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 networks, Neural networks, Modeling, Forecasting, Energy demand, Time series forecasting, Power system demand time series based only on data for six years to forecast the demand for the seventh year. Both
Modeling Time Series of Real Systems using Genetic Programming
Dilip P. Ahalpara; Jitendra C. Parikh
2006-07-14
Analytic models of two computer generated time series (Logistic map and Rossler system) and two real time series (ion saturation current in Aditya Tokamak plasma and NASDAQ composite index) are constructed using Genetic Programming (GP) framework. In each case, the optimal map that results from fitting part of the data set also provides a very good description of rest of the data. Predictions made using the map iteratively range from being very good to fair.
Functional Coefficient Regression Models for Non-linear Time Series: A Polynomial
Shen, Haipeng
Functional Coefficient Regression Models for Non-linear Time Series: A Polynomial Spline Approach of functional coefficient regression models for non-linear time series. Consistency and rate of convergence to estimate the coefficient functions. Cai et al. (2000) and Chen & Liu (2001) used the local linear method
A regression model with a hidden logistic process for feature extraction from time series
Chamroukhi, Faicel
A regression model with a hidden logistic process for feature extraction from time series Faicel from time series is proposed in this paper. This approach consists of a specific regression model Reweighted Least-Squares (IRLS) algorithm. A piecewise regression algorithm and its iterative variant have
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
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
Siggiridou, Elsa
2015-01-01
Granger causality has been used for the investigation of the inter-dependence structure of the underlying systems of multi-variate time series. In particular, the direct causal effects are commonly estimated by the conditional Granger causality index (CGCI). In the presence of many observed variables and relatively short time series, CGCI may fail because it is based on vector autoregressive models (VAR) involving a large number of coefficients to be estimated. In this work, the VAR is restricted by a scheme that modifies the recently developed method of backward-in-time selection (BTS) of the lagged variables and the CGCI is combined with BTS. Further, the proposed approach is compared favorably to other restricted VAR representations, such as the top-down strategy, the bottom-up strategy, and the least absolute shrinkage and selection operator (LASSO), in terms of sensitivity and specificity of CGCI. This is shown by using simulations of linear and nonlinear, low and high-dimensional systems and different t...
Modeling Gene Regulatory Networks from Time Series Data using Particle Filtering
Noor, Amina
2012-10-19
This thesis considers the problem of learning the structure of gene regulatory networks using gene expression time series data. A more realistic scenario where the state space model representing a gene network evolves nonlinearly is considered while...
Modelling signal interactions with application to financial time series
Jain, Bonny
2014-01-01
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 ...
Desertification of high latitude ecosystems: conceptual models, time-series analyses and experiments
Thorsson, Johann
2009-05-15
-1 DESERTIFICATION OF HIGH LATITUDE ECOSYSTEMS: CONCEPTUAL MODELS, TIME-SERIES ANALYSES AND EXPERIMENTS A Dissertation by JOHANN THORSSON Submitted to the Office of Graduate Studies of Texas A&M University in partial fulfillment of the requirements... for the degree of DOCTOR OF PHILOSOPHY December 2008 Major Subject: Rangeland Ecology and Management DESERTIFICATION OF HIGH LATITUDE ECOSYSTEMS: CONCEPTUAL MODELS, TIME-SERIES ANALYSES AND EXPERIMENTS A Dissertation by JOHANN...
A FAST MODEL-BUILDING METHOD FOR TIME SERIES USING GENETIC PROGRAMMING
Fernandez, Thomas
generation, initial values of the parameters in an model (offspring) are inherited from the parents. step-2 series and applied it to lots of time series: (1) computer generated chaos e.g. Logistic, Loessler is made by using a set of finite number of past values measured from the system )x,,x,(xfx~ n-t2-t1-tt
IMPROVED SEMI-PARAMETRIC TIME SERIES MODELS OF AIR POLLUTION AND MORTALITY
Dominici, Francesca
IMPROVED SEMI-PARAMETRIC TIME SERIES MODELS OF AIR POLLUTION AND MORTALITY Francesca Dominici series analyses of air pollution and health attracted the attention of the scientific community, policy makers, the press, and the diverse stakeholders con- cerned with air pollution. As the Environmental
Self-organizing Time Series Model Tomoyuki Higuchi
Higuchi, Tomoyuki
.1) observation model yt r( jxt obs) (1.2) where xt is an nx 1 vector of unobserved sate variables, and yt R) (1.6) where F G, and H are nx nx, nx nv , and ny nx matrices, respectively. Q and R enormously with respect to the state dimension nx (Carlin, Polson and Sto er 1992, Fahrmeir 1992, Fruhwirth
TIME SERIES MODELS OF THREE SETS OF RXTE OBSERVATIONS OF 4U 1543-47
Koen, C.
2013-03-01
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.
Aalborg Universitet ARIMA-Based Time Series Model of Stochastic Wind Power Generation
Bak-Jensen, Birgitte
the nonstationarity and physical limits of stochastic wind power generation. The model is constructed based on wind power measurement of one year from the Nysted offshore wind farm in Denmark. The proposed limitedAalborg Universitet ARIMA-Based Time Series Model of Stochastic Wind Power Generation Chen, Peiyuan
Denoising Deterministic Time Series
Steven P. Lalley; Andrew B. Nobel
2006-04-21
This paper is concerned with the problem of recovering a finite, deterministic time series from observations that are corrupted by additive, independent noise. A distinctive feature of this problem is that the available data exhibit long-range dependence and, as a consequence, existing statistical theory and methods are not readily applicable. This paper gives an analysis of the denoising problem that extends recent work of Lalley, but begins from first principles. Both positive and negative results are established. The positive results show that denoising is possible under somewhat restrictive conditions on the additive noise. The negative results show that, under more general conditions on the noise, no procedure can recover the underlying deterministic series.
Siracusa, Michael Richard, 1980-
2009-01-01
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. ...
Statistical criteria for characterizing irradiance time series.
Stein, Joshua S.; Ellis, Abraham; Hansen, Clifford W.
2010-10-01
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.
Time Series Analysis 1 Time series in astronomy
Babu, G. Jogesh
(supernovae, gamma-ray bursts) Difficulties in astronomical time series Gapped data streams: Diurnal & monthly phenomena: thermonuclear (novae, X-ray bursts), magnetic reconnection (solar/stellar flares), star death); pulsation (helioseismology, Cepheids) Stochastic phenomena: accretion (CVs, X-ray binaries, Seyfert gals
Maximum likelihood parameter estimation in time series models using sequential Monte Carlo
Yildirim, Sinan
2013-06-11
, respectively. This approach is useful to handle the case where the columns of Y are generated sequentially in time, such as in audio signal processing. Usually very large number of columns in Y leads to the necessity of online algorithms to learn the model... .6 (dashed lines). For illustrative purposes, every 1000th estimate is shown . . . . . . . . . . . . . . . . . . . . . . . 130 6.1 Histograms of Monte Carlo estimates of gradients of log p?,?,?? (Y ?,?,?) w.r.t. the parameters of the ?-stable distribution...
Segmenting Time Series for Weather Forecasting
Reiter, Ehud
summarisation. We found three alternative ways in which we could model data summarisation. One approach is based turbines. In the domain of meteorology, time series data produced by numerical weather prediction (NWP) models is summarised as weather forecast texts. In the domain of gas turbines, sensor data from
Kaski, Samuel
Series Yubin Park1 Carlos M. Carvalho2 Joydeep Ghosh1 1 Department of Electrical Computer Engineering by the authors. In the fraud detection community, purchase records and click streams have been key factors: interpretability and extensibility. Indeed, the VAR process has a rich history with parsimonious the- oretical
Regression quantiles for time series
Cai, Zongwu
2002-02-01
~see, e+g+, Ibragimov and Linnik, 1971, p+ 316!+ Namely, partition REGRESSION QUANTILES FOR TIME SERIES 187 $1, + + + , n% into 2qn 1 1 subsets with large block of size r 5 rn and small block of size s 5 sn+ Set q 5 qn 5 ? n rn 1 sn? , (A.7) where {x...! are the standard Lindeberg–Feller conditions for asymptotic normality of Qn,1 for the independent setup+ Let us first establish ~A+8!+ To this effect, we define the large-block size rn by rn 5 {~nhn!102} and the small-block size sn 5 {~nhn!1020log n}+ Then, as n r...
Marzouk, Youssef; Fast P. (Lawrence Livermore National Laboratory, Livermore, CA); Kraus, M.; Ray, J. P.
2006-01-01
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.
IMPROVED SEMI-PARAMETRIC TIME SERIES MODELS OF AIR POLLUTION AND MORTALITY
Hastie, Trevor
we provide improvements in semi-parametric regression directly relevant to risk estimation in time of an intense national debate, that has led to a high profile research agenda (National Research Council, 1998, 1999, 2001). In the United States and elsewhere, evidence
Detection Methods for Astronomical Time Series
Coehlo, Nathan Kirk
2010-01-01
Time Series by Nathan Kirk Coehlo A dissertation submittedCopyright 2010 by Nathan Kirk Coehlo Abstract DetectionTime Series by Nathan Kirk Coehlo Doctor of Philosophy in
Inverting multispectral thermal time series images of volcanic eruptions for lava emplacement models
Barnie, T. D.; Oppenheimer, C.
2015-06-04
is small – this can be 434 considered to model a situation in which there is a lot of ‘churn’ at the hot surface and most 435 material is removed in some way. In Figure 10 the NAE has a the same support at high temperatures 436 as the previous ‘complex...
Chen, Wei-Chen [ORNL; Maitra, Ranjan [Iowa State University
2011-01-01
We propose a model-based approach for clustering time series regression data in an unsupervised machine learning framework to identify groups under the assumption that each mixture component follows a Gaussian autoregressive regression model of order p. Given the number of groups, the traditional maximum likelihood approach of estimating the parameters using the expectation-maximization (EM) algorithm can be employed, although it is computationally demanding. The somewhat fast tune to the EM folk song provided by the Alternating Expectation Conditional Maximization (AECM) algorithm can alleviate the problem to some extent. In this article, we develop an alternative partial expectation conditional maximization algorithm (APECM) that uses an additional data augmentation storage step to efficiently implement AECM for finite mixture models. Results on our simulation experiments show improved performance in both fewer numbers of iterations and computation time. The methodology is applied to the problem of clustering mutual funds data on the basis of their average annual per cent returns and in the presence of economic indicators.
Normalizing the causality between time series
Liang, X San
2015-01-01
Recently, a rigorous yet concise formula has been derived to evaluate the information flow, and hence the causality in a quantitative sense, between time series. To assess the importance of a resulting causality, it needs to be normalized. The normalization is achieved through distinguishing three types of fundamental mechanisms that govern the marginal entropy change of the flow recipient. A normalized or relative flow measures its importance relative to other mechanisms. In analyzing realistic series, both absolute and relative information flows need to be taken into account, since the normalizers for a pair of reverse flows belong to two different entropy balances; it is quite normal that two identical flows may differ a lot in relative importance in their respective balances. We have reproduced these results with several autoregressive models. We have also shown applications to a climate change problem and a financial analysis problem. For the former, reconfirmed is the role of the Indian Ocean Dipole as ...
Multivariate Time Series Forecasting in Incomplete Environments
Roberts, Stephen
Multivariate Time Series Forecasting in Incomplete Environments Technical Report PARG 08-03 Seung of Oxford December 2008 #12;Seung Min Lee and Stephen J. Roberts Technical Report PARG 08-03 Multivariate missing observations and forecasting future values in incomplete multivariate time series data. We study
14.384 Time Series Analysis, Fall 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 ...
Integrated method for chaotic time series analysis
Hively, L.M.; Ng, E.G.
1998-09-29
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)
1998-01-01
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.
1991-12-31
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.
1991-01-01
This paper describes the use of artificial neural networks to model the complex oscillations defined by a chaotic Verhuist animal population dynamic. A predictive artificial neural network model is developed and tested, and results of computer simulations are given. These results show that the artificial neural network model predicts the chaotic time series with various initial conditions, growth parameters, or noise.
Can biomass time series be reliably assessed from CPUE time series data Francis Lalo1
Hawai'i at Manoa, University of
1 Can biomass time series be reliably assessed from CPUE time series data only? Francis Laloë1 to abundance. This means (i) that catchability is constant and (ii) that all the biomass is catchable. If so, relative variations in CPUE indicate the same relative variations in biomass. Myers and Worm consider
Nonlinear time-series analysis revisited
Elizabeth Bradley; Holger Kantz
2015-03-25
In 1980 and 1981, two pioneering papers laid the foundation for what became known as nonlinear time-series analysis: the analysis of observed data---typically univariate---via dynamical systems theory. Based on the concept of state-space reconstruction, this set of methods allows us to compute characteristic quantities such as Lyapunov exponents and fractal dimensions, to predict the future course of the time series, and even to reconstruct the equations of motion in some cases. In practice, however, there are a number of issues that restrict the power of this approach: whether the signal accurately and thoroughly samples the dynamics, for instance, and whether it contains noise. Moreover, the numerical algorithms that we use to instantiate these ideas are not perfect; they involve approximations, scale parameters, and finite-precision arithmetic, among other things. Even so, nonlinear time-series analysis has been used to great advantage on thousands of real and synthetic data sets from a wide variety of systems ranging from roulette wheels to lasers to the human heart. Even in cases where the data do not meet the mathematical or algorithmic requirements to assure full topological conjugacy, the results of nonlinear time-series analysis can be helpful in understanding, characterizing, and predicting dynamical systems.
Random Matrix Spectra as a Time Series
Ruben Fossion; Gamaliel Torres Vargas; Juan Carlos López Vieyra
2013-11-23
Spectra of ordered eigenvalues of finite Random Matrices are interpreted as a time series. Dataadaptive techniques from signal analysis are applied to decompose the spectrum in clearly differentiated trend and fluctuation modes, avoiding possible artifacts introduced by standard unfolding techniques. The fluctuation modes are scale invariant and follow different power laws for Poisson and Gaussian ensembles, which already during the unfolding allows to distinguish the two cases.
Wang, Ruofan; Wang, Jiang; Deng, Bin Liu, Chen; Wei, Xile; Tsang, K. M.; Chan, W. L.
2014-03-15
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.
Abstract--We present a method to integrate environmental time series
89 Abstract--We present a method to integrate environmental time series into stock assessment). A general framework for integrating environmental time series into stock assessment models: model models and to test the significance of correlations between population processes and the environmental
Nonlinear chaos in temperature time series: Part I: Case studies
Yaron Rosenstein; Gal Zahavi
2012-11-27
In this work we present 3 case studies of local temperature time series obtained from stations in Europe and Israel. The nonlinear nature of the series is presented along with model based forecasting. Data is nonlinearly filtered using high dimensional projection and analysis is performed on the filtered data. A lorenz type model of 3 first order ODEs is then fitted. Forecasts are shown for periods of 100 days ahead, outperforming any existing forecast method known today. While other models fail at forecasting periods above 11 days, ours shows remarkable stability 100 days ahead. Thus finally a local dynamical system if found for local temperature forecasting not requiring solution of Navier-Stokes equations. Thus saving computational costs.
Exact Primitives for Time Series Data Mining
Mueen, Abdullah Al
2012-01-01
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,
Burra G. Sidharth
2008-09-03
We briefly review two concepts of time - the usual time associated with "being" and more recent ideas, answering to the description of "becoming". The approximation involved in the former is examined. Finally we argue that it is (unpredictable) fluctuations that underlie time.
Mining Time Series Data: Flying Insect Classification and Detection
Chen, Yanping
2015-01-01
Application of Data Mining. ” KDD'11: 761-764, 2011. G.Wang, E. J. Keogh. “Querying and mining of time series data.Mining
Time Series Photometry Data: Standard Access, Standard Formats
Holl, András
Time Series Photometry Data: Standard Access, Standard Formats Andr#19; as Holl Konkoly Observatory a discussion on data access and #12;le format aspects of photometry. Introduction Presently there is time series photometry data available in public databases, but the access to these varies from one collection
Efficient Mining of Partial Periodic Patterns in Time Series Database
Dong, Guozhu
Efficient Mining of Partial Periodic Patterns in Time Series Database In ICDE 99 Jiawei Han \\Lambda peri odic patterns in timeseries databases, is an interesting data mining problem. Previous studies several algorithms for efficient mining of par tial periodic patterns, by exploring some interesting
A Multivariate Approach to Estimate Complexity of FMRI Time Series
A Multivariate Approach to Estimate Complexity of FMRI Time Series Henry SchÂ¨utze1,2 , Thomas (MPSE), a multivariate entropy ap- proach that estimates spatio-temporal complexity of fMRI time series. In a temporally sliding window, MPSE measures the differential entropy of an assumed multivariate Gaussian density
A METHOD FOR IDENTIFYING REPETITION STRUCTURE IN MUSICAL AUDIO BASED ON TIME SERIES PREDICTION
Dixon, Simon
A METHOD FOR IDENTIFYING REPETITION STRUCTURE IN MUSICAL AUDIO BASED ON TIME SERIES PREDICTION This paper investigates techniques for determining the repeti- tion structure of musical audio. In particular. To this end, we propose a novel approach based on multivari- ate time series modelling of audio features
2001, Applied Statistics, 50, 143-154. Nonlinear autoregressive time series with multivariate
Glasbey, Chris
series is proposed to model solar radiation data, by specifying joint marginal distributions at low lags, Multiprocess dynamic linear model, Solar radiation 1 Introduction Knowledge of the statistical characteristics of time series of solar radiation has many uses, one of which is in the design and evaluation of solar
Text Queries on Document Time Series
Baeza-Yates, Ricardo
Retrieved for Query "iraq war" #12;Smoothed Timeline for "iraq war" #12;Temporal Models Goal: Estimate;Documents Retrieved for Query "iraq war" #12;Weighted by Document Relevance #12;Smoothed with Background
Multiple Time Series 7.1 Introduction
Penny, Will
, W.D. Penny, April 2000. 7.2.1 CrossÂcorrelation is asymmetric First, we reÂcap as to why the auto, W.D. Penny, April 2000. 89 (a) 0 20 40 60 80 100 -2 -1 0 1 2 3 4 Figure 7.1: Signals x t (top) and y this should occur ? #12; 90 Signal Processing Course, W.D. Penny, April 2000. 7.2.3 TimeÂDelay Estimation
Times Series Study of Effects of Petroleum Production on GDP
Ballinger, Leslie 1991-
2012-05-02
development. The countries studied include: Argentina, Canada, Colombia, the United States, Mexico, Venezuela, Peru, and Indonesia. The dates of analysis are different for every country due to data reliability. This paper focuses mainly on a time series...
Generalized Volterra-Wiener and surrogate data methods for complex time series analysis
Shashidhar, Akhil
2006-01-01
This thesis describes the current state-of-the-art in nonlinear time series analysis, bringing together approaches from a broad range of disciplines including the non-linear dynamical systems, nonlinear modeling theory, ...
Nonparametric estimation of additive nonlinear ARX time series: Local Linear Fitting and Projections
Cai, Zongwu; Masry, Elias
2000-08-01
We consider the estimation and identification of the components (endogenous and exogenous) of additive nonlinear ARX time series models. We employ a local polynomial fitting scheme coupled with projections. We establish ...
First time-series optical photometry from Antarctica
K. G. Strassmeier; R. Briguglio; T. Granzer; G. Tosti; I. DiVarano; I. Savanov; M. Bagaglia; S. Castellini; A. Mancini; G. Nucciarelli; O. Straniero; E. Distefano; S. Messina; G. Cutispoto
2008-07-18
Beating the Earth's day-night cycle is mandatory for long and continuous time-series photometry and had been achieved with either large ground-based networks of observatories at different geographic longitudes or when conducted from space. A third possibility is offered by a polar location with astronomically-qualified site characteristics. Aims. In this paper, we present the first scientific stellar time-series optical photometry from Dome C in Antarctica and analyze approximately 13,000 CCD frames taken in July 2007. We conclude that high-precision CCD photometry with exceptional time coverage and cadence can be obtained at Dome C in Antarctica and be successfully used for time-series astrophysics.
Resampling Methodology in Spatial Prediction and Repeated Measures Time Series
Rister, Krista Dianne
2012-02-14
of an SEM image. . . . . . . . . . . . . . . . . . . . . . . . 56 10 Framework of time time series representation of SEM image. . . . . . 57 11 Approximate values of f(L; ?, ?) for L = 200 for varying values of ?. 63 12 Bootstrap variance estimates... Cor- rected Predictor . . . . . . . . . . . . . . . . . . . . . 20 3. Bias of Predictors . . . . . . . . . . . . . . . . . . . . 21 F. Simulations . . . . . . . . . . . . . . . . . . . . . . . . . . 26 1. Framework...
Feature-preserving interpolation and filtering of environmental time series
Mariethoz, Gregoire; Jougnot, Damien; Rezaee, Hassan
2015-01-01
We propose a method for filling gaps and removing interferences in time series for applications involving continuous monitoring of environmental variables. The approach is non-parametric and based on an iterative pattern-matching between the affected and the valid parts of the time series. It considers several variables jointly in the pattern matching process and allows preserving linear or non-linear dependences between variables. The uncertainty in the reconstructed time series is quantified through multiple realizations. The method is tested on self-potential data that are affected by strong interferences as well as data gaps, and the results show that our approach allows reproducing the spectral features of the original signal. Even in the presence of intense signal perturbations, it significantly improves the signal and corrects bias introduced by asymmetrical interferences. Potential applications are wide-ranging, including geophysics, meteorology and hydrology.
Iterative prediction of chaotic time series using a recurrent neural network
Essawy, M.A.; Bodruzzaman, M. [Tennessee State Univ., Nashville, TN (United States). Dept. of Electrical and Computer Engineering; Shamsi, A.; Noel, S. [USDOE Morgantown Energy Technology Center, WV (United States)
1996-12-31
Chaotic systems are known for their unpredictability due to their sensitive dependence on initial conditions. When only time series measurements from such systems are available, neural network based models are preferred due to their simplicity, availability, and robustness. However, the type of neutral network used should be capable of modeling the highly non-linear behavior and the multi-attractor nature of such systems. In this paper the authors use a special type of recurrent neural network called the ``Dynamic System Imitator (DSI)``, that has been proven to be capable of modeling very complex dynamic behaviors. The DSI is a fully recurrent neural network that is specially designed to model a wide variety of dynamic systems. The prediction method presented in this paper is based upon predicting one step ahead in the time series, and using that predicted value to iteratively predict the following steps. This method was applied to chaotic time series generated from the logistic, Henon, and the cubic equations, in addition to experimental pressure drop time series measured from a Fluidized Bed Reactor (FBR), which is known to exhibit chaotic behavior. The time behavior and state space attractor of the actual and network synthetic chaotic time series were analyzed and compared. The correlation dimension and the Kolmogorov entropy for both the original and network synthetic data were computed. They were found to resemble each other, confirming the success of the DSI based chaotic system modeling.
NONLINEAR MULTIVARIATE AND TIME SERIES ANALYSIS BY NEURAL NETWORK METHODS
Hsieh, William
NONLINEAR MULTIVARIATE AND TIME SERIES ANALYSIS BY NEURAL NETWORK METHODS William W. Hsieh] Methods in multivariate statistical analysis are essential for working with large amounts of geophysical multivariate statistical analysis, there is a hierarchy of methods, starting with linear regression at the base
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
Symbolic Dynamic Analysis of Transient Time Series for Fault
Ray, Asok
Symbolic Dynamic Analysis of Transient Time Series for Fault Detection in Gas Turbine Engines paper presents a symbolic dynamics-based method for detection of incipient faults in gas turbine engines dynamics, fault detection, aircraft gas turbine engines 1 Introduction Performance monitoring of aircraft
Discrimination of Locally Stationary Time Series Based on the Excess Mass Functional
Polonik, Wolfgang
Discrimination of Locally Stationary Time Series Based on the Excess Mass Functional Gabriel CHANDLER and Wolfgang POLONIK Discrimination of time series is an important practical problem the time series. Instead, features are measured for each time series, and discrimination is based
Donges, Jonathan F; Beronov, Boyan; Wiedermann, Marc; Runge, Jakob; Feng, Qing Yi; Tupikina, Liubov; Stolbova, Veronika; Donner, Reik V; Marwan, Norbert; Dijkstra, Henk A; Kurths, Jürgen
2015-01-01
We introduce the pyunicorn (Pythonic unified complex network and recurrence analysis toolbox) open source software package for applying and combining modern methods of data analysis and modeling from complex network theory and nonlinear time series analysis. pyunicorn is a fully object-oriented and easily parallelizable package written in the language Python. It allows for the construction of functional networks such as climate networks in climatology or functional brain networks in neuroscience representing the structure of statistical interrelationships in large data sets of time series and, subsequently, investigating this structure using advanced methods of complex network theory such as measures and models for spatial networks, networks of interacting networks, node-weighted statistics or network surrogates. Additionally, pyunicorn provides insights into the nonlinear dynamics of complex systems as recorded in uni- and multivariate time series from a non-traditional perspective by means of recurrence qua...
Integrated Mathematical Modeling Software Series of Vehicle Propulsion...
Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site
Mathematical Modeling Software Series of Vehicle Propulsion System: (1) Tractive Effort (T sub ew) of Vehicle Road WheelTrack Sprocket Integrated Mathematical Modeling Software...
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
Characterizing Weak Chaos using Time Series of Lyapunov Exponents
R. M. da Silva; C. Manchein; M. W. Beims; E. G. Altmann
2015-06-13
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.; Smith, Jeff; Dugan, Roger
2013-01-01
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.
EMCS and time-series energy data analysis in a large government office building
Piette, Mary Ann; Kinney, Satkartar; Friedman, Hannah
2001-01-01
th EMCS and Time-Series Energy Data Analysis in a LargeEMCS and Time-Series Energy Data Analysis in a Largeyears of utility bill energy data to evaluate whole-building
New Problems for an Old Design: Time-Series Analyses of Air Pollution and Health
Dominici, Francesca
New Problems for an Old Design: Time-Series Analyses of Air Pollution and Health Jonathan M. Samet1 of particulate air pollution on the same or recent days (1;2). Studies of similar time-series design of morbidity for adverse effects of particulate air pollution on the public's health. The daily time-series studies of air
Exposure Measurement Error in Time-Series Studies of Air Pollution: Concepts and Consequences
Dominici, Francesca
1 Exposure Measurement Error in Time-Series Studies of Air Pollution: Concepts and Consequences S in time-series studies 1 11/11/99 Keywords: measurement error, air pollution, time series, exposure of air pollution and health. Because measurement error may have substantial implications for interpreting
Ray, Asok
February 8, 2015 16:49 World Scientific Review Volume - 9in x 6in "time-series classification" page:49 World Scientific Review Volume - 9in x 6in "time-series classification" page 2 2 S. Bahrampour and N. M
Detecting and interpreting distortions in hierarchical organization of complex time series
Dro?d?, Stanis?aw
2015-01-01
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...
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.
1996-03-31
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)
2006-07-15
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.
On the long-term correlations and multifractal properties of electric arc furnace time series
Livi, Lorenzo; Rizzi, Antonello; Sadeghian, Alireza
2015-01-01
In this paper, we study long-term correlations and multifractal properties elaborated from time series of three-phase current signals coming from an industrial electric arc furnace plant. Implicit sinusoidal trends are suitably detected in the scaling of the fluctuation function of such time series. Time series are then initially filtered via a Fourier based analysis, removing hence such strong periodicities. In the filtered time series we detected long-term, positive correlations. The presence of persistent correlations is in agreement with the typical V--I characteristic (hysteresis) of the electric arc furnace, justifying thus the memory effects found in the current time series. The multifractal signature is strong enough in the filtered time series to be effectively classified as multifractal.
Tataw, Oben Moses
2013-01-01
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.
348 Book Reviews Nonlinear Time Series: Nonparametric and Parametric Methods.
Fan, Jianqing
diagnostics, and then computes optimal predictors for future values of the series. Autoregressive moving aver of topics covered in this book makes for a large and awk- ward load. It is like coming home from the grocery, and breaks, and some items are lost altogether. This book has scratches scattered throughout, in the form
Input Data Reduction for the Prediction of Financial Time Series
Verleysen, Michel
on data from the BEL20 market index. 1. Introduction Since the beginning of this century, the question of the predictability of financial series (at least of stock market prices) has been the subject of a highly. To perform the transformation between the initial inputs and the new variables, we may choose to use a linear
Multifractal analysis of stress time series during ultrathin lubricant film melting
A. V. Khomenko; I. A. Lyashenko; V. N. Borisyuk
2010-07-20
Melting of an ultrathin lubricant film confined between two atomically flat surfaces is we studied using the rheological model for viscoelastic matter approximation. Phase diagram with domains, corresponding to sliding, dry, and two types of $stick-slip$ friction regimes has been built taking into account additive noises of stress, strain, and temperature of the lubricant. The stress time series have been obtained for all regimes of friction using the Stratonovich interpretation. It has been shown that self-similar regime of lubricant melting is observed when intensity of temperature noise is much larger than intensities of strain and stress noises. This regime is defined by homogenous distribution, at which characteristic stress scale is absent. We study stress time series obtained for all friction regimes using multifractal detrended fluctuation analysis. It has been shown that multifractality of these series is caused by different correlations that are present in the system and also by a power-law distribution. Since the power-law distribution is related to small stresses, this case corresponds to self-similar solid-like lubricant.
Engine Control Improvement through Application of Chaotic Time Series Analysis
Green, J.B., Jr.; Daw, C.S.
2003-07-15
The objective of this program was to investigate cyclic variations in spark-ignition (SI) engines under lean fueling conditions and to develop options to reduce emissions of nitrogen oxides (NOx) and particulate matter (PM) in compression-ignition direct-injection (CIDI) engines at high exhaust gas recirculation (EGR) rates. The CIDI activity builds upon an earlier collaboration between ORNL and Ford examining combustion instabilities in SI engines. Under the original CRADA, the principal objective was to understand the fundamental causes of combustion instability in spark-ignition engines operating with lean fueling. The results of this earlier activity demonstrated that such combustion instabilities are dominated by the effects of residual gas remaining in each cylinder from one cycle to the next. A very simple, low-order model was developed that explained the observed combustion instability as a noisy nonlinear dynamical process. The model concept lead to development of a real-time control strategy that could be employed to significantly reduce cyclic variations in real engines using existing sensors and engine control systems. This collaboration led to the issuance of a joint patent for spark-ignition engine control. After a few years, the CRADA was modified to focus more on EGR and CIDI engines. The modified CRADA examined relationships between EGR, combustion, and emissions in CIDI engines. Information from CIDI engine experiments, data analysis, and modeling were employed to identify and characterize new combustion regimes where it is possible to simultaneously achieve significant reductions in NOx and PM emissions. These results were also used to develop an on-line combustion diagnostic (virtual sensor) to make cycle-resolved combustion quality assessments for active feedback control. Extensive experiments on engines at Ford and ORNL led to the development of the virtual sensor concept that may be able to detect simultaneous reductions in NOx and PM emissions under low temperature combustion (LTC) regimes. An invention disclosure was submitted to ORNL for the virtual sensor under the CRADA. Industrial in-kind support was available throughout the project period. Review of the research results were carried out on a regular basis (annual reports and meetings) followed by suggestions for improvement in ongoing work and direction for future work. A significant portion of the industrial support was in the form of experimentation, data analysis, data exchange, and technical consultation.
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
SVG and Geo Web Services for visualization of time series data of flood risk Barend Kbben
Köbben, Barend
SVG and Geo Web Services for visualization of time series data of flood risk Barend Köbben. The Open Geospatial Consortiums Web Map Service (WMS) specification is no doubt the most widely implemented webservices Open Web Services specifications Time series in WMS RIMapperWMS: SVG from WMS SVG animation of Geo-WebServices
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
Cirpka, Olaf Arie
Stochastic Generation of Synthetic Precipitation Time Series with High Temporal and Spatial.Brommundt@iws.uni-stuttgart.de Introduction The stochastic precipitation time series generator, NiedSim, has been developed and installed been generated. In the year 2004 NiedSim was set up for Hessen and Rheinland-Pfalz. The total project
Towards Never-Ending Learning from Time Series Streams , Yanping Chen*
Zordan, Victor
that an email is sent to the building supervisor with a picture of the patterns and any other useful metadata a time series produced by a light sensor at Soda Hall in Berkley. While the sensor will produce data sensors at Soda Hall produce a never- ending time series, of which we can cache only a small subset main
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
Summarizing Neonatal Time Series Data Somayajulu G. Sripada, Ehud Reiter, Jim Hunter and Jin Yu
a time series. We are building a system to summarize physiological times series data such as heart rate forecasts from weather data such as wind speed, wind direction, and wave heights. In gas turbines we pressure sampled every second for three hours. Figure 2 shows its summary extracted from a small corpus
Summarizing Neonatal Time Series Data Somayajulu G. Sripada, Ehud Reiter, Jim Hunter and Jin Yu
Reiter, Ehud
a time series. We are building a system to summarize physiological times series data such as heart rate forecasts from weather data such as wind speed, wind direction, and wave heights. In gas turbines we for three hours. Figure 2 shows its summary extracted from a small corpus of human written summaries we
Essays on Bayesian Time Series and Variable Selection
De, Debkumar
2014-05-08
Estimating model parameters in dynamic model continues to be challenge. In my dissertation, we have introduced a Stochastic Approximation based parameter estimation approach under Ensemble Kalman Filter set-up. Asymptotic properties of the resultant...
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
ENERGY SERIES "CFD Modeling and its Application in Steam Condenser
Bergman, Keren
SEMINAR: ENERGY SERIES "CFD Modeling and its Application in Steam Condenser Performance Improvement will discuss the application of CFD to steam condensers, an area where both of the above mentioned limitations of computational fluid dynamics, having applied these techniques extensively in the design large heat exchangers
Stochastic Simulation Methods for Precipitation and Streamflow Time Series
Li, Chao
2013-04-30
One major acknowledged challenge in daily precipitation is the inability to model extreme events in the spectrum of events. These extreme events are rare but may cause large losses. How to realistically simulate extreme ...
Topic Time Series Analysis of Microblogs ellai@uci.edu
Bertozzi, Andrea L.
-worthy phenomena. However, transforming raw, free-form, real time text into meaningful in- formation remains spatially, temporally or both might be of interest to analysts, marketers, researchers, law enforcement of microblog topics, where edges represent the predictive power of one topic for another. Recovery
RESULTS Greenhouse Gas Time Series SUMMARY AND CONCLUSIONS
fitting method2 . · Soil temperature at 5 cm taken concurrently with chambers · Soil water content of top limited below a soil water content of 63% and are diffusion limited above 63%. · Soil temperature with showing an exponential dependence of CO2 on temperature; b) Soil water content vs. temperature CO2 model
Applications of Time Series in Finance and Macroeconomics
Ibarra Ramirez, Raul
2011-08-08
out-of-sample fore- casts for the in ation rate in Mexico. Factor models are useful to summarize the information contained in large datasets. We evaluate the role of using a wide range of macroeconomic variables to forecast in ation, with particular...-2006 : : : : 42 V Stochastic Dominance Test : : : : : : : : : : : : : : : : : : : : : : : 46 VI Forecasting Results: Headline In ation : : : : : : : : : : : : : : : : : 65 VII Forecasting Results: Core In ation : : : : : : : : : : : : : : : : : : : 66 VIII...
Time Series Methods for ForecastingElectricityMarket Pricing Zoran Obradovic Kevin Tomsovic
Obradovic, Zoran
of traditional commodities, such as,oil or agricultural products. Clearly, assessing the effectivenessTime Series Methods for ForecastingElectricityMarket Pricing Zoran Obradovic Kevin Tomsovic PO Box
Time-Series Classification of High-Temporal Resolution AVHRR NDVI Imagery of Mexico
Egbert, Stephen L.; Ortega-Huerta, Miguel; Martí nez-Meyer, Enrique; Price, Kevin P.; Peterson, A. Townsend
2000-01-01
Time-series data from wide-field sensors, acquired for the period of a growing season or longer, capitalize on phenological changes in vegetation and make it possible to identify vegetated land cover types in greater detail. ...
Time Series and the Dynamics of Demand Pacing Daniel T. Kaplan
Kaplan, Daniel T.
Time Series and the Dynamics of Demand Pacing Daniel T. Kaplan Dept. of Mathematics & Computer on in Kaplan2 and Christini and Kaplan3 . Along with the theory, I will detail some of the signal processing
Mining Time Series Data: Moving from Toy Problems to Realistic Deployments
Hu, Bing
2013-01-01
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.
A Time Series Analysis of Microarray Data Selnur Erdal1,2
Ferhatosmanoglu, Hakan
by algorithms that can extract and cluster related behaviors from the full population of time-series behaviors observed. Although traditional clus- tering techniques have shown to be effective for certain types
Analysis of MODIS 250 m NDVI Using Different Time-Series Data for Crop Type Separability
Lee, Eunmok
2014-08-31
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 ...
The application of complex network time series analysis in turbulent heated jets
Charakopoulos, A. K.; Karakasidis, T. E. Liakopoulos, A.; Papanicolaou, P. N.
2014-06-15
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
2014-01-01
We present a new global high-resolution renewable energy atlas (REatlas) that can be used to calculate customised hourly time series of wind and solar PV power generation. In this paper, the atlas is applied to produce 32-year-long hourly model wind power time series for Denmark for each historical and future year between 1980 and 2035. These are calibrated and validated against real production data from the period 2000 to 2010. The high number of years allows us to discuss how the characteristics of Danish wind power generation varies between individual weather years. As an example, the annual energy production is found to vary by $\\pm10\\%$ from the average. Furthermore, we show how the production pattern change as small onshore turbines are gradually replaced by large onshore and offshore turbines. In most energy system analysis tools, fixed hourly time series of wind power generation are used to model future power systems with high penetrations of wind energy. Here, we compare the wind power time series fo...
Hsu, P. J.; Lai, S. K., E-mail: sklai@coll.phy.ncu.edu.tw [Complex Liquids Laboratory, Department of Physics, National Central University, Chungli 320 Taiwan (China); Molecular Science and Technology Program, Taiwan International Graduate Program, Academia Sinica, Taipei 115, Taiwan (China); Cheong, S. A. [Division of Physics and Applied Physics, School of Physical and Mathematical Sciences, Nanyang Technological University, 21 Nanyang Link, Singapore 637371 (Singapore)
2014-05-28
Folded conformations of proteins in thermodynamically stable states have long lifetimes. Before it folds into a stable conformation, or after unfolding from a stable conformation, the protein will generally stray from one random conformation to another leading thus to rapid fluctuations. Brief structural changes therefore occur before folding and unfolding events. These short-lived movements are easily overlooked in studies of folding/unfolding for they represent momentary excursions of the protein to explore conformations in the neighborhood of the stable conformation. The present study looks for precursory signatures of protein folding/unfolding within these rapid fluctuations through a combination of three techniques: (1) ultrafast shape recognition, (2) time series segmentation, and (3) time series correlation analysis. The first procedure measures the differences between statistical distance distributions of atoms in different conformations by calculating shape similarity indices from molecular dynamics simulation trajectories. The second procedure is used to discover the times at which the protein makes transitions from one conformation to another. Finally, we employ the third technique to exploit spatial fingerprints of the stable conformations; this procedure is to map out the sequences of changes preceding the actual folding and unfolding events, since strongly correlated atoms in different conformations are different due to bond and steric constraints. The aforementioned high-frequency fluctuations are therefore characterized by distinct correlational and structural changes that are associated with rate-limiting precursors that translate into brief segments. Guided by these technical procedures, we choose a model system, a fragment of the protein transthyretin, for identifying in this system not only the precursory signatures of transitions associated with ? helix and ? hairpin, but also the important role played by weaker correlations in such protein folding dynamics.
Anomaly detection in thermal pulse combustors using symbolic time series analysis
Ray, Asok
pulse combustor. Results are presented to exemplify early detection of combustion instability due339 Anomaly detection in thermal pulse combustors using symbolic time series analysis S Gupta1 for anomaly detection in thermal pulse combustors. The anomaly detection method has been tested on the time
Climate signal detection using wavelet transform: How to make a time series sing
Lau, K.M.; Weng, H.
1995-12-01
In this paper, the application of the wavelet transform (WT) to climate time series analyses is introduced. A tutorial description of the basic concept of WT, compared with similar concepts used in music, is also provided. Using an analogy between WT representation of a time series and a music score, the authors illustrate the importance of local versus global information in the time-frequency localization of climate signals. Examples of WT applied to climate data analysis are demonstrated using analytic signals as well as real climate time series. Results of WT applied to two climate time series-that is, a proxy paleoclimate time series with a 2.5-Myr deep-sea sediment record of {gamma}{sup 18}O and a 140-yr monthly record of Northern Hemisphere surface temperature-are presented. The former shows the presence of a 40-kyr and a 100-kyr oscillation and an abrupt transition in the oscillation regime at 0.7 Myr before the present, consistent with previous studies. The latter possesses a myriad of oscillatory modes f rom interannual (2-5 yr), interdecadal (10-12 yr, 20-25 yr, and 40-60 yr), and century ({approximately}180 yr) scales at different periods of the data record. In spite of the large difference in timescales, common features in time-frequency characteristics of these two time series have been identified. These features suggest that the variations of the earth`s climate are consistent with those exhibited by a nonlinear dynamical system under external forcings. 32 refs., 9 figs.
Forecasting of preprocessed daily solar radiation time series using neural networks
Paoli, Christophe; Muselli, Marc; Nivet, Marie-Laure [University of Corsica, CNRS UMR SPE, Corte (France); Voyant, Cyril [University of Corsica, CNRS UMR SPE, Corte (France); Hospital of Castelluccio, Radiotherapy Unit, Ajaccio (France)
2010-12-15
In this paper, we present an application of Artificial Neural Networks (ANNs) in the renewable energy domain. We particularly look at the Multi-Layer Perceptron (MLP) network which has been the most used of ANNs architectures both in the renewable energy domain and in the time series forecasting. We have used a MLP and an ad hoc time series pre-processing to develop a methodology for the daily prediction of global solar radiation on a horizontal surface. First results are promising with nRMSE {proportional_to} 21% and RMSE {proportional_to} 3.59 MJ/m{sup 2}. The optimized MLP presents predictions similar to or even better than conventional and reference methods such as ARIMA techniques, Bayesian inference, Markov chains and k-Nearest-Neighbors. Moreover we found that the data pre-processing approach proposed can reduce significantly forecasting errors of about 6% compared to conventional prediction methods such as Markov chains or Bayesian inference. The simulator proposed has been obtained using 19 years of available data from the meteorological station of Ajaccio (Corsica Island, France, 41 55'N, 8 44'E, 4 m above mean sea level). The predicted whole methodology has been validated on a 1.175 kWc mono-Si PV power grid. Six prediction methods (ANN, clear sky model, combination..) allow to predict the best daily DC PV power production at horizon d + 1. The cumulated DC PV energy on a 6-months period shows a great agreement between simulated and measured data (R{sup 2} > 0.99 and nRMSE < 2%). (author)
Time Series Evaluation of Radiation Portal Monitor Data for Point Source Detection
Robinson, Sean M.; Bender, Sarah E.; Flumerfelt, Eric L.; Lopresti, Charles A.; Woodring, Mitchell L.
2009-12-08
The time series of data from a Radiation Portal Monitor (RPM) system are evaluated for the presence of point sources by isolating the contribution of anomalous radiation. Energy-windowed background spectra taken from the RPM are compared with the observed spectra at each time step during a vehicle drive-through. The total signal is turned into a spectral distance index using this method. This provides a time series with reduced systematic fluctuations due to background attenuation by the vehicle, and allows for point source detection by time-series analyses. The anomalous time series is reanalyzed by using a wavelet filter function of similar size to the expected source profile. A number of real drive-through data sets taken at a U.S. port of entry are analyzed in this way. A set of isotopes are injected into the data set, and the resultant benign and injected data sets are analyzed with gross-counting, spectral-ratio, and time-based algorithms. Spectral and time methods together offer a significant increase to detection performance.
A non subjective approach to the GP algorithm for analysing noisy time series
K. P. Harikrishnan; R. Misra; G. Ambika; A. K. Kembhavi
2006-03-11
We present an adaptation of the standard Grassberger-Proccacia (GP) algorithm for estimating the Correlation Dimension of a time series in a non subjective manner. The validity and accuracy of this approach is tested using different types of time series, such as, those from standard chaotic systems, pure white and colored noise and chaotic systems added with noise. The effectiveness of the scheme in analysing noisy time series, particularly those involving colored noise, is investigated. An interesting result we have obtained is that, for the same percentage of noise addition, data with colored noise is more distinguishable from the corresponding surrogates, than data with white noise. As examples for real life applications, analysis of data from an astrophysical X-ray object and human brain EEG, are presented.
Detrended partial cross-correlation analysis of two time series influenced by common external forces
Qian, Xi-Yuan; Jiang, Zhi-Qiang; Podobnik, Boris; Zhou, Wei-Xing; Stanley, H Eugene
2015-01-01
We propose a new method, detrended partial cross-correlation analysis (DPXA), to uncover the intrinsic power-law cross-correlations between two simultaneously recorded time series in the presence of nonstationarity after removing the effects of other time series acting as common forces. The DPXA method is a generalization of the detrended cross-correlation analysis by taking into account the partial correlation analysis. We illustrate the performance of the method using bivariate fractional Brownian motions and multifractal binomial measures with analytical expressions and apply it to extract the intrinsic cross-correlation between crude oil and gold futures by considering the impact of the US dollar index.
Modeling of Time with Metamaterials
Igor I. Smolyaninov; Yu-Ju Hung
2011-05-12
Metamaterials have been already used to model various exotic "optical spaces". Here we demonstrate that mapping of monochromatic extraordinary light distribution in a hyperbolic metamaterial along some spatial direction may model the "flow of time". This idea is illustrated in experiments performed with plasmonic hyperbolic metamaterials. Appearance of the "statistical arrow of time" is examined in an experimental scenario which emulates a Big Bang-like event.
Nonlinear analysis of time series of vibration data from a friction brake: SSA, PCA, and MFDFA
Nikolay K. Vitanov; Norbert P. Hoffmann; Boris Wernitz
2014-10-23
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.
Caldwell, J.S.; Bahnfleth, W.P.
1998-12-31
Several one-dimensional models of mixing in stratified chilled-water thermal energy storage tanks have been proposed. In the simplest models, mixing is assumed to be uniform throughout the tank. Other models permit spatial variation of mixing intensity. Published models were developed by adjusting model parameters to achieve qualitative agreement with measured profiles. The literature does not describe quantitative criteria for evaluating the performance of mixing models. This paper describes a method that can be used to determine the relative spatial distribution of mixing effects directly from experimental data. It also illustrates a method for quantitative comparison of experimental and modeled temperature profiles. The mixing calculation procedure may be applied to instantaneous spatial temperature data if temperature sensor spacing is sufficiently small. When sensors are widely spaced, time series data taken at individual sensors provide better accuracy. A criterion for maximum sensor spacing is proposed. The application of these procedures to time series charge-cycle operating data from a full-scale chilled-water thermal storage system serving a large medical center is described. Results of this analysis indicate that mixing is localized near the inlet diffuser and that one-dimensional flow with streamwise conduction predominates in most of the tank.
Time-varying Spectral Analysis in Neurophysiological Time Series Using Hilbert
Whitcher, Brandon
ability to detect time-varying coherence and phase properties. Key words: Coherence, electromyographic
Neural networks as a tool for constructing continuous NDVI time series from AVHRR and MODIS
Neural networks as a tool for constructing continuous NDVI time series from AVHRR and MODIS M. E-stationary aspect of NDVI, we use an artificial neural network (ANN) to map the NDVI indices from AVHRR to those the AVHRR record. Four years of overlap between the two sensors is used to train a neural network to remove
Railway Subsidence Monitoring by High Resolution INSAR Time Series Analysis in Tianjin
Perissin, Daniele
Railway Subsidence Monitoring by High Resolution INSAR Time Series Analysis in Tianjin Qingli Luo1 and the development of urban are seriously affected by the subsidence of them. Permanent Scatterers (PS) technology was developed as a powerful tool for subsidence monitoring. High resolution of 1m data can be provided by Terra
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
Evolving Neural Network Weights for Time-Series Prediction of General Aviation Flight Data
Hu, Wen-Chen
and predictive maintenance systems, reducing accident rates and saving lives. Keywords: Time-Series Prediction and lucrative industry, it has the highest accident rates within civil aviation [21]. For many years between 0.08% for altitude to 2% for roll. Cross validation of the best neural networks indicate
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 (SHM) systems. Different methods have been developed for detection of damages in WT blades. However a damage detection method based on autocorrelations of response accelerations. The damage sensitive feature
Mapping Deforestation and Forest Degradation Using Landsat Time Series: a Case of Sumatra--Indonesia
20 Mapping Deforestation and Forest Degradation Using Landsat Time Series: a Case of Sumatra--Indonesia Belinda Arunarwati Margono1, 2 Abstract Indonesia experiences the second highest rate of deforestation monitoring system, in addition to the problem of cloud cover in Indonesia. In this work, we demonstrate
Indexing of Time Series by Major Minima and Maxima Eugene Fink
Fink, Eugene
sets: stock prices, air and sea temperatures, and wind speeds. Keywords: Compression, indexing.ics.uci.edu). Wind speeds: We have used daily wind speeds at twelve sites in Ireland, from 1961 to 1978, ob- tained. Indexing: The indexing of a time-series database is based on the notion of major inclines, illustrated
Indexing of Time Series by Major Minima and Maxima Eugene Fink
Fink, Eugene
sets: stock prices, air and sea temperatures, and wind speeds. Keywords: Compression, indexing.ics.uci.edu). Wind speeds: We have used daily wind speeds at twelve sites in Ireland, from 1961 to 1978, ob tained. Indexing: The indexing of a timeseries database is based on the notion of major inclines, illustrated
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
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 that it is very important to identify such patterns in any attempt at summarisation. In the gas turbine domain
Creating and Using Geospatial Ontology Time Series in a Semantic Cultural Heritage Portal
Hyvönen, Eero
Creating and Using Geospatial Ontology Time Series in a Semantic Cultural Heritage Portal Tomi annotations in semantic cultural heritage portals commonly make spatiotemporal references to historical heritage portal CULTURESAMPO to sup- port faceted semantic search of contents and to visualize historical
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
Ultrasound radio-frequency time series for finding malignant breast lesions
Freitas, Nando de
-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
Monitoring water stress using time series of observed to unstressed surface temperature difference
Gentine, Pierre
Monitoring water stress using time series of observed to unstressed surface temperature difference to monitor stress have shifted from establishing empirical relationships between combined vegetation cover/temperature surface temperature as a baseline to monitor water stress. The unstressed temperature is the equilibrium
Time-series validation of MODIS land biophysical products in a Kalahari woodland, Africa
Myneni, Ranga B.
Time-series validation of MODIS land biophysical products in a Kalahari woodland, Africa K. F MODIS variables are produced from the same algorithm. Solar zenith angle effects, differences between the two sides of the leaves are not symmetrical; 3. horizontally projected LAI is the area of `shadow
Time Series 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
1.2000-2009 time-series return information for Snake River: a. Fall Chinook Salmon
#12;Content: 1.2000-2009 time-series return information for Snake River: a. Fall Chinook Salmon b. Sockeye Salmon c. Summer Steelhead d. Spring/Summer Chinook Salmon 2.2010 run-size forecasts for: a. Sockeye Salmon b. Spring/Summer Chinook Salmon #12;#12;Species: Run: Origin: Period: Chinook Salmon Fall
Masci, Frank
The Fourier Transform The Fourier transform is crucial to any discussion of time series analysis: Fourier Series Fourier Transform Example and Interpretation Oddness and Evenness The Convolution Theorem Discrete Fourier Transforms Definitions Example Implementation Author Ã Fourier Series Recall the Fourier
Using Fourier Series to Model Hourly Energy Use in Commercial Buildings
Dhar, A.; Reddy, T. A.; Claridge, D. E.
1993-01-01
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...
Tse, Chi K. "Michael"
IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS--I: FUNDAMENTAL THEORY AND APPLICATIONS, VOL. 50, NO. 5 that may be applied to determine whether an observed time series is inconsis- tent with a specific class to the residuals of nonlinear models is equiv- alent to fitting that model subject to an information theoretic
Martin, Luis; Marchante, Ruth; Cony, Marco; Zarzalejo, Luis F.; Polo, Jesus; Navarro, Ana
2010-10-15
Due to strong increase of solar power generation, the predictions of incoming solar energy are acquiring more importance. Photovoltaic and solar thermal are the main sources of electricity generation from solar energy. In the case of solar thermal energy plants with storage energy system, its management and operation need reliable predictions of solar irradiance with the same temporal resolution as the temporal capacity of the back-up system. These plants can work like a conventional power plant and compete in the energy stock market avoiding intermittence in electricity production. This work presents a comparisons of statistical models based on time series applied to predict half daily values of global solar irradiance with a temporal horizon of 3 days. Half daily values consist of accumulated hourly global solar irradiance from solar raise to solar noon and from noon until dawn for each day. The dataset of ground solar radiation used belongs to stations of Spanish National Weather Service (AEMet). The models tested are autoregressive, neural networks and fuzzy logic models. Due to the fact that half daily solar irradiance time series is non-stationary, it has been necessary to transform it to two new stationary variables (clearness index and lost component) which are used as input of the predictive models. Improvement in terms of RMSD of the models essayed is compared against the model based on persistence. The validation process shows that all models essayed improve persistence. The best approach to forecast half daily values of solar irradiance is neural network models with lost component as input, except Lerida station where models based on clearness index have less uncertainty because this magnitude has a linear behaviour and it is easier to simulate by models. (author)
Subba Rao, Suhasini
A test for second order stationarity of a time series based on the Discrete Fourier Transform stationary. Exploiting this important property, we construct a Portmanteau type test statistic for testing stationarity of the time series. It is shown that under the null of stationarity, the test statistic has
Gaudi, B. Scott
PUSHING THE LIMITS OF GROUND-BASED PHOTOMETRIC PRECISION: SUBMILLIMAGNITUDE TIME-SERIES PHOTOMETRY of this study was to demonstrate the ability to obtain very high precision photometry for a large number to obtain high-precision (millimagnitude, or less than 1%) time-series, optical and infrared photometry
Time Series Evaluation of Radiation Portal Monitor Data for Point Source Discrimination.
Robinson, Sean M.; Bender, Sarah E.; Flumerfelt, Eric L.; Lopresti, Charles A.; Woodring, Mitchell L.
2009-07-20
A novel algorithm approach to evaluating data from PVT-based Radiation Portal Monitor (RPM) systems is established. Time series of data from RPMs are evaluated for the presence of sources of interest by comparing the background to the vehicle spectrum at each successive time step, isolating the contribution of anomalous radiation. At each time in the data sequence, a “spectral distance” index is calculated using this method. This method may dramatically reduce systematic fluctuations due to background attenuation by a vehicle (the so-called “shadow shielding” effect), and allow for time-series matched filtering for discrimination of compact anomalous sources. This is attempted by using a wavelet filter function of similar size to the expected source profile on the output of the spectral distance method. Performance of this method is shown by analysis (injection studies) of a number of real drive-through data sets taken at a U.S. port of entry. Spectra from isotopes of interest are injected into the data set, and the resultant “benign” and “injected” data sets are analyzed with gross-counting, spectral distance, and spatial algorithms. The combination of spectral and spatial analysis methods showed a significant increase to detection performance.
Time cartogram series to explore differences in the level of railway services: a case, population or travelling-time. A time cartogram is a type of cartogram in which the geographic-distance between locations is replaced by a time-related attribute (e.g., travelling-time) and the geography
Plotkin, S.; Stephens, T.; McManus, W.
2013-03-01
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.
Plotkin, Steve; Stephens, Thomas; McManus, Walter
2013-03-01
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.
Interpretation of engine cycle-to-cycle variation by chaotic time series analysis
Daw, C.S.; Kahl, W.K.
1990-01-01
In this paper we summarize preliminary results from applying a new mathematical technique -- chaotic time series analysis (CTSA) -- to cylinder pressure data from a spark-ignition (SI) four-stroke engine fueled with both methanol and iso-octane. Our objective is to look for the presence of deterministic chaos'' dynamics in peak pressure variations and to investigate the potential usefulness of CTSA as a diagnostic tool. Our results suggest that sequential peak cylinder pressures exhibit some characteristic features of deterministic chaos and that CTSA can extract previously unrecognized information from such data. 18 refs., 11 figs., 2 tabs.
Fast detection of nonlinearity and nonstationarity in short and noisy time series
M. De Domenico; V. Latora
2010-07-07
We introduce a statistical method to detect nonlinearity and nonstationarity in time series, that works even for short sequences and in presence of noise. The method has a discrimination power similar to that of the most advanced estimators on the market, yet it depends only on one parameter, is easier to implement and faster. Applications to real data sets reject the null hypothesis of an underlying stationary linear stochastic process with a higher confidence interval than the best known nonlinear discriminators up to date.
Time series models with an EGB2 conditional distribution
Harvey, Andrew; Caivano, Michele
2013-07-17
function; see Kleiber4 and Kotz (2003, ch6). The GB2 distribution contains many important distributions as special cases, including the Burr (#24; = 1) and log-logistic (#24; = 1; & = 1). GB2 distributions are fat tailed for ?nite #24; and & with upper... and lower tail indices of #17; = and #17; = #24;#23; respectively. The absolute value5 of a tf variate is GB2(f 1=2'; 2; 1=2; f=2) with tail index is #17; = #17; = f: 4Note that Kleiber and Kotz (2003) have #11; and #23; in reverse order, ie they write...
Modeling and Prediction of Time Series of Directed Binary Networks
Betancourt, Brenda
2015-01-01
O. , Sindharan, K. & Tewari, A. (2010). Learning exponentialC . Shalev-Shwartz, S. & Tewari, A. (2011). Stochasticby Shalev- Shwartz & Tewari (2011) (see also Carpenter,
Perpinan, O.; Lorenzo, E.
2011-01-15
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)
Kriegel, Hans-Peter
, evolution of stock charts, research on medical behavior of organisms, or analysis and detec- tion of motion of environmental data. 1 Introduction In a large range of application domains, e.g. environmental analysis series. Overall, TiP serves as a framework to effectively and efficiently manage dual- domain time series
Modeling of ECM Controlled Series Fan-powered VAV Terminal Units
Yin, Peng
2011-10-21
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...
Jensen, Deborah Larkey
2005-02-17
. The mean and standard deviation of observable decision-action rates on teacher-identified ?teaching days? were higher than the rates on ?guiding? days. Bivariate time series analysis of decision-action rates and physiological response rates showed a...
Modeling an Application's Theoretical Minimum and Average Transactional Response Times
Paiz, Mary Rose
2015-04-01
The theoretical minimum transactional response time of an application serves as a ba- sis for the expected response time. The lower threshold for the minimum response time represents the minimum amount of time that the application should take to complete a transaction. Knowing the lower threshold is beneficial in detecting anomalies that are re- sults of unsuccessful transactions. On the converse, when an application's response time falls above an upper threshold, there is likely an anomaly in the application that is causing unusual performance issues in the transaction. This report explains how the non-stationary Generalized Extreme Value distribution is used to estimate the lower threshold of an ap- plication's daily minimum transactional response time. It also explains how the seasonal Autoregressive Integrated Moving Average time series model is used to estimate the upper threshold for an application's average transactional response time.
Experimental nonlinear dynamical studies in cesium magneto-optical trap using time-series analysis
Anwar, M. Islam, R.; Faisal, M.; Sikandar, M.; Ahmed, M.
2015-03-30
A magneto-optical trap of neutral atoms is essentially a dissipative quantum system. The fast thermal atoms continuously dissipate their energy to the environment via spontaneous emissions during the cooling. The atoms are, therefore, strongly coupled with the vacuum reservoir and the laser field. The vacuum fluctuations as well as the field fluctuations are imparted to the atoms as random photon recoils. Consequently, the external and internal dynamics of atoms becomes stochastic. In this paper, we have investigated the stochastic dynamics of the atoms in a magneto-optical trap during the loading process. The time series analysis of the fluorescence signal shows that the dynamics of the atoms evolves, like all dissipative systems, from deterministic to the chaotic regime. The subsequent disappearance and revival of chaos was attributed to chaos synchronization between spatially different atoms in the magneto-optical trap.
Development of models for series and parallel fan variable air volume terminal units
Furr, James C., Jr
2007-09-17
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...
CEE 812 Structural Engineering Seminar Series Modeling seismic isolation systems for critical
Kamat, Vineet R.
hazards. At much smaller scales, seismic qualification criteria for telecommunications equipment involvesCEE 812 Structural Engineering Seminar Series Modeling seismic isolation systems for critical operations. The use of seismic isolation in the protection of these facilities is predicated upon
A New Intermolecular Potential Model for the n-Alkane Homologous Series
for the production of natural gas, pet- rochemicals, gasoline, kerosene, oil, and paraffin wax. They are utilized model for the n-alkane homologous series has been developed, param- eterized to the vapor-liquid used to determine the model parameters. The new model repro- duces the experimental saturated liquid
Assessment of Time-Series MODIS Data for Cropland Mapping in the U.S. Central Great Plains
Masialeti, Iwake
2008-07-23
.1 Introduction 141 4.2 Research Objectives 143 4.3 Study Area 144 4.4 Data and Methods 145 4.4.1 Time-Series MODIS NDVI Data 146 4.4.2 Common Land Unit (CLU) and Field Site Database for 2005 147 4.4.3 Kansas Average NDVI... because it is expensive to collect, inadequate in spatial and temporal coverage, inadvertently inaccurate, outdated, legally restricted, or non-existent; 2) Evaluate the applicability of time-series MODIS 250-m NDVI data for crop-type discrimination...
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.
2014-10-01
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.
Novel Dynamical Modeling for Series-Parallel Resonant Converter
Noé, Reinhold
and voltage waveforms in the resonant tank are assumed to be sinusoidal. Using this approach steady enables accurate calculation of steady-state characteristics under all (light to heavy) load conditions. For studying the dynamical behavior of the SPRC and for control design dynamical modeling techniques
Percival, Don
signal. We find that common signals in electrical records have time scales of approxi- mately 13 years of Washington, Seattle, WA 98195 5640, USA #12;Abstract The acquisition and interpretation of increasingly high series of electrical and oxygen isotope mea- surements from a spatial array of firn cores with 3.57 km
Time reversal symmetry and collapse models
Daniel Bedingham; Owen Maroney
2015-02-24
Collapse models are modifications of quantum theory where the wave function is treated as physically real and the collapse of the wave function is a physical process. This appears to introduce a time reversal asymmetry into the dynamics of the wave function since the collapses affect only the future state. This paper challenges this conclusion, showing that in three different examples of time asymmetries associated with collapse models, if the physically real part of the model can be reduced to the locations in space and time about which collapses occur, then such a model works both forward and backward in time, in each case satisfying the Born rule. Despite the apparent asymmetry of the collapse process, these models in fact have time reversal symmetry. Any physically observed time asymmetries that arise in such models are due to the asymmetric imposition of initial or final time boundary conditions, rather than from an inherent asymmetry in the dynamical law. This is the standard explanation of time asymmetric behaviour resulting from time symmetric laws.
Nonlinear Time Domain Modeling and Simulation of Surface and...
Office of Environmental Management (EM)
Nonlinear Time Domain Modeling and Simulation of Surface and Embedded NPPS Nonlinear Time Domain Modeling and Simulation of Surface and Embedded NPPS Nonlinear Time Domain Modeling...
Time symmetry in wave function collapse models
Daniel Bedingham
2015-02-25
A framework for wave function collapse models that is symmetric under time reversal is presented. Within this framework there are equivalent pictures of collapsing wave functions evolving in both time directions. The backwards-in-time Born rule can be broken by an initial condition on the Universe resulting in asymmetric behaviour. Similarly the forwards-in-time Born rule can in principle be broken by a final condition on the Universe.
IGR For GR/M76881/01: Generating Summaries of Time-Series Data (SumTime) Background/Context
Sripada, Yaji
of numerical time-series data. The modern world is being flooded with such data. For example, a typical gas-turbine worked in three domains: weather forecasts, summaries of gas-turbine sensor data, and summaries of sensor number of input data values; this meant it could not be used in our hospital and gas-turbine domains
Turova, Varvara
International Series of Numerical Mathematics, Vol. 160, 521540 Freezing of Living Cells, stresses arising due to non-simultaneous freezing of water in- side and outside of cells are modeled and outside of living cells during freezing is derived by applying an appropriate averaging technique
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.
2008-01-01
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) primary air inlets from three different... manufacturers were evaluated. Generalized models were developed from the experimental data with coef- ficients varying by size and manufacturer. Fan power and airflow data were collected at downstream static pressures of 0.25 w.g. (63 Pa). Upstream static...
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), both domain knowledge from experts about how to solve problems in the gas turbine and information about
Martinez, L.T.
1997-05-01
The objective of this study was to determine the effect of nonrandom sampling over time may have on the estimation of variability, namely the geometric standard deviation, using time series of personal exposure data.
I. Ermolli; S. K. Solanki; A. G. Tlatov; N. A. Krivova; R. K. Ulrich; J. Singh
2008-02-26
Various observatories around the globe started regular full-disk imaging of the solar atmosphere in the Ca II K line since the early decades of the 20th century. The archives made by these observations have the potential of providing far more detailed information on solar magnetism than just the sunspot number and area records to which most studies of solar activity and irradiance changes are restricted. We evaluate the image contents of three Ca II K spectroheliogram time-series, specifically those obtained by the digitization of the Arcetri, Kodaikanal, and Mt Wilson photographic archives. We describe the main problems afflicting these data and analyze their quality by expressing the image contents through several quantities. We compare the results obtained with those for similar present-day observations taken with the Meudon spectroheliograph and with the Rome-PSPT. We show that historic data suffer from stronger geometrical distortions and photometric uncertainties than similar present-day observations. The latter uncertainties mostly originate from the photographic calibration of the original data and from stray-light effects. We also show that the image contents of the three analyzed series vary in time. These variations are probably due to instrument changes and aging of the spectrographs used, as well as changes of the observing programs. Our results imply that the main challenge for the analysis of historic data is their accurate photometric calibration. This problem must be solved before they can provide reliable information about solar magnetism and activity over the last century. Moreover, inter-calibration of results obtained from independent time-series is required to reliably trace changes of solar properties with time from the analysis of such data.
Fluorescence spectrum analysis using Fourier series modeling for Fluorescein solution in Ethanol
Hadi, Mahasin F
2011-01-01
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.
Exploratory Spectral Analysis of Hydrological Time Series A.I. McLeod
McLeod, Ian
of Systems Design Engineering University of Waterloo Waterloo, Ontario, Canada N2L 3C5 December 1994 #12 previ- ously to these datasets adequately describe the low frequency component. The software and data are prewhitened by fitting either trend models or simple parametric models such as autore- gressive
Time series analysis of the lead-lag relationship of freight futures and spot market prices
Gavriilidis, Nikolaos
2008-01-01
This thesis analyzes the relationship between the physical and paper shipping markets. The main objective is to find if one market leads the other by a specific time period so that market players can take advantage from ...
Mining Markov chain transition matrix from wind speed time series data Zhe Song a,
Kusiak, Andrew
. Researches related with wind speed are quite extensive, includ- ing wind speed forecasting (Kusiak, Zheng, Essiarab, & Sayigh, 2004; Sahin & Sen, 2001) and so on. Wind speed forecasting and simulation could approaches, Markov chain is a popular tool to model, forecast and simulate the wind speed in a discrete
A new approach for rapid detection of nearby thresholds in ecosystem time series
Pace, Michael L.
July 2013 Recognition of an incoming nuclear missile is a case where fast detection is needed for quickest detection of change points, such as appearance of a missile on radar or a submarine on sonar models, one for the status quo (`no submarine') and one for a new and different situation (`submarine
Time series analysis of AERI radiances for GCM testing and improvement
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: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantityBonneville Power AdministrationRobust,Field-effectWorking With U.S.Week DayDr.Theories (Journal Article)Clean4, 9/26/14),Time
Ghosh, Sayantan; Panigrahi, Prasanta K
2010-01-01
We make use of wavelet transform to study the multi-scale, self similar behavior and deviations thereof, in the stock prices of large companies, belonging to different economic sectors. The stock market returns exhibit multi-fractal characteristics, with some of the companies showing deviations at small and large scales. The fact that, the wavelets belonging to the Daubechies' (Db) basis enables one to isolate local polynomial trends of different degrees, plays the key role in isolating fluctuations at different scales. We make use of Db4 and Db6 basis sets to respectively isolate local linear and quadratic trends at different scales in order to study the statistical characteristics of these financial time series. The fluctuations reveal fat tail non-Gaussian behavior, unstable periodic modulations, at finer scales, from which the characteristic $k^{-3}$ power law behavior emerges at sufficiently large scales. We further identify stable periodic behavior through the continuous Morlet wavelet.
Time series association learning
Papcun, George J. (Santa Fe, NM)
1995-01-01
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
2004-09-30
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...
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
Reiter, Ehud
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 simply from sensors in aircraft engines (Hey and Trefethen 2003). Currently numeric time-series data
Real-time Volumetric Deformable Models for Surgery Simulation using
Real-time Volumetric Deformable Models for Surgery Simulation using Finite Elements volumetric Finite Element models to surgery simulation. In particular it presents three new approaches: Virtual Surgery, Real-Time Deformation, Solid Volumetric Deformable Mod- els, Virtual Reality, Finite
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
Seminar Series: MAE Seminar, 2015 spring quarter Date and Time: 05/08/2015 -10:30 am11:30 am
Mease, Kenneth D.
In this seminar, I will first discuss our research results of photoelectrochemical generation of hydrogen some of my research into the design and development of quinoline-based organic semiconducting materialsSeminar Series: MAE Seminar, 2015 spring quarter Date and Time: 05/08/2015 - 10:30 am11:30 am
Introduction to Ocean Station Time Series CD-ROM The National Oceanographic Data Center (NODC) and the World Data Center for Oceanography (WDC) have compiled from the NODC Oceanographic Station Data File a set of oceanographic data having repetitive samples along ocean sections or at fixed locations
Schick, Anton
ESTIMATORS FOR TIME SERIES Anton Schick Department of Mathematical Sciences, Binghamtom University Binghamton is semiparametric, with 1 #12;March 3, 2005 14:40 WSPC/Trim Size: 9in x 6in for Review Volume m-bickel04 2 A. Schick
Rabatel, Antoine
Using remote-sensing data to determine equilibrium-line altitude and mass-balance time series to calculate glacier mass balance using remote-sensing data. Snowline measurements from remotely sensed images by ground measurements and remote sensing are compared and show excellent correlation (r2 > 0.89), both
International Association for Cryptologic Research (IACR)
analysis, machine learning, time series classification. 1 Introduction Embedded devices such as smart cards operations allowing to secure, for example, bank transfers, buildings and cars. A modern bank card embeds securely a secret information allowing in fine to transfer cash. This operation is allowed by the smart
Abstract--In this study, we analyzed a dataset of time-series vital-signs data collected combination of the automatically-collected and -qualified vital signs provides the best discrimination between of the vital-signs variables, and used the area under the receiver operating characteristic curve (ROC AUC
Hierarchical Bayesian models for space-time air pollution data
Sahu, Sujit K
Hierarchical Bayesian models for space-time air pollution data Sujit K. Sahu June 14, 2011 sets have led to a step change in the analysis of space-time air pollution data. Accurate predictions-time air pollution data and illustrate the benefits of modeling with a real data example on monitoring
Statistical Model Checking for Networks of Priced Timed Automata
David, Alexandre
Statistical Model Checking for Networks of Priced Timed Automata Alexandre David1 , Kim G. Larsen1- and cost-bounded properties. A second contribution of the paper is the application of Statistical Model-time and hybrid systems with quantitative constraints on time, energy or more general continuous aspects [1
Model-Checking One-Clock Priced Timed Automata
Doyen, Laurent
Model-Checking One-Clock Priced Timed Automata Patricia Bouyer1 , Kim G. Larsen2 , and Nicolas, Denmark kgl@cs.aau.dk Abstract. We consider the model of priced (a.k.a. weighted) timed au- tomata, 18, 7]. In particu- lar, as part of this effort, the notion of priced (or weighted) timed automata [4
ModelChecking OneClock Priced Timed Automata
Doyen, Laurent
ModelChecking OneClock Priced Timed Automata Patricia Bouyer 1# , Kim G. Larsen 2## , and Nicolas, Denmark kgl@cs.aau.dk Abstract. We consider the model of priced (a.k.a. weighted) timed au tomata, 18, 7]. In particu lar, as part of this e#ort, the notion of priced (or weighted) timed automata [4
Time-Varying Stochastic Turbulence Model Curtis R. Vogela
Vogel, Curtis
Time-Varying Stochastic Turbulence Model Curtis R. Vogela aDepartment of Mathematical Sciences for time-varying turbulence. The model can be viewed as a linearization of the Navier-Stokes equation, with deterministic drift and diffusion terms, plus an additional stochastic driving term. Fixed-time realizations
Automatic Learning of Block Storage Access Time Models
Crume, Adam
2015-01-01
3 Storage devices 3.1 Scope ofedge-on . . . . . . . . Queueing in a storage device with noAUTOMATIC LEARNING OF BLOCK STORAGE ACCESS TIME MODELS A
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 ...
Continuous time random walk models for fractional space-time diffusion equations
Sabir Umarov
2014-09-14
In this paper continuous time random walk models approximating fractional space-time diffusion processes are studied. Stochastic processes associated with the considered equations represent time-changed processes, where the time-change process is a L\\'evy's stable subordinator with the stability index $\\beta \\in (0,1).$ In the parer the convergence of constructed CTRWs to time-changed processes associated with the corresponding fractional diffusion equations are proved using a new analytic method.
Estimating transition times for a model of
Mitchener, W. Garrett
= mean usage rate of G2 dm dt = birth q(m) - death m 0.0 0.2 0.4 0.6 0.8 1.0 0.2 0.4 0.6 0.8 1.0 Mean at a rate k K Simplify K = 1: Each agent uses G1 (state 0) or G2 (state 1) @ Ck = number youth in state kD = death rate: each time step each adult dies with prob- ability pD = rD N , replaced by sampling from
A Real-time Framework for Model Predictive Control of Continuous-Time Nonlinear Systems
Sontag, Eduardo
for piecewise constant NMPC of continuous-time processes. Index Terms-- nonlinear model predictive control, real-time optimization, optimal control, piecewise constant control I. INTRODUCTION Model predictive control (MPC horizon, open-loop optimal control problem. The unprecedented industrial success of MPC ap- proaches based
Utility Maximization under Model Uncertainty in Discrete Time
Nutz, Marcel
Utility Maximization under Model Uncertainty in Discrete Time Marcel Nutz January 14, 2014 Abstract We give a general formulation of the utility maximization problem under nondominated model uncertainty in discrete time and show that an optimal portfolio exists for any utility function
Hyper-Real-Time Ice Simulation and Modeling Using GPGPU
Peters, Dennis
Hyper-Real-Time Ice Simulation and Modeling Using GPGPU By c Shadi Alawneh, B. Eng., M. Eng's, Newfoundland Title: Hyper-Real-Time Ice Simulation and Modeling Using GPGPU Author: Shadi Alawneh, B. Eng operating in pack ice is a computationally in- tensive process to which General Purpose Computing
Model checking Timed CSP Philip Armstrong Gavin Lowe Joel Ouaknine
Ouaknine, JoÃ«l
Model checking Timed CSP Philip Armstrong Gavin Lowe JoÂ¨el Ouaknine A.W. Roscoe Oxford University Department of Computer Science Abstract Though Timed CSP was developed 25 years ago and the CSP for Timed CSP. In this paper we report on the creation of such a version, based on the digitisation results
Development of a probabilistic timing model for the ingestion of tap water.
Davis, M. J.; Janke, R.; Environmental Science Division; EPA
2009-01-01
A contamination event in a water distribution system can result in adverse health impacts to individuals consuming contaminated water from the system. Assessing impacts to such consumers requires accounting for the timing of exposures of individuals to tap-water contaminants that have time-varying concentrations. Here we present a probabilistic model for the timing of ingestion of tap water that we developed for use in the U.S. Environmental Protection Agency's Threat Ensemble Vulnerability Assessment and Sensor Placement Tool, which is designed to perform consequence assessments for contamination events in water distribution systems. We also present a statistical analysis of the timing of ingestion activity using data collected by the American Time Use Survey. The results of the analysis provide the basis for our model, which accounts for individual variability in ingestion timing and provides a series of potential ingestion times for tap water. It can be combined with a model for ingestion volume to perform exposure assessments and applied in cases for which the use of characteristics typical of the United States is appropriate.
Essays on empirical time series modeling with causality and structural change
Kim, Jin Woong
2006-10-30
sector is the most root cause sector. Test results show that DAG from ex ante forecast innovations is consistent with the DAG fro m ex post fit innovations. This supports innovation accounting based on DAGs using ex post innovations. In the second essay...
A supply forecasting model for Zimbabwe's corn sector: a time series and structural analysis
Makaudze, Ephias
1993-01-01
Board's financial resource needs. Thus, the corn supply forecasts are important information used by the government for contingency planning, decision-making, policy-formulation and implementation. As such, the need for accurate forecasts is obvious...
Multivariate and Time Series Models for Circular Data with Applications to Protein
Stone, J. V.
, University of Leeds) for his helpful comments at annual reviews. As mentioned in the abstract, bioinformatics The University of Leeds Department of Statistics January 2007 The candidate confirms that the work submitted involved is exemplified by the Leeds Annual Statistical Research (LASR) workshops (www.maths.leeds
Data Tools & Models - Time Series - U.S. Energy Information Administration
Gasoline and Diesel Fuel Update (EIA)
AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity of Natural GasAdjustments (Billion Cubic Feet) Wyoming Dry Natural GasNatural Gas Usage Form 2003(EIA) The following is a
Statistical testing and estimation in continuous time interest rate models
Kim, Myung Suk
2006-10-30
The shape of drift function in continuous time interest rate models has been investigated by many authors during the past decade. The main concerns have been whether the drift function is linear or nonlinear, but no convincing conclusions have been...
Pulse combustor modeling demonstration of the importance of characteristic times
Barr, P.K.; Keller, J.O.; Bramlette, T.T.; Dec, J.E. (Combustion Research Facility, Sandia National Lab., Livermore, CA (US)); Westbrook, C.K. (Lawrence Livermore National Lab., Univ. of California, Livermore, CA (US))
1990-12-01
A numerical model has been developed to study the sensitivity of a pulse combustor's performance to changes in the relative timing between several of the dominant physical processes. The model is used to demonstrate the importance of the characteristic times associated with acoustics, fluid mixing, and chemical kinetics, which have been identified from both theoretical and experimental evidence. The combination of submodels for acoustics, injection, and combustion produces a pulse combustor model that is dynamic in that it fully couples the injection and mixing processes to the acoustic waves. Comparisons of simulations with experimental results show good agreement, verifying the model over a wide range of operating conditions. Because the model provides more control of the dominant processes than can be obtained in experiments, the parametric study establishes the cause-effect relations between the characteristic times and the resulting combustor performance.
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
Deep Random Search for Efficient Model Checking of Timed Automata
Grosu, Radu
Deep Random Search for Efficient Model Checking of Timed Automata R. Grosu1 , X. Huang1 , S}@imag.fr Abstract. We present DRS (Deep Random Search), a new Las Vegas algorithm for model checking safety fringe, which is the starting point of additional deep random walks. The DRS algorithm is complete
Snyder-de Sitter model from two-time physics
Carrisi, M. C.; Mignemi, S.
2010-11-15
We show that the symplectic structure of the Snyder model on a de Sitter background can be derived from two-time physics in seven dimensions and propose a Hamiltonian for a free particle consistent with the symmetries of the model.
Short-term time step convergence in a climate model
DOE Public Access Gateway for Energy & Science Beta (PAGES Beta)
Wan, Hui; Rasch, Philip J.; Taylor, Mark A.; Jablonowski, Christiane
2015-02-11
This paper evaluates the numerical convergence of very short (1 h) simulations carried out with a spectral-element (SE) configuration of the Community Atmosphere Model version 5 (CAM5). While the horizontal grid spacing is fixed at approximately 110 km, the process-coupling time step is varied between 1800 and 1 s to reveal the convergence rate with respect to the temporal resolution. Special attention is paid to the behavior of the parameterized subgrid-scale physics. First, a dynamical core test with reduced dynamics time steps is presented. The results demonstrate that the experimental setup is able to correctly assess the convergence rate ofmore »the discrete solutions to the adiabatic equations of atmospheric motion. Second, results from full-physics CAM5 simulations with reduced physics and dynamics time steps are discussed. It is shown that the convergence rate is 0.4—considerably slower than the expected rate of 1.0. Sensitivity experiments indicate that, among the various subgrid-scale physical parameterizations, the stratiform cloud schemes are associated with the largest time-stepping errors, and are the primary cause of slow time step convergence. While the details of our findings are model specific, the general test procedure is applicable to any atmospheric general circulation model. The need for more accurate numerical treatments of physical parameterizations, especially the representation of stratiform clouds, is likely common in many models. The suggested test technique can help quantify the time-stepping errors and identify the related model sensitivities.« less
Neutrino flavor instabilities in a time-dependent supernova model
Abbar, Sajad
2015-01-01
A dense neutrino medium such as that inside a core-collapse supernova can experience collective flavor conversion or oscillations because of the neutral-current weak interaction among the neutrinos. This phenomenon has been studied in a restricted, stationary supernova model which possesses the (spatial) spherical symmetry about the center of the supernova and the (directional) axial symmetry around the radial direction. Recently it has been shown that these spatial and directional symmetries can be broken spontaneously by collective neutrino oscillations. In this paper we analyze the neutrino flavor instabilities in a time-dependent supernova model. Our results show that collective neutrino oscillations start at approximately the same radius in both the stationary and time-dependent supernova models unless there exist very rapid variations in local physical conditions on timescales of a few microseconds or shorter. Our results also suggest that collective neutrino oscillations can vary rapidly with time in t...
Small-energy series for one-dimensional quantum-mechanical models with non-symmetric potentials
Paolo Amore; Francisco M. Fernández
2014-10-21
We generalize a recently proposed small-energy expansion for one-dimensional quantum-mechanical models. The original approach was devised to treat symmetric potentials and here we show how to extend it to non-symmetric ones. Present approach is based on matching the logarithmic derivatives for the left and right solutions to the Schr\\"odinger equation at the origin (or any other point chosen conveniently) . As in the original method, each logarithmic derivative can be expanded in a small-energy series by straightforward perturbation theory. We test the new approach on four simple models, one of which is not exactly solvable. The perturbation expansion converges in all the illustrative examples so that one obtains the ground-state energy with an accuracy determined by the number of available perturbation corrections.
Yvonne C. Unruh; Natalie A. Krivova; Sami K. Solanki; Jerald W. Harder; Greg Kopp
2008-02-28
Aims: We test the reliability of the observed and calculated spectral irradiance variations between 200 and 1600 nm over a time span of three solar rotations in 2004. Methods: We compare our model calculations to spectral irradiance observations taken with SORCE/SIM, SoHO/VIRGO and UARS/SUSIM. The calculations assume LTE and are based on the SATIRE (Spectral And Total Irradiance REconstruction) model. We analyse the variability as a function of wavelength and present time series in a number of selected wavelength regions covering the UV to the NIR. We also show the facular and spot contributions to the total calculated variability. Results: In most wavelength regions, the variability agrees well between all sets of observations and the model calculations. The model does particularly well between 400 and 1300 nm, but fails below 220 nm as well as for some of the strong NUV lines. Our calculations clearly show the shift from faculae-dominated variability in the NUV to spot-dominated variability above approximately 400 nm. We also discuss some of the remaining problems, such as the low sensitivity of SUSIM and SORCE for wavelengths between approximately 310 and 350 nm, where currently the model calculations still provide the best estimates of solar variability.
Mitchell, Christopher J; Ahrens, James P; Wang, Jun
2010-10-15
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.
Short-term time step convergence in a climate model
DOE Public Access Gateway for Energy & Science Beta (PAGES Beta)
Wan, Hui; Rasch, Philip J.; Taylor, Mark; Jablonowski, Christiane
2015-02-11
A testing procedure is designed to assess the convergence property of a global climate model with respect to time step size, based on evaluation of the root-mean-square temperature difference at the end of very short (1 h) simulations with time step sizes ranging from 1 s to 1800 s. A set of validation tests conducted without sub-grid scale parameterizations confirmed that the method was able to correctly assess the convergence rate of the dynamical core under various configurations. The testing procedure was then applied to the full model, and revealed a slow convergence of order 0.4 in contrast to themore »expected first-order convergence. Sensitivity experiments showed without ambiguity that the time stepping errors in the model were dominated by those from the stratiform cloud parameterizations, in particular the cloud microphysics. This provides a clear guidance for future work on the design of more accurate numerical methods for time stepping and process coupling in the model.« less
Modeling Combined Time-and Event-Driven Dynamic Systems
Baclawski, Kenneth B.
such as logistical systems, distributed sensor sys- tems and intelligent highway vehicle systems, are complex dynamic. In this approach, future behaviors are generated through quantitative simulation which "executes" a simulation model, typically at fixed time steps, to obtain quantitative values of state and/or output variables. 1
REAL TIME ACQUISITION AND RENDERING OF LARGE 3D MODELS
Rusinkiewicz, Szymon
OF THE REQUIREMENTS FOR THE DEGREE OF DOCTOR OF PHILOSOPHY Szymon Marek Rusinkiewicz August 2001 #12;ii c Copyright grid, and point (splat) rendering is used to provide a real-time display of the partial 3D model. Given, backface culling, level-of-detail control, and splat rendering. The system may also be extended
Models at Run-time for Sustaining User Interface Plasticity
Models at Run-time for Sustaining User Interface Plasticity Jean-Sébastien Sottet1 Gaëlle Calvary1, Environment>) while preserving usability. This capacity of UIs is called Plasticity. In a forward engineering) to code. It is now well understood that plasticity may impact UIs at any level of abstraction. This calls
Continuous time Markov chain models for chemical reaction networks
Kurtz, Tom
Continuous time Markov chain models for chemical reaction networks David F. Anderson Departments Abstract A reaction network is a chemical system involving multiple reactions and chemical species exploit the representation of the stochastic equation for chemical reaction networks and, under what
Real-time Modelling of Tsunami Data Applied Physics Laboratory
Percival, Don
Real-time Modelling of Tsunami Data Applied Physics Laboratory Department of Statistics University for Tsunami Research #12;Background - I · even before disasterous Sumatra tsunami in December 2004, de- structive potential of earthquake-generated tsunamis was well- known · due to rate at which a tsunami
Short-term Time Step Convergence in a Climate Model
DOE Public Access Gateway for Energy & Science Beta (PAGES Beta)
Wan, Hui; Rasch, Philip J.; Taylor, Mark; Jablonowski, Christiane
2015-02-11
A testing procedure is designed to assess the convergence property of a global climate model with respect to time step size, based on evaluation of the root-mean-square temperature difference at the end of very short (1 h) simulations with time step sizes ranging from 1 s to 1800 s. A set of validation tests conducted without sub-grid scale parameterizations confirmed that the method was able to correctly assess the convergence rate of the dynamical core under various configurations. The testing procedure was then applied to the full model, and revealed a slow convergence of order 0.4 in contrast to themore »expected first-order convergence. Sensitivity experiments showed without ambiguity that the time stepping errors in the model were dominated by those from the stratiform cloud parameterizations, in particular the cloud microphysics. This provides a clear guidance for future work on the design of more accurate numerical methods for time stepping and process coupling in the model.« less
Space-time models derived from Schwarzschild's solution
Lluis Bel
2008-12-09
We discuss two space-time models: one is expanding, the other is static. They are both derived from Schwarzschild's exterior solution. But they differ in the implementation of the parallelism at a distance and the choice of their master frame of reference.
ARIMA Models versus Gene Expression Programming In Precipitation Modeling
Fernandez, Thomas
ARIMA Models versus Gene Expression Programming In Precipitation Modeling ALINA BRBULESCU and ELENA, Precipitation 1 Introduction Time series are ubiquitous in the real world. They are usually generated
Barker, Erin I.; Choi, Kyoo Sil; Sun, Xin; Deda, Erin; Allison, John; Li, Mei; Forsmark, Joy; Zindel, Jacob; Godlewski, Larry
2014-09-30
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.
Time-evolving measures and macroscopic modeling of pedestrian flow
Benedetto Piccoli; Andrea Tosin
2010-04-27
This paper deals with the early results of a new model of pedestrian flow, conceived within a measure-theoretical framework. The modeling approach consists in a discrete-time Eulerian macroscopic representation of the system via a family of measures which, pushed forward by some motion mappings, provide an estimate of the space occupancy by pedestrians at successive time steps. From the modeling point of view, this setting is particularly suitable to treat nonlocal interactions among pedestrians, obstacles, and wall boundary conditions. In addition, analysis and numerical approximation of the resulting mathematical structures, which is the main target of this work, follow more easily and straightforwardly than in case of standard hyperbolic conservation laws, also used in the specialized literature by some Authors to address analogous problems.
Emergent Semiclassical Time in Quantum Gravity. I. Mechanical Models
Edward Anderson
2007-11-04
Strategies intended to resolve the problem of time in quantum gravity by means of emergent or hidden timefunctions are considered in the arena of relational particle toy models. In situations with `heavy' and `light' degrees of freedom, two notions of emergent semiclassical WKB time emerge; these are furthermore equivalent to two notions of emergent classical `Leibniz--Mach--Barbour' time. I futhermore study the semiclassical approach, in a geometric phase formalism, extended to include linear constraints, and with particular care to make explicit those approximations and assumptions used. I propose a new iterative scheme for this in the cosmologically-motivated case with one heavy degree of freedom. I find that the usual semiclassical quantum cosmology emergence of time comes hand in hand with the emergence of other qualitatively significant terms, including back-reactions on the heavy subsystem and second time derivatives. I illustrate my analysis by taking it further for relational particle models with linearly-coupled harmonic oscillator potentials. As these examples are exactly soluble by means outside the semiclassical approach, they are additionally useful for testing the justifiability of some of the approximations and assumptions habitually made in the semiclassical approach to quantum cosmology. Finally, I contrast the emergent semiclassical timefunction with its hidden dilational Euler time counterpart.
Distinguishing causal time from Minkowski time and a model for the black hole quantum eigenstates
G. 't Hooft
1997-11-18
A discussion is presented of the principle of black hole com- plementarity. It is argued that this principle could be viewed as a breakdown of general relativity, or alternatively, as the introduction of a time variable with multiple `sheets' or `branches' A consequence of the theory is that the stress-energy tensor as viewed by an outside observer is not simply the Lorentz-transform of the tensor viewed by an ingoing observer. This can serve as a justification of a new model for the black hole atmosphere, recently re-introduced. It is discussed how such a model may lead to a dynamical description of the black hole quantum states.
Daily Time Step Simulation with a Priority Order Based Surface Water Allocation Model
Hoffpauir, Richard James
2011-02-22
Surface water availability models often use monthly simulation time steps for reasons of data availability, model parameter parsimony, and reduced computational time. Representing realistic streamflow variability, ...
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; Gilbert, Bob; Lake, Larry W.; Weiss, Chester Joseph; Lorenz, John Clay; Elbring, Gregory Jay; Wheeler, Mary Fanett; Thomas, Sunil G.; Rightley, Michael J.; Rodriguez, Adolfo; Klie, Hector; Banchs, Rafael; Nunez, Emilio J.; Jablonowski, Chris
2006-11-01
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.
Preliminary time-phased TWRS process model results
Orme, R.M.
1995-03-24
This report documents the first phase of efforts to model the retrieval and processing of Hanford tank waste within the constraints of an assumed tank farm configuration. This time-phased approach simulates a first try at a retrieval sequence, the batching of waste through retrieval facilities, the batching of retrieved waste through enhanced sludge washing, the batching of liquids through pretreatment and low-level waste (LLW) vitrification, and the batching of pretreated solids through high-level waste (HLW) vitrification. The results reflect the outcome of an assumed retrieval sequence that has not been tailored with respect to accepted measures of performance. The batch data, composition variability, and final waste volume projects in this report should be regarded as tentative. Nevertheless, the results provide interesting insights into time-phased processing of the tank waste. Inspection of the composition variability, for example, suggests modifications to the retrieval sequence that will further improve the uniformity of feed to the vitrification facilities. This model will be a valuable tool for evaluating suggested retrieval sequences and establishing a time-phased processing baseline. An official recommendation on tank retrieval sequence will be made in September, 1995.
Spectral Models for Early Time SN 2011fe Observations
Baron, E; Sullivan, M; Hsiao, E; Ellis, R S; Gal-Yam, A; Howell, D A; Nugent, P E; Dominguez, I; Krisciunas, K; Phillips, M M; Suntzeff, N; Wang, L; Thomas, R C
2015-01-01
We use observed UV through near IR spectra to examine whether SN 2011fe can be understood in the framework of Branch-normal SNe Ia and to examine its individual peculiarities. As a benchmark, we use a delayed-detonation model with a progenitor metallicity of Z_solar/20. We study the sensitivity of features to variations in progenitor metallicity, the outer density profile, and the distribution of radioactive nickel. The effect of metallicity variations in the progenitor have a relatively small effect on the synthetic spectra. We also find that the abundance stratification of SN 2011fe resembles closely that of a delayed detonation model with a transition density that has been fit to other Branch-normal Type Ia supernovae. At early times, the model photosphere is formed in material with velocities that are too high, indicating that the photosphere recedes too slowly or that SN 2011fe has a lower specific energy in the outer ~0.1 M_sun than does the model. We discuss several explanations for the discrepancies. ...
Künstler, A; Strassmeier, K G
2015-01-01
Solar spots appear to decay linearly proportional to their size. The decay rate of solar spots is directly related to magnetic diffusivity, which itself is a key quantity for the length of a magnetic-activity cycle. Is a linear spot decay also seen on other stars, and is this in agreement with the large range of solar and stellar activity cycle lengths? We investigate the evolution of starspots on the rapidly-rotating ($P_{\\rm rot}$ $\\approx$ 24 d) K0 giant XX Tri, using consecutive time-series Doppler images. Our aim is to obtain a well-sampled movie of the stellar surface over many years, and thereby detect and quantify a starspot decay law for further comparison with the Sun. We obtained continuous high-resolution and phase-resolved spectroscopy with the 1.2-m robotic STELLA telescope on Tenerife over six years. For each observing season, we obtained between 5 to 7 independent Doppler images, one per stellar rotation, making up a total of 36 maps. To quantify starspot area decay and growth, we match the ob...
DOE Public Access Gateway for Energy & Science Beta (PAGES Beta)
Frolov, Vladimir; Backhaus, Scott; Chertkov, Misha
2014-10-24
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 l1 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 Polishmore »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.« less
Frolov, Vladimir; Backhaus, Scott N.; Chertkov, Michael
2014-01-14
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.
Nacional de San Luis, Universidad
of uranium uptake A.S. Cid a , R.M. Anjos a, * , C.B. Zamboni b , R. Cardoso a , M. Muniz a , A. Corona c , D-series dating Neutron activation analysis Uranium uptake Radial diffusioneadsorption model a b s t r a c- logical sites. However, since bone is an open system for uranium, it cannot be dated directly
TIME-DEPENDENT MODELING OF PULSAR WIND NEBULAE
Vorster, M. J.; Ferreira, S. E. S.; Tibolla, O.; Kaufmann, S. E-mail: omar.tibolla@gmail.com
2013-08-20
A spatially independent model that calculates the time evolution of the electron spectrum in a spherically expanding pulsar wind nebula (PWN) is presented, allowing one to make broadband predictions for the PWN's non-thermal radiation. The source spectrum of electrons injected at the termination shock of the PWN is chosen to be a broken power law. In contrast to previous PWN models of a similar nature, the source spectrum has a discontinuity in intensity at the transition between the low- and high-energy components. To test the model, it is applied to the young PWN G21.5-0.9, where it is found that a discontinuous source spectrum can model the emission at all wavelengths better than a continuous one. The model is also applied to the unidentified sources HESS J1427-608 and HESS J1507-622. Parameters are derived for these two candidate nebulae that are consistent with the values predicted for other PWNe. For HESS J1427-608, a present day magnetic field of B{sub age} = 0.4 {mu}G is derived. As a result of the small present day magnetic field, this source has a low synchrotron luminosity, while remaining bright at GeV/TeV energies. It is therefore possible to interpret HESS J1427-608 within the ancient PWN scenario. For the second candidate PWN HESS J1507-622, a present day magnetic field of B{sub age} = 1.7 {mu}G is derived. Furthermore, for this candidate PWN a scenario is favored in the present paper in which HESS J1507-622 has been compressed by the reverse shock of the supernova remnant.
Multiple-relaxation-time lattice Boltzmann kinetic model for combustion
Aiguo Xu; Chuandong Lin; Guangcai Zhang; Yingjun Li
2015-03-13
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.; Catelan, M.; Smith, H. A.; Kuehn, C. A.; Pritzl, B. J.; Borissova, J.
2010-12-15
We present new time-series CCD photometry, in the B and V bands, for the moderately metal-rich ([Fe/H] {approx_equal} -1.3) Galactic globular cluster M62 (NGC 6266). The present data set is the largest obtained so far for this cluster and consists of 168 images per filter, obtained with the Warsaw 1.3 m telescope at the Las Campanas Observatory and the 1.3 m telescope of the Cerro Tololo Inter-American Observatory, in two separate runs over the time span of 3 months. The procedure adopted to detect the variable stars was the optimal image subtraction method (ISIS v2.2), as implemented by Alard. The photometry was performed using both ISIS and Stetson's DAOPHOT/ALLFRAME package. We have identified 245 variable stars in the cluster fields that have been analyzed so far, of which 179 are new discoveries. Of these variables, 133 are fundamental mode RR Lyrae stars (RRab), 76 are first overtone (RRc) pulsators, 4 are type II Cepheids, 25 are long-period variables (LPVs), 1 is an eclipsing binary, and 6 are not yet well classified. Such a large number of RR Lyrae stars places M62 among the top two most RR Lyrae-rich (in the sense of total number of RR Lyrae stars present) globular clusters known in the Galaxy, second only to M3 (NGC 5272) with a total of 230 known RR Lyrae stars. Since this study covers most but not all of the cluster area, it is not unlikely that M62 is in fact the most RR Lyrae-rich globular cluster in the Galaxy. In like vein, thanks to the time coverage of our data sets, we were also able to detect the largest sample of LPVs known so far in a Galactic globular cluster. We analyze a variety of Oosterhoff type indicators for the cluster, including mean periods, period distribution, Bailey diagrams, and Fourier decomposition parameters (as well as the physical parameters derived therefrom). All of these indicators clearly show that M62 is an Oosterhoff type I system. This is in good agreement with the moderately high metallicity of the cluster, in spite of its predominantly blue horizontal branch morphology-which is more typical of Oosterhoff type II systems. We thus conclude that metallicity plays a key role in defining Oosterhoff type. Finally, based on an application of the 'A-method', we conclude that the cluster RR Lyrae stars have a similar He abundance as M3, although more work on the temperatures of the M62 RR Lyrae is needed before this result can be conclusively established.
G. Konisi; T. Saito; Z. Maki; M. Nakahara
1998-12-08
The left-right symmetric model (LRSM) with gauge group $SU(2)_{L} \\times SU(2)_{R} \\times U(1)_{B-L}$ is reconstructed from the geometric formulation of gauge theory in $M_4 \\times Z_2 \\times Z_2$ where $M_4$ is the four-dimensional Minkowski space and $Z_2 \\times Z_2$ the discrete space with four points. The geometrical structure of this model becomes clearer compared with other works based on noncommutative geometry. As a result, the Yukawa coupling terms and the Higgs potential are derived in more restricted forms than in the standard LRSM.
Showalter, Kenneth
developments and experimental applications of feedback control to nonlinear dynamical systems [211]. Recent of Dynamical Systems from Time Series Valery Petrov and Kenneth Showalter* Department of Chemistry, West of multidimensional, nonlinear single-input single-output systems is formulated in terms of an invariant hypersurface
Dhar, A. [Enron Corp., Houston, TX (United States); Reddy, T.A. [Drexel Univ., Philadelphia, PA (United States). Civil and Architectural Engineering Dept.; Claridge, D.E. [Texas A and M Univ., College Station, TX (United States). Energy Systems Lab.
1999-02-01
Accurate modeling of hourly heating and cooling energy use in commercial buildings can be achieved by a Generalized Fourier Series (GFS) approach involving weather variables such as dry-bulb temperature, specific humidity and horizontal solar flux. However, there are situations when only temperature data is available. The objective of this paper is to (i) describe development of a variant of the GFS approach which allows modeling both heating and cooling hourly energy use in commercial buildings with outdoor temperature as the only weather variable and (ii) illustrate its application with monitored hourly data from several buildings in Texas. It is found that the new Temperature based Fourier Series (TFS) approach (1) provides better approximation to heating energy use than the existing GFS approach, (ii) can indirectly account for humidity and solar effects in the cooling energy use, (iii) offers physical insight into the operating pattern of a building HVAC system and (iv) can be used for diagnostic purposes.
Leemis, Larry
Variate Generation for Accelerated Life and Proportional Hazards Models with Time Dependent, Monte Carlo simulation, Proportional hazards model, Time dependent covariates, Variate generation. #12 Engineering 202 West Boyd, Room 124 Norman, OK 73019 September, 1989 SUMMARY Variate generation algorithms
MODELING REAL-TIME HUMAN-AUTOMATION COLLABORATIVE SCHEDULING OF UNMANNED VEHICLES
Cummings, Mary "Missy"
MODELING REAL-TIME HUMAN-AUTOMATION COLLABORATIVE SCHEDULING OF UNMANNED VEHICLES by ANDREW S, Humans and Automation Laboratory Certified by;3 MODELING REAL-TIME HUMAN-AUTOMATION COLLABORATIVE SCHEDULING OF UNMANNED VEHICLES by Andrew S. Clare
Analyzing California's GHG Reduction Paths using CA-TIMES Energy System Model
California at Davis, University of
Analyzing California's GHG Reduction Paths using CA-TIMES Energy System Model Christopher Yang@ucdavis.edu NextSTEPS (Sustainable Transportation Energy Pathways) #12;CA-TIMES Model Overview · CA-TIMES is a bottom-up, linear optimization model of California's energy sectors Technology and resources details
Invariance and homogenization of an adaptive time gap car-following model
Monneau, Régis
Invariance and homogenization of an adaptive time gap car-following model R. Monneau , M called the adaptive time gap car- following model. This is a system of ODEs which describes the interactions between cars moving on a single line. The time gap is the time that a car needs to reach
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
CONTINUOUS TIME MARKOV CHAIN MODELS FOR CHEMICAL REACTION NETWORKS
Anderson, David F.
classifications. 65L05, 65L06, 65L80, 90C30, 80A30 1. Introduction. The microscopic modeling of the dynamics
Dominici, Francesca
of the mortality and morbidity air pollution effects are 0.42 (95% interval 0.05, 1.18), and 0.31 (95% interval 0 relative rate, Air pollution. Francesca Dominici, Scott L. Zeger, Department of Biostatistics, Jonathan M The potential for air pollution at high concentrations to cause excess deaths and morbidity was firmly establis
Unfolding time : a projective model for the moving image
Watkins, Elizabeth Anne
2012-01-01
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, ...
Analysis of Competitive Electricity Markets under a New Model of Real-Time Retail Pricing with
Bhatia, Sangeeta
Analysis of Competitive Electricity Markets under a New Model of Real-Time Retail Pricing with Ex@tum.de Abstract--In this paper, we propose a new real-time retail pricing model characterized by ex and robustness properties than pure exant´e pricing. Index Terms--Real-Time Pricing, Market Stability, Economic
Application of time reverse modeling on ultrasonic non-destructive testing of concrete
Application of time reverse modeling on ultrasonic non-destructive testing of concrete Erik H-differences Wave propagation Source localization Non-destructive testing a b s t r a c t Time reverse modeling (TRM is to transform a method within exploration geo- physics to non-destructive testing. In contrast to previous time
Modeling and Analysis of Detection Time Trade-offs for Channel Searching in Cognitive
Roy, Sumit
and correlated channel model. We then highlight a key trade-off underlying the overall mean time to detect a free1 Modeling and Analysis of Detection Time Trade-offs for Channel Searching in Cognitive Radio, search scheme, sensing trade-off, optimal detection time. I. INTRODUCTION Large segments of the radio
Subexponential Tails of Discounted Aggregate Claims in a Time-Dependent Renewal Risk Model
Tang, Qihe
Subexponential Tails of Discounted Aggregate Claims in a Time-Dependent Renewal Risk Model JinzhuP05; Secondary 62H20, 60E05 1 Introduction The renewal risk model has been playing a fundamental of the renewal risk model, both claim sizes Xk, k = 1; 2; : : :, and inter-arrival times k, k = 1; 2; : : :, form
Ruin probabilities and de cit for the renewal risk model with phase{type interarrival times
Avram, Florin
Ruin probabilities and de#12;cit for the renewal risk model with phase{type interarrival times F killed ruin probability, de#12;cit at ruin, Sparre Andersen Model, phase{type distributions, Laplace transform of the #12;nite time ruin probability, by considering also the de#12;cit at ruin; the model
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
Dating Concurrent Objects: Real-Time Modeling and Schedulability Analysis
Johnsen, Einar Broch
. This research is partly funded by the EU projects IST-33826 CREDO: Modeling and Analysis of Evolutionary Structures for Distributed Services (http://credo.cwi.nl) and FP7-231620 HATS: Highly Adaptable and Trust
Time consistency and risk averse dynamic decision models ...
2013-05-02
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 ...
Lewicki, Jennifer; Lewicki, J.L.; Fischer, M.L.; Hilley, G.E.
2007-10-15
CO{sub 2} and heat fluxes were measured over a six-week period (09/08/2006 to 10/24/2006) by the eddy covariance (EC) technique at the Horseshoe Lake tree kill (HLTK), Mammoth Mountain, CA, a site with complex terrain and high, spatially heterogeneous CO{sub 2} emission rates. EC CO{sub 2} fluxes ranged from 218 to 3500 g m{sup -2} d{sup -1} (mean = 1346 g m{sup -2} d{sup -1}). Using footprint modeling, EC CO{sub 2} fluxes were compared to CO{sub 2} fluxes measured by the chamber method on a grid repeatedly over a 10-day period. Half-hour EC CO{sub 2} fluxes were moderately correlated (R{sup 2} = 0.42) with chamber fluxes, whereas average-daily EC CO{sub 2} fluxes were well correlated (R{sup 2} = 0.70) with chamber measurements. Average daily EC CO{sub 2} fluxes were correlated with both average daily wind speed and atmospheric pressure; relationships were similar to those observed between chamber CO{sub 2} fluxes and the atmospheric parameters over a comparable time period. Energy balance closure was assessed by statistical regression of EC energy fluxes (sensible and latent heat) against available energy (net radiation, less soil heat flux). While incomplete (R{sup 2} = 0.77 for 1:1 line), the degree of energy balance closure fell within the range observed in many investigations conducted in contrasting ecosystems and climates. Results indicate that despite complexities presented by the HLTK, EC can be reliably used to monitor background variations in volcanic CO{sub 2} fluxes associated with meteorological forcing, and presumably changes related to deeply derived processes such as volcanic activity.
Mining, Modeling, and Analyzing Real-Time Social Trails
Kamath, Krishna Y
2013-05-28
Real-time social systems are the fastest growing phenomena on the web, enabling millions of users to generate, share, and consume content on a massive scale. These systems are manifestations of a larger trend toward the global sharing of the real...
EXPERIMENTS IN MODELING THE SPACE-TIME INDOOR WIRELESS COMMUNICATION CHANNEL
Swindlehurst, A. Lee
include only time of arrival characteris- tics. However, in order to use statistical models in simu to know the statis- tics of the angle of arrival and its correlation with time of arrival. Inthis paper
Oracle Circuits for Branching-Time Model Checking
Doyen, Laurent
is at least exponen- tially more succinct than its pure-future fragment [LMS02b]. 2 There is a similar model checking problem [LMS01,LMS02a]. However, for some remaining logics, the techniques used in [LMS01,LMS02a] for proving p 2-hardness do not apply. The difficulty here is that, if these prob- lems
NUMERICAL MODELING OF FLUID FLOW AND TIME-LAPSE ...
gabriela
CO2 injection operation at the Sleipner gas field in the North Sea, operated by Statoil ... The simultaneous flow of brine and CO2 is modeled with the Black-Oil formulation for ..... As water saturation is reduced, and the larger pores drained first, ...
Synchronous Closing of Timed SDL Systems for Model Checking
Sidorova, Natalia
the model from a piece of software? additional techniques: 1. abstraction: (a) data abstraction: replace concrete domains by finite, abstract ones (b) control abstraction, i.e., add non-determinism 2. system solutions 1. one-valued data abstraction ¢¡ no external data 2. three-valued timer abstraction 3
About model of the Universe with accelerated movement of the time
W. B. Belayev
1999-03-30
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 .
Effectiveness of 4D construction modeling in detecting time-space conflicts of construction sites
Nigudkar, Narendra Shriniwas
2005-11-01
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...
SQUARE SUMMABLE POWER SERIES Louis de Branges Preface ...
1911-01-10
The space C(z) of square summable power series is the set of power series ...... model of the linear system is constructed in a Hilbert space of power series with ...
A quantum model of space-time-matter
Isaac Cohen
2005-03-24
We study a quantum mechanics with the usual postulates but in which the Heisenberg algebra of canonical commutation relations and the Poincare algebra are replaced by the Lie algebra of the homogeneous Lorentz group SO(5,1). It arises from the hypothesis that the above group is the fundamental group of invariance for the laws of physics. The observables of the theory like position, time, momentum, energy, angular momentum and others are the generators of the algebra of the group. Neither position and time observables commute between them, nor momentum and energy observables. The algebra of Poincare quantum mechanics is recovered in the limit in which two parameters, that we physically interpret as the Hubble constant and the Planck mass, are taken to zero and infinite respectively. We consider the equations that are satisfied by the spinor representation of the group.
Open Universe Modeling: Information Layer and Time Dilation
Baris Baykant Alagoz
2010-11-10
In this paper, we suppose that the universe has an information processing layer, which coveys the informational contents accompanying the physical events. In this manner, universe is considered to be composed of several associative layers such that one rises on the other layer. Preliminary, we present a method for the analytical treatment of the amount of information processed by universe itself, and then we try to show its correspondence with theories developed for the time dilation and gravitational forces.
A comparative study of continuous-time modelings for scheduling of crude oil operations
Grossmann, Ignacio E.
A comparative study of continuous-time modelings for scheduling of crude oil operations Xuan Chena and formulations for the crude oil scheduling problem. We compare the event-based model, the unit slot model on its efficient performance for industrial problems. Keywords: Crude oil scheduling; event-based model
Method of modeling transmissions for real-time simulation
Hebbale, Kumaraswamy V.
2012-09-25
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.
Wehlau, David
Math 421 Fourier Series Autumn 2006 Text: Fourier Series, by Rajendra Bhatia, Math. Assoc. of America, 2005. Topics Covered: Ch. 1, Fourier series and the heat equation Ch. 2, Convergence of Fourier series Ch. 3, Sine and cosine series, arbitrary pe- riods, sin(x)/x, Gibbs's phenomenon Ch. 4
Fourier Series and Integrals Fourier Series
Mehta, Pankaj
Fourier Series and Integrals Fourier Series Let f(x) be a piecewise linear function on [-L, L(x) can be expanded in a Fourier series f(x) = a0 2 + n=1 an cos nx L + bn sin nx L , (1a) or schematic form of the Fourier series is f(x) = n (an^cn + bn^sn). (2) This emphasizes that the Fourier
Space-time complexity in solid state models
Bishop, A.R.
1985-01-01
In this Workshop on symmetry-breaking it is appropriate to include the evolving fields of nonlinear-nonequilibrium systems in which transitions to and between various degrees of ''complexity'' (including ''chaos'') occur in time or space or both. These notions naturally bring together phenomena of pattern formation and chaos and therefore have ramifications for a huge array of natural sciences - astrophysics, plasmas and lasers, hydrodynamics, field theory, materials and solid state theory, optics and electronics, biology, pattern recognition and evolution, etc. Our particular concerns here are with examples from solid state and condensed matter.
First-time measurements will advance turbulence models
Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)
AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantityBonneville Power Administration would likeUniverse (Journal Article) |Final Reportthe GrowingDirectProofofFirstorderFirst-time
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
2015-01-01
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.
Analytical, Wavelet and Frequency based Mathematical Models for Real-Time Rendering
Columbia University
Analytical, Wavelet and Frequency based Mathematical Models for Real-Time Rendering Bo Sun School of Arts and Sciences COLUMBIA UNIVERSITY 2008 #12;c 2008 Bo Sun All Rights Reserved #12;ABSTRACT Analytical, Wavelet and Frequency based Mathematical Models for Real-Time Rendering Bo Sun Real
El Nino duration time (month) Dynamic coupling of an ENSO model to the
Goelzer, Heiko
El Nino duration time (month) Dynamic coupling of an ENSO model to the global coupled climate model changes in the thermohaline circulation and changes in the El Nino/Southern Oscillation (ENSO), the Zebiak distribution El Nino event interval (month) · Interval between ENSO events shifted towards longer times
A modelling framework for the prices and times of trades made on the New York stock
Wolfe, Patrick J.
A modelling framework for the prices and times of trades made on the New York stock exchange Tina for price changes over pre-speci ed intervals of times, such as 30 seconds, 20 minutes or a day option pricing model. In practice almost all the prices at which nancial assets transact live
MODELING AND VERIFICATION OF REAL-TIME AND CYBER-PHYSICAL SYSTEMS
Gupta, Gopal
MODELING AND VERIFICATION OF REAL-TIME AND CYBER-PHYSICAL SYSTEMS by Neda Saeedloei APPROVED Copyright 2011 Neda Saeedloei All Rights Reserved #12;To my mother. #12;MODELING AND VERIFICATION OF REAL-TIME AND CYBER-PHYSICAL SYSTEMS by NEDA SAEEDLOEI, B.S., M.S. DISSERTATION Presented to the Faculty
Numerical modeling of fluid flow and time-lapse seismics to monitor CO2
Santos, Juan
Numerical modeling of fluid flow and time-lapse seismics to monitor CO2 Sequestration in aquifers J, ITALY). IMAL, 30/5/2014 Numerical modeling of fluid flow and time-lapse seismics to monitor CO2 Sequestration in aquifers Â p. #12;Introduction. I Storage of CO2 in geological formations is a procedure
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
Time delay for dispersive systems in quantum scattering theory. I. The Friedrichs model
Rafael Tiedra de Aldecoa
2008-04-08
We present a method for proving the existence of time delay (defined in terms of sojourn times) as well as its identity with Eisenbud-Wigner time delay in the case of the Friedrichs model. We show that this method applies to scattering by finite rank potentials.
A Tactical Planning Model for a Production Network with Continuous-Time Control
Graves, Stephen C.
1 A Tactical Planning Model for a Production Network with Continuous-Time Control Chee-Chong Teo1 for production planning, the time period needs to be long enough to coincide with the underlying time buckets network. Subject classifications: Inventory/production: tactical planning that considers tradeoffs between
Field Quality Study of the LARP Nb3Sn 3.7m-Long Quadrupole Models of LQ Series
AMbrosio, G.; Andreev, N.; Bossert, R.; Chlachidze, G.; DiMarco, J.; Kashikhin, V.V.; Lamm, M.J.; Nobrega, F.; Prebys, E.; Sylvester, C.; Tartaglia, M.; /Fermilab /LBL, Berkeley /Brookhaven
2011-09-01
After the successful test of the first long Nb{sub 3}Sn quadrupole magnet (LQS01), the US LHC Accelerator Research Program (LARP) has assembled and tested a new 3.7 m-long Nb{sub 3}Sn quadrupole (LQS02). This magnet has four new coils made of the same conductor as LQS01 coils, and it is using the same support structure. LQS02 was tested at the Fermilab Vertical Magnet Test Facility with the main goal to confirm that the long models can achieve field gradient above 200 T/m, LARP target for 90-mm aperture, as well as to measure the field quality. These long models lack some alignment features and it is important to study the field harmonics. Previous field quality measurements of LQS01 showed higher than expected differences between measured and calculated harmonics compared to the short models (TQS) assembled in a similar structure. These differences could be explained by the use of two different impregnation fixtures during coil fabrication. In this paper, we present a comparison of the field quality measurements between LQS01 and LQS02 as well as a comparison with the short TQS models. If the result supports the coil fabrication hypothesis, another LQS assembly with all coils fabricated in the same fixture will be produced for understanding the cause of the discrepancy between short and long models.
A Real-time World Model for Multi-Robot Teams with High-Latency Communication
Veloso, Manuela M.
A Real-time World Model for Multi-Robot Teams with High-Latency Communication Maayan Roth, Douglas Vail, and Manuela Veloso School of Computer Science Carnegie Mellon University Pittsburgh PA, 15213- structing a world model in a multi-robot team. We in- troduce two separate world models, namely
Driver Models For Timing And Noise Analysis Bogdan Tutuianu and Ross Baldick
Baldick, Ross
Driver Models For Timing And Noise Analysis Bogdan Tutuianu and Ross Baldick Abstract and ways to model and analyze it is given in [23]. Other tools and methodologies for functional noise analysis are proposed in [19], [10] and [1]. Special circuit modeling techniques to asses global noise
International Association for Cryptologic Research (IACR)
inputs collected through a smart metering network. The main shortcomings of this solution are its environment whereby data is produced by a set of users that hold smart meters. Smart meters can report accurately at specific time intervals energy, gas or water consumption. Considering electricity consumption
Specific Heat Exponent for the 3-d Ising Model from a 24-th Order High Temperature Series
G. Bhanot; M. Creutz; U. Glaessner; K. Schilling
1993-12-10
We compute high temperature expansions of the 3-d Ising model using a recursive transfer-matrix algorithm and extend the expansion of the free energy to 24th order. Using ID-Pade and ratio methods, we extract the critical exponent of the specific heat to be alpha=0.104(4).
Proposed SPAR Modeling Method for Quantifying Time Dependent Station Blackout Cut Sets
John A. Schroeder
2010-06-01
Abstract: The U.S. Nuclear Regulatory Commission’s (USNRC’s) Standardized Plant Analysis Risk (SPAR) models and industry risk models take similar approaches to analyzing the risk associated with loss of offsite power and station blackout (LOOP/SBO) events at nuclear reactor plants. In both SPAR models and industry models, core damage risk resulting from a LOOP/SBO event is analyzed using a combination of event trees and fault trees that produce cut sets that are, in turn, quantified to obtain a numerical estimate of the resulting core damage risk. A proposed SPAR method for quantifying the time-dependent cut sets is sometimes referred to as a convolution method. The SPAR method reflects assumptions about the timing of emergency diesel failures, the timing of subsequent attempts at emergency diesel repair, and the timing of core damage that may be different than those often used in industry models. This paper describes the proposed SPAR method.
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
2014-01-01
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.
Design and Modeling of a Continuous-Time Delta-Sigma Modulator for Biopotential Signal
Mohanty, Saraju P.
Design and Modeling of a Continuous-Time Delta-Sigma Modulator for Biopotential Signal Acquisition in biopotential signal acquisition. The rest of this paper is organized as follows: Section II presents the CT DSM
Nonlinear Time Domain Modeling and Simulation of Surface and Embedded NPPS
Broader source: Energy.gov [DOE]
Nonlinear Time Domain Modeling and Simulation of Surface and Embedded NPPS Boris Jeremic with contributions from Federico Pisanò, Jose Abell, Kohei Watanabe, Chao Luo University of California, Davis Lawrence Berkeley National Laboratory, Berkeley DOE NPH, October 2014
3D weak-dispersion reverse time migration using a stereo-modeling operator
Li, Jingshuang
Reliable 3D imaging is a required tool for developing models of complex geologic structures. Reverse time migration (RTM), as the most powerful depth imaging method, has become the preferred imaging tool because of its ...
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
Toward Real-time Modeling of Human Heart Ventricles at Cellular...
Office of Scientific and Technical Information (OSTI)
Conference: Toward Real-time Modeling of Human Heart Ventricles at Cellular Resolution: Multi-hour Simulation of Drug-induced Arrhythmias Citation Details In-Document Search Title:...
A time-delay approach for the modeling and control of plasma instabilities in thermonuclear fusion
Sipahi, Rifat
1 A time-delay approach for the modeling and control of plasma instabilities in thermonuclear for thermonuclear fusion plasmas. Indeed, advanced plasma confinement scenarios, such as the ones considered
QGP time formation in holographic shock waves model of heavy ion collisions
Aref'eva, Irina Ya
2015-01-01
We estimate the thermalization time in two colliding shock waves holographic model of heavy-ion collisions. For this purpose we model the process by the Vaidya metric with a horizon defined by the trapped surface location. We consider two bottom-up AdS/QCD models that give, within the colliding shock waves approach, the dependence of multiplicity on the energy compatible with RHIC and LHC results. One model is a bottom-up AdS/QCD confining model and the other is related to an anisotropic thermalization. We estimate the thermalization time and show that increasing the confining potential decreases the thermalization time as well as an anisotropy accelerates the thermalization.
QGP time formation in holographic shock waves model of heavy ion collisions
Irina Ya. Aref'eva
2015-03-07
We estimate the thermalization time in two colliding shock waves holographic model of heavy-ion collisions. For this purpose we model the process by the Vaidya metric with a horizon defined by the trapped surface location. We consider two bottom-up AdS/QCD models that give, within the colliding shock waves approach, the dependence of multiplicity on the energy compatible with RHIC and LHC results. One model is a bottom-up AdS/QCD confining model and the other is related to an anisotropic thermalization. We estimate the thermalization time and show that increasing the confining potential decreases the thermalization time as well as an anisotropy accelerates the thermalization.
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
Kumar, Ajitabh
2009-05-15
using reservoir models and inverse modeling for updating reservoir models using the data collected from field. The viability of time-lapse seismic monitoring using an integrated modeling of fluid flow, including chemical reactions, and seismic response...
Numerical modeling of fluid flow and time-lapse seismograms applied to
Santos, Juan
; and CO2 and CO2 are the CO2 mole fraction and the CO2 mass fraction in the brine phase. This conversionNumerical modeling of fluid flow and time-lapse seismograms applied to CO2 storage and monitoring G and time-lapse seismograms applied to CO2 storage and monitoring p. #12;Introduction · Fossil
A Real-Time Reliability Model for Ontology-Based Dynamic Web Service Composition
Xu, Haiping
153 A Real-Time Reliability Model for Ontology-Based Dynamic Web Service Composition Harmeet Chawla--Ontology-based web service composition allows for integration of available web services in real-time to meet desired objectives. In order to evaluate the quality of composite web services at runtime, there is a pressing need
Linear Compositional Delay Model for the Timing Analysis of Sub-Powered Combinational Circuits
Linear Compositional Delay Model for the Timing Analysis of Sub-Powered Combinational Circuits the propagation delay through nanometer CMOS circuits is highly desirable. Statistical Static Timing Analysis to accurately capture the circuit behaviour. In view of this we introduce an Inverse Gaussian Distribution (IGD
Modeling and Analysis of Load and Time Dependent Software Rejuvenation Policies
Telek, Miklós
divided into design, coding and test ing phase. Traditionally, software quality improve mentModeling and Analysis of Load and Time Dependent Software Rejuvenation Policies S. Garg 1 , A running clientserver type software systems by many clients, such software ``ages'' with time
An Approach of Modeling, Monitoring and Managing Business Operations for Just-In-Time Manufacturing
Li, Haifei
An Approach of Modeling, Monitoring and Managing Business Operations for Just-In-Time Manufacturing execution and monitoring for the JIT (Just In Time) schedule execution. JIT is a manufacturing method to change their manufacturing orders. When a manufacturer receives an order change request, the manufacturer
ForPeerReview Time-varying autoregressive conditional duration model
Morettin, Pedro A.
-stationary processes without preliminary data transformations. The time-varying ACD model estimation was done Introduction As computation power and data storage capacity grows, it becomes possible to gather and analyze, in other words, longer times between transactions indicate less activity of the market. The behavior
A Generic Timing Model for Cyber-Physical Florian Kluge, Mike Gerdes, Florian Haas, Theo Ungerer
Ungerer, Theo
, for example, the crank shaft in a combustion engine. Certain angu- larities of the crank shaft raise of the crank shaft and changes over time. Specialised real-time task models, e.g. [5,6], are able to map
Paris-Sud XI, Université de
Analyzing water supply in future energy systems using the TIMES Integrated Assessment Model (TIAM Mathematics, MINES ParisTech Sophia Antipolis, France ABSTRACT Even though policies related to water is required to maintain water supplies while water is essential to produce energy. However, the models
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
NUMERICAL SOLUTION OF RESERVOIR FLOW MODELS BASED ON LARGE TIME STEP OPERATOR SPLITTING ALGORITHMS
NUMERICAL SOLUTION OF RESERVOIR FLOW MODELS BASED ON LARGE TIME STEP OPERATOR SPLITTING ALGORITHMS. Special focus is posed on the numerical solution algorithms for the saturation equation, which. The general background for the reservoir ow model is reviewed, and the main features of the numerical
NUMERICAL SOLUTION OF RESERVOIR FLOW MODELS BASED ON LARGE TIME STEP OPERATOR SPLITTING ALGORITHMS
NUMERICAL SOLUTION OF RESERVOIR FLOW MODELS BASED ON LARGE TIME STEP OPERATOR SPLITTING ALGORITHMS focus is posed on the numerical solution algorithms for the saturation equation, which is a convectionÂ eral background for the reservoir flow model is reviewed, and the main features of the numerical
Tentzeris, Manos
Modeling and Optimization of RF-MEMS Reconfigurable Tuners with Computationally Efficient Time of Technology, Atlanta, GA 30332 2 Raytheon Company, Tucson AZ, 85734 Abstract -- Modern RF-MEMS device design methods in which the FDTD technique can be used to model a reconfigurable RF-MEMS tuner. A new method
Spatio-temporal precipitation modeling based on time-varying regressions Oleg Makhnin
Borchers, Brian
Spatio-temporal precipitation modeling based on time-varying regressions Oleg Makhnin Department on monthly precipitation data from gauge measurements. The model accounts for orographic effects in northern New Mexico. We assess spatio-temporal variability and also trace the dependence of precipitation
Dedicated and intrinsic models of time Richard B. Ivry1,2
Jacobs, Lucia
Dedicated and intrinsic models of time perception Richard B. Ivry1,2 and John E. Schlerf2 1 of a stimulus depends on the operation of dedicated neural mechanisms specialized for representing the temporal be addressed before we dispense with models of duration perception that are based on dedicated processes
The IAU Resolutions on Astronomical Reference Systems, Time Scales, and Earth Rotation Models
George H. Kaplan
2006-02-03
Recent resolutions passed by the International Astronomical Union (IAU) on astronomical reference systems, time scales, and Earth rotation models are the most significant set of international agreements in positional astronomy in several decades. These resolutions, the result of over ten years of international research and study, provide a coherent set of foundational standards for the treatment of astrometric data and the modeling of dynamics in the solar system. This circular explains these resolutions and provides a complete set of practical formulas for their implementation. The six main chapters cover relativity, time scales, the fundamental celestial reference system, ephemerides of solar system bodies, precession and nutation, and modeling the Earth's rotation.
Time-variability of alpha from realistic models of Oklo reactors
C. R. Gould; E. I. Sharapov; S. K. Lamoreaux
2007-04-30
We reanalyze Oklo $^{149}$Sm data using realistic models of the natural nuclear reactors. Disagreements among recent Oklo determinations of the time evolution of $\\alpha$, the electromagnetic fine structure constant, are shown to be due to different reactor models, which led to different neutron spectra used in the calculations. We use known Oklo reactor epithermal spectral indices as criteria for selecting realistic reactor models. Two Oklo reactors, RZ2 and RZ10, were modeled with MCNP. The resulting neutron spectra were used to calculate the change in the $^{149}$Sm effective neutron capture cross section as a function of a possible shift in the energy of the 97.3-meV resonance. We independently deduce ancient $^{149}$Sm effective cross sections, and use these values to set limits on the time-variation of $\\alpha$. Our study resolves a contradictory situation with previous Oklo $\\alpha$-results. Our suggested $2 \\sigma$ bound on a possible time variation of $\\alpha$ over two billion years is stringent: $ -0.24 \\times 10^{-7} \\le \\frac{\\Delta \\alpha}{\\alpha} \\le 0.11 \\times 10^{-7}$, but model dependent in that it assumes only $\\alpha$ has varied over time.
Kim, Hee-Kyung
2008-01-01
production function, the optimal allocation of time tofunction, the structural model of household resource allocationfunction. Domestic production model The optimal allocation
Improvements of the shock arrival times at the Earth model STOA
Liu, H -L
2015-01-01
Prediction of the shocks' arrival times (SATs) at the Earth is very important for space weather forecast. There is a well-known SAT model, STOA, which is widely used in the space weather forecast. However, the shock transit time from STOA model usually has a relative large error compared to the real measurements. In addition, STOA tends to yield too much `yes' prediction, which causes a large number of false alarms. Therefore, in this work, we work on the modification of STOA model. First, we give a new method to calculate the shock transit time by modifying the way to use the solar wind speed in STOA model. Second, we develop new criteria for deciding whether the shock will arrive at the Earth with the help of the sunspot numbers and the angle distances of the flare events. It is shown that our work can improve the SATs prediction significantly, especially the prediction of flare events without shocks arriving at the Earth.
Arnold, Jonathan
Series Packages MASTERWORKS · Atlanta Symphony Orchestra and Chorus September 20 · Atlanta PACKAGE · Includes all of the concerts on both the Masterworks and Classics series. Ten performances · This package includes all of the events on the Show Biz and Celebrity Evenings series. Ten performances in all
- ued "brightening" of this class III AVO reservoir with pro- duction as the gas saturation continuouslyWhy perform time-lapse seismic monitoring? Is it to ver- ify the reservoir model? No! We should conduct time-lapse seismic surveys in order to find out what is incorrect in the reservoir model, in a way
Zwickl, Derrick J.; Holder, Mark T.
2004-01-01
.— Bayesian phylo^enetic methods reiiuire Ihe selection of prior probability distribulions for all parameters of the model of evolution. These distribulii>ns allow one to incorporate prior information into a liayesian analysis, but even in the absence...
El-Halwagi, Ali
2012-05-03
City may be different than those in lesser-developed regions like Thailand. Estimation of model parameters provides us insight into the driving forces affecting the spread of the disease. _______________ This thesis follows the style of Chemical...
Learning connections in financial time series
Gartheeban, Ganeshapillai
2014-01-01
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 ...
Exact Primitives for Time Series Data Mining
Mueen, Abdullah Al
2012-01-01
on Knowledge discovery and data mining, KDD, pages 947–956,on Knowledge discovery and data mining, KDD ’11, pages [15]on Knowledge discovery and data mining, KDD ’03, pages 493–
Real time assimilation of HF radar currents into a coastal ocean model
Breivik, Øyvind; 10.1016/S0924-7963(01)00002-1
2012-01-01
A real time assimilation and forecasting system for coastal currents is presented. The purpose of the system is to deliver current analyses and forecasts based on assimilation of high frequency radar surface current measurements. The local Vessel Traffic Service monitoring the ship traffic to two oil terminals on the coast of Norway received the analyses and forecasts in real time. A new assimilation method based on optimal interpolation is presented where spatial covariances derived from an ocean model are used instead of simplified mathematical formulations. An array of high frequency radar antennae provide the current measurements. A suite of nested ocean models comprise the model system. The observing system is found to yield good analyses and short range forecasts that are significantly improved compared to a model twin without assimilation. The system is fast; analysis and six hour forecasts are ready at the Vessel Traffic Service 45 minutes after acquisition of radar measurements.
Lie algebra solution of population models based on time-inhomogeneous Markov chains
House, Thomas
2011-01-01
Many natural populations are well modelled through time-inhomogeneous stochastic processes. Such processes have been analysed in the physical sciences using a method based on Lie algebras, but this methodology is not widely used for models with ecological, medical and social applications. This paper presents the Lie algebraic method, and applies it to three biologically well motivated examples. The result of this is a solution form that is often highly computationally advantageous.
Experiments with a time-dependent, zonally averaged, seasonal, enery balance climatic model
Thompson, Starley Lee
1977-01-01
EXPERIMENTS WITH A TI&E-DEPENDENT, ZONALLY AVERAGED, SEASONAL, ENERGY BALANCE CLIMATIC MODEL A Thesis by STARLEY LEE THOMPSON Submitted to the Graduate College of Texas ASM University in partial fulfillment of the requirement for the decree... of MASTER OF SCIENCE December 1977 Major Subject: Meteorology EXPERIMENTS WITH A TIME DEPENDENT~ ZONALLY AVERAGED~ SEASONAL, ENERGY BALANCE CLIMATIC MODEL A Thesis by STARLEY LEE THOMPSON Approved as to style and content by: (Chairman of Committee...
time algorithm for d-dimensional protein folding in the HP-model
Istrail, Sorin
A 2O(n 1-1 d log n) time algorithm for d-dimensional protein folding in the HP-model Bin Fu Wei Wang Abstract The protein folding problem in the HP-model is NP-hard in both 2D and 3D [4, 6 structure. By studying how proteins fold, their functions can be better understood. The study of protein
Real-time characterization of partially observed epidemics using surrogate models.
Safta, Cosmin; Ray, Jaideep; Lefantzi, Sophia; Crary, David; Sargsyan, Khachik; Cheng, Karen
2011-09-01
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.
Series Transmission Line Transformer
Buckles, Robert A. (Livermore, CA); Booth, Rex (Livermore, CA); Yen, Boris T. (El Cerrito, CA)
2004-06-29
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.
Day-Ahead and Real-Time Models for Large-Scale Energy Storage
Engineering Research Center Empowering Minds to Engineer the Future Electric Energy System #12;DayDay-Ahead and Real-Time Models for Large-Scale Energy Storage Final Project Report Power Systems of Electrical, Computer, and Energy Engineering P.O. BOX 875706 Tempe, AZ 85287-5706 Phone: 480 965-1276 Fax
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
Climate Projections Using Bayesian Model Averaging and Space-Time Dependence
Haran, Murali
Climate Projections Using Bayesian Model Averaging and Space-Time Dependence K. Sham Bhat, Murali Haran, Adam Terando, and Klaus Keller. Abstract Projections of future climatic changes are a key input to the design of climate change mitiga- tion and adaptation strategies. Current climate change projections
A Performance Model to Estimate Execution Time of Scientific Workflows on the Cloud
Sakellariou, Rizos
. In the evaluation, three real-world scientific workflows are used to compare the estimated makespan calculatedA Performance Model to Estimate Execution Time of Scientific Workflows on the Cloud Ilia Pietri.K Information Sciences Institute, University of Southern California, USA Abstract--Scientific workflows, which
Aalborg Universitet Time-Varying FOPDT Modeling and On-line Parameter Identification
Yang, Zhenyu
Zhen Sun Department of Energy Technology, Aalborg University, Esbjerg Campus, Niels Bohrs Vej 8, DK; Sun, Zhen Published in: 3th IFAC Symposium on Large Scale Complex Systems: Theory and Applications for published version (APA): Yang, Z., & Sun, Z. (2013). Time-Varying FOPDT Modeling and On-line Parameter
A Novel Virtual Age Reliability Model for Time-to-Failure Prediction
Cotofana, Sorin
counts, devices approaching physical feature size limits and nuclear plant comparable power densityA Novel Virtual Age Reliability Model for Time-to-Failure Prediction Yao Wang, Sorin Cotofana their relatively short operating lifetime. To overcome the MTTF weakness, this paper proposes a novel virtual age
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
deYoung, Brad
Modelling the distribution, sustainability and diapause emergence timing of the copepod Calanus of population sustainability. We are able to simulate reasonably well the temporal and spatial patterns, however, are dependent upon ships of opportunity, which rarely venture into the mid- and northern Labrador
MODELING SPACE-TIME DEPENDENT HELIUM BUBBLE EVOLUTION IN TUNGSTEN ARMOR UNDER IFE CONDITIONS
Ghoniem, Nasr M.
dependent Helium transport in finite geometries, including the simultaneous transient production of defects of Helium bubbles. I. INTRODUCTION Helium production and helium bubble evolution in neutronMODELING SPACE-TIME DEPENDENT HELIUM BUBBLE EVOLUTION IN TUNGSTEN ARMOR UNDER IFE CONDITIONS Qiyang
A Real-Time Opponent Modeling System for Rush Football Kennard Laviers
Sukthankar, Gita Reese
A Real-Time Opponent Modeling System for Rush Football Kennard Laviers Department of EECS football game (Rush 2008) to create an au- tonomous offensive team capable of responding to unexpected a popular domain where planning is crucial and accurate plan recognition is possible--American football
Real-Time Model-Based Fault Diagnosis for Switching Power Converters
Sanders, Seth
demonstration for a 1.2 kW rack-level uninterruptable power supply (UPS) dc-dc converter for data center for a 1.2 kW rack- level uninterruptable power supply (UPS) dc-dc converter for data center applicationsReal-Time Model-Based Fault Diagnosis for Switching Power Converters Jason Poon, Ioannis C
Analysis of Competitive Electricity Markets under a New Model of Real-Time Retail Pricing with
Hirche, Sandra
Analysis of Competitive Electricity Markets under a New Model of Real-Time Retail Pricing with Ex loop system. Under this pricing mechanism, electricity is priced at the exant´e price (calculated based, dahleh, mitter}@mit.edu Siemens Corporate Technology, Munich, Germany dragan
Energy-Aware Modeling and Scheduling of Real-Time Tasks for Dynamic Voltage Scaling
Xu, Cheng-Zhong
scaling (DVS) is an effective approach to power reduction by scaling the processor voltage and frequency the voltage accordingly. On the other hand, a reduction of the operating frequency leads to an increaseEnergy-Aware Modeling and Scheduling of Real-Time Tasks for Dynamic Voltage Scaling Xiliang Zhong
Modeling of Large Scale RF-MEMS Circuits Using Efficient Time-Domain Techniques
Tentzeris, Manos
Modeling of Large Scale RF-MEMS Circuits Using Efficient Time-Domain Techniques N. Bushyager, E Engineering Georgia Institute of Technology Atlanta, GA 30332-0250, USA Abstract RF-MEMS design is made difficult due to the lack of tools capable of simulating both MEMS devices and their surrounding circuits
A time-delay approach for the modeling and control of plasma instabilities in thermonuclear fusion
Paris-Sud XI, Université de
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
Control-Oriented Model of a Dual Equal Variable Cam Timing Spark Ignition Engine
Grizzle, Jessy W.
Control-Oriented Model of a Dual Equal Variable Cam Timing Spark Ignition Engine A. G of min- imizing exhaust emissions, providing increased fuel economy and satisfying driver perfor- mance that provides a tradeo among idle stability, fuel economy, and maximum torque performance. There are also
Computer representation of the model covariance function resulting from travel-time tomography
Cerveny, Vlastislav
Karlovu 3, 121 16 Praha 2, Czech Republic, http://sw3d.cz/sta#11;/klimes.htm Summary This paper represents generalization of the equations from interpo- lation of slowness to interpolation of general power of velocity is designed. Keywords Travel{time tomographic inversion, resolution, velocity model, medium covariance func
Ris-R-1174(EN) RTMOD: Real-Time MODel Evaluation
Risø-R-1174(EN) RTMOD: Real-Time MODel Evaluation Giovanni Graziani and Stefano Galmarini JRC January 2000 #12;Abstract. The 1998 - 1999 RTMOD project is a system based on an automated statistical-friendly interface for data submission and an interactive program module for displaying, intercomparison and analysis
Introduction to Fourier Series
2014-10-15
Oct 15, 2014 ... The Basics. Fourier series ... period L. Sine and cosine are the most “basic” periodic functions! .... So just sit back, relax, and enjoy the ride!
A multiple-relaxation-time lattice Boltzmann model for convection heat transfer in porous media
Liu, Q; Li, Q
2013-01-01
In this paper, a multiple-relaxation-time (MRT) lattice Boltzmann (LB) model is developed for simulating convection heat transfer in porous media at the representative elementary volume scale. In the model, a MRT-LB equation is used to simulate the flow field, while another MRT-LB equation is employed to simulate the temperature field. The effect of the porous media is considered by introducing the porosity into the equilibrium moments, and adding a forcing term to the MRT-LB equation of the flow field in the moment space. The proposed MRT-LB model is validated by numerical simulations of several two-dimensional convection problems in porous media. The numerical results predicted by the present MRT-LB model agree well with those reported in the literature.
How real-time cosmology can distinguish between different anisotropic models
Amendola, Luca; Bjælde, Ole Eggers; Valkenburg, Wessel; Wong, Yvonne Y.Y. E-mail: oeb@phys.au.dk E-mail: yvonne.y.wong@unsw.edu.au
2013-12-01
We present a new analysis on how to distinguish between isotropic and anisotropic cosmological models based on tracking the angular displacements of a large number of distant quasars over an extended period of time, and then performing a multipole-vector decomposition of the resulting displacement maps. We find that while the GAIA mission operating at its nominal specifications does not have sufficient angular resolution to resolve anisotropic universes from isotropic ones using this method within a reasonable timespan of ten years, a next-generation GAIA-like survey with a resolution ten times better should be equal to the task. Distinguishing between different anisotropic models is however more demanding. Keeping the observational timespan to ten years, we find that the angular resolution of the survey will need to be of order 0.1 ?as in order for certain rotating anisotropic models to produce a detectable signature that is also unique to models of this class. However, should such a detection become possible, it would immediately allow us to rule out large local void models.
Late time acceleration in a non-commutative model of modified cosmology
B. Malekolkalami; K. Atazadeh; B. Vakili
2014-11-25
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.
UserCalc: A Web-based uranium series calculator for magma migration problems
Spiegelman, Marc W.
UserCalc: A Web-based uranium series calculator for magma migration problems M. Spiegelman Lamont] Abstract: Measured departures from secular equilibrium in the uranium series decay chains provide important series models. Keywords: Uranium series disequilibrium; geochemical models; mantle modeling; magma
Real-Time Forcast Model Analysis of Daily Average Building Load for a Thermal Storage System Control
Song, L.; Joo, I. S.; Guwana, S.
2009-01-01
methods for real-time forecasting of building electrical demand, ASHRAE Transaction vol.97(1):710-721 D.C. Montgomery, C. L. Jennings, M. Kulahci. 2007. Introduction to time series analysis and forecasting, ISBN 978-0-471-65397-4. L Ljung, T. S...?derstr?m, 1987, Theory and application of recursive identification, ISBN 978-0-262-12095-1 ESL-IC-09-11-03 Proceedings of the Ninth International Conference for Enhanced Building Operations, Austin, Texas, November 17 - 19, 2009 ...
Li, C.; Su, W.; Fang, C.; Zhong, S. J.; Wang, L.
2014-09-10
We present a study of the waiting time distributions (WTDs) of solar energetic particle (SEP) events observed with the spacecraft WIND and GOES. The WTDs of both solar electron events (SEEs) and solar proton events (SPEs) display a power-law tail of ??t {sup –?}. The SEEs display a broken power-law WTD. The power-law index is ?{sub 1} = 0.99 for the short waiting times (<70 hr) and ?{sub 2} = 1.92 for large waiting times (>100 hr). The break of the WTD of SEEs is probably due to the modulation of the corotating interaction regions. The power-law index, ? ? 1.82, is derived for the WTD of the SPEs which is consistent with the WTD of type II radio bursts, indicating a close relationship between the shock wave and the production of energetic protons. The WTDs of SEP events can be modeled with a non-stationary Poisson process, which was proposed to understand the waiting time statistics of solar flares. We generalize the method and find that, if the SEP event rate ? = 1/?t varies as the time distribution of event rate f(?) = A?{sup –?}exp (– ??), the time-dependent Poisson distribution can produce a power-law tail WTD of ??t {sup ?} {sup –3}, where 0 ? ? < 2.
Generalized Uncertainty Relations and Long Time Limits for Quantum Brownian Motion Models
C. Anastopoulos; J. J. Halliwell
1994-07-27
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.
Fast history matching of time-lapse seismic and production data for high resolution models
Jimenez, Eduardo Antonio
2008-10-10
monitoring fluid movements throughout the reservoir. 4D seismic advances are also being driven by an increased need by the petroleum engineering community to become more quantitative and accurate in our ability to monitor reservoir processes. Qualitative... interpretations of time-lapse anomalies are being replaced by quantitative inversions of 4D seismic data to produce accurate maps of fluid saturations, pore pressure, temperature, among others. Within all steps involved in this subsurface modeling process...
Real-Time Multi-Sensor Multi-Source Network Data Fusion Using Dynamic Traffic Assignment Models
Ben-Akiva, Moshe E.
This paper presents a model-based data fusion framework that allows systematic fusing of multi-sensor multi-source traffic network data at real-time. Using simulation-based Dynamic Traffic Assignment (DTA) models, the ...
Salvaggio, Carl
images representing what an airborne or satellite thermal infrared imaging sensor would record. The scene sensors to a point where the model can be usedas a research tool to evaluate the limitations in our infrared (TIR) imagery generated by midwave (3-5 Rm) and longwave (8-14 pm) sensors is being increasingly
Jackson, Robert B.
decomposition data with process-based biogeochemical models is essential to quantify the turnover of organic to model multiple cohort decomposition, unifying both types of experimental data in one theory. Based models with a single time-dependent decay rate, and two models based on a continuous distribution
Model-independent plotting of the cosmological scale factor as a function of lookback time
Ringermacher, H. I.; Mead, L. R., E-mail: ringerha@gmail.com, E-mail: Lawrence.mead@usm.edu [Department of Physics and Astronomy, University of Southern Mississippi, Hattiesburg, MS 39406 (United States)
2014-11-01
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.
The time evolution of cosmological redshift in non-standard dark energy models
Balbi, A
2007-01-01
The variation of the expansion rate of the universe with time produces an evolution in the cosmological redshift of distant sources (for example quasars), that might be directly observed (over a decade or so) by future ultra stable, high-resolution spectrographs (such as CODEX) coupled to extremely large telescopes (such as ESO's ELT). This would open a new window to explore the physical mechanism responsible for the current acceleration of the universe. We investigate the evolution of cosmological redshift from a variety of non-standard dark energy models, and compare it with simulated data based on realistic assumptions. We perform a Fisher matrix analysis, in order to estimate the expected constraints on the parameters of the models. We find that there are interesting prospects for constraining the parameters of non-standard dark energy models and for discriminating among competing candidates.
A cyclic time-dependent Markov process to model daily patterns in wind turbine power production
Scholz, Teresa; Estanqueiro, Ana
2013-01-01
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...
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)
2014-03-14
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.
2012-06-01
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.
Mark W. Coffey
2008-12-09
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.
Fourier series and periodicity
Donal F. Connon
2014-12-07
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.
Kalueff, Allan V.
adaptation, computer software, or by similar or dissimilar methodology now known or hereafter developed + Business Media made a renewed commitment to this series. The new program will focus on methods
Kalueff, Allan V.
analysis. Use in connection with any form of information storage and retrieval, electronic adaptation Science + Business Media made a renewed commitment to this series. The new program will focus on methods
A multiscale MDCT image-based breathing lung model with time-varying regional ventilation
Yin, Youbing, E-mail: youbing-yin@uiowa.edu [Department of Mechanical and Industrial Engineering, The University of Iowa, Iowa City, IA 52242 (United States) [Department of Mechanical and Industrial Engineering, The University of Iowa, Iowa City, IA 52242 (United States); IIHR-Hydroscience and Engineering, The University of Iowa, Iowa City, IA 52242 (United States); Department of Radiology, The University of Iowa, Iowa City, IA 52242 (United States); Choi, Jiwoong, E-mail: jiwoong-choi@uiowa.edu [Department of Mechanical and Industrial Engineering, The University of Iowa, Iowa City, IA 52242 (United States) [Department of Mechanical and Industrial Engineering, The University of Iowa, Iowa City, IA 52242 (United States); IIHR-Hydroscience and Engineering, The University of Iowa, Iowa City, IA 52242 (United States); Hoffman, Eric A., E-mail: eric-hoffman@uiowa.edu [Department of Radiology, The University of Iowa, Iowa City, IA 52242 (United States); Department of Biomedical Engineering, The University of Iowa, Iowa City, IA 52242 (United States); Department of Internal Medicine, The University of Iowa, Iowa City, IA 52242 (United States); Tawhai, Merryn H., E-mail: m.tawhai@auckland.ac.nz [Auckland Bioengineering Institute, The University of Auckland, Auckland (New Zealand); Lin, Ching-Long, E-mail: ching-long-lin@uiowa.edu [Department of Mechanical and Industrial Engineering, The University of Iowa, Iowa City, IA 52242 (United States) [Department of Mechanical and Industrial Engineering, The University of Iowa, Iowa City, IA 52242 (United States); IIHR-Hydroscience and Engineering, The University of Iowa, Iowa City, IA 52242 (United States)
2013-07-01
A novel algorithm is presented that links local structural variables (regional ventilation and deforming central airways) to global function (total lung volume) in the lung over three imaged lung volumes, to derive a breathing lung model for computational fluid dynamics simulation. The algorithm constitutes the core of an integrative, image-based computational framework for subject-specific simulation of the breathing lung. For the first time, the algorithm is applied to three multi-detector row computed tomography (MDCT) volumetric lung images of the same individual. A key technique in linking global and local variables over multiple images is an in-house mass-preserving image registration method. Throughout breathing cycles, cubic interpolation is employed to ensure C{sub 1} continuity in constructing time-varying regional ventilation at the whole lung level, flow rate fractions exiting the terminal airways, and airway deformation. The imaged exit airway flow rate fractions are derived from regional ventilation with the aid of a three-dimensional (3D) and one-dimensional (1D) coupled airway tree that connects the airways to the alveolar tissue. An in-house parallel large-eddy simulation (LES) technique is adopted to capture turbulent-transitional-laminar flows in both normal and deep breathing conditions. The results obtained by the proposed algorithm when using three lung volume images are compared with those using only one or two volume images. The three-volume-based lung model produces physiologically-consistent time-varying pressure and ventilation distribution. The one-volume-based lung model under-predicts pressure drop and yields un-physiological lobar ventilation. The two-volume-based model can account for airway deformation and non-uniform regional ventilation to some extent, but does not capture the non-linear features of the lung.
Pathobiology Department Seminar Series COMPARATIVE PATHOBIOLOGY SEMINAR SERIES
Alpay, S. Pamir
. Bushmich) Senior Director of Investigative Pathology Drug Safety Research & Development Pfizer, Inc "TissuePathobiology Department Seminar Series COMPARATIVE PATHOBIOLOGY SEMINAR SERIES Thursdays, 11:00 A
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)
2013-09-01
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
2014-01-01
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.
A late time accelerated FRW model with scalar and vector fields via Noether symmetry
Babak Vakili
2014-10-22
We study the evolution of a three-dimensional minisuperspace cosmological model by the Noether symmetry approach. The phase space variables turn out to correspond to the scale factor of a flat Friedmann-Robertson-Walker (FRW) model, a scalar field with potential function $V(\\phi)$ with which the gravity part of the action is minimally coupled and a vector field of its kinetic energy is coupled with the scalar field by a coupling function $f(\\phi)$. Then, the Noether symmetry of such a cosmological model is investigated by utilizing the behavior of the corresponding Lagrangian under the infinitesimal generator of the desired symmetry. We explicitly calculate the form of the coupling function between the scalar and the vector fields and also the scalar field potential function for which such symmetry exists. Finally, by means of the corresponding Noether current, we integrate the equations of motion and obtain exact solutions for the scale factor, scalar and vector fields. It is shown that the resulting cosmology is an accelerated expansion universe for which its expansion is due to the presence of the vector field in the early times, while the scalar field is responsible of its late time expansion.
The shortest time and/or the shortest path strategies in a CA FF pedestrian dynamics model
Ekaterina Kirik; Tat'yana Yurgel'yan; Dmitriy Krouglov
2009-06-23
This paper deals with a mathematical model of a pedestrian movement. A stochastic cellular automata (CA) approach is used here. The Floor Field (FF) model is a basis model. FF models imply that virtual people follow the shortest path strategy. But people are followed by a strategy of the shortest time as well. This paper is focused on how to mathematically formalize and implement to a model these features of the pedestrian movement. Some results of a simulation are presented.
Time-dependent modeling of radiative processes in hot magnetized plasmas
Indrek Vurm; Juri Poutanen
2009-03-03
Numerical simulations of radiative processes in magnetized compact sources such as hot accretion disks around black holes, relativistic jets in active galaxies and gamma-ray bursts are complicated because the particle and photon distributions span many orders of magnitude in energy, they also strongly depend on each other, the radiative processes behave significantly differently depending on the energy regime, and finally due to the enormous difference in the time-scales of the processes. We have developed a novel computer code for the time-dependent simulations that overcomes these problems. The processes taken into account are Compton scattering, electron-positron pair production and annihilation, Coulomb scattering as well as synchrotron emission and absorption. No approximation has been made on the corresponding rates. For the first time, we solve coupled integro-differential kinetic equations for photons and electrons/positrons without any limitations on the photon and lepton energies. A numerical scheme is proposed to guarantee energy conservation when dealing with synchrotron processes in electron and photon equations. We apply the code to model non-thermal pair cascades in the blackbody radiation field, to study the synchrotron self-absorption as particle thermalization mechanism, and to simulate time evolution of stochastically heated pairs and corresponding synchrotron self-Compton photon spectra which might be responsible for the prompt emission of gamma-ray bursts. Good agreement with previous works is found in the parameter regimes where comparison is feasible, with the differences attributable to our improved treatment of the microphysics.
Similarity dark energy models in Bianchi type -I space-time
Ali, Ahmad T; Alzahrani, Abdulah K
2015-01-01
We investigate some new similarity solutions of anisotropic dark energy and perfect fluid in Bianchi type-I space-time. Three different time dependent skewness parameters along the spatial directions are introduced to quantify the deviation of pressure from isotropy. We consider the case when the dark energy is minimally coupled to the perfect fluid as well as direct interaction with it. The Lie symmetry generators that leave the equation invariant are identified and we generate an optimal system of one-dimensional subalgebras. Each element of the optimal system is used to reduce the partial differential equation to an ordinary differential equation which is further analyzed. We solve the Einstein field equations, described by a system of non-linear partial differential equations (NLPDEs), by using the Lie point symmetry analysis method. The geometrical and kinematical features of the models and the behavior of the anisotropy of dark energy, are examined in detail.
Mark A. Meadows
2006-03-31
Injection of carbon dioxide (CO2) into subsurface aquifers for geologic storage/sequestration, and into subsurface hydrocarbon reservoirs for enhanced oil recovery, has become an important topic to the nation because of growing concerns related to global warming and energy security. In this project we developed new ways to predict and quantify the effects of CO2 on seismic data recorded over porous reservoir/aquifer rock systems. This effort involved the research and development of new technology to: (1) Quantitatively model the rock physics effects of CO2 injection in porous saline and oil/brine reservoirs (both miscible and immiscible). (2) Quantitatively model the seismic response to CO2 injection (both miscible and immiscible) from well logs (1D). (3) Perform quantitative inversions of time-lapse 4D seismic data to estimate injected CO2 distributions within subsurface reservoirs and aquifers. This work has resulted in an improved ability to remotely monitor the injected CO2 for safe storage and enhanced hydrocarbon recovery, predict the effects of CO2 on time-lapse seismic data, and estimate injected CO2 saturation distributions in subsurface aquifers/reservoirs. We applied our inversion methodology to a 3D time-lapse seismic dataset from the Sleipner CO2 sequestration project, Norwegian North Sea. We measured changes in the seismic amplitude and traveltime at the top of the Sleipner sandstone reservoir and used these time-lapse seismic attributes in the inversion. Maps of CO2 thickness and its standard deviation were generated for the topmost layer. From this information, we estimated that 7.4% of the total CO2 injected over a five-year period had reached the top of the reservoir. This inversion approach could also be applied to the remaining levels within the anomalous zone to obtain an estimate of the total CO2 injected.
Stringy models of modified gravity: space-time defects and structure formation
Mavromatos, Nick E.; Sakellariadou, Mairi; Yusaf, Muhammad Furqaan, E-mail: nikolaos.mavromatos@kcl.ac.uk, E-mail: mairi.sakellariadou@kcl.ac.uk, E-mail: muhammad.yusaf@kcl.ac.uk [King's College London, Department of Physics, Strand, London WC2R 2LS (United Kingdom)
2013-03-01
Starting from microscopic models of space-time foam, based on brane universes propagating in bulk space-times populated by D0-brane defects (''D-particles''), we arrive at effective actions used by a low-energy observer on the brane world to describe his/her observations of the Universe. These actions include, apart from the metric tensor field, also scalar (dilaton) and vector fields, the latter describing the interactions of low-energy matter on the brane world with the recoiling point-like space-time defect (D-particle). The vector field is proportional to the recoil velocity of the D-particle and as such it satisfies a certain constraint. The vector breaks locally Lorentz invariance, which however is assumed to be conserved on average in a space-time foam situation, involving the interaction of matter with populations of D-particle defects. In this paper we clarify the role of fluctuations of the vector field on structure formation and galactic growth. In particular we demonstrate that, already at the end of the radiation era, the (constrained) vector field associated with the recoil of the defects provides the seeds for a growing mode in the evolution of the Universe. Such a growing mode survives during the matter dominated era, provided the variance of the D-particle recoil velocities on the brane is larger than a critical value. We note that in this model, as a result of specific properties of D-brane dynamics in the bulk, there is no issue of overclosing the brane Universe for large defect densities. Thus, in these models, the presence of defects may be associated with large-structure formation. Although our string inspired models do have (conventional, from a particle physics point of view) dark matter components, nevertheless it is interesting that the role of ''extra'' dark matter is also provided by the population of massive defects. This is consistent with the weakly interacting character of the D-particle defects, which predominantly interact only gravitationally.
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
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)
2013-01-01
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.
Model based approach to UXO imaging using the time domain electromagnetic method
Lavely, E.M.
1999-04-01
Time domain electromagnetic (TDEM) sensors have emerged as a field-worthy technology for UXO detection in a variety of geological and environmental settings. This success has been achieved with commercial equipment that was not optimized for UXO detection and discrimination. The TDEM response displays a rich spatial and temporal behavior which is not currently utilized. Therefore, in this paper the author describes a research program for enhancing the effectiveness of the TDEM method for UXO detection and imaging. Fundamental research is required in at least three major areas: (a) model based imaging capability i.e. the forward and inverse problem, (b) detector modeling and instrument design, and (c) target recognition and discrimination algorithms. These research problems are coupled and demand a unified treatment. For example: (1) the inverse solution depends on solution of the forward problem and knowledge of the instrument response; (2) instrument design with improved diagnostic power requires forward and inverse modeling capability; and (3) improved target recognition algorithms (such as neural nets) must be trained with data collected from the new instrument and with synthetic data computed using the forward model. Further, the design of the appropriate input and output layers of the net will be informed by the results of the forward and inverse modeling. A more fully developed model of the TDEM response would enable the joint inversion of data collected from multiple sensors (e.g., TDEM sensors and magnetometers). Finally, the author suggests that a complementary approach to joint inversions is the statistical recombination of data using principal component analysis. The decomposition into principal components is useful since the first principal component contains those features that are most strongly correlated from image to image.
Models of the Time Variability of BHC: Light Curves, PSD, Lags
Demosthenes Kazanas
2000-01-13
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.
Leptogenesis in $E_6 \\times U(1)_A$ SUSY GUT model
Ishihara, Takuya; Takegawa, Mao; Yamanaka, Masato
2015-01-01
We study the thermal leptogenesis in the $E_6\\times U(1)_A$ SUSY GUT model in which realistic masses and mixings of quarks and leptons can be realized. We show that the sufficient baryon number can be produced by the leptogenesis in the model, in which the mass parameter of the lightest right-handed neutrino is predicted to be smaller than $10^8$ GeV. The essential point is that the mass of the lightest right-handed neutrino can be enhanced in the model because it has a lot of mass terms whose mass parameters are predicted to be the same order of magnitude which is smaller than $10^8$ GeV. We show that O(10) enhancement for the lightest right-handed neutrino mass is sufficient for the observed baryon asymmetry. Note that such mass enhancements do not change the predictions of neutrino masses and mixings at the low energy scale in the $E_6$ model which has six right-handed neutrinos. In the calculation, we include the effects of supersymmetry and flavor in final states of the right-handed neutrino decay. We sh...
Liberzon, Daniel
International Conference on FormalInternational Conference on Formal ModellingModelling andand, SwedenFORMATS 2005, Uppsala, Sweden #12;International Conference on FormalInternational Conference on the specification language Interface to Theorem Provers Simulator Model checking #12;International Conference
Long-time evolution of models of aeolian sand dune fields: Influence of dune formation and collision
Glasner, Karl B.
Long-time evolution of models of aeolian sand dune fields: Influence of dune formation December 2008 Accepted 6 February 2009 Available online xxxx Keywords: Sand dune Dune field Dune field model Dune collision Coarsening Coalescence Theoretical models which approximate individual sand dunes
Author's personal copy Long-time evolution of models of aeolian sand dune elds: In uence of dune
Byrne, Shane
Author's personal copy Long-time evolution of models of aeolian sand dune elds: In uence of dune December 2008 Accepted 6 February 2009 Available online 20 February 2009 Keywords: Sand dune Dune eld Dune eld model Dune collision Coarsening Coalescence Theoretical models which approximate individual sand
Scheichl, Robert
2013-01-01
shed light on the rich phenomenology of both the original and extended adaptive voter models, includingRogers, T. C. and Gross, T. (2013) Consensus time and conformity in the adaptive voter model in the adaptive voter model Tim Rogers Centre for Networks and Collective Behaviour, Department of Mathematical
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
2015-02-09
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
Multi-fluid transport code modeling of time-dependent recycling in ELMy H-mode
Pigarov, A. Yu.; Krasheninnikov, S. I.; Hollmann, E. M.; Rognlien, T. D.; Lasnier, C. J.; Unterberg, E.
2014-06-15
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.; Krasheninnikov, S. I.; Rognlien, T. D.; Hollmann, E. M.; Lasnier, C. J.; Unterberg, Ezekial A
2014-01-01
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.
Kidon, Lyran; Rabani, Eran
2015-01-01
The generalized quantum master equation provides a powerful tool to describe the dynamics in quantum impurity models driven away from equilibrium. Two complementary approaches, one based on Nakajima--Zwanzig--Mori time-convolution (TC) and the other on the Tokuyama--Mori time-convolutionless (TCL) formulations provide a starting point to describe the time-evolution of the reduced density matrix. A key in both approaches is to obtain the so called "memory kernel" or "generator", going beyond second or fourth order perturbation techniques. While numerically converged techniques are available for the TC memory kernel, the canonical approach to obtain the TCL generator is based on inverting a super-operator in the \\emph{full} Hilbert space, which is difficult to perform and thus, all applications of the TCL approach rely on a perturbative scheme of some sort. Here, the TCL generator is expressed using a reduced system propagator which can be obtained from system observables alone and requires the calculation of s...
Energy Management Webinar Series
Broader source: Energy.gov [DOE]
Boost your knowledge on how to implement an energy management system through this four-part webinar series from the Superior Energy Performance program. Each webinar introduces various elements of the ISO 50001 energy management standard—based on the Plan-Do-Check-Act approach—and the associated steps of DOE's eGuide for ISO 50001 software tool.
Klein, Ophir
Bay Area Global Health Seminar Series 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
Stoltz, Brian M.
Bioengineering Lecture Series Refreshments will be served at 3:40 pm in the lobby BELS contact Sang Yup Lee KAIST mbel.kaist.ac.kr/lab/family/professor.html Distinguished Professor of Bioengineering-amines, and biopolymers will be described. Co-sponsored by the Bioengineering Department and the Resnick Institute #12;
Goulias, Kostas; Janelle, Donald G.
2006-01-01
GPS Tracking and Time-Geography Applications for Activityevents/meetings/time-geography/ Center for SpatiallyGPS Tracking and Time Geography ii FHWA Peer Exchange and
Time-Dependent Modeling of Gamma-ray Flares in Blazar PKS1510-089
Saito, Shinya; Tanaka, Yasuyuki; Takahashi, Tadayuki; Sikora, Marek; Moderski, Rafal
2015-01-01
Here we present a new approach for constraining luminous blazars, incorporating fully time-dependent and self-consistent modeling of bright gamma-ray flares of PKS1510-089 resolved with Fermi-LAT, in the framework of the internal shock scenario. The results of our modeling imply the location of the gamma-ray flaring zone outside of the broad-line region, namely around 0.3pc from the core for a free-expanding jet with the opening angle Gamma, \\theta_\\mathrm{jet} \\simeq 1 (where Gamma is the jet bulk Lorentz factor), up to \\simeq 3pc for a collimated outflow with Gamma, \\theta_\\mathrm{jet} \\simeq 0.1. Moreover, under the Gamma, \\theta_\\mathrm{jet} \\simeq 1 condition, our modeling indicates the maximum efficiency of the jet production during the flares, with the total jet energy flux strongly dominated by protons and exceeding the available accretion power in the source. This is in contrast to the quiescence states of the blazar, characterized by lower jet kinetic power and an approximate energy equipartition be...
Briceno, Luis Diego [Colorado State University, Fort Collins; Khemka, Bhavesh [Colorado State University, Fort Collins; Siegel, Howard Jay [Colorado State University, Fort Collins; Maciejewski, Anthony A [ORNL; Groer, Christopher S [ORNL; Koenig, Gregory A [ORNL; Okonski, Gene D [ORNL; Poole, Stephen W [ORNL
2011-01-01
This study considers a heterogeneous computing system and corresponding workload being investigated by the Extreme Scale Systems Center (ESSC) at Oak Ridge National Laboratory (ORNL). The ESSC is part of a collaborative effort between the Department of Energy (DOE) and the Department of Defense (DoD) to deliver research, tools, software, and technologies that can be integrated, deployed, and used in both DOE and DoD environments. The heterogeneous system and workload described here are representative of a prototypical computing environment being studied as part of this collaboration. Each task can exhibit a time-varying importance or utility to the overall enterprise. In this system, an arriving task has an associated priority and precedence. The priority is used to describe the importance of a task, and precedence is used to describe how soon the task must be executed. These two metrics are combined to create a utility function curve that indicates how valuable it is for the system to complete a task at any given moment. This research focuses on using time-utility functions to generate a metric that can be used to compare the performance of different resource schedulers in a heterogeneous computing system. The contributions of this paper are: (a) a mathematical model of a heterogeneous computing system where tasks arrive dynamically and need to be assigned based on their priority, precedence, utility characteristic class, and task execution type, (b) the use of priority and precedence to generate time-utility functions that describe the value a task has at any given time, (c) the derivation of a metric based on the total utility gained from completing tasks to measure the performance of the computing environment, and (d) a comparison of the performance of resource allocation heuristics in this environment.
Fernandez, Thomas
Genetic Programming Dilip P. Ahalpara Institute for Plasma Research, Near Indira Bridge, Gandhinagar
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
Cohen, Jonathan
techniques. We demonstrate the system on a model of a coal-fired power plant composed of more than 15 million such techniques. Choosing a 15-million-triangle model of a coal-fired electric power plant (Image 1) as our (Graphics data structures), I.3.7 Three-Dimensional Graphics and Realism (Virtual reality), J.2 Physical
Optical models of the big bang and non-trivial space-time metrics based on metamaterials
Igor I. Smolyaninov
2009-08-17
Optics of metamaterials is shown to provide interesting table top models of many non-trivial space-time metrics. The range of possibilities is broader than the one allowed in classical general relativity. For example, extraordinary waves in indefinite metamaterials experience an effective metric, which is formally equivalent to the "two times physics" model in 2+2 dimensions. An optical analogue of a "big bang" event is presented during which a (2+1) Minkowski space-time is created together with large number of particles populating this space-time. Such metamaterial models enable experimental exploration of the metric phase transitions to and from the Minkowski space-time as a function of temperature and/or light frequency.
Climate Modeling and Function Fitting
Blais, Brian
Climate Modeling and Function Fitting Brown Bag Research Wednesday, October 26, 11 #12;Abstract In this seminar I hope to explore an approach to climate modeling to which I was just introduced, which focusses are those who are interested in any of the topics of time-series analysis, climate modeling , spectrum
Henrik Stenlund
2012-04-24
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.
Numerical wind speed simulation model
Ramsdell, J.V.; Athey, G.F.; Ballinger, M.Y.
1981-09-01
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.
Shekhar, Ravi
2009-05-15
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...
UserCalc: a web-based Uranium Series Calculator for magma migration problems
Spiegelman, Marc W.
UserCalc: a web-based Uranium Series Calculator for magma migration problems M. Spiegelman Lamont. Measured departures from secular equilibrium in the Uranium-series decay chains provide important-series models. Introduction Radioactive decay chains such as the two Uranium series 238 U230 Th226 Ra and 235 U
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
Environmental Research Group 2015 Spring Seminar Series
:00 Estimating the Environmental Impacts of New Technologies Using Agent-Based Modeling Shelie Miller CenterEnvironmental Research Group 2015 Spring Seminar Series April 17, 2015 Gregg 320, 12:00 1 changes to a design will have the greatest influence on environmental performance at this crucial stage
Ahmad, Mushtaq
2005-07-27
models were created for all the buildings; the massless model with emphasis on the envelope using massless construction and typical values for system parameters and the advanced model with the inclusion of thermal mass and extensive as-built details...
Michael, Panayiotis Adamos
2015-01-01
in active databases: Model and implementation”. In VLDB,Bassam Islam, "Stack Database Model/View of Multimedia Data"implementing a fragmented database model of Spatio-Temporal
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: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantityBonneville Power AdministrationRobust,Field-effect Photovoltaics -7541 *ImpactScience of SignaturesSoft0 Soils Soil Series and
Time-dependent Radiation Transfer in the Internal Shock Model Scenario for Blazar Jets
Manasvita Joshi; Markus Boettcher
2010-11-13
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.
J. R. Morris
1995-11-10
A supersymmetric extension of the $U(1)\\times U(1)^{\\prime }$-Higgs bosonic superconducting cosmic string model is considered,and the constraints imposed upon such a model due to renormalizability, supersymmetry, and gauge invariance are examined. For a simple model with a single $U(1)$ chiral superfield and a single $% U(1)^{\\prime }$ chiral superfield, the Witten mechanism for bosonic superconductivity (giving rise to long range gauge fields outside of the string) does not exist. The simplest model that can accommodate the requisite interactions requires five chiral supermultiplets. This superconducting cosmic string solution is investigated.
-encounter-Bethe BEB model in which a simple expression for the optical-oscillator strength, based on the results from H, He, and H2, is employed in the ex- pression of the Bethe cross section. Both the BED and BEB
Bretherton, Chris
of required research on this subject. 1. Introduction Potential global warming caused by increasing greenhouse reduce or amplify a global warming projection. Figure 1. Schematic illustration of the solar and infrared discrepancy in the magnitude of the simulated global warming in different models. In response to a doubling
Hart, W.E.; Istrail, S. [Sandia National Labs., Albuquerque, NM (United States). Algorithms and Discrete Mathematics Dept.
1996-08-09
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.
Climate induced changes in benthic macrofauna--A non-linear model approach Karin Junker a,
Dippner, Joachim W.
Climate induced changes in benthic macrofauna--A non-linear model approach Karin Junker a, , Dusan macrofauna communities Climate indices Neural network Climate variability Time series forecasting Regime-nearest neighbours" (OPKNN) are applied to relate various climate indices to time series of biomass, abun- dance
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
Logistic Models with Time-Dependent Coefficients and Some of Their Applications
Raquel M. Lopez; Benjamin R. Morin; Sergei K. Suslov
2010-08-15
We discuss explicit solutions of the logistic model with variable parameters. Classical data on the sunflower seeds growth are revisited as a simple application of the logistic model with periodic coefficients. Some applications to related biological systems are briefly reviewed.
Fast History Matching of Time-Lapse Seismic and Production-Data for High Resolution Models
Rey Amaya, Alvaro
2012-10-19
Seismic data have been established as a valuable source of information for the construction of reservoir simulation models, most commonly for determination of the modeled geologic structure, and also for population of static petrophysical properties...
Applying the multivariate time-rescaling theorem to neural population models
Gerhard, Felipe
Statistical models of neural activity are integral to modern neuroscience. Recently interest has grown in modeling the spiking activity of populations of simultaneously recorded neurons to study the effects of correlations ...
Carney, Laurel H.
Binaural detection with narrowband and wideband reproducible noise maskers. IV. Models using (ITD) cues for the dichotic tone-in-noise detection task. Several models have been used to predict models cannot predict listeners' detection performance for reproducible-noise maskers without fitting
Yoshihito Kuno; Kenichi Kasamatsu; Yoshiro Takahashi; Ikuo Ichinose; Tetsuo Matsui
2015-06-05
Lattice gauge theory has provided a crucial non-perturbative method in studying canonical models in high-energy physics such as quantum chromodynamics. Among other models of lattice gauge theory, the lattice gauge-Higgs model is a quite important one because it describes wide variety of phenomena/models related to the Anderson-Higgs mechanism such as superconductivity, the standard model of particle physics, and inflation process of the early universe. In this paper, we first show that atomic description of the lattice gauge model allows us to explore real time dynamics of the gauge variables by using the Gross-Pitaevskii equations. Numerical simulations of the time development of an electric flux reveal some interesting characteristics of dynamical aspect of the model and determine its phase diagram. Next, to realize a quantum simulator of the U(1) lattice gauge-Higgs model on an optical lattice filled by cold atoms, we propose two feasible methods: (i) Wannier states in the excited bands and (ii) dipolar atoms in a multilayer optical lattice. We pay attentions to respect the constraint of Gauss's law and avoid nonlocal gauge interactions.
Moeller, M. P.; Urbanik, II, T.; Desrosiers, A. E.
1982-03-01
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.
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
Wu, Huan; Adler, Robert F.; Tian, Yudong; Huffman, George; Li, Hongyi; Wang, Jianjian
2014-04-09
A community land surface model, the Variable Infiltration Capacity (VIC) model, is coupled with a newly developed hierarchical dominant river tracing-based runoff-routing model to form the Dominant river tracing-Routing Integrated with VIC Environment (DRIVE) model system, which serves as the new core of the real-time Global Flood Monitoring System (GFMS). The GFMS uses real-time satellite-based precipitation to derive flood-monitoring parameters for the latitude-band 50{degree sign}N-50{degree sign}S at relatively high spatial (~12km) and temporal (3-hourly) resolution. Examples of model results for recent flood events are computed using the real-time GFMS (http://flood.umd.edu). To evaluate the accuracy of the new GFMS, the DRIVE model is run retrospectively for 15 years using both research-quality and real-time satellite precipitation products. Statistical results are slightly better for the research-quality input and significantly better for longer duration events (three-day events vs. one-day events). Basins with fewer dams tend to provide lower false alarm ratios. For events longer than three days in areas with few dams, the probability of detection is ~0.9 and the false alarm ratio is ~0.6. In general, these statistical results are better than those of the previous system. Streamflow was evaluated at 1,121 river gauges across the quasi-global domain. Validation using real-time precipitation across the tropics (30ºS-30ºN) gives positive daily Nash-Sutcliffe Coef?cients for 107 out of 375 (28%) stations with a mean of 0.19 and 51% of the same gauges at monthly scale with a mean of 0.33. There were poorer results in higher latitudes, probably due to larger errors in the satellite precipitation input.
Michael, Panayiotis Adamos
2015-01-01
Time Granularities in Databases, Data Mining, and Temporal3] D. Stott Parker. “Stream Data Analysis in Prolog”. In L.Conference on Innovative Data Systems Research (CIDR 2005),
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
2010-01-01
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
Thomson, Ty M. (Ty Matthew)
2008-01-01
Molecular signaling systems allow cells to sense and respond to environmental stimuli. Quantitative modeling can be a valuable tool for evaluating and extending our understanding of signaling systems. In particular, studies ...
Kamat, Vineet R.
Real-time drill monitoring and control using building information models augmented with 3D imaging and incorporating point cloud data obtained from 3D imaging technologies1 into the drilling process in was de bridge deck. Once the point clouds were processed, zones which are safe for drilling were automatically
Tentzeris, Manos
environments and standards (US, Europe, Asia) [2]. This paper presents for the first time the design, modeling, in this inductively coupled RFID antenna, the radiated energy is focused directionally in a dumbbell shape as shown is expected to achieve with RFID antennas in such a configuration. Paper is considered one of the best
Istrail, Sorin
Lattice and Off-Lattice Side Chain Models of Protein Folding: Linear Time Structure Prediction This paper considers the protein structure prediction problem for lattice and off-lattice protein folding tools for reasoning about protein folding in unrestricted continuous space through anal- ogy. This paper
Tafreshi, Hooman Vahedi
time. To the knowledge of the authors, there are no criteria for designing pleat shape and pleat count time S. Fotovati a , H. Vahedi Tafreshi a, , B. Pourdeyhimi b a Department of Mechanical and Nuclear geometry. The general consensus in designing pleated fibrous filters in industry is that a filter
Michael, Panayiotis Adamos
2015-01-01
a new model and architecture for data stream management”.Order Processing: A New Architecture for High- PerformanceDistributed Streamonas Architecture – and its Performance
Mathematical Modeling of the Stress-Strain-Time Behavior of Geosynthetics Using the Findley Equation
Horvath, John S.
......................................................................................................... 9 3.3 Portrayal of Creep-Test Data ............................................................................................................................... 2 Section 2 - Creep Models 2.1 Overview ..................................................................................................................................... 9 3.2 Description of Test Conditions
TCTL model-checking of Time Petri Nets Hanifa Boucheneb1
Paris-Sud XI, Université de
Verification of concurrent systems is a complex task that requires powerful models and efficient analysis tech- niques. Model checking is one of the most popular verification techniques of concurrent systems verification of properties of real-life systems. In this paper, we consider subscript TCTL for TPN (TPN
A Time-AverageModel of the RF PlasmaSheath Demetre J, Economou.3
Economou, Demetre J.
discharge. Quantities that affect the energy and/or directionality of bombarding ions include the sheath velocity. The sheath model was used to investigate the ion energy and flux on the electrodes of plasma plasma reactor models which consider transport and re- action phenomena along surfaces undergoing etching
Random polynomial-time attacks and Dolev-Yao models Mathieu Baudet
Doyen, Laurent
that under sufficient realistic assump- tions the extended models are equivalent to standard Dolev-Yao models by the the RNTL projects EVA and ProuvÂ´e, the ACI SÂ´ecuritÂ´e Informatique Rossignol, the ACI Cryptologie Psi-Robuste, and the ACI jeunes chercheurs "SÂ´ecuritÂ´e informatique, protocoles cryptographiques et dÂ´etection d
Modeling Time-Triggered Ethernet in SystemC/TLM for Virtual Prototyping of
Koutsoukos, Xenofon D.
, and has been used in many CPS domains, such as automotive, aerospace, and industrial process control platform model for design space exploration. We validate the model by comparing latency and jitter layer, the network/platform layer, and the physical layer [1]. The interactions within and across
Supervised Learning Based Model for Predicting Variability-Induced Timing Errors
Gupta, Rajesh
combat variations in hardware and workload by increasing conservative guardbanding that leads, for a given amount of guardband reduction. The proposed methodology enables a model-based rule method the robustness of our modeling methodology by considering various operating voltage and temperature corners. Our
Hickey, Barbara
river flow with errors of 520%. Furthermore, a more stringent test, when the model is run with tidal, Washington, a macrotidal estuary with a complex channel geometry. When the model is run with realistic winter-storm-level river flows, river- and ocean-density-driven exchanges are discernable but secondary
Comen, E; Mason, J; Kuhn, P; Nieva, J; Newton, P; Norton, L; Venkatappa, N; Jochelson, M
2014-06-01
Purpose: Traditionally, breast cancer metastasis is described as a process wherein cancer cells spread from the breast to multiple organ systems via hematogenous and lymphatic routes. Mapping organ specific patterns of cancer spread over time is essential to understanding metastatic progression. In order to better predict sites of metastases, here we demonstrate modeling of the patterned migration of metastasis. Methods: We reviewed the clinical history of 453 breast cancer patients from Memorial Sloan Kettering Cancer Center who were non-metastatic at diagnosis but developed metastasis over time. We used the variables of organ site of metastases as well as time to create a Markov chain model of metastasis. We illustrate the probabilities of metastasis occurring at a given anatomic site together with the probability of spread to additional sites. Results: Based on the clinical histories of 453 breast cancer patients who developed metastasis, we have learned (i) how to create the Markov transition matrix governing the probabilities of cancer progression from site to site; (ii) how to create a systemic network diagram governing disease progression modeled as a random walk on a directed graph; (iii) how to classify metastatic sites as ‘sponges’ that tend to only receive cancer cells or ‘spreaders’ that receive and release them; (iv) how to model the time-scales of disease progression as a Weibull probability distribution function; (v) how to perform Monte Carlo simulations of disease progression; and (vi) how to interpret disease progression as an entropy-increasing stochastic process. Conclusion: Based on our modeling, metastatic spread may follow predictable pathways. Mapping metastasis not simply by organ site, but by function as either a ‘spreader’ or ‘sponge’ fundamentally reframes our understanding of metastatic processes. This model serves as a novel platform from which we may integrate the evolving genomic landscape that drives cancer metastasis. PS-OC Trans-Network Project Grant Award for “Data Assimilation and ensemble statistical forecasting methods applied to the MSKCC longitudinal metastatic breast cancer cohort.”.
Rydberg series of calcium monofluoride : spectrum, structure, and dynamics
Kay, Jeffrey J
2007-01-01
This thesis summarizes progress toward the ultimate goal of building a complete structural and dynamical model for the CaF molecule. The quantum defects of the Rydberg series of the molecule, as well as their dependences ...
Born series and unitarity in noncommutative quantum mechanics
F. S. Bemfica; H. O. Girotti
2008-02-11
This paper is dedicated to present model independent results for noncommutative quantum mechanics. We determine sufficient conditions for the convergence of the Born series and, in the sequel, unitarity is proved in full generality.
Mountain, Christopher Eugene
1993-01-01
One application of travel time information explored in this thesis is freeway incident detection. It is vital to develop reliable methods for automatically detecting incidents to facilitate the quick response and removal of incidents before...
A biophysically-based neuromorphic model of spike rate- and timing-dependent plasticity
Rachmuth, Guy
Current advances in neuromorphic engineering have made it possible to emulate complex neuronal ion channel and intracellular ionic dynamics in real time using highly compact and power-efficient complementary metal-oxide- ...
Modeling real-time human-automation collaborative scheduling of unmanned vehicles
Clare, Andrew S
2013-01-01
Recent advances in autonomy have enabled a future vision of single operator control of multiple heterogeneous Unmanned Vehicles (UVs). Real-time scheduling for multiple UVs in uncertain environments will require the ...
Ramachandran, Arun
2006-08-16
A general framework for performance optimization of continuous-time OTA-C (Operational Transconductance Amplifier-Capacitor) filters is proposed. Efficient procedures for evaluating nonlinear distortion and noise valid for ...
Lawrence, Peter J.; Feddema, Johannes J.; Bonan, Gordon B.; Meehl, Gerald A.; O’ Neill, Brian C.; Oleson, Keith W.; Levis, Samuel; Lawrence, David M.; Kluzek, Erik; Lindsay, Keith
2012-05-01
To assess the climate impacts of historical and projected land cover change in the Community Climate System Model, version 4 (CCSM4), new time series of transient Community Land Model, version 4 (CLM4) plant functional ...
Veronica J. Rutledge
2013-01-01
The absence of industrial scale nuclear fuel reprocessing in the U.S. has precluded the necessary driver for developing the advanced simulation capability now prevalent in so many other countries. Thus, it is essential to model complex series of unit operations to simulate, understand, and predict inherent transient behavior and feedback loops. A capability of accurately simulating the dynamic behavior of advanced fuel cycle separation processes will provide substantial cost savings and many technical benefits. The specific fuel cycle separation process discussed in this report is the off-gas treatment system. The off-gas separation consists of a series of scrubbers and adsorption beds to capture constituents of interest. Dynamic models are being developed to simulate each unit operation involved so each unit operation can be used as a stand-alone model and in series with multiple others. Currently, an adsorption model has been developed within Multi-physics Object Oriented Simulation Environment (MOOSE) developed at the Idaho National Laboratory (INL). Off-gas Separation and REcoverY (OSPREY) models the adsorption of off-gas constituents for dispersed plug flow in a packed bed under non-isothermal and non-isobaric conditions. Inputs to the model include gas, sorbent, and column properties, equilibrium and kinetic data, and inlet conditions. The simulation outputs component concentrations along the column length as a function of time from which breakthrough data is obtained. The breakthrough data can be used to determine bed capacity, which in turn can be used to size columns. It also outputs temperature along the column length as a function of time and pressure drop along the column length. Experimental data and parameters were input into the adsorption model to develop models specific for krypton adsorption. The same can be done for iodine, xenon, and tritium. The model will be validated with experimental breakthrough curves. Customers will be given access to OSPREY to used and evaluate the model.
Spectral modeling of two incline cylinders with validation in the time domain
Oswalt, Aaron Jacob
1999-01-01
Function. 2. 3 Two Input/Single Output System . 2. 4 Conditioned Spectral Analysis. 2. 5 Partial Coherence 2. 6 Formulation of the Nonlinear Model 2. 6. 1 Nonlinear System Form . . 2. 6. 2 Reverse Dynamic Nonlinear System. 2. 6. 3 SDOF Nonlinear...) . . . . . . . . . . . . . . . 15 5 SVSO model for two-input system used to remove the correlated effects of xr(r) . . 18 6 Conditioned spectral model with noise for a two-input / single-output system . . . . . . 20 7 Classification of interference regions for inline...
Modeling and centralization of strategic inventory for repairable and long lead-time spare parts
Duncan, Tyeliah Elaine
2011-01-01
This thesis develops an optimal inventory model for repairable and long leadtime spare parts for an Engine overhaul business. In addition, it presents a business case for centralization of inventory. Pratt & Whitney purchased ...
Time-evolving acoustic propagation modeling in a complex ocean environment
Colin, M. E. G. D.
During naval operations, sonar performance estimates often need to be computed in-situ with limited environmental information. This calls for the use of fast acoustic propagation models. Many naval operations are carried ...
Real-time detection of malicious network activity using stochastic models
Jung, Jaeyeon, Ph. D. Massachusetts Institute of Technology
2006-01-01
This dissertation develops approaches to rapidly detect malicious network traffic including packets sent by portscanners and network worms. The main hypothesis is that stochastic models capturing a host's particular ...
Lapp, Tiffany Rae, 1979-
2004-01-01
This thesis presents the design and implementation of a model predictive control based trajectory optimization method for Nap-of-the-Earth (NOE) flight. A NOE trajectory reference is generated over a subspace of the terrain. ...
Space-Time Models based on Random Fields with Local Interactions
Dionissios T. Hristopulos; Ivi C. Tsantili
2015-03-06
The analysis of space-time data from complex, real-life phenomena requires the use of flexible and physically motivated covariance functions. In most cases, it is not possible to explicitly solve the equations of motion for the fields or the respective covariance functions. In the statistical literature, covariance functions are often based on mathematical constructions. We propose deriving space-time covariance functions by solving "effective equations of motion", which can be used as statistical representations of systems with diffusive behavior. In particular, we propose using the linear response theory to formulate space-time covariance functions based on an equilibrium effective Hamiltonian. The effective space-time dynamics are then generated by a stochastic perturbation around the equilibrium point of the classical field Hamiltonian leading to an associated Langevin equation. We employ a Hamiltonian which extends the classical Gaussian field theory by including a curvature term and leads to a diffusive Langevin equation. Finally, we derive new forms of space-time covariance functions.
Modeling the Coastal Ocean over a Time Period of Several April 8, 2008
Frénod, Emmanuel
, lost objects or oil spill over long periods of time in near coastal ocean areas. Such methods would. The final target of this program is to develop methods to forecast the drift of things like con- tainers be of interest for services in charge of maritime safety, environmental studies or pollution impact assessment
Use of a Levy Distribution for Modeling Best Case Execution Time Variation
Chamberlain, Roger
or the maximal vari- ation might be a futile task, we take a different approach, focusing in- stead on the best. Chamberlain receive income based on the license of technology by the university to Exegy, Inc. A. Horv examples of successive execution times that are not Gaussian with any high probability. Other phenomena
Control-oriented time-varying input-delayed temperature model for SI engine exhaust catalyst
pollutants resulting from the combustion: hydrocarbons HC, carbon monoxide CO and nitrogen oxide NOx. Yet to reach high level of pollutant conversion. Classically, warm-up strategies exploit combustion timing shifting [7], which usually leads to combustion efficiency degradation. Indeed, by appropriately modifying
A Model for Real-Time Computation in Generic Neural Microcircuits
Maass, Wolfgang
from a rapidly changing environment can be processed by stereotypical recurrent circuits of integrate-dependent construction of neural circuits. Instead it is based on principles of high dimensional dynamical systems recurrent circuit (or other medium) with a continuous input stream %¡'&(¥ , and looks at a later time §0
Event-Oriented Data Models and Temporal Queries in Transaction-Time Databases
Zaniolo, Carlo
on SQL-compliant DBMS. More recently however, there has been significant interest and progress on event standards, a first interesting development is that several DBMS vendors are proposing new specs in the past (as opposed to the human recreated history of a valid-time database). Furthermore, for web doc
Kalman Filter in the Real Time URBIS model Date June 2010
Vuik, Kees
Keywords NOx, Real Time URBIS, Uncertainty, Rijnmond, Kalman filter, Screening process Target Master Thesis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 45 #12;6 / 120 6 Kalman filter on all emission sources 47 6.1 Introduction emission source . . . . . . . . . . . . . . . . . . . . 69 9.3 Annual mean of the uncertainty without
Real-Time Implementation of an Online Model Predictive Control for IPMSM Using Parallel
Paderborn, Universität
computational cost and the associated long control cycle time. This makes MPC unattractive for processes parameters are calculated only once during the de- sign process. Thus the control dynamics are only Control (MPC) is more effective. MPCs are based on the solution of a dynamic optimization problem
A Real-Time Capable Many-Core Model Stefan Metzlaff, Jorg Mische, Theo Ungerer
Ungerer, Theo
of Computer Science University of Augsburg Augsburg, Germany {metzlaff architectures. We think that the usage of processors with high core numbers will also emerge in embedded real for embedded real-time systems: predictability, performance and energy efficiency. At first we enunciate a set
PHYSICAL REVIEW E 88, 062910 (2013) Nonlinear time reversal of classical waves: Experiment and model
Anlage, Steven
2013-01-01
Department of Electrical and Computer Engineering, University of Maryland, College Park, Maryland 20742 interpretation of the experimental results. DOI: 10.1103/PhysRevE.88.062910 PACS number(s): 05.45.Vx, 42.25.Dd, allowing a single wave-absorbing receiver to record a single time-reversible sona signal over a long
Processor Sharing Queueing Models of Mixed Scheduling Disciplines for Time Shared Systems
Kleinrock, Leonard
design of discriminatory treatment among jobs (in favor of short jobs and against long iobs) in time Machinery, Inc. General permission to republish, but not for profit, all or part of this material is granted privileges were granted by permission of the Association for Computing Machinery. Authors' address
Capozziello, S.; Cardone, V.F.; Funaro, M.; Andreon, S.
2004-12-15
An impressive amount of different astrophysical data converges towards the picture of a spatially flat Universe undergoing today a phase of accelerated expansion. The nature of the dark energy dominating the energy content of the Universe is still unknown, and a lot of different scenarios are viable candidates to explain cosmic acceleration. Most of the methods employed to test these cosmological models are essentially based on distance measurements to a particular class of objects. A different method, based on the lookback time to galaxy clusters and the age of the Universe, is used here. In particular, we constrain the characterizing parameters of three classes of dark energy cosmological models to see whether they are in agreement with this kind of data, based on time measurements rather than distance observations.
Incorporation of a time-dependent thermodynamic model and a radiation
Salvaggio, Carl
the phenomenology commonly observed by high-resolution thermal infrared sensors to a point where the model can be used as a research tool to evaluate the limitations in our understanding of the thermal infrared into infrared three-dimensional synthetic image generation John R. Schott, MEMBER SPIE Rolando Raqueno Carl
Modeling and Generation of Space-Time Correlated Signals for Sensor Network Fields
Rossi, Michele
and recovery in Wireless Sensor Networks (WSNs) have utilized the spatio-temporal statistics of real world signals in order to achieve good performance in terms of energy savings and improved signal reconstruction model is accurate in reproducing the signal statistics of interest. I. INTRODUCTION AND RELATED WORK
AN RT-UML MODEL FOR BUILDING FASTER-THAN-REAL-TIME SIMULATORS
Katsaros, Panagiotis
demanding, requiring a consistent specification for developing such systems. This paper presents guidelines, obtaining and storing system and the model data during the auditing interval, and auditing, that is, examining a) if the system has been #12;modified during the last auditing interval (system reformations), b
Discrete-Time Model of an IPMSM Based on Variational Integrators
Noé, Reinhold
as automobile traction drives for electric and hybrid electric vehicles. Since motor control is commonly. INTRODUCTION Interior permanent magnet synchronous motors (IPMSM) provide a high efficiency besides very high motor models are needed to design appropriate control algorithms based on a deep insight into the motor
Right on time: Measuring Kuramoto model coupling from a survey of wristwatches
Reginald D. Smith
2010-03-25
Using a survey of wristwatch synchronization from a randomly selected group of independent volunteers, one can model the system as a Kuramoto-type coupled oscillator network. Based on the phase data, both the order parameter and an estimated value of the coupling is derived and the possibilities for similar research to deduce topology from dynamics are discussed.
Modeling Resource-Aware Virtualized Applications for the Cloud in Real-Time ABS
Johnsen, Einar Broch
S or increase cost. Virtualized applications need to manage their acquisition of resources. In this paper available on de- mand. When its work load increases, the application must decide whether to reduce Qo of the Montage system then demonstrates how to use such a model to compare resource manage- ment strategies
DOE Public Access Gateway for Energy & Science Beta (PAGES Beta)
Pusateri, Elise N.; Morris, Heidi E.; Nelson, Eric M.; Ji, Wei
2015-08-04
Electromagnetic pulse (EMP) events produce low-energy conduction electrons from Compton electron or photoelectron ionizations with air. It is important to understand how conduction electrons interact with air in order to accurately predict EMP evolution and propagation. An electron swarm model can be used to monitor the time evolution of conduction electrons in an environment characterized by electric field and pressure. Here a swarm model is developed that is based on the coupled ordinary differential equations (ODEs) described by Higgins et al. (1973), hereinafter HLO. The ODEs characterize the swarm electric field, electron temperature, electron number density, and drift velocity. Importantmore »swarm parameters, the momentum transfer collision frequency, energy transfer collision frequency, and ionization rate, are calculated and compared to the previously reported fitted functions given in HLO. These swarm parameters are found using BOLSIG+, a two term Boltzmann solver developed by Hagelaar and Pitchford (2005), which utilizes updated cross sections from the LXcat website created by Pancheshnyi et al. (2012). We validate the swarm model by comparing to experimental effective ionization coefficient data in Dutton (1975) and drift velocity data in Ruiz-Vargas et al. (2010). In addition, we report on electron equilibrium temperatures and times for a uniform electric field of 1 StatV/cm for atmospheric heights from 0 to 40 km. We show that the equilibrium temperature and time are sensitive to the modifications in the collision frequencies and ionization rate based on the updated electron interaction cross sections.« less
Power Series Power series are one of the most useful type of series in analysis. For example,
Hunter, John K.
Chapter 6 Power Series Power series are one of the most useful type of series in analysis functions (and many other less familiar functions). 6.1. Introduction A power series (centered at 0 coefficients. If all but finitely many of the an are zero, then the power series is a polynomial function
Li, Z.
1998-01-12
A seaport simulation model, PORTSIM, has been developed for the Department of Defense (DOD) at Argonne National Laboratory. PORTSIM simulates the detailed processes of cargo loading and unloading in a seaport and provides throughput capability, resource utilization, and other important information on the bottlenecks in a seaport operation, which are crucial data in determining troop and equipment deployment capability. There are two key problems to solve in developing the HLA-compliant PORTSIM model. The first is the cargo object ownership transfer problem. In PORTSIM, cargo items, e.g. vehicles, containers, and pallets, are objects having asset attributes. Cargo comes to a seaport for loading or unloading. The ownership of a cargo object transfers from its carrier to the port and then from the port to a new carrier. Each owner of the cargo object is responsible for publishing and updating the attributes of the cargo object when it has the ownership. This creates a unique situation in developing the PORTSIM federate object model, that is, the ownership of the object instead of the attributes needs to be changed in handling the cargo object in the PORTSIM federate. The ownership management service provided by the current RTI does not directly address this issue. The second is the time management issue. PORTSIM is an event-driven simulation that models seaport operations over time. To make PORTSIM HLA compliant, time management must be addressed to allow for synchronization with other simulation models. This paper attempts to address these two issues and methodologies developed for solving these two problems.
Texas at Austin. University of
Stopping supersonic oxygen with a series of pulsed electromagnetic coils: A molecular coilgun, using a series of pulsed electromagnetic coils. A series of coils is fired in a timed sequence to bring in some experiments by interactions with pulsed electric fields Stark decelerator 46 , by inter- actions
Stochastic Model Based Proxy Servers Architecture for VoD to Achieve Reduced Client Waiting Time
Nair, T R GopalaKrishnan
2010-01-01
In a video on demand system, the main video repository may be far away from the user and generally has limited streaming capacities. Since a high quality video's size is huge, it requires high bandwidth for streaming over the internet. In order to achieve a higher video hit ratio, reduced client waiting time, distributed server's architecture can be used, in which multiple local servers are placed close to clients and, based on their regional demands video contents are cached dynamically from the main server. As the cost of proxy server is decreasing and demand for reduced waiting time is increasing day by day, newer architectures are explored, innovative schemes are arrived at. In this paper we present novel 3 layer architecture, includes main multimedia server, a Tracker and Proxy servers. This architecture targets to optimize the client waiting time. We also propose an efficient prefix caching and load sharing algorithm at the proxy server to allocate the cache according to regional popularity of the video...
Time-domain Simulation of Multibody Floating Systems based on State-space Modeling Technology
Yu, Xiaochuan
2012-10-19
operation. Hong, et al. (2005) applied the Higher-Order Boundary Element Method (HOBEM) to analyze the motions and drift force of side-by-side moored multiple vessels, such as Floating Production Storage and Offloading (FPSO) unit for Liquid Natural Gas... associated with the small gap between two barges, which is fundamental for understanding FPSO-shuttle tanker interactions during side-by- side offloading. The test results and comparisons with numerical model predictions were used to optimize future test...
A Spatio-Temporal Point Process Model for Ambulance Demand
Woodard, Dawn B.
(EMS) managers need accurate demand estimates to mini- mize response times to emergencies and keep. Several studies have modeled aggregate ambulance demand as a temporal process. Channouf et al. (2007) use by combining a dynamic latent factor structure with integer time series models. Other aggregate demand studies
Mellor, David Hugh
2001-01-01
The article shows how McTaggart’s distinction between A- and B-series ways of locating events in time prompted and enabled the twentieth century’s most important advances in the philosophy of time. It argues that, even if the B-series represents...
Mechanical Engineering Department Seminar Series
Awtar, Shorya
Mechanical Engineering Department Seminar Series Mechanics of a Mosquito Professor of Mechanical Engineering Clemson University Tuesday, March 24, 2015 4:00 5:00 pm Room 1303 EECS Abstract: The mechanics of a fascicle insertion into the skin
Solar Permitting & Inspection Webinar Series
Office of Energy Efficiency and Renewable Energy (EERE)
ICLEI Local Governments for Sustainability U.S.A. and the Interstate Renewable Energy Council, Inc. (IREC) present a series of three webinars on Solar Permitting & Inspection. As part of the U...
Mechanical Engineering Department Seminar Series
Awtar, Shorya
Mechanical Engineering Department Seminar Series The use of Virtual Prototyping and 3D Printing-based medical device design and manufacture linked up with 3D printing. The improvements will include patient
UNEP Policy Series ECOSYSTEM MANAGEMENT
1 UNEP Policy Series ECOSYSTEM MANAGEMENT Sustaining Forests: Sustaining forests: Investing in our ...........................................................................6 II. Threats to the world's forests: a complex policy problem ............................7 A. Market failures, financial mechanisms and costs of business ..................8 III. Innovative policy
Eisenstein Series in String Theory
N. A. Obers; B. Pioline
2000-03-01
We discuss the relevance of Eisenstein series for representing certain G(Z)-invariant string theory amplitudes which receive corrections from BPS states only. The Eisenstein series are constructed using G(Z)-invariant mass formulae and are manifestly invariant modular functions on the symmetric space K\\G(R) of non-compact type, with K the maximal compact subgroup of G(R). In particular, we show how Eisenstein series of the T-duality group SO(d,d,Z) can be used to represent one- and g-loop amplitudes in compactified string theory. We also obtain their non-perturbative extensions in terms of the Eisenstein series of the U-duality group E_{d+1(d+1)}(Z).
Castle series, 1954. Technical report
Martin, E.J.; Rowland, R.H.
1982-04-01
CASTLE was an atmospheric nuclear weapons test series held in the Marshall Islands at Enewetak and Bikini atolls in 1954. This is a report of DOD peronnel in CASTLE with an emphasis on operations and radiological safety.
Pressel, Kyle Gregory
2012-01-01
11 2 Scaling of Water Vapor Structure Functions as 2.1cloud model. q is the total water mixing-ratio and q ? isAIRS Exponents from AIRS Data Water Vapor Time Series from a
response in the time series and vice versa. Figure 1 illustrates this situation. The shaded areas indicate, Department of Radiology Brigham and Women's Hospital, Harvard Medical School ABSTRACT The models used
Robust design of control charts for autocorrelated processes with model uncertainty
Lee, Hyun Cheol
2005-11-01
Statistical process control (SPC) procedures suitable for autocorrelated processes have been extensively investigated in recent years. The most popular method is the residual-based control chart. To implement this method, a time series model, which...
Basic Fourier Series Academic Resource Center
Heller, Barbara
Basic Fourier Series Academic Resource Center Workshop for BME by: Neha Bansal #12;Agenda · Fourier Series · Trigonometric Fourier Series · Compact Trigonometric Fourier Series · Examples o Square Waves o Sawtooth Waves · References #12;Fourier Series · A periodic function f(t) can be represented by an infinite
Pillow, Jonathan
. Acknowledgments 9. Conclusions · Conditional renewal (CR) process model incorporates real-time and rescaled dependencies between ISIs can also be modeled using conditional renewal densities 4. Time-rescaling theorem of conditional renewal model 8. Application to retinal data 7. Removing serial dependencies 2. Incorporating
A. E. Koshelev; I. A. Sadovskyy; C. L. Phillips; A. Glatz
2015-10-01
Introducing nanoparticles into superconducting materials has emerged as an efficient route to enhance their current-carrying capability. We address the problem of optimizing vortex pinning landscape for randomly distributed metallic spherical inclusions using large-scale numerical simulations of time-dependent Ginzburg-Landau equations. We found the size and density of particles for which the highest critical current is realized in a fixed magnetic field. For each particle size and magnetic field, the critical current reaches a maximum value at a certain particle density, which typically corresponds to 15-23% of the total volume being replaced by nonsuperconducting material. For fixed diameter, this optimal particle density increases with the magnetic field. Moreover, we found that the optimal particle diameter slowly decreases with the magnetic field from 4.5 to 2.5 coherence lengths at a given temperature. This result shows that pinning landscapes have to be designed for specific applications taking into account relevant magnetic field scales.
Van Nguyen, Linh; Chainais, Pierre
2015-01-01
The study of turbulent flows calls for measurements with high resolution both in space and in time. We propose a new approach to reconstruct High-Temporal-High-Spatial resolution velocity fields by combining two sources of information that are well-resolved either in space or in time, the Low-Temporal-High-Spatial (LTHS) and the High-Temporal-Low-Spatial (HTLS) resolution measurements. In the framework of co-conception between sensing and data post-processing, this work extensively investigates a Bayesian reconstruction approach using a simulated database. A Bayesian fusion model is developed to solve the inverse problem of data reconstruction. The model uses a Maximum A Posteriori estimate, which yields the most probable field knowing the measurements. The DNS of a wall-bounded turbulent flow at moderate Reynolds number is used to validate and assess the performances of the present approach. Low resolution measurements are subsampled in time and space from the fully resolved data. Reconstructed velocities ar...
Division of Economics and Business Working Paper Series
Division of Economics and Business Working Paper Series A Simple Mineral Market Model: Can of Economics and Business Working Paper No. 2012-05 July 2012 Title: A Simple Mineral Market Model: Can and the structural transformation that accompanies economic development in an emerging region is specified. Using