Time Series Models: Hidden Markov Models
Roweis, Sam
Time Series Models: Hidden Markov Models & Linear Dynamical Systems Sam Roweis Gatsby Computational before. Discrete state: { Moore and Mealy machines (engineering) { stochastic #12;nite state automata (CS chain with stochastic measurements. Gauss-Markov process in a pancake. PSfrag replacements x 1 y 1 x 2 y
Time Series Models: Hidden Markov Models
Roweis, Sam
Time Series Models: Hidden Markov Models & Linear Dynamical Systems Sam Roweis Gatsby Computational. Discrete state: { Moore and Mealy machines (engineering) { stochastic #12;nite state automata (CS with stochastic measurements. Gauss-Markov process in a pancake. PSfrag replacements x 1 y 1 x 2 y 2 x 3 y 3 x T y
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
Analysis of Time Series Using Compact Model-Based Descriptions
Kriegel, Hans-Peter
Analysis of Time Series Using Compact Model-Based Descriptions Hans-Peter Kriegel, Peer Kr this is a combination of the coefficients 1, . . . , 3 representing the three input time series using a function f-of-the-art compression methods. The results are visually presented in a very concise way so that the user can easily
Bayesian time series models and scalable inference
Johnson, Matthew James, Ph. D. Massachusetts Institute of Technology
2014-01-01T23:59:59.000Z
With large and growing datasets and complex models, there is an increasing need for scalable Bayesian inference. We describe two lines of work to address this need. In the first part, we develop new algorithms for inference ...
Univariate Modeling and Forecasting of Monthly Energy Demand Time Series
Abdel-Aal, Radwan E.
Univariate Modeling and Forecasting of Monthly Energy Demand Time Series Using Abductive and Neural dedicated models to forecast the 12 individual months directly. Results indicate better performance is superior to naÃ¯ve forecasts based on persistence and seasonality, and is better than results quoted
1MaPhySto Workshop 9/04 Nonlinear Time Series ModelingNonlinear Time Series Modeling
. "Stylized facts" concerning financial time series 4. ARCH and GARCH models 5. Forecasting with GARCH 6 of multivariate RV equivalence 8.5 examples 8.6 Extremes for GARCH and SV models 8.7 Summary of results for ACF of GARCH & SV models #12;4MaPhySto Workshop 9/04 Part III: Nonlinear and NonGaussian State-Space Models 1
Time Series Models for Measuring Market Risk Time Series Models for Measuring Market Risk
Hernández Lobato, José Miguel
and collaborative mixtures of experts 3 GARCH processes with non-parametric innovations 4 Conclusions and future Competitive and collaborative mixtures of experts 3 GARCH processes with non-parametric innovations 4 Volatility models: GARCH processes We say {rt}T t=1 follows a GARCH(1,1) process if: rt = tt (4) 2 t = + |rt
Roweis, Sam
SCIA 2003 Tutorial: Hidden Markov Models Sam Roweis, University of Toronto June 29, 2003 Probabilistic Generative Models for Time Series #15; Stochastic models for time-series: y 1 ; y 2 ; : : : ; y #15; Add noise to make the system stochastic: p(y t jy t 1 ;y t 2 ; : : : ;y t k ) #15; Markov models
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.
breaks in this series? #12;5Banff 6/06 Introduction Examples AR GARCH Stochastic volatility State space Simulation results Applications Simulation results for GARCH and SV models #12;6Banff 6/06 Examples 1 ),,( 1 jjpj K #12;7Banff 6/06 Examples (cont) 2. Segmented GARCH model: where 0 = 1
-202 Any breaks in this series? #12;5NCAR-IMAGe 2006 Introduction Examples AR GARCH Stochastic volatility break estimation Simulation results Applications Simulation results for GARCH and SV models #12;6NCAR-tjptjptjjt tYYY jj GARCH model
Introduction to (Generalized) Autoregressive Conditional Heteroskedasticity Models in Time Series
Morrow, James A.
. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7 4 ARCH/GARCH models 8 4.1 Sample Application and application of the ARCH/GARCH models proposed in the 1980's by econometricians such as Robert Engle (who won at the time). In particular, we focus on the paper, "GARCH 101: The Use of ARCH/GARCH Models in Applied Econo
Early Classification of Multivariate Time Series Using a Hybrid HMM/SVM model
Obradovic, Zoran
Early Classification of Multivariate Time Series Using a Hybrid HMM/SVM model Mohamed F. Ghalwash to use a shorter time interval for classification is often more favorable than having a slightly more with other models that use full time series both in training and testing. Analysis of biomedical data has
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
Paris-Sud XI, UniversitÃ© de
1 Time series modeling and large scale global solar radiation forecasting from geostationary global solar radiation. In this paper, we use geostationary satellites data to generate 2-D time series of solar radiation for the next hour. The results presented in this paper relate to a particular territory
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
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, nation-wide industry...
A FAST MODEL-BUILDING METHOD FOR TIME SERIES USING GENETIC PROGRAMMING
Fernandez, Thomas
A FAST MODEL-BUILDING METHOD FOR TIME SERIES USING GENETIC PROGRAMMING I. Yoshihara Faculty) financial problems e.g. stock price indices and gold prices. The experiments lead us to the conclusion
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
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 ...
Time series models with an EGB2 conditional distribution
Caivano, Michele; Harvey, Andrew
2014-07-09T23:59:59.000Z
was made by Wang et. al. (2001) who ?tted GARCH-EGB2 models to exchange rate data. The article is organized as follows. In Section 2, the DCS location model based on the general form of the EGB2 distribution, which allows for skew- ness, is introduced... of the location score, dividing (12) by #15;t gives a bounded function as j#15;tj ! 1: Note that the score function is often called the news-impact curve in the GARCH literature and that it becomes asymmetic when a leverage term is introduced into the dynamics...
Regressive Modeling 4 pieces, 2.58 seconds. #12;4Kaiserslautern 9/05 Introduction Examples AR GARCH Stochastic for structural break estimation Simulation results Applications Simulation results for GARCH and SSM #12. Segmented GARCH model: where 0 = 1
Volatility Forecasts in Financial Time Series with HMM-GARCH Models
Chen, Yiling
Volatility Forecasts in Financial Time Series with HMM-GARCH Models Xiong-Fei Zhuang and Lai {xfzhuang,lwchan}@cse.cuhk.edu.hk Abstract. Nowadays many researchers use GARCH models to generate of the two parameters G1 and A1[1], in GARCH models is usually too high. Since volatility forecasts in GARCH
TIME SERIES MODELS OF THREE SETS OF RXTE OBSERVATIONS OF 4U 1543-47
Koen, C. [Department of Statistics, University of the Western Cape, Private Bag X17, Bellville, 7535 Cape (South Africa)] [Department of Statistics, University of the Western Cape, Private Bag X17, Bellville, 7535 Cape (South Africa)
2013-03-01T23:59:59.000Z
The X-ray nova 4U 1543-47 was in a different physical state (low/hard, high/soft, and very high) during the acquisition of each of the three time series analyzed in this paper. Standard time series models of the autoregressive moving average (ARMA) family are fitted to these series. The low/hard data can be adequately modeled by a simple low-order model with fixed coefficients, once the slowly varying mean count rate has been accounted for. The high/soft series requires a higher order model, or an ARMA model with variable coefficients. The very high state is characterized by a succession of 'dips', with roughly equal depths. These seem to appear independently of one another. The underlying stochastic series can again be modeled by an ARMA form, or roughly as the sum of an ARMA series and white noise. The structuring of each model in terms of short-lived aperiodic and 'quasi-periodic' components is discussed.
CHANGE OF STRUCTURE IN FINANCIAL TIME SERIES, LONG RANGE DEPENDENCE AND THE GARCH MODEL
Mikosch, Thomas
CHANGE OF STRUCTURE IN FINANCIAL TIME SERIES, LONG RANGE DEPENDENCE AND THE GARCH MODEL THOMAS having as limit a Gaussian #12;eld. In the case of GARCH(p; q) processes a statistic closely related limit theorem for this statistic under the hypothesis of a GARCH(p; q) sequence with a #12;nite 4th
Some methods and models for analyzing time-series gene expression data
Jammalamadaka, Arvind K. (Arvind Kumar), 1981-
2009-01-01T23:59:59.000Z
Experiments in a variety of fields generate data in the form of a time-series. Such time-series profiles, collected sometimes for tens of thousands of experiments, are a challenge to analyze and explore. In this work, ...
Fernandez, Thomas
of the meteorological time series used, which includes the use of statistical techniques to detect whether there exist for the time series using an evolutionary algorithm that adaptively adjusts some of its parameters during its and temperatures collected in a region of Romania. The results are promising for the analysis of such time series
Tappert, Charles
Series Using a Focused Time Lagged FeedForward Neural Network N. Moseley ABSTRACT, - Artificial neural other series expansion.[2]. The motivation for analysis of time series using neural netwoProceedings of Student Research Day, CSIS, Pace University, May 9th, 2003 Modeling Economic Time
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).
Voyant, Cyril; Muselli, Marc; Paoli, Christophe; Nivet, Marie Laure
2014-01-01T23:59:59.000Z
When a territory is poorly instrumented, geostationary satellites data can be useful to predict global solar radiation. In this paper, we use geostationary satellites data to generate 2-D time series of solar radiation for the next hour. The results presented in this paper relate to a particular territory, the Corsica Island, but as data used are available for the entire surface of the globe, our method can be easily exploited to another place. Indeed 2-D hourly time series are extracted from the HelioClim-3 surface solar irradiation database treated by the Heliosat-2 model. Each point of the map have been used as training data and inputs of artificial neural networks (ANN) and as inputs for two persistence models (scaled or not). Comparisons between these models and clear sky estimations were proceeded to evaluate the performances. We found a normalized root mean square error (nRMSE) close to 16.5% for the two best predictors (scaled persistence and ANN) equivalent to 35-45% related to ground measurements. F...
Multi-horizon solar radiation forecasting for Mediterranean locations using time series models
Voyant, Cyril; Muselli, Marc; Nivet, Marie Laure
2013-01-01T23:59:59.000Z
Considering the grid manager's point of view, needs in terms of prediction of intermittent energy like the photovoltaic resource can be distinguished according to the considered horizon: following days (d+1, d+2 and d+3), next day by hourly step (h+24), next hour (h+1) and next few minutes (m+5 e.g.). Through this work, we have identified methodologies using time series models for the prediction horizon of global radiation and photovoltaic power. What we present here is a comparison of different predictors developed and tested to propose a hierarchy. For horizons d+1 and h+1, without advanced ad hoc time series pre-processing (stationarity) we find it is not easy to differentiate between autoregressive moving average (ARMA) and multilayer perceptron (MLP). However we observed that using exogenous variables improves significantly the results for MLP . We have shown that the MLP were more adapted for horizons h+24 and m+5. In summary, our results are complementary and improve the existing prediction techniques ...
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
A Fuzzy-Convolution Model for Physical Action and Behaviour Pattern Recognition of 3D Time Series
Hu, Huosheng
A Fuzzy-Convolution Model for Physical Action and Behaviour Pattern Recognition of 3D Time Series-- Pattern Classification, Action Recognition, Fuzzy Classifiers, Signal Convolution. I. INTRODUCTION researchers in pattern recognition on the field of intelligent surveillance. Fuzzy logic has been extensively
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
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...
Temporal Resolution in Time Series and Probabilistic Models of Renewable Power Eric Hoevenaars
Victoria, University of
. . . . . . . . . . . . . . . . . . . . . . . 12 2.2.2 Solar Photovoltaic Model . . . . . . . . . . . . . . . . . . . . . 16 2.2.3 Battery Bank
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.
Time series analysis of regional climate model performance Jason P. Evans
Evans, Jason
in Kansas, United States, including the First International Satellite Land Surface Climatology Project, both regional and global, has become apparent. Predictions of the energy and water balance to evapotranspiration and fails to close the energy budget. All of the models overestimate runoff and evapotranspiration
Almog, Assaf
2014-01-01T23:59:59.000Z
The dynamics of complex systems, from financial markets to the brain, can be monitored in terms of time series of activity of their fundamental elements (such as stocks or neurons respectively). While the main focus of time series analysis is on the magnitude of temporal increments, a significant piece of information is encoded into the binary projection (i.e. the sign) of such increments. In this paper we provide further evidence of this by showing strong nonlinear relationships between binary and non-binary properties of financial time series. We then introduce an information-theoretic approach to the analysis of the binary signature of single and multiple time series. Through the definition of maximum-entropy ensembles of binary matrices, we quantify the information encoded into the simplest binary properties of real time series and identify the most informative property given a set of measurements. Our formalism is able to replicate the observed binary/non-binary relations very well, and to mathematically...
Dominici, Francesca
for 10 metropolitan areas in the United States from 1986 to 1993. We postulate that these time series relative rates of mortality and morbidity associated with exposure to PM10 within each location. The sample covariance matrix of the estimated log relative rates is obtained using a novel generalized estimating
Exact Primitives for Time Series Data Mining
Mueen, Abdullah Al
2012-01-01T23:59:59.000Z
142 Sony AIBO Robot: Surfacetrajectories and ac- celerometer signals from SONY AIBOclasses of time series from the SONY AIBO accelerometer. (b)
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 ...
Turbulencelike Behavior of Seismic Time Series
Manshour, P.; Saberi, S. [Department of Physics, Sharif University of Technology, Tehran 11155-9161 (Iran, Islamic Republic of); Sahimi, Muhammad [Mork Family Department of Chemical Engineering and Materials Science, University of Southern California, Los Angeles, California 90089-1211 (United States); Peinke, J. [Institute of Physics, Carl von Ossietzky University, D-26111 Oldenburg (Germany); Pacheco, Amalio F. [Department of Theoretical Physics, University of Zaragoza, Pedro Cerbuna 12, 50009 Zaragoza (Spain); Rahimi Tabar, M. Reza [Department of Physics, Sharif University of Technology, Tehran 11155-9161 (Iran, Islamic Republic of); Institute of Physics, Carl von Ossietzky University, D-26111 Oldenburg (Germany); CNRS UMR 6202, Observatoire de la Cote d'Azur, BP 4229, 06304 Nice Cedex 4 (France)
2009-01-09T23:59:59.000Z
We report on a stochastic analysis of Earth's vertical velocity time series by using methods originally developed for complex hierarchical systems and, in particular, for turbulent flows. Analysis of the fluctuations of the detrended increments of the series reveals a pronounced transition in their probability density function from Gaussian to non-Gaussian. The transition occurs 5-10 hours prior to a moderate or large earthquake, hence representing a new and reliable precursor for detecting such earthquakes.
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, 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.
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.
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
Local prediction of turning points of oscillating time series
D. Kugiumtzis
2008-08-06T23:59:59.000Z
For oscillating time series, the prediction is often focused on the turning points. In order to predict the turning point magnitudes and times it is proposed to form the state space reconstruction only from the turning points and modify the local (nearest neighbor) model accordingly. The model on turning points gives optimal prediction at a lower dimensional state space than the optimal local model applied directly on the oscillating time series and is thus computationally more efficient. Monte Carlo simulations on different oscillating nonlinear systems showed that it gives better predictions of turning points and this is confirmed also for the time series of annual sunspots and total stress in a plastic deformation experiment.
Multilinear Dynamical Systems for Tensor Time Series
Russell, Stuart
of the stock prices of n multiple companies comprise a time series of 6 × n tensors. A grayscale video sequence ocean temperatures will increase. Prediction of stock prices may not only inform investors but also help to stabilize the economy and prevent market collapse. The relationships between particular subsets of tensor
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
Mikosch, Thomas
. The resulting theory is applied to popular financial time series models: GARCH(1, 1), asymmetric GARCH(1, 1 for a general class of heteroscedastic time series models, which includes GARCH(1, 1). Recall that the time series (X t ) is called a GARCH(p, q) (generalized autoregressive conditionally heteroscedastic) process
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.
Wolpert, Robert L
Bayesian analysis of GARCH and stochastic volatility: modeling leverage, jumps and heavy for two broad major classes of varying volatility model, GARCH and stochastic volatility (SV) models-t errors yields the best performance among the competing models on the return data. Key words: GARCH, Heavy
Improving predictability of time series using maximum entropy methods
Gregor Chliamovitch; Alexandre Dupuis; Bastien Chopard; Anton Golub
2014-11-28T23:59:59.000Z
We discuss how maximum entropy methods may be applied to the reconstruction of Markov processes underlying empirical time series and compare this approach to usual frequency sampling. It is shown that, at least in low dimension, there exists a subset of the space of stochastic matrices for which the MaxEnt method is more efficient than sampling, in the sense that shorter historical samples have to be considered to reach the same accuracy. Considering short samples is of particular interest when modelling smoothly non-stationary processes, for then it provides, under some conditions, a powerful forecasting tool. The method is illustrated for a discretized empirical series of exchange rates.
Improving predictability of time series using maximum entropy methods
Chliamovitch, Gregor; Chopard, Bastien; Golub, Anton
2014-01-01T23:59:59.000Z
We discuss how maximum entropy methods may be applied to the reconstruction of Markov processes underlying empirical time series and compare this approach to usual frequency sampling. It is shown that, at least in low dimension, there exists a subset of the space of stochastic matrices for which the MaxEnt method is more efficient than sampling, in the sense that shorter historical samples have to be considered to reach the same accuracy. Considering short samples is of particular interest when modelling smoothly non-stationary processes, for then it provides, under some conditions, a powerful forecasting tool. The method is illustrated for a discretized empirical series of exchange rates.
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.
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,
Forecasting the underlying potential governing climatic time series
Livina, V N; Mudelsee, M; Lenton, T M
2012-01-01T23:59:59.000Z
We introduce a technique of time series analysis, potential forecasting, which is based on dynamical propagation of the probability density of time series. We employ polynomial coefficients of the orthogonal approximation of the empirical probability distribution and extrapolate them in order to forecast the future probability distribution of data. The method is tested on artificial data, used for hindcasting observed climate data, and then applied to forecast Arctic sea-ice time series. The proposed methodology completes a framework for `potential analysis' of climatic tipping points which altogether serves anticipating, detecting and forecasting climate transitions and bifurcations using several independent techniques of time series analysis.
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 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,...
Shiqing Ling Time-Series Econometric Theory
Ling, Shiqing
. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11 2.4 GARCH Models . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 33 3.3 GARCH(1, 1) Models . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 63 5.3 LAN of FARIMA-GARCH Models . . . . . . . . . . . . . . . . . . . . . . . . . . . 67 5
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
Distribution Based Data Filtering for Financial Time Series Forecasting
Bailey, James
recent past. In this paper, we address the challenge of forecasting the behavior of time series using@unimelb.edu.au Abstract. Changes in the distribution of financial time series, particularly stock market prices, can of stock prices, which aims to forecast the future values of the price of a stock, in order to obtain
APPARENT WATER OPTICAL PROPERTIES AT THE CARIBBEAN TIME SERIES STATION
Gilbes, Fernando
APPARENT WATER OPTICAL PROPERTIES AT THE CARIBBEAN TIME SERIES STATION Roy A. Armstrong, Jose M of Puerto Rico MayagÃ¼ez, Puerto Rico 00681 ABSTRACT The Caribbean Time Series, located 28 nautical miles in near- surface waters of the northeastern Caribbean Basin. Apparent optical properties such as, remote
IMPROVEMENTS TO THE RADIANT TIME SERIES METHOD COOLING LOAD CALCULATION
IMPROVEMENTS TO THE RADIANT TIME SERIES METHOD COOLING LOAD CALCULATION PROCEDURE By BEREKET, Australia 1998 Submitted to the Faculty of the Graduate College of the Oklahoma State University in partial TO THE RADIANT TIME SERIES METHOD COOLING LOAD CALCULATION PROCEDURE Dissertation Approved: Dr. Jeffrey D
State Space Reconstruction for Multivariate Time Series Prediction
I. Vlachos; D. Kugiumtzis
2008-09-12T23:59:59.000Z
In the nonlinear prediction of scalar time series, the common practice is to reconstruct the state space using time-delay embedding and apply a local model on neighborhoods of the reconstructed space. The method of false nearest neighbors is often used to estimate the embedding dimension. For prediction purposes, the optimal embedding dimension can also be estimated by some prediction error minimization criterion. We investigate the proper state space reconstruction for multivariate time series and modify the two abovementioned criteria to search for optimal embedding in the set of the variables and their delays. We pinpoint the problems that can arise in each case and compare the state space reconstructions (suggested by each of the two methods) on the predictive ability of the local model that uses each of them. Results obtained from Monte Carlo simulations on known chaotic maps revealed the non-uniqueness of optimum reconstruction in the multivariate case and showed that prediction criteria perform better when the task is prediction.
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.
A Multivariate Time Series Method for Monte Carlo Reactor Analysis
Taro Ueki
2008-08-14T23:59:59.000Z
A robust multivariate time series method has been established for the Monte Carlo calculation of neutron multiplication problems. The method is termed Coarse Mesh Projection Method (CMPM) and can be implemented using the coarse statistical bins for acquisition of nuclear fission source data. A novel aspect of CMPM is the combination of the general technical principle of projection pursuit in the signal processing discipline and the neutron multiplication eigenvalue problem in the nuclear engineering discipline. CMPM enables reactor physicists to accurately evaluate major eigenvalue separations of nuclear reactors with continuous energy Monte Carlo calculation. CMPM was incorporated in the MCNP Monte Carlo particle transport code of Los Alamos National Laboratory. The great advantage of CMPM over the traditional Fission Matrix method is demonstrated for the three space-dimensional modeling of the initial core of a pressurized water reactor.
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.
Continuous Time Random Walks and South Spain Seismic Series
A. Posadas; J. Morales; F. Vidal; O. Sotolongo-Costa; J. C. Antoranz
2002-05-27T23:59:59.000Z
Levy flights were introduced through the mathematical research of the algebra or random variables with infinite moments. Mandelbrot recognized that the Levy flight prescription had a deep connection to scale-invariant fractal random walk trajectories. The theory of Continuous Time Random Walks (CTRW) can be described in terms of Levy distribution functions and it can be used to explain some earthquake characteristics like the distribution of waiting times and hypocenter locations in a seismic region. This paper checks the validity of this assumption analyzing three seismic series localized in South Spain. The three seismic series (Alboran, Antequera and Loja) show qualitatively the same behavior, although there are quantitative differences between them.
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.
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
Time series of a CME blasting out from the Sun
Christian, Eric
#12;Time series of a CME blasting out from the Sun Composite image of the Sun in UV light with the naked eye, the Sun seems static, placid, constant. From the ground, the only notice- able variations in the Sun are its location (where will it rise and set today?) and its color (will clouds cover
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
Visual Analysis of Frequent Patterns In Large Time Series
Ramakrishnan, Naren
1 shows an example on how to monitor chiller efficiency in data centers using a pair of data center chiller time series in which different motifs were discovered. The illustrated process can be subdivided valued vector ti captures the data values (e.g., chiller utilization in the data center example), we
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
Estimating the predictability of economic and financial time series
Quentin Giai Gianetto; Jean-Marc Le Caillec; Erwan Marrec
2012-12-12T23:59:59.000Z
The predictability of a time series is determined by the sensitivity to initial conditions of its data generating process. In this paper our goal is to characterize this sensitivity from a finite sample by assuming few hypotheses on the data generating model structure. In order to measure the distance between two trajectories induced by a same noisy chaotic dynamic from two close initial conditions, a symmetric Kullback-Leiber divergence measure is used. Our approach allows to take into account the dependence of the residual variance on initial conditions. We show it is linked to a Fisher information matrix and we investigated its expressions in the cases of covariance-stationary processes and ARCH($\\infty$) processes. Moreover, we propose a consistent non-parametric estimator of this sensitivity matrix in the case of conditionally heteroscedastic autoregressive nonlinear processes. Various statistical hypotheses can so be tested as for instance the hypothesis that the data generating process is "almost" independently distributed at a given moment. Applications to simulated data and to the stock market index S&P500 illustrate our findings. More particularly, we highlight a significant relationship between the sensitivity to initial conditions of the daily returns of the S&P 500 and their volatility.
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
De Bilt, 2012 | Technical Report ; TR-326 Time series transformation tool
Stoffelen, Ad
De Bilt, 2012 | Technical Report ; TR-326 Time series transformation tool: description #12;#12;Time series transformation tool: description of the program to generate time series consistent ransformation tool: description of the program to generate time series consistent with the KNMI'06 climate
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
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
Lin, Ying-Tsong
In this paper, a method for merging partial overlapping time series of ocean profiles into a single time series of profiles using empirical orthogonal function (EOF) decomposition with the objective analysis is presented. ...
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
Geospatial analysis of vulnerable beach-foredune systems from decadal time series of lidar data
Mitasova, Helena
Geospatial analysis of vulnerable beach-foredune systems from decadal time series of lidar data, Geospatial analysis of vulnerable beach- foredune systems from decadal time series of lidar data, Journal densities; therefore, geospatial analysis, when applied to decadal lidar time series, needs to address
Filtering out high frequencies in time series using F-transform$
Kreinovich, Vladik
Filtering out high frequencies in time series using F-transform$ VilÂ´em NovÂ´akc , Irina Perfilievac) Preprint submitted to Elsevier February 10, 2013 #12;Filtering out high frequencies in time series using F at El Paso 500 W. University, El Paso, TX 79968, USA This paper is devoted to analysis of time series
Filtering out high frequencies in time series using F-transform$
Kreinovich, Vladik
Filtering out high frequencies in time series using F-transform$ VilÂ´em NovÂ´akc , Irina Perfilievac) Preprint submitted to Elsevier February 3, 2014 #12;Filtering out high frequencies in time series using F, El Paso, TX 79968, USA 1. Introduction This paper is devoted to analysis of time series using fuzzy
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
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
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...
Gutierrez, Rafael M.; Useche, Gina M.; Buitrago, Elias [Centro de Investigaciones, Universidad Antonio Narino, Carrera 3 Este No. 47A--15 Bogota (Colombia)
2007-11-13T23:59:59.000Z
We present a procedure developed to detect stochastic and deterministic information contained in empirical time series, useful to characterize and make models of different aspects of complex phenomena represented by such data. This procedure is applied to a seismological time series to obtain new information to study and understand geological phenomena. We use concepts and methods from nonlinear dynamics and maximum entropy. The mentioned method allows an optimal analysis of the available information.
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 of Aberdeen Aberdeen, AB24 3UE, UK {jyu, ereiter, jhunter, ssripada}@csd.abdn.ac.uk Abstract: SumTime-Turbine produces textual summaries of archived time- series data from gas turbines. These summaries should help
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.
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.
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
DETERMINING THE FRACTAL DIMENSION OF A TIME SERIES WITH A NEURAL NET
Danon, Yaron
DETERMINING THE FRACTAL DIMENSION OF A TIME SERIES WITH A NEURAL NET MARK J. EMBRECHTS AND YARON and require expert interaction for interpreting the calculated fractal dimension. Artificial neural nets (ANN) offer a fast and elegant way to estimate the fractal dimension of a time series. A backpropagation net
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
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
autoregressive time series: Topics by E-print Network
Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)
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...
astronomical time series: Topics by E-print Network
Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)
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...
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.
Applications of Time Series in Finance and Macroeconomics
Ibarra Ramirez, Raul
2011-08-08T23:59:59.000Z
with constant intensity. The last essay applies a dynamic factor model to generate out-of-sample forecasts for the inflation rate in Mexico. Factor models are useful to summarize the information contained in large datasets. We evaluate the role of using a wide...
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...
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.
Heal, Mathew R; Elton, Robert A; Hibbs, Leon R; Agius, Raymond M; Beverland, Iain J
2009-01-01T23:59:59.000Z
-soluble and total-extractable content of 11 trace metals determined in each sample. Time series were analysed using generalised additive Poisson regression models, including adjustment for minimum temperature and loess smoothing of trends. Methods were explored...
Wu, Guo-Qiang
A wide variety of methods based on fractal, entropic or chaotic approaches have been applied to the analysis of complex physiological time series. In this paper, we show that fractal and entropy measures are poor indicators ...
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.
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 ...
Using temporal averaging to decouple annual and nonannual information in AVHRR NDVI time series
Kastens, Jude Heathcliff; Lerner, David E.; Jakubauskas, Mark E.
2003-11-01T23:59:59.000Z
As regularly spaced time series imagery becomes more prevalent in the remote sensing community, monitoring these data for temporal consistency will become an increasingly important problem. Long-term trends must be identified, and it must...
The Spectral Density Estimation of Stationary Time Series with Missing Data
Schellekens, Michel P.
reported in literature (see, e.g. Green et al., 2002, Kaneoke and Vitek, 1996, Fortin and Mackey, 1999, and Laguna et al., 1998). Here we consider estimating the spectral density of stationary time series
EXPERIMENTAL VALIDATION OF THE RADIANT TIME SERIES METHOD FOR COOLING LOAD
EXPERIMENTAL VALIDATION OF THE RADIANT TIME SERIES METHOD FOR COOLING LOAD CALCULATIONS By IP SENG College of the Oklahoma State University in partial fulfillment of the requirements for the Degree LOAD CALCULATIONS Thesis Approved: _______________________________________ Thesis Advisor
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
Clustering of Unevenly Sampled Gene Expression Time-Series Data
Rostock, Universität
-means, k-means, average linkage hierarchical algorithm and random clustering are compared to the proposed the genes which define the model profiles in [2]. The fuzzy c-means, k- means, average linkage hierarchical as follows: The effects of the temporal information in the comparison of shapes are discussed first, followed
The relation between Brazilian and Chicago Board of Trade soybean prices: a time series test
Melcher, Bruno
1991-01-01T23:59:59.000Z
THE RELATION BETWEEN BRAZILIAN AND CHICAGO BOARD OF TRADE SOYBEAN PRICES ? A TIME SERIES TEST A Thesis BRUNO MELCHER 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 May 1991 Major Subject: Agricultural Economics THE RELATION BETWEEN BRAZILIAN AND CHICAGO BOARD OF TRADE SOYBEAN PRICES ? A TIME SERIES TEST A Thesis by BRUNO MELCHER Approved as to style and content by: ' f J David...
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...
Roweis, Sam
Multiple Alignment of Continuous Time Series Jennifer Listgarten + , Radford M. Neal + , Sam T of continuousvalued time series from a stochastic process often contain systematic variations in rate time series generated by a noisy, stochastic process, large sys tematic sources of variability
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.
Modeling exchange rate dependence dynamics at different time horizons
Embrechts, Paul
, Copula-GARCH, Conditional dependence, Dynamic copula Corresponding author. Tel.: +44(0) 247 657 4297. Financial time-series are often modeled with GARCH type models. In the multivariate GARCH literature there exist several models, like CCC- GARCH, DVEC, matrix-diagonal GARCH, BEKK and principal components GARCH
Anomaly detection in thermal pulse combustors using symbolic time series analysis
Ray, Asok
339 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 pulse combustor. Results are presented to exemplify early detection of combustion instability due
Visualizing Frequent Patterns in Large Multivariate Time Series , M. Marwah1
Ramakrishnan, Naren
languages, detecting anomalies in patients' medical records over time [5], and chiller efficiency in data centers [14]. Figure 1 shows an example of the visual analysis of a pair of data center chiller time series in which different motifs were discovered. A chiller is a key component of the cooling
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/mÂ²] xt, xd,y Time
Representing and Utilizing Changing Historical Places as an Ontology Time Series
Hyvönen, Eero
Chapter 1 Representing and Utilizing Changing Historical Places as an Ontology Time Series Eero Hyv.g. Check Republic or Slo- vakia) or overlapping historic names of different times (e.g. Roman Empire interfaces. The system has been applied in the semantic cultural heritage portal CULTURESAMPO for semantic
Melting of small Arctic ice caps observed from ERS scatterometer time series
Smith, Laurence C.
Melting of small Arctic ice caps observed from ERS scatterometer time series Laurence C. Smith,1 of melt onset can be observed over small ice caps, as well as the major ice sheets and multi-year sea ice for 14 small Arctic ice caps from 19922000. Interannual and regional variability in the timing of melt
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...
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.
Gordon, Geoffrey J.
are in constant movement within the cell, we extended our studies to time series images, which contain both to identify a protein's subcellular location is to label it with fluorescent dye, take microscope images this last step. The automated approach is more objective and sensitive than visual examination, and single
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
DAMAGE DETECTION IN A WIND TURBINE BLADE BASED ON TIME SERIES Simon Hoell, Piotr Omenzetter
Boyer, Edmond
DAMAGE DETECTION IN A WIND TURBINE BLADE BASED ON TIME SERIES METHODS Simon Hoell, Piotr Omenzetter, the consequences are growing sizes of wind turbines (WTs) and erections in remote places, such as off in the past years, thus efficient energy harvesting becomes more important. For the sector of wind energy
Time Series Methods for ForecastingElectricityMarket Pricing Zoran Obradovic Kevin Tomsovic
Obradovic, Zoran
tested by attempting to capture relationships between present and past share prices using simpleTime 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
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
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
RESEARCH ARTICLE Time series analysis of infrared satellite data for detecting
Wright, Robert
successfully detected ther- mal anomalies in TIR data from the Advanced Very High Resolution Radiometer (AVHRR algorithm that analyzes thermal infrared satellite time series data to detect and quantify the excess energy. These instruments provide data over potentially dangerous, high-temperature phenomena, such as volcanic eruptions
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
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
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
EOF analysis of a time series with application to tsunami detection
Tolkova, Elena
determines the accuracy of any forecast of the future tsunami evolution. A tsunami wave in the open ocean isEOF 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
Multi-Resolution K-Means Clustering of Time Series and Application to Images
Lin, Jessica
Multi-Resolution K-Means Clustering of Time Series and Application to Images Michail Vlachos using orthonormal decompositions, we present an anytime version of the k-Means algorithm. The algorithm centers for k-Means is mitigated by assigning the final centers at each approximation level as the initial
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
SEAWIFS VALIDATION AT THE CARIBBEAN TIME SERIES STATION (CATS) Jess Lee-Borges* and Roy Armstrong
Gilbes, Fernando
SEAWIFS VALIDATION AT THE CARIBBEAN TIME SERIES STATION (CATS) JesÃºs Lee-Borges* and Roy Armstrong. This is of particular importance to areas such as the Eastern Caribbean which has traditionally been viewed the dynamic nature of the northeastern Caribbean, underscoring the significant effect of periodic intrusions
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...
Directed Monitoring Using Cuscore Charts for Seasonal Time Series Harriet Black Nembhard*
Nembhard, Harriet Black
a special cause in a process, statistical process control (SPC) charts are traditionally used. If the data1 Directed Monitoring Using Cuscore Charts for Seasonal Time Series Harriet Black Nembhard used statistical process control charts to detect special causes are Shewhart and Cusum charts. However
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.
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
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
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
BN-97-4-4 (RP-875) The Radiant Time Series Cooling
of the proceduresare described in chapters 2 and 10 of the current ASHRAECool#zg and Heating LoadCalculation ManualBN-97-4-4 (RP-875) The Radiant Time Series Cooling Load Calculation Procedure Jeffrey D. Spitler calculations, derived from the heat balancemethod.It effectively replacesall other simpli- fied (non-heat
A Novel Approach to the Analysis of Nonlinear Time Series with Applications to Financial Data
Lee, Jun Bum
2012-07-16T23:59:59.000Z
LIST OF FIGURES : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : ix CHAPTER I INTRODUCTION : : : : : : : : : : : : : : : : : : : : : : : : : : 1 II THE QUANTILE SPECTRAL DENSITY AND COMPAR- ISON BASED TESTS FOR NONLINEAR TIME SERIES... : : : 5 1. Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . 5 2. The quantile spectral density and the test statistic . . . . . 7 3. Sampling properties . . . . . . . . . . . . . . . . . . . . . . 18 4. Testing for equality of serial...
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
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
Using Fourier Series to Model Hourly Energy Use in Commercial Buildings
Dhar, A.; Reddy, T. A.; Claridge, D. E.
1993-01-01T23:59:59.000Z
Fourier series analysis is eminently suitable for modeling strongly periodic data. Weather independent energy use such as lighting and equipment load in commercial buildings is strongly periodic and is thus appropriate for Fourier series treatment...
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.
Ruoxi Xiang; Michael Small
2014-06-18T23:59:59.000Z
In this work, the topologies of networks constructed from time series from an underlying system undergo a period doubling cascade have been explored by means of the prevalence of different motifs using an efficient computational motif detection algorithm. By doing this we adopt a refinement based on the $k$ nearest neighbor recurrence-based network has been proposed. We demonstrate that the refinement of network construction together with the study of prevalence of different motifs allows a full explosion of the evolving period doubling cascade route to chaos in both discrete and continuous dynamical systems. Further, this links the phase space time series topologies to the corresponding network topologies, and thus helps to understand the empirical "superfamily" phenomenon, as shown by Xu.
Time series analysis, 2013, PC 8 | ARCH and GARCH processes 9 8 ARCH and GARCH processes
GaÃ¯ffas, StÃ©phane
Time series analysis, 2013, PC 8 | ARCH and GARCH processes 9 8 ARCH and GARCH processes A GARCH(q) process. Exercise 8.2 (Computation of the kurtosis of a conditionally Gaussian GARCH(1, 1) pro- cess that = 3 + 3 Var(E[X2 t | Gt 1]) (E[X2 t ])2 . 3. For a GARCH(1,1) process, with p = q = 1 and a, b = b1, c
Tominski, Christian
that can be used to explore and analyze multivariate time series data. We propose different types of drawings. 1 INTRODUCTION The analysis of time series data is a fundamental task addressed by information of multivariate data is not a new topic to information visualization researchers. A variety of approaches have
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
Noncommutative space-time models
N. A. Gromov; V. V. Kuratov
2005-07-01T23:59:59.000Z
The FRT quantum Euclidean spaces $O_q^N$ are formulated in terms of Cartesian generators. The quantum analogs of N-dimensional Cayley-Klein spaces are obtained by contractions and analytical continuations. Noncommutative constant curvature spaces are introduced as a spheres in the quantum Cayley-Klein spaces. For N=5 part of them are interpreted as the noncommutative analogs of (1+3) space-time models. As a result the quantum (anti) de Sitter, Newton, Galilei kinematics with the fundamental length and the fundamental time are suggested.
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
Hurst exponent of very long birth time series in XX century Romania. Social and religious aspects
Rotundo, G; Herteliu, C; Ileanu, B
2015-01-01T23:59:59.000Z
The Hurst exponent of very long birth time series in Romania has been extracted from official daily records, i.e. over 97 years between 1905 and 2001 included. The series result from distinguishing between families located in urban (U) or rural (R) areas, and belonging (Ox) or not (NOx) to the orthodox religion. Four time series combining both criteria, (U,R) and (Ox, NOx), are also examined. A statistical information is given on these sub-populations measuring their XX-th century state as a snapshot. However, the main goal is to investigate whether the "daily" production of babies is purely noisy or is fluctuating according to some non trivial fractional Brownian motion, - in the four types of populations, characterized by either their habitat or their religious attitude, yet living within the same political regime. One of the goals was also to find whether combined criteria implied a different behavior. Moreover, we wish to observe whether some seasonal periodicity exists. The detrended fluctuation analysis...
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.
Learning Dynamic Systems From Time-Series Data - An Application to Gene Regulatory Networks
Timoteo, Ivo J. P. M.; Holden, Sean B.
2015-01-01T23:59:59.000Z
the second half of the time-series data provided; that is, from the point when the pertur- bation is lifted, as we do not know the exact nature of the perturbation. The DREAM4 Challenge evaluated performance using the p-values for the area under the ROC curve... ., and Druzdzel, M. (2010). Learn- ing why things change: The difference-based causal- ity learner. In Proceedings of the Twenty-Sixth An- nual Conference on Uncertainty in Artificial Intelli- gence (UAI). Yip, K., Alexander, R., Yan, K., and Gerstein, M. (2010...
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.
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)
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...
Modeling North Pacific Climate Time Series Don Percival
Percival, Don
-- autocovariance sequence (ACVS) and -- spectral density function (SDF) . essential di#erence between processes and SDF given by s X,# # cov{X t , X t+# } = # 2 # # |# | 1 - # 2 & SX (f ) = # 2 # 1 + # 2 - 2# cos(2#f noise; LM if # > 0) . ACVS and SDF given by s Y,# = # 2 # sin(##)#(1 - 2#)#(# + #) ##(# + 1 - #) & S Y
Modeling North Pacific Climate Time Series Don Percival
Percival, Don
Â autocovariance sequence (ACVS) and Â spectral density function (SDF) Â· essential difference between processes with mean zero and variance 2 3. || SDF given by sX, cov if > 0) Â· ACVS and SDF given by sY, = 2 sin()(1 - 2)( + ) ( + 1 - ) & SY (f) = 2 |2 sin(f)|2 Â· for 1
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.
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.
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.
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
Roweis, Sam
Multiple Alignment of Continuous Time Series Jennifer Listgarten y , Radford M. Neal y , Sam T of continuousvalued time series from a stochastic process often contain systematic variations in rate time series generated by a noisy, stochastic process, large sys tematic sources of variability
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
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...
Reverberation mapping of active galactic nuclei : The SOLA method for time-series inversion
Frank P. Pijpers; Ignaz Wanders
1994-06-27T23:59:59.000Z
In this paper a new method is presented to find the transfer function of the broad-line region in active galactic nuclei. The subtractive optimally localized averages (SOLA) method is a modified version of the Backus-Gilbert method and is presented as an alternative to the more often used maximum-entropy method. The SOLA method has been developed for use in helioseismology. It has been applied to the solar oscillation frequency splitting data currently available to deduce the internal rotation rate of the sun. The original SOLA method is reformulated in the present paper to cope with the slightly different problem of inverting time series. We use simulations to test the viability of the method and apply the SOLA method to the real data of the Seyfert-1 galaxy NGC 5548. We investigate the effects of measurement errors and how the resolution of the TF critically depends upon both the sampling rate and the photometric accuracy of the data. A uuencoded compressed postscript file of the paper which includes the figures is available by anonymous ftp at ftp://solaris.astro.uu.se/pub/articles/atmos/frank/PijWan.uue
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 ...
Jan de Leeuw; Peter G.M. van der Heijden; Peter Verboon
2011-01-01T23:59:59.000Z
DE L E E U W (1989), Latent budget analysis, in: A. DECARLI,DER H E U D E N (1988), The analysis of time- budgets with alatent-time-budget model, in E. Diday et al. (eds. ), Data
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.
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
Kirchner, James W.
High-frequency precipitation and stream water quality time series from Plynlimon, Wales: an openly Colin Vincent,6 Kathryn Lehto,6 Simon Grant,2 Jeremy Williams,7 Margaret Neal,1 Heather Wickham,1 Sarah-element high- frequency water quality data set that is openly accessible to the research community. The data
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 ...
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
Rabatel, Antoine
measurements. A recent time series of images from optical and SAR data are selected on 3 outlet glaciers well-scale areas. The limitations are cloudiness for optical data and high slope distortion on SAR images. I resolution, repeat coverage, radiometric calibration and stereo capabilities (automatic generation of DEM
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%.
Fortuna: Model Checking Priced Probabilistic Timed Automata
Vaandrager, Frits
Fortuna: Model Checking Priced Probabilistic Timed Automata Jasper Berendsen, David N. Jansen.O. Box 9010, 6500 GL Nijmegen, the Netherlands Abstract. We introduce Fortuna, the first tool for model checking priced probabilistic timed automata (PPTAs). Fortuna can handle the combination of real
Fortuna: Model Checking Priced Probabilistic Timed Automata
Vaandrager, Frits
Fortuna: Model Checking Priced Probabilistic Timed Automata Jasper Berendsen, David N. Jansen, the Netherlands Email: jasperb,dnjansen,fvaan @cs.ru.nl Abstract--We introduce FORTUNA, the first tool for model of probabilistic timed automata (PTAs) with cost-rates and discrete cost increments on states. FORTUNA is able
Bayesian inference for pulsar timing models
Vigeland, Sarah J
2013-01-01T23:59:59.000Z
The extremely regular, periodic radio emission from millisecond pulsars make them useful tools for studying neutron star astrophysics, general relativity, and low-frequency gravitational waves. These studies require that the observed pulse time of arrivals are fit to complicated timing models that describe numerous effects such as the astrometry of the source, the evolution of the pulsar's spin, the presence of a binary companion, and the propagation of the pulses through the interstellar medium. In this paper, we discuss the benefits of using Bayesian inference to obtain these timing solutions. These include the validation of linearized least-squares model fits when they are correct, and the proper characterization of parameter uncertainties when they are not; the incorporation of prior parameter information and of models of correlated noise; and the Bayesian comparison of alternative timing models. We describe our computational setup, which combines the timing models of tempo2 with the nested-sampling integ...
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.
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
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.
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...
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...
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
SATELLITE BASED ASSESSMENT OF THE NSRDB SITE IRRADIANCES AND TIME SERIES FROM
Perez, Richard R.
sets from two models, the Meteorological-Statistical (METSTAT) model [2] and the State University of New York (SUNY) model [3]. The 1991-2005 NSRDB has data from 1,454 ground sites that are divided continuous, and over 99% of its data are modeled and less than 1% are from instrumental measurements
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 ...
CITED REFERENCES Acevedo, W; Masuoka, P. 1997. Time-Series Animation Techniques for Visualizing
Julien, Pierre Y.
. Transactions of the ASAE, 23(4): 938-944. Bennet, JP. 1974. Concepts of Mathematical Modeling of Sediment Yield
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.
Fluorescence spectrum analysis using Fourier series modeling for Fluorescein solution in Ethanol
Hadi, Mahasin F
2011-01-01T23:59:59.000Z
We have measured the fluorescence spectrum for fluorescein solution in ethanol with concentration 1 {\\times} 10-3 mol/liter at different temperatures from room temperature to freezing point of solvent, (T = 153, 183, 223, 253, and 303 K) using liquid nitrogen. Table curve 2D version 5.01 program has been used to determine the fitting curve and fitting equation for each fluorescence spectrum. Fourier series (3 {\\times} 2) was the most suitable fitting equation for all spectra. Theoretical fluorescence spectrum of fluorescein in ethanol at T = 183K was calculated and compared with experimental fluorescence spectrum at the same temperature. There is a good similarity between them.
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...
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...
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
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...
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
Private and Dynamic Time-Series Data Aggregation with Trust Relaxation
of users along a specific time period. These statistics can then help the energy provider perform various operations such as load balancing and forecasting for potential acquirement. Despite its merits, statistical analyzer to compute global statistics over the set of individual inputs that are protected by some
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.
Quantification of depth of anesthesia by nonlinear time series analysis of brain electrical activity
G. Widman; T. Schreiber; B. Rehberg; A. Hoeft; C. E. Elger
2000-07-20T23:59:59.000Z
We investigate several quantifiers of the electroencephalogram (EEG) signal with respect to their ability to indicate depth of anesthesia. For 17 patients anesthetized with Sevoflurane, three established measures (two spectral and one based on the bispectrum), as well as a phase space based nonlinear correlation index were computed from consecutive EEG epochs. In absence of an independent way to determine anesthesia depth, the standard was derived from measured blood plasma concentrations of the anesthetic via a pharmacokinetic/pharmacodynamic model for the estimated effective brain concentration of Sevoflurane. In most patients, the highest correlation is observed for the nonlinear correlation index D*. In contrast to spectral measures, D* is found to decrease monotonically with increasing (estimated) depth of anesthesia, even when a "burst-suppression" pattern occurs in the EEG. The findings show the potential for applications of concepts derived from the theory of nonlinear dynamics, even if little can be assumed about the process under investigation.
Puschmann, K G; Vazquez, M; Bonet, J A; Hanslmeier, A; 10.1051/0004-6361:20047193
2012-01-01T23:59:59.000Z
From the inversion of a time series of high resolution slit spectrograms obtained from the quiet sun, the spatial and temporal distribution of the thermodynamical quantities and the vertical flow velocity is derived as a function of logarithmic optical depth and geometrical height. Spatial coherence and phase shift analyzes between temperature and vertical velocity depict the height variation of these physical quantities for structures of different size. An average granular cell model is presented, showing the granule-intergranular lane stratification of temperature, vertical velocity, gas pressure and density as a function of logarithmic optical depth and geometrical height. Studies of a specific small and a specific large granular cell complement these results. A strong decay of the temperature fluctuations with increasing height together with a less efficient penetration of smaller cells is revealed. The T -T coherence at all granular scales is broken already at log tau =-1 or z~170 km. At the layers beyon...
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
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.
On the modeling of time-varying delays
Shah, Chirag Laxmikant
2004-09-30T23:59:59.000Z
This thesis is an effort to develop generalized dynamic models for systems with time-varying time delays. Unlike the simple time-delay model characterized by a transportation lag in the case of a fixed time delay, time-varying delays exhibit quite...
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
A component GARCH model with time varying weights
Nesterov, Yurii
2007/19 A component GARCH model with time varying weights Luc Bauwens and Giuseppe Storti #12;CORE DISCUSSION PAPER 2007/19 A component GARCH model with time varying weights Luc BAUWENS1 and Giuseppe STORTI2 March2007 Abstract We present a novel GARCH model that accounts for time varying, state dependent
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 ...
A Time Model for Distributed Multimedia Applications
KÃ¼hnhauser, Winfried
properties, using time to specify synchroneity, periodicity, ordering and timeliness. Last but not least objects arriving too late may become useless. Here, time is used to synchronize stream processing, encompassing for example HDTV video streams with a bit rate of up to 2.8 GBit/sec. Media streams have real-time
Rocke, David M.
Analysis of MALDI FT-ICR Mass Spectrometry Data: a Time Series Approach Donald A. Barkauskasa/ionization Fourier transform ion cyclotron resonance mass spectrometry is a technique for high mass gamma distribution with varying scale parameter but constant shape parameter and exponent. This enables
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
Intelligent Time-Successive Production Modeling
Mohaghegh, Shahab
;Background Â· Production Data Analysis Decline Curve Analysis (Arps, 1945) Type Curve Matching (Fetkovich Analysis Pressure Data + Production Rate Data Â·Material Balance methods Â·Pseudo time and pseudo pressure
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
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
Modeling and Application of Series Elastic Actuators for Force Control Multi Legged Robots
S, Arumugom; V, Ponselvan
2009-01-01T23:59:59.000Z
Series Elastic Actuators provide many benefits in force control of robots in unconstrained environments. These benefits include high force fidelity, extremely low impedance, low friction, and good force control bandwidth. Series Elastic Actuators employ a novel mechanical design architecture which goes against the common machine design principal of "stiffer is better". A compliant element is placed between the gear train and driven load to intentionally reduce the stiffness of the actuator. A position sensor measures the deflection, and the force output is accurately calculated using Hooke's Law (F=Kx). A control loop then servos the actuator to the desired output force. The resulting actuator has inherent shock tolerance, high force fidelity and extremely low impedance. These characteristics are desirable in many applications including legged robots, exoskeletons for human performance amplification, robotic arms, haptic interfaces, and adaptive suspensions. We describe several variations of Series Elastic Ac...
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
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
Modeling, Safely Advertising and Verifying Time-aware Business Processes
Paris-Sud XI, UniversitÃ© de
Modeling, Safely Advertising and Verifying Time-aware Business Processes : Towards a holistic. Nowadays, the business process model and notation BPMN standard is gaining widspread use in the business, we propose a BPMN extension for capturing temporal requirements during the business process modelling
Modeling highway travel time distribution with conditional probability models
Oliveira Neto, Francisco Moraes [ORNL] [ORNL; Chin, Shih-Miao [ORNL] [ORNL; Hwang, Ho-Ling [ORNL] [ORNL; Han, Lee [University of Tennessee, Knoxville (UTK)] [University of Tennessee, Knoxville (UTK)
2014-01-01T23:59:59.000Z
ABSTRACT Under the sponsorship of the Federal Highway Administration's Office of Freight Management and Operations, the American Transportation Research Institute (ATRI) has developed performance measures through the Freight Performance Measures (FPM) initiative. Under this program, travel speed information is derived from data collected using wireless based global positioning systems. These telemetric data systems are subscribed and used by trucking industry as an operations management tool. More than one telemetric operator submits their data dumps to ATRI on a regular basis. Each data transmission contains truck location, its travel time, and a clock time/date stamp. Data from the FPM program provides a unique opportunity for studying the upstream-downstream speed distributions at different locations, as well as different time of the day and day of the week. This research is focused on the stochastic nature of successive link travel speed data on the continental United States Interstates network. Specifically, a method to estimate route probability distributions of travel time is proposed. This method uses the concepts of convolution of probability distributions and bivariate, link-to-link, conditional probability to estimate the expected distributions for the route travel time. Major contribution of this study is the consideration of speed correlation between upstream and downstream contiguous Interstate segments through conditional probability. The established conditional probability distributions, between successive segments, can be used to provide travel time reliability measures. This study also suggests an adaptive method for calculating and updating route travel time distribution as new data or information is added. This methodology can be useful to estimate performance measures as required by the recent Moving Ahead for Progress in the 21st Century Act (MAP 21).
Simulation of Water Level Fluctuations in Kettle Holes Using a Time Series Model
Kleyer, Michael
online: 21 April 2011 # Society of Wetland Scientists 2011 Abstract Kettle holes are widespread in the future, conservation strategies for kettle holes should include the effects of climate change. Keywords). This number is comparable with the wetland loss in the United States (Dahl 1990; Johnston 1994), Japan
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...
Essays on empirical time series modeling with causality and structural change
Kim, Jin Woong
2006-10-30T23:59:59.000Z
.278 41.056 0.001 0.073 0.036 2 0.027 0.205 0.008 0.395 0.012 0.348 57.943 40.910 0.002 0.129 0.047 9 0.047 0.509 0.227 1.262 0.024 3.096 54.463 39.942 0.013 0.413 0.052 29 0.076 0.820 1.361 2.934 0...
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
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...
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
Statistical Analysis and Time Series Models for Minimum/Maximum Temperatures
Sidorov, Nikita
temperatures, thereby reducing the adverse effect of global warming in the Antarctic Peninsula. Keywords that the observed increase in the minimum temperatures is a consequence of human activity rather than natural causes
A supply forecasting model for Zimbabwe's corn sector: a time series and structural analysis
Makaudze, Ephias
1993-01-01T23:59:59.000Z
The Zimbabwean government utilizes the corn supply forecasts to establish producer prices for the following growing season, estimate corn storage and handling costs, project corn import needs and associated costs, and to assess the Grain Marketing...
Data Tools & Models - Time Series - U.S. Energy Information Administration
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: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625govInstrumentstdmadapInactiveVisitingContract Management Fermi SitePARTOfficeOctoberDaniel WoodIDManagement
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.
Modeling of Travel Time Variations on Urban Links in London
Hasan, Samiul
An econometric framework was developed to combine data from various sources to identify the key factors contributing to travel time variations in Central London. Nonlinear latent variable regression models that explicitly ...
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.
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
Modeling Space-Time Data Using Stochastic Differential Equations
Wolpert, Robert L
(email: cf.sirmans@business.uconn.edu). The authors thank Thomas Thibodeau for providing the Dallas house ecological process models such as photosynthesis, transpiration, and soil moisture; diffusion models for populations, products or technologies; financial processes such as house price and/or land values over time
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...
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.
A Two-Step Filtering approach for detecting maize and soybean phenology with time-series MODIS data
Gitelson, Anatoly
Soybean MODIS Shape-model fitting The crop developmental stage represents essential information Program (CSP) at the University of Nebraska-Lincoln.A comparison of satellite-based retrievals with ground-based crop growth stage observations collected by the CSP over the six growing seasons for these three sites
Egbert, Stephen L.; Martí nez-Meyer, Enrique; Ortega-Huerta, Miguel; Peterson, A. Townsend
2002-06-01T23:59:59.000Z
to be the case, it may be possible to use AVHRR, MODIS, or similar imagery, either in raw form or as easily and cheaply derived datasets, as direct inputs to models that predict species’ distributions. II. METHODS In this pilot analysis, we selected... for Advanced Computational Infrastructure, Earth System Science (NPACI/ESS) Thrust. E.M-M. was supported by a graduate fellowship from the Direccion General de Asuntos del Personal Academico of the National University of Mexico (UNAM...
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.
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.
Time-to-Compromise Model for Cyber Risk Reduction Estimation
Miles A. McQueen; Wayne F. Boyer; Mark A. Flynn; George A. Beitel
2005-09-01T23:59:59.000Z
We propose a new model for estimating the time to compromise a system component that is visible to an attacker. The model provides an estimate of the expected value of the time-to-compromise as a function of known and visible vulnerabilities, and attacker skill level. The time-to-compromise random process model is a composite of three subprocesses associated with attacker actions aimed at the exploitation of vulnerabilities. In a case study, the model was used to aid in a risk reduction estimate between a baseline Supervisory Control and Data Acquisition (SCADA) system and the baseline system enhanced through a specific set of control system security remedial actions. For our case study, the total number of system vulnerabilities was reduced by 86% but the dominant attack path was through a component where the number of vulnerabilities was reduced by only 42% and the time-to-compromise of that component was increased by only 13% to 30% depending on attacker skill level.
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
A Bayesian Bivariate Failure Time Regression Model by Paul Damien
West, Mike
. In engineering studies, reliability is defined as the probability that the system has not failed at time t . The reliability of a system using the model in (1) is given by R(t) = P (T 1 ? t; T 2 ? t) = exp(\\Gammaâ??t)[1 using Markov Chain Monte Carlo methods. Keywords: Gumbel Distribution, Gibbs Sampling, Correlation
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.
Models with time-dependent parameters using transform methods: application to Heston's model
Elices, A
2007-01-01T23:59:59.000Z
This paper presents a methodology to introduce time-dependent parameters for a wide family of models preserving their analytic tractability. This family includes hybrid models with stochastic volatility, stochastic interest-rates, jumps and their non-hybrid counterparts. The methodology is applied to Heston's model. A bootstrapping algorithm is presented for calibration. A case study works out the calibration of the time-dependent parameters to the volatility surface of the Eurostoxx 50 index. The methodology is also applied to the analytic valuation of forward start vanilla options driven by Heston's model. This result is used to explore the forward skew of the case study.
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...
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.
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.
Multiple-relaxation-time lattice Boltzmann kinetic model for combustion
Aiguo Xu; Chuandong Lin; Guangcai Zhang; Yingjun Li
2014-11-25T23:59:59.000Z
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 each simulation step. Via the MRT model, it is more convenient to track the effects of TNE and how the TNE influence the MNE behaviors. The model is verified and validated via well-known benchmark tests. It is found that around the detonation wave there are competition between the viscous effect, thermal diffusion effect and the gradient effects of physical quantities. Consequently, with decreasing the collision parameters, (i) the nonequilibrium region becomes wider and the gradients of physical quantities decrease; (ii) the position where the internal energy in the shocking degree of freedom equals the one averaged over all degrees of freedom moves away from the position for the von Neumann peak.
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.
$J/?$ suppression in the threshold model and QGP formation time
A. K. Chaudhuri
2007-09-03T23:59:59.000Z
In the QGP motivated threshold model, in addition to the normal nuclear absorption, $J/\\psi$'s are subjected to an additional "anomalous" suppression. We have analysed the recently published PHENIX data on the participant number dependence of the nuclear modification factor for $J/\\psi$'s in Au+Au collisions and extracted the anomalous suppression required to explain the data. At mid rapidity $J/\\psi$'s are anomalously suppressed only above a threshold density $n_c$=3.73 fm$^{-2}$. The forward rapidity data on the otherhand require that $J/\\psi$'s are continuously "anomalously" suppressed. The analysis strongly indicate that in mid rapidity $J/\\psi$'s are suppressed in a deconfined medium. Using the PHENIX data on the participant number dependence of the Bjorken energy density, we have also estimated the QGP formation time. For critical temperature $T_c$=192 MeV, estimated QGP formation time ranges between 0.06-0.08 fm/c.
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.
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.
Bayesian Estimation of a Continuous-Time Model for Discretely-Observed Panel Data
Boulton, Aaron Jacob
2014-08-31T23:59:59.000Z
Continuous-time models are used in many areas of science. However, in psychology and related fields, continuous-time models are often difficult to apply because only a small number of repeated observations are typically ...
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.
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
UCLA space-time area law model: A persuasive foundation for hadronization
Abachi, S; Buchanan, C; Chien, A; Chun, S; Hartfiel, B
2007-01-01T23:59:59.000Z
UCLA-HEP-06-001 UCLA space-time area law model: A persuasivedominantly controlled by a Space- Time Area Law (“STAL”), anheavy quarks whose classical space-time world-lines deviate
SCIA 2003 Tutorial: Hidden Markov Models
Roweis, Sam
SCIA 2003 Tutorial: Hidden Markov Models Sam Roweis, University of Toronto June 29, 2003 Probabilistic Generative Models for Time Series · Stochastic models for time-series: y1, y2, . . . , yT To get the system stochastic: p(yt|yt-1, yt-2, . . . , yt-k) · Markov models have two problems: need big order
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
A Survey on Time-aware Business Process Modeling Saoussen Cheikhrouhou1
Paris-Sud XI, UniversitÃ© de
A Survey on Time-aware Business Process Modeling Saoussen Cheikhrouhou1 , Slim Kallel1 , Nawal : Business Process Modeling (BPM) : Workflow : Web service composition : Inter-Organisational Business suites. Consequently, modeling and managing temporal requirements in the business process field
Engineering Instutute Seminar Series
Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)
Engineering Institute Engineering Instutute Seminar Series Engineering Instutute Seminar Series Calendar Contact Professional Staff Assistant Jutta Kayser Engineering Institute...
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...
Siegel, D.I.
1998-01-01T23:59:59.000Z
The large peat basins of North America are an important reservoir in the global carbon cycle and a significant source of atmospheric methane. The authors investigated carbon cycling in the Glacial Lake Agassiz peatlands (GLAP) of Minnesota. Initially in 1990, they identified a dramatic change in the concentration of methane in the pore-waters of the raised bogs in the GLAP during an extreme drought. This methane dissipated when the drought broke in 1991 and the occurrence of deep methane is related to changes in the direction of groundwater flow in the peat column. The production of methane and its diffusive loss to the atmosphere was modeled and was about 10 times less than that measured directly in chambers at the land surface. It is clear from the reversals in hydraulic heat, changes in pore-water chemical composition over time, and paleostratigraphic markers, that regional ground water flow systems that are controlled by climate change are unexpectedly a major control over methanogenesis and carbon cycling in GLAP. Seismic profiles made showed that buried bedrock ridges particularly deflect regional groundwater flow upwards towards the land surface and towards raised bog landforms. In addition, high-resolution GPS measurements from data stations funded by this DOE project have shown this year that the peakland land surface elevation changes daily on a scale of cms, and seasonally on a scale of 10s of cm. This most recent observation is exciting because it may reflect episodic degassing of free phase methane from the peat column to the atmosphere, a source for methane previously unaccounted for by methane researchers.
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
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
An integrated system for real-time Model Predictive Control of humanoid robots
Todorov, Emanuel
this goal. The automatic controller is based on real-time model-predictive control (MPC) applied to the full. The resulting composite cost is sent to the MPC machinery which constructs a new locally-optimal time- varying-based optimal control is called Model-Predictive Control (MPC), an approach that relies on real-time trajectory
ASYMPTOTIC DISTRIBUTION OF ESTIMATES FOR A TIME-VARYING PARAMETER IN A HARMONIC MODEL
Irizarry, Rafael A.
ASYMPTOTIC DISTRIBUTION OF ESTIMATES FOR A TIME-VARYING PARAMETER IN A HARMONIC MODEL WITH MULTIPLE harmonic regression models are useful for cases where harmonic parameters appear to be time-varying. Least, harmonic regression, signal processing, sound analysis, time-varying parameters, weighted least squares
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, ...
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
Toward a Time-centric modeling of Business Processes in BPMN 2.0
Paris-Sud XI, UniversitÃ© de
Toward a Time-centric modeling of Business Processes in BPMN 2.0 Saoussen Cheikhrouhou Re, regulatory, and managerial rules. One of the most promising standards for business process model- ing, namely the Business process Model and notation BPMN poorly addresses the time dimension so far. In this paper, we
A time varying GARCH (p, q) model and related statistical inference
Bandyopadhyay, Antar
A time varying GARCH (p, q) model and related statistical inference Technical Report No: ISINE Institute North-East Centre, Tezpur, Assam-784028 #12;A time varying GARCH (p, q) model and related varying GARCH (tvGARCH (p, q)) model and consider certain related inferential problems. A two-step local
Fast Seismic Modeling and Reverse Time Migration on a GPU Cluster R. Abdelkhalek1
Paris-Sud XI, UniversitÃ© de
Fast Seismic Modeling and Reverse Time Migration on a GPU Cluster R. Abdelkhalek1 , H. Calandra1 equation in an oil exploration industrial context aims at speeding up seismic modeling and Reverse Time application over a sequential code running on general purpose CPU. KEYWORDS: Seismic modeling, Finite
Multiagent Bayesian Forecasting of Structural Time-Invariant Dynamic Systems with
Xiang, Yang
. Alternatively, time series are represented by state-space models, also referred to as multivariate dynamic and science. We study forecasting of stochastic, dynamic systems based on observations from multivariate time to a discrete time, multivariate time series [1, 2]. The primary inference that we address is one- step
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... , generation and wind data as described in the previous section. The model then calculates the forward looking least cost invest- ment and operation plan to serve demand. Figure 4 illustrates the resulting cumulative new build in each of the regions. 10...
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 ...
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...
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
Extending Qualitative Modelling for Simulation of TimeDelayed Behaviour
Miguel, Ian
industrial plants is to choose a measured variable and maintain the reÂ quired value of this variable through a process of meaÂ surement, comparison, and adjustment. A time delay between a disturbance in the plant applicable to simulators that enable synchronous tracking. The rest of this paper is arranged as follows
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
Effectiveness of 4D construction modeling in detecting time-space conflicts of construction sites
Nigudkar, Narendra Shriniwas
2005-11-01T23:59:59.000Z
This research investigated whether 4D construction model effectively helps project participants on construction sites in detecting time-space conflicts in the schedule. Previous researchers on construction space management typically modeled space...
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 .
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 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
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.
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.
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: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645U.S. DOE Office of Science (SC) Environmental Assessments (EA)Budget Â»TraveleBooks FindFirstFirst-time measurements
From Jammer to Gambler: Modeling and Detection of Jamming Attacks against Time-Critical Traffic
Wang, Wenye
From Jammer to Gambler: Modeling and Detection of Jamming Attacks against Time-Critical Traffic attacks. However, existing methods to characterize and detect jamming attacks cannot be applied directly. In this paper, we aim at modeling and detecting jamming attacks against time-critical traffic. We introduce
Dynamic Optimization in Continuous-Time Economic Models (A Guide for the Perplexed)
Sadoulet, Elisabeth
Dynamic Optimization in Continuous-Time Economic Models (A Guide for the Perplexed) Maurice, continuous-time modeling allows application of a powerful mathematical tool, the theory of optimal dynamic control. The basic idea of optimal control theory is easy to grasp-- indeed it follows from elementary
SPACE-TIME BLOCK CODING : JOINT DETECTION AND CHANNEL ESTIMATION USING MULTIPLE MODEL THEORY
Imperial College, London
SPACE-TIME BLOCK CODING : JOINT DETECTION AND CHANNEL ESTIMATION USING MULTIPLE MODEL THEORY Harini of Sheffield, Mappin Street, Sheffield S1 3JD. Email: visakan@sheffield.ac.uk ABSTRACT A joint decoding method for space-time block codes [1, 2] is pre- sented. The space-time coded signals can be viewed as a first
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
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
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
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
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
Observatory, China derived with a solar scintillometer (Seykora 1992) and a Solar Differential Image MotionCurrent Theoretical Models and Future High Resolution Solar Observations: Preparing for ATST ASP-Site Observatory Carsten Denker New Jersey Institute of Technology, Center for Solar Research 323 Martin Luther
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
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.
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
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
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...
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...
USING TIME-LAPSE SEISMIC MEASUREMENTS TO IMPROVE FLOW MODELING OF CO2 INJECTION
Marly. The EOR process in the RCP section of the Weyburn Field uses CO2 and water injection to displaceUSING TIME-LAPSE SEISMIC MEASUREMENTS TO IMPROVE FLOW MODELING OF CO2 INJECTION IN THE WEYBURN, particularly CO2. Time lapse seismic monitoring has motivated changes to the reservoir description in a flow
Telescopic Time-Scale Bridging for Modeling Dispersion in Rapidly Oscillating Flows
Zakhor, Avideh
Telescopic Time-Scale Bridging for Modeling Dispersion in Rapidly Oscillating Flows Ram K between the oscillation and dispersion time scales. Here, we present a methodology based on an implicit introduced errors. The error was found to decrease with mesh refinement, but a small inherent error
Modeling and rendering heterogeneous fog in real-time using B-Spline wavelets
Paris-Sud XI, Université de
Modeling and rendering heterogeneous fog in real-time using B-Spline wavelets Anthony Giroud method to render heterogeneous fog in real-time. The extinction function of our fog, related to its to obtain a decomposition in both space and frequency domains. A grid traversal is used to render the fog
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
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
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
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
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
Smith, Brian (1126 Delaware St., Berkeley, CA 94702); Menchaca, Leticia (1126 Delaware St., Berkeley, CA 94702)
1999-01-01T23:59:59.000Z
A method for determination of .sup.18 O/.sup.16 O and .sup.2 H/.sup.1 H ratios and .sup.3 H concentrations of xylem and subsurface waters using time series sampling, insulating sampling chambers, and combined .sup.18 O/.sup.16 O, .sup.2 H/.sup.1 H and .sup.3 H concentration data on transpired water. The method involves collecting water samples transpired from living plants and correcting the measured isotopic compositions of oxygen (.sup.18 O/.sup.16 O) and hydrogen (.sup.2 H/.sup.1 H and/or .sup.3 H concentrations) to account for evaporative isotopic fractionation in the leafy material of the plant.
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
Real-time Rendering of Complex Vector Data on 3d Terrain Models
Behnke, Sven
Real-time Rendering of Complex Vector Data on 3d Terrain Models M. Schneider, M. Guthe, and R of buildings, streets and runway (from left to right). Abstract. In this paper we present a hybrid technique model. The first part of this hybrid technique is a texture-based approach that is especially suited
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
Quantifying the gap between embedded control models and time-triggered implementations
Pappas, George J.
Quantifying the gap between embedded control models and time-triggered implementations Hakan the controller design is complete, the designed controller model is typically expressed as a set of control control components to exe- cutable code introduces errors due to a variety of factors
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
Using Space-Time Constraints to Guide Model Interoperability Paul F. Reynolds Jr.
Brogan, David
to motion retargeting Â accurately transferring human motions to animated characters. A typical goalUsing Space-Time Constraints to Guide Model Interoperability Paul F. Reynolds Jr. Dept of Computer-924-1039 (V) , 434-982-2214 (F) reynolds@virginia.edu Keywords: Interoperability, Multi-Resolution Modeling
Expressing and computing passage time measures of GSPN models with HASL
Paris-Sud XI, UniversitÃ© de
Expressing and computing passage time measures of GSPN models with HASL Elvio Gilberto Amparore1 measures in (Tagged) GSPNs using the Hybrid Automata Stochastic Logic (HASL) and the statistical model), formally express them in HASL terms and assess them by means of simulation in the COSMOS tool. The interest
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
Harmonic Modelling of Thyristor Bridges using a Simplified Time Domain Method
Lehn, Peter W.
1 Harmonic Modelling of Thyristor Bridges using a Simplified Time Domain Method P. W. Lehn, Senior form solution for the harmonic injection of the converter is developed. For the more general case model module takes as input the ac voltage harmonics at the point of common coupling and outputs
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.
A Flow Time Model for Melt-Cast Insensitive Explosive Process Guillemin Jean-Philippe*, Brunet Luc
Boyer, Edmond
and inserted in our flow time equations. De Larrard's model for the calculation of the maximum packing density The purpose of this article is to propose a predictive model of the flow time necessary for emptying a reactor
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 ...
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 . . . . . . . . . . . . . . . . . . .
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.
Bootstrap Prediction Intervals for Time Series /
Pan, Li
2013-01-01T23:59:59.000Z
1.5 Joint Prediction intervals . . . . . . . . . . . . .1.6 Generalized Bootstrap prediction1.8.1 Bootstrap Prediction Intervals Based on Studentized
Overview of the Radiant Time Series Method
as basis for CLTDs and CLFs 1980 Â ASHRAE publishes Cooling and Heating Load Calculation Manual by Rudoy) 1992 Â ASHRAE publishes 2nd Edition of Cooling and Heating Load Calculation Manual by Mc publishes Cooling and Heating Load Calculation Principles with HBM and RTSM 2001 Â HBM and RTSM
M. Khurshudyan; N. S. Mazhari; D. Momeni; R. Myrzakulov; M. Raza
2014-06-24T23:59:59.000Z
The subject of this paper is to investigate the weak regime covariant scalar-tensor-vector gravity (STVG) theory, known as the MOdified gravity (MOG) theory of gravity. First, we show that the MOG in the absence of scalar fields is converted into $\\Lambda(t),G(t)$ models. Time evolution of the cosmological parameters for a family of viable models have been investigated. Numerical results with the cosmological data have been adjusted. We've introduced a model for dark energy (DE) density and cosmological constant which involves first order derivatives of Hubble parameter. To extend this model, correction terms including the gravitational constant are added. In our scenario, the cosmological constant is a function of time. To complete the model,interaction terms between dark energy and dark matter (DM) manually entered in phenomenological form. Instead of using the dust model for DM, we have proposed DM equivalent to a barotropic fluid. Time evolution of DM is a function of other cosmological parameters. Using sophisticated algorithms, the behavior of various quantities including the densities, Hubble parameter, etc. have been investigated graphically. The statefinder parameters have been used for the classification of DE models. Consistency of the numerical results with experimental data of $SneIa+BAO+CMB$ are studied by numerical analysis with high accuracy.
Time integration for diffuse interface models for two-phase flow
Aland, Sebastian, E-mail: sebastian.aland@tu-dresden.de
2014-04-01T23:59:59.000Z
We propose a variant of the ?-scheme for diffuse interface models for two-phase flow, together with three new linearization techniques for the surface tension. These involve either additional stabilizing force terms, or a fully implicit coupling of the Navier–Stokes and Cahn–Hilliard equation. In the common case that the equations for interface and flow are coupled explicitly, we find a time step restriction which is very different to other two-phase flow models and in particular is independent of the grid size. We also show that the proposed stabilization techniques can lift this time step restriction. Even more pronounced is the performance of the proposed fully implicit scheme which is stable for arbitrarily large time steps. We demonstrate in a Taylor-flow application that this superior coupling between flow and interface equation can decrease the computation time by several orders of magnitude.
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.
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...
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.
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.
Infrared problem for the Nelson model on static space-times
Christian Gérard; Fumio Hiroshima; Annalisa Panati; Akito Suzuki
2011-01-03T23:59:59.000Z
We consider the Nelson model with variable coefficients and investigate the problem of existence of a ground state and the removal of the ultraviolet cutoff. Nelson models with variable coefficients arise when one replaces in the usual Nelson model the flat Minkowski metric by a static metric, allowing also the boson mass to depend on position. A physical example is obtained by quantizing the Klein-Gordon equation on a static space-time coupled with a non-relativistic particle. We investigate the existence of a ground state of the Hamiltonian in the presence of the infrared problem, i.e. assuming that the boson mass tends to 0 at infinity.
Mauve: a Component-based Modeling Framework for Real-time Analysis of Robotic Applications
Mauve: a Component-based Modeling Framework for Real-time Analysis of Robotic Applications Charles paradigm for robotic software devel- opment [2], applied in many applications [3], [4], [5], [6]. Resulting validation of the robotic application, by directly analysing the architecture specification, and limiting
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
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
Physiologically realistic modelling of a mechanism for neural representation of intervals of time
Fukai, Tomoki
-8610, Japan c CREST, Japan Science and Technology (JST), Saitama 332-0012, Japan Abstract A model, Fuji Xerox Co. Ltd., 430 Sakai, Nakai-machi, Ashigarakami-gun, Kanagawa 259-0157, Japan b Department as well as the difference stated above, will lead us to the idea that an interval of time, T
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 for Information and Decision Systems, Massachusetts Institute of Technology, Cambridge, MA, USA {mardavij, mdrine loop system. Under this pricing mechanism, electricity is priced at the exant´e price (calculated based
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
A real-time hydrological model for flood prediction using GIS and the WWW
Blackburn, Alan
water distribution. The development of such a system would be particularly important outside of urban and spatial real-time, emergency decision support. Rather than discuss develop- ments in the modelling Computers, Environment and Urban Systems 27 (2003) 9Â32 www.elsevier.com/locate/compenvurbsys 0198
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
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
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
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
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
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
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
MODELING SPACE-TIME DEPENDENT HELIUM BUBBLE EVOLUTION IN TUNGSTEN ARMOR UNDER IFE CONDITIONS
Ghoniem, Nasr M.
MODELING SPACE-TIME DEPENDENT HELIUM BUBBLE EVOLUTION IN TUNGSTEN ARMOR UNDER IFE CONDITIONS Qiyang 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 neutron
Solar Models: current epoch and time dependences, neutrinos, and helioseismological properties
John N. Bahcall; M. H. Pinsonneault; Sarbani Basu
2001-03-13T23:59:59.000Z
We calculate accurate solar models and report the detailed time dependences of important solar quantities. We use helioseismology to constrain the luminosity evolution of the sun and report the discovery of semi-convection in evolved solar models that include diffusion. In addition, we compare the computed sound speeds with the results of p-mode observations by BiSON, GOLF, GONG, LOWL, and MDI instruments. We contrast the neutrino predictions from a set of eight standard-like solar models and four deviant (or deficient) solar models with the results of solar neutrino experiments. For solar neutrino and for helioseismological applications, we present present-epoch numerical tabulations of characteristics of the standard solar model as a function of solar radius, including the principal physical and composition variables, sound speeds, neutrino fluxes, and functions needed for calculating solar neutrino oscillations.
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.
Discrete-Time Block Models for Transmission Line Channels: Static and Doubly Selective Cases
Galli, Stefano
2011-01-01T23:59:59.000Z
Most methodologies for modeling Transmission Line (TL) based channels define the input-output relationship in the frequency domain (FD) and handle the TL resorting to a two-port network (2PN) formalism. These techniques have not yet been formally mapped into a discrete-time (DT) block model, which is useful to simulate and estimate the channel response as well as to design optimal precoding strategies. TL methods also fall short when they are applied to Time Varying (TV) systems, such as the power line channel. The objective of this paper is to establish if and how one can introduce a DT block model for the Power Line Channel. We prove that it is possible to use Lifting and Trailing Zeros (L&TZ) techniques to derive a DT block model that maps the TL-based input-output description directly in the time domain (TD) block channel model. More specifically, we find an interesting relationship between the elements of an ABCD matrix, defined in the FD, and filtering kernels that allow an elegant representation of...
Chang, S -W; Hartman, J D
2015-01-01T23:59:59.000Z
We introduce new methods for robust high-precision photometry from well-sampled images of a non-crowded field with a strongly varying point-spread function. For this work, we used archival imaging data of the open cluster M37 taken by MMT 6.5m telescope. We find that the archival light curves from the original image subtraction procedure exhibit many unusual outliers, and more than 20% of data get rejected by the simple filtering algorithm adopted by early analysis. In order to achieve better photometric precisions and also to utilize all available data, the entire imaging database was re-analyzed with our time-series photometry technique (Multi-aperture Indexing Photometry) and a set of sophisticated calibration procedures. The merit of this approach is as follows: we find an optimal aperture for each star with a maximum signal-to-noise ratio, and also treat peculiar situations where photometry returns misleading information with more optimal photometric index. We also adopt photometric de-trending based on ...
Real-Time Forcast Model Analysis of Daily Average Building Load for a Thermal Storage System Control
Song, L.; Joo, I. S.; Guwana, S.
of a building and three real-time building load forecasting models were developed. They are first-order autogressive model, random walk model and linear regression model. Finally, the comparison of results show the random walk model provides the best...
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
Analytic solutions for seismic travel time and ray path geometry through simple velocity models.
Ballard, Sanford
2007-12-01T23:59:59.000Z
The geometry of ray paths through realistic Earth models can be extremely complex due to the vertical and lateral heterogeneity of the velocity distribution within the models. Calculation of high fidelity ray paths and travel times through these models generally involves sophisticated algorithms that require significant assumptions and approximations. To test such algorithms it is desirable to have available analytic solutions for the geometry and travel time of rays through simpler velocity distributions against which the more complex algorithms can be compared. Also, in situations where computational performance requirements prohibit implementation of full 3D algorithms, it may be necessary to accept the accuracy limitations of analytic solutions in order to compute solutions that satisfy those requirements. Analytic solutions are described for the geometry and travel time of infinite frequency rays through radially symmetric 1D Earth models characterized by an inner sphere where the velocity distribution is given by the function V (r) = A-Br{sup 2}, optionally surrounded by some number of spherical shells of constant velocity. The mathematical basis of the calculations is described, sample calculations are presented, and results are compared to the Taup Toolkit of Crotwell et al. (1999). These solutions are useful for evaluating the fidelity of sophisticated 3D travel time calculators and in situations where performance requirements preclude the use of more computationally intensive calculators. It should be noted that most of the solutions presented are only quasi-analytic. Exact, closed form equations are derived but computation of solutions to specific problems generally require application of numerical integration or root finding techniques, which, while approximations, can be calculated to very high accuracy. Tolerances are set in the numerical algorithms such that computed travel time accuracies are better than 1 microsecond.
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)
Modeling and analysis of EWMA control schemes with time varying control limits
Chandrasekaran, Sreenivasan
1991-01-01T23:59:59.000Z
of EWMA schemes that afford the desired degree of protection against shifts that lead to a potential increase in scrap. Next, a stochastic model of the EWMA control scheme with supplementary runs rules is constructed. Mean absorption time for various... be reworked constitute scrap. Depending upon the product that is being manufactured, observations falling above the USL or below the LSL will constitute scrap. Without loss of generality, let an observation falling beyond the USL constitute scrap. Clearly...
Fast history matching of time-lapse seismic and production data for high resolution models
Jimenez, Eduardo Antonio
2008-10-10T23:59:59.000Z
..............................................................33 2.20 Discretization elements in finite-differences and streamline simulation..........34 2.21 Faulted grid with permeability contrast along non-neighbor connections. A finite LBL construction is provided to examine the underlying flow field... water cut match for synthetic model.....................................................61 3.6 Flow domain decoupling provided by streamline-based sensitivities ..............62 3.7 Water cut performance before and after generalized travel time...
Viscosity, relaxation time, and dynamics within a model asphalt of larger molecules
Li, Derek D.; Greenfield, Michael L., E-mail: greenfield@egr.uri.edu [Department of Chemical Engineering, University of Rhode Island, Kingston, Rhode Island 02881 (United States)
2014-01-21T23:59:59.000Z
The dynamics properties of a new “next generation” model asphalt system that represents SHRP AAA-1 asphalt using larger molecules than past models is studied using molecular simulation. The system contains 72 molecules distributed over 12 molecule types that range from nonpolar branched alkanes to polar resins and asphaltenes. Molecular weights range from 290 to 890 g/mol. All-atom molecular dynamics simulations conducted at six temperatures from 298.15 to 533.15 K provide a wealth of correlation data. The modified Kohlrausch-Williams-Watts equation was regressed to reorientation time correlation functions and extrapolated to calculate average rotational relaxation times for individual molecules. The rotational relaxation rate of molecules decreased significantly with increasing size and decreasing temperature. Translational self-diffusion coefficients followed an Arrhenius dependence. Similar activation energies of ?42 kJ/mol were found for all 12 molecules in the model system, while diffusion prefactors spanned an order of magnitude. Viscosities calculated directly at 533.15 K and estimated at lower temperatures using the Debye-Stokes-Einstein relationship were consistent with experimental data for asphalts. The product of diffusion coefficient and rotational relaxation time showed only small changes with temperature above 358.15 K, indicating rotation and translation that couple self-consistently with viscosity. At lower temperatures, rotation slowed more than diffusion.
Flow control techniques for real-time media applications in best-effort networks using fluid models
Konstantinou, Apostolos
2004-11-15T23:59:59.000Z
at the application layer. An end-to-end ?uid model is used, including the source bu?er, the network and the destination bu?er. Traditional con- trol techniques, along with more advanced adaptive predictive control methods, are considered in order to provide... OF THE END-TO-END FLOW TRANSPORT SYSTEM : : : : : : : : : : : : : : : : : : : : : : 25 A. Source Bu?er Model . . . . . . . . . . . . . . . . . . . . . 25 B. Network Dynamic Model . . . . . . . . . . . . . . . . . . . 27 1. Time-Varying Time Delay Model...
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.
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 ...
Mark W. Coffey
2008-12-09T23:59:59.000Z
We evaluate binomial series with harmonic number coefficients, providing recursion relations, integral representations, and several examples. The results are of interest to analytic number theory, the analysis of algorithms, and calculations of theoretical physics, as well as other applications.
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.
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
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.
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.
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...
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 ...
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
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.
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.
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
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.
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.
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
Ford, Eric B. [Astronomy Department, University of Florida, 211 Bryant Space Sciences Center, Gainesville, FL 32111 (United States); Ragozzine, Darin; Holman, Matthew J. [Harvard-Smithsonian Center for Astrophysics, 60 Garden Street, Cambridge, MA 02138 (United States); Rowe, Jason F.; Barclay, Thomas; Borucki, William J.; Bryson, Stephen T.; Caldwell, Douglas A.; Kinemuchi, Karen; Koch, David G.; Lissauer, Jack J.; Still, Martin; Tenenbaum, Peter [NASA Ames Research Center, Moffett Field, CA 94035 (United States); Steffen, Jason H. [Fermilab Center for Particle Astrophysics, P.O. Box 500, MS 127, Batavia, IL 60510 (United States); Batalha, Natalie M. [Department of Physics and Astronomy, San Jose State University, San Jose, CA 95192 (United States); Fabrycky, Daniel C. [UCO/Lick Observatory, University of California, Santa Cruz, CA 95064 (United States); Gautier, Thomas N. [Jet Propulsion Laboratory/California Institute of Technology, Pasadena, CA 91109 (United States); Ibrahim, Khadeejah A.; Uddin, Kamal [Orbital Sciences Corporation/NASA Ames Research Center, Moffett Field, CA 94035 (United States); Kjeldsen, Hans, E-mail: eford@astro.ufl.edu [Department of Physics and Astronomy, Aarhus University, DK-8000 Aarhus C (Denmark); and others
2012-09-10T23:59:59.000Z
Transit timing variations provide a powerful tool for confirming and characterizing transiting planets, as well as detecting non-transiting planets. We report the results of an updated transit timing variation (TTV) analysis for 1481 planet candidates based on transit times measured during the first sixteen months of Kepler observations. We present 39 strong TTV candidates based on long-term trends (2.8% of suitable data sets). We present another 136 weaker TTV candidates (9.8% of suitable data sets) based on the excess scatter of TTV measurements about a linear ephemeris. We anticipate that several of these planet candidates could be confirmed and perhaps characterized with more detailed TTV analyses using publicly available Kepler observations. For many others, Kepler has observed a long-term TTV trend, but an extended Kepler mission will be required to characterize the system via TTVs. We find that the occurrence rate of planet candidates that show TTVs is significantly increased ({approx}68%) for planet candidates transiting stars with multiple transiting planet candidates when compared to planet candidates transiting stars with a single transiting planet candidate.
IBM Lecture Series on Service Quality May 19, 2010
Glushko, Robert J.
IBM Lecture Series on Service Quality May 19, 2010 Two New Perspectives for Service System Design at design time or run time, whether it is coarse-grained or fine-grained, and whether it is partial or total
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
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
7000 Series MODIFIED MICROLITERTM
Kleinfeld, David
. This syringe series is unique, as the sample is held in the stainless steel needle. The tungsten plunger wire resistance to plunger movement is felt. Use of pliers on the knurled hub nut may be required to achieve this tightness. The black PTFE-coated plunger sleeve makes it easy to read the exact volume. Two sizes of spacers
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.
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.
Mosuro, Sulaiman
2012-11-29T23:59:59.000Z
application was prototyped for disseminating time-series flood model information and for reporting details of flood events as they occur to serve for model calibration and enhancement, thereby completing the flood modelling lifecycle....
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
Fernandez, Thomas
Programming Dilip P. Ahalpara Institute for Plasma Research, Near Indira Bridge, Gandhinagar-382428, India
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.
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.
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
Dark Energy Model in Anisotropic Bianchi Type-III Space-Time with Variable EoS Parameter
Anirudh Pradhan; Hassan Amirhashchi
2010-10-12T23:59:59.000Z
A new dark energy model in anisotropic Bianchi type-III space-time with variable equation of state (EoS) parameter has been investigated in the present paper. To get the deterministic model, we consider that the expansion $\\theta$ in the model is proportional to the eigen value $\\sigma^{2}_{~2}$ of the shear tensor $\\sigma^{j}_~i$. The EoS parameter $\\omega$ is found to be time dependent and its existing range for this model is in good agreement with the recent observations of SNe Ia data (Knop et al. 2003) and SNe Ia data with CMBR anisotropy and galaxy clustering statistics (Tegmark et al. 2004). It has been suggested that the dark energy that explains the observed accelerating expansion of the universe may arise due to the contribution to the vacuum energy of the EoS in a time dependent background. Some physical aspects of dark energy model are also discussed.
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
Lestelle, Lawrence C.; Lichatowich, James A.; Mobrand, Lars E.; Cullinan, Valerie I.
1994-03-01T23:59:59.000Z
This document describes the formulation and operation of a model designed to assist in planning supplementation projects. It also has application in examining a broader array of questions related to natural fish production and stock restoration. The model is referred to as the Ecosystem Diagnosis and Treatment (EDT) Model because of its utility in helping to diagnose and identify possible treatments to be applied to natural production problems for salmonids. It was developed through the Regional Assessment of Supplementation Project (RASP), which was an initiative to help coordinate supplementation planning in the Columbia Basin. The model is operated within the spreadsheet environment of Quattro Pro using a system of customized menus. No experience with spreadsheet macros is required to operate it. As currently configured, the model should only be applied to spring chinook; modifications are required to apply it to fall chinook and other species. The purpose of the model is to enable managers to consider possible outcomes of supplementation under different sets of assumptions about the natural production system and the integration of supplementation fish into that system. It was designed to help assess uncertainty and the relative risks and benefits of alternative supplementation strategies. The model is a tool to facilitate both planning and learning; it is not a predictive model. This document consists of three principal parts. Part I provides a description of the model. Part II is a guide to running the model. Part III provides theoretical documentation. In addition, a sensitivity analysis of many of the model's parameters is provided in the appendix. This analysis was used to test whether the model produces consistent and reasonable results and to assess the relative effects of specific parameter inputs on outcome.
Area-preserving maps models of gyro-averaged ${\\bf E} \\times {\\bf B}$ chaotic transport
J. D. da Fonseca; D. del-Castillo-Negrete; I. L. Caldas
2014-09-10T23:59:59.000Z
Discrete maps have been extensively used to model 2-dimensional chaotic transport in plasmas and fluids. Here we focus on area-preserving maps describing finite Larmor radius (FLR) effects on ${\\bf E} \\times {\\bf B}$ chaotic transport in magnetized plasmas with zonal flows perturbed by electrostatic drift waves. FLR effects are included by gyro-averaging the Hamiltonians of the maps which, depending on the zonal flow profile, can have monotonic or non-monotonic frequencies. In the limit of zero Larmor radius, the monotonic frequency map reduces to the standard Chirikov-Taylor map, and, in the case of non-monotonic frequency, the map reduces to the standard nontwist map. We show that in both cases FLR leads to chaos suppression, changes in the stability of fixed points, and robustness of transport barriers. FLR effects are also responsible for changes in the phase space topology and zonal flow bifurcations. Dynamical systems methods based on recurrence time statistics are used to quantify the dependence on the Larmor radius of the threshold for the destruction of transport barriers.
Beyond the pseudo-time-dependent approach: chemical models of dense core precursors
Hassel, G E; Bergin, E A
2010-01-01T23:59:59.000Z
Context: Chemical models of dense cloud cores often utilize the so-called pseudo-time-dependent approximation, in which the physical conditions are held fixed and uniform as the chemistry occurs. In this approximation, the initial abundances chosen, which are totally atomic in nature except for molecular hydrogen, are artificial. A more detailed approach to the chemistry of dense cold cores should include the physical evolution during their early stages of formation. Aims: Our major goal is to investigate the initial synthesis of molecular ices and gas-phase molecules as cold molecular gas begins to form behind a shock in the diffuse interstellar medium. The abundances calculated as the conditions evolve can then be utilized as reasonable initial conditions for a theory of the chemistry of dense cores. Methods: Hydrodynamic shock-wave simulations of the early stages of cold core formation are used to determine the time-dependent physical conditions for a gas-grain chemical network. We follow the cold post-sho...
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.
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
Asbeck, Peter M.
mi': iaE Large-Signal HBT Model with Improved Collector Transit Time Formulation for GaAs and In large-signal HBT model which accurately accounts for the intricate hias dependence of collector delay collector delay function accounts for the variation of electron velocity with electric field
. 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
Christensen, Kim
Time-dependent extinction rate and species abundance in a tangled-nature model of biological properties. The macrodynamics exhibit intermittent two-mode switching with a gradually decreasing extinction sense. The form of the species abundance curve compares well with observed func- tional forms. The model
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
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
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...
Plimpton, Steve
2005-01-01T23:59:59.000Z
Cell Modeling via Reacting Diffusive Particles Steven J. Plimpton and Alex Slepoy Sandia National-based simulator called ChemCell that we are developing with the goal of modeling the protein chemistry are represented by triangulated surfaces. Diffusing particles represent proteins, complexes, or other biomolecules
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
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.
Resource characterization series (final)
Hower, J.C.; Wild, G.D.
1981-01-01T23:59:59.000Z
Coals from the Princess Reserve District in northeastern Kentucky were obtained from the R-series cores and from Kentucky Geological Survey collections. The coals span the stratigraphic section from the Bruin coal near the base of the Breathitt Formation to a coal near the top of the Conemaugh Formation. The Princess District coals are high volatile C and B bituminous. High volatile A bituminous coals occur in southern Lawrence County. Reflectance highs and reactive maceral lows were noted in the Princess 3 and Princess 7 coals in along a north-south trend which may be parallel to the Waverly Arch.
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
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
Causal Modeling with Applications to the Foreign Exchange Market
Deaton, Brian D.
2013-11-27T23:59:59.000Z
, Japanese yen, and United States dollar). This information is used in portfolio management to improve risk management, to visualize the causal connections between currencies, and enhance the forecasting ability of time series models. In the first section, a...
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.
Time-dependent Radiation Transfer in the Internal Shock Model Scenario for Blazar Jets
Manasvita Joshi; Markus Boettcher
2010-11-13T23:59:59.000Z
We describe the time-dependent radiation transfer in blazar jets, within the internal shock model. We assume that the central engine, which consists of a black hole and an accretion disk, spews out relativistic shells of plasma with different velocity, mass, and energy. We consider a single inelastic collision between a faster (inner) and a slower (outer) moving shell. We study the dynamics of the collision and evaluate the subsequent emission of radiation via the synchrotron and synchrotron self Compton (SSC) processes after the interaction between the two shells has begun. The collision results in the formation of a forward shock (FS) and a reverse shock (RS) that convert the ordered bulk kinetic energy of the shells into magnetic field energy and accelerate the particles, which then radiate. We assume a cylindrical geometry for the emission region of the jet. We treat the self-consistent radiative transfer by taking into account the inhomogeneity in the photon density throughout the region. In this paper, we focus on understanding the effects of varying relevant input parameters on the simulated spectral energy distribution (SED) and spectral variability patterns.
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
Schlichenmaier, Rolf
of the umbra, FU, amounts to some 25% of that of the overall solar surface, F , while the penumbra of the umbra and decreases gradually outwards, reaches some 800 Gauss at the outer continuum = 211 #12;212 Schlichenmaier p-g . A model that incorporates three stratifications (the umbra, the penum
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.
Time-domain Simulation of Multibody Floating Systems based on State-space Modeling Technology
Yu, Xiaochuan
2012-10-19T23:59:59.000Z
A numerical scheme to simulate time-domain motion responses of multibody floating systems has been successfully proposed. This scheme is integrated into a time-domain simulation tool, with fully coupled hydrodynamic ...
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
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.
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 ...
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.
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
Hydrogeologic Modeling: GLY-5826 Meeting time: T, Th 11-12:15
Sukop, Mike
11. Finite Element Methods a. MicroFEM b. SUTRA 12. Fractured Media 13. Analytic Element models Level: Graduate 5826 Sections: 1 Course Catalogue Description Techniques used in modeling groundwater introductions to the theory and implementation of hydrogeological modeling techniques. Students will develop
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
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
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
Operating Innovative Networks Workshop Series
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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...
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 ...
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
Metric spaces as models for real-time concurrency G.M. Reed and A.W. Roscoe1
Roscoe, Bill
Pro- cesses) We shall essentially extend the abstract syntax for untimed CSP from [BHR,BR] (with for real time concurrent systems, based on the fail- ures model for CSP. The fixed point theory is based. We have chosen to base our work on (extensions of) the theoretical version of CSP and to try