation of a metric based on the total utility gained from completing tasks to measure the performance of the computing environment, and (d) a comparison of the performance of resource allocation heuristics in this environment.
Agilent Infiniium 90000 Series
Anlage, Steven
s1 Agilent Infiniium 90000 Series Oscilloscopes Programmer's Reference #12;Notices © Agilent laws. Manual Part Number Version 04.50.0000 Edition May 28, 2013 Available in electronic format only), as applicable in any technical data. Safety Notices CAUTION A CAUTION notice denotes a haz- ard. It calls
Energy Management Webinar Series
Broader source: Energy.gov [DOE]
Boost your knowledge on how to implement an energy management system through this four-part webinar series from the Superior Energy Performance program. Each webinar introduces various elements of the ISO 50001 energy management standard—based on the Plan-Do-Check-Act approach—and the associated steps of DOE's eGuide for ISO 50001 software tool.
Klein, Ophir
Bay Area Global Health Seminar Series Monday, January 27, 2014 2:30pm 4:00pm (Reception to follow at the Center for Health Policy and the Woods Institute for the Environment. He studies how economic, political, and natural environments affect population health in developing countries using a mix of experimental
Klein, Ophir
Bay Area Global Health Seminar Series Moving beyond millennium targets in global health: The challenges of investing in health and universal health coverage Although targets can help to focus global health efforts, they can also detract attention from deeper underlying challenges in global health
Fernandez, Thomas
Programming Dilip P. Ahalpara Institute for Plasma Research, Near Indira Bridge, Gandhinagar-382428, India
Giannakis, Georgios
, France. G. B. Giannakis was with the Department of Electrical Engineering, University of Virginia of Minnesota, Minneapolis, MN 55455 USA. F. Gini is with Dipartimento di Ingegneria dell' Informazione
Vieira, Veronica M.; Weinberg, Janice M.; Webster, Thomas F.
2012-01-01T23:59:59.000Z
data using generalized additive modeling. BMC Public HealthTibshirani R: Generalized Additive Models. London: Chapmanapplication using generalized additive models. Int J Health
Numerical wind speed simulation model
Ramsdell, J.V.; Athey, G.F.; Ballinger, M.Y.
1981-09-01T23:59:59.000Z
A relatively simple stochastic model for simulating wind speed time series that can be used as an alternative to time series from representative locations is described in this report. The model incorporates systematic seasonal variation of the mean wind, its standard deviation, and the correlation speeds. It also incorporates systematic diurnal variation of the mean speed and standard deviation. To demonstrate the model capabilities, simulations were made using model parameters derived from data collected at the Hanford Meteorology Station, and results of analysis of simulated and actual data were compared.
Yue-Liang Wu
2007-01-22T23:59:59.000Z
Based on a maximally symmetric minimal unification hypothesis and a quantum charge-dimension correspondence principle, it is demonstrated that each family of quarks and leptons belongs to the Majorana-Weyl spinor representation of 14-dimensions that relate to quantum spin-isospin-color charges. Families of quarks and leptons attribute to a spinor structure of extra 6-dimensions that relate to quantum family charges. Of particular, it is shown that 10-dimensions relating to quantum spin-family charges form a motional 10-dimensional quantum space-time with a generalized Lorentz symmetry SO(1,9), and 10-dimensions relating to quantum isospin-color charges become a motionless 10-dimensional quantum intrinsic space. Its corresponding 32-component fermions in the spinor representation possess a maximal gauge symmetry SO(32). As a consequence, a maximally symmetric minimal unification model SO(32) containing three families in ten dimensional quantum space-time is naturally obtained by choosing a suitable Majorana-Weyl spinor structure into which quarks and leptons are directly embedded. Both resulting symmetry and dimensions coincide with the ones of type I string and heterotic string SO(32) in string theory.
Hering, Amanda S.
2010-10-12T23:59:59.000Z
relating wind speed to power output. This proposed loss measure yields more insight into the true value of each model's predictions. One method of evaluating time series forecasts, such as wind speed forecasts, is to test the null hypothesis...
Rangaswami, Raju
network routing protocols can be categorised as analytical, simulation-based, and emulation-based. Here we146 Int. J. Simulation and Process Modelling, Vol. 5, No. 2, 2009 Real-time network simulation integrates the open-source XORP router implementation with a real-time large-scale network simulation engine
Combustion Phasing Model for Control of a Gasoline-Ethanol Fueled SI Engine with Variable Valve an interest in both alternative fuels and new engine technologies such as variable valve timing to improve equipped with variable valve timing (VVT), a technology which allows increased control of the quantity
Henrik Stenlund
2012-04-24T23:59:59.000Z
This work introduces a new functional series for expanding an analytic function in terms of an arbitrary analytic function. It is generally applicable and straightforward to use. It is also suitable for approximating the behavior of a function with a few terms. A new expression is presented for the composite function's n'th derivative. The inverse-composite method is handled in this work also.
. Hedin, Ion Cyclotron Heating in Toroidal Plasmas, Ph.D. thesis, Royal Institute of Technology StockholmTowards a 3D time dependent Fokker-Planck solver for modelling RF heating in realistic tokamak supercomputers and the need for predictive tools to guide the experiments, modelling radio frequency heating
Shekhar, Ravi
2009-05-15T23:59:59.000Z
and amplitude variation with offset (AVO) results for our example model predicts that CO2 is easier to detect than brine in the fractured reservoirs. The effects of geochemical processes on seismics are simulated by time-lapse modeling for t = 1000 years. My...
Modeling of Packet Loss and Delay and Their E ect on Real-Time Multimedia Service Quality
Yang, Junfeng
Modeling of Packet Loss and Delay and Their E#11;ect on Real-Time Multimedia Service Quality Wenyu Jiang, Henning Schulzrinne fwenyu,schulzrinneg@cs.columbia.edu Department of Computer Science Columbia of Forward Error Correction (FEC). To char- acterize this burstiness, we #12;rst discuss the modeling
Stefanelli, Ulisse
FOR SHAPE-MEMORY ALLOYS SERGIO FRIGERI AND ULISSE STEFANELLI Abstract. We prove the global existence of solutions for a shape-memory alloys constitutive model at finite strains. The model has been presented within a constructive time-discretization procedure. 1. Introduction Shape-memory alloys (SMAs) show
ARC Collaborative Research Seminar Series Winter 2009
Papalambros, Panos
and uncertainty. In this talk, recent developments of a design methodology considering the product lifecycle cost in a series-system fashion. The lifecycle cost includes the production cost, the inspection cost Recent Developments in Time-Dependent Reliability and Design for Lifecycle Cost Amandeep Singh, Zissimos
LANL* V1.0: a radiation belt drift shell model suitable for real-time and reanalysis applications
Koller, Josep [Los Alamos National Laboratory; Reeves, Geoffrey D [Los Alamos National Laboratory; Friedel, Reiner H W [Los Alamos National Laboratory
2008-01-01T23:59:59.000Z
Space weather modeling, forecasts, and predictions, especially for the radiation belts in the inner magnetosphere, require detailed information about the Earth's magnetic field. Results depend on the magnetic field model and the L* (pron. L-star) values which are used to describe particle drift shells. Space wather models require integrating particle motions along trajectories that encircle the Earth. Numerical integration typically takes on the order of 10{sup 5} calls to a magnetic field model which makes the L* calculations very slow, in particular when using a dynamic and more accurate magnetic field model. Researchers currently tend to pick simplistic models over more accurate ones but also risking large inaccuracies and even wrong conclusions. For example, magnetic field models affect the calculation of electron phase space density by applying adiabatic invariants including the drift shell value L*. We present here a new method using a surrogate model based on a neural network technique to replace the time consuming L* calculations made with modern magnetic field models. The advantage of surrogate models (or meta-models) is that they can compute the same output in a fraction of the time while adding only a marginal error. Our drift shell model LANL* (Los Alamos National Lab L-star) is based on L* calculation using the TSK03 model. The surrogate model has currently been tested and validated only for geosynchronous regions but the method is generally applicable to any satellite orbit. Computations with the new model are several million times faster compared to the standard integration method while adding less than 1% error. Currently, real-time applications for forecasting and even nowcasting inner magnetospheric space weather is limited partly due to the long computing time of accurate L* values. Without them, real-time applications are limited in accuracy. Reanalysis application of past conditions in the inner magnetosphere are used to understand physical processes and their effect. Without sufficiently accurate L* values, the interpretation of reanalysis results becomes difficult and uncertain. However, with a method that can calculate accurate L* values orders of magnitude faster, analyzing whole solar cycles worth of data suddenly becomes feasible.
Michael, Panayiotis Adamos
2015-01-01T23:59:59.000Z
in active databases: Model and implementation”. In VLDB,Bassam Islam, "Stack Database Model/View of Multimedia Data"implementing a fragmented database model of Spatio-Temporal
Saskatchewan, University of
lter Eco-friendly,GoodTCO,and Easy Operation The VPL-E Series is an Excellent Choice for Education consumption, allowing users to make significant savings on their electricity expenses. Simple Projector in education or business. The values are approximate. VPL-EX120 Conventional Model 6000 hours Longer Lamp
Liu, Qing
2015-01-01T23:59:59.000Z
In this paper, a double multiple-relaxation-time lattice Boltzmann model is developed for simulating transient solid-liquid phase change problems in porous media at the representative elementary volume scale. The model uses two different multiple-relaxation-time lattice Boltzmann equations, one for the flow field and the other for the temperature field with nonlinear latent heat source term. The model is based on the generalized non-Darcy formulation, and the solid-liquid phase change interface is traced through the liquid fraction which is determined by the enthalpy method. The model is validated by numerical simulations of conduction melting in a semi-infinite space, solidification in a semi-infinite corner, and convection melting in a square cavity filled with porous media. The numerical results demonstrate the efficiency and accuracy of the present model for simulating transient solid-liquid phase change problems in porous media.
Sequential Monte Carlo in Model Comparison: Example in Cellular Dynamics in Systems Biology
Richardson, David
: American Statistical Association (2009): 1274-1287. Abstract Sequential Monte Carlo analysis of time series. Mukherjee L. You M. West -- Published in: JSM Proceedings/Bayesian Statistical Science. Alexandria, VA statistical model assessment is really just beginning in this new field. Single cell time series data
Climate induced changes in benthic macrofauna--A non-linear model approach Karin Junker a,
Dippner, Joachim W.
Climate induced changes in benthic macrofauna--A non-linear model approach Karin Junker a, , Dusan macrofauna communities Climate indices Neural network Climate variability Time series forecasting Regime-nearest neighbours" (OPKNN) are applied to relate various climate indices to time series of biomass, abun- dance
J. R. Morris
1995-11-10T23:59:59.000Z
A supersymmetric extension of the $U(1)\\times U(1)^{\\prime }$-Higgs bosonic superconducting cosmic string model is considered,and the constraints imposed upon such a model due to renormalizability, supersymmetry, and gauge invariance are examined. For a simple model with a single $U(1)$ chiral superfield and a single $% U(1)^{\\prime }$ chiral superfield, the Witten mechanism for bosonic superconductivity (giving rise to long range gauge fields outside of the string) does not exist. The simplest model that can accommodate the requisite interactions requires five chiral supermultiplets. This superconducting cosmic string solution is investigated.
The U-series toolbox for paleoceanography Gideon M. Henderson
Henderson, Gideon
Uranium has a reasonably constant seawater concentration in both space and time, varying only in line-mail: boba@ldeo.columbia.edu Reviews in Mineralogy and Geochemistry "Uranium Series Geochemistry" Revised (Cochran and Masque, 2003). 2. U-series isotopes in the ocean environment 2.1 The ocean uranium budget
Hart, W.E.; Istrail, S. [Sandia National Labs., Albuquerque, NM (United States). Algorithms and Discrete Mathematics Dept.
1996-08-09T23:59:59.000Z
This paper considers the protein structure prediction problem for lattice and off-lattice protein folding models that explicitly represent side chains. Lattice models of proteins have proven extremely useful tools for reasoning about protein folding in unrestricted continuous space through analogy. This paper provides the first illustration of how rigorous algorithmic analyses of lattice models can lead to rigorous algorithmic analyses of off-lattice models. The authors consider two side chain models: a lattice model that generalizes the HP model (Dill 85) to explicitly represent side chains on the cubic lattice, and a new off-lattice model, the HP Tangent Spheres Side Chain model (HP-TSSC), that generalizes this model further by representing the backbone and side chains of proteins with tangent spheres. They describe algorithms for both of these models with mathematically guaranteed error bounds. In particular, the authors describe a linear time performance guaranteed approximation algorithm for the HP side chain model that constructs conformations whose energy is better than 865 of optimal in a face centered cubic lattice, and they demonstrate how this provides a 70% performance guarantee for the HP-TSSC model. This is the first algorithm in the literature for off-lattice protein structure prediction that has a rigorous performance guarantee. The analysis of the HP-TSSC model builds off of the work of Dancik and Hannenhalli who have developed a 16/30 approximation algorithm for the HP model on the hexagonal close packed lattice. Further, the analysis provides a mathematical methodology for transferring performance guarantees on lattices to off-lattice models. These results partially answer the open question of Karplus et al. concerning the complexity of protein folding models that include side chains.
Modelling and Verification of Automated Transit Systems, Using Timed Automata, Invariants and
Lynch, Nancy
and gates, steam boiler control) appear in [8, 10]. Briefly, a timed automaton is a labelled transition
Modelling and Veri cation of Automated Transit Systems, using Timed Automata, Invariants and
Lynch, Nancy
and gates, steam boiler control) appear in 8, 10]. Brie y, a timed automaton is a labelled transition system
An Analytical Solution to a MEMS Seek Time Model hongbo@cse.ucsc.edu
Miller, Ethan L.
times 1020 times faster than hard drives, storage densities 10 times greater, and power consumption the surfaces relative to each other using MEMS actuators, each read/write head can access a region tips called tip arrays that are used to access data on a movable media sled. In a modern disk drive
Modeling and Analyzing Asynchronous Real-Time Systems Victor Pollex, Steffen Kollmann, Frank Slomka
Ulm, Universität
frequencies are used. For instance a combustion engine where ignition times have to be computed for each to be verified. With a simulation the system's real-time behaviour can be ob- served. Due to the rarity of corner cases a simulation can only verify the real-time requirements with a certain prob- ability. A formal
-encounter-Bethe BEB model in which a simple expression for the optical-oscillator strength, based on the results from H, He, and H2, is employed in the ex- pression of the Bethe cross section. Both the BED and BEB
Bretherton, Chris
of the climate system, three-dimensional numerical models are the only tools to reliably project future climate role in the sensitivity of the climate system. It reviews available cloud feedback diagnostic methods. Clouds reflect solar (shortwave) radiation to space, thus serving as a cooling agent to the Earth
Applying the multivariate time-rescaling theorem to neural population models
Gerhard, Felipe
Statistical models of neural activity are integral to modern neuroscience. Recently interest has grown in modeling the spiking activity of populations of simultaneously recorded neurons to study the effects of correlations ...
Logistic Models with Time-Dependent Coefficients and Some of Their Applications
Raquel M. Lopez; Benjamin R. Morin; Sergei K. Suslov
2010-08-15T23:59:59.000Z
We discuss explicit solutions of the logistic model with variable parameters. Classical data on the sunflower seeds growth are revisited as a simple application of the logistic model with periodic coefficients. Some applications to related biological systems are briefly reviewed.
Yoshihito Kuno; Kenichi Kasamatsu; Yoshiro Takahashi; Ikuo Ichinose; Tetsuo Matsui
2015-06-05T23:59:59.000Z
Lattice gauge theory has provided a crucial non-perturbative method in studying canonical models in high-energy physics such as quantum chromodynamics. Among other models of lattice gauge theory, the lattice gauge-Higgs model is a quite important one because it describes wide variety of phenomena/models related to the Anderson-Higgs mechanism such as superconductivity, the standard model of particle physics, and inflation process of the early universe. In this paper, we first show that atomic description of the lattice gauge model allows us to explore real time dynamics of the gauge variables by using the Gross-Pitaevskii equations. Numerical simulations of the time development of an electric flux reveal some interesting characteristics of dynamical aspect of the model and determine its phase diagram. Next, to realize a quantum simulator of the U(1) lattice gauge-Higgs model on an optical lattice filled by cold atoms, we propose two feasible methods: (i) Wannier states in the excited bands and (ii) dipolar atoms in a multilayer optical lattice. We pay attentions to respect the constraint of Gauss's law and avoid nonlocal gauge interactions.
can the forecasts completely cover the evolution of earthquake-generated tsunami waves: generationDevelopment, testing, and applications of site-specific tsunami inundation models for real and applications of site-specific tsunami inundation models (forecast models) for use in NOAA's tsunami forecast
Moeller, M. P.; Urbanik, II, T.; Desrosiers, A. E.
1982-03-01T23:59:59.000Z
This paper describes the methodology and application of the computer model CLEAR (Calculates Logical Evacuation And Response) which estimates the time required for a specific population density and distribution to evacuate an area using a specific transportation network. The CLEAR model simulates vehicle departure and movement on a transportation network according to the conditions and consequences of traffic flow. These include handling vehicles at intersecting road segments, calculating the velocity of travel on a road segment as a function of its vehicle density, and accounting for the delay of vehicles in traffic queues. The program also models the distribution of times required by individuals to prepare for an evacuation. In order to test its accuracy, the CLEAR model was used to estimate evacuatlon tlmes for the emergency planning zone surrounding the Beaver Valley Nuclear Power Plant. The Beaver Valley site was selected because evacuation time estimates had previously been prepared by the licensee, Duquesne Light, as well as by the Federal Emergency Management Agency and the Pennsylvania Emergency Management Agency. A lack of documentation prevented a detailed comparison of the estimates based on the CLEAR model and those obtained by Duquesne Light. However, the CLEAR model results compared favorably with the estimates prepared by the other two agencies.
Weighted Logics for Nested Words and Algebraic Formal Power Series
Mathissen, Christian
2010-01-01T23:59:59.000Z
Nested words, a model for recursive programs proposed by Alur and Madhusudan, have recently gained much interest. In this paper we introduce quantitative extensions and study nested word series which assign to nested words elements of a semiring. We show that regular nested word series coincide with series definable in weighted logics as introduced by Droste and Gastin. For this we establish a connection between nested words and the free bisemigroup. Applying our result, we obtain characterizations of algebraic formal power series in terms of weighted logics. This generalizes results of Lautemann, Schwentick and Therien on context-free languages.
Wu, Huan; Adler, Robert F.; Tian, Yudong; Huffman, George; Li, Hongyi; Wang, Jianjian
2014-04-09T23:59:59.000Z
A community land surface model, the Variable Infiltration Capacity (VIC) model, is coupled with a newly developed hierarchical dominant river tracing-based runoff-routing model to form the Dominant river tracing-Routing Integrated with VIC Environment (DRIVE) model system, which serves as the new core of the real-time Global Flood Monitoring System (GFMS). The GFMS uses real-time satellite-based precipitation to derive flood-monitoring parameters for the latitude-band 50{degree sign}N-50{degree sign}S at relatively high spatial (~12km) and temporal (3-hourly) resolution. Examples of model results for recent flood events are computed using the real-time GFMS (http://flood.umd.edu). To evaluate the accuracy of the new GFMS, the DRIVE model is run retrospectively for 15 years using both research-quality and real-time satellite precipitation products. Statistical results are slightly better for the research-quality input and significantly better for longer duration events (three-day events vs. one-day events). Basins with fewer dams tend to provide lower false alarm ratios. For events longer than three days in areas with few dams, the probability of detection is ~0.9 and the false alarm ratio is ~0.6. In general, these statistical results are better than those of the previous system. Streamflow was evaluated at 1,121 river gauges across the quasi-global domain. Validation using real-time precipitation across the tropics (30ºS-30ºN) gives positive daily Nash-Sutcliffe Coef?cients for 107 out of 375 (28%) stations with a mean of 0.19 and 51% of the same gauges at monthly scale with a mean of 0.33. There were poorer results in higher latitudes, probably due to larger errors in the satellite precipitation input.
Mrofka, David Douglas
2010-01-01T23:59:59.000Z
a fossil water table: Sedimentology, v. 14, p. 175-185, 6Neoproterozoic times: Sedimentology Review, v. 1, p. 1-16.1996, Stratigraphy, sedimentology, and isotopic geochemistry
Gibbsianness versus Non-Gibbsianness of time-evolved planar rotor models
enough. Le Ny and Redig generalized in [LeNRed02] the result for small times t to more general dynamics
van der Lee, Suzan
A new P-velocity model for the Tethyan margin from a scaled S-velocity model and the inversion of P- and PKP-delay times Sung-Joon Chang a, , Suzan Van der Lee a , Megan P. Flanagan b a Dept. of Earth Livermore National Laboratory, P.O. Box 808, L-205, Livermore, CA 94551, USA a r t i c l e i n f o Article
Simulating Hamiltonian Dynamics with a Truncated Taylor Series
Berry, Dominic W.
We describe a simple, efficient method for simulating Hamiltonian dynamics on a quantum computer by approximating the truncated Taylor series of the evolution operator. Our method can simulate the time evolution of a wide ...
Thomson, Ty M. (Ty Matthew)
2008-01-01T23:59:59.000Z
Molecular signaling systems allow cells to sense and respond to environmental stimuli. Quantitative modeling can be a valuable tool for evaluating and extending our understanding of signaling systems. In particular, studies ...
Sub-national TIMES model for analyzing regional future use of Biomass and Biofuels in France and
Boyer, Edmond
1 Sub-national TIMES model for analyzing regional future use of Biomass and Biofuels in France Introduction Renewable energy sources such as biomass and biofuels are increasingly being seen as important of biofuels on the final consumption of energy in transport should be 10%. The long-term target is to reduce
Istrail, Sorin
Lattice and Off-Lattice Side Chain Models of Protein Folding: Linear Time Structure Prediction This paper considers the protein structure prediction problem for lattice and off-lattice protein folding tools for reasoning about protein folding in unrestricted continuous space through anal- ogy. This paper
Initial Simulation Results of Storm-Time Ring Current in a Self-Consistent Magnetic Field Model
Lyons, Larry
, and electrons. The ring current is greatly intensified during geomagnetic storms, and produces large measurement of the magnetic disturbances from all magnetospheric currents on the surface of the EarthInitial Simulation Results of Storm-Time Ring Current in a Self-Consistent Magnetic Field Model S
Stefanopoulou, Anna
and multivariable. The control scheme jointly manages fuel and cam position. 1 Introduction. Modern automobile external exhaust gas recirculation (EGR) systems commonly used for NOx reduction. Control SystemsModeling and Control of a Spark Ignition Engine with Variable Cam Timing A. G. Stefanopoulou, J. A
Error bounds for space-time discretizations of a 3D model for shape-memory materials
Stefanelli, Ulisse
Error bounds for space-time discretizations of a 3D model for shape-memory materials Alexander in shape- memory materials. After recalling existence and uniqueness results, a fully evolution of shape-memory alloys (SMAs). The latter are metallic alloys showing some surprising thermo
Michael, Panayiotis Adamos
2015-01-01T23:59:59.000Z
a new model and architecture for data stream management”.Order Processing: A New Architecture for High- PerformanceDistributed Streamonas Architecture – and its Performance
Mathematical Modeling of the Stress-Strain-Time Behavior of Geosynthetics Using the Findley Equation
Horvath, John S.
......................................................................................................... 9 3.3 Portrayal of Creep-Test Data ............................................................................................................................... 2 Section 2 - Creep Models 2.1 Overview ..................................................................................................................................... 9 3.2 Description of Test Conditions
Lawrence, Peter J.; Feddema, Johannes J.; Bonan, Gordon B.; Meehl, Gerald A.; O’ Neill, Brian C.; Oleson, Keith W.; Levis, Samuel; Lawrence, David M.; Kluzek, Erik; Lindsay, Keith
2012-05-01T23:59:59.000Z
To assess the climate impacts of historical and projected land cover change in the Community Climate System Model, version 4 (CCSM4), new time series of transient Community Land Model, version 4 (CLM4) plant functional ...
RINGS OF SEPARATED POWER SERIES
power series rings Sm;n (Section 4) and (ii) to develop the ingredients of sheaf. theory for ... systems of modules behave under ground eld extension. Here we ...
Operating Innovative Networks Workshop Series
Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)
Workshop Series Enlighten Your Research Global Program Science Requirements Reviews Case Studies Contact Us Technical Assistance: 1 800-33-ESnet (Inside US) 1 800-333-7638...
Comen, E; Mason, J; Kuhn, P [The Scripps Research Institute, La Jolla, CA (United States); Nieva, J [Billings Clinic, Billings, Montana (United States); Newton, P [University of Southern California, Los Angeles, CA (United States); Norton, L; Venkatappa, N; Jochelson, M [Memorial Sloan-Kettering Cancer Center, NY, NY (United States)
2014-06-01T23:59:59.000Z
Purpose: Traditionally, breast cancer metastasis is described as a process wherein cancer cells spread from the breast to multiple organ systems via hematogenous and lymphatic routes. Mapping organ specific patterns of cancer spread over time is essential to understanding metastatic progression. In order to better predict sites of metastases, here we demonstrate modeling of the patterned migration of metastasis. Methods: We reviewed the clinical history of 453 breast cancer patients from Memorial Sloan Kettering Cancer Center who were non-metastatic at diagnosis but developed metastasis over time. We used the variables of organ site of metastases as well as time to create a Markov chain model of metastasis. We illustrate the probabilities of metastasis occurring at a given anatomic site together with the probability of spread to additional sites. Results: Based on the clinical histories of 453 breast cancer patients who developed metastasis, we have learned (i) how to create the Markov transition matrix governing the probabilities of cancer progression from site to site; (ii) how to create a systemic network diagram governing disease progression modeled as a random walk on a directed graph; (iii) how to classify metastatic sites as ‘sponges’ that tend to only receive cancer cells or ‘spreaders’ that receive and release them; (iv) how to model the time-scales of disease progression as a Weibull probability distribution function; (v) how to perform Monte Carlo simulations of disease progression; and (vi) how to interpret disease progression as an entropy-increasing stochastic process. Conclusion: Based on our modeling, metastatic spread may follow predictable pathways. Mapping metastasis not simply by organ site, but by function as either a ‘spreader’ or ‘sponge’ fundamentally reframes our understanding of metastatic processes. This model serves as a novel platform from which we may integrate the evolving genomic landscape that drives cancer metastasis. PS-OC Trans-Network Project Grant Award for “Data Assimilation and ensemble statistical forecasting methods applied to the MSKCC longitudinal metastatic breast cancer cohort.”.
Random polynomial-time attacks and Dolev-Yao models Mathieu Baudet
Doyen, Laurent
that under sufficient realistic assump- tions the extended models are equivalent to standard Dolev-Yao models by the the RNTL projects EVA and ProuvÂ´e, the ACI SÂ´ecuritÂ´e Informatique Rossignol, the ACI Cryptologie Psi-Robuste, and the ACI jeunes chercheurs "SÂ´ecuritÂ´e informatique, protocoles cryptographiques et dÂ´etection d
Driver Models For Timing And Noise Analysis Bogdan Tutuianu and Ross Baldick
Baldick, Ross
additional non-linear circuit simulations and gen- erates re-usable models. Introduction: One of the problems analysis are proposed in [19], [10] and [1]. Special circuit modeling techniques to asses global noise and the analysis is reduced to linear cir- cuit simulation. In the case of delay noise, functional noise
Supervised Learning Based Model for Predicting Variability-Induced Timing Errors
Gupta, Rajesh
combat variations in hardware and workload by increasing conservative guardbanding that leads, for a given amount of guardband reduction. The proposed methodology enables a model-based rule method the robustness of our modeling methodology by considering various operating voltage and temperature corners. Our
Modeling Time-Triggered Ethernet in SystemC/TLM for Virtual Prototyping of
Koutsoukos, Xenofon D.
, and has been used in many CPS domains, such as automotive, aerospace, and industrial process control platform model for design space exploration. We validate the model by comparing latency and jitter layer, the network/platform layer, and the physical layer [1]. The interactions within and across
NUMERICAL SOLUTION OF RESERVOIR FLOW MODELS BASED ON LARGE TIME STEP OPERATOR SPLITTING ALGORITHMS
processes. A black-oil model is commonly used to describe water injection. This model works well. Special focus is posed on the numerical solution algorithms for the saturation equation, which is a convection dominated, degenerate convection-di#11;usion equation. Both theory and applications are discussed
TCTL model-checking of Time Petri Nets Hanifa Boucheneb1
Paris-Sud XI, Université de
Verification of concurrent systems is a complex task that requires powerful models and efficient analysis tech- niques. Model checking is one of the most popular verification techniques of concurrent systems verification of properties of real-life systems. In this paper, we consider subscript TCTL for TPN (TPN
Ramachandran, Arun
2006-08-16T23:59:59.000Z
A general framework for performance optimization of continuous-time OTA-C (Operational Transconductance Amplifier-Capacitor) filters is proposed. Efficient procedures for evaluating nonlinear distortion and noise valid for any filter of arbitrary...
A Framework to Model Branch Prediction for Worst Case Execution Time Analysis
Roychoudhury, Abhik
execution history. This allows the program execution to proceed by speculating the control flow. Branch with an external environment in a timely fashion. Many embedded systems are safety critical, e.g., automobiles
Hardware Simulator: Digital Block Design for Time-Varying MIMO Channels with TGn Model B Test
Paris-Sud XI, Université de
[3]. This is made possible by advances at all levels of the communication platform, as the monolithic]. Moreover, a new method based on determining the parameters of the simulator by fitting the space time
Discrete-time, cyclostationary phase-locked loop model for jitter analysis
Vamvakos, Socrates D.
Timing jitter is one of the most significant phase-locked loop characteristics, with high impact on performance in a range of applications. It is, therefore, important to develop the tools necessary to study and predict ...
Moorcroft, Paul R.
Mechanistic scaling of ecosystem function and dynamics in space and time: Ecosystem Demography] Insights into how terrestrial ecosystems affect the Earth's response to changes in climate and rising contain detailed mechanistic representations of biological processes affecting terrestrial ecosystems
Estimating Seasonal Drivers in Childhood Infectious Diseases with Continuous Time Models
Abbott, George H.
2010-07-14T23:59:59.000Z
. This research addresses several shortcomings of the discrete-time approaches, including removing the need for the reporting interval to match the serial interval of the disease using infectious disease data from three major cities: New York City, London...
Timed model-based programming : executable specifications for robust mission-critical sequences
Ingham, Michel D. (Michel Donald), 1972-
2003-01-01T23:59:59.000Z
There is growing demand for high-reliability embedded systems that operate robustly and autonomously in the presence of tight real-time constraints. For robotic spacecraft, robust plan execution is essential during ...
Ramachandran, Arun
2006-08-16T23:59:59.000Z
A general framework for performance optimization of continuous-time OTA-C (Operational Transconductance Amplifier-Capacitor) filters is proposed. Efficient procedures for evaluating nonlinear distortion and noise valid for any filter of arbitrary...
Modeling real-time human-automation collaborative scheduling of unmanned vehicles
Clare, Andrew S
2013-01-01T23:59:59.000Z
Recent advances in autonomy have enabled a future vision of single operator control of multiple heterogeneous Unmanned Vehicles (UVs). Real-time scheduling for multiple UVs in uncertain environments will require the ...
Hidden Process Models Tom M. Mitchell1,2,3
introduce the Hidden Process Model (HPM), a probabilistic model for multivariate time series data intended 2 #12;1 Introduction In this paper, we propose the Hidden Process Model (HPM), a probabilistic model the set of assumptions captured in the HPM format requires a complex DBN. For instance, we must inflate
Born series and unitarity in noncommutative quantum mechanics
Bemfica, F. S.; Girotti, H. O. [Instituto de Fisica, Universidade Federal do Rio Grande do Sul, Caixa Postal 15051, 91501-970 - Porto Alegre, Rio Grande do Sul (Brazil)
2008-01-15T23:59:59.000Z
This paper is dedicated to present model independent results for noncommutative quantum mechanics. We determine sufficient conditions for the convergence of the Born series and, in the sequel, unitarity is proved in full generality.
Born series and unitarity in noncommutative quantum mechanics
F. S. Bemfica; H. O. Girotti
2008-02-11T23:59:59.000Z
This paper is dedicated to present model independent results for noncommutative quantum mechanics. We determine sufficient conditions for the convergence of the Born series and, in the sequel, unitarity is proved in full generality.
Rydberg series of calcium monofluoride : spectrum, structure, and dynamics
Kay, Jeffrey J
2007-01-01T23:59:59.000Z
This thesis summarizes progress toward the ultimate goal of building a complete structural and dynamical model for the CaF molecule. The quantum defects of the Rydberg series of the molecule, as well as their dependences ...
Spectral modeling of two incline cylinders with validation in the time domain
Oswalt, Aaron Jacob
1999-01-01T23:59:59.000Z
Function. 2. 3 Two Input/Single Output System . 2. 4 Conditioned Spectral Analysis. 2. 5 Partial Coherence 2. 6 Formulation of the Nonlinear Model 2. 6. 1 Nonlinear System Form . . 2. 6. 2 Reverse Dynamic Nonlinear System. 2. 6. 3 SDOF Nonlinear...) . . . . . . . . . . . . . . . 15 5 SVSO model for two-input system used to remove the correlated effects of xr(r) . . 18 6 Conditioned spectral model with noise for a two-input / single-output system . . . . . . 20 7 Classification of interference regions for inline...