Time-varying correlation and common structures in volatility

NARCIS (Netherlands)

Liu, Yang

2016-01-01

This thesis studies time series properties of the covariance structure of multivariate asset returns. First, the time-varying feature of correlation is investigated at the intraday level with a new correlation model incorporating the intraday correlation dynamics. Second, the thesis develops a

Transport properties of the continuous-time random walk with a long-tailed waiting-time density

International Nuclear Information System (INIS)

Weissman, H.; Havlin, S.; Weiss, G.H.

1989-01-01

The authors derive asymptotic properties of the propagator p(r, t) of a continuous-time random walk (CTRW) in which the waiting time density has the asymptotic form ψ(t) ∼ T α /t α+1 when t >> T and 0 = ∫ 0 ∞ τψ(τ)dτ is finite. One is that the asymptotic behavior of p(0, t) is demonstrated by the waiting time at the origin rather than by the dimension. The second difference is that in the presence of a field p(r, t) no longer remains symmetric around a moving peak. Rather, it is shown that the peak of this probability always occurs at r = 0, and the effect of the field is to break the symmetry that occurs when < ∞. Finally, they calculate similar properties, although in not such great detail, for the case in which the single-step jump probabilities themselves have an infinite mean

Scattering of a TEM wave from a time varying surface

Science.gov (United States)

Elcrat, Alan R.; Harder, T. Mark; Stonebraker, John T.

1990-03-01

A solution is given for reflection of a plane wave with TEM polarization from a planar surface with time varying properties. These properties are given in terms of the currents on the surface. The solution is obtained by numerically solving a system of differential-delay equations in the time domain.

Ellipsometry with randomly varying polarization states

NARCIS (Netherlands)

Liu, F.; Lee, C. J.; Chen, J. Q.; E. Louis,; van der Slot, P. J. M.; Boller, K. J.; F. Bijkerk,

2012-01-01

We show that, under the right conditions, one can make highly accurate polarization-based measurements without knowing the absolute polarization state of the probing light field. It is shown that light, passed through a randomly varying birefringent material has a well-defined orbit on the Poincar

Projected space-time and varying speed of light

International Nuclear Information System (INIS)

Iovane, G.; Bellucci, S.; Benedetto, E.

2008-01-01

In this paper starting from El Naschie's Cantorian space-time and our model of projected Universe, we consider its properties in connection with varying speed of light. A possible way-out of the related problem is provided by the Fantappie group approach

Two-dimensional phononic crystals with time-varying properties: a multiple scattering analysis

International Nuclear Information System (INIS)

Wright, D W; Cobbold, R S C

2010-01-01

Multiple scattering theory is a versatile two- and three-dimensional method for characterizing the acoustic wave transmission through many scatterers. It provides analytical solutions to wave propagation in scattering structures, and its computational complexity grows logarithmically with the number of scatterers. In this paper we show how the 2D method can be adapted to include the effects of time-varying material parameters. Specifically, a new T-matrix is defined to include the effects of frequency modulation that occurs in time-varying phononic crystals. Solutions were verified against finite difference time domain (FDTD) simulations and showed excellent agreement. This new method enables fast characterization of time-varying phononic crystals without the need to resort to lengthy FDTD simulations. Also, the method of combining T-matrices to form the T-supermatrix remains unchanged provided that the new matrix definitions are used. The method is quite compatible with existing implementations of multiple scattering theory and could be readily extended to three-dimensional multiple scattering theory

Modelling Conditional and Unconditional Heteroskedasticity with Smoothly Time-Varying Structure

DEFF Research Database (Denmark)

Amado, Christina; Teräsvirta, Timo

multiplier type misspecification tests. Finite-sample properties of these procedures and tests are examined by simulation. An empirical application to daily stock returns and another one to daily exchange rate returns illustrate the functioning and properties of our modelling strategy in practice......In this paper, we propose two parametric alternatives to the standard GARCH model. They allow the conditional variance to have a smooth time-varying structure of either ad- ditive or multiplicative type. The suggested parameterizations describe both nonlinearity and structural change...... in the conditional and unconditional variances where the transition between regimes over time is smooth. A modelling strategy for these new time-varying parameter GARCH models is developed. It relies on a sequence of Lagrange multiplier tests, and the adequacy of the estimated models is investigated by Lagrange...

On-line statistical processing of radiation detector pulse trains with time-varying count rates

International Nuclear Information System (INIS)

Apostolopoulos, G.

2008-01-01

Statistical analysis is of primary importance for the correct interpretation of nuclear measurements, due to the inherent random nature of radioactive decay processes. This paper discusses the application of statistical signal processing techniques to the random pulse trains generated by radiation detectors. The aims of the presented algorithms are: (i) continuous, on-line estimation of the underlying time-varying count rate θ(t) and its first-order derivative dθ/dt; (ii) detection of abrupt changes in both of these quantities and estimation of their new value after the change point. Maximum-likelihood techniques, based on the Poisson probability distribution, are employed for the on-line estimation of θ and dθ/dt. Detection of abrupt changes is achieved on the basis of the generalized likelihood ratio statistical test. The properties of the proposed algorithms are evaluated by extensive simulations and possible applications for on-line radiation monitoring are discussed

Endogenous time-varying risk aversion and asset returns.

Science.gov (United States)

Berardi, Michele

2016-01-01

Stylized facts about statistical properties for short horizon returns in financial markets have been identified in the literature, but a satisfactory understanding for their manifestation is yet to be achieved. In this work, we show that a simple asset pricing model with representative agent is able to generate time series of returns that replicate such stylized facts if the risk aversion coefficient is allowed to change endogenously over time in response to unexpected excess returns under evolutionary forces. The same model, under constant risk aversion, would instead generate returns that are essentially Gaussian. We conclude that an endogenous time-varying risk aversion represents a very parsimonious way to make the model match real data on key statistical properties, and therefore deserves careful consideration from economists and practitioners alike.

Nonlinear recurrent neural networks for finite-time solution of general time-varying linear matrix equations.

Science.gov (United States)

Xiao, Lin; Liao, Bolin; Li, Shuai; Chen, Ke

2018-02-01

In order to solve general time-varying linear matrix equations (LMEs) more efficiently, this paper proposes two nonlinear recurrent neural networks based on two nonlinear activation functions. According to Lyapunov theory, such two nonlinear recurrent neural networks are proved to be convergent within finite-time. Besides, by solving differential equation, the upper bounds of the finite convergence time are determined analytically. Compared with existing recurrent neural networks, the proposed two nonlinear recurrent neural networks have a better convergence property (i.e., the upper bound is lower), and thus the accurate solutions of general time-varying LMEs can be obtained with less time. At last, various different situations have been considered by setting different coefficient matrices of general time-varying LMEs and a great variety of computer simulations (including the application to robot manipulators) have been conducted to validate the better finite-time convergence of the proposed two nonlinear recurrent neural networks. Copyright © 2017 Elsevier Ltd. All rights reserved.

Modeling information diffusion in time-varying community networks

Science.gov (United States)

Cui, Xuelian; Zhao, Narisa

2017-12-01

Social networks are rarely static, and they typically have time-varying network topologies. A great number of studies have modeled temporal networks and explored social contagion processes within these models; however, few of these studies have considered community structure variations. In this paper, we present a study of how the time-varying property of a modular structure influences the information dissemination. First, we propose a continuous-time Markov model of information diffusion where two parameters, mobility rate and community attractiveness, are introduced to address the time-varying nature of the community structure. The basic reproduction number is derived, and the accuracy of this model is evaluated by comparing the simulation and theoretical results. Furthermore, numerical results illustrate that generally both the mobility rate and community attractiveness significantly promote the information diffusion process, especially in the initial outbreak stage. Moreover, the strength of this promotion effect is much stronger when the modularity is higher. Counterintuitively, it is found that when all communities have the same attractiveness, social mobility no longer accelerates the diffusion process. In addition, we show that the local spreading in the advantage group has been greatly enhanced due to the agglomeration effect caused by the social mobility and community attractiveness difference, which thus increases the global spreading.

Handling Interfaces and Time-varying Properties in Radionuclide Transport Models

International Nuclear Information System (INIS)

Robinson, Peter; Watson, Claire

2010-12-01

This report documents studies undertaken by Quintessa during 2010 in preparation for the SR-Site review that will be initiated by SSM in 2011. The studies relate to consequence analysis calculations, that is to the calculation of radionuclide release and transport if a canister is breached. A sister report documents modelling work undertaken to investigate the coupled processes relevant to copper corrosion and buffer erosion. The Q eq concept is an important part of SKB's current methodology for radionuclide transport using one-dimensional transport modelling; it is used in particular to model transport at the buffer/fracture interface. Quintessa's QPAC code has been used to investigate the Q eq approach and to explore the importance of heterogeneity in the fracture and spalling on the deposition hole surface. The key conclusions are that: - The basic approach to calculating Q eq values is sound and can be reproduced in QPAC. - The fracture resistance dominates over the diffusive resistance in the buffer except for the highest velocity cases. - Heterogeneity in the fracture, in terms of uncorrelated random variations in the fracture aperture, tends to reduce releases, so the use of a constant average aperture approach is conservative. - Narrow channels could lead to the same release as larger fractures with the same pore velocity, so a channel enhancement factor of √10 should be considered. - A spalling zone that increases the area of contact between flowing water and the buffer has the potential to increase the release significantly and changes the functional dependence of Q eq frac on the flowing velocity. Quintessa's AMBER software has previously been used to reproduce SKB's one-dimensional transport calculations and AMBER allows the use of time varying properties. This capability has been used to investigate the effects of glacial episodes on radionuclide transport. The main parameters that could be affected are sorption coefficients and flow rates. For both

Handling Interfaces and Time-varying Properties in Radionuclide Transport Models

Energy Technology Data Exchange (ETDEWEB)

Robinson, Peter; Watson, Claire (Quintessa Ltd., Henley-on-Thames (United Kingdom))

2010-12-15

This report documents studies undertaken by Quintessa during 2010 in preparation for the SR-Site review that will be initiated by SSM in 2011. The studies relate to consequence analysis calculations, that is to the calculation of radionuclide release and transport if a canister is breached. A sister report documents modelling work undertaken to investigate the coupled processes relevant to copper corrosion and buffer erosion. The Q{sub eq} concept is an important part of SKB's current methodology for radionuclide transport using one-dimensional transport modelling; it is used in particular to model transport at the buffer/fracture interface. Quintessa's QPAC code has been used to investigate the Q{sub eq} approach and to explore the importance of heterogeneity in the fracture and spalling on the deposition hole surface. The key conclusions are that: - The basic approach to calculating Q{sub eq} values is sound and can be reproduced in QPAC. - The fracture resistance dominates over the diffusive resistance in the buffer except for the highest velocity cases. - Heterogeneity in the fracture, in terms of uncorrelated random variations in the fracture aperture, tends to reduce releases, so the use of a constant average aperture approach is conservative. - Narrow channels could lead to the same release as larger fractures with the same pore velocity, so a channel enhancement factor of sq root10 should be considered. - A spalling zone that increases the area of contact between flowing water and the buffer has the potential to increase the release significantly and changes the functional dependence of Q{sub eq}frac on the flowing velocity. Quintessa's AMBER software has previously been used to reproduce SKB's one-dimensional transport calculations and AMBER allows the use of time varying properties. This capability has been used to investigate the effects of glacial episodes on radionuclide transport. The main parameters that could be affected are

Holographic cinematography of time-varying reflecting and time-varying phase objects using a Nd:YAG laser

Science.gov (United States)

Decker, A. J.

1982-01-01

The use of a Nd:YAG laser to record holographic motion pictures of time-varying reflecting objects and time-varying phase objects is discussed. Sample frames from both types of holographic motion pictures are presented. The holographic system discussed is intended for three-dimensional flow visualization of the time-varying flows that occur in jet-engine components.

Wavelet ridge diagnosis of time-varying elliptical signals with application to an oceanic eddy

OpenAIRE

Lilly , J. M.; Gascard , Jean-Claude

2006-01-01

International audience; A method for diagnosing the physical properties of a time-varying ellipse is presented. This essentially involves extending the notion of instantaneous frequency to the bivariate case. New complications, and possibilities, arise from the fact that there are several meaningful forms in which a time-varying ellipse may be represented. A perturbation analysis valid for the near-circular case clarifies these issues. Diagnosis of the ellipse properties may then be performed...

Micro-Randomized Trials: An Experimental Design for Developing Just-in-Time Adaptive Interventions

Science.gov (United States)

Klasnja, Predrag; Hekler, Eric B.; Shiffman, Saul; Boruvka, Audrey; Almirall, Daniel; Tewari, Ambuj; Murphy, Susan A.

2015-01-01

Objective This paper presents an experimental design, the micro-randomized trial, developed to support optimization of just-in-time adaptive interventions (JITAIs). JITAIs are mHealth technologies that aim to deliver the right intervention components at the right times and locations to optimally support individuals’ health behaviors. Micro-randomized trials offer a way to optimize such interventions by enabling modeling of causal effects and time-varying effect moderation for individual intervention components within a JITAI. Methods The paper describes the micro-randomized trial design, enumerates research questions that this experimental design can help answer, and provides an overview of the data analyses that can be used to assess the causal effects of studied intervention components and investigate time-varying moderation of those effects. Results Micro-randomized trials enable causal modeling of proximal effects of the randomized intervention components and assessment of time-varying moderation of those effects. Conclusions Micro-randomized trials can help researchers understand whether their interventions are having intended effects, when and for whom they are effective, and what factors moderate the interventions’ effects, enabling creation of more effective JITAIs. PMID:26651463

On properties of continuous-time random walks with non-Poissonian jump-times

International Nuclear Information System (INIS)

Villarroel, Javier; Montero, Miquel

2009-01-01

The usual development of the continuous-time random walk (CTRW) proceeds by assuming that the present is one of the jumping times. Under this restrictive assumption integral equations for the propagator and mean escape times have been derived. We generalize these results to the case when the present is an arbitrary time by recourse to renewal theory. The case of Erlang distributed times is analyzed in detail. Several concrete examples are considered.

Direct prediction of spatially and temporally varying physical properties from time-lapse electrical resistance data

Science.gov (United States)

Hermans, Thomas; Oware, Erasmus; Caers, Jef

2016-09-01

Time-lapse applications of electrical methods have grown significantly over the last decade. However, the quantitative interpretation of tomograms in terms of physical properties, such as salinity, temperature or saturation, remains difficult. In many applications, geophysical models are transformed into hydrological models, but this transformation suffers from spatially and temporally varying resolution resulting from the regularization used by the deterministic inversion. In this study, we investigate a prediction-focused approach (PFA) to directly estimate subsurface physical properties with electrical resistance data, circumventing the need for classic tomographic inversions. First, we generate a prior set of resistance data and physical property forecast through hydrogeological and geophysical simulations mimicking the field experiment. We reduce the dimension of both the data and the forecast through principal component analysis in order to keep the most informative part of both sets in a reduced dimension space. Then, we apply canonical correlation analysis to explore the relationship between the data and the forecast in their reduced dimension space. If a linear relationship can be established, the posterior distribution of the forecast can be directly sampled using a Gaussian process regression where the field data scores are the conditioning data. In this paper, we demonstrate PFA for various physical property distributions. We also develop a framework to propagate the estimated noise level in the reduced dimension space. We validate the results by a Monte Carlo study on the posterior distribution and demonstrate that PFA yields accurate uncertainty for the cases studied.

Unraveling spurious properties of interaction networks with tailored random networks.

Directory of Open Access Journals (Sweden)

Stephan Bialonski

Full Text Available We investigate interaction networks that we derive from multivariate time series with methods frequently employed in diverse scientific fields such as biology, quantitative finance, physics, earth and climate sciences, and the neurosciences. Mimicking experimental situations, we generate time series with finite length and varying frequency content but from independent stochastic processes. Using the correlation coefficient and the maximum cross-correlation, we estimate interdependencies between these time series. With clustering coefficient and average shortest path length, we observe unweighted interaction networks, derived via thresholding the values of interdependence, to possess non-trivial topologies as compared to Erdös-Rényi networks, which would indicate small-world characteristics. These topologies reflect the mostly unavoidable finiteness of the data, which limits the reliability of typically used estimators of signal interdependence. We propose random networks that are tailored to the way interaction networks are derived from empirical data. Through an exemplary investigation of multichannel electroencephalographic recordings of epileptic seizures--known for their complex spatial and temporal dynamics--we show that such random networks help to distinguish network properties of interdependence structures related to seizure dynamics from those spuriously induced by the applied methods of analysis.

Transformation of binaural response properties in the ascending auditory pathway: influence of time-varying interaural phase disparity.

Science.gov (United States)

Spitzer, M W; Semple, M N

1998-12-01

Transformation of binaural response properties in the ascending auditory pathway: influence of time-varying interaural phase disparity. J. Neurophysiol. 80: 3062-3076, 1998. Previous studies demonstrated that tuning of inferior colliculus (IC) neurons to interaural phase disparity (IPD) is often profoundly influenced by temporal variation of IPD, which simulates the binaural cue produced by a moving sound source. To determine whether sensitivity to simulated motion arises in IC or at an earlier stage of binaural processing we compared responses in IC with those of two major IPD-sensitive neuronal classes in the superior olivary complex (SOC), neurons whose discharges were phase locked (PL) to tonal stimuli and those that were nonphase locked (NPL). Time-varying IPD stimuli consisted of binaural beats, generated by presenting tones of slightly different frequencies to the two ears, and interaural phase modulation (IPM), generated by presenting a pure tone to one ear and a phase modulated tone to the other. IC neurons and NPL-SOC neurons were more sharply tuned to time-varying than to static IPD, whereas PL-SOC neurons were essentially uninfluenced by the mode of stimulus presentation. Preferred IPD was generally similar in responses to static and time-varying IPD for all unit populations. A few IC neurons were highly influenced by the direction and rate of simulated motion, but the major effect for most IC neurons and all SOC neurons was a linear shift of preferred IPD at high rates-attributable to response latency. Most IC and NPL-SOC neurons were strongly influenced by IPM stimuli simulating motion through restricted ranges of azimuth; simulated motion through partially overlapping azimuthal ranges elicited discharge profiles that were highly discontiguous, indicating that the response associated with a particular IPD is dependent on preceding portions of the stimulus. In contrast, PL-SOC responses tracked instantaneous IPD throughout the trajectory of simulated

First-passage time asymptotics over moving boundaries for random walk bridges

OpenAIRE

Sloothaak, F.; Zwart, B.; Wachtel, V.

2017-01-01

We study the asymptotic tail probability of the first-passage time over a moving boundary for a random walk conditioned to return to zero, where the increments of the random walk have finite variance. Typically, the asymptotic tail behavior may be described through a regularly varying function with exponent -1/2, where the impact of the boundary is captured by the slowly varying function. Yet, the moving boundary may have a stronger effect when the tail is considered at a time close to the re...

Asymptotic Properties of Multistate Random Walks. I. Theory

NARCIS (Netherlands)

Roerdink, J.B.T.M.; Shuler, K.E.

1985-01-01

A calculation is presented of the long-time behavior of various random walk properties (moments, probability of return to the origin, expected number of distinct sites visited) for multistate random walks on periodic lattices. In particular, we consider inhomogeneous periodic lattices, consisting of

A Tentative Application Of Morphological Filters To Time-Varying Images

Science.gov (United States)

Billard, D.; Poquillon, B.

1989-03-01

In this paper, morphological filters, which are commonly used to process either 2D or multidimensional static images, are generalized to the analysis of time-varying image sequence. The introduction of the time dimension induces then interesting prop-erties when designing such spatio-temporal morphological filters. In particular, the specification of spatio-temporal structuring ele-ments (equivalent to time-varying spatial structuring elements) can be adjusted according to the temporal variations of the image sequences to be processed : this allows to derive specific morphological transforms to perform noise filtering or moving objects discrimination on dynamic images viewed by a non-stationary sensor. First, a brief introduction to the basic principles underlying morphological filters will be given. Then, a straightforward gener-alization of these principles to time-varying images will be pro-posed. This will lead us to define spatio-temporal opening and closing and to introduce some of their possible applications to process dynamic images. At last, preliminary results obtained us-ing a natural forward looking infrared (FUR) image sequence are presented.

The influence of tyre transient side force properties on vehicle lateral acceleration for a time-varying vertical force

Science.gov (United States)

Takahashi, Toshimichi

2018-05-01

The tyre model which formerly developed by the author et al. and describes the tyre transient responses of side force and aligning moment under the time-varying vertical force was implemented to the vehicle dynamics simulation software and the influence of tyre side force transient property on the vehicle behaviour was investigated. The vehicle responses with/without tyre transient property on sinusoidally undulated road surfaces were simulated and compared. It was found that the average lateral acceleration of the vehicle at the sinusoidal steering wheel angle input decreases on the undulated road of long wavelength (3 m) for both cases, but when the wavelength becomes shorter (1 m), the average lateral acceleration increases only in the case that the transient property is considered. The cause of those changes is explained by using the tyre-related variables. Also the steady-state turning behaviour of the vehicle on undulated roads are shown and discussed.

Time-varying coefficient estimation in SURE models. Application to portfolio management

DEFF Research Database (Denmark)

Casas, Isabel; Ferreira, Eva; Orbe, Susan

This paper provides a detailed analysis of the asymptotic properties of a kernel estimator for a Seemingly Unrelated Regression Equations model with time-varying coefficients (tv-SURE) under very general conditions. Theoretical results together with a simulation study differentiates the cases...

Real-time Kalman filter implementation for active feedforward control of time-varying broadband noise and vibrations

NARCIS (Netherlands)

Ophem, S. van; Berkhoff, A.P.

2012-01-01

Tracking behavior and the rate of convergence are critical properties in active noise control applications with time-varying disturbance spectra. As compared to the standard filtered-reference Least Mean Square (LMS) algorithm, improved convergence can be obtained with schemes based on

Zhang neural network for online solution of time-varying convex quadratic program subject to time-varying linear-equality constraints

International Nuclear Information System (INIS)

Zhang Yunong; Li Zhan

2009-01-01

In this Letter, by following Zhang et al.'s method, a recurrent neural network (termed as Zhang neural network, ZNN) is developed and analyzed for solving online the time-varying convex quadratic-programming problem subject to time-varying linear-equality constraints. Different from conventional gradient-based neural networks (GNN), such a ZNN model makes full use of the time-derivative information of time-varying coefficient. The resultant ZNN model is theoretically proved to have global exponential convergence to the time-varying theoretical optimal solution of the investigated time-varying convex quadratic program. Computer-simulation results further substantiate the effectiveness, efficiency and novelty of such ZNN model and method.

Random queues and risk averse users

DEFF Research Database (Denmark)

de Palma, André; Fosgerau, Mogens

2013-01-01

We analyze Nash equilibrium in time of use of a congested facility. Users are risk averse with general concave utility. Queues are subject to varying degrees of random sorting, ranging from strict queue priority to a completely random queue. We define the key “no residual queue” property, which...

Palm theory for random time changes

Directory of Open Access Journals (Sweden)

Masakiyo Miyazawa

2001-01-01

Full Text Available Palm distributions are basic tools when studying stationarity in the context of point processes, queueing systems, fluid queues or random measures. The framework varies with the random phenomenon of interest, but usually a one-dimensional group of measure-preserving shifts is the starting point. In the present paper, by alternatively using a framework involving random time changes (RTCs and a two-dimensional family of shifts, we are able to characterize all of the above systems in a single framework. Moreover, this leads to what we call the detailed Palm distribution (DPD which is stationary with respect to a certain group of shifts. The DPD has a very natural interpretation as the distribution seen at a randomly chosen position on the extended graph of the RTC, and satisfies a general duality criterion: the DPD of the DPD gives the underlying probability P in return.

Tracking time-varying coefficient-functions

DEFF Research Database (Denmark)

Nielsen, Henrik Aalborg; Nielsen, Torben Skov; Joensen, Alfred K.

2000-01-01

is a combination of recursive least squares with exponential forgetting and local polynomial regression. It is argued, that it is appropriate to let the forgetting factor vary with the value of the external signal which is the argument of the coefficient functions. Some of the key properties of the modified method...... are studied by simulation...

Time-varying Crash Risk

DEFF Research Database (Denmark)

Christoffersen, Peter; Feunoua, Bruno; Jeon, Yoontae

We estimate a continuous-time model with stochastic volatility and dynamic crash probability for the S&P 500 index and find that market illiquidity dominates other factors in explaining the stock market crash risk. While the crash probability is time-varying, its dynamic depends only weakly on re...

Taylor-series and Monte-Carlo-method uncertainty estimation of the width of a probability distribution based on varying bias and random error

International Nuclear Information System (INIS)

Wilson, Brandon M; Smith, Barton L

2013-01-01

Uncertainties are typically assumed to be constant or a linear function of the measured value; however, this is generally not true. Particle image velocimetry (PIV) is one example of a measurement technique that has highly nonlinear, time varying local uncertainties. Traditional uncertainty methods are not adequate for the estimation of the uncertainty of measurement statistics (mean and variance) in the presence of nonlinear, time varying errors. Propagation of instantaneous uncertainty estimates into measured statistics is performed allowing accurate uncertainty quantification of time-mean and statistics of measurements such as PIV. It is shown that random errors will always elevate the measured variance, and thus turbulent statistics such as u'u'-bar. Within this paper, nonlinear, time varying errors are propagated from instantaneous measurements into the measured mean and variance using the Taylor-series method. With these results and knowledge of the systematic and random uncertainty of each measurement, the uncertainty of the time-mean, the variance and covariance can be found. Applicability of the Taylor-series uncertainty equations to time varying systematic and random errors and asymmetric error distributions are demonstrated with Monte-Carlo simulations. The Taylor-series uncertainty estimates are always accurate for uncertainties on the mean quantity. The Taylor-series variance uncertainty is similar to the Monte-Carlo results for cases in which asymmetric random errors exist or the magnitude of the instantaneous variations in the random and systematic errors is near the ‘true’ variance. However, the Taylor-series method overpredicts the uncertainty in the variance as the instantaneous variations of systematic errors are large or are on the same order of magnitude as the ‘true’ variance. (paper)

A comparison of time-varying covariates in two smoking cessation interventions for cardiac patients

NARCIS (Netherlands)

Prenger, Hendrikje Cornelia; Pieterse, Marcel E.; Braakman-Jansen, Louise Marie Antoinette; Bolman, Catherine; Ruitenbeek-Wiggers, L.; de Vries, H.

2013-01-01

The aim of the study was to explore the time-varying contribution of social cognitive determinants of smoking cessation following an intervention on cessation. Secondary analyses were performed on data from two comparable randomized controlled trials on brief smoking cessation interventions for

Conditional CAPM: Time-varying Betas in the Brazilian Market

Directory of Open Access Journals (Sweden)

Frances Fischberg Blank

2014-10-01

Full Text Available The conditional CAPM is characterized by time-varying market beta. Based on state-space models approach, beta behavior can be modeled as a stochastic process dependent on conditioning variables related to business cycle and estimated using Kalman filter. This paper studies alternative models for portfolios sorted by size and book-to-market ratio in the Brazilian stock market and compares their adjustment to data. Asset pricing tests based on time-series and cross-sectional approaches are also implemented. A random walk process combined with conditioning variables is the preferred model, reducing pricing errors compared to unconditional CAPM, but the errors are still significant. Cross-sectional test show that book-to-market ratio becomes less relevant, but past returns still capture cross-section variation

An integrative time-varying frequency detection and channel sounding method for dynamic plasma sheath

Science.gov (United States)

Shi, Lei; Yao, Bo; Zhao, Lei; Liu, Xiaotong; Yang, Min; Liu, Yanming

2018-01-01

The plasma sheath-surrounded hypersonic vehicle is a dynamic and time-varying medium and it is almost impossible to calculate time-varying physical parameters directly. The in-fight detection of the time-varying degree is important to understand the dynamic nature of the physical parameters and their effect on re-entry communication. In this paper, a constant envelope zero autocorrelation (CAZAC) sequence based on time-varying frequency detection and channel sounding method is proposed to detect the plasma sheath electronic density time-varying property and wireless channel characteristic. The proposed method utilizes the CAZAC sequence, which has excellent autocorrelation and spread gain characteristics, to realize dynamic time-varying detection/channel sounding under low signal-to-noise ratio in the plasma sheath environment. Theoretical simulation under a typical time-varying radio channel shows that the proposed method is capable of detecting time-variation frequency up to 200 kHz and can trace the channel amplitude and phase in the time domain well under -10 dB. Experimental results conducted in the RF modulation discharge plasma device verified the time variation detection ability in practical dynamic plasma sheath. Meanwhile, nonlinear phenomenon of dynamic plasma sheath on communication signal is observed thorough channel sounding result.

First-passage time asymptotics over moving boundaries for random walk bridges

NARCIS (Netherlands)

Sloothaak, F.; Zwart, B.; Wachtel, V.

2017-01-01

We study the asymptotic tail probability of the first-passage time over a moving boundary for a random walk conditioned to return to zero, where the increments of the random walk have finite variance. Typically, the asymptotic tail behavior may be described through a regularly varying function with

Exponential stability of fuzzy cellular neural networks with constant and time-varying delays

International Nuclear Information System (INIS)

Liu Yanqing; Tang Wansheng

2004-01-01

In this Letter, the global stability of delayed fuzzy cellular neural networks (FCNN) with either constant delays or time varying delays is proposed. Firstly, we give the existence and uniqueness of the equilibrium point by using the theory of topological degree and the properties of nonsingular M-matrix and the sufficient conditions for ascertaining the global exponential stability by constructing a suitable Lyapunov functional. Secondly, the criteria for guaranteeing the global exponential stability of FCNN with time varying delays are given and the estimation of exponential convergence rate with regard to speed of vary of delays is presented by constructing a suitable Lyapunov functional

Transport methods: general. 2. Monte Carlo Particle Transport in Media with Exponentially Varying Time-Dependent Cross Sections

International Nuclear Information System (INIS)

Brown, Forrest B.; Martin, William R.

2001-01-01

We have investigated Monte Carlo schemes for analyzing particle transport through media with exponentially varying time-dependent cross sections. For such media, the cross sections are represented in the form Σ(t) = Σ 0 e -at (1) or equivalently as Σ(x) = Σ 0 e -bx (2) where b = av and v is the particle speed. For the following discussion, the parameters a and b may be either positive, for exponentially decreasing cross sections, or negative, for exponentially increasing cross sections. For most time-dependent Monte Carlo applications, the time and spatial variations of the cross-section data are handled by means of a stepwise procedure, holding the cross sections constant for each region over a small time interval Δt, performing the Monte Carlo random walk over the interval Δt, updating the cross sections, and then repeating for a series of time intervals. Continuously varying spatial- or time-dependent cross sections can be treated in a rigorous Monte Carlo fashion using delta-tracking, but inefficiencies may arise if the range of cross-section variation is large. In this paper, we present a new method for sampling collision distances directly for cross sections that vary exponentially in space or time. The method is exact and efficient and has direct application to Monte Carlo radiation transport methods. To verify that the probability density function (PDF) is correct and that the random-sampling procedure yields correct results, numerical experiments were performed using a one-dimensional Monte Carlo code. The physical problem consisted of a beam source impinging on a purely absorbing infinite slab, with a slab thickness of 1 cm and Σ 0 = 1 cm -1 . Monte Carlo calculations with 10 000 particles were run for a range of the exponential parameter b from -5 to +20 cm -1 . Two separate Monte Carlo calculations were run for each choice of b, a continuously varying case using the random-sampling procedures described earlier, and a 'conventional' case where the

Robustness analysis of the Zhang neural network for online time-varying quadratic optimization

International Nuclear Information System (INIS)

Zhang Yunong; Ruan Gongqin; Li Kene; Yang Yiwen

2010-01-01

A general type of recurrent neural network (termed as Zhang neural network, ZNN) has recently been proposed by Zhang et al for the online solution of time-varying quadratic-minimization (QM) and quadratic-programming (QP) problems. Global exponential convergence of the ZNN could be achieved theoretically in an ideal error-free situation. In this paper, with the normal differentiation and dynamics-implementation errors considered, the robustness properties of the ZNN model are investigated for solving these time-varying problems. In addition, linear activation functions and power-sigmoid activation functions could be applied to such a perturbed ZNN model. Both theoretical-analysis and computer-simulation results demonstrate the good ZNN robustness and superior performance for online time-varying QM and QP problem solving, especially when using power-sigmoid activation functions.

Design of 2D time-varying vector fields.

Science.gov (United States)

Chen, Guoning; Kwatra, Vivek; Wei, Li-Yi; Hansen, Charles D; Zhang, Eugene

2012-10-01

Design of time-varying vector fields, i.e., vector fields that can change over time, has a wide variety of important applications in computer graphics. Existing vector field design techniques do not address time-varying vector fields. In this paper, we present a framework for the design of time-varying vector fields, both for planar domains as well as manifold surfaces. Our system supports the creation and modification of various time-varying vector fields with desired spatial and temporal characteristics through several design metaphors, including streamlines, pathlines, singularity paths, and bifurcations. These design metaphors are integrated into an element-based design to generate the time-varying vector fields via a sequence of basis field summations or spatial constrained optimizations at the sampled times. The key-frame design and field deformation are also introduced to support other user design scenarios. Accordingly, a spatial-temporal constrained optimization and the time-varying transformation are employed to generate the desired fields for these two design scenarios, respectively. We apply the time-varying vector fields generated using our design system to a number of important computer graphics applications that require controllable dynamic effects, such as evolving surface appearance, dynamic scene design, steerable crowd movement, and painterly animation. Many of these are difficult or impossible to achieve via prior simulation-based methods. In these applications, the time-varying vector fields have been applied as either orientation fields or advection fields to control the instantaneous appearance or evolving trajectories of the dynamic effects.

Securing OFDM over Wireless Time-Varying Channels Using Subcarrier Overloading with Joint Signal Constellations

Directory of Open Access Journals (Sweden)

Gill R. Tsouri

2009-01-01

Full Text Available A method of overloading subcarriers by multiple transmitters to secure OFDM in wireless time-varying channels is proposed and analyzed. The method is based on reverse piloting, superposition modulation, and joint decoding. It makes use of channel randomness, reciprocity, and fast decorrelation in space to secure OFDM with low overheads on encryption, decryption, and key distribution. These properties make it a good alternative to traditional software-based information security algorithms in systems where the costs associated with such algorithms are an implementation obstacle. A necessary and sufficient condition for achieving information theoretic security in accordance with channel and system parameters is derived. Security by complexity is assessed for cases where the condition for information theoretic security is not satisfied. In addition, practical means for implementing the method are derived including generating robust joint constellations, decoding data with low complexity, and mitigating the effects of imperfections due to mobility, power control errors, and synchronization errors.

Design of 2D Time-Varying Vector Fields

KAUST Repository

Chen, Guoning

2012-10-01

Design of time-varying vector fields, i.e., vector fields that can change over time, has a wide variety of important applications in computer graphics. Existing vector field design techniques do not address time-varying vector fields. In this paper, we present a framework for the design of time-varying vector fields, both for planar domains as well as manifold surfaces. Our system supports the creation and modification of various time-varying vector fields with desired spatial and temporal characteristics through several design metaphors, including streamlines, pathlines, singularity paths, and bifurcations. These design metaphors are integrated into an element-based design to generate the time-varying vector fields via a sequence of basis field summations or spatial constrained optimizations at the sampled times. The key-frame design and field deformation are also introduced to support other user design scenarios. Accordingly, a spatial-temporal constrained optimization and the time-varying transformation are employed to generate the desired fields for these two design scenarios, respectively. We apply the time-varying vector fields generated using our design system to a number of important computer graphics applications that require controllable dynamic effects, such as evolving surface appearance, dynamic scene design, steerable crowd movement, and painterly animation. Many of these are difficult or impossible to achieve via prior simulation-based methods. In these applications, the time-varying vector fields have been applied as either orientation fields or advection fields to control the instantaneous appearance or evolving trajectories of the dynamic effects. © 1995-2012 IEEE.

Design of 2D Time-Varying Vector Fields

KAUST Repository

Chen, Guoning; Kwatra, Vivek; Wei, Li-Yi; Hansen, Charles D.; Zhang, Eugene

2012-01-01

Design of time-varying vector fields, i.e., vector fields that can change over time, has a wide variety of important applications in computer graphics. Existing vector field design techniques do not address time-varying vector fields. In this paper, we present a framework for the design of time-varying vector fields, both for planar domains as well as manifold surfaces. Our system supports the creation and modification of various time-varying vector fields with desired spatial and temporal characteristics through several design metaphors, including streamlines, pathlines, singularity paths, and bifurcations. These design metaphors are integrated into an element-based design to generate the time-varying vector fields via a sequence of basis field summations or spatial constrained optimizations at the sampled times. The key-frame design and field deformation are also introduced to support other user design scenarios. Accordingly, a spatial-temporal constrained optimization and the time-varying transformation are employed to generate the desired fields for these two design scenarios, respectively. We apply the time-varying vector fields generated using our design system to a number of important computer graphics applications that require controllable dynamic effects, such as evolving surface appearance, dynamic scene design, steerable crowd movement, and painterly animation. Many of these are difficult or impossible to achieve via prior simulation-based methods. In these applications, the time-varying vector fields have been applied as either orientation fields or advection fields to control the instantaneous appearance or evolving trajectories of the dynamic effects. © 1995-2012 IEEE.

Estimating time-varying RSA to examine psychophysiological linkage of marital dyads.

Science.gov (United States)

Gates, Kathleen M; Gatzke-Kopp, Lisa M; Sandsten, Maria; Blandon, Alysia Y

2015-08-01

One of the primary tenets of polyvagal theory dictates that parasympathetic influence on heart rate, often estimated by respiratory sinus arrhythmia (RSA), shifts rapidly in response to changing environmental demands. The current standard analytic approach of aggregating RSA estimates across time to arrive at one value fails to capture this dynamic property within individuals. By utilizing recent methodological developments that enable precise RSA estimates at smaller time intervals, we demonstrate the utility of computing time-varying RSA for assessing psychophysiological linkage (or synchrony) in husband-wife dyads using time-locked data collected in a naturalistic setting. © 2015 Society for Psychophysiological Research.

Fluctuating interaction network and time-varying stability of a natural fish community

Science.gov (United States)

Ushio, Masayuki; Hsieh, Chih-Hao; Masuda, Reiji; Deyle, Ethan R.; Ye, Hao; Chang, Chun-Wei; Sugihara, George; Kondoh, Michio

2018-02-01

Ecological theory suggests that large-scale patterns such as community stability can be influenced by changes in interspecific interactions that arise from the behavioural and/or physiological responses of individual species varying over time. Although this theory has experimental support, evidence from natural ecosystems is lacking owing to the challenges of tracking rapid changes in interspecific interactions (known to occur on timescales much shorter than a generation time) and then identifying the effect of such changes on large-scale community dynamics. Here, using tools for analysing nonlinear time series and a 12-year-long dataset of fortnightly collected observations on a natural marine fish community in Maizuru Bay, Japan, we show that short-term changes in interaction networks influence overall community dynamics. Among the 15 dominant species, we identify 14 interspecific interactions to construct a dynamic interaction network. We show that the strengths, and even types, of interactions change with time; we also develop a time-varying stability measure based on local Lyapunov stability for attractor dynamics in non-equilibrium nonlinear systems. We use this dynamic stability measure to examine the link between the time-varying interaction network and community stability. We find seasonal patterns in dynamic stability for this fish community that broadly support expectations of current ecological theory. Specifically, the dominance of weak interactions and higher species diversity during summer months are associated with higher dynamic stability and smaller population fluctuations. We suggest that interspecific interactions, community network structure and community stability are dynamic properties, and that linking fluctuating interaction networks to community-level dynamic properties is key to understanding the maintenance of ecological communities in nature.

State space modeling of time-varying contemporaneous and lagged relations in connectivity maps.

Science.gov (United States)

Molenaar, Peter C M; Beltz, Adriene M; Gates, Kathleen M; Wilson, Stephen J

2016-01-15

Most connectivity mapping techniques for neuroimaging data assume stationarity (i.e., network parameters are constant across time), but this assumption does not always hold true. The authors provide a description of a new approach for simultaneously detecting time-varying (or dynamic) contemporaneous and lagged relations in brain connectivity maps. Specifically, they use a novel raw data likelihood estimation technique (involving a second-order extended Kalman filter/smoother embedded in a nonlinear optimizer) to determine the variances of the random walks associated with state space model parameters and their autoregressive components. The authors illustrate their approach with simulated and blood oxygen level-dependent functional magnetic resonance imaging data from 30 daily cigarette smokers performing a verbal working memory task, focusing on seven regions of interest (ROIs). Twelve participants had dynamic directed functional connectivity maps: Eleven had one or more time-varying contemporaneous ROI state loadings, and one had a time-varying autoregressive parameter. Compared to smokers without dynamic maps, smokers with dynamic maps performed the task with greater accuracy. Thus, accurate detection of dynamic brain processes is meaningfully related to behavior in a clinical sample. Published by Elsevier Inc.

Time varying voltage combustion control and diagnostics sensor

Science.gov (United States)

Chorpening, Benjamin T [Morgantown, WV; Thornton, Jimmy D [Morgantown, WV; Huckaby, E David [Morgantown, WV; Fincham, William [Fairmont, WV

2011-04-19

A time-varying voltage is applied to an electrode, or a pair of electrodes, of a sensor installed in a fuel nozzle disposed adjacent the combustion zone of a continuous combustion system, such as of the gas turbine engine type. The time-varying voltage induces a time-varying current in the flame which is measured and used to determine flame capacitance using AC electrical circuit analysis. Flame capacitance is used to accurately determine the position of the flame from the sensor and the fuel/air ratio. The fuel and/or air flow rate (s) is/are then adjusted to provide reduced flame instability problems such as flashback, combustion dynamics and lean blowout, as well as reduced emissions. The time-varying voltage may be an alternating voltage and the time-varying current may be an alternating current.

Consumer responses to time varying prices for electricity

International Nuclear Information System (INIS)

Thorsnes, Paul; Williams, John; Lawson, Rob

2012-01-01

We report new experimental evidence of the household response to weekday differentials in peak and off-peak electricity prices. The data come from Auckland, New Zealand, where peak residential electricity consumption occurs in winter for heating. Peak/off-peak price differentials ranged over four randomly selected groups from 1.0 to 3.5. On average, there was no response except in winter. In winter, participant households reduced electricity consumption by at least 10%, took advantage of lower off-peak prices but did not respond to the peak price differentials. Response varied with house and household size, time spent away from home, and whether water was heated with electricity. - Highlights: ► Seasonal effects in winter. ► High conservation effect from information. ► Higher peak prices no effect on peak use. ► Low off-peak prices encourage less conservation off-peak.

Time-varying effect moderation using the structural nested mean model: estimation using inverse-weighted regression with residuals

Science.gov (United States)

Almirall, Daniel; Griffin, Beth Ann; McCaffrey, Daniel F.; Ramchand, Rajeev; Yuen, Robert A.; Murphy, Susan A.

2014-01-01

This article considers the problem of examining time-varying causal effect moderation using observational, longitudinal data in which treatment, candidate moderators, and possible confounders are time varying. The structural nested mean model (SNMM) is used to specify the moderated time-varying causal effects of interest in a conditional mean model for a continuous response given time-varying treatments and moderators. We present an easy-to-use estimator of the SNMM that combines an existing regression-with-residuals (RR) approach with an inverse-probability-of-treatment weighting (IPTW) strategy. The RR approach has been shown to identify the moderated time-varying causal effects if the time-varying moderators are also the sole time-varying confounders. The proposed IPTW+RR approach provides estimators of the moderated time-varying causal effects in the SNMM in the presence of an additional, auxiliary set of known and measured time-varying confounders. We use a small simulation experiment to compare IPTW+RR versus the traditional regression approach and to compare small and large sample properties of asymptotic versus bootstrap estimators of the standard errors for the IPTW+RR approach. This article clarifies the distinction between time-varying moderators and time-varying confounders. We illustrate the methodology in a case study to assess if time-varying substance use moderates treatment effects on future substance use. PMID:23873437

Dual Extended Kalman Filter for the Identification of Time-Varying Human Manual Control Behavior

Science.gov (United States)

Popovici, Alexandru; Zaal, Peter M. T.; Pool, Daan M.

2017-01-01

A Dual Extended Kalman Filter was implemented for the identification of time-varying human manual control behavior. Two filters that run concurrently were used, a state filter that estimates the equalization dynamics, and a parameter filter that estimates the neuromuscular parameters and time delay. Time-varying parameters were modeled as a random walk. The filter successfully estimated time-varying human control behavior in both simulated and experimental data. Simple guidelines are proposed for the tuning of the process and measurement covariance matrices and the initial parameter estimates. The tuning was performed on simulation data, and when applied on experimental data, only an increase in measurement process noise power was required in order for the filter to converge and estimate all parameters. A sensitivity analysis to initial parameter estimates showed that the filter is more sensitive to poor initial choices of neuromuscular parameters than equalization parameters, and bad choices for initial parameters can result in divergence, slow convergence, or parameter estimates that do not have a real physical interpretation. The promising results when applied to experimental data, together with its simple tuning and low dimension of the state-space, make the use of the Dual Extended Kalman Filter a viable option for identifying time-varying human control parameters in manual tracking tasks, which could be used in real-time human state monitoring and adaptive human-vehicle haptic interfaces.

Adaptive operational modal identification for slow linear time-varying structures based on frozen-in coefficient method and limited memory recursive principal component analysis

Science.gov (United States)

Wang, Cheng; Guan, Wei; Wang, J. Y.; Zhong, Bineng; Lai, Xiongming; Chen, Yewang; Xiang, Liang

2018-02-01

To adaptively identify the transient modal parameters for linear weakly damped structures with slow time-varying characteristics under unmeasured stationary random ambient loads, this paper proposes a novel operational modal analysis (OMA) method based on the frozen-in coefficient method and limited memory recursive principal component analysis (LMRPCA). In the modal coordinate, the random vibration response signals of mechanical weakly damped structures can be decomposed into the inner product of modal shapes and modal responses, from which the natural frequencies and damping ratios can be well acquired by single-degree-of-freedom (SDOF) identification approach such as FFT. Hence, for the OMA method based on principal component analysis (PCA), it becomes very crucial to examine the relation between the transformational matrix and the modal shapes matrix, to find the association between the principal components (PCs) matrix and the modal responses matrix, and to turn the operational modal parameter identification problem into PCA of the stationary random vibration response signals of weakly damped mechanical structures. Based on the theory of "time-freezing", the method of frozen-in coefficient, and the assumption of "short time invariant" and "quasistationary", the non-stationary random response signals of the weakly damped and slow linear time-varying structures (LTV) can approximately be seen as the stationary random response time series of weakly damped and linear time invariant structures (LTI) in a short interval. Thus, the adaptive identification of time-varying operational modal parameters is turned into decompositing the PCs of stationary random vibration response signals subsection of weakly damped mechanical structures after choosing an appropriate limited memory window. Finally, a three-degree-of-freedom (DOF) structure with weakly damped and slow time-varying mass is presented to illustrate this method of identification. Results show that the LMRPCA

A Comparison of Evolutionary Algorithms for Tracking Time-Varying Recursive Systems

Directory of Open Access Journals (Sweden)

White Michael S

2003-01-01

Full Text Available A comparison is made of the behaviour of some evolutionary algorithms in time-varying adaptive recursive filter systems. Simulations show that an algorithm including random immigrants outperforms a more conventional algorithm using the breeder genetic algorithm as the mutation operator when the time variation is discontinuous, but neither algorithm performs well when the time variation is rapid but smooth. To meet this deficit, a new hybrid algorithm which uses a hill climber as an additional genetic operator, applied for several steps at each generation, is introduced. A comparison is made of the effect of applying the hill climbing operator a few times to all members of the population or a larger number of times solely to the best individual; it is found that applying to the whole population yields the better results, substantially improved compared with those obtained using earlier methods.

Timed arrays wideband and time varying antenna arrays

CERN Document Server

Haupt, Randy L

2015-01-01

Introduces timed arrays and design approaches to meet the new high performance standards The author concentrates on any aspect of an antenna array that must be viewed from a time perspective. The first chapters briefly introduce antenna arrays and explain the difference between phased and timed arrays. Since timed arrays are designed for realistic time-varying signals and scenarios, the book also reviews wideband signals, baseband and passband RF signals, polarization and signal bandwidth. Other topics covered include time domain, mutual coupling, wideband elements, and dispersion. The auth

A Time-Varied Probabilistic ON/OFF Switching Algorithm for Cellular Networks

KAUST Repository

Rached, Nadhir B.; Ghazzai, Hakim; Kadri, Abdullah; Alouini, Mohamed-Slim

2018-01-01

In this letter, we develop a time-varied probabilistic on/off switching planning method for cellular networks to reduce their energy consumption. It consists in a risk-aware optimization approach that takes into consideration the randomness of the user profile associated with each base station (BS). The proposed approach jointly determines (i) the instants of time at which the current active BS configuration must be updated due to an increase or decrease of the network traffic load, and (ii) the set of minimum BSs to be activated to serve the networks’ subscribers. Probabilistic metrics modeling the traffic profile variation are developed to trigger this dynamic on/off switching operation. Selected simulation results are then performed to validate the proposed algorithm for different system parameters.

A Time-Varied Probabilistic ON/OFF Switching Algorithm for Cellular Networks

KAUST Repository

Rached, Nadhir B.

2018-01-11

In this letter, we develop a time-varied probabilistic on/off switching planning method for cellular networks to reduce their energy consumption. It consists in a risk-aware optimization approach that takes into consideration the randomness of the user profile associated with each base station (BS). The proposed approach jointly determines (i) the instants of time at which the current active BS configuration must be updated due to an increase or decrease of the network traffic load, and (ii) the set of minimum BSs to be activated to serve the networks’ subscribers. Probabilistic metrics modeling the traffic profile variation are developed to trigger this dynamic on/off switching operation. Selected simulation results are then performed to validate the proposed algorithm for different system parameters.

Heterogeneous continuous-time random walks

Science.gov (United States)

Grebenkov, Denis S.; Tupikina, Liubov

2018-01-01

We introduce a heterogeneous continuous-time random walk (HCTRW) model as a versatile analytical formalism for studying and modeling diffusion processes in heterogeneous structures, such as porous or disordered media, multiscale or crowded environments, weighted graphs or networks. We derive the exact form of the propagator and investigate the effects of spatiotemporal heterogeneities onto the diffusive dynamics via the spectral properties of the generalized transition matrix. In particular, we show how the distribution of first-passage times changes due to local and global heterogeneities of the medium. The HCTRW formalism offers a unified mathematical language to address various diffusion-reaction problems, with numerous applications in material sciences, physics, chemistry, biology, and social sciences.

Effect of time varying phosphorus implantation on optoelectronics properties of RF sputtered ZnO thin-films

Science.gov (United States)

Murkute, Punam; Ghadi, Hemant; Saha, Shantanu; Chavan, Vinayak; Chakrabarti, Subhananda

2018-03-01

ZnO has potential application in the field of short wavelength devices like LED's, laser diodes, UV detectors etc, because of its wide band gap (3.34 eV) and high exciton binding energy (60 meV). ZnO possess N-type conductivity due to presence of defects arising from oxygen and zinc interstitial vacancies. In order to achieve P-type or intrinsic carrier concentration an implantation study is preferred. In this report, we have varied phosphorous implantation time and studied its effect on optical as well structural properties of RF sputtered ZnO thin-films. Implantation was carried out using Plasma Immersion ion implantation technique for 10 and 20 s. These films were further annealed at 900°C for 10 s in oxygen ambient to activate phosphorous dopants. Low temperature photoluminescence (PL) spectra measured two distinct peaks at 3.32 and 3.199 eV for 20 s implanted sample annealed at 900°C. Temperature dependent PL measurement shows slightly blue shift in peak position from 18 K to 300 K. 3.199 eV peak can be attributed to donoracceptor pair (DAP) emission and 3.32 eV peak corresponds to conduction-band-to-acceptor (eA0) transition. High resolution x-ray diffraction revels dominant (002) peak from all samples. Increasing implantation time resulted in low peak intensity suggesting a formation of implantation related defects. Compression in C-axis with implantation time indicates incorporation of phosphorus in the formed film. Improvement in surface quality was observed from 20 s implanted sample which annealed at 900°C.

Stability in Cohen Grossberg-type bidirectional associative memory neural networks with time-varying delays

Science.gov (United States)

Cao, Jinde; Song, Qiankun

2006-07-01

In this paper, the exponential stability problem is investigated for a class of Cohen-Grossberg-type bidirectional associative memory neural networks with time-varying delays. By using the analysis method, inequality technique and the properties of an M-matrix, several novel sufficient conditions ensuring the existence, uniqueness and global exponential stability of the equilibrium point are derived. Moreover, the exponential convergence rate is estimated. The obtained results are less restrictive than those given in the earlier literature, and the boundedness and differentiability of the activation functions and differentiability of the time-varying delays are removed. Two examples with their simulations are given to show the effectiveness of the obtained results.

Long time tails in stationary random media II: Applications

NARCIS (Netherlands)

Machta, J.; Ernst, M.H.; Dorfman, J.R.; Beijeren, H. van

1984-01-01

In a previous paper we developed a mode-coupling theory to describe the long time properties of diffusion in stationary, statistically homogeneous, random media. Here the general theory is applied to deterministic and stochastic Lorentz models and several hopping models. The mode-coupling theory

A note on "Multicriteria adaptive paths in stochastic, time-varying networks"

DEFF Research Database (Denmark)

Pretolani, Daniele; Nielsen, Lars Relund; Andersen, Kim Allan

In a recent paper, Opasanon and Miller-Hooks study multicriteria adaptive paths in stochastic time-varying networks. They propose a label correcting algorithm for finding the full set of efficient strategies. In this note we show that their algorithm is not correct, since it is based on a property...... that does not hold in general. Opasanon and Miller-Hooks also propose an algorithm for solving a parametric problem. We give a simplified algorithm which is linear in the input size....

Time-varying value of electric energy efficiency

Energy Technology Data Exchange (ETDEWEB)

Mims, Natalie A.; Eckman, Tom; Goldman, Charles

2017-06-30

Electric energy efficiency resources save energy and may reduce peak demand. Historically, quantification of energy efficiency benefits has largely focused on the economic value of energy savings during the first year and lifetime of the installed measures. Due in part to the lack of publicly available research on end-use load shapes (i.e., the hourly or seasonal timing of electricity savings) and energy savings shapes, consideration of the impact of energy efficiency on peak demand reduction (i.e., capacity savings) has been more limited. End-use load research and the hourly valuation of efficiency savings are used for a variety of electricity planning functions, including load forecasting, demand-side management and evaluation, capacity and demand response planning, long-term resource planning, renewable energy integration, assessing potential grid modernization investments, establishing rates and pricing, and customer service. This study reviews existing literature on the time-varying value of energy efficiency savings, provides examples in four geographically diverse locations of how consideration of the time-varying value of efficiency savings impacts the calculation of power system benefits, and identifies future research needs to enhance the consideration of the time-varying value of energy efficiency in cost-effectiveness screening analysis. Findings from this study include: -The time-varying value of individual energy efficiency measures varies across the locations studied because of the physical and operational characteristics of the individual utility system (e.g., summer or winter peaking, load factor, reserve margin) as well as the time periods during which savings from measures occur. -Across the four locations studied, some of the largest capacity benefits from energy efficiency are derived from the deferral of transmission and distribution system infrastructure upgrades. However, the deferred cost of such upgrades also exhibited the greatest range

Statistical properties of several models of fractional random point processes

Science.gov (United States)

Bendjaballah, C.

2011-08-01

Statistical properties of several models of fractional random point processes have been analyzed from the counting and time interval statistics points of view. Based on the criterion of the reduced variance, it is seen that such processes exhibit nonclassical properties. The conditions for these processes to be treated as conditional Poisson processes are examined. Numerical simulations illustrate part of the theoretical calculations.

Global exponential stability of BAM neural networks with time-varying delays and diffusion terms

International Nuclear Information System (INIS)

Wan Li; Zhou Qinghua

2007-01-01

The stability property of bidirectional associate memory (BAM) neural networks with time-varying delays and diffusion terms are considered. By using the method of variation parameter and inequality technique, the delay-independent sufficient conditions to guarantee the uniqueness and global exponential stability of the equilibrium solution of such networks are established

Global exponential stability of BAM neural networks with time-varying delays and diffusion terms

Science.gov (United States)

Wan, Li; Zhou, Qinghua

2007-11-01

The stability property of bidirectional associate memory (BAM) neural networks with time-varying delays and diffusion terms are considered. By using the method of variation parameter and inequality technique, the delay-independent sufficient conditions to guarantee the uniqueness and global exponential stability of the equilibrium solution of such networks are established.

Pemodelan Markov Switching Dengan Time-varying Transition Probability

OpenAIRE

Savitri, Anggita Puri; Warsito, Budi; Rahmawati, Rita

2016-01-01

Exchange rate or currency is an economic variable which reflects country's state of economy. It fluctuates over time because of its ability to switch the condition or regime caused by economic and political factors. The changes in the exchange rate are depreciation and appreciation. Therefore, it could be modeled using Markov Switching with Time-Varying Transition Probability which observe the conditional changes and use information variable. From this model, time-varying transition probabili...

Soil erosion under multiple time-varying rainfall events

Science.gov (United States)

Heng, B. C. Peter; Barry, D. Andrew; Jomaa, Seifeddine; Sander, Graham C.

2010-05-01

Soil erosion is a function of many factors and process interactions. An erosion event produces changes in surface soil properties such as texture and hydraulic conductivity. These changes in turn alter the erosion response to subsequent events. Laboratory-scale soil erosion studies have typically focused on single independent rainfall events with constant rainfall intensities. This study investigates the effect of multiple time-varying rainfall events on soil erosion using the EPFL erosion flume. The rainfall simulator comprises ten Veejet nozzles mounted on oscillating bars 3 m above a 6 m × 2 m flume. Spray from the nozzles is applied onto the soil surface in sweeps; rainfall intensity is thus controlled by varying the sweeping frequency. Freshly-prepared soil with a uniform slope was subjected to five rainfall events at daily intervals. In each 3-h event, rainfall intensity was ramped up linearly to a maximum of 60 mm/h and then stepped down to zero. Runoff samples were collected and analysed for particle size distribution (PSD) as well as total sediment concentration. We investigate whether there is a hysteretic relationship between sediment concentration and discharge within each event and how this relationship changes from event to event. Trends in the PSD of the eroded sediment are discussed and correlated with changes in sediment concentration. Close-up imagery of the soil surface following each event highlight changes in surface soil structure with time. This study enhances our understanding of erosion processes in the field, with corresponding implications for soil erosion modelling.

Statistical analysis of random pulse trains

International Nuclear Information System (INIS)

Da Costa, G.

1977-02-01

Some experimental and theoretical results concerning the statistical properties of optical beams formed by a finite number of independent pulses are presented. The considered waves (corresponding to each pulse) present important spatial variations of the illumination distribution in a cross-section of the beam, due to the time-varying random refractive index distribution in the active medium. Some examples of this kind of emission are: (a) Free-running ruby laser emission; (b) Mode-locked pulse trains; (c) Randomly excited nonlinear media

Critical Properties of Pure and Random Antiferromagnets

DEFF Research Database (Denmark)

Cowley, R. A.; Carneiro, K.

1980-01-01

Neutron scattering techniques have been used to study the critical properties of CoF2 and the randomly mixed systems: Co/ZnF2 and KMn/NiF3. The results for CoF2 are in excellent accord with the critical properties of the three-dimensional Ising model. In all of the random crystals studied the tra...

Solution Methods for Structures with Random Properties Subject to Random Excitation

DEFF Research Database (Denmark)

Köylüoglu, H. U.; Nielsen, Søren R. K.; Cakmak, A. S.

This paper deals with the lower order statistical moments of the response of structures with random stiffness and random damping properties subject to random excitation. The arising stochastic differential equations (SDE) with random coefficients are solved by two methods, a second order...... the SDE with random coefficients with deterministic initial conditions to an equivalent nonlinear SDE with deterministic coefficient and random initial conditions. In both methods, the statistical moment equations are used. Hierarchy of statistical moments in the markovian approach is closed...... by the cumulant neglect closure method applied at the fourth order level....

Experimental evidence for amplitude death induced by a time-varying interaction

Energy Technology Data Exchange (ETDEWEB)

Suresh, K. [Centre for Nonlinear Dynamics, School of Physics, Bharathidasan University, Tiruchirappalli 620024, Tamil Nadu (India); Shrimali, M.D. [Department of Physics, Central University of Rajasthan, NH-8, Bandar Sindri, Ajmer 305 801 (India); Prasad, Awadhesh [Department of Physics and Astrophysics, University of Delhi, Delhi 110 007 (India); Thamilmaran, K., E-mail: maran.cnld@gmail.com [Centre for Nonlinear Dynamics, School of Physics, Bharathidasan University, Tiruchirappalli 620024, Tamil Nadu (India)

2014-08-01

In this paper, we study the time-varying interaction in coupled oscillatory systems. For this purpose, we have designed a novel time-varying resistive network using an analog switch and inverter circuits. We have applied this time-varying resistive network to mutually coupled identical Chua's oscillators. When the resistances are varied in time, we find that amplitude death arises in coupled identical oscillators. This has been observed numerically as well as verified through hardware experiments. - Highlights: • We have implemented the time-varying interaction in coupled oscillatory systems. • We have designed a novel time-varying resistive network using an analog switch and inverter circuits. • When the resistances are varied in time, we find that amplitude death arises in coupled identical oscillators.

First passage times for combinations of random loads

OpenAIRE

Jacobs, Patricia A.

1985-01-01

Structures are subject to changing loads from various sources. In many instances these loads fluctuate in time apparently random fashion. Models are considered for which the stress put on the structure by various loads simultaneously can be described by a regenerative process. The distribution of the first time until the stress on the structure exceeds a given level x is studied. Asymptotic properties of the distribution are given for a large stress level x and for the tail of the distributio...

On exponential stability of bidirectional associative memory neural networks with time-varying delays

International Nuclear Information System (INIS)

Park, Ju H.; Lee, S.M.; Kwon, O.M.

2009-01-01

For bidirectional associate memory neural networks with time-varying delays, the problems of determining the exponential stability and estimating the exponential convergence rate are investigated by employing the Lyapunov functional method and linear matrix inequality (LMI) technique. A novel criterion for the stability, which give information on the delay-dependent property, is derived. A numerical example is given to demonstrate the effectiveness of the obtained results.

Analysis of time-varying psoriasis lesion image patterns

DEFF Research Database (Denmark)

Maletti, Gabriela Mariel; Ersbøll, Bjarne Kjær; Nielsen, Allan Aasbjerg

2004-01-01

The multivariate alteration detection transform is applied to pairs of within and between time varying registered psoriasis image patterns. Color band contribution to the variates explaining maximal change is analyzed.......The multivariate alteration detection transform is applied to pairs of within and between time varying registered psoriasis image patterns. Color band contribution to the variates explaining maximal change is analyzed....

Optical properties of Al nanostructures from time dependent density functional theory

KAUST Repository

Mokkath, Junais Habeeb; Schwingenschlö gl, Udo

2016-01-01

The optical properties of Al nanostructures are investigated by means of time dependent density functional theory, considering chains of varying length and ladders/stripes of varying aspect ratio. The absorption spectra show redshifting

Variable Selection in Time Series Forecasting Using Random Forests

Directory of Open Access Journals (Sweden)

Hristos Tyralis

2017-10-01

Full Text Available Time series forecasting using machine learning algorithms has gained popularity recently. Random forest is a machine learning algorithm implemented in time series forecasting; however, most of its forecasting properties have remained unexplored. Here we focus on assessing the performance of random forests in one-step forecasting using two large datasets of short time series with the aim to suggest an optimal set of predictor variables. Furthermore, we compare its performance to benchmarking methods. The first dataset is composed by 16,000 simulated time series from a variety of Autoregressive Fractionally Integrated Moving Average (ARFIMA models. The second dataset consists of 135 mean annual temperature time series. The highest predictive performance of RF is observed when using a low number of recent lagged predictor variables. This outcome could be useful in relevant future applications, with the prospect to achieve higher predictive accuracy.

Time-Varying Value of Energy Efficiency in Michigan

Energy Technology Data Exchange (ETDEWEB)

Mims, Natalie; Eckman, Tom; Schwartz, Lisa C.

2018-04-02

Quantifying the time-varying value of energy efficiency is necessary to properly account for all of its benefits and costs and to identify and implement efficiency resources that contribute to a low-cost, reliable electric system. Historically, most quantification of the benefits of efficiency has focused largely on the economic value of annual energy reduction. Due to the lack of statistically representative metered end-use load shape data in Michigan (i.e., the hourly or seasonal timing of electricity savings), the ability to confidently characterize the time-varying value of energy efficiency savings in the state, especially for weather-sensitive measures such as central air conditioning, is limited. Still, electric utilities in Michigan can take advantage of opportunities to incorporate the time-varying value of efficiency into their planning. For example, end-use load research and hourly valuation of efficiency savings can be used for a variety of electricity planning functions, including load forecasting, demand-side management and evaluation, capacity planning, long-term resource planning, renewable energy integration, assessing potential grid modernization investments, establishing rates and pricing, and customer service (KEMA 2012). In addition, accurately calculating the time-varying value of efficiency may help energy efficiency program administrators prioritize existing offerings, set incentive or rebate levels that reflect the full value of efficiency, and design new programs.

Multivariate time-varying volatility modeling using probabilistic fuzzy systems

NARCIS (Netherlands)

Basturk, N.; Almeida, R.J.; Golan, R.; Kaymak, U.

2016-01-01

Methods to accurately analyze financial risk have drawn considerable attention in financial institutions. One difficulty in financial risk analysis is the fact that banks and other financial institutions invest in several assets which show time-varying volatilities and hence time-varying financial

Cover times of random searches

Science.gov (United States)

Chupeau, Marie; Bénichou, Olivier; Voituriez, Raphaël

2015-10-01

How long must one undertake a random search to visit all sites of a given domain? This time, known as the cover time, is a key observable to quantify the efficiency of exhaustive searches, which require a complete exploration of an area and not only the discovery of a single target. Examples range from immune-system cells chasing pathogens to animals harvesting resources, from robotic exploration for cleaning or demining to the task of improving search algorithms. Despite its broad relevance, the cover time has remained elusive and so far explicit results have been scarce and mostly limited to regular random walks. Here we determine the full distribution of the cover time for a broad range of random search processes, including Lévy strategies, intermittent strategies, persistent random walks and random walks on complex networks, and reveal its universal features. We show that for all these examples the mean cover time can be minimized, and that the corresponding optimal strategies also minimize the mean search time for a single target, unambiguously pointing towards their robustness.

Long memory of financial time series and hidden Markov models with time-varying parameters

DEFF Research Database (Denmark)

Nystrup, Peter; Madsen, Henrik; Lindström, Erik

Hidden Markov models are often used to capture stylized facts of daily returns and to infer the hidden state of financial markets. Previous studies have found that the estimated models change over time, but the implications of the time-varying behavior for the ability to reproduce the stylized...... facts have not been thoroughly examined. This paper presents an adaptive estimation approach that allows for the parameters of the estimated models to be time-varying. It is shown that a two-state Gaussian hidden Markov model with time-varying parameters is able to reproduce the long memory of squared...... daily returns that was previously believed to be the most difficult fact to reproduce with a hidden Markov model. Capturing the time-varying behavior of the parameters also leads to improved one-step predictions....

Coupled continuous time-random walks in quenched random environment

Science.gov (United States)

Magdziarz, M.; Szczotka, W.

2018-02-01

We introduce a coupled continuous-time random walk with coupling which is characteristic for Lévy walks. Additionally we assume that the walker moves in a quenched random environment, i.e. the site disorder at each lattice point is fixed in time. We analyze the scaling limit of such a random walk. We show that for large times the behaviour of the analyzed process is exactly the same as in the case of uncoupled quenched trap model for Lévy flights.

Emergence of synchronization and regularity in firing patterns in time-varying neural hypernetworks

Science.gov (United States)

Rakshit, Sarbendu; Bera, Bidesh K.; Ghosh, Dibakar; Sinha, Sudeshna

2018-05-01

We study synchronization of dynamical systems coupled in time-varying network architectures, composed of two or more network topologies, corresponding to different interaction schemes. As a representative example of this class of time-varying hypernetworks, we consider coupled Hindmarsh-Rose neurons, involving two distinct types of networks, mimicking interactions that occur through the electrical gap junctions and the chemical synapses. Specifically, we consider the connections corresponding to the electrical gap junctions to form a small-world network, while the chemical synaptic interactions form a unidirectional random network. Further, all the connections in the hypernetwork are allowed to change in time, modeling a more realistic neurobiological scenario. We model this time variation by rewiring the links stochastically with a characteristic rewiring frequency f . We find that the coupling strength necessary to achieve complete neuronal synchrony is lower when the links are switched rapidly. Further, the average time required to reach the synchronized state decreases as synaptic coupling strength and/or rewiring frequency increases. To quantify the local stability of complete synchronous state we use the Master Stability Function approach, and for global stability we employ the concept of basin stability. The analytically derived necessary condition for synchrony is in excellent agreement with numerical results. Further we investigate the resilience of the synchronous states with respect to increasing network size, and we find that synchrony can be maintained up to larger network sizes by increasing either synaptic strength or rewiring frequency. Last, we find that time-varying links not only promote complete synchronization, but also have the capacity to change the local dynamics of each single neuron. Specifically, in a window of rewiring frequency and synaptic coupling strength, we observe that the spiking behavior becomes more regular.

Overcoming Spurious Regression Using time-Varying Fourier ...

African Journals Online (AJOL)

Non-stationary time series data have been traditionally analyzed in the frequency domain by assuming constant amplitudes regardless of the timelag. A new approach called time-varying amplitude method (TVAM) is presented here. Oscillations are analyzed for changes in the magnitude of Fourier Coefficients which are ...

Vesicle biomechanics in a time-varying magnetic field.

Science.gov (United States)

Ye, Hui; Curcuru, Austen

2015-01-01

Cells exhibit distortion when exposed to a strong electric field, suggesting that the field imposes control over cellular biomechanics. Closed pure lipid bilayer membranes (vesicles) have been widely used for the experimental and theoretical studies of cellular biomechanics under this electrodeformation. An alternative method used to generate an electric field is by electromagnetic induction with a time-varying magnetic field. References reporting the magnetic control of cellular mechanics have recently emerged. However, theoretical analysis of the cellular mechanics under a time-varying magnetic field is inadequate. We developed an analytical theory to investigate the biomechanics of a modeled vesicle under a time-varying magnetic field. Following previous publications and to simplify the calculation, this model treated the inner and suspending media as lossy dielectrics, the membrane thickness set at zero, and the electric resistance of the membrane assumed to be negligible. This work provided the first analytical solutions for the surface charges, electric field, radial pressure, overall translational forces, and rotational torques introduced on a vesicle by the time-varying magnetic field. Frequency responses of these measures were analyzed, particularly the frequency used clinically by transcranial magnetic stimulation (TMS). The induced surface charges interacted with the electric field to produce a biomechanical impact upon the vesicle. The distribution of the induced surface charges depended on the orientation of the coil and field frequency. The densities of these charges were trivial at low frequency ranges, but significant at high frequency ranges. The direction of the radial force on the vesicle was dependent on the conductivity ratio between the vesicle and the medium. At relatively low frequencies (biomechanics under a time-varying magnetic field. Biological effects of clinical TMS are not likely to occur via alteration of the biomechanics of brain

Probability, random processes, and ergodic properties

CERN Document Server

Gray, Robert M

1988-01-01

This book has been written for several reasons, not all of which are academic. This material was for many years the first half of a book in progress on information and ergodic theory. The intent was and is to provide a reasonably self-contained advanced treatment of measure theory, prob ability theory, and the theory of discrete time random processes with an emphasis on general alphabets and on ergodic and stationary properties of random processes that might be neither ergodic nor stationary. The intended audience was mathematically inc1ined engineering graduate students and visiting scholars who had not had formal courses in measure theoretic probability . Much of the material is familiar stuff for mathematicians, but many of the topics and results have not previously appeared in books. The original project grew too large and the first part contained much that would likely bore mathematicians and dis courage them from the second part. Hence I finally followed the suggestion to separate the material and split...

Generalized Dynamic Panel Data Models with Random Effects for Cross-Section and Time

NARCIS (Netherlands)

Mesters, G.; Koopman, S.J.

2014-01-01

An exact maximum likelihood method is developed for the estimation of parameters in a nonlinear non-Gaussian dynamic panel data model with unobserved random individual-specific and time-varying effects. We propose an estimation procedure based on the importance sampling technique. In particular, a

Modelling Time-Varying Volatility in Financial Returns

DEFF Research Database (Denmark)

Amado, Cristina; Laakkonen, Helinä

2014-01-01

The “unusually uncertain” phase in the global financial markets has inspired many researchers to study the effects of ambiguity (or “Knightian uncertainty”) on the decisions made by investors and their implications for the capital markets. We contribute to this literature by using a modified...... version of the time-varying GARCH model of Amado and Teräsvirta (2013) to analyze whether the increasing uncertainty has caused excess volatility in the US and European government bond markets. In our model, volatility is multiplicatively decomposed into two time-varying conditional components: the first...... being captured by a stable GARCH(1,1) process and the second driven by the level of uncertainty in the financial market....

Identification of time-varying nonlinear systems using differential evolution algorithm

DEFF Research Database (Denmark)

Perisic, Nevena; Green, Peter L; Worden, Keith

2013-01-01

(DE) algorithm for the identification of time-varying systems. DE is an evolutionary optimisation method developed to perform direct search in a continuous space without requiring any derivative estimation. DE is modified so that the objective function changes with time to account for the continuing......, thus identification of time-varying systems with nonlinearities can be a very challenging task. In order to avoid conventional least squares and gradient identification methods which require uni-modal and double differentiable objective functions, this work proposes a modified differential evolution...... inclusion of new data within an error metric. This paper presents results of identification of a time-varying SDOF system with Coulomb friction using simulated noise-free and noisy data for the case of time-varying friction coefficient, stiffness and damping. The obtained results are promising and the focus...

Student throughput variables and properties: Varying cohort sizes

Directory of Open Access Journals (Sweden)

Lucas C.A. Stoop

2017-11-01

Full Text Available A recent research paper described how student throughput variables and properties combine to explain the behaviour of stationary or simplified throughput systems. Such behaviour can be understood in terms of the locus of a point in the triangular admissible region of the H-S plane, where H represents headcounts and S successful credits, each depending on the system properties at that point. The efficiency of the student throughput process is given by the ratio S/H. Simplified throughput systems are characterised by stationary graduation and dropout patterns of students as well as by annual intakes of student cohorts of equal size. The effect of varying the size of the annual intakes of student cohorts is reported on here. The observations made lead to the establishment of a more generalised student throughput theory which includes the simplified theory as a special case. The generalised theory still retains the notion of a triangular admissible region in the H-S plane but with the size and shape of the triangle depending on the size of the student cohorts. The ratio S/H again emerges as the process efficiency measure for throughput systems in general with unchanged roles assigned to important system properties. This theory provides for a more fundamental understanding of student throughput systems encountered in real life. Significance: A generalised stationary student throughput theory through varying cohort sizes allows for a far better understanding of real student throughput systems.

Gossip Consensus Algorithm Based on Time-Varying Influence Factors and Weakly Connected Graph for Opinion Evolution in Social Networks

Directory of Open Access Journals (Sweden)

Lingyun Li

2013-01-01

Full Text Available We provide a new gossip algorithm to investigate the problem of opinion consensus with the time-varying influence factors and weakly connected graph among multiple agents. What is more, we discuss not only the effect of the time-varying factors and the randomized topological structure but also the spread of misinformation and communication constrains described by probabilistic quantized communication in the social network. Under the underlying weakly connected graph, we first denote that all opinion states converge to a stochastic consensus almost surely; that is, our algorithm indeed achieves the consensus with probability one. Furthermore, our results show that the mean of all the opinion states converges to the average of the initial states when time-varying influence factors satisfy some conditions. Finally, we give a result about the square mean error between the dynamic opinion states and the benchmark without quantized communication.

Continuous-time random walks with reset events. Historical background and new perspectives

Science.gov (United States)

Montero, Miquel; Masó-Puigdellosas, Axel; Villarroel, Javier

2017-09-01

In this paper, we consider a stochastic process that may experience random reset events which relocate the system to its starting position. We focus our attention on a one-dimensional, monotonic continuous-time random walk with a constant drift: the process moves in a fixed direction between the reset events, either by the effect of the random jumps, or by the action of a deterministic bias. However, the orientation of its motion is randomly determined after each restart. As a result of these alternating dynamics, interesting properties do emerge. General formulas for the propagator as well as for two extreme statistics, the survival probability and the mean first-passage time, are also derived. The rigor of these analytical results is verified by numerical estimations, for particular but illuminating examples.

Time-varying linear control for tiltrotor aircraft

Directory of Open Access Journals (Sweden)

Jing ZHANG

2018-04-01

Full Text Available Tiltrotor aircraft have three flight modes: helicopter mode, airplane mode, and transition mode. A tiltrotor has characteristics of highly nonlinear, time-varying flight dynamics and inertial/control couplings in its transition mode. It can transit from the helicopter mode to the airplane mode by tilting its nacelles, and an effective controller is crucial to accomplish tilting transition missions. Longitudinal dynamic characteristics of the tiltrotor are described by a nonlinear Lagrange-form model, which takes into account inertial/control couplings and aerodynamic interferences. Reference commands for airspeed velocity and attitude in the transition mode are calculated dynamically by visiting a command library which is founded in advance by analyzing the flight envelope of the tiltrotor. A Time-Varying Linear (TVL model is obtained using a Taylor-expansion based online linearization technique from the nonlinear model. Subsequently, based on an optimal control concept, an online optimization based control method with input constraints considered is proposed. To validate the proposed control method, three typical tilting transition missions are simulated using the nonlinear model of XV-15 tiltrotor aircraft. Simulation results show that the controller can be used to control the tiltrotor throughout its operating envelop which includes a transition flight, and can also deal with vertical gust disturbances. Keywords: Constrained optimal control, Inertia/control couplings, Tiltrotor aircraft, Time-varying control, Transition mode

Identification of Time-Varying Pilot Control Behavior in Multi-Axis Control Tasks

Science.gov (United States)

Zaal, Peter M. T.; Sweet, Barbara T.

2012-01-01

Recent developments in fly-by-wire control architectures for rotorcraft have introduced new interest in the identification of time-varying pilot control behavior in multi-axis control tasks. In this paper a maximum likelihood estimation method is used to estimate the parameters of a pilot model with time-dependent sigmoid functions to characterize time-varying human control behavior. An experiment was performed by 9 general aviation pilots who had to perform a simultaneous roll and pitch control task with time-varying aircraft dynamics. In 8 different conditions, the axis containing the time-varying dynamics and the growth factor of the dynamics were varied, allowing for an analysis of the performance of the estimation method when estimating time-dependent parameter functions. In addition, a detailed analysis of pilots adaptation to the time-varying aircraft dynamics in both the roll and pitch axes could be performed. Pilot control behavior in both axes was significantly affected by the time-varying aircraft dynamics in roll and pitch, and by the growth factor. The main effect was found in the axis that contained the time-varying dynamics. However, pilot control behavior also changed over time in the axis not containing the time-varying aircraft dynamics. This indicates that some cross coupling exists in the perception and control processes between the roll and pitch axes.

Testing for time-varying loadings in dynamic factor models

DEFF Research Database (Denmark)

Mikkelsen, Jakob Guldbæk

Abstract: In this paper we develop a test for time-varying factor loadings in factor models. The test is simple to compute and is constructed from estimated factors and residuals using the principal components estimator. The hypothesis is tested by regressing the squared residuals on the squared...... there is evidence of time-varying loadings on the risk factors underlying portfolio returns for around 80% of the portfolios....

Time-Varying Periodicity in Intraday Volatility

DEFF Research Database (Denmark)

Andersen, Torben Gustav; Thyrsgaard, Martin; Todorov, Viktor

We develop a nonparametric test for deciding whether return volatility exhibits time-varying intraday periodicity using a long time-series of high-frequency data. Our null hypothesis, commonly adopted in work on volatility modeling, is that volatility follows a stationary process combined...... with a constant time-of-day periodic component. We first construct time-of-day volatility estimates and studentize the high-frequency returns with these periodic components. If the intraday volatility periodicity is invariant over time, then the distribution of the studentized returns should be identical across...... with estimating volatility moments through their sample counterparts. Critical values are computed via easy-to-implement simulation. In an empirical application to S&P 500 index returns, we find strong evidence for variation in the intraday volatility pattern driven in part by the current level of volatility...

The deformation of the front of a 3D interface crack propagating quasistatically in a medium with random fracture properties

Science.gov (United States)

Pindra, Nadjime; Lazarus, Véronique; Leblond, Jean-Baptiste

One studies the evolution in time of the deformation of the front of a semi-infinite 3D interface crack propagating quasistatically in an infinite heterogeneous elastic body. The fracture properties are assumed to be lower on the interface than in the materials so that crack propagation is channelled along the interface, and to vary randomly within the crack plane. The work is based on earlier formulae which provide the first-order change of the stress intensity factors along the front of a semi-infinite interface crack arising from some small but otherwise arbitrary in-plane perturbation of this front. The main object of study is the long-time behavior of various statistical measures of the deformation of the crack front. Special attention is paid to the influences of the mismatch of elastic properties, the type of propagation law (fatigue or brittle fracture) and the stable or unstable character of 2D crack propagation (depending on the loading) upon the development of this deformation.

Tendon material properties vary and are interdependent among turkey hindlimb muscles.

Science.gov (United States)

Matson, Andrew; Konow, Nicolai; Miller, Samuel; Konow, Pernille P; Roberts, Thomas J

2012-10-15

The material properties of a tendon affect its ability to store and return elastic energy, resist damage, provide mechanical feedback and amplify or attenuate muscle power. While the structural properties of a tendon are known to respond to a variety of stimuli, the extent to which material properties vary among individual muscles remains unclear. We studied the tendons of six different muscles in the hindlimb of Eastern wild turkeys to determine whether there was variation in elastic modulus, ultimate tensile strength and resilience. A hydraulic testing machine was used to measure tendon force during quasi-static lengthening, and a stress-strain curve was constructed. There was substantial variation in tendon material properties among different muscles. Average elastic modulus differed significantly between some tendons, and values for the six different tendons varied nearly twofold, from 829±140 to 1479±106 MPa. Tendons were stretched to failure, and the stress at failure, or ultimate tensile stress, was taken as a lower-limit estimate of tendon strength. Breaking tests for four of the tendons revealed significant variation in ultimate tensile stress, ranging from 66.83±14.34 to 112.37±9.39 MPa. Resilience, or the fraction of energy returned in cyclic length changes was generally high, and one of the four tendons tested was significantly different in resilience from the other tendons (range: 90.65±0.83 to 94.02±0.71%). An analysis of correlation between material properties revealed a positive relationship between ultimate tensile strength and elastic modulus (r(2)=0.79). Specifically, stiffer tendons were stronger, and we suggest that this correlation results from a constrained value of breaking strain, which did not vary significantly among tendons. This finding suggests an interdependence of material properties that may have a structural basis and may explain some adaptive responses observed in studies of tendon plasticity.

Errors in 'BED'-derived estimates of HIV incidence will vary by place, time and age.

Directory of Open Access Journals (Sweden)

Timothy B Hallett

2009-05-01

Full Text Available The BED Capture Enzyme Immunoassay, believed to distinguish recent HIV infections, is being used to estimate HIV incidence, although an important property of the test--how specificity changes with time since infection--has not been not measured.We construct hypothetical scenarios for the performance of BED test, consistent with current knowledge, and explore how this could influence errors in BED estimates of incidence using a mathematical model of six African countries. The model is also used to determine the conditions and the sample sizes required for the BED test to reliably detect trends in HIV incidence.If the chance of misclassification by BED increases with time since infection, the overall proportion of individuals misclassified could vary widely between countries, over time, and across age-groups, in a manner determined by the historic course of the epidemic and the age-pattern of incidence. Under some circumstances, changes in BED estimates over time can approximately track actual changes in incidence, but large sample sizes (50,000+ will be required for recorded changes to be statistically significant.The relationship between BED test specificity and time since infection has not been fully measured, but, if it decreases, errors in estimates of incidence could vary by place, time and age-group. This means that post-assay adjustment procedures using parameters from different populations or at different times may not be valid. Further research is urgently needed into the properties of the BED test, and the rate of misclassification in a wide range of populations.

Finite-Time Stability of Large-Scale Systems with Interval Time-Varying Delay in Interconnection

Directory of Open Access Journals (Sweden)

T. La-inchua

2017-01-01

Full Text Available We investigate finite-time stability of a class of nonlinear large-scale systems with interval time-varying delays in interconnection. Time-delay functions are continuous but not necessarily differentiable. Based on Lyapunov stability theory and new integral bounding technique, finite-time stability of large-scale systems with interval time-varying delays in interconnection is derived. The finite-time stability criteria are delays-dependent and are given in terms of linear matrix inequalities which can be solved by various available algorithms. Numerical examples are given to illustrate effectiveness of the proposed method.

Time-varying multiplex network: Intralayer and interlayer synchronization

Science.gov (United States)

Rakshit, Sarbendu; Majhi, Soumen; Bera, Bidesh K.; Sinha, Sudeshna; Ghosh, Dibakar

2017-12-01

A large class of engineered and natural systems, ranging from transportation networks to neuronal networks, are best represented by multiplex network architectures, namely a network composed of two or more different layers where the mutual interaction in each layer may differ from other layers. Here we consider a multiplex network where the intralayer coupling interactions are switched stochastically with a characteristic frequency. We explore the intralayer and interlayer synchronization of such a time-varying multiplex network. We find that the analytically derived necessary condition for intralayer and interlayer synchronization, obtained by the master stability function approach, is in excellent agreement with our numerical results. Interestingly, we clearly find that the higher frequency of switching links in the layers enhances both intralayer and interlayer synchrony, yielding larger windows of synchronization. Further, we quantify the resilience of synchronous states against random perturbations, using a global stability measure based on the concept of basin stability, and this reveals that intralayer coupling strength is most crucial for determining both intralayer and interlayer synchrony. Lastly, we investigate the robustness of interlayer synchronization against a progressive demultiplexing of the multiplex structure, and we find that for rapid switching of intralayer links, the interlayer synchronization persists even when a large number of interlayer nodes are disconnected.

Do Time-Varying Covariances, Volatility Comovement and Spillover Matter?

OpenAIRE

Lakshmi Balasubramanyan

2005-01-01

Financial markets and their respective assets are so intertwined; analyzing any single market in isolation ignores important information. We investigate whether time varying volatility comovement and spillover impact the true variance-covariance matrix under a time-varying correlation set up. Statistically significant volatility spillover and comovement between US, UK and Japan is found. To demonstrate the importance of modelling volatility comovement and spillover, we look at a simple portfo...

Asymptotic Properties of Multistate Random Walks. II. Applications to Inhomogeneous Periodic and Random Lattices

NARCIS (Netherlands)

Roerdink, J.B.T.M.; Shuler, K.E.

1985-01-01

The previously developed formalism for the calculation of asymptotic properties of multistate random walks is used to study random walks on several inhomogeneous periodic lattices, where the periodically repeated unit cell contains a number of inequivalent sites, as well as on lattices with a random

Asymptotic theory of time varying networks with burstiness and heterogeneous activation patterns

Science.gov (United States)

Burioni, Raffaella; Ubaldi, Enrico; Vezzani, Alessandro

2017-05-01

The recent availability of large-scale, time-resolved and high quality digital datasets has allowed for a deeper understanding of the structure and properties of many real-world networks. The empirical evidence of a temporal dimension prompted the switch of paradigm from a static representation of networks to a time varying one. In this work we briefly review the framework of time-varying-networks in real world social systems, especially focusing on the activity-driven paradigm. We develop a framework that allows for the encoding of three generative mechanisms that seem to play a central role in the social networks’ evolution: the individual’s propensity to engage in social interactions, its strategy in allocate these interactions among its alters and the burstiness of interactions amongst social actors. The functional forms and probability distributions encoding these mechanisms are typically data driven. A natural question arises if different classes of strategies and burstiness distributions, with different local scale behavior and analogous asymptotics can lead to the same long time and large scale structure of the evolving networks. We consider the problem in its full generality, by investigating and solving the system dynamics in the asymptotic limit, for general classes of ties allocation mechanisms and waiting time probability distributions. We show that the asymptotic network evolution is driven by a few characteristics of these functional forms, that can be extracted from direct measurements on large datasets.

Study of selected phenotype switching strategies in time varying environment

Energy Technology Data Exchange (ETDEWEB)

Horvath, Denis, E-mail: horvath.denis@gmail.com [Centre of Interdisciplinary Biosciences, Institute of Physics, Faculty of Science, P.J. Šafárik University in Košice, Jesenná 5, 040 01 Košice (Slovakia); Brutovsky, Branislav, E-mail: branislav.brutovsky@upjs.sk [Department of Biophysics, Institute of Physics, P.J. Šafárik University in Košice, Jesenná 5, 040 01 Košice (Slovakia)

2016-03-22

Population heterogeneity plays an important role across many research, as well as the real-world, problems. The population heterogeneity relates to the ability of a population to cope with an environment change (or uncertainty) preventing its extinction. However, this ability is not always desirable as can be exemplified by an intratumor heterogeneity which positively correlates with the development of resistance to therapy. Causation of population heterogeneity is therefore in biology and medicine an intensively studied topic. In this paper the evolution of a specific strategy of population diversification, the phenotype switching, is studied at a conceptual level. The presented simulation model studies evolution of a large population of asexual organisms in a time-varying environment represented by a stochastic Markov process. Each organism disposes with a stochastic or nonlinear deterministic switching strategy realized by discrete-time models with evolvable parameters. We demonstrate that under rapidly varying exogenous conditions organisms operate in the vicinity of the bet-hedging strategy, while the deterministic patterns become relevant as the environmental variations are less frequent. Statistical characterization of the steady state regimes of the populations is done using the Hellinger and Kullback–Leibler functional distances and the Hamming distance. - Highlights: • Relation between phenotype switching and environment is studied. • The Markov chain Monte Carlo based model is developed. • Stochastic and deterministic strategies of phenotype switching are utilized. • Statistical measures of the dynamic heterogeneity reveal universal properties. • The results extend to higher lattice dimensions.

Study of selected phenotype switching strategies in time varying environment

International Nuclear Information System (INIS)

Horvath, Denis; Brutovsky, Branislav

2016-01-01

Population heterogeneity plays an important role across many research, as well as the real-world, problems. The population heterogeneity relates to the ability of a population to cope with an environment change (or uncertainty) preventing its extinction. However, this ability is not always desirable as can be exemplified by an intratumor heterogeneity which positively correlates with the development of resistance to therapy. Causation of population heterogeneity is therefore in biology and medicine an intensively studied topic. In this paper the evolution of a specific strategy of population diversification, the phenotype switching, is studied at a conceptual level. The presented simulation model studies evolution of a large population of asexual organisms in a time-varying environment represented by a stochastic Markov process. Each organism disposes with a stochastic or nonlinear deterministic switching strategy realized by discrete-time models with evolvable parameters. We demonstrate that under rapidly varying exogenous conditions organisms operate in the vicinity of the bet-hedging strategy, while the deterministic patterns become relevant as the environmental variations are less frequent. Statistical characterization of the steady state regimes of the populations is done using the Hellinger and Kullback–Leibler functional distances and the Hamming distance. - Highlights: • Relation between phenotype switching and environment is studied. • The Markov chain Monte Carlo based model is developed. • Stochastic and deterministic strategies of phenotype switching are utilized. • Statistical measures of the dynamic heterogeneity reveal universal properties. • The results extend to higher lattice dimensions.

Newtonian cosmology with a time-varying constant of gravitation

International Nuclear Information System (INIS)

McVittie, G.C.

1978-01-01

Newtonian cosmology is based on the Eulerian equations of fluid mechanics combined with Poisson's equation modified by the introduction of a time-varying G. Spherically symmetric model universes are worked out with instantaneously uniform densities. They are indeterminate unless instantaneous uniformity of the pressure is imposed. When G varies as an inverse power of the time, the models can in some cases be shown to depend on the solution of a second-order differential equation which also occurs in the Friedmann models of general relativity. In Section 3, a method for 'passing through' a singularity of this equation is proposed which entails making four arbitrary mathematical assumptions. When G varies as (time) -1 , models with initially cycloidal motion are possible, each cycle becoming longer as time progresses. Finally, gravitation becomes so weak that the model expands to infinity. Kinetic and potential energies for the whole model are derived from the basic equations; their sum is not constant. (author)

Modeling of Electricity Demand for Azerbaijan: Time-Varying Coefficient Cointegration Approach

Directory of Open Access Journals (Sweden)

Jeyhun I. Mikayilov

2017-11-01

Full Text Available Recent literature has shown that electricity demand elasticities may not be constant over time and this has investigated using time-varying estimation methods. As accurate modeling of electricity demand is very important in Azerbaijan, which is a transitional country facing significant change in its economic outlook, we analyze whether the response of electricity demand to income and price is varying over time in this economy. We employed the Time-Varying Coefficient cointegration approach, a cutting-edge time-varying estimation method. We find evidence that income elasticity demonstrates sizeable variation for the period of investigation ranging from 0.48% to 0.56%. The study has some useful policy implications related to the income and price aspects of the electricity consumption in Azerbaijan.

Visualizing time-varying harmonics using filter banks

NARCIS (Netherlands)

Duque, C.A.; Da Silveira, P.M.; Ribeiro, P.F.

2011-01-01

Although it is well known that Fourier analysis is in reality only accurately applicable to steady state waveforms, it is a widely used tool to study and monitor time-varying signals, such as are commonplace in electrical power systems. The disadvantages of Fourier analysis, such as frequency

Stabilization of the Wave Equation with Boundary Time-Varying Delay

Directory of Open Access Journals (Sweden)

Hao Li

2014-01-01

Full Text Available We study the stabilization of the wave equation with variable coefficients in a bounded domain and a time-varying delay term in the time-varying, weakly nonlinear boundary feedbacks. By the Riemannian geometry methods and a suitable assumption of nonlinearity, we obtain the uniform decay of the energy of the closed loop system.

Investigating Time-Varying Drivers of Grid Project Emissions Impacts

Energy Technology Data Exchange (ETDEWEB)

Barrett, Emily L.; Thayer, Brandon L.; Pal, Seemita; Studarus, Karen E.

2017-11-15

The emissions consequences of smart grid technologies depend heavily on their context and vary not only by geographical location, but by time of year. The same technology operated to meet the same objective may increase the emissions associated with energy generation for part of the year and decrease emissions during other times. The Grid Project Impact Quantification (GridPIQ) tool provides the ability to estimate these seasonal variations and garner insight into the time-varying drivers of grid project emissions impacts. This work leverages GridPIQ to examine the emissions implications across years and seasons of adding energy storage technology to reduce daily peak demand in California and New York.

Synchronization properties of coupled chaotic neurons: The role of random shared input

International Nuclear Information System (INIS)

Kumar, Rupesh; Bilal, Shakir; Ramaswamy, Ram

2016-01-01

Spike-time correlations of neighbouring neurons depend on their intrinsic firing properties as well as on the inputs they share. Studies have shown that periodically firing neurons, when subjected to random shared input, exhibit asynchronicity. Here, we study the effect of random shared input on the synchronization of weakly coupled chaotic neurons. The cases of so-called electrical and chemical coupling are both considered, and we observe a wide range of synchronization behaviour. When subjected to identical shared random input, there is a decrease in the threshold coupling strength needed for chaotic neurons to synchronize in-phase. The system also supports lag–synchronous states, and for these, we find that shared input can cause desynchronization. We carry out a master stability function analysis for a network of such neurons and show agreement with the numerical simulations. The contrasting role of shared random input for complete and lag synchronized neurons is useful in understanding spike-time correlations observed in many areas of the brain.

Synchronization properties of coupled chaotic neurons: The role of random shared input

Energy Technology Data Exchange (ETDEWEB)

Kumar, Rupesh [School of Computational and Integrative Sciences, Jawaharlal Nehru University, New Delhi 110067 (India); Bilal, Shakir [Department of Physics and Astrophysics, University of Delhi, Delhi 110 007 (India); Ramaswamy, Ram [School of Computational and Integrative Sciences, Jawaharlal Nehru University, New Delhi 110067 (India); School of Physical Sciences, Jawaharlal Nehru University, New Delhi 110067 (India)

2016-06-15

Spike-time correlations of neighbouring neurons depend on their intrinsic firing properties as well as on the inputs they share. Studies have shown that periodically firing neurons, when subjected to random shared input, exhibit asynchronicity. Here, we study the effect of random shared input on the synchronization of weakly coupled chaotic neurons. The cases of so-called electrical and chemical coupling are both considered, and we observe a wide range of synchronization behaviour. When subjected to identical shared random input, there is a decrease in the threshold coupling strength needed for chaotic neurons to synchronize in-phase. The system also supports lag–synchronous states, and for these, we find that shared input can cause desynchronization. We carry out a master stability function analysis for a network of such neurons and show agreement with the numerical simulations. The contrasting role of shared random input for complete and lag synchronized neurons is useful in understanding spike-time correlations observed in many areas of the brain.

Single server queueing networks with varying service times and renewal input

Directory of Open Access Journals (Sweden)

Pierre Le Gall

2000-01-01

Full Text Available Using recent results in tandem queues and queueing networks with renewal input, when successive service times of the same customer are varying (and when the busy periods are frequently not broken up in large networks, the local queueing delay of a single server queueing network is evaluated utilizing new concepts of virtual and actual delays (respectively. It appears that because of an important property, due to the underlying tandem queue effect, the usual queueing standards (related to long queues cannot protect against significant overloads in the buffers due to some possible “agglutination phenomenon” (related to short queues. Usual network management methods and traffic simulation methods should be revised, and should monitor the partial traffic streams loads (and not only the server load.

Long Memory of Financial Time Series and Hidden Markov Models with Time-Varying Parameters

DEFF Research Database (Denmark)

Nystrup, Peter; Madsen, Henrik; Lindström, Erik

2016-01-01

Hidden Markov models are often used to model daily returns and to infer the hidden state of financial markets. Previous studies have found that the estimated models change over time, but the implications of the time-varying behavior have not been thoroughly examined. This paper presents an adaptive...... to reproduce with a hidden Markov model. Capturing the time-varying behavior of the parameters also leads to improved one-step density forecasts. Finally, it is shown that the forecasting performance of the estimated models can be further improved using local smoothing to forecast the parameter variations....

Continuous time modelling with individually varying time intervals for oscillating and non-oscillating processes.

Science.gov (United States)

Voelkle, Manuel C; Oud, Johan H L

2013-02-01

When designing longitudinal studies, researchers often aim at equal intervals. In practice, however, this goal is hardly ever met, with different time intervals between assessment waves and different time intervals between individuals being more the rule than the exception. One of the reasons for the introduction of continuous time models by means of structural equation modelling has been to deal with irregularly spaced assessment waves (e.g., Oud & Delsing, 2010). In the present paper we extend the approach to individually varying time intervals for oscillating and non-oscillating processes. In addition, we show not only that equal intervals are unnecessary but also that it can be advantageous to use unequal sampling intervals, in particular when the sampling rate is low. Two examples are provided to support our arguments. In the first example we compare a continuous time model of a bivariate coupled process with varying time intervals to a standard discrete time model to illustrate the importance of accounting for the exact time intervals. In the second example the effect of different sampling intervals on estimating a damped linear oscillator is investigated by means of a Monte Carlo simulation. We conclude that it is important to account for individually varying time intervals, and encourage researchers to conceive of longitudinal studies with different time intervals within and between individuals as an opportunity rather than a problem. © 2012 The British Psychological Society.

Study on time-varying velocity measurement with self-mixing laser diode based on Discrete Chirp-Fourier Transform

International Nuclear Information System (INIS)

Zhang Zhaoyun; Gao Yang; Zhao Xinghai; Zhao Xiang

2011-01-01

Laser's optical output power and frequency are modulated when the optical beam is back-scattered into the active cavity of the laser. By signal processing, the Doppler frequency can be acquired, and the target's velocity can be calculated. Based on these properties, an interferometry velocity sensor can be designed. When target move in time-varying velocity mode, it is difficult to extract the target's velocity. Time-varying velocity measurement by self-mixing laser diode is explored. A mathematics model was proposed for the time-varying velocity (invariable acceleration) measurement by self-mixing laser diode. Based on this model, a Discrete Chirp-Fourier Transform (DCFT) method was applied, DCFT is analogous to DFT. We show that when the signal length N is prime, the magnitudes of all the side lobes are 1, whereas the magnitudes of the main lobe is √N, And the coordinates of the main lobe shows the target's velocity and acceleration information. The simulation results prove the validity of the algorithm even in the situation of low SNR when N is prime.

The necessity for a time local dimension in systems with time-varying attractors

DEFF Research Database (Denmark)

Særmark, Knud H; Ashkenazy, Y; Levitan, J

1997-01-01

We show that a simple non-linear system for ordinary differential equations may possess a time-varying attractor dimension. This indicates that it is infeasible to characterize EEG and MEG time series with a single time global dimension. We suggest another measure for the description of non...

Ponderomotive force of a uniform electromagnetic wave in a time varying dielectric medium

International Nuclear Information System (INIS)

Mori, W.B.; Katsouleas, T.

1992-01-01

A ponderomotive force associated with a uniform electromagnetic wave propagating in a medium with time varying dielectric properties [e.g., ε=ε(x-v 0 t)] is identified. In particular, when a laser ionizes a gas through which it propagates, a force is exerted on the medium at the ionization front that is proportional to (∇ε)E 2 rather than the usual (ε-1)∇E 2 . This force excites a wake in the plasma medium behind the ionization front. The ponderomotive force and wake amplitude are derived and tested with 1D particle-in-cell simulations

Time-varying bispectral analysis of visually evoked multi-channel EEG

Science.gov (United States)

Chandran, Vinod

2012-12-01

Theoretical foundations of higher order spectral analysis are revisited to examine the use of time-varying bicoherence on non-stationary signals using a classical short-time Fourier approach. A methodology is developed to apply this to evoked EEG responses where a stimulus-locked time reference is available. Short-time windowed ensembles of the response at the same offset from the reference are considered as ergodic cyclostationary processes within a non-stationary random process. Bicoherence can be estimated reliably with known levels at which it is significantly different from zero and can be tracked as a function of offset from the stimulus. When this methodology is applied to multi-channel EEG, it is possible to obtain information about phase synchronization at different regions of the brain as the neural response develops. The methodology is applied to analyze evoked EEG response to flash visual stimulii to the left and right eye separately. The EEG electrode array is segmented based on bicoherence evolution with time using the mean absolute difference as a measure of dissimilarity. Segment maps confirm the importance of the occipital region in visual processing and demonstrate a link between the frontal and occipital regions during the response. Maps are constructed using bicoherence at bifrequencies that include the alpha band frequency of 8Hz as well as 4 and 20Hz. Differences are observed between responses from the left eye and the right eye, and also between subjects. The methodology shows potential as a neurological functional imaging technique that can be further developed for diagnosis and monitoring using scalp EEG which is less invasive and less expensive than magnetic resonance imaging.

Time-varying surrogate data to assess nonlinearity in nonstationary time series: application to heart rate variability.

Science.gov (United States)

Faes, Luca; Zhao, He; Chon, Ki H; Nollo, Giandomenico

2009-03-01

We propose a method to extend to time-varying (TV) systems the procedure for generating typical surrogate time series, in order to test the presence of nonlinear dynamics in potentially nonstationary signals. The method is based on fitting a TV autoregressive (AR) model to the original series and then regressing the model coefficients with random replacements of the model residuals to generate TV AR surrogate series. The proposed surrogate series were used in combination with a TV sample entropy (SE) discriminating statistic to assess nonlinearity in both simulated and experimental time series, in comparison with traditional time-invariant (TIV) surrogates combined with the TIV SE discriminating statistic. Analysis of simulated time series showed that using TIV surrogates, linear nonstationary time series may be erroneously regarded as nonlinear and weak TV nonlinearities may remain unrevealed, while the use of TV AR surrogates markedly increases the probability of a correct interpretation. Application to short (500 beats) heart rate variability (HRV) time series recorded at rest (R), after head-up tilt (T), and during paced breathing (PB) showed: 1) modifications of the SE statistic that were well interpretable with the known cardiovascular physiology; 2) significant contribution of nonlinear dynamics to HRV in all conditions, with significant increase during PB at 0.2 Hz respiration rate; and 3) a disagreement between TV AR surrogates and TIV surrogates in about a quarter of the series, suggesting that nonstationarity may affect HRV recordings and bias the outcome of the traditional surrogate-based nonlinearity test.

Flexible time-varying filter banks

Science.gov (United States)

Tuncer, Temel E.; Nguyen, Truong Q.

1993-09-01

Linear phase maximally flat FIR Butterworth filter approximations are discussed and a new filter design method is introduced. This variable cutoff filter design method uses the cosine modulated versions of a prototype filter. The design procedure is simple and different variants of this procedure can be used to obtain close to optimum linear phase filters. Using this method, flexible time-varying filter banks with good reconstruction error are introduced. These types of oversampled filter banks have small magnitude error which can be easily controlled by the appropriate choice of modulation frequency. This error can be further decreased by magnitude equalization without increasing the computational complexity considerably. Two dimensional design examples are also given.

Optical properties of Al nanostructures from time dependent density functional theory

KAUST Repository

Mokkath, Junais Habeeb

2016-04-05

The optical properties of Al nanostructures are investigated by means of time dependent density functional theory, considering chains of varying length and ladders/stripes of varying aspect ratio. The absorption spectra show redshifting for increasing length and aspect ratio. For the chains the absorption is dominated by HOMO → LUMO transitions, whereas ladders and stripes reveal more complex spectra of plasmonic nature above a specific aspect ratio.

Multistability and instability analysis of recurrent neural networks with time-varying delays.

Science.gov (United States)

Zhang, Fanghai; Zeng, Zhigang

2018-01-01

This paper provides new theoretical results on the multistability and instability analysis of recurrent neural networks with time-varying delays. It is shown that such n-neuronal recurrent neural networks have exactly [Formula: see text] equilibria, [Formula: see text] of which are locally exponentially stable and the others are unstable, where k 0 is a nonnegative integer such that k 0 ≤n. By using the combination method of two different divisions, recurrent neural networks can possess more dynamic properties. This method improves and extends the existing results in the literature. Finally, one numerical example is provided to show the superiority and effectiveness of the presented results. Copyright © 2017 Elsevier Ltd. All rights reserved.

A New Time-varying Concept of Risk in a Changing Climate

Science.gov (United States)

Sarhadi, Ali; Ausín, María Concepción; Wiper, Michael P.

2016-10-01

In a changing climate arising from anthropogenic global warming, the nature of extreme climatic events is changing over time. Existing analytical stationary-based risk methods, however, assume multi-dimensional extreme climate phenomena will not significantly vary over time. To strengthen the reliability of infrastructure designs and the management of water systems in the changing environment, multidimensional stationary risk studies should be replaced with a new adaptive perspective. The results of a comparison indicate that current multi-dimensional stationary risk frameworks are no longer applicable to projecting the changing behaviour of multi-dimensional extreme climate processes. Using static stationary-based multivariate risk methods may lead to undesirable consequences in designing water system infrastructures. The static stationary concept should be replaced with a flexible multi-dimensional time-varying risk framework. The present study introduces a new multi-dimensional time-varying risk concept to be incorporated in updating infrastructure design strategies under changing environments arising from human-induced climate change. The proposed generalized time-varying risk concept can be applied for all stochastic multi-dimensional systems that are under the influence of changing environments.

A New Time-varying Concept of Risk in a Changing Climate.

Science.gov (United States)

Sarhadi, Ali; Ausín, María Concepción; Wiper, Michael P

2016-10-20

In a changing climate arising from anthropogenic global warming, the nature of extreme climatic events is changing over time. Existing analytical stationary-based risk methods, however, assume multi-dimensional extreme climate phenomena will not significantly vary over time. To strengthen the reliability of infrastructure designs and the management of water systems in the changing environment, multidimensional stationary risk studies should be replaced with a new adaptive perspective. The results of a comparison indicate that current multi-dimensional stationary risk frameworks are no longer applicable to projecting the changing behaviour of multi-dimensional extreme climate processes. Using static stationary-based multivariate risk methods may lead to undesirable consequences in designing water system infrastructures. The static stationary concept should be replaced with a flexible multi-dimensional time-varying risk framework. The present study introduces a new multi-dimensional time-varying risk concept to be incorporated in updating infrastructure design strategies under changing environments arising from human-induced climate change. The proposed generalized time-varying risk concept can be applied for all stochastic multi-dimensional systems that are under the influence of changing environments.

Time-Varying Networks of Inter-Ictal Discharging Reveal Epileptogenic Zone.

Science.gov (United States)

Zhang, Luyan; Liang, Yi; Li, Fali; Sun, Hongbin; Peng, Wenjing; Du, Peishan; Si, Yajing; Song, Limeng; Yu, Liang; Xu, Peng

2017-01-01

The neuronal synchronous discharging may cause an epileptic seizure. Currently, most of the studies conducted to investigate the mechanism of epilepsy are based on EEGs or functional magnetic resonance imaging (fMRI) recorded during the ictal discharging or the resting-state, and few studies have probed into the dynamic patterns during the inter-ictal discharging that are much easier to record in clinical applications. Here, we propose a time-varying network analysis based on adaptive directed transfer function to uncover the dynamic brain network patterns during the inter-ictal discharging. In addition, an algorithm based on the time-varying outflow of information derived from the network analysis is developed to detect the epileptogenic zone. The analysis performed revealed the time-varying network patterns during different stages of inter-ictal discharging; the epileptogenic zone was activated prior to the discharge onset then worked as the source to propagate the activity to other brain regions. Consistence between the epileptogenic zones detected by our proposed approach and the actual epileptogenic zones proved that time-varying network analysis could not only reveal the underlying neural mechanism of epilepsy, but also function as a useful tool in detecting the epileptogenic zone based on the EEGs in the inter-ictal discharging.

Frequency variations of gravity waves interacting with a time-varying tide

Energy Technology Data Exchange (ETDEWEB)

Huang, C.M.; Zhang, S.D.; Yi, F.; Huang, K.M.; Gan, Q.; Gong, Y. [Wuhan Univ., Hubei (China). School of Electronic Information; Ministry of Education, Wuhan, Hubei (China). Key Lab. of Geospace Environment and Geodesy; State Observatory for Atmospheric Remote Sensing, Wuhan, Hubei (China); Zhang, Y.H. [Nanjing Univ. of Information Science and Technology (China). College of Hydrometeorolgy

2013-11-01

Using a nonlinear, 2-D time-dependent numerical model, we simulate the propagation of gravity waves (GWs) in a time-varying tide. Our simulations show that when aGW packet propagates in a time-varying tidal-wind environment, not only its intrinsic frequency but also its ground-based frequency would change significantly. The tidal horizontal-wind acceleration dominates the GW frequency variation. Positive (negative) accelerations induce frequency increases (decreases) with time. More interestingly, tidal-wind acceleration near the critical layers always causes the GW frequency to increase, which may partially explain the observations that high-frequency GW components are more dominant in the middle and upper atmosphere than in the lower atmosphere. The combination of the increased ground-based frequency of propagating GWs in a time-varying tidal-wind field and the transient nature of the critical layer induced by a time-varying tidal zonal wind creates favorable conditions for GWs to penetrate their originally expected critical layers. Consequently, GWs have an impact on the background atmosphere at much higher altitudes than expected, which indicates that the dynamical effects of tidal-GW interactions are more complicated than usually taken into account by GW parameterizations in global models.

A Solution Method for Linear and Geometrically Nonlinear MDOF Systems with Random Properties subject to Random Excitation

DEFF Research Database (Denmark)

Micaletti, R. C.; Cakmak, A. S.; Nielsen, Søren R. K.

structural properties. The resulting state-space formulation is a system of ordinary stochastic differential equations with random coefficient and deterministic initial conditions which are subsequently transformed into ordinary stochastic differential equations with deterministic coefficients and random......A method for computing the lower-order moments of randomly-excited multi-degree-of-freedom (MDOF) systems with random structural properties is proposed. The method is grounded in the techniques of stochastic calculus, utilizing a Markov diffusion process to model the structural system with random...... initial conditions. This transformation facilitates the derivation of differential equations which govern the evolution of the unconditional statistical moments of response. Primary consideration is given to linear systems and systems with odd polynomial nonlinearities, for in these cases...

Modeling polar cap F-region patches using time varying convection

International Nuclear Information System (INIS)

Sojka, J.J.; Bowline, M.D.; Schunk, R.W.; Decker, D.T.; Valladares, C.E.; Sheehan, R.; Anderson, D.N.; Heelis, R.A.

1993-01-01

Here the authors present the results of computerized simulations of the polar cap regions which were able to model the formation of polar cap patches. They used the Utah State University Time-Dependent Ionospheric Model (TDIM) and the Phillips Laboratory (PL) F-region models in this work. By allowing a time varying magnetospheric electric field in the models, they were able to generate the patches. This time varying field generates a convection in the ionosphere. This convection is similar to convective changes observed in the ionosphere at times of southward pointing interplanetary magnetic field, due to changes in the B y component of the IMF

Computing Conditional VaR using Time-varying CopulasComputing Conditional VaR using Time-varying Copulas

Directory of Open Access Journals (Sweden)

Beatriz Vaz de Melo Mendes

2005-12-01

Full Text Available It is now widespread the use of Value-at-Risk (VaR as a canonical measure at risk. Most accurate VaR measures make use of some volatility model such as GARCH-type models. However, the pattern of volatility dynamic of a portfolio follows from the (univariate behavior of the risk assets, as well as from the type and strength of the associations among them. Moreover, the dependence structure among the components may change conditionally t past observations. Some papers have attempted to model this characteristic by assuming a multivariate GARCH model, or by considering the conditional correlation coefficient, or by incorporating some possibility for switches in regimes. In this paper we address this problem using time-varying copulas. Our modeling strategy allows for the margins to follow some FIGARCH type model while the copula dependence structure changes over time.

On H∞ Fault Estimator Design for Linear Discrete Time-Varying Systems under Unreliable Communication Link

Directory of Open Access Journals (Sweden)

Yueyang Li

2014-01-01

Full Text Available This paper investigates the H∞ fixed-lag fault estimator design for linear discrete time-varying (LDTV systems with intermittent measurements, which is described by a Bernoulli distributed random variable. Through constructing a novel partially equivalent dynamic system, the fault estimator design is converted into a deterministic quadratic minimization problem. By applying the innovation reorganization technique and the projection formula in Krein space, a necessary and sufficient condition is obtained for the existence of the estimator. The parameter matrices of the estimator are derived by recursively solving two standard Riccati equations. An illustrative example is provided to show the effectiveness and applicability of the proposed algorithm.

Impact of preacidification of milk and fermentation time on the properties of yogurt.

Science.gov (United States)

Peng, Y; Horne, D S; Lucey, J A

2009-07-01

Casein interactions play an important role in the textural properties of yogurt. The objective of this study was to investigate how the concentration of insoluble calcium phosphate (CCP) that is associated with casein particles and the length of fermentation time influence properties of yogurt gels. A central composite experimental design was used. The initial milk pH was varied by preacidification with glucono-delta-lactone (GDL), and fermentation time (time to reach pH 4.6 from the initial pH) was altered by varying the inoculum level. We hypothesized that by varying the initial milk pH value, the amount of CCP would be modified and that by varying the length of the fermentation time we would influence the rate and extent of solubilization of CCP during any subsequent gelation process. We believe that both of these factors could influence casein interactions and thereby alter gel properties. Milks were preacidified to pH values from 6.55 to 5.65 at 40 degrees C using GDL and equilibrated for 4 h before inoculation. Fermentation time was varied from 250 to 500 min by adding various amounts of culture at 40 degrees C. Gelation properties were monitored using dynamic oscillatory rheology, and microstructure was studied using fluorescence microscopy. Whey separation and permeability were analyzed at pH 4.6. The preacidification pH value significantly affected the solubilization of CCP. Storage modulus values at pH 4.6 were positively influenced by the preacidification pH value and negatively affected by fermentation time. The value for the loss tangent maximum during gelation was positively affected by the preacidification pH value. Fermentation time positively affected whey separation and significantly influenced the rate of CCP dissolution during fermentation, as CCP dissolution was a slow process. Longer fermentation times resulted in greater loss of CCP at the pH of gelation. At the end of fermentation (pH approximately 4.6), virtually all CCP was dissolved

Flexible Demand Management under Time-Varying Prices

Science.gov (United States)

Liang, Yong

In this dissertation, the problem of flexible demand management under time-varying prices is studied. This generic problem has many applications, which usually have multiple periods in which decisions on satisfying demand need to be made, and prices in these periods are time-varying. Examples of such applications include multi-period procurement problem, operating room scheduling, and user-end demand scheduling in the Smart Grid, where the last application is used as the main motivating story throughout the dissertation. The current grid is experiencing an upgrade with lots of new designs. What is of particular interest is the idea of passing time-varying prices that reflect electricity market conditions to end users as incentives for load shifting. One key component, consequently, is the demand management system at the user-end. The objective of the system is to find the optimal trade-off between cost saving and discomfort increment resulted from load shifting. In this dissertation, we approach this problem from the following aspects: (1) construct a generic model, solve for Pareto optimal solutions, and analyze the robust solution that optimizes the worst-case payoffs, (2) extend to a distribution-free model for multiple types of demand (appliances), for which an approximate dynamic programming (ADP) approach is developed, and (3) design other efficient algorithms for practical purposes of the flexible demand management system. We first construct a novel multi-objective flexible demand management model, in which there are a finite number of periods with time-varying prices, and demand arrives in each period. In each period, the decision maker chooses to either satisfy or defer outstanding demand to minimize costs and discomfort over a certain number of periods. We consider both the deterministic model, models with stochastic demand or prices, and when only partial information about the stochastic demand or prices is known. We first analyze the stochastic

Electromagnetic radiation in a time-varying background medium

NARCIS (Netherlands)

Budko, N.V.

2009-01-01

Analytical solutions are presented for the electromagnetic radiation by an arbitrary pulsed source into a homogeneous time-varying background medium. In the constant-impedance case an explicit radiation formula is obtained for the synchronous permittivity and permeability described by any positive

Housing Cycles in Switzerland - A Time-Varying Approach

OpenAIRE

Drechsel, Dirk

2015-01-01

In light of the strong increase of house prices in Switzerland, we analyze the effects of mortgage rate shocks, changes in the interplay between housing demand and supply and GDP growth on house prices for the time period 1981- 2014. We employ Bayesian time-varying coefficients vector autoregressions to allow different monetary and immigration regimes over time. A number of structural changes, such as regulatory changes in the aftermath of the 1990s real estate crisis, the introduction of fre...

Exploring Heterogeneous and Time-Varying Materials for Photonic Applications, Towards Solutions for the Manipulation and Confinement of Light.

KAUST Repository

San Roman Alerigi, Damian

2014-01-01

Over the past several decades our understanding and meticulous characterization of the transient and spatial properties of materials evolved rapidly. The results present an exciting field for discovery, and craft materials to control and reshape light that we are just beginning to fathom. State-of-the-art nano-deposition processes, for example, can be utilized to build stratified waveguides made of thin dielectric layers, which put together result in a material with effective abnormal dispersion. Moreover, materials once deemed well known are revealing astonishing properties, v.gr. chalcogenide glasses undergo an atomic reconfiguration when illuminated with electrons or photons, this ensues in a temporal modification of its permittivity and permeability which could be used to build new Photonic Integrated Circuits.. This work revolves around the characterization and model of heterogeneous and time-varying materials and their applications, revisits Maxwell's equations in the context of nonlinear space- and time-varying media, and based on it introduces a numerical scheme that can be used to model waves in this kind of media. Finally some interesting applications for light confinement and beam transformations are shown.

Exploring Heterogeneous and Time-Varying Materials for Photonic Applications, Towards Solutions for the Manipulation and Confinement of Light.

KAUST Repository

San Roman Alerigi, Damian

2014-11-01

Over the past several decades our understanding and meticulous characterization of the transient and spatial properties of materials evolved rapidly. The results present an exciting field for discovery, and craft materials to control and reshape light that we are just beginning to fathom. State-of-the-art nano-deposition processes, for example, can be utilized to build stratified waveguides made of thin dielectric layers, which put together result in a material with effective abnormal dispersion. Moreover, materials once deemed well known are revealing astonishing properties, v.gr. chalcogenide glasses undergo an atomic reconfiguration when illuminated with electrons or photons, this ensues in a temporal modification of its permittivity and permeability which could be used to build new Photonic Integrated Circuits.. This work revolves around the characterization and model of heterogeneous and time-varying materials and their applications, revisits Maxwell\\'s equations in the context of nonlinear space- and time-varying media, and based on it introduces a numerical scheme that can be used to model waves in this kind of media. Finally some interesting applications for light confinement and beam transformations are shown.

Time varying, multivariate volume data reduction

Energy Technology Data Exchange (ETDEWEB)

Ahrens, James P [Los Alamos National Laboratory; Fout, Nathaniel [UC DAVIS; Ma, Kwan - Liu [UC DAVIS

2010-01-01

Large-scale supercomputing is revolutionizing the way science is conducted. A growing challenge, however, is understanding the massive quantities of data produced by large-scale simulations. The data, typically time-varying, multivariate, and volumetric, can occupy from hundreds of gigabytes to several terabytes of storage space. Transferring and processing volume data of such sizes is prohibitively expensive and resource intensive. Although it may not be possible to entirely alleviate these problems, data compression should be considered as part of a viable solution, especially when the primary means of data analysis is volume rendering. In this paper we present our study of multivariate compression, which exploits correlations among related variables, for volume rendering. Two configurations for multidimensional compression based on vector quantization are examined. We emphasize quality reconstruction and interactive rendering, which leads us to a solution using graphics hardware to perform on-the-fly decompression during rendering. In this paper we present a solution which addresses the need for data reduction in large supercomputing environments where data resulting from simulations occupies tremendous amounts of storage. Our solution employs a lossy encoding scheme to acrueve data reduction with several options in terms of rate-distortion behavior. We focus on encoding of multiple variables together, with optional compression in space and time. The compressed volumes can be rendered directly with commodity graphics cards at interactive frame rates and rendering quality similar to that of static volume renderers. Compression results using a multivariate time-varying data set indicate that encoding multiple variables results in acceptable performance in the case of spatial and temporal encoding as compared to independent compression of variables. The relative performance of spatial vs. temporal compression is data dependent, although temporal compression has the

An Explicit MOT-TD-VIE Solver for Time Varying Media

KAUST Repository

Sayed, Sadeed Bin; Ulku, Huseyin Arda; Bagci, Hakan

2016-01-01

An explicit marching on-in-time (MOT) scheme for solving the time domain electric field integral equation enforced on volumes with time varying dielectric permittivity is proposed. Unknowns of the integral equation and the constitutive relation, i

Epidemic spreading in time-varying community networks.

Science.gov (United States)

Ren, Guangming; Wang, Xingyuan

2014-06-01

The spreading processes of many infectious diseases have comparable time scale as the network evolution. Here, we present a simple networks model with time-varying community structure, and investigate susceptible-infected-susceptible epidemic spreading processes in this model. By both theoretic analysis and numerical simulations, we show that the efficiency of epidemic spreading in this model depends intensively on the mobility rate q of the individuals among communities. We also find that there exists a mobility rate threshold qc. The epidemic will survive when q > qc and die when q epidemic spreading in complex networks with community structure.

Time-varying Concurrent Risk of Extreme Droughts and Heatwaves in California

Science.gov (United States)

Sarhadi, A.; Diffenbaugh, N. S.; Ausin, M. C.

2016-12-01

Anthropogenic global warming has changed the nature and the risk of extreme climate phenomena such as droughts and heatwaves. The concurrent of these nature-changing climatic extremes may result in intensifying undesirable consequences in terms of human health and destructive effects in water resources. The present study assesses the risk of concurrent extreme droughts and heatwaves under dynamic nonstationary conditions arising from climate change in California. For doing so, a generalized fully Bayesian time-varying multivariate risk framework is proposed evolving through time under dynamic human-induced environment. In this methodology, an extreme, Bayesian, dynamic copula (Gumbel) is developed to model the time-varying dependence structure between the two different climate extremes. The time-varying extreme marginals are previously modeled using a Generalized Extreme Value (GEV) distribution. Bayesian Markov Chain Monte Carlo (MCMC) inference is integrated to estimate parameters of the nonstationary marginals and copula using a Gibbs sampling method. Modelled marginals and copula are then used to develop a fully Bayesian, time-varying joint return period concept for the estimation of concurrent risk. Here we argue that climate change has increased the chance of concurrent droughts and heatwaves over decades in California. It is also demonstrated that a time-varying multivariate perspective should be incorporated to assess realistic concurrent risk of the extremes for water resources planning and management in a changing climate in this area. The proposed generalized methodology can be applied for other stochastic nature-changing compound climate extremes that are under the influence of climate change.

Bit-level plane image encryption based on coupled map lattice with time-varying delay

Science.gov (United States)

Lv, Xiupin; Liao, Xiaofeng; Yang, Bo

2018-04-01

Most of the existing image encryption algorithms had two basic properties: confusion and diffusion in a pixel-level plane based on various chaotic systems. Actually, permutation in a pixel-level plane could not change the statistical characteristics of an image, and many of the existing color image encryption schemes utilized the same method to encrypt R, G and B components, which means that the three color components of a color image are processed three times independently. Additionally, dynamical performance of a single chaotic system degrades greatly with finite precisions in computer simulations. In this paper, a novel coupled map lattice with time-varying delay therefore is applied in color images bit-level plane encryption to solve the above issues. Spatiotemporal chaotic system with both much longer period in digitalization and much excellent performances in cryptography is recommended. Time-varying delay embedded in coupled map lattice enhances dynamical behaviors of the system. Bit-level plane image encryption algorithm has greatly reduced the statistical characteristics of an image through the scrambling processing. The R, G and B components cross and mix with one another, which reduces the correlation among the three components. Finally, simulations are carried out and all the experimental results illustrate that the proposed image encryption algorithm is highly secure, and at the same time, also demonstrates superior performance.

Occupation times and ergodicity breaking in biased continuous time random walks

International Nuclear Information System (INIS)

Bel, Golan; Barkai, Eli

2005-01-01

Continuous time random walk (CTRW) models are widely used to model diffusion in condensed matter. There are two classes of such models, distinguished by the convergence or divergence of the mean waiting time. Systems with finite average sojourn time are ergodic and thus Boltzmann-Gibbs statistics can be applied. We investigate the statistical properties of CTRW models with infinite average sojourn time; in particular, the occupation time probability density function is obtained. It is shown that in the non-ergodic phase the distribution of the occupation time of the particle on a given lattice point exhibits bimodal U or trimodal W shape, related to the arcsine law. The key points are as follows. (a) In a CTRW with finite or infinite mean waiting time, the distribution of the number of visits on a lattice point is determined by the probability that a member of an ensemble of particles in equilibrium occupies the lattice point. (b) The asymmetry parameter of the probability distribution function of occupation times is related to the Boltzmann probability and to the partition function. (c) The ensemble average is given by Boltzmann-Gibbs statistics for either finite or infinite mean sojourn time, when detailed balance conditions hold. (d) A non-ergodic generalization of the Boltzmann-Gibbs statistical mechanics for systems with infinite mean sojourn time is found

Electricity Futures Prices : Time Varying Sensitivity to Fundamentals

NARCIS (Netherlands)

S-E. Fleten (Stein-Erik); R. Huisman (Ronald); M. Kilic (Mehtap); H.P.G. Pennings (Enrico); S. Westgaard (Sjur)

2014-01-01

textabstractThis paper provides insight in the time-varying relation between electricity futures prices and fundamentals in the form of prices of contracts for fossil fuels. As supply curves are not constant and different producers have different marginal costs of production, we argue that the

Discrete-Time Sliding-Mode Control of Uncertain Systems with Time-Varying Delays via Descriptor Approach

Directory of Open Access Journals (Sweden)

Maode Yan

2008-01-01

Full Text Available This paper considers the problem of robust discrete-time sliding-mode control (DT-SMC design for a class of uncertain linear systems with time-varying delays. By applying a descriptor model transformation and Moon's inequality for bounding cross terms, a delay-dependent sufficient condition for the existence of stable sliding surface is given in terms of linear matrix inequalities (LMIs. Based on this existence condition, the synthesized sliding mode controller can guarantee the sliding-mode reaching condition of the specified discrete-time sliding surface for all admissible uncertainties and time-varying delays. An illustrative example verifies the effectiveness of the proposed method.

Randomized trial of weight-loss-diets for young adults varying in fish and fish oil content

NARCIS (Netherlands)

Thorsdottir, I.; Tomasson, H.; Gunnarsdottir, I.; Gisladottir, E.; Kiely, M.; Parra, M.D.; Bandarra, N.M.; Schaafsma, G.; Martinez, J.A.

2007-01-01

Objective: To investigate the effect of including seafood and fish oils, as part of an energy-restricted diet, on weight loss in young overweight adults. Design: Randomized controlled trial of energy-restricted diet varying in fish and fish oil content was followed for 8 weeks. Subjects were

Synchronization of uncertain time-varying network based on sliding mode control technique

Science.gov (United States)

Lü, Ling; Li, Chengren; Bai, Suyuan; Li, Gang; Rong, Tingting; Gao, Yan; Yan, Zhe

2017-09-01

We research synchronization of uncertain time-varying network based on sliding mode control technique. The sliding mode control technique is first modified so that it can be applied to network synchronization. Further, by choosing the appropriate sliding surface, the identification law of uncertain parameter, the adaptive law of the time-varying coupling matrix element and the control input of network are designed, it is sure that the uncertain time-varying network can synchronize effectively the synchronization target. At last, we perform some numerical simulations to demonstrate the effectiveness of the proposed results.

Conceptual Modeling of Time-Varying Information

DEFF Research Database (Denmark)

Gregersen, Heidi; Jensen, Christian S.

2004-01-01

A wide range of database applications manage information that varies over time. Many of the underlying database schemas of these were designed using the Entity-Relationship (ER) model. In the research community as well as in industry, it is common knowledge that the temporal aspects of the mini......-world are important, but difficult to capture using the ER model. Several enhancements to the ER model have been proposed in an attempt to support the modeling of temporal aspects of information. Common to the existing temporally extended ER models, few or no specific requirements to the models were given...

A time-varying magnetic flux concentrator

International Nuclear Information System (INIS)

Kibret, B; Premaratne, M; Lewis, P M; Thomson, R; Fitzgerald, P B

2016-01-01

It is known that diverse technological applications require the use of focused magnetic fields. This has driven the quest for controlling the magnetic field. Recently, the principles in transformation optics and metamaterials have allowed the realization of practical static magnetic flux concentrators. Extending such progress, here, we propose a time-varying magnetic flux concentrator cylindrical shell that uses electric conductors and ferromagnetic materials to guide magnetic flux to its center. Its performance is discussed based on finite-element simulation results. Our proposed design has potential applications in magnetic sensors, medical devices, wireless power transfer, and near-field wireless communications. (paper)

Electron dynamics in solid state via time varying wavevectors

Science.gov (United States)

Khaneja, Navin

2018-06-01

In this paper, we study electron wavepacket dynamics in electric and magnetic fields. We rigorously derive the semiclassical equations of electron dynamics in electric and magnetic fields. We do it both for free electron and electron in a periodic potential. We do this by introducing time varying wavevectors k(t). In the presence of magnetic field, our wavepacket reproduces the classical cyclotron orbits once the origin of the Schröedinger equation is correctly chosen to be center of cyclotron orbit. In the presence of both electric and magnetic fields, our equations for wavepacket dynamics differ from classical Lorentz force equations. We show that in a periodic potential, on application of electric field, the electron wave function adiabatically follows the wavefunction of a time varying Bloch wavevector k(t), with its energies suitably shifted with time. We derive the effective mass equation and discuss conduction in conductors and insulators.

Time varying determinants of bond flows to emerging markets

Directory of Open Access Journals (Sweden)

Yasemin Erduman

2016-06-01

Full Text Available This paper investigates the time varying nature of the determinants of bond flows with a focus on the global financial crisis period. We estimate a time varying regression model using Bayesian estimation methods, where the posterior distribution is approximated by Gibbs sampling algorithm. Our findings suggest that the interest rate differential is the most significant pull factor of portfolio bond flows, along with the inflation rate, while the growth rate does not play a significant role. Among the push factors, global liquidity is the most important driver of bond flows. It matters the most, when unconventional monetary easing policies were first announced; and its importance as a determinant of portfolio bond flows decreases over time, starting with the Eurozone crisis, and diminishes with the tapering talk. Global risk appetite and the risk perception towards the emerging countries also have relatively small and stable significant effects on bond flows.

Lifetime, turnover time, and fast magnetic field regeneration in random flows

International Nuclear Information System (INIS)

Tanner, S. E. M.

2007-01-01

The fast dynamo is thought to be relevant in the regeneration of magnetic fields in astrophysics where the value of the magnetic Reynolds number (Rm) is immense. The fast dynamo picture is one in which chaotic flows provide a mechanism for the stretching of magnetic field lines. Furthermore, a cascade of energy down to small scales results in intermittent regions of a small-scale, intense magnetic field. Given this scenario it is natural to invoke the use of kinematic random flows in order to understand field regeneration mechanisms better. Here a family of random flows is used to study the effects that L, the lifetime of the cell, and τ, the turnover time of the cell, may have on magnetic field regeneration. Defining the parameter Γ=L/τ, it has been varied according to Γ>1, Γ<1, Γ∼O(1). In the kinematic regime, dynamo growth rates and Lyapunov exponents are examined at varying values of Rm. The possibility of fast dynamo action is considered. In the nonlinear regime, magnetic and kinetic energies are examined. Results indicate that there does appear to be a relationship between Γ and dynamo efficiency. In particular, the most efficient dynamos seem to operate at lower values of Γ

Global stabilization of linear continuous time-varying systems with bounded controls

International Nuclear Information System (INIS)

Phat, V.N.

2004-08-01

This paper deals with the problem of global stabilization of a class of linear continuous time-varying systems with bounded controls. Based on the controllability of the nominal system, a sufficient condition for the global stabilizability is proposed without solving any Riccati differential equation. Moreover, we give sufficient conditions for the robust stabilizability of perturbation/uncertain linear time-varying systems with bounded controls. (author)

Non-fragile observer design for discrete-time genetic regulatory networks with randomly occurring uncertainties

International Nuclear Information System (INIS)

Banu, L Jarina; Balasubramaniam, P

2015-01-01

This paper investigates the problem of non-fragile observer design for a class of discrete-time genetic regulatory networks (DGRNs) with time-varying delays and randomly occurring uncertainties. A non-fragile observer is designed, for estimating the true concentration of mRNAs and proteins from available measurement outputs. One important feature of the results obtained that are reported here is that the parameter uncertainties are assumed to be random and their probabilities of occurrence are known a priori. On the basis of the Lyapunov–Krasovskii functional approach and using a convex combination technique, a delay-dependent estimation criterion is established for DGRNs in terms of linear matrix inequalities (LMIs) that can be efficiently solved using any available LMI solver. Finally numerical examples are provided to substantiate the theoretical results. (paper)

Randomizing growing networks with a time-respecting null model

Science.gov (United States)

Ren, Zhuo-Ming; Mariani, Manuel Sebastian; Zhang, Yi-Cheng; Medo, Matúš

2018-05-01

Complex networks are often used to represent systems that are not static but grow with time: People make new friendships, new papers are published and refer to the existing ones, and so forth. To assess the statistical significance of measurements made on such networks, we propose a randomization methodology—a time-respecting null model—that preserves both the network's degree sequence and the time evolution of individual nodes' degree values. By preserving the temporal linking patterns of the analyzed system, the proposed model is able to factor out the effect of the system's temporal patterns on its structure. We apply the model to the citation network of Physical Review scholarly papers and the citation network of US movies. The model reveals that the two data sets are strikingly different with respect to their degree-degree correlations, and we discuss the important implications of this finding on the information provided by paradigmatic node centrality metrics such as indegree and Google's PageRank. The randomization methodology proposed here can be used to assess the significance of any structural property in growing networks, which could bring new insights into the problems where null models play a critical role, such as the detection of communities and network motifs.

Finite-Time Reentry Attitude Control Using Time-Varying Sliding Mode and Disturbance Observer

Directory of Open Access Journals (Sweden)

Xuzhong Wu

2015-01-01

Full Text Available This paper presents the finite-time attitude control problem for reentry vehicle with redundant actuators in consideration of planet uncertainties and external disturbances. Firstly, feedback linearization technique is used to cancel the nonlinearities of equations of motion to construct a basic mode for attitude controller. Secondly, two kinds of time-varying sliding mode control methods with disturbance observer are integrated with the basic mode in order to enhance the control performance and system robustness. One method is designed based on boundary layer technique and the other is a novel second-order sliding model control method. The finite-time stability analyses of both resultant closed-loop systems are carried out. Furthermore, after attitude controller produces the torque commands, an optimization control allocation approach is introduced to allocate them into aerodynamic surface deflections and on-off reaction control system thrusts. Finally, the numerical simulation results demonstrate that both of the time-varying sliding mode control methods are robust to uncertainties and disturbances without chattering phenomenon. Moreover, the proposed second-order sliding mode control method possesses better control accuracy.

Finite-time and fixed-time synchronization analysis of inertial memristive neural networks with time-varying delays.

Science.gov (United States)

Wei, Ruoyu; Cao, Jinde; Alsaedi, Ahmed

2018-02-01

This paper investigates the finite-time synchronization and fixed-time synchronization problems of inertial memristive neural networks with time-varying delays. By utilizing the Filippov discontinuous theory and Lyapunov stability theory, several sufficient conditions are derived to ensure finite-time synchronization of inertial memristive neural networks. Then, for the purpose of making the setting time independent of initial condition, we consider the fixed-time synchronization. A novel criterion guaranteeing the fixed-time synchronization of inertial memristive neural networks is derived. Finally, three examples are provided to demonstrate the effectiveness of our main results.

Radiosensitizing and cytotoxic properties of DNA targeted phenanthridine-linked nitroheterocycles of varying electron affinities

International Nuclear Information System (INIS)

Cowan, D.S.M.; Rauth, A.M.; Toronto Univ., ON; Matejovic, J.F.; McClelland, R.A.; Wardman, P.

1994-01-01

2-Nitroimidazoles targeted to DNA via intercalation have previously been shown to be as much as 10-100 times more efficient on a molar basis than the untargeted nitroimidazole, misonidazole, in vitro as hypoxic cell selective radiosensitizers and cytotoxins based on extracellular concentrations. In this work the effect of varying the nitroaromatic group has been examined through the preparation of a DNA-targeted 4-nitroimidazole (4-MeNLP-3), a 5-nitroimidazole (5-NLP-3) and a 5-nitrofuran (FEP-2) linked to phenanthridinium ions. With the previously synthesized 2-nitroimidazoles, this provides a series of DNA targeted compounds of varying electron affinity as well as structure at the nitroaromatic position. The present series of compounds was tested for partition coefficient, DNA binding ability, reduction potentials and in vitro radiosensitizing and cytotoxic abilities. The results obtained indicate that targeting such compounds to DNA diminishes the dependency of radiosensitizing and cytotoxic properties on reduction potential and may allow significant uncoupling of toxicity from radiosensitizing ability. (author)

Multi-state time-varying reliability evaluation of smart grid with flexible demand resources utilizing Lz transform

Science.gov (United States)

Jia, Heping; Jin, Wende; Ding, Yi; Song, Yonghua; Yu, Dezhao

2017-01-01

With the expanding proportion of renewable energy generation and development of smart grid technologies, flexible demand resources (FDRs) have been utilized as an approach to accommodating renewable energies. However, multiple uncertainties of FDRs may influence reliable and secure operation of smart grid. Multi-state reliability models for a single FDR and aggregating FDRs have been proposed in this paper with regard to responsive abilities for FDRs and random failures for both FDR devices and information system. The proposed reliability evaluation technique is based on Lz transform method which can formulate time-varying reliability indices. A modified IEEE-RTS has been utilized as an illustration of the proposed technique.

Synchronization of Markovian jumping stochastic complex networks with distributed time delays and probabilistic interval discrete time-varying delays

International Nuclear Information System (INIS)

Li Hongjie; Yue Dong

2010-01-01

The paper investigates the synchronization stability problem for a class of complex dynamical networks with Markovian jumping parameters and mixed time delays. The complex networks consist of m modes and the networks switch from one mode to another according to a Markovian chain with known transition probability. The mixed time delays are composed of discrete and distributed delays, the discrete time delay is assumed to be random and its probability distribution is known a priori. In terms of the probability distribution of the delays, the new type of system model with probability-distribution-dependent parameter matrices is proposed. Based on the stochastic analysis techniques and the properties of the Kronecker product, delay-dependent synchronization stability criteria in the mean square are derived in the form of linear matrix inequalities which can be readily solved by using the LMI toolbox in MATLAB, the solvability of derived conditions depends on not only the size of the delay, but also the probability of the delay-taking values in some intervals. Finally, a numerical example is given to illustrate the feasibility and effectiveness of the proposed method.

Effect of storage time and temperature on the rheological and microstructural properties of gluten

NARCIS (Netherlands)

Nicolas, Y.; Smit, R.J.M.; van Aalst, H.; Esselink, F.J.; Weegels, P.L.; Agterof, W.G.M.

2003-01-01

To investigate the effects of frozen storage on the rheological and microstructural properties of gluten, two model systems were investigated: System A, gluten and water; System B, gluten, water, and NaCl. The storage time was varied from 1 to 16 weeks and the storage temperature was varied from -5

Statistical properties of random clique networks

Science.gov (United States)

Ding, Yi-Min; Meng, Jun; Fan, Jing-Fang; Ye, Fang-Fu; Chen, Xiao-Song

2017-10-01

In this paper, a random clique network model to mimic the large clustering coefficient and the modular structure that exist in many real complex networks, such as social networks, artificial networks, and protein interaction networks, is introduced by combining the random selection rule of the Erdös and Rényi (ER) model and the concept of cliques. We find that random clique networks having a small average degree differ from the ER network in that they have a large clustering coefficient and a power law clustering spectrum, while networks having a high average degree have similar properties as the ER model. In addition, we find that the relation between the clustering coefficient and the average degree shows a non-monotonic behavior and that the degree distributions can be fit by multiple Poisson curves; we explain the origin of such novel behaviors and degree distributions.

Vector-field statistics for the analysis of time varying clinical gait data.

Science.gov (United States)

Donnelly, C J; Alexander, C; Pataky, T C; Stannage, K; Reid, S; Robinson, M A

2017-01-01

In clinical settings, the time varying analysis of gait data relies heavily on the experience of the individual(s) assessing these biological signals. Though three dimensional kinematics are recognised as time varying waveforms (1D), exploratory statistical analysis of these data are commonly carried out with multiple discrete or 0D dependent variables. In the absence of an a priori 0D hypothesis, clinicians are at risk of making type I and II errors in their analyis of time varying gait signatures in the event statistics are used in concert with prefered subjective clinical assesment methods. The aim of this communication was to determine if vector field waveform statistics were capable of providing quantitative corroboration to practically significant differences in time varying gait signatures as determined by two clinically trained gait experts. The case study was a left hemiplegic Cerebral Palsy (GMFCS I) gait patient following a botulinum toxin (BoNT-A) injection to their left gastrocnemius muscle. When comparing subjective clinical gait assessments between two testers, they were in agreement with each other for 61% of the joint degrees of freedom and phases of motion analysed. For tester 1 and tester 2, they were in agreement with the vector-field analysis for 78% and 53% of the kinematic variables analysed. When the subjective analyses of tester 1 and tester 2 were pooled together and then compared to the vector-field analysis, they were in agreement for 83% of the time varying kinematic variables analysed. These outcomes demonstrate that in principle, vector-field statistics corroborates with what a team of clinical gait experts would classify as practically meaningful pre- versus post time varying kinematic differences. The potential for vector-field statistics to be used as a useful clinical tool for the objective analysis of time varying clinical gait data is established. Future research is recommended to assess the usefulness of vector-field analyses

Time-varying economic dominance in financial markets: A bistable dynamics approach

Science.gov (United States)

He, Xue-Zhong; Li, Kai; Wang, Chuncheng

2018-05-01

By developing a continuous-time heterogeneous agent financial market model of multi-assets traded by fundamental and momentum investors, we provide a potential mechanism for generating time-varying dominance between fundamental and non-fundamental in financial markets. We show that investment constraints lead to the coexistence of a locally stable fundamental steady state and a locally stable limit cycle around the fundamental, characterized by a Bautin bifurcation. This provides a mechanism for market prices to switch stochastically between the two persistent but very different market states, leading to the coexistence and time-varying dominance of seemingly controversial efficient market and price momentum over different time periods. The model also generates other financial market stylized facts, such as spillover effects in both momentum and volatility, market booms, crashes, and correlation reduction due to cross-sectional momentum trading. Empirical evidence based on the U.S. market supports the main findings. The mechanism developed in this paper can be used to characterize time-varying economic dominance in economics and finance in general.

Optimal critic learning for robot control in time-varying environments.

Science.gov (United States)

Wang, Chen; Li, Yanan; Ge, Shuzhi Sam; Lee, Tong Heng

2015-10-01

In this paper, optimal critic learning is developed for robot control in a time-varying environment. The unknown environment is described as a linear system with time-varying parameters, and impedance control is employed for the interaction control. Desired impedance parameters are obtained in the sense of an optimal realization of the composite of trajectory tracking and force regulation. Q -function-based critic learning is developed to determine the optimal impedance parameters without the knowledge of the system dynamics. The simulation results are presented and compared with existing methods, and the efficacy of the proposed method is verified.

Consequences of varied soil hydraulic and meteorological complexity on unsaturated zone time lag estimates.

Science.gov (United States)

Vero, S E; Ibrahim, T G; Creamer, R E; Grant, J; Healy, M G; Henry, T; Kramers, G; Richards, K G; Fenton, O

2014-12-01

The true efficacy of a programme of agricultural mitigation measures within a catchment to improve water quality can be determined only after a certain hydrologic time lag period (subsequent to implementation) has elapsed. As the biophysical response to policy is not synchronous, accurate estimates of total time lag (unsaturated and saturated) become critical to manage the expectations of policy makers. The estimation of the vertical unsaturated zone component of time lag is vital as it indicates early trends (initial breakthrough), bulk (centre of mass) and total (Exit) travel times. Typically, estimation of time lag through the unsaturated zone is poor, due to the lack of site specific soil physical data, or by assuming saturated conditions. Numerical models (e.g. Hydrus 1D) enable estimates of time lag with varied levels of input data. The current study examines the consequences of varied soil hydraulic and meteorological complexity on unsaturated zone time lag estimates using simulated and actual soil profiles. Results indicated that: greater temporal resolution (from daily to hourly) of meteorological data was more critical as the saturated hydraulic conductivity of the soil decreased; high clay content soils failed to converge reflecting prevalence of lateral component as a contaminant pathway; elucidation of soil hydraulic properties was influenced by the complexity of soil physical data employed (textural menu, ROSETTA, full and partial soil water characteristic curves), which consequently affected time lag ranges; as the importance of the unsaturated zone increases with respect to total travel times the requirements for high complexity/resolution input data become greater. The methodology presented herein demonstrates that decisions made regarding input data and landscape position will have consequences for the estimated range of vertical travel times. Insufficiencies or inaccuracies regarding such input data can therefore mislead policy makers regarding

Epidemic spreading in time-varying community networks

Energy Technology Data Exchange (ETDEWEB)

Ren, Guangming, E-mail: wangxy@dlut.edu.cn, E-mail: ren-guang-ming@163.com [School of Electronic and Information, Guangdong Polytechnic Normal University, Guangzhou 510665 (China); Faculty of Electronic Information and Electrical Engineering, Dalian University of Technology, Dalian 116024 (China); Wang, Xingyuan, E-mail: wangxy@dlut.edu.cn, E-mail: ren-guang-ming@163.com [Faculty of Electronic Information and Electrical Engineering, Dalian University of Technology, Dalian 116024 (China)

2014-06-15

The spreading processes of many infectious diseases have comparable time scale as the network evolution. Here, we present a simple networks model with time-varying community structure, and investigate susceptible-infected-susceptible epidemic spreading processes in this model. By both theoretic analysis and numerical simulations, we show that the efficiency of epidemic spreading in this model depends intensively on the mobility rate q of the individuals among communities. We also find that there exists a mobility rate threshold q{sub c}. The epidemic will survive when q > q{sub c} and die when q < q{sub c}. These results can help understanding the impacts of human travel on the epidemic spreading in complex networks with community structure.

Epidemic spreading in time-varying community networks

International Nuclear Information System (INIS)

Ren, Guangming; Wang, Xingyuan

2014-01-01

The spreading processes of many infectious diseases have comparable time scale as the network evolution. Here, we present a simple networks model with time-varying community structure, and investigate susceptible-infected-susceptible epidemic spreading processes in this model. By both theoretic analysis and numerical simulations, we show that the efficiency of epidemic spreading in this model depends intensively on the mobility rate q of the individuals among communities. We also find that there exists a mobility rate threshold q c . The epidemic will survive when q > q c and die when q  c . These results can help understanding the impacts of human travel on the epidemic spreading in complex networks with community structure

Adaptive sliding control of non-autonomous active suspension systems with time-varying loadings

Science.gov (United States)

Chen, Po-Chang; Huang, An-Chyau

2005-04-01

An adaptive sliding controller is proposed in this paper for controlling a non-autonomous quarter-car suspension system with time-varying loadings. The bound of the car-body loading is assumed to be available. Then, the reference coordinate is placed at the static position under the nominal loading so that the system dynamic equation is derived. Due to spring nonlinearities, the system property becomes asymmetric after coordinate transformation. Besides, in practical cases, system parameters are not easy to be obtained precisely for controller design. Therefore, in this paper, system uncertainties are lumped into two unknown time-varying functions. Since the variation bound of one of the unknown functions is not available, conventional adaptive schemes and robust designs are not applicable. To deal with this problem, the function approximation technique is employed to represent the unknown function as a finite combination of basis functions. The Lyapunov direct method can thus be used to find adaptive laws for updating coefficients in the approximating series and to prove stability of the closed-loop system. Since the position and velocity measurements of the unsprung mass are lumped into the unknown function, there is no need to install sensors on the axle and wheel assembly in the actual implementation. Simulation results are presented to show the performance of the proposed strategy.

Efficient rare-event simulation for multiple jump events in regularly varying random walks and compound Poisson processes

NARCIS (Netherlands)

B. Chen (Bohan); J. Blanchet; C.H. Rhee (Chang-Han); A.P. Zwart (Bert)

2017-01-01

textabstractWe propose a class of strongly efficient rare event simulation estimators for random walks and compound Poisson processes with a regularly varying increment/jump-size distribution in a general large deviations regime. Our estimator is based on an importance sampling strategy that hinges

TIME-VARYING DYNAMICAL STAR FORMATION RATE

Energy Technology Data Exchange (ETDEWEB)

Lee, Eve J.; Chang, Philip; Murray, Norman, E-mail: evelee@berkeley.edu [Canadian Institute for Theoretical Astrophysics, 60 St. George Street, University of Toronto, Toronto, ON M5S 3H8 (Canada)

2015-02-10

We present numerical evidence of dynamic star formation in which the accreted stellar mass grows superlinearly with time, roughly as t {sup 2}. We perform simulations of star formation in self-gravitating hydrodynamic and magnetohydrodynamic turbulence that is continuously driven. By turning the self-gravity of the gas in the simulations on or off, we demonstrate that self-gravity is the dominant physical effect setting the mass accretion rate at early times before feedback effects take over, contrary to theories of turbulence-regulated star formation. We find that gravitational collapse steepens the density profile around stars, generating the power-law tail on what is otherwise a lognormal density probability distribution function. Furthermore, we find turbulent velocity profiles to flatten inside collapsing regions, altering the size-line width relation. This local flattening reflects enhancements of turbulent velocity on small scales, as verified by changes to the velocity power spectra. Our results indicate that gas self-gravity dynamically alters both density and velocity structures in clouds, giving rise to a time-varying star formation rate. We find that a substantial fraction of the gas that forms stars arrives via low-density flows, as opposed to accreting through high-density filaments.

Time-varying and time-invariant dimensions of depression in children and adolescents: Implications for cross-informant agreement.

Science.gov (United States)

Cole, David A; Martin, Joan M; Jacquez, Farrah M; Tram, Jane M; Zelkowitz, Rachel; Nick, Elizabeth A; Rights, Jason D

2017-07-01

The longitudinal structure of depression in children and adolescents was examined by applying a Trait-State-Occasion structural equation model to 4 waves of self, teacher, peer, and parent reports in 2 age groups (9 to 13 and 13 to 16 years old). Analyses revealed that the depression latent variable consisted of 2 longitudinal factors: a time-invariant dimension that was completely stable over time and a time-varying dimension that was not perfectly stable over time. Different sources of information were differentially sensitive to these 2 dimensions. Among adolescents, self- and parent reports better reflected the time-invariant aspects. For children and adolescents, peer and teacher reports better reflected the time-varying aspects. Relatively high cross-informant agreement emerged for the time-invariant dimension in both children and adolescents. Cross-informant agreement for the time-varying dimension was high for adolescents but very low for children. Implications emerge for theoretical models of depression and for its measurement, especially when attempting to predict changes in depression in the context of longitudinal studies. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

PCA-based detection of damage in time-varying systems

Science.gov (United States)

Bellino, A.; Fasana, A.; Garibaldi, L.; Marchesiello, S.

2010-10-01

When performing Structural Health Monitoring, it is well known that the natural frequencies do not depend only on the damage but also on environmental conditions, such as temperature and humidity. The Principal Component Analysis is used to take this problem into account, because it allows eliminating the effect of external factors. The purpose of the present work is to show that this technique can be successfully used not only for time-invariant systems, but also for time-varying ones. Referring to the latter, one of the most studied systems which shows these characteristics is the bridge with crossing loads, such as the case of the railway bridge studied in present paper; in this case, the mass and the velocity of the train can be considered as "environmental" factors.This paper, after a brief description of the PCA method and one example of its application on time-invariant systems, presents the great potentialities of the methodology when applied to time-varying systems. The results show that this method is able to better detect the presence of damage and also to properly distinguish among different levels of crack depths.

Microstructure, mechanical, and in vitro properties of mica glass-ceramics with varying fluorine content.

Science.gov (United States)

Molla, Atiar Rahaman; Basu, Bikramjit

2009-04-01

The design and development of glass ceramic materials provide us the unique opportunity to study the microstructure development with changes in either base glass composition or heat treatment conditions as well as to understand processing-microstructure-property (mechanical/biological) relationship. In the present work, it is demonstrated how various crystal morphology can develop when F(-) content in base glass (K(2)O-B(2)O(3)-Al(2)O(3)-SiO(2)-MgO-F) is varied in the range of 1.08-3.85% and when all are heat treated at varying temperatures of 1000-1120 degrees C. For some selected heat treatment temperature, the heat treatment time is also varied over 4-24 h. It was established that with increase in fluoride content in the glass composition, the crystal volume fraction of the glass-ceramic decreases. Using 1.08% fluoride, more than 80% crystal volume fraction could be achieved in the K(2)O-B(2)O(3)-Al(2)O(3)-SiO(2)-MgO-F system. It was observed that with lower fluoride content glass-ceramic, if heated at 1040 degrees C for 12 h, an oriented microstructure with 'envelop like' crystals can develop. For glass ceramics with higher fluorine content (2.83% or 3.85%), hexagonal-shaped crystals are formed. Importantly, high hardness of around 8 GPa has been measured in glass ceramics with maximum amount of crystals. The three-point flexural strength and elastic modulus of the glass-ceramic (heat treated at 1040 degrees C for 24 h) was 80 MPa and 69 GPa of the sample containing 3.85% fluorine, whereas, similar properties obtained for the sample containing 1.08% F(-) was 94 MPa and 57 GPa, respectively. Further, in vitro dissolution study of the all three glass-ceramic composition in artificial saliva (AS) revealed that leached fluoride ion concentration was 0.44 ppm, when the samples were immersed in AS for 8 weeks. This was much lower than the WHO recommended safety limits of 1.5 ppm. Among all the investigated glass-ceramic samples, the glass ceramic with 3.85% F

On the synchronization of neural networks containing time-varying delays and sector nonlinearity

International Nuclear Information System (INIS)

Yan, J.-J.; Lin, J.-S.; Hung, M.-L.; Liao, T.-L.

2007-01-01

We present a systematic design procedure for synchronization of neural networks subject to time-varying delays and sector nonlinearity in the control input. Based on the drive-response concept and the Lyapunov stability theorem, a memoryless decentralized control law is proposed which guarantees exponential synchronization even when input nonlinearity is present. The supplementary requirement that the time-derivative of time-varying delays must be smaller than one is released for the proposed control scheme. A four-dimensional Hopfield neural network with time-varying delays is presented as the illustrative example to demonstrate the effectiveness of the proposed synchronization scheme

Time distributions of solar energetic particle events: Are SEPEs really random?

Science.gov (United States)

Jiggens, P. T. A.; Gabriel, S. B.

2009-10-01

Solar energetic particle events (SEPEs) can exhibit flux increases of several orders of magnitude over background levels and have always been considered to be random in nature in statistical models with no dependence of any one event on the occurrence of previous events. We examine whether this assumption of randomness in time is correct. Engineering modeling of SEPEs is important to enable reliable and efficient design of both Earth-orbiting and interplanetary spacecraft and future manned missions to Mars and the Moon. All existing engineering models assume that the frequency of SEPEs follows a Poisson process. We present analysis of the event waiting times using alternative distributions described by Lévy and time-dependent Poisson processes and compared these with the usual Poisson distribution. The results show significant deviation from a Poisson process and indicate that the underlying physical processes might be more closely related to a Lévy-type process, suggesting that there is some inherent “memory” in the system. Inherent Poisson assumptions of stationarity and event independence are investigated, and it appears that they do not hold and can be dependent upon the event definition used. SEPEs appear to have some memory indicating that events are not completely random with activity levels varying even during solar active periods and are characterized by clusters of events. This could have significant ramifications for engineering models of the SEP environment, and it is recommended that current statistical engineering models of the SEP environment should be modified to incorporate long-term event dependency and short-term system memory.

A Hilbert transform method for parameter identification of time-varying structures with observer techniques

International Nuclear Information System (INIS)

Wang, Zuo-Cai; Ren, Wei-Xin; Chen, Gen-Da

2012-01-01

This paper presents a recursive Hilbert transform method for the time-varying property identification of large-scale shear-type buildings with limited sensor deployments. An observer technique is introduced to estimate the building responses from limited available measurements. For an n-story shear-type building with l measurements (l ≤ n), the responses of other stories without measurements can be estimated based on the first r mode shapes (r ≤ l) as-built conditions and l measurements. Both the measured responses and evaluated responses and their Hilbert transforms are then used to track any variation of structural parameters of a multi-story building over time. Given floor masses, both the stiffness and damping coefficients of the building are identified one-by-one from the top to the bottom story. When variations of parameters are detected, a new developed branch-and-bound technique can be used to update the first r mode shapes with the identified parameters. A 60-story shear building with abruptly varying stiffness at different floors is simulated as an example. The numerical results indicate that the proposed method can detect variations of the parameters of large-scale shear-type buildings with limited sensor deployments at appropriate locations. (paper)

Properties and simulation of α-permanental random fields

DEFF Research Database (Denmark)

Møller, Jesper; Rubak, Ege Holger

An α-permanental random field is briefly speaking a model for a collection of random variables with positive associations, where α is a positive number and the probability generating function is given in terms of a covariance or more general function so that density and moment expressions are given...... by certain α-permanents. Though such models possess many appealing probabilistic properties, many statisticians seem unaware of  α-permanental random fields and their potential applications. The purpose of this paper is first to summarize useful probabilistic results using the simplest possible setting......, and second to study stochastic constructions and simulation techniques, which should provide a useful basis for discussing the statistical aspects in future work. The paper also discusses some examples of  α-permanental random fields....

Asymptotic stability of discrete-time systems with time-varying delay subject to saturation nonlinearities

International Nuclear Information System (INIS)

Chen, S.-F.

2009-01-01

The asymptotic stability problem for discrete-time systems with time-varying delay subject to saturation nonlinearities is addressed in this paper. In terms of linear matrix inequalities (LMIs), a delay-dependent sufficient condition is derived to ensure the asymptotic stability. A numerical example is given to demonstrate the theoretical results.

The limit distribution of the maximum increment of a random walk with regularly varying jump size distribution

DEFF Research Database (Denmark)

Mikosch, Thomas Valentin; Rackauskas, Alfredas

2010-01-01

In this paper, we deal with the asymptotic distribution of the maximum increment of a random walk with a regularly varying jump size distribution. This problem is motivated by a long-standing problem on change point detection for epidemic alternatives. It turns out that the limit distribution...... of the maximum increment of the random walk is one of the classical extreme value distributions, the Fréchet distribution. We prove the results in the general framework of point processes and for jump sizes taking values in a separable Banach space...

Testing and estimating time-varying elasticities of Swiss gasoline demand

International Nuclear Information System (INIS)

Neto, David

2012-01-01

This paper is intended to test and estimate time-varying elasticities for gasoline demand in Switzerland. For this purpose, a smooth time-varying cointegrating parameters model is investigated in order to describe smooth mutations of the Swiss gasoline demand. The methodology, based on Chebyshev polynomials, is rigorously outlined. Our empirical finding states that the time-invariance assumption does not hold for long-run price and income elasticities. Furthermore they highlight that gasoline demand passed through some periods of sensitivity and non sensitivity with respect to the price. Our empirical statements are of great importance to assess the performance of a gasoline tax as an instrument for CO 2 reduction policy. Indeed, such an instrument can contribute to reduce emissions of greenhouse gases only if the demand is not fully inelastic with respect to the price. Our results suggest that such a carbon-tax would not be always suitable since the price elasticity is found not stable over time and not always significant.

Studies in astronomical time series analysis: Modeling random processes in the time domain

Science.gov (United States)

Scargle, J. D.

1979-01-01

Random process models phased in the time domain are used to analyze astrophysical time series data produced by random processes. A moving average (MA) model represents the data as a sequence of pulses occurring randomly in time, with random amplitudes. An autoregressive (AR) model represents the correlations in the process in terms of a linear function of past values. The best AR model is determined from sampled data and transformed to an MA for interpretation. The randomness of the pulse amplitudes is maximized by a FORTRAN algorithm which is relatively stable numerically. Results of test cases are given to study the effects of adding noise and of different distributions for the pulse amplitudes. A preliminary analysis of the optical light curve of the quasar 3C 273 is given.

Time-Varying Biased Proportional Guidance with Seeker’s Field-of-View Limit

OpenAIRE

Yang, Zhe; Wang, Hui; Lin, Defu

2016-01-01

Traditional guidance laws with range-to-go information or time-to-go estimation may not be implemented in passive homing missiles since passive seekers cannot measure relative range directly. A time-varying biased proportional guidance law, which only uses line-of-sight (LOS) rate and look angle information, is proposed to satisfy both impact angle constraint and seeker’s field-of-view (FOV) limit. In the proposed guidance law, two time-varying bias terms are applied to divide the trajectory ...

Simple Model with Time-Varying Fine-Structure ``Constant''

Science.gov (United States)

Berman, M. S.

2009-10-01

Extending the original version written in colaboration with L.A. Trevisan, we study the generalisation of Dirac's LNH, so that time-variation of the fine-structure constant, due to varying electrical and magnetic permittivities is included along with other variations (cosmological and gravitational ``constants''), etc. We consider the present Universe, and also an inflationary scenario. Rotation of the Universe is a given possibility in this model.

Contact Dynamics of EHL Contacts under Time Varying Conditions

NARCIS (Netherlands)

Venner, Cornelis H.; Popovici, G.; Wijnant, Ysbrand H.; Dalmaz, G.; Lubrecht, A.A.; Priest, M

2004-01-01

By means of numerical simulations of two situations with time varying operating conditions it is shown that the dynamic behaviour of Elasto-Hydrodynamically Lubricated contacts in terms of vibrations can be characterized as: Changes in the mutual approach lead to film thickness changes in the inlet

Visualizing Robustness of Critical Points for 2D Time-Varying Vector Fields

KAUST Repository

Wang, B.

2013-06-01

Analyzing critical points and their temporal evolutions plays a crucial role in understanding the behavior of vector fields. A key challenge is to quantify the stability of critical points: more stable points may represent more important phenomena or vice versa. The topological notion of robustness is a tool which allows us to quantify rigorously the stability of each critical point. Intuitively, the robustness of a critical point is the minimum amount of perturbation necessary to cancel it within a local neighborhood, measured under an appropriate metric. In this paper, we introduce a new analysis and visualization framework which enables interactive exploration of robustness of critical points for both stationary and time-varying 2D vector fields. This framework allows the end-users, for the first time, to investigate how the stability of a critical point evolves over time. We show that this depends heavily on the global properties of the vector field and that structural changes can correspond to interesting behavior. We demonstrate the practicality of our theories and techniques on several datasets involving combustion and oceanic eddy simulations and obtain some key insights regarding their stable and unstable features. © 2013 The Author(s) Computer Graphics Forum © 2013 The Eurographics Association and Blackwell Publishing Ltd.

Visualizing Robustness of Critical Points for 2D Time-Varying Vector Fields

KAUST Repository

Wang, B.; Rosen, P.; Skraba, P.; Bhatia, H.; Pascucci, V.

2013-01-01

Analyzing critical points and their temporal evolutions plays a crucial role in understanding the behavior of vector fields. A key challenge is to quantify the stability of critical points: more stable points may represent more important phenomena or vice versa. The topological notion of robustness is a tool which allows us to quantify rigorously the stability of each critical point. Intuitively, the robustness of a critical point is the minimum amount of perturbation necessary to cancel it within a local neighborhood, measured under an appropriate metric. In this paper, we introduce a new analysis and visualization framework which enables interactive exploration of robustness of critical points for both stationary and time-varying 2D vector fields. This framework allows the end-users, for the first time, to investigate how the stability of a critical point evolves over time. We show that this depends heavily on the global properties of the vector field and that structural changes can correspond to interesting behavior. We demonstrate the practicality of our theories and techniques on several datasets involving combustion and oceanic eddy simulations and obtain some key insights regarding their stable and unstable features. © 2013 The Author(s) Computer Graphics Forum © 2013 The Eurographics Association and Blackwell Publishing Ltd.

Gray bootstrap method for estimating frequency-varying random vibration signals with small samples

Directory of Open Access Journals (Sweden)

Wang Yanqing

2014-04-01

Full Text Available During environment testing, the estimation of random vibration signals (RVS is an important technique for the airborne platform safety and reliability. However, the available methods including extreme value envelope method (EVEM, statistical tolerances method (STM and improved statistical tolerance method (ISTM require large samples and typical probability distribution. Moreover, the frequency-varying characteristic of RVS is usually not taken into account. Gray bootstrap method (GBM is proposed to solve the problem of estimating frequency-varying RVS with small samples. Firstly, the estimated indexes are obtained including the estimated interval, the estimated uncertainty, the estimated value, the estimated error and estimated reliability. In addition, GBM is applied to estimating the single flight testing of certain aircraft. At last, in order to evaluate the estimated performance, GBM is compared with bootstrap method (BM and gray method (GM in testing analysis. The result shows that GBM has superiority for estimating dynamic signals with small samples and estimated reliability is proved to be 100% at the given confidence level.

Tolerable Time-Varying Overflow on Grass-Covered Slopes

Directory of Open Access Journals (Sweden)

Steven A. Hughes

2015-03-01

Full Text Available Engineers require estimates of tolerable overtopping limits for grass-covered levees, dikes, and embankments that might experience steady overflow. Realistic tolerance estimates can be used for both resilient design and risk assessment. A simple framework is developed for estimating tolerable overtopping on grass-covered slopes caused by slowly-varying (in time overtopping discharge (e.g., events like storm surges or river flood waves. The framework adapts the well-known Hewlett curves of tolerable limiting velocity as a function of overflow duration. It has been hypothesized that the form of the Hewlett curves suggests that the grass erosion process is governed by the flow work on the slope above a critical threshold velocity (referred to as excess work, and the tolerable erosional limit is reached when the cumulative excess work exceeds a given value determined from the time-dependent Hewlett curves. The cumulative excess work is expressed in terms of overflow discharge above a critical discharge that slowly varies in time, similar to a discharge hydrograph. The methodology is easily applied using forecast storm surge hydrographs at specific locations where wave action is minimal. For preliminary planning purposes, when storm surge hydrographs are unavailable, hypothetical equations for the water level and overflow discharge hydrographs are proposed in terms of the values at maximum overflow and the total duration of overflow. An example application is given to illustrate use of the methodology.

Path probabilities of continuous time random walks

International Nuclear Information System (INIS)

Eule, Stephan; Friedrich, Rudolf

2014-01-01

Employing the path integral formulation of a broad class of anomalous diffusion processes, we derive the exact relations for the path probability densities of these processes. In particular, we obtain a closed analytical solution for the path probability distribution of a Continuous Time Random Walk (CTRW) process. This solution is given in terms of its waiting time distribution and short time propagator of the corresponding random walk as a solution of a Dyson equation. Applying our analytical solution we derive generalized Feynman–Kac formulae. (paper)

Finite-Time H∞ Filtering for Linear Continuous Time-Varying Systems with Uncertain Observations

Directory of Open Access Journals (Sweden)

Huihong Zhao

2012-01-01

Full Text Available This paper is concerned with the finite-time H∞ filtering problem for linear continuous time-varying systems with uncertain observations and ℒ2-norm bounded noise. The design of finite-time H∞ filter is equivalent to the problem that a certain indefinite quadratic form has a minimum and the filter is such that the minimum is positive. The quadratic form is related to a Krein state-space model according to the Krein space linear estimation theory. By using the projection theory in Krein space, the finite-time H∞ filtering problem is solved. A numerical example is given to illustrate the performance of the H∞ filter.

Continuous-time random walks on networks with vertex- and time-dependent forcing.

Science.gov (United States)

Angstmann, C N; Donnelly, I C; Henry, B I; Langlands, T A M

2013-08-01

We have investigated the transport of particles moving as random walks on the vertices of a network, subject to vertex- and time-dependent forcing. We have derived the generalized master equations for this transport using continuous time random walks, characterized by jump and waiting time densities, as the underlying stochastic process. The forcing is incorporated through a vertex- and time-dependent bias in the jump densities governing the random walking particles. As a particular case, we consider particle forcing proportional to the concentration of particles on adjacent vertices, analogous to self-chemotactic attraction in a spatial continuum. Our algebraic and numerical studies of this system reveal an interesting pair-aggregation pattern formation in which the steady state is composed of a high concentration of particles on a small number of isolated pairs of adjacent vertices. The steady states do not exhibit this pair aggregation if the transport is random on the vertices, i.e., without forcing. The manifestation of pair aggregation on a transport network may thus be a signature of self-chemotactic-like forcing.

Identification of Time Varying Civil Engineering Structures using Multivariate Recursive Time Domain Models

DEFF Research Database (Denmark)

Andersen, P.; Skjærbæk, P. S.; Kirkegaard, Poul Henning

with the smoothed quanties which have been obtained from SARCOF. The results show the usefulness of the technique for identification of a time varying civil engineering structure. It is found that all the techniques give reliable estiates of the frequencies of the two lowest modes and the first mode shape. Only...

Stochastic analysis of epidemics on adaptive time varying networks

Science.gov (United States)

Kotnis, Bhushan; Kuri, Joy

2013-06-01

Many studies investigating the effect of human social connectivity structures (networks) and human behavioral adaptations on the spread of infectious diseases have assumed either a static connectivity structure or a network which adapts itself in response to the epidemic (adaptive networks). However, human social connections are inherently dynamic or time varying. Furthermore, the spread of many infectious diseases occur on a time scale comparable to the time scale of the evolving network structure. Here we aim to quantify the effect of human behavioral adaptations on the spread of asymptomatic infectious diseases on time varying networks. We perform a full stochastic analysis using a continuous time Markov chain approach for calculating the outbreak probability, mean epidemic duration, epidemic reemergence probability, etc. Additionally, we use mean-field theory for calculating epidemic thresholds. Theoretical predictions are verified using extensive simulations. Our studies have uncovered the existence of an “adaptive threshold,” i.e., when the ratio of susceptibility (or infectivity) rate to recovery rate is below the threshold value, adaptive behavior can prevent the epidemic. However, if it is above the threshold, no amount of behavioral adaptations can prevent the epidemic. Our analyses suggest that the interaction patterns of the infected population play a major role in sustaining the epidemic. Our results have implications on epidemic containment policies, as awareness campaigns and human behavioral responses can be effective only if the interaction levels of the infected populace are kept in check.

Time-varying long term memory in the European Union stock markets

Science.gov (United States)

Sensoy, Ahmet; Tabak, Benjamin M.

2015-10-01

This paper proposes a new efficiency index to model time-varying inefficiency in stock markets. We focus on European stock markets and show that they have different degrees of time-varying efficiency. We observe that the 2008 global financial crisis has an adverse effect on almost all EU stock markets. However, the Eurozone sovereign debt crisis has a significant adverse effect only on the markets in France, Spain and Greece. For the late members, joining EU does not have a uniform effect on stock market efficiency. Our results have important implications for policy makers, investors, risk managers and academics.

Multifractality, imperfect scaling and hydrological properties of rainfall time series simulated by continuous universal multifractal and discrete random cascade models

Directory of Open Access Journals (Sweden)

F. Serinaldi

2010-12-01

Full Text Available Discrete multiplicative random cascade (MRC models were extensively studied and applied to disaggregate rainfall data, thanks to their formal simplicity and the small number of involved parameters. Focusing on temporal disaggregation, the rationale of these models is based on multiplying the value assumed by a physical attribute (e.g., rainfall intensity at a given time scale L, by a suitable number b of random weights, to obtain b attribute values corresponding to statistically plausible observations at a smaller L/b time resolution. In the original formulation of the MRC models, the random weights were assumed to be independent and identically distributed. However, for several studies this hypothesis did not appear to be realistic for the observed rainfall series as the distribution of the weights was shown to depend on the space-time scale and rainfall intensity. Since these findings contrast with the scale invariance assumption behind the MRC models and impact on the applicability of these models, it is worth studying their nature. This study explores the possible presence of dependence of the parameters of two discrete MRC models on rainfall intensity and time scale, by analyzing point rainfall series with 5-min time resolution. Taking into account a discrete microcanonical (MC model based on beta distribution and a discrete canonical beta-logstable (BLS, the analysis points out that the relations between the parameters and rainfall intensity across the time scales are detectable and can be modeled by a set of simple functions accounting for the parameter-rainfall intensity relationship, and another set describing the link between the parameters and the time scale. Therefore, MC and BLS models were modified to explicitly account for these relationships and compared with the continuous in scale universal multifractal (CUM model, which is used as a physically based benchmark model. Monte Carlo simulations point out

Adaptive Neural Network Control for Nonlinear Hydraulic Servo-System with Time-Varying State Constraints

Directory of Open Access Journals (Sweden)

Shu-Min Lu

2017-01-01

Full Text Available An adaptive neural network control problem is addressed for a class of nonlinear hydraulic servo-systems with time-varying state constraints. In view of the low precision problem of the traditional hydraulic servo-system which is caused by the tracking errors surpassing appropriate bound, the previous works have shown that the constraint for the system is a good way to solve the low precision problem. Meanwhile, compared with constant constraints, the time-varying state constraints are more general in the actual systems. Therefore, when the states of the system are forced to obey bounded time-varying constraint conditions, the high precision tracking performance of the system can be easily realized. In order to achieve this goal, the time-varying barrier Lyapunov function (TVBLF is used to prevent the states from violating time-varying constraints. By the backstepping design, the adaptive controller will be obtained. A radial basis function neural network (RBFNN is used to estimate the uncertainties. Based on analyzing the stability of the hydraulic servo-system, we show that the error signals are bounded in the compacts sets; the time-varying state constrains are never violated and all singles of the hydraulic servo-system are bounded. The simulation and experimental results show that the tracking accuracy of system is improved and the controller has fast tracking ability and strong robustness.

Estimating time-varying exposure-outcome associations using case-control data: logistic and case-cohort analyses.

Science.gov (United States)

Keogh, Ruth H; Mangtani, Punam; Rodrigues, Laura; Nguipdop Djomo, Patrick

2016-01-05

Traditional analyses of standard case-control studies using logistic regression do not allow estimation of time-varying associations between exposures and the outcome. We present two approaches which allow this. The motivation is a study of vaccine efficacy as a function of time since vaccination. Our first approach is to estimate time-varying exposure-outcome associations by fitting a series of logistic regressions within successive time periods, reusing controls across periods. Our second approach treats the case-control sample as a case-cohort study, with the controls forming the subcohort. In the case-cohort analysis, controls contribute information at all times they are at risk. Extensions allow left truncation, frequency matching and, using the case-cohort analysis, time-varying exposures. Simulations are used to investigate the methods. The simulation results show that both methods give correct estimates of time-varying effects of exposures using standard case-control data. Using the logistic approach there are efficiency gains by reusing controls over time and care should be taken over the definition of controls within time periods. However, using the case-cohort analysis there is no ambiguity over the definition of controls. The performance of the two analyses is very similar when controls are used most efficiently under the logistic approach. Using our methods, case-control studies can be used to estimate time-varying exposure-outcome associations where they may not previously have been considered. The case-cohort analysis has several advantages, including that it allows estimation of time-varying associations as a continuous function of time, while the logistic regression approach is restricted to assuming a step function form for the time-varying association.

Structural nested mean models for assessing time-varying effect moderation.

Science.gov (United States)

Almirall, Daniel; Ten Have, Thomas; Murphy, Susan A

2010-03-01

This article considers the problem of assessing causal effect moderation in longitudinal settings in which treatment (or exposure) is time varying and so are the covariates said to moderate its effect. Intermediate causal effects that describe time-varying causal effects of treatment conditional on past covariate history are introduced and considered as part of Robins' structural nested mean model. Two estimators of the intermediate causal effects, and their standard errors, are presented and discussed: The first is a proposed two-stage regression estimator. The second is Robins' G-estimator. The results of a small simulation study that begins to shed light on the small versus large sample performance of the estimators, and on the bias-variance trade-off between the two estimators are presented. The methodology is illustrated using longitudinal data from a depression study.

Local inertial oscillations in the surface ocean generated by time-varying winds

Science.gov (United States)

Chen, Shengli; Polton, Jeff A.; Hu, Jianyu; Xing, Jiuxing

2015-12-01

A new relationship is presented to give a review study on the evolution of inertial oscillations in the surface ocean locally generated by time-varying wind stress. The inertial oscillation is expressed as the superposition of a previous oscillation and a newly generated oscillation, which depends upon the time-varying wind stress. This relationship is employed to investigate some idealized wind change events. For a wind series varying temporally with different rates, the induced inertial oscillation is dominated by the wind with the greatest variation. The resonant wind, which rotates anti-cyclonically at the local inertial frequency with time, produces maximal amplitude of inertial oscillations, which grows monotonically. For the wind rotating at non-inertial frequencies, the responses vary periodically, with wind injecting inertial energy when it is in phase with the currents, but removing inertial energy when it is out of phase. The wind rotating anti-cyclonically with time is much more favorable to generate inertial oscillations than the cyclonic rotating wind. The wind with a frequency closer to the inertial frequency generates stronger inertial oscillations. For a diurnal wind, the induced inertial oscillation is dependent on latitude and is most significant at 30 °. This relationship is also applied to examine idealized moving cyclones. The inertial oscillation is much stronger on the right-hand side of the cyclone path than on the left-hand side (in the northern hemisphere). This is due to the wind being anti-cyclonic with time on the right-hand side, but cyclonic on the other side. The inertial oscillation varies with the cyclone translation speed. The optimal translation speed generating the greatest inertial oscillations is 2 m/s at the latitude of 10 ° and gradually increases to 6 m/s at the latitude of 30 °.

Network Coded Cooperation Over Time-Varying Channels

DEFF Research Database (Denmark)

Khamfroush, Hana; Roetter, Daniel Enrique Lucani; Barros, João

2014-01-01

transmissions, e.g., in terms of the rate of packet transmission or the energy consumption. A comprehensive analysis of the MDP solution is carried out under different network conditions to extract optimal rules of packet transmission. Inspired by the extracted rules, we propose two near-optimal heuristics......In this paper, we investigate the optimal design of cooperative network-coded strategies for a three-node wireless network with time-varying, half-duplex erasure channels. To this end, we formulate the problem of minimizing the total cost of transmitting M packets from source to two receivers...... as a Markov Decision Process (MDP). The actions of the MDP model include the source and the type of transmission to be used in a given time slot given perfect knowledge of the system state. The cost of packet transmission is defined such that it can incorporate the difference between broadcast and unicast...

Frequency-scanning interferometry using a time-varying Kalman filter for dynamic tracking measurements.

Science.gov (United States)

Jia, Xingyu; Liu, Zhigang; Tao, Long; Deng, Zhongwen

2017-10-16

Frequency scanning interferometry (FSI) with a single external cavity diode laser (ECDL) and time-invariant Kalman filtering is an effective technique for measuring the distance of a dynamic target. However, due to the hysteresis of the piezoelectric ceramic transducer (PZT) actuator in the ECDL, the optical frequency sweeps of the ECDL exhibit different behaviors, depending on whether the frequency is increasing or decreasing. Consequently, the model parameters of Kalman filter appear time varying in each iteration, which produces state estimation errors with time-invariant filtering. To address this, in this paper, a time-varying Kalman filter is proposed to model the instantaneous movement of a target relative to the different optical frequency tuning durations of the ECDL. The combination of the FSI method with the time-varying Kalman filter was theoretically analyzed, and the simulation and experimental results show the proposed method greatly improves the performance of dynamic FSI measurements.

A behavioral asset pricing model with a time-varying second moment

International Nuclear Information System (INIS)

Chiarella, Carl; He Xuezhong; Wang, Duo

2006-01-01

We develop a simple behavioral asset pricing model with fundamentalists and chartists in order to study price behavior in financial markets when chartists estimate both conditional mean and variance by using a weighted averaging process. Through a stability, bifurcation, and normal form analysis, the market impact of the weighting process and time-varying second moment are examined. It is found that the fundamental price becomes stable (unstable) when the activities from both types of traders are balanced (unbalanced). When the fundamental price becomes unstable, the weighting process leads to different price dynamics, depending on whether the chartists act as either trend followers or contrarians. It is also found that a time-varying second moment of the chartists does not change the stability of the fundamental price, but it does influence the stability of the bifurcations. The bifurcation becomes stable (unstable) when the chartists are more (less) concerned about the market risk characterized by the time-varying second moment. Different routes to complicated price dynamics are also observed. The analysis provides an analytical foundation for the statistical analysis of the corresponding stochastic version of this type of behavioral model

Estimating time-varying exposure-outcome associations using case-control data: logistic and case-cohort analyses

Directory of Open Access Journals (Sweden)

Ruth H. Keogh

2016-01-01

Full Text Available Abstract Background Traditional analyses of standard case-control studies using logistic regression do not allow estimation of time-varying associations between exposures and the outcome. We present two approaches which allow this. The motivation is a study of vaccine efficacy as a function of time since vaccination. Methods Our first approach is to estimate time-varying exposure-outcome associations by fitting a series of logistic regressions within successive time periods, reusing controls across periods. Our second approach treats the case-control sample as a case-cohort study, with the controls forming the subcohort. In the case-cohort analysis, controls contribute information at all times they are at risk. Extensions allow left truncation, frequency matching and, using the case-cohort analysis, time-varying exposures. Simulations are used to investigate the methods. Results The simulation results show that both methods give correct estimates of time-varying effects of exposures using standard case-control data. Using the logistic approach there are efficiency gains by reusing controls over time and care should be taken over the definition of controls within time periods. However, using the case-cohort analysis there is no ambiguity over the definition of controls. The performance of the two analyses is very similar when controls are used most efficiently under the logistic approach. Conclusions Using our methods, case-control studies can be used to estimate time-varying exposure-outcome associations where they may not previously have been considered. The case-cohort analysis has several advantages, including that it allows estimation of time-varying associations as a continuous function of time, while the logistic regression approach is restricted to assuming a step function form for the time-varying association.

Phase transition of the susceptible-infected-susceptible dynamics on time-varying configuration model networks

Science.gov (United States)

St-Onge, Guillaume; Young, Jean-Gabriel; Laurence, Edward; Murphy, Charles; Dubé, Louis J.

2018-02-01

We present a degree-based theoretical framework to study the susceptible-infected-susceptible (SIS) dynamics on time-varying (rewired) configuration model networks. Using this framework on a given degree distribution, we provide a detailed analysis of the stationary state using the rewiring rate to explore the whole range of the time variation of the structure relative to that of the SIS process. This analysis is suitable for the characterization of the phase transition and leads to three main contributions: (1) We obtain a self-consistent expression for the absorbing-state threshold, able to capture both collective and hub activation. (2) We recover the predictions of a number of existing approaches as limiting cases of our analysis, providing thereby a unifying point of view for the SIS dynamics on random networks. (3) We obtain bounds for the critical exponents of a number of quantities in the stationary state. This allows us to reinterpret the concept of hub-dominated phase transition. Within our framework, it appears as a heterogeneous critical phenomenon: observables for different degree classes have a different scaling with the infection rate. This phenomenon is followed by the successive activation of the degree classes beyond the epidemic threshold.

Disk Density Tuning of a Maximal Random Packing.

Science.gov (United States)

Ebeida, Mohamed S; Rushdi, Ahmad A; Awad, Muhammad A; Mahmoud, Ahmed H; Yan, Dong-Ming; English, Shawn A; Owens, John D; Bajaj, Chandrajit L; Mitchell, Scott A

2016-08-01

We introduce an algorithmic framework for tuning the spatial density of disks in a maximal random packing, without changing the sizing function or radii of disks. Starting from any maximal random packing such as a Maximal Poisson-disk Sampling (MPS), we iteratively relocate, inject (add), or eject (remove) disks, using a set of three successively more-aggressive local operations. We may achieve a user-defined density, either more dense or more sparse, almost up to the theoretical structured limits. The tuned samples are conflict-free, retain coverage maximality, and, except in the extremes, retain the blue noise randomness properties of the input. We change the density of the packing one disk at a time, maintaining the minimum disk separation distance and the maximum domain coverage distance required of any maximal packing. These properties are local, and we can handle spatially-varying sizing functions. Using fewer points to satisfy a sizing function improves the efficiency of some applications. We apply the framework to improve the quality of meshes, removing non-obtuse angles; and to more accurately model fiber reinforced polymers for elastic and failure simulations.

Robust stabilisation of time-varying delay systems with probabilistic uncertainties

Science.gov (United States)

Jiang, Ning; Xiong, Junlin; Lam, James

2016-09-01

For robust stabilisation of time-varying delay systems, only sufficient conditions are available to date. A natural question is as follows: if the existing sufficient conditions are not satisfied, and hence no controllers can be found, what can one do to improve the stability performance of time-varying delay systems? This question is addressed in this paper when there is a probabilistic structure on the parameter uncertainty set. A randomised algorithm is proposed to design a state-feedback controller, which stabilises the system over the uncertainty domain in a probabilistic sense. The capability of the designed controller is quantified by the probability of stability of the resulting closed-loop system. The accuracy of the solution obtained from the randomised algorithm is also analysed. Finally, numerical examples are used to illustrate the effectiveness and advantages of the developed controller design approach.

Robust Stabilization of Discrete-Time Systems with Time-Varying Delay: An LMI Approach

Directory of Open Access Journals (Sweden)

Valter J. S. Leite

2008-01-01

Full Text Available Sufficient linear matrix inequality (LMI conditions to verify the robust stability and to design robust state feedback gains for the class of linear discrete-time systems with time-varying delay and polytopic uncertainties are presented. The conditions are obtained through parameter-dependent Lyapunov-Krasovskii functionals and use some extra variables, which yield less conservative LMI conditions. Both problems, robust stability analysis and robust synthesis, are formulated as convex problems where all system matrices can be affected by uncertainty. Some numerical examples are presented to illustrate the advantages of the proposed LMI conditions.

Dynamical properties of the S =1/2 random Heisenberg chain

Science.gov (United States)

Shu, Yu-Rong; Dupont, Maxime; Yao, Dao-Xin; Capponi, Sylvain; Sandvik, Anders W.

2018-03-01

We study dynamical properties at finite temperature (T ) of Heisenberg spin chains with random antiferromagnetic exchange couplings, which realize the random singlet phase in the low-energy limit, using three complementary numerical methods: exact diagonalization, matrix-product-state algorithms, and stochastic analytic continuation of quantum Monte Carlo results in imaginary time. Specifically, we investigate the dynamic spin structure factor S (q ,ω ) and its ω →0 limit, which are closely related to inelastic neutron scattering and nuclear magnetic resonance (NMR) experiments (through the spin-lattice relaxation rate 1 /T1 ). Our study reveals a continuous narrow band of low-energy excitations in S (q ,ω ) , extending throughout the q space, instead of being restricted to q ≈0 and q ≈π as found in the uniform system. Close to q =π , the scaling properties of these excitations are well captured by the random-singlet theory, but disagreements also exist with some aspects of the predicted q dependence further away from q =π . Furthermore we also find spin diffusion effects close to q =0 that are not contained within the random-singlet theory but give non-negligible contributions to the mean 1 /T1 . To compare with NMR experiments, we consider the distribution of the local relaxation rates 1 /T1 . We show that the local 1 /T1 values are broadly distributed, approximately according to a stretched exponential. The mean 1 /T1 first decreases with T , but below a crossover temperature it starts to increase and likely diverges in the limit of a small nuclear resonance frequency ω0. Although a similar divergent behavior has been predicted and experimentally observed for the static uniform susceptibility, this divergent behavior of the mean 1 /T1 has never been experimentally observed. Indeed, we show that the divergence of the mean 1 /T1 is due to rare events in the disordered chains and is concealed in experiments, where the typical 1 /T1 value is accessed.

Continuous-time quantum random walks require discrete space

International Nuclear Information System (INIS)

Manouchehri, K; Wang, J B

2007-01-01

Quantum random walks are shown to have non-intuitive dynamics which makes them an attractive area of study for devising quantum algorithms for long-standing open problems as well as those arising in the field of quantum computing. In the case of continuous-time quantum random walks, such peculiar dynamics can arise from simple evolution operators closely resembling the quantum free-wave propagator. We investigate the divergence of quantum walk dynamics from the free-wave evolution and show that, in order for continuous-time quantum walks to display their characteristic propagation, the state space must be discrete. This behavior rules out many continuous quantum systems as possible candidates for implementing continuous-time quantum random walks

Continuous-time quantum random walks require discrete space

Science.gov (United States)

Manouchehri, K.; Wang, J. B.

2007-11-01

Quantum random walks are shown to have non-intuitive dynamics which makes them an attractive area of study for devising quantum algorithms for long-standing open problems as well as those arising in the field of quantum computing. In the case of continuous-time quantum random walks, such peculiar dynamics can arise from simple evolution operators closely resembling the quantum free-wave propagator. We investigate the divergence of quantum walk dynamics from the free-wave evolution and show that, in order for continuous-time quantum walks to display their characteristic propagation, the state space must be discrete. This behavior rules out many continuous quantum systems as possible candidates for implementing continuous-time quantum random walks.

The optimal manufacturing batch size with rework under time-varying demand process for a finite time horizon

Science.gov (United States)

Musa, Sarah; Supadi, Siti Suzlin; Omar, Mohd

2014-07-01

Rework is one of the solutions to some of the main issues in reverse logistic and green supply chain as it reduces production cost and environmental problem. Many researchers focus on developing rework model, but to the knowledge of the author, none of them has developed a model for time-varying demand rate. In this paper, we extend previous works and develop multiple batch production system for time-varying demand rate with rework. In this model, the rework is done within the same production cycle.

Robust stability analysis of uncertain stochastic neural networks with interval time-varying delay

International Nuclear Information System (INIS)

Feng Wei; Yang, Simon X.; Fu Wei; Wu Haixia

2009-01-01

This paper addresses the stability analysis problem for uncertain stochastic neural networks with interval time-varying delays. The parameter uncertainties are assumed to be norm bounded, and the delay factor is assumed to be time-varying and belong to a given interval, which means that the lower and upper bounds of interval time-varying delays are available. A sufficient condition is derived such that for all admissible uncertainties, the considered neural network is robustly, globally, asymptotically stable in the mean square. Some stability criteria are formulated by means of the feasibility of a linear matrix inequality (LMI), which can be effectively solved by some standard numerical packages. Finally, numerical examples are provided to demonstrate the usefulness of the proposed criteria.

Nonlinearly Activated Neural Network for Solving Time-Varying Complex Sylvester Equation.

Science.gov (United States)

Li, Shuai; Li, Yangming

2013-10-28

The Sylvester equation is often encountered in mathematics and control theory. For the general time-invariant Sylvester equation problem, which is defined in the domain of complex numbers, the Bartels-Stewart algorithm and its extensions are effective and widely used with an O(n³) time complexity. When applied to solving the time-varying Sylvester equation, the computation burden increases intensively with the decrease of sampling period and cannot satisfy continuous realtime calculation requirements. For the special case of the general Sylvester equation problem defined in the domain of real numbers, gradient-based recurrent neural networks are able to solve the time-varying Sylvester equation in real time, but there always exists an estimation error while a recently proposed recurrent neural network by Zhang et al [this type of neural network is called Zhang neural network (ZNN)] converges to the solution ideally. The advancements in complex-valued neural networks cast light to extend the existing real-valued ZNN for solving the time-varying real-valued Sylvester equation to its counterpart in the domain of complex numbers. In this paper, a complex-valued ZNN for solving the complex-valued Sylvester equation problem is investigated and the global convergence of the neural network is proven with the proposed nonlinear complex-valued activation functions. Moreover, a special type of activation function with a core function, called sign-bi-power function, is proven to enable the ZNN to converge in finite time, which further enhances its advantage in online processing. In this case, the upper bound of the convergence time is also derived analytically. Simulations are performed to evaluate and compare the performance of the neural network with different parameters and activation functions. Both theoretical analysis and numerical simulations validate the effectiveness of the proposed method.

Delay-Dependent Exponential Stability for Discrete-Time BAM Neural Networks with Time-Varying Delays

Directory of Open Access Journals (Sweden)

Yonggang Chen

2008-01-01

Full Text Available This paper considers the delay-dependent exponential stability for discrete-time BAM neural networks with time-varying delays. By constructing the new Lyapunov functional, the improved delay-dependent exponential stability criterion is derived in terms of linear matrix inequality (LMI. Moreover, in order to reduce the conservativeness, some slack matrices are introduced in this paper. Two numerical examples are presented to show the effectiveness and less conservativeness of the proposed method.

Sojourn time asymptotics in Processor Sharing queues with varying service rate

NARCIS (Netherlands)

Egorova, R.; Mandjes, M.R.H.; Zwart, B.

2007-01-01

Abstract This paper addresses the sojourn time asymptotics for a GI/GI/⋅ queue operating under the Processor Sharing (PS) discipline with stochastically varying service rate. Our focus is on the logarithmic estimates of the tail of sojourn-time distribution, under the assumption that the job-size

A Method of Time-Varying Rayleigh Channel Tracking in MIMO Radio System

Institute of Scientific and Technical Information of China (English)

GONG Yan-fei; HE Zi-shu; HAN Chun-lin

2005-01-01

A method of MIMO channel tracking based on Kalman filter and MMSE-DFE is proposed. The Kalman filter tracks the time-varying channel by using the MMSE-DFE decision and the MMSE-DFE conducts the next decision by using the channel estimates produced by the Kalman filter. Polynomial fitting is used to bridge the gap between the channel estimates produced by the Kalman filter and those needed for the DFE decision. Computer simulation demonstrates that this method can track the MIMO time-varying channel effectively.

Models of quality-adjusted life years when health varies over time

DEFF Research Database (Denmark)

Hansen, Kristian Schultz; Østerdal, Lars Peter Raahave

2006-01-01

Qualityadjusted life year (QALY) models are widely used for economic evaluation in the health care sector. In the first part of the paper, we establish an overview of QALY models where health varies over time and provide a theoretical analysis of model identification and parameter estimation from...... time tradeoff (TTO) and standard gamble (SG) scores. We investigate deterministic and probabilistic models and consider five different families of discounting functions in all. The second part of the paper discusses four issues recurrently debated in the literature. This discussion includes questioning...... of these two can be used to disentangle risk aversion from discounting. We find that caution must be taken when drawing conclusions from models with chronic health states to situations where health varies over time. One notable difference is that in the former case, risk aversion may be indistinguishable from...

Time-varying causality between energy consumption, CO2 emissions, and economic growth: evidence from US states.

Science.gov (United States)

Tzeremes, Panayiotis

2018-02-01

This study is the first attempt to investigate the relationship between CO 2 emissions, energy consumption, and economic growth at a state level, for the 50 US states, through a time-varying causality approach using annual data over the periods 1960-2010. The time-varying causality test facilitates the better understanding of the causal relationship between the covariates owing to the fact that it might identify causalities when the time-constant hypothesis is rejected. Our findings indicate the existence of a time-varying causality at the state level. Specifically, the results probe eight bidirectional time-varying causalities between energy consumption and CO 2 emission, six cases of two-way time-varying causalities between economic growth and energy consumption, and five bidirectional time-varying causalities between economic growth and CO 2 emission. Moreover, we examine the traditional environmental Kuznets curve hypothesis for the states. Notably, our results do not endorse the validity of the EKC, albeit the majority of states support an inverted N-shaped relationship. Lastly, we can identify multiple policy implications based on the empirical results.

Anomalous dispersion in correlated porous media: a coupled continuous time random walk approach

Science.gov (United States)

Comolli, Alessandro; Dentz, Marco

2017-09-01

We study the causes of anomalous dispersion in Darcy-scale porous media characterized by spatially heterogeneous hydraulic properties. Spatial variability in hydraulic conductivity leads to spatial variability in the flow properties through Darcy's law and thus impacts on solute and particle transport. We consider purely advective transport in heterogeneity scenarios characterized by broad distributions of heterogeneity length scales and point values. Particle transport is characterized in terms of the stochastic properties of equidistantly sampled Lagrangian velocities, which are determined by the flow and conductivity statistics. The persistence length scales of flow and transport velocities are imprinted in the spatial disorder and reflect the distribution of heterogeneity length scales. Particle transitions over the velocity length scales are kinematically coupled with the transition time through velocity. We show that the average particle motion follows a coupled continuous time random walk (CTRW), which is fully parameterized by the distribution of flow velocities and the medium geometry in terms of the heterogeneity length scales. The coupled CTRW provides a systematic framework for the investigation of the origins of anomalous dispersion in terms of heterogeneity correlation and the distribution of conductivity point values. We derive analytical expressions for the asymptotic scaling of the moments of the spatial particle distribution and first arrival time distribution (FATD), and perform numerical particle tracking simulations of the coupled CTRW to capture the full average transport behavior. Broad distributions of heterogeneity point values and lengths scales may lead to very similar dispersion behaviors in terms of the spatial variance. Their mechanisms, however are very different, which manifests in the distributions of particle positions and arrival times, which plays a central role for the prediction of the fate of dissolved substances in

Multi-disciplinary techniques for understanding time-varying space-based imagery

Science.gov (United States)

Casasent, D.; Sanderson, A.; Kanade, T.

1984-06-01

A multidisciplinary program for space-based image processing is reported. This project combines optical and digital processing techniques and pattern recognition, image understanding and artificial intelligence methodologies. Time change image processing was recognized as the key issue to be addressed. Three time change scenarios were defined based on the frame rate of the data change. This report details the recent research on: various statistical and deterministic image features, recognition of sub-pixel targets in time varying imagery, and 3-D object modeling and recognition.

Consumption growth and time-varying expected stock returns

DEFF Research Database (Denmark)

Vinther Møller, Stig

2008-01-01

When the consumption growth rate is measured based upon fourth quarter data, it tracks predictable variation in future excess stock returns. Low fourth quarter consumption growth rates predict high future excess stock returns such that expected returns are high at business cycle troughs and low...... of each calendar year, and at possibly random times in between. The consumption growth rate measured based upon fourth quarter data is a much stronger predictive variable than benchmark predictive variables such as the dividend-price ratio, the term spread, and the default spread....

Tracking control of time-varying knee exoskeleton disturbed by interaction torque.

Science.gov (United States)

Li, Zhan; Ma, Wenhao; Yin, Ziguang; Guo, Hongliang

2017-11-01

Knee exoskeletons have been increasingly applied as assistive devices to help lower-extremity impaired people to make their knee joints move through providing external movement compensation. Tracking control of knee exoskeletons guided by human intentions often encounters time-varying (time-dependent) issues and the disturbance interaction torque, which may dramatically put an influence up on their dynamic behaviors. Inertial and viscous parameters of knee exoskeletons can be estimated to be time-varying due to unexpected mechanical vibrations and contact interactions. Moreover, the interaction torque produced from knee joint of wearers has an evident disturbance effect on regular motions of knee exoskeleton. All of these points can increase difficultly of accurate control of knee exoskeletons to follow desired joint angle trajectories. This paper proposes a novel control strategy for controlling knee exoskeleton with time-varying inertial and viscous coefficients disturbed by interaction torque. Such designed controller is able to make the tracking error of joint angle of knee exoskeletons exponentially converge to zero. Meanwhile, the proposed approach is robust to guarantee the tracking error bounded when the interaction torque exists. Illustrative simulation and experiment results are presented to show efficiency of the proposed controller. Additionally, comparisons with gradient dynamic (GD) approach and other methods are also presented to demonstrate efficiency and superiority of the proposed control strategy for tracking joint angle of knee exoskeleton. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

Forced solitary Rossby waves under the influence of slowly varying topography with time

International Nuclear Information System (INIS)

Yang Hong-Wei; Yin Bao-Shu; Yang De-Zhou; Xu Zhen-Hua

2011-01-01

By using a weakly nonlinear and perturbation method, the generalized inhomogeneous Korteweg—de Vries (KdV)—Burgers equation is derived, which governs the evolution of the amplitude of Rossby waves under the influence of dissipation and slowly varying topography with time. The analysis indicates that dissipation and slowly varying topography with time are important factors in causing variation in the mass and energy of solitary waves. (general)

Stability of Nonlinear Systems with Unknown Time-varying Feedback Delay

Science.gov (United States)

Chunodkar, Apurva A.; Akella, Maruthi R.

2013-12-01

This paper considers the problem of stabilizing a class of nonlinear systems with unknown bounded delayed feedback wherein the time-varying delay is 1) piecewise constant 2) continuous with a bounded rate. We also consider application of these results to the stabilization of rigid-body attitude dynamics. In the first case, the time-delay in feedback is modeled specifically as a switch among an arbitrarily large set of unknown constant values with a known strict upper bound. The feedback is a linear function of the delayed states. In the case of linear systems with switched delay feedback, a new sufficiency condition for average dwell time result is presented using a complete type Lyapunov-Krasovskii (L-K) functional approach. Further, the corresponding switched system with nonlinear perturbations is proven to be exponentially stable inside a well characterized region of attraction for an appropriately chosen average dwell time. In the second case, the concept of the complete type L-K functional is extended to a class of nonlinear time-delay systems with unknown time-varying time-delay. This extension ensures stability robustness to time-delay in the control design for all values of time-delay less than the known upper bound. Model-transformation is used in order to partition the nonlinear system into a nominal linear part that is exponentially stable with a bounded perturbation. We obtain sufficient conditions which ensure exponential stability inside a region of attraction estimate. A constructive method to evaluate the sufficient conditions is presented together with comparison with the corresponding constant and piecewise constant delay. Numerical simulations are performed to illustrate the theoretical results of this paper.

Robustness Analysis of Hybrid Stochastic Neural Networks with Neutral Terms and Time-Varying Delays

Directory of Open Access Journals (Sweden)

Chunmei Wu

2015-01-01

Full Text Available We analyze the robustness of global exponential stability of hybrid stochastic neural networks subject to neutral terms and time-varying delays simultaneously. Given globally exponentially stable hybrid stochastic neural networks, we characterize the upper bounds of contraction coefficients of neutral terms and time-varying delays by using the transcendental equation. Moreover, we prove theoretically that, for any globally exponentially stable hybrid stochastic neural networks, if additive neutral terms and time-varying delays are smaller than the upper bounds arrived, then the perturbed neural networks are guaranteed to also be globally exponentially stable. Finally, a numerical simulation example is given to illustrate the presented criteria.

Maximal Increments of Local Time of a Random Walk

OpenAIRE

Jain, Naresh C.; Pruitt, William E.

1987-01-01

Let $(S_j)$ be a lattice random walk, i.e., $S_j = X_1 + \\cdots + X_j$, where $X_1, X_2,\\ldots$ are independent random variables with values in $\\mathbb{Z}$ and common nondegenerate distribution $F$. Let $\\{t_n\\}$ be a nondecreasing sequence of positive integers, $t_n \\leq n$, and $L^\\ast_n = \\max_{0\\leq j\\leq n-t_n}(L_{j+t_n} - L_j)$, where $L_n = \\sum^n_{j=1}1_{\\{0\\}}(S_j)$, the number of times zero is visited by the random walk by time $n$. Assuming that the random walk is recurrent and sa...

Estimating time-varying conditional correlations between stock and foreign exchange markets

Science.gov (United States)

Tastan, Hüseyin

2006-02-01

This study explores the dynamic interaction between stock market returns and changes in nominal exchange rates. Many financial variables are known to exhibit fat tails and autoregressive variance structure. It is well-known that unconditional covariance and correlation coefficients also vary significantly over time and multivariate generalized autoregressive model (MGARCH) is able to capture the time-varying variance-covariance matrix for stock market returns and changes in exchange rates. The model is applied to daily Euro-Dollar exchange rates and two stock market indexes from the US economy: Dow-Jones Industrial Average Index and S&P500 Index. The news impact surfaces are also drawn based on the model estimates to see the effects of idiosyncratic shocks in respective markets.

Global exponential stability of BAM neural networks with time-varying delays: The discrete-time case

Science.gov (United States)

Raja, R.; Marshal Anthoni, S.

2011-02-01

This paper deals with the problem of stability analysis for a class of discrete-time bidirectional associative memory (BAM) neural networks with time-varying delays. By employing the Lyapunov functional and linear matrix inequality (LMI) approach, a new sufficient conditions is proposed for the global exponential stability of discrete-time BAM neural networks. The proposed LMI based results can be easily checked by LMI control toolbox. Moreover, an example is also provided to demonstrate the effectiveness of the proposed method.

Overlapping quadratic optimal control of linear time-varying commutative systems

Czech Academy of Sciences Publication Activity Database

Bakule, Lubomír; Rodellar, J.; Rossell, J. M.

2002-01-01

Roč. 40, č. 5 (2002), s. 1611-1627 ISSN 0363-0129 R&D Projects: GA AV ČR IAA2075802 Institutional research plan: CEZ:AV0Z1075907 Keywords : overlapping * optimal control * linear time-varying systems Subject RIV: BC - Control Systems Theory Impact factor: 1.441, year: 2002

An Explicit MOT-TD-VIE Solver for Time Varying Media

KAUST Repository

Sayed, Sadeed Bin

2016-03-15

An explicit marching on-in-time (MOT) scheme for solving the time domain electric field integral equation enforced on volumes with time varying dielectric permittivity is proposed. Unknowns of the integral equation and the constitutive relation, i.e., flux density and field intensity, are discretized using full and half Schaubert-Wilton-Glisson functions in space. Temporal interpolation is carried out using band limited approximate prolate spherical wave functions. The discretized coupled system of integral equation and constitutive relation is integrated in time using a PE(CE)m type linear multistep scheme. Unlike the existing MOT methods, the resulting explicit MOT scheme allows for straightforward incorporation of the time variation in the dielectric permittivity.

Time-varying Capital Requirements and Disclosure Rules

DEFF Research Database (Denmark)

Kragh, Jonas; Rangvid, Jesper

, implying that resilience in the banking system is also increased. The increase in capital ratios is partly due to a modest reduction in lending. Using a policy changes, we show that banks react stronger to changes in capital requirements when these are public. Our results further suggest that the impact......Unique and confidential Danish data allow us to identify how changes in disclosure requirements and bank-specific time-varying capital requirements affect banks' lending and capital accumu-lation decisions. We find that banks increase their capital ratios after capital requirements are increased...... of capital requirements differ for small and large banks. Large banks raise their capital ratios more, reduce lending less, and accumulate more new capital compared to small banks....

Time-varying vector fields and their flows

CERN Document Server

Jafarpour, Saber

2014-01-01

This short book provides a comprehensive and unified treatment of time-varying vector fields under a variety of regularity hypotheses, namely finitely differentiable, Lipschitz, smooth, holomorphic, and real analytic. The presentation of this material in the real analytic setting is new, as is the manner in which the various hypotheses are unified using functional analysis. Indeed, a major contribution of the book is the coherent development of locally convex topologies for the space of real analytic sections of a vector bundle, and the development of this in a manner that relates easily to classically known topologies in, for example, the finitely differentiable and smooth cases. The tools used in this development will be of use to researchers in the area of geometric functional analysis.

Dynamical continuous time random Lévy flights

Science.gov (United States)

Liu, Jian; Chen, Xiaosong

2016-03-01

The Lévy flights' diffusive behavior is studied within the framework of the dynamical continuous time random walk (DCTRW) method, while the nonlinear friction is introduced in each step. Through the DCTRW method, Lévy random walker in each step flies by obeying the Newton's Second Law while the nonlinear friction f(v) = - γ0v - γ2v3 being considered instead of Stokes friction. It is shown that after introducing the nonlinear friction, the superdiffusive Lévy flights converges, behaves localization phenomenon with long time limit, but for the Lévy index μ = 2 case, it is still Brownian motion.

The 'emergent scaling' phenomenon and the dielectric properties of random resistor-capacitor networks

CERN Document Server

Bouamrane, R

2003-01-01

An efficient algorithm, based on the Frank-Lobb reduction scheme, for calculating the equivalent dielectric properties of very large random resistor-capacitor (R-C) networks has been developed. It has been used to investigate the network size and composition dependence of dielectric properties and their statistical variability. The dielectric properties of 256 samples of random networks containing: 512, 2048, 8192 and 32 768 components distributed randomly in the ratios 60% R-40% C, 50% R-50% C and 40% R-60% C have been computed. It has been found that these properties exhibit the anomalous power law dependences on frequency known as the 'universal dielectric response' (UDR). Attention is drawn to the contrast between frequency ranges across which percolation determines dielectric response, where considerable variability is found amongst the samples, and those across which power laws define response where very little variability is found between samples. It is concluded that the power law UDRs are emergent pr...

Properties making a chaotic system a good Pseudo Random Number Generator

OpenAIRE

Falcioni, Massimo; Palatella, Luigi; Pigolotti, Simone; Vulpiani, Angelo

2005-01-01

We discuss two properties making a deterministic algorithm suitable to generate a pseudo random sequence of numbers: high value of Kolmogorov-Sinai entropy and high-dimensionality. We propose the multi dimensional Anosov symplectic (cat) map as a Pseudo Random Number Generator. We show what chaotic features of this map are useful for generating Pseudo Random Numbers and investigate numerically which of them survive in the discrete version of the map. Testing and comparisons with other generat...

Digital Generation of Noise-Signals with Arbitrary Constant or Time-Varying Spectra (A noise generation software package and its application)

CERN Document Server

Tückmantel, Joachim

2008-01-01

Artificial creation of arbitrary noise signals is used in accelerator physics to reproduce a measured perturbation spectrum for simulations but also to generate real-time shaped noise spectra for controlled emittance blow-up giving tailored properties to the final bunch shape. It is demonstrated here how one can produce numerically what is, for all practical purposes, an unlimited quantity of non-periodic noise data having any predefined spectral density. This spectral density may be constant or varying with time. The noise output never repeats and has excellent statistical properties, important for very long-term applications. It is difficult to obtain such flexibility and spectral cleanliness using analogue techniques. This algorithm was applied both in computer simulations of bunch behaviour in the presence of RF noise in the PS, SPS and LHC and also to generate real-time noise, tracking the synchrotron frequency change during the energy ramp of the SPS and producing controlled longitudinal emittance blow-...

Delay-Dependent Guaranteed Cost Control of an Interval System with Interval Time-Varying Delay

Directory of Open Access Journals (Sweden)

Xiao Min

2009-01-01

Full Text Available This paper concerns the problem of the delay-dependent robust stability and guaranteed cost control for an interval system with time-varying delay. The interval system with matrix factorization is provided and leads to less conservative conclusions than solving a square root. The time-varying delay is assumed to belong to an interval and the derivative of the interval time-varying delay is not a restriction, which allows a fast time-varying delay; also its applicability is broad. Based on the Lyapunov-Ktasovskii approach, a delay-dependent criterion for the existence of a state feedback controller, which guarantees the closed-loop system stability, the upper bound of cost function, and disturbance attenuation lever for all admissible uncertainties as well as out perturbation, is proposed in terms of linear matrix inequalities (LMIs. The criterion is derived by free weighting matrices that can reduce the conservatism. The effectiveness has been verified in a number example and the compute results are presented to validate the proposed design method.

RANDOM FUNCTIONS AND INTERVAL METHOD FOR PREDICTING THE RESIDUAL RESOURCE OF BUILDING STRUCTURES

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Shmelev Gennadiy Dmitrievich

2017-11-01

Full Text Available Subject: possibility of using random functions and interval prediction method for estimating the residual life of building structures in the currently used buildings. Research objectives: coordination of ranges of values to develop predictions and random functions that characterize the processes being predicted. Materials and methods: when performing this research, the method of random functions and the method of interval prediction were used. Results: in the course of this work, the basic properties of random functions, including the properties of families of random functions, are studied. The coordination of time-varying impacts and loads on building structures is considered from the viewpoint of their influence on structures and representation of the structures’ behavior in the form of random functions. Several models of random functions are proposed for predicting individual parameters of structures. For each of the proposed models, its scope of application is defined. The article notes that the considered approach of forecasting has been used many times at various sites. In addition, the available results allowed the authors to develop a methodology for assessing the technical condition and residual life of building structures for the currently used facilities. Conclusions: we studied the possibility of using random functions and processes for the purposes of forecasting the residual service lives of structures in buildings and engineering constructions. We considered the possibility of using an interval forecasting approach to estimate changes in defining parameters of building structures and their technical condition. A comprehensive technique for forecasting the residual life of building structures using the interval approach is proposed.

Discrete-time recurrent neural networks with time-varying delays: Exponential stability analysis

International Nuclear Information System (INIS)

Liu, Yurong; Wang, Zidong; Serrano, Alan; Liu, Xiaohui

2007-01-01

This Letter is concerned with the analysis problem of exponential stability for a class of discrete-time recurrent neural networks (DRNNs) with time delays. The delay is of the time-varying nature, and the activation functions are assumed to be neither differentiable nor strict monotonic. Furthermore, the description of the activation functions is more general than the recently commonly used Lipschitz conditions. Under such mild conditions, we first prove the existence of the equilibrium point. Then, by employing a Lyapunov-Krasovskii functional, a unified linear matrix inequality (LMI) approach is developed to establish sufficient conditions for the DRNNs to be globally exponentially stable. It is shown that the delayed DRNNs are globally exponentially stable if a certain LMI is solvable, where the feasibility of such an LMI can be easily checked by using the numerically efficient Matlab LMI Toolbox. A simulation example is presented to show the usefulness of the derived LMI-based stability condition

Global exponential stability of uncertain fuzzy BAM neural networks with time-varying delays

International Nuclear Information System (INIS)

Syed Ali, M.; Balasubramaniam, P.

2009-01-01

In this paper, the Takagi-Sugeno (TS) fuzzy model representation is extended to the stability analysis for uncertain Bidirectional Associative Memory (BAM) neural networks with time-varying delays using linear matrix inequality (LMI) theory. A novel LMI-based stability criterion is obtained by LMI optimization algorithms to guarantee the exponential stability of uncertain BAM neural networks with time-varying delays which are represented by TS fuzzy models. Finally, the proposed stability conditions are demonstrated with numerical examples.

On the impact of topography and building mask on time varying gravity due to local hydrology

Science.gov (United States)

Deville, S.; Jacob, T.; Chéry, J.; Champollion, C.

2013-01-01

We use 3 yr of surface absolute gravity measurements at three sites on the Larzac plateau (France) to quantify the changes induced by topography and the building on gravity time-series, with respect to an idealized infinite slab approximation. Indeed, local topography and buildings housing ground-based gravity measurement have an effect on the distribution of water storage changes, therefore affecting the associated gravity signal. We first calculate the effects of surrounding topography and building dimensions on the gravity attraction for a uniform layer of water. We show that a gravimetric interpretation of water storage change using an infinite slab, the so-called Bouguer approximation, is generally not suitable. We propose to split the time varying gravity signal in two parts (1) a surface component including topographic and building effects (2) a deep component associated to underground water transfer. A reservoir modelling scheme is herein presented to remove the local site effects and to invert for the effective hydrological properties of the unsaturated zone. We show that effective time constants associated to water transfer vary greatly from site to site. We propose that our modelling scheme can be used to correct for the local site effects on gravity at any site presenting a departure from a flat topography. Depending on sites, the corrected signal can exceed measured values by 5-15 μGal, corresponding to 120-380 mm of water using the Bouguer slab formula. Our approach only requires the knowledge of daily precipitation corrected for evapotranspiration. Therefore, it can be a useful tool to correct any kind of gravimetric time-series data.

Time-varying market integration and expected returns in emerging mrkets

NARCIS (Netherlands)

de Jong, F.C.J.M.; de Roon, F.

2001-01-01

We use a simple model in which the expected returns in emerging markets depend on their systematicrisk as measured by their beta relative to the world portfolio as well as on the level ofintegration in that market. The level of integration is a time-varying variable that depends on themarket value

Estimation of time-varying reactivity by the H∞ optimal linear filter

International Nuclear Information System (INIS)

Suzuki, Katsuo; Shimazaki, Junya; Watanabe, Koiti

1995-01-01

The problem of estimating the time-varying net reactivity from flux measurements is solved for a point reactor kinetics model using a linear filtering technique in an H ∞ settings. In order to sue this technique, an appropriate dynamical model of the reactivity is constructed that can be embedded into the reactor model as one of its variables. A filter, which minimizes the H ∞ norm of the estimation error power spectrum, operates on neutron density measurements corrupted by noise and provides an estimate of the dynamic net reactivity. Computer simulations are performed to reveal the basic characteristics of the H ∞ optimal filter. The results of the simulation indicate that the filter can be used to determine the time-varying reactivity from neutron density measurements that have been corrupted by noise

Globally Asymptotic Stability of Stochastic Nonlinear Systems with Time-Varying Delays via Output Feedback Control

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Mingzhu Song

2016-01-01

Full Text Available We address the problem of globally asymptotic stability for a class of stochastic nonlinear systems with time-varying delays. By the backstepping method and Lyapunov theory, we design a linear output feedback controller recursively based on the observable linearization for a class of stochastic nonlinear systems with time-varying delays to guarantee that the closed-loop system is globally asymptotically stable in probability. In particular, we extend the deterministic nonlinear system to stochastic nonlinear systems with time-varying delays. Finally, an example and its simulations are given to illustrate the theoretical results.

Chemical Continuous Time Random Walks

Science.gov (United States)

Aquino, T.; Dentz, M.

2017-12-01

Traditional methods for modeling solute transport through heterogeneous media employ Eulerian schemes to solve for solute concentration. More recently, Lagrangian methods have removed the need for spatial discretization through the use of Monte Carlo implementations of Langevin equations for solute particle motions. While there have been recent advances in modeling chemically reactive transport with recourse to Lagrangian methods, these remain less developed than their Eulerian counterparts, and many open problems such as efficient convergence and reconstruction of the concentration field remain. We explore a different avenue and consider the question: In heterogeneous chemically reactive systems, is it possible to describe the evolution of macroscopic reactant concentrations without explicitly resolving the spatial transport? Traditional Kinetic Monte Carlo methods, such as the Gillespie algorithm, model chemical reactions as random walks in particle number space, without the introduction of spatial coordinates. The inter-reaction times are exponentially distributed under the assumption that the system is well mixed. In real systems, transport limitations lead to incomplete mixing and decreased reaction efficiency. We introduce an arbitrary inter-reaction time distribution, which may account for the impact of incomplete mixing. This process defines an inhomogeneous continuous time random walk in particle number space, from which we derive a generalized chemical Master equation and formulate a generalized Gillespie algorithm. We then determine the modified chemical rate laws for different inter-reaction time distributions. We trace Michaelis-Menten-type kinetics back to finite-mean delay times, and predict time-nonlocal macroscopic reaction kinetics as a consequence of broadly distributed delays. Non-Markovian kinetics exhibit weak ergodicity breaking and show key features of reactions under local non-equilibrium.

Effect of ageing time on mechanical properties of plasticized poly(hydroxybutyrate) (PHB)

Science.gov (United States)

Farris, Giuseppe; Cinelli, Patrizia; Anguillesi, Irene; Salvadori, Sara; Coltelli, Maria-Beatrice; Lazzeri, Andrea

2014-05-01

Polyhydroxybutyrate (PHB) based materials were prepared by melt extrusion by using different plasticizers, such as poly(ethylene glycol)s (PEG)s having different molecular weight (400, 1500 and 4000). The plasticizers content was varied in the range 10-20% by weight versus the PHB polymeric matrix. The variation of tensile properties of the different samples was monitored as a function of time of ageing to study the stability of the material. The elastic modulus and tensile strength increased as a function of time, whereas the strain at break decreased. The experimental results were explained by considering both the demixing of the plasticizers and the occurring of secondary crystallization. Moreover the variation in mechanical properties was correlated to the structure and concentration of the different plasticizers employed.

Exponential stability of switched linear systems with time-varying delay

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Satiracoo Pairote

2007-11-01

Full Text Available We use a Lyapunov-Krasovskii functional approach to establish the exponential stability of linear systems with time-varying delay. Our delay-dependent condition allows to compute simultaneously the two bounds that characterize the exponential stability rate of the solution. A simple procedure for constructing switching rule is also presented.

Relay selection in cooperative communication systems over continuous time-varying fading channel

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Ke Geng

2017-02-01

Full Text Available In this paper, we study relay selection under outdated channel state information (CSI in a decode-and-forward (DF cooperative system. Unlike previous researches on cooperative communication under outdated CSI, we consider that the channel varies continuously over time, i.e., the channel not only changes between relay selection and data transmission but also changes during data transmission. Thus the level of accuracy of the CSI used in relay selection degrades with data transmission. We first evaluate the packet error rate (PER of the cooperative system under continuous time-varying fading channel, and find that the PER performance deteriorates more seriously under continuous time-varying fading channel than when the channel is assumed to be constant during data transmission. Then, we propose a repeated relay selection (RRS strategy to improve the PER performance, in which the forwarded data is divided into multiple segments and relay is reselected before the transmission of each segment based on the updated CSI. Finally, we propose a combined relay selection (CRS strategy which takes advantage of three different relay selection strategies to further mitigate the impact of outdated CSI.

One-dimensional radionuclide transport under time-varying conditions

International Nuclear Information System (INIS)

Gelbard, F.; Olague, N.E.; Longsine, D.E.

1990-01-01

This paper discusses new analytical and numerical solutions presented for one-dimensional radionuclide transport under time-varying fluid-flow conditions including radioactive decay. The analytical solution assumes that all radionuclides have identical retardation factors, and is limited to instantaneous releases. The numerical solution does not have these limitations, but is tested against the limiting case given for the analytical solution. Reasonable agreement between the two solutions was found. Examples are given for the transport of a three-member radionuclide chain transported over distances and flow rates comparable to those reported for Yucca Mountain, the proposed disposal site for high-level nuclear waste

Effect of long-time immersion of soft denture liners in water on viscoelastic properties.

Science.gov (United States)

Iwasaki, Naohiko; Yamaki, Chisato; Takahashi, Hidekazu; Oki, Meiko; Suzuki, Tetsuya

2017-09-26

Aim of this study was to investigate the effect of long-time immersion of soft denture liners in 37°C water on viscoelastic properties. Six silicone-based and two acrylic resin-based soft denture liners were selected. Cylindrical specimens were stored in distilled water at 37°C for 6 months. Viscoelastic properties, which were instantaneous and delayed elastic displacements, viscous flow, and residual displacement, were determined using a creep meter, and analyzed with 2-way analysis of variance and Tukey's comparison (α=0.05). Viscoelastic properties and their time-dependent changes were varied among materials examined. The observed viscoelastic properties of three from six silicone-based liners did not significantly change after 6-month immersion, but those of two acrylic resin-based liners significantly changed with the increase of immersion time. However, the sum of initial instantaneous elastic displacement and delayed elastic displacement of two acrylic resin-based liners during 6-month immersion changed less than 10%, which might indicate clinically sufficient elastic performance.

Generalized Projective Synchronization between Two Complex Networks with Time-Varying Coupling Delay

International Nuclear Information System (INIS)

Mei, Sun; Chang-Yan, Zeng; Li-Xin, Tian

2009-01-01

Generalized projective synchronization (GPS) between two complex networks with time-varying coupling delay is investigated. Based on the Lyapunov stability theory, a nonlinear controller and adaptive updated laws are designed. Feasibility of the proposed scheme is proven in theory. Moreover, two numerical examples are presented, using the energy resource system and Lü's system [Physica A 382 (2007) 672] as the nodes of the networks. GPS between two energy resource complex networks with time-varying coupling delay is achieved. This study can widen the application range of the generalized synchronization methods and will be instructive for the demand–supply of energy resource in some regions of China

Compensating Unknown Time-Varying Delay in Opto-Electronic Platform Tracking Servo System

Directory of Open Access Journals (Sweden)

Ruihong Xie

2017-05-01

Full Text Available This paper investigates the problem of compensating miss-distance delay in opto-electronic platform tracking servo system. According to the characteristic of LOS (light-of-sight motion, we setup the Markovian process model and compensate this unknown time-varying delay by feed-forward forecasting controller based on robust H∞ control. Finally, simulation based on double closed-loop PI (Proportion Integration control system indicates that the proposed method is effective for compensating unknown time-varying delay. Tracking experiments on the opto-electronic platform indicate that RMS (root-mean-square error is 1.253 mrad when tracking 10° 0.2 Hz signal.

Generalized Projective Synchronization between Two Complex Networks with Time-Varying Coupling Delay

Science.gov (United States)

Sun, Mei; Zeng, Chang-Yan; Tian, Li-Xin

2009-01-01

Generalized projective synchronization (GPS) between two complex networks with time-varying coupling delay is investigated. Based on the Lyapunov stability theory, a nonlinear controller and adaptive updated laws are designed. Feasibility of the proposed scheme is proven in theory. Moreover, two numerical examples are presented, using the energy resource system and Lü's system [Physica A 382 (2007) 672] as the nodes of the networks. GPS between two energy resource complex networks with time-varying coupling delay is achieved. This study can widen the application range of the generalized synchronization methods and will be instructive for the demand-supply of energy resource in some regions of China.

Emerging properties of financial time series in the ``Game of Life''

Science.gov (United States)

Hernández-Montoya, A. R.; Coronel-Brizio, H. F.; Stevens-Ramírez, G. A.; Rodríguez-Achach, M.; Politi, M.; Scalas, E.

2011-12-01

We explore the spatial complexity of Conway’s “Game of Life,” a prototypical cellular automaton by means of a geometrical procedure generating a two-dimensional random walk from a bidimensional lattice with periodical boundaries. The one-dimensional projection of this process is analyzed and it turns out that some of its statistical properties resemble the so-called stylized facts observed in financial time series. The scope and meaning of this result are discussed from the viewpoint of complex systems. In particular, we stress how the supposed peculiarities of financial time series are, often, overrated in their importance.

Multi-pulse chaotic motions of a rotor-active magnetic bearing system with time-varying stiffness

International Nuclear Information System (INIS)

Zhang, W.; Yao, M.H.; Zhan, X.P.

2006-01-01

In this paper, we investigate the Shilnikov type multi-pulse chaotic dynamics for a rotor-active magnetic bearings (AMB) system with 8-pole legs and the time-varying stiffness. The stiffness in the AMB is considered as the time-varying in a periodic form. The dimensionless equation of motion for the rotor-AMB system with the time-varying stiffness in the horizontal and vertical directions is a two-degree-of-freedom nonlinear system with quadratic and cubic nonlinearities and parametric excitation. The asymptotic perturbation method is used to obtain the averaged equations in the case of primary parametric resonance and 1/2 subharmonic resonance. It is found from the numerical results that there are the phenomena of the Shilnikov type multi-pulse chaotic motions for the rotor-AMB system. A new jumping phenomenon is discovered in the rotor-AMB system with the time-varying stiffness

Time Varying Market Integration and Expected Rteurns in Emerging Markets

NARCIS (Netherlands)

de Jong, F.C.J.M.; de Roon, F.A.

2001-01-01

We use a simple model in which the expected returns in emerging markets depend on their systematic risk as measured by their beta relative to the world portfolio as well as on the level of integration in that market.The level of integration is a time-varying variable that depends on the market value

A new time-varying harmonic decomposition structure based on recursive hanning window

NARCIS (Netherlands)

Martins, C.H.; Silva, L.R.M.; Duque, C.A.; Cerqueira, A.S.; Teixeira, E.C.; Ribeiro, P.F.

2012-01-01

Analysis of power quality phenomena under time-varying conditions has become an important subject as the complexity of the grid increases. As a consequence, several methods have been developed/applied also to study power quality parameters during transient conditions such as time-frequency methods.

Using random response input in Ibrahim Time Domain

DEFF Research Database (Denmark)

Olsen, Peter; Brincker, R.

2013-01-01

In this paper the time domain technique Ibrahim Time Domain (ITD) is used to analyze random time data. ITD is known to be a technique for identification of output only systems. The traditional formulation of ITD is claimed to be limited, when identifying closely spaced modes, because....... In this article it is showed that when using the modified ITD random time data can be analyzed. The application of the technique is displayed by a case study, with simulations and experimental data....... of the technique being Single Input Multiple Output (SIMO). It has earlier been showed that when modifying ITD with Toeplitz matrix averaging. Identification of time data with closely spaced modes is improved. In the traditional formulation of ITD the time data has to be free decays or impulse response functions...

Uniform stability for time-varying infinite-dimensional discrete linear systems

International Nuclear Information System (INIS)

Kubrusly, C.S.

1988-09-01

Stability for time-varying discrete linear systems in a Banach space is investigated. On the one hand, it established a fairly complete collection of necessary and sufficient conditions for uniform asymptotic equistability for input-free systems. This includes uniform and strong power equistability, and uniform and strong l p -equistability, among other technical conditions which also play essential role in stability theory. On other hand, it is shown that uniform asymptotic equistability for input-free systems is equivalent to each of the following concepts of uniform stability for forced systems: l p -input l p -state, c o -input c o -state, bounded-input bounded-state, l p>1 -input bounded-state, c sub (o)-input bounded-state, and convergent-input bounded-state; which are also equivalent to their nonuniform counterparts. For time-varying convergent systems, the above is also equivalent to convergent-input convergent-state stability. The proofs presented here are all ''elementary'' in the sense that they are based essentially only on the Banach-Steinhaus theorem. (autor) [pt

Optimal Consumption and Investment under Time-Varying Relative Risk Aversion

DEFF Research Database (Denmark)

Steffensen, Mogens

2011-01-01

We consider the continuous time consumption-investment problem originally formalized and solved by Merton in case of constant relative risk aversion. We present a complete solution for the case where relative risk aversion with respect to consumption varies with time, having in mind an investor...... with age-dependent risk aversion. This provides a new motivation for life-cycle investment rules. We study the optimal consumption and investment rules, in particular in the case where the relative risk aversion with respect to consumption is increasing with age....

Detection of dynamically varying interaural time differences

DEFF Research Database (Denmark)

Kohlrausch, Armin; Le Goff, Nicolas; Breebaart, Jeroen

2010-01-01

of fringes surrounding the probe is equal to the addition of the effects of the individual fringes. In this contribution, we present behavioral data for the same experimental condition, called dynamically varying ITD detection, but for a wider range of probe and fringe durations. Probe durations varied...

Mean Square Exponential Stability of Stochastic Switched System with Interval Time-Varying Delays

Directory of Open Access Journals (Sweden)

Manlika Rajchakit

2012-01-01

Full Text Available This paper is concerned with mean square exponential stability of switched stochastic system with interval time-varying delays. The time delay is any continuous function belonging to a given interval, but not necessary to be differentiable. By constructing a suitable augmented Lyapunov-Krasovskii functional combined with Leibniz-Newton’s formula, a switching rule for the mean square exponential stability of switched stochastic system with interval time-varying delays and new delay-dependent sufficient conditions for the mean square exponential stability of the switched stochastic system are first established in terms of LMIs. Numerical example is given to show the effectiveness of the obtained result.

Time scale of random sequential adsorption.

Science.gov (United States)

Erban, Radek; Chapman, S Jonathan

2007-04-01

A simple multiscale approach to the diffusion-driven adsorption from a solution to a solid surface is presented. The model combines two important features of the adsorption process: (i) The kinetics of the chemical reaction between adsorbing molecules and the surface and (ii) geometrical constraints on the surface made by molecules which are already adsorbed. The process (i) is modeled in a diffusion-driven context, i.e., the conditional probability of adsorbing a molecule provided that the molecule hits the surface is related to the macroscopic surface reaction rate. The geometrical constraint (ii) is modeled using random sequential adsorption (RSA), which is the sequential addition of molecules at random positions on a surface; one attempt to attach a molecule is made per one RSA simulation time step. By coupling RSA with the diffusion of molecules in the solution above the surface the RSA simulation time step is related to the real physical time. The method is illustrated on a model of chemisorption of reactive polymers to a virus surface.

H ∞ synchronization of the coronary artery system with input time-varying delay

International Nuclear Information System (INIS)

Li Xiao-Meng; Zhao Zhan-Shan; Sun Lian-Kun; Zhang Jing

2016-01-01

This paper investigates the H ∞ synchronization of the coronary artery system with input delay and disturbance. We focus on reducing the conservatism of existing synchronization strategies. Base on the triple integral forms of the Lyapunov–Krasovskii functional (LKF), we utilize single and double integral forms of Wirtinger-based inequality to guarantee that the synchronization feedback controller has good performance against time-varying delay and external disturbance. The effectiveness of our strategy can be exhibited by simulations under the different time-varying delays and different disturbances. (paper)

Application of continuous-time random walk to statistical arbitrage

Directory of Open Access Journals (Sweden)

Sergey Osmekhin

2015-01-01

Full Text Available An analytical statistical arbitrage strategy is proposed, where the distribution of the spread is modelled as a continuous-time random walk. Optimal boundaries, computed as a function of the mean and variance of the firstpassage time ofthe spread,maximises an objective function. The predictability of the trading strategy is analysed and contrasted for two forms of continuous-time random walk processes. We found that the waiting-time distribution has a significant impact on the prediction of the expected profit for intraday trading

Dynamical properties of a particle in a time-dependent double-well potential

International Nuclear Information System (INIS)

Leonel, Edson D; McClintock, P V E

2004-01-01

Some chaotic properties of a classical particle interacting with a time-dependent double-square-well potential are studied. The dynamics of the system is characterized using a two-dimensional nonlinear area-preserving map. Scaling arguments are used to study the chaotic sea in the low-energy domain. It is shown that the distributions of successive reflections and of corresponding successive reflection times obey power laws with the same exponent. If one or both wells move randomly, the particle experiences the phenomenon of Fermi acceleration in the sense that it has unlimited energy growth

Effects of varying feeding times on fertility and hatchability of broiler ...

African Journals Online (AJOL)

Effects of varying feeding times on fertility and hatchability of broiler chicken breeders in a tropical environment. ... Journal Home > Vol 65, No 4 (2017) > ... Prior to the eighth week data collection, the birds were allowed to get accustomed to ...

Synchronization of Hierarchical Time-Varying Neural Networks Based on Asynchronous and Intermittent Sampled-Data Control.

Science.gov (United States)

Xiong, Wenjun; Patel, Ragini; Cao, Jinde; Zheng, Wei Xing

In this brief, our purpose is to apply asynchronous and intermittent sampled-data control methods to achieve the synchronization of hierarchical time-varying neural networks. The asynchronous and intermittent sampled-data controllers are proposed for two reasons: 1) the controllers may not transmit the control information simultaneously and 2) the controllers cannot always exist at any time . The synchronization is then discussed for a kind of hierarchical time-varying neural networks based on the asynchronous and intermittent sampled-data controllers. Finally, the simulation results are given to illustrate the usefulness of the developed criteria.In this brief, our purpose is to apply asynchronous and intermittent sampled-data control methods to achieve the synchronization of hierarchical time-varying neural networks. The asynchronous and intermittent sampled-data controllers are proposed for two reasons: 1) the controllers may not transmit the control information simultaneously and 2) the controllers cannot always exist at any time . The synchronization is then discussed for a kind of hierarchical time-varying neural networks based on the asynchronous and intermittent sampled-data controllers. Finally, the simulation results are given to illustrate the usefulness of the developed criteria.

Modal Vibration Control in Periodic Time-Varying Structures with Focus on Rotor Blade Systems

DEFF Research Database (Denmark)

Christensen, Rene Hardam; Santos, Ilmar

2004-01-01

of active modal controllers. The main aim is to reduce vibrations in periodic time-varying structures. Special emphasis is given to vibration control of coupled bladed rotor systems. A state feedback modal control law is developed based on modal analysis in periodic time-varying structures. The first step...... in the procedure is a transformation of the model into a time-invariant modal form by applying the modal matrices, which are also periodic time-variant. Due to coupled rotor and blade motions complex vibration modes occur in the modal transformed state space model. This implies that the modal transformed model...

First passage time problems in time-dependent fields

International Nuclear Information System (INIS)

Fletcher, J.E.; Havlin, S.; Weiss, G.H.

1988-01-01

This paper discusses the simplest first passage time problems for random walks and diffusion processes on a line segment. When a diffusing particle moves in a time-varying field, use of the adjoint equation does not lead to any simplification in the calculation of moments of the first passage time as is the case for diffusion in a time-invariant field. We show that for a discrete random walk in the presence of a sinusoidally varying field there is a resonant frequency omega* for which the mean residence time on the line segment in a minimum. It is shown that for a random walk on a line segment of length L the mean residence time goes like L 2 for large L when omega omega*, but when omega = omega* the dependence is proportional to L. The results of our simulation are numerical, but can be regarded as exact. Qualitatively similar results are shown to hold for diffusion processes by a perturbation expansion in powers of a dimensionless velocity. These results are extended to higher values of this parameter by a numerical solution of the forward equation

Methods of Reverberation Mapping. I. Time-lag Determination by Measures of Randomness

Energy Technology Data Exchange (ETDEWEB)

Chelouche, Doron; Pozo-Nuñez, Francisco [Department of Physics, Faculty of Natural Sciences, University of Haifa, Haifa 3498838 (Israel); Zucker, Shay, E-mail: doron@sci.haifa.ac.il, E-mail: francisco.pozon@gmail.com, E-mail: shayz@post.tau.ac.il [Department of Geosciences, Raymond and Beverly Sackler Faculty of Exact Sciences, Tel Aviv University, Tel Aviv 6997801 (Israel)

2017-08-01

A class of methods for measuring time delays between astronomical time series is introduced in the context of quasar reverberation mapping, which is based on measures of randomness or complexity of the data. Several distinct statistical estimators are considered that do not rely on polynomial interpolations of the light curves nor on their stochastic modeling, and do not require binning in correlation space. Methods based on von Neumann’s mean-square successive-difference estimator are found to be superior to those using other estimators. An optimized von Neumann scheme is formulated, which better handles sparsely sampled data and outperforms current implementations of discrete correlation function methods. This scheme is applied to existing reverberation data of varying quality, and consistency with previously reported time delays is found. In particular, the size–luminosity relation of the broad-line region in quasars is recovered with a scatter comparable to that obtained by other works, yet with fewer assumptions made concerning the process underlying the variability. The proposed method for time-lag determination is particularly relevant for irregularly sampled time series, and in cases where the process underlying the variability cannot be adequately modeled.

Exponential stability for stochastic delayed recurrent neural networks with mixed time-varying delays and impulses: the continuous-time case

International Nuclear Information System (INIS)

Karthik Raja, U; Leelamani, A; Raja, R; Samidurai, R

2013-01-01

In this paper, the exponential stability for a class of stochastic neural networks with time-varying delays and impulsive effects is considered. By constructing suitable Lyapunov functionals and by using the linear matrix inequality optimization approach, we obtain sufficient delay-dependent criteria to ensure the exponential stability of stochastic neural networks with time-varying delays and impulses. Two numerical examples with simulation results are provided to illustrate the effectiveness of the obtained results over those already existing in the literature. (paper)

A discrete time-varying internal model-based approach for high precision tracking of a multi-axis servo gantry.

Science.gov (United States)

Zhang, Zhen; Yan, Peng; Jiang, Huan; Ye, Peiqing

2014-09-01

In this paper, we consider the discrete time-varying internal model-based control design for high precision tracking of complicated reference trajectories generated by time-varying systems. Based on a novel parallel time-varying internal model structure, asymptotic tracking conditions for the design of internal model units are developed, and a low order robust time-varying stabilizer is further synthesized. In a discrete time setting, the high precision tracking control architecture is deployed on a Voice Coil Motor (VCM) actuated servo gantry system, where numerical simulations and real time experimental results are provided, achieving the tracking errors around 3.5‰ for frequency-varying signals. Copyright © 2014 ISA. Published by Elsevier Ltd. All rights reserved.

Pseudo-random bit generator based on lag time series

Science.gov (United States)

García-Martínez, M.; Campos-Cantón, E.

2014-12-01

In this paper, we present a pseudo-random bit generator (PRBG) based on two lag time series of the logistic map using positive and negative values in the bifurcation parameter. In order to hidden the map used to build the pseudo-random series we have used a delay in the generation of time series. These new series when they are mapped xn against xn+1 present a cloud of points unrelated to the logistic map. Finally, the pseudo-random sequences have been tested with the suite of NIST giving satisfactory results for use in stream ciphers.

Generic Properties of Random Gene Regulatory Networks.

Science.gov (United States)

Li, Zhiyuan; Bianco, Simone; Zhang, Zhaoyang; Tang, Chao

2013-12-01

Modeling gene regulatory networks (GRNs) is an important topic in systems biology. Although there has been much work focusing on various specific systems, the generic behavior of GRNs with continuous variables is still elusive. In particular, it is not clear typically how attractors partition among the three types of orbits: steady state, periodic and chaotic, and how the dynamical properties change with network's topological characteristics. In this work, we first investigated these questions in random GRNs with different network sizes, connectivity, fraction of inhibitory links and transcription regulation rules. Then we searched for the core motifs that govern the dynamic behavior of large GRNs. We show that the stability of a random GRN is typically governed by a few embedding motifs of small sizes, and therefore can in general be understood in the context of these short motifs. Our results provide insights for the study and design of genetic networks.

Estimation of Time-Varying Coherence and Its Application in Understanding Brain Functional Connectivity

Directory of Open Access Journals (Sweden)

Cheng Liu

2010-01-01

Full Text Available Time-varying coherence is a powerful tool for revealing functional dynamics between different regions in the brain. In this paper, we address ways of estimating evolutionary spectrum and coherence using the general Cohen's class distributions. We show that the intimate connection between the Cohen's class-based spectra and the evolutionary spectra defined on the locally stationary time series can be linked by the kernel functions of the Cohen's class distributions. The time-varying spectra and coherence are further generalized with the Stockwell transform, a multiscale time-frequency representation. The Stockwell measures can be studied in the framework of the Cohen's class distributions with a generalized frequency-dependent kernel function. A magnetoencephalography study using the Stockwell coherence reveals an interesting temporal interaction between contralateral and ipsilateral motor cortices under the multisource interference task.

Subgeometric Ergodicity Analysis of Continuous-Time Markov Chains under Random-Time State-Dependent Lyapunov Drift Conditions

Directory of Open Access Journals (Sweden)

Mokaedi V. Lekgari

2014-01-01

Full Text Available We investigate random-time state-dependent Foster-Lyapunov analysis on subgeometric rate ergodicity of continuous-time Markov chains (CTMCs. We are mainly concerned with making use of the available results on deterministic state-dependent drift conditions for CTMCs and on random-time state-dependent drift conditions for discrete-time Markov chains and transferring them to CTMCs.

Robust outer synchronization between two nonlinear complex networks with parametric disturbances and mixed time-varying delays

Science.gov (United States)

Zhang, Chuan; Wang, Xingyuan; Luo, Chao; Li, Junqiu; Wang, Chunpeng

2018-03-01

In this paper, we focus on the robust outer synchronization problem between two nonlinear complex networks with parametric disturbances and mixed time-varying delays. Firstly, a general complex network model is proposed. Besides the nonlinear couplings, the network model in this paper can possess parametric disturbances, internal time-varying delay, discrete time-varying delay and distributed time-varying delay. Then, according to the robust control strategy, linear matrix inequality and Lyapunov stability theory, several outer synchronization protocols are strictly derived. Simple linear matrix controllers are designed to driver the response network synchronize to the drive network. Additionally, our results can be applied on the complex networks without parametric disturbances. Finally, by utilizing the delayed Lorenz chaotic system as the dynamics of all nodes, simulation examples are given to demonstrate the effectiveness of our theoretical results.

Improvement of and Parameter Identification for the Bimodal Time-Varying Modified Kanai-Tajimi Power Spectral Model

Directory of Open Access Journals (Sweden)

Huiguo Chen

2017-01-01

Full Text Available Based on the Kanai-Tajimi power spectrum filtering method proposed by Du Xiuli et al., a genetic algorithm and a quadratic optimization identification technique are employed to improve the bimodal time-varying modified Kanai-Tajimi power spectral model and the parameter identification method proposed by Vlachos et al. Additionally, a method for modeling time-varying power spectrum parameters for ground motion is proposed. The 8244 Orion and Chi-Chi earthquake accelerograms are selected as examples for time-varying power spectral model parameter identification and ground motion simulations to verify the feasibility and effectiveness of the improved bimodal time-varying modified Kanai-Tajimi power spectral model. The results of this study provide important references for designing ground motion inputs for seismic analyses of major engineering structures.

Randomized Caches Considered Harmful in Hard Real-Time Systems

Directory of Open Access Journals (Sweden)

Jan Reineke

2014-06-01

Full Text Available We investigate the suitability of caches with randomized placement and replacement in the context of hard real-time systems. Such caches have been claimed to drastically reduce the amount of information required by static worst-case execution time (WCET analysis, and to be an enabler for measurement-based probabilistic timing analysis. We refute these claims and conclude that with prevailing static and measurement-based analysis techniques caches with deterministic placement and least-recently-used replacement are preferable over randomized ones.

Multimodal Pilot Behavior in Multi-Axis Tracking Tasks with Time-Varying Motion Cueing Gains

Science.gov (United States)

Zaal, P. M. T; Pool, D. M.

2014-01-01

In a large number of motion-base simulators, adaptive motion filters are utilized to maximize the use of the available motion envelope of the motion system. However, not much is known about how the time-varying characteristics of such adaptive filters affect pilots when performing manual aircraft control. This paper presents the results of a study investigating the effects of time-varying motion filter gains on pilot control behavior and performance. An experiment was performed in a motion-base simulator where participants performed a simultaneous roll and pitch tracking task, while the roll and/or pitch motion filter gains changed over time. Results indicate that performance increases over time with increasing motion gains. This increase is a result of a time-varying adaptation of pilots' equalization dynamics, characterized by increased visual and motion response gains and decreased visual lead time constants. Opposite trends are found for decreasing motion filter gains. Even though the trends in both controlled axes are found to be largely the same, effects are less significant in roll. In addition, results indicate minor cross-coupling effects between pitch and roll, where a cueing variation in one axis affects the behavior adopted in the other axis.

Applications, dosimetry and biological interactions of static and time-varying magnetic fields

International Nuclear Information System (INIS)

Tenforde, T.S.

1988-08-01

The primary topics of this presentation include: (1) the applications of magnetic fields in research, industry, and medical technologies; (2) mechanisms of interaction of static and time-varying magnetic fields with living systems; (3) human health effects of exposure to static and time-varying magnetic fields in occupational, medical, and residential settings; and (4) recent advances in the dosimetry of extremely-low-frequency electromagnetic fields. The discussion of these topics is centered about two issues of considerable contemporary interest: (1) potential health effects of the fields used in magnetic resonance imaging and in vivo spectroscopy, and (2) the controversial issue of whether exposure to extremely-low-frequency (ELF) electromagnetic fields in the home and workplace leads to an elevated risk of cancer. 11 refs

A simple analytical model for dynamics of time-varying target leverage ratios

Science.gov (United States)

Lo, C. F.; Hui, C. H.

2012-03-01

In this paper we have formulated a simple theoretical model for the dynamics of the time-varying target leverage ratio of a firm under some assumptions based upon empirical observations. In our theoretical model the time evolution of the target leverage ratio of a firm can be derived self-consistently from a set of coupled Ito's stochastic differential equations governing the leverage ratios of an ensemble of firms by the nonlinear Fokker-Planck equation approach. The theoretically derived time paths of the target leverage ratio bear great resemblance to those used in the time-dependent stationary-leverage (TDSL) model [Hui et al., Int. Rev. Financ. Analy. 15, 220 (2006)]. Thus, our simple model is able to provide a theoretical foundation for the selected time paths of the target leverage ratio in the TDSL model. We also examine how the pace of the adjustment of a firm's target ratio, the volatility of the leverage ratio and the current leverage ratio affect the dynamics of the time-varying target leverage ratio. Hence, with the proposed dynamics of the time-dependent target leverage ratio, the TDSL model can be readily applied to generate the default probabilities of individual firms and to assess the default risk of the firms.

Characterization of maximally random jammed sphere packings. III. Transport and electromagnetic properties via correlation functions

Science.gov (United States)

Klatt, Michael A.; Torquato, Salvatore

2018-01-01

In the first two papers of this series, we characterized the structure of maximally random jammed (MRJ) sphere packings across length scales by computing a variety of different correlation functions, spectral functions, hole probabilities, and local density fluctuations. From the remarkable structural features of the MRJ packings, especially its disordered hyperuniformity, exceptional physical properties can be expected. Here we employ these structural descriptors to estimate effective transport and electromagnetic properties via rigorous bounds, exact expansions, and accurate analytical approximation formulas. These property formulas include interfacial bounds as well as universal scaling laws for the mean survival time and the fluid permeability. We also estimate the principal relaxation time associated with Brownian motion among perfectly absorbing traps. For the propagation of electromagnetic waves in the long-wavelength limit, we show that a dispersion of dielectric MRJ spheres within a matrix of another dielectric material forms, to a very good approximation, a dissipationless disordered and isotropic two-phase medium for any phase dielectric contrast ratio. We compare the effective properties of the MRJ sphere packings to those of overlapping spheres, equilibrium hard-sphere packings, and lattices of hard spheres. Moreover, we generalize results to micro- and macroscopically anisotropic packings of spheroids with tensorial effective properties. The analytic bounds predict the qualitative trend in the physical properties associated with these structures, which provides guidance to more time-consuming simulations and experiments. They especially provide impetus for experiments to design materials with unique bulk properties resulting from hyperuniformity, including structural-color and color-sensing applications.

Delay-Dependent Guaranteed Cost H∞ Control of an Interval System with Interval Time-Varying Delay

Directory of Open Access Journals (Sweden)

Zhongke Shi

2009-01-01

Full Text Available This paper concerns the problem of the delay-dependent robust stability and guaranteed cost H∞ control for an interval system with time-varying delay. The interval system with matrix factorization is provided and leads to less conservative conclusions than solving a square root. The time-varying delay is assumed to belong to an interval and the derivative of the interval time-varying delay is not a restriction, which allows a fast time-varying delay; also its applicability is broad. Based on the Lyapunov-Ktasovskii approach, a delay-dependent criterion for the existence of a state feedback controller, which guarantees the closed-loop system stability, the upper bound of cost function, and disturbance attenuation lever for all admissible uncertainties as well as out perturbation, is proposed in terms of linear matrix inequalities (LMIs. The criterion is derived by free weighting matrices that can reduce the conservatism. The effectiveness has been verified in a number example and the compute results are presented to validate the proposed design method.

Observation of time-varying photoconductivity and persistent photoconductivity in porous silicon

DEFF Research Database (Denmark)

Frello, T.; Veje, E.; Leistiko, Otto

1996-01-01

We have observed time-varying photoconductivity and persistent photoconductivity in porous silicon, both with time-evolution scales of the order of several minutes or hours. The time evolutions depend on the wavelength and the intensity of the illuminating light. The data indicate the presence...... of at least two competing mechanisms, one is tentatively related to photoinduced creation of charge carriers in the silicon substrate followed by diffusion into the porous silicon layer, and the other is tentatively related to desorption of hydrogen from the porous silicon. ©1996 American Institute of Physics....

Time-varying acceleration coefficients IPSO for solving dynamic economic dispatch with non-smooth cost function

International Nuclear Information System (INIS)

Mohammadi-ivatloo, Behnam; Rabiee, Abbas; Ehsan, Mehdi

2012-01-01

Highlights: ► New approach to solve power systems dynamic economic dispatch. ► Considering Valve-point effect, prohibited operation zones. ► Proposing TVAC-IPSO algorithm. - Abstract: The objective of the dynamic economic dispatch (DED) problem is to schedule power generation for the online units for a given time horizon economically, satisfying various operational constraints. Due to the effect of valve-point effects and prohibited operating zones (POZs) in the generating units cost functions, DED problem is a highly non-linear and non-convex optimization problem. The DED problem even may be more complicated if transmission losses and ramp-rate constraints are taken into account. This paper presents a novel and heuristic algorithm to solve DED problem of generating units, by employing time varying acceleration coefficients iteration particle swarm optimization (TVAC-IPSO) method. The effectiveness of the proposed method is examined and validated by carrying out extensive tests on different test systems, i.e. 5-unit and 10-unit test systems. Valve-point effects, POZs and ramp-rate constraints along with transmission losses are considered. To examine the efficiency of the proposed TVAC-IPSO algorithm, comprehensive studies are carried out, which compare convergence properties of the proposed TVAC-IPSO approach with conventional PSO algorithm, in addition to the other recently reported approaches. Numerical results show that the TVAC-IPSO method has good convergence properties and the generation costs resulted from the proposed method are lower than other algorithms reported in recent literature.

Identification of time-varying structural dynamic systems - An artificial intelligence approach

Science.gov (United States)

Glass, B. J.; Hanagud, S.

1992-01-01

An application of the artificial intelligence-derived methodologies of heuristic search and object-oriented programming to the problem of identifying the form of the model and the associated parameters of a time-varying structural dynamic system is presented in this paper. Possible model variations due to changes in boundary conditions or configurations of a structure are organized into a taxonomy of models, and a variant of best-first search is used to identify the model whose simulated response best matches that of the current physical structure. Simulated model responses are verified experimentally. An output-error approach is used in a discontinuous model space, and an equation-error approach is used in the parameter space. The advantages of the AI methods used, compared with conventional programming techniques for implementing knowledge structuring and inheritance, are discussed. Convergence conditions and example problems have been discussed. In the example problem, both the time-varying model and its new parameters have been identified when changes occur.

Monopoly models with time-varying demand function

Science.gov (United States)

Cavalli, Fausto; Naimzada, Ahmad

2018-05-01

We study a family of monopoly models for markets characterized by time-varying demand functions, in which a boundedly rational agent chooses output levels on the basis of a gradient adjustment mechanism. After presenting the model for a generic framework, we analytically study the case of cyclically alternating demand functions. We show that both the perturbation size and the agent's reactivity to profitability variation signals can have counterintuitive roles on the resulting period-2 cycles and on their stability. In particular, increasing the perturbation size can have both a destabilizing and a stabilizing effect on the resulting dynamics. Moreover, in contrast with the case of time-constant demand functions, the agent's reactivity is not just destabilizing, but can improve stability, too. This means that a less cautious behavior can provide better performance, both with respect to stability and to achieved profits. We show that, even if the decision mechanism is very simple and is not able to always provide the optimal production decisions, achieved profits are very close to those optimal. Finally, we show that in agreement with the existing empirical literature, the price series obtained simulating the proposed model exhibit a significant deviation from normality and large volatility, in particular when underlying deterministic dynamics become unstable and complex.

Time-varying parameter models for catchments with land use change: the importance of model structure

Science.gov (United States)

Pathiraja, Sahani; Anghileri, Daniela; Burlando, Paolo; Sharma, Ashish; Marshall, Lucy; Moradkhani, Hamid

2018-05-01

Rapid population and economic growth in Southeast Asia has been accompanied by extensive land use change with consequent impacts on catchment hydrology. Modeling methodologies capable of handling changing land use conditions are therefore becoming ever more important and are receiving increasing attention from hydrologists. A recently developed data-assimilation-based framework that allows model parameters to vary through time in response to signals of change in observations is considered for a medium-sized catchment (2880 km2) in northern Vietnam experiencing substantial but gradual land cover change. We investigate the efficacy of the method as well as the importance of the chosen model structure in ensuring the success of a time-varying parameter method. The method was used with two lumped daily conceptual models (HBV and HyMOD) that gave good-quality streamflow predictions during pre-change conditions. Although both time-varying parameter models gave improved streamflow predictions under changed conditions compared to the time-invariant parameter model, persistent biases for low flows were apparent in the HyMOD case. It was found that HyMOD was not suited to representing the modified baseflow conditions, resulting in extreme and unrealistic time-varying parameter estimates. This work shows that the chosen model can be critical for ensuring the time-varying parameter framework successfully models streamflow under changing land cover conditions. It can also be used to determine whether land cover changes (and not just meteorological factors) contribute to the observed hydrologic changes in retrospective studies where the lack of a paired control catchment precludes such an assessment.

Time-varying parameter models for catchments with land use change: the importance of model structure

Directory of Open Access Journals (Sweden)

S. Pathiraja

2018-05-01

Full Text Available Rapid population and economic growth in Southeast Asia has been accompanied by extensive land use change with consequent impacts on catchment hydrology. Modeling methodologies capable of handling changing land use conditions are therefore becoming ever more important and are receiving increasing attention from hydrologists. A recently developed data-assimilation-based framework that allows model parameters to vary through time in response to signals of change in observations is considered for a medium-sized catchment (2880 km2 in northern Vietnam experiencing substantial but gradual land cover change. We investigate the efficacy of the method as well as the importance of the chosen model structure in ensuring the success of a time-varying parameter method. The method was used with two lumped daily conceptual models (HBV and HyMOD that gave good-quality streamflow predictions during pre-change conditions. Although both time-varying parameter models gave improved streamflow predictions under changed conditions compared to the time-invariant parameter model, persistent biases for low flows were apparent in the HyMOD case. It was found that HyMOD was not suited to representing the modified baseflow conditions, resulting in extreme and unrealistic time-varying parameter estimates. This work shows that the chosen model can be critical for ensuring the time-varying parameter framework successfully models streamflow under changing land cover conditions. It can also be used to determine whether land cover changes (and not just meteorological factors contribute to the observed hydrologic changes in retrospective studies where the lack of a paired control catchment precludes such an assessment.

Robust pre-specified time synchronization of chaotic systems by employing time-varying switching surfaces in the sliding mode control scheme

Science.gov (United States)

Khanzadeh, Alireza; Pourgholi, Mahdi

2016-08-01

In the conventional chaos synchronization methods, the time at which two chaotic systems are synchronized, is usually unknown and depends on initial conditions. In this work based on Lyapunov stability theory a sliding mode controller with time-varying switching surfaces is proposed to achieve chaos synchronization at a pre-specified time for the first time. The proposed controller is able to synchronize chaotic systems precisely at any time when we want. Moreover, by choosing the time-varying switching surfaces in a way that the reaching phase is eliminated, the synchronization becomes robust to uncertainties and exogenous disturbances. Simulation results are presented to show the effectiveness of the proposed method of stabilizing and synchronizing chaotic systems with complete robustness to uncertainty and disturbances exactly at a pre-specified time.

Robust pre-specified time synchronization of chaotic systems by employing time-varying switching surfaces in the sliding mode control scheme

International Nuclear Information System (INIS)

Khanzadeh, Alireza; Pourgholi, Mahdi

2016-01-01

In the conventional chaos synchronization methods, the time at which two chaotic systems are synchronized, is usually unknown and depends on initial conditions. In this work based on Lyapunov stability theory a sliding mode controller with time-varying switching surfaces is proposed to achieve chaos synchronization at a pre-specified time for the first time. The proposed controller is able to synchronize chaotic systems precisely at any time when we want. Moreover, by choosing the time-varying switching surfaces in a way that the reaching phase is eliminated, the synchronization becomes robust to uncertainties and exogenous disturbances. Simulation results are presented to show the effectiveness of the proposed method of stabilizing and synchronizing chaotic systems with complete robustness to uncertainty and disturbances exactly at a pre-specified time. (paper)

Forecast Accuracy and Economic Gains from Bayesian Model Averaging using Time Varying Weights

NARCIS (Netherlands)

L.F. Hoogerheide (Lennart); R.H. Kleijn (Richard); H.K. van Dijk (Herman); M.J.C.M. Verbeek (Marno)

2009-01-01

textabstractSeveral Bayesian model combination schemes, including some novel approaches that simultaneously allow for parameter uncertainty, model uncertainty and robust time varying model weights, are compared in terms of forecast accuracy and economic gains using financial and macroeconomic time

Concurrence of Quantum States: Algebraic Dynamical Method Study XXX Models in a Time-Depending Random External Field

International Nuclear Information System (INIS)

Fu Chuanji; Zhu Qinsheng; Wu Shaoyi

2010-01-01

Based on algebraic dynamics and the concept of the concurrence of the entanglement, we investigate the evolutive properties of the two-qubit entanglement that formed by Heisenberg XXX models under a time-depending external held. For this system, the property of the concurrence that is only dependent on the coupling constant J and total values of the external field is proved. Furthermore, we found that the thermal concurrence of the system under a static random external field is a function of the coupling constant J, temperature T, and the magnitude of external held. (general)

The time-varying role of the family in student time use and achievement

Directory of Open Access Journals (Sweden)

Marie C. Hull

2017-10-01

Full Text Available Abstract In this paper, I use a unique dataset linking administrative school data with birth records to quantify the importance of time-varying family factors for child achievement and time use. Specifically, I take a model of academic achievement commonly used in the test score literature, and I augment it to include a family-year effect. Identification comes from the large number of sibling pairs observed in the same year. While prior literature has focused on specific shocks, such as job loss, I capture the full set of innovations that are shared across siblings in a given year. The distributions of fixed effects reveal that annual family innovations, relative to what was expected based on the previous year, are more important than teacher assignment for student achievement and also play a substantial role in the time students spend on homework, free reading, and television. JEL Classification I21, J13, J24

Time-varying metamaterials based on graphene-wrapped microwires: Modeling and potential applications

Science.gov (United States)

Salary, Mohammad Mahdi; Jafar-Zanjani, Samad; Mosallaei, Hossein

2018-03-01

The successful realization of metamaterials and metasurfaces requires the judicious choice of constituent elements. In this paper, we demonstrate the implementation of time-varying metamaterials in the terahertz frequency regime by utilizing graphene-wrapped microwires as building blocks and modulation of graphene conductivity through exterior electrical gating. These elements enable enhancement of light-graphene interaction by utilizing optical resonances associated with Mie scattering, yielding a large tunability and modulation depth. We develop a semianalytical framework based on transition-matrix formulation for modeling and analysis of periodic and aperiodic arrays of such time-varying building blocks. The proposed method is validated against full-wave numerical results obtained using the finite-difference time-domain method. It provides an ideal tool for mathematical synthesis and analysis of space-time gradient metamaterials, eliminating the need for computationally expensive numerical models. Moreover, it allows for a wider exploration of exotic space-time scattering phenomena in time-modulated metamaterials. We apply the method to explore the role of modulation parameters in the generation of frequency harmonics and their emerging wavefronts. Several potential applications of such platforms are demonstrated, including frequency conversion, holographic generation of frequency harmonics, and spatiotemporal manipulation of light. The presented results provide key physical insights to design time-modulated functional metadevices using various building blocks and open up new directions in the emerging paradigm of time-modulated metamaterials.

Brownian motion properties of optoelectronic random bit generators based on laser chaos.

Science.gov (United States)

Li, Pu; Yi, Xiaogang; Liu, Xianglian; Wang, Yuncai; Wang, Yongge

2016-07-11

The nondeterministic property of the optoelectronic random bit generator (RBG) based on laser chaos are experimentally analyzed from two aspects of the central limit theorem and law of iterated logarithm. The random bits are extracted from an optical feedback chaotic laser diode using a multi-bit extraction technique in the electrical domain. Our experimental results demonstrate that the generated random bits have no statistical distance from the Brownian motion, besides that they can pass the state-of-the-art industry-benchmark statistical test suite (NIST SP800-22). All of them give a mathematically provable evidence that the ultrafast random bit generator based on laser chaos can be used as a nondeterministic random bit source.

Parametric output-only identification of time-varying structures using a kernel recursive extended least squares TARMA approach

Science.gov (United States)

Ma, Zhi-Sai; Liu, Li; Zhou, Si-Da; Yu, Lei; Naets, Frank; Heylen, Ward; Desmet, Wim

2018-01-01

The problem of parametric output-only identification of time-varying structures in a recursive manner is considered. A kernelized time-dependent autoregressive moving average (TARMA) model is proposed by expanding the time-varying model parameters onto the basis set of kernel functions in a reproducing kernel Hilbert space. An exponentially weighted kernel recursive extended least squares TARMA identification scheme is proposed, and a sliding-window technique is subsequently applied to fix the computational complexity for each consecutive update, allowing the method to operate online in time-varying environments. The proposed sliding-window exponentially weighted kernel recursive extended least squares TARMA method is employed for the identification of a laboratory time-varying structure consisting of a simply supported beam and a moving mass sliding on it. The proposed method is comparatively assessed against an existing recursive pseudo-linear regression TARMA method via Monte Carlo experiments and shown to be capable of accurately tracking the time-varying dynamics. Furthermore, the comparisons demonstrate the superior achievable accuracy, lower computational complexity and enhanced online identification capability of the proposed kernel recursive extended least squares TARMA approach.

Time-varying exchange rate pass-through: experiences of some industrial countries

OpenAIRE

Toshitaka Sekine

2006-01-01

This paper estimates exchange rate pass-through of six major industrial countries using a time-varying parameter with stochastic volatility model. Exchange rate pass-through is divided into impacts of exchange rate fluctuations to import prices (first-stage pass-through) and those of import price movements to consumer prices (second-stage pass-through). The paper finds that both stages of pass-through have declined over time for all the sample countries. The decline in second-stage pass-throu...

A delay-dependent LMI approach to dynamics analysis of discrete-time recurrent neural networks with time-varying delays

International Nuclear Information System (INIS)

Song, Qiankun; Wang, Zidong

2007-01-01

In this Letter, the analysis problem for the existence and stability of periodic solutions is investigated for a class of general discrete-time recurrent neural networks with time-varying delays. For the neural networks under study, a generalized activation function is considered, and the traditional assumptions on the boundedness, monotony and differentiability of the activation functions are removed. By employing the latest free-weighting matrix method, an appropriate Lyapunov-Krasovskii functional is constructed and several sufficient conditions are established to ensure the existence, uniqueness, and globally exponential stability of the periodic solution for the addressed neural network. The conditions are dependent on both the lower bound and upper bound of the time-varying time delays. Furthermore, the conditions are expressed in terms of the linear matrix inequalities (LMIs), which can be checked numerically using the effective LMI toolbox in MATLAB. Two simulation examples are given to show the effectiveness and less conservatism of the proposed criteria

Generating variable and random schedules of reinforcement using Microsoft Excel macros.

Science.gov (United States)

Bancroft, Stacie L; Bourret, Jason C

2008-01-01

Variable reinforcement schedules are used to arrange the availability of reinforcement following varying response ratios or intervals of time. Random reinforcement schedules are subtypes of variable reinforcement schedules that can be used to arrange the availability of reinforcement at a constant probability across number of responses or time. Generating schedule values for variable and random reinforcement schedules can be difficult. The present article describes the steps necessary to write macros in Microsoft Excel that will generate variable-ratio, variable-interval, variable-time, random-ratio, random-interval, and random-time reinforcement schedule values.

Discrete random walk models for space-time fractional diffusion

International Nuclear Information System (INIS)

Gorenflo, Rudolf; Mainardi, Francesco; Moretti, Daniele; Pagnini, Gianni; Paradisi, Paolo

2002-01-01

A physical-mathematical approach to anomalous diffusion may be based on generalized diffusion equations (containing derivatives of fractional order in space or/and time) and related random walk models. By space-time fractional diffusion equation we mean an evolution equation obtained from the standard linear diffusion equation by replacing the second-order space derivative with a Riesz-Feller derivative of order α is part of (0,2] and skewness θ (moduleθ≤{α,2-α}), and the first-order time derivative with a Caputo derivative of order β is part of (0,1]. Such evolution equation implies for the flux a fractional Fick's law which accounts for spatial and temporal non-locality. The fundamental solution (for the Cauchy problem) of the fractional diffusion equation can be interpreted as a probability density evolving in time of a peculiar self-similar stochastic process that we view as a generalized diffusion process. By adopting appropriate finite-difference schemes of solution, we generate models of random walk discrete in space and time suitable for simulating random variables whose spatial probability density evolves in time according to this fractional diffusion equation

Achieving Synchronization in Arrays of Coupled Differential Systems with Time-Varying Couplings

Directory of Open Access Journals (Sweden)

Xinlei Yi

2013-01-01

Full Text Available We study complete synchronization of the complex dynamical networks described by linearly coupled ordinary differential equation systems (LCODEs. Here, the coupling is timevarying in both network structure and reaction dynamics. Inspired by our previous paper (Lu et al. (2007-2008, the extended Hajnal diameter is introduced and used to measure the synchronization in a general differential system. Then we find that the Hajnal diameter of the linear system induced by the time-varying coupling matrix and the largest Lyapunov exponent of the synchronized system play the key roles in synchronization analysis of LCODEs with identity inner coupling matrix. As an application, we obtain a general sufficient condition guaranteeing directed time-varying graph to reach consensus. Example with numerical simulation is provided to show the effectiveness of the theoretical results.

Nonlinear systems time-varying parameter estimation: Application to induction motors

Energy Technology Data Exchange (ETDEWEB)

Kenne, Godpromesse [Laboratoire d' Automatique et d' Informatique Appliquee (LAIA), Departement de Genie Electrique, IUT FOTSO Victor, Universite de Dschang, B.P. 134 Bandjoun (Cameroon); Ahmed-Ali, Tarek [Ecole Nationale Superieure des Ingenieurs des Etudes et Techniques d' Armement (ENSIETA), 2 Rue Francois Verny, 29806 Brest Cedex 9 (France); Lamnabhi-Lagarrigue, F. [Laboratoire des Signaux et Systemes (L2S), C.N.R.S-SUPELEC, Universite Paris XI, 3 Rue Joliot Curie, 91192 Gif-sur-Yvette (France); Arzande, Amir [Departement Energie, Ecole Superieure d' Electricite-SUPELEC, 3 Rue Joliot Curie, 91192 Gif-sur-Yvette (France)

2008-11-15

In this paper, an algorithm for time-varying parameter estimation for a large class of nonlinear systems is presented. The proof of the convergence of the estimates to their true values is achieved using Lyapunov theories and does not require that the classical persistent excitation condition be satisfied by the input signal. Since the induction motor (IM) is widely used in several industrial sectors, the algorithm developed is potentially useful for adjusting the controller parameters of variable speed drives. The method proposed is simple and easily implementable in real-time. The application of this approach to on-line estimation of the rotor resistance of IM shows a rapidly converging estimate in spite of measurement noise, discretization effects, parameter uncertainties (e.g. inaccuracies on motor inductance values) and modeling inaccuracies. The robustness analysis for this IM application also revealed that the proposed scheme is insensitive to the stator resistance variations within a wide range. The merits of the proposed algorithm in the case of on-line time-varying rotor resistance estimation are demonstrated via experimental results in various operating conditions of the induction motor. The experimental results obtained demonstrate that the application of the proposed algorithm to update on-line the parameters of an adaptive controller (e.g. IM and synchronous machines adaptive control) can improve the efficiency of the industrial process. The other interesting features of the proposed method include fault detection/estimation and adaptive control of IM and synchronous machines. (author)

Study of the effect of varying core diameter, shell thickness and strain velocity on the tensile properties of single crystals of Cu-Ag core-shell nanowire using molecular dynamics simulations

Science.gov (United States)

Sarkar, Jit; Das, D. K.

2018-01-01

Core-shell type nanostructures show exceptional properties due to their unique structure having a central solid core of one type and an outer thin shell of another type which draw immense attention among researchers. In this study, molecular dynamics simulations are carried out on single crystals of copper-silver core-shell nanowires having wire diameter ranging from 9 to 30 nm with varying core diameter, shell thickness, and strain velocity. The tensile properties like yield strength, ultimate tensile strength, and Young's modulus are studied and correlated by varying one parameter at a time and keeping the other two parameters constant. The results obtained for a fixed wire size and different strain velocities were extrapolated to calculate the tensile properties like yield strength and Young's modulus at standard strain rate of 1 mm/min. The results show ultra-high tensile properties of copper-silver core-shell nanowires, several times than that of bulk copper and silver. These copper-silver core-shell nanowires can be used as a reinforcing agent in bulk metal matrix for developing ultra-high strength nanocomposites.

Rate Control for Network-Coded Multipath Relaying with Time-Varying Connectivity

Science.gov (United States)

2010-12-10

Armen Babikyan, Nathaniel M. Jones, Thomas H. Shake, and Andrew P. Worthen MIT Lincoln Laboratory 244 Wood Street Lexington, MA 02420 DDRE, 1777...delay U U U U SAR 11 Zach Sweet 781-981-5997 1 Rate Control for Network-Coded Multipath Relaying with Time-Varying Connectivity Brooke Shrader, Armen

The Scalp Time-Varying Networks of N170: Reference, Latency, and Information Flow

Directory of Open Access Journals (Sweden)

Yin Tian

2018-04-01

Full Text Available Using the scalp time-varying network method, the present study is the first to investigate the temporal influence of the reference on N170, a negative event-related potential component (ERP appeared about 170 ms that is elicited by facial recognition, in the network levels. Two kinds of scalp electroencephalogram (EEG references, namely, AR (average of all recording channels and reference electrode standardization technique (REST, were comparatively investigated via the time-varying processing of N170. Results showed that the latency and amplitude of N170 were significantly different between REST and AR, with the former being earlier and smaller. In particular, the information flow from right temporal-parietal P8 to left P7 in the time-varying network was earlier in REST than that in AR, and this phenomenon was reproduced by simulation, in which the performance of REST was closer to the true case at source level. These findings indicate that reference plays a crucial role in ERP data interpretation, and importantly, the newly developed approximate zero-reference REST would be a superior choice for precise evaluation of the scalp spatio-temporal changes relating to various cognitive events.

Research on Adaptive Neural Network Control System Based on Nonlinear U-Model with Time-Varying Delay

Directory of Open Access Journals (Sweden)

Fengxia Xu

2014-01-01

Full Text Available U-model can approximate a large class of smooth nonlinear time-varying delay system to any accuracy by using time-varying delay parameters polynomial. This paper proposes a new approach, namely, U-model approach, to solving the problems of analysis and synthesis for nonlinear systems. Based on the idea of discrete-time U-model with time-varying delay, the identification algorithm of adaptive neural network is given for the nonlinear model. Then, the controller is designed by using the Newton-Raphson formula and the stability analysis is given for the closed-loop nonlinear systems. Finally, illustrative examples are given to show the validity and applicability of the obtained results.

Robust stability for uncertain stochastic fuzzy BAM neural networks with time-varying delays

Science.gov (United States)

Syed Ali, M.; Balasubramaniam, P.

2008-07-01

In this Letter, by utilizing the Lyapunov functional and combining with the linear matrix inequality (LMI) approach, we analyze the global asymptotic stability of uncertain stochastic fuzzy Bidirectional Associative Memory (BAM) neural networks with time-varying delays which are represented by the Takagi-Sugeno (TS) fuzzy models. A new class of uncertain stochastic fuzzy BAM neural networks with time varying delays has been studied and sufficient conditions have been derived to obtain conservative result in stochastic settings. The developed results are more general than those reported in the earlier literatures. In addition, the numerical examples are provided to illustrate the applicability of the result using LMI toolbox in MATLAB.

Robust stability for uncertain stochastic fuzzy BAM neural networks with time-varying delays

International Nuclear Information System (INIS)

Syed Ali, M.; Balasubramaniam, P.

2008-01-01

In this Letter, by utilizing the Lyapunov functional and combining with the linear matrix inequality (LMI) approach, we analyze the global asymptotic stability of uncertain stochastic fuzzy Bidirectional Associative Memory (BAM) neural networks with time-varying delays which are represented by the Takagi-Sugeno (TS) fuzzy models. A new class of uncertain stochastic fuzzy BAM neural networks with time varying delays has been studied and sufficient conditions have been derived to obtain conservative result in stochastic settings. The developed results are more general than those reported in the earlier literatures. In addition, the numerical examples are provided to illustrate the applicability of the result using LMI toolbox in MATLAB

Modeling the time--varying subjective quality of HTTP video streams with rate adaptations.

Science.gov (United States)

Chen, Chao; Choi, Lark Kwon; de Veciana, Gustavo; Caramanis, Constantine; Heath, Robert W; Bovik, Alan C

2014-05-01

Newly developed hypertext transfer protocol (HTTP)-based video streaming technologies enable flexible rate-adaptation under varying channel conditions. Accurately predicting the users' quality of experience (QoE) for rate-adaptive HTTP video streams is thus critical to achieve efficiency. An important aspect of understanding and modeling QoE is predicting the up-to-the-moment subjective quality of a video as it is played, which is difficult due to hysteresis effects and nonlinearities in human behavioral responses. This paper presents a Hammerstein-Wiener model for predicting the time-varying subjective quality (TVSQ) of rate-adaptive videos. To collect data for model parameterization and validation, a database of longer duration videos with time-varying distortions was built and the TVSQs of the videos were measured in a large-scale subjective study. The proposed method is able to reliably predict the TVSQ of rate adaptive videos. Since the Hammerstein-Wiener model has a very simple structure, the proposed method is suitable for online TVSQ prediction in HTTP-based streaming.

Robust stability of uncertain Markovian jumping Cohen-Grossberg neural networks with mixed time-varying delays

International Nuclear Information System (INIS)

Sheng Li; Yang Huizhong

2009-01-01

This paper considers the robust stability of a class of uncertain Markovian jumping Cohen-Grossberg neural networks (UMJCGNNs) with mixed time-varying delays. The parameter uncertainties are norm-bounded and the mixed time-varying delays comprise discrete and distributed time delays. Based on the Lyapunov stability theory and linear matrix inequality (LMI) technique, some robust stability conditions guaranteeing the global robust convergence of the equilibrium point are derived. An example is given to show the effectiveness of the proposed results.

The time-varying shortest path problem with fuzzy transit costs and speedup

Directory of Open Access Journals (Sweden)

Rezapour Hassan

2016-08-01

Full Text Available In this paper, we focus on the time-varying shortest path problem, where the transit costs are fuzzy numbers. Moreover, we consider this problem in which the transit time can be shortened at a fuzzy speedup cost. Speedup may also be a better decision to find the shortest path from a source vertex to a specified vertex.

Positive Almost Periodic Solutions for a Time-Varying Fishing Model with Delay

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Xia Li

2011-01-01

Full Text Available This paper is concerned with a time-varying fishing model with delay. By means of the continuation theorem of coincidence degree theory, we prove that it has at least one positive almost periodic solution.

Effective soil hydraulic properties in space and time: some field data analysis and modeling concepts

Science.gov (United States)

Soil hydraulic properties, which control surface fluxes and storage of water and chemicals in the soil profile, vary in space and time. Spatial variability above the measurement scale (e.g., soil area of 0.07 m2 or support volume of 14 L) must be upscaled appropriately to determine “effective” hydr...

Visualizing time: how linguistic metaphors are incorporated into displaying instruments in the process of interpreting time-varying signals

Science.gov (United States)

Garcia-Belmonte, Germà

2017-06-01

Spatial visualization is a well-established topic of education research that has allowed improving science and engineering students' skills on spatial relations. Connections have been established between visualization as a comprehension tool and instruction in several scientific fields. Learning about dynamic processes mainly relies upon static spatial representations or images. Visualization of time is inherently problematic because time can be conceptualized in terms of two opposite conceptual metaphors based on spatial relations as inferred from conventional linguistic patterns. The situation is particularly demanding when time-varying signals are recorded using displaying electronic instruments, and the image should be properly interpreted. This work deals with the interplay between linguistic metaphors, visual thinking and scientific instrument mediation in the process of interpreting time-varying signals displayed by electronic instruments. The analysis draws on a simplified version of a communication system as example of practical signal recording and image visualization in a physics and engineering laboratory experience. Instrumentation delivers meaningful signal representations because it is designed to incorporate a specific and culturally favored time view. It is suggested that difficulties in interpreting time-varying signals are linked with the existing dual perception of conflicting time metaphors. The activation of specific space-time conceptual mapping might allow for a proper signal interpretation. Instruments play then a central role as visualization mediators by yielding an image that matches specific perception abilities and practical purposes. Here I have identified two ways of understanding time as used in different trajectories through which students are located. Interestingly specific displaying instruments belonging to different cultural traditions incorporate contrasting time views. One of them sees time in terms of a dynamic metaphor

Mesoscopic description of random walks on combs

Science.gov (United States)

Méndez, Vicenç; Iomin, Alexander; Campos, Daniel; Horsthemke, Werner

2015-12-01

Combs are a simple caricature of various types of natural branched structures, which belong to the category of loopless graphs and consist of a backbone and branches. We study continuous time random walks on combs and present a generic method to obtain their transport properties. The random walk along the branches may be biased, and we account for the effect of the branches by renormalizing the waiting time probability distribution function for the motion along the backbone. We analyze the overall diffusion properties along the backbone and find normal diffusion, anomalous diffusion, and stochastic localization (diffusion failure), respectively, depending on the characteristics of the continuous time random walk along the branches, and compare our analytical results with stochastic simulations.

Perfect fluid Bianchi Type-I cosmological models with time varying G ...

Indian Academy of Sciences (India)

Abstract. Bianchi Type-I cosmological models containing perfect fluid with time vary- ing G and Λ have been presented. The solutions obtained represent an expansion scalar θ bearing a constant ratio to the anisotropy in the direction of space-like unit vector λi. Of the two models obtained, one has negative vacuum energy ...

Inferring time-varying network topologies from gene expression data.

Science.gov (United States)

Rao, Arvind; Hero, Alfred O; States, David J; Engel, James Douglas

2007-01-01

Most current methods for gene regulatory network identification lead to the inference of steady-state networks, that is, networks prevalent over all times, a hypothesis which has been challenged. There has been a need to infer and represent networks in a dynamic, that is, time-varying fashion, in order to account for different cellular states affecting the interactions amongst genes. In this work, we present an approach, regime-SSM, to understand gene regulatory networks within such a dynamic setting. The approach uses a clustering method based on these underlying dynamics, followed by system identification using a state-space model for each learnt cluster--to infer a network adjacency matrix. We finally indicate our results on the mouse embryonic kidney dataset as well as the T-cell activation-based expression dataset and demonstrate conformity with reported experimental evidence.

Complexity Variability Assessment of Nonlinear Time-Varying Cardiovascular Control

Science.gov (United States)

Valenza, Gaetano; Citi, Luca; Garcia, Ronald G.; Taylor, Jessica Noggle; Toschi, Nicola; Barbieri, Riccardo

2017-02-01

The application of complex systems theory to physiology and medicine has provided meaningful information about the nonlinear aspects underlying the dynamics of a wide range of biological processes and their disease-related aberrations. However, no studies have investigated whether meaningful information can be extracted by quantifying second-order moments of time-varying cardiovascular complexity. To this extent, we introduce a novel mathematical framework termed complexity variability, in which the variance of instantaneous Lyapunov spectra estimated over time serves as a reference quantifier. We apply the proposed methodology to four exemplary studies involving disorders which stem from cardiology, neurology and psychiatry: Congestive Heart Failure (CHF), Major Depression Disorder (MDD), Parkinson’s Disease (PD), and Post-Traumatic Stress Disorder (PTSD) patients with insomnia under a yoga training regime. We show that complexity assessments derived from simple time-averaging are not able to discern pathology-related changes in autonomic control, and we demonstrate that between-group differences in measures of complexity variability are consistent across pathologies. Pathological states such as CHF, MDD, and PD are associated with an increased complexity variability when compared to healthy controls, whereas wellbeing derived from yoga in PTSD is associated with lower time-variance of complexity.

Novel criteria for exponential synchronization of inner time-varying complex networks with coupling delay

International Nuclear Information System (INIS)

Zhang Qun-Jiao; Zhao Jun-Chan

2012-01-01

This paper mainly investigates the exponential synchronization of an inner time-varying complex network with coupling delay. Firstly, the synchronization of complex networks is decoupled into the stability of the corresponding dynamical systems. Based on the Lyapunov function theory, some sufficient conditions to guarantee its stability with any given convergence rate are derived, thus the synchronization of the networks is achieved. Finally, the results are illustrated by a simple time-varying network model with a coupling delay. All involved numerical simulations verify the correctness of the theoretical analysis. (general)

Plasmonic modes and extinction properties of a random nanocomposite cylinder

Energy Technology Data Exchange (ETDEWEB)

Moradi, Afshin, E-mail: a.moradi@kut.ac.ir [Department of Basic Sciences, Kermanshah University of Technology, Kermanshah, Iran and Department of Nano Science, Institute for Studies in Theoretical Physics and Mathematics (IPM), Tehran (Iran, Islamic Republic of)

2014-04-15

We study the properties of surface plasmon-polariton waves of a random metal-dielectric nanocomposite cylinder, consisting of bulk metal embedded with dielectric nanoparticles. We use the Maxwell-Garnett formulation to model the effective dielectric function of the composite medium and show that there exist two surface mode bands. We investigate the extinction properties of the system, and obtain the dependence of the extinction spectrum on the nanoparticles’ shape and concentration as well as the cylinder radius and the incidence angle for both TE and TM polarization.

Simulations of hybrid system varying solar radiation and microturbine response time

Directory of Open Access Journals (Sweden)

Yolanda Fernández Ribaya

2015-07-01

Full Text Available Hybrid power systems, such as combinations of renewable power sources with intermittent power production and non-renewable power sources, theoretically increase the reliability and thus integration of renewable sources in the electrical system. However, a recent increase in the number of hybrid installations has sparked interest in the effects of their connection to the grid, especially in remote areas. This paper analyses a photovoltaic-gas microturbine hybrid system dimensioned to be installed in La Paz (Mexico.The research presented in this paper studies and quantifies the effects on the total electric power produced, varying both the solar radiation and the gas microturbine response time. The gas microturbine and the photovoltaic panels are modelled using Matlab/Simulink software, obtaining a platform where different tests to simulate real conditions have been executed. They consist of diverse ramps of irradiance that replicate solar radiation variations, and different microturbine response times reproduced by the time constants of a first order transfer function that models the microturbine dynamic response. The results obtained show that when radiation varies quickly it does not produce significant differences in the power guarantee or the microturbine gas consumption, to any microturbine response time. However, these two parameters are highly variable with smooth radiance variations. The maximum total power variation decreases greatly as the radiation variation gets lower. In addition, by decreasing the microturbine response time, it is possible to appreciably increase the power guarantee although the maximum power variation and gas consumption increase. Only in cases of low radiation variation is there no appreciable difference in the maximum power variation obtained by the different turbine response times.

Simulations of hybrid system varying solar radiation and microturbine response time

Energy Technology Data Exchange (ETDEWEB)

Fernández Ribaya, Yolanda, E-mail: fernandezryolanda@uniovi.es; Álvarez, Eduardo; Paredes Sánchez, José Pablo; Xiberta Bernat, Jorge [Department of Energy E.I.M.E.M., University of Oviedo. 13 Independencia Street 2" n" d floor, 36004, Oviedo (Spain)

2015-07-15

Hybrid power systems, such as combinations of renewable power sources with intermittent power production and non-renewable power sources, theoretically increase the reliability and thus integration of renewable sources in the electrical system. However, a recent increase in the number of hybrid installations has sparked interest in the effects of their connection to the grid, especially in remote areas. This paper analyses a photovoltaic-gas microturbine hybrid system dimensioned to be installed in La Paz (Mexico).The research presented in this paper studies and quantifies the effects on the total electric power produced, varying both the solar radiation and the gas microturbine response time. The gas microturbine and the photovoltaic panels are modelled using Matlab/Simulink software, obtaining a platform where different tests to simulate real conditions have been executed. They consist of diverse ramps of irradiance that replicate solar radiation variations, and different microturbine response times reproduced by the time constants of a first order transfer function that models the microturbine dynamic response. The results obtained show that when radiation varies quickly it does not produce significant differences in the power guarantee or the microturbine gas consumption, to any microturbine response time. However, these two parameters are highly variable with smooth radiance variations. The maximum total power variation decreases greatly as the radiation variation gets lower. In addition, by decreasing the microturbine response time, it is possible to appreciably increase the power guarantee although the maximum power variation and gas consumption increase. Only in cases of low radiation variation is there no appreciable difference in the maximum power variation obtained by the different turbine response times.

Noise level estimation in weakly nonlinear slowly time-varying systems

International Nuclear Information System (INIS)

Aerts, J R M; Dirckx, J J J; Lataire, J; Pintelon, R

2008-01-01

Recently, a method using multisine excitation was proposed for estimating the frequency response, the nonlinear distortions and the disturbing noise of weakly nonlinear time-invariant systems. This method has been demonstrated on the measurement of nonlinear distortions in the vibration of acoustically driven systems such as a latex membrane, which is a good example of a time-invariant system [1]. However, not all systems are perfectly time invariant, e.g. biomechanical systems. This time variation can be misinterpreted as an elevated noise floor, and the classical noise estimation method gives a wrong result. Two improved methods to retrieve the correct noise information from the measurements are presented. Both of them make use of multisine excitations. First, it is demonstrated that the improved methods give the same result as the classical noise estimation method when applied to a time-invariant system (high-quality microphone membrane). Next, it is demonstrated that the new methods clearly give an improved estimate of the noise level on time-varying systems. As an application example results for the vibration response of an eardrum are shown

Stability Control of Force-Reflected Nonlinear Multilateral Teleoperation System under Time-Varying Delays

Directory of Open Access Journals (Sweden)

Da Sun

2016-01-01

Full Text Available A novel control algorithm based on the modified wave-variable controllers is proposed to achieve accurate position synchronization and reasonable force tracking of the nonlinear single-master-multiple-slave teleoperation system and simultaneously guarantee overall system’s stability in the presence of large time-varying delays. The system stability in different scenarios of human and environment situations has been analyzed. The proposed method is validated through experimental work based on the 3-DOF trilateral teleoperation system consisting of three different manipulators. The experimental results clearly demonstrate the feasibility of the proposed algorithm to achieve high transparency and robust stability in nonlinear single-master-multiple-slave teleoperation system in the presence of time-varying delays.

Instability in time-delayed switched systems induced by fast and random switching

Science.gov (United States)

Guo, Yao; Lin, Wei; Chen, Yuming; Wu, Jianhong

2017-07-01

In this paper, we consider a switched system comprising finitely or infinitely many subsystems described by linear time-delayed differential equations and a rule that orchestrates the system switching randomly among these subsystems, where the switching times are also randomly chosen. We first construct a counterintuitive example where even though all the time-delayed subsystems are exponentially stable, the behaviors of the randomly switched system change from stable dynamics to unstable dynamics with a decrease of the dwell time. Then by using the theories of stochastic processes and delay differential equations, we present a general result on when this fast and random switching induced instability should occur and we extend this to the case of nonlinear time-delayed switched systems as well.

A hepatitis C virus infection model with time-varying drug effectiveness: solution and analysis.

Directory of Open Access Journals (Sweden)

Jessica M Conway

2014-08-01

Full Text Available Simple models of therapy for viral diseases such as hepatitis C virus (HCV or human immunodeficiency virus assume that, once therapy is started, the drug has a constant effectiveness. More realistic models have assumed either that the drug effectiveness depends on the drug concentration or that the effectiveness varies over time. Here a previously introduced varying-effectiveness (VE model is studied mathematically in the context of HCV infection. We show that while the model is linear, it has no closed-form solution due to the time-varying nature of the effectiveness. We then show that the model can be transformed into a Bessel equation and derive an analytic solution in terms of modified Bessel functions, which are defined as infinite series, with time-varying arguments. Fitting the solution to data from HCV infected patients under therapy has yielded values for the parameters in the model. We show that for biologically realistic parameters, the predicted viral decay on therapy is generally biphasic and resembles that predicted by constant-effectiveness (CE models. We introduce a general method for determining the time at which the transition between decay phases occurs based on calculating the point of maximum curvature of the viral decay curve. For the parameter regimes of interest, we also find approximate solutions for the VE model and establish the asymptotic behavior of the system. We show that the rate of second phase decay is determined by the death rate of infected cells multiplied by the maximum effectiveness of therapy, whereas the rate of first phase decline depends on multiple parameters including the rate of increase of drug effectiveness with time.

Statistical analysis of random duration times

International Nuclear Information System (INIS)

Engelhardt, M.E.

1996-04-01

This report presents basic statistical methods for analyzing data obtained by observing random time durations. It gives nonparametric estimates of the cumulative distribution function, reliability function and cumulative hazard function. These results can be applied with either complete or censored data. Several models which are commonly used with time data are discussed, and methods for model checking and goodness-of-fit tests are discussed. Maximum likelihood estimates and confidence limits are given for the various models considered. Some results for situations where repeated durations such as repairable systems are also discussed

Control-focused, nonlinear and time-varying modelling of dielectric elastomer actuators with frequency response analysis

International Nuclear Information System (INIS)

Jacobs, William R; Dodd, Tony J; Anderson, Sean R; Wilson, Emma D; Porrill, John; Assaf, Tareq; Rossiter, Jonathan

2015-01-01

Current models of dielectric elastomer actuators (DEAs) are mostly constrained to first principal descriptions that are not well suited to the application of control design due to their computational complexity. In this work we describe an integrated framework for the identification of control focused, data driven and time-varying DEA models that allow advanced analysis of nonlinear system dynamics in the frequency-domain. Experimentally generated input–output data (voltage-displacement) was used to identify control-focused, nonlinear and time-varying dynamic models of a set of film-type DEAs. The model description used was the nonlinear autoregressive with exogenous input structure. Frequency response analysis of the DEA dynamics was performed using generalized frequency response functions, providing insight and a comparison into the time-varying dynamics across a set of DEA actuators. The results demonstrated that models identified within the presented framework provide a compact and accurate description of the system dynamics. The frequency response analysis revealed variation in the time-varying dynamic behaviour of DEAs fabricated to the same specifications. These results suggest that the modelling and analysis framework presented here is a potentially useful tool for future work in guiding DEA actuator design and fabrication for application domains such as soft robotics. (paper)

A Kalman-filter based approach to identification of time-varying gene regulatory networks.

Directory of Open Access Journals (Sweden)

Jie Xiong

Full Text Available MOTIVATION: Conventional identification methods for gene regulatory networks (GRNs have overwhelmingly adopted static topology models, which remains unchanged over time to represent the underlying molecular interactions of a biological system. However, GRNs are dynamic in response to physiological and environmental changes. Although there is a rich literature in modeling static or temporally invariant networks, how to systematically recover these temporally changing networks remains a major and significant pressing challenge. The purpose of this study is to suggest a two-step strategy that recovers time-varying GRNs. RESULTS: It is suggested in this paper to utilize a switching auto-regressive model to describe the dynamics of time-varying GRNs, and a two-step strategy is proposed to recover the structure of time-varying GRNs. In the first step, the change points are detected by a Kalman-filter based method. The observed time series are divided into several segments using these detection results; and each time series segment belonging to two successive demarcating change points is associated with an individual static regulatory network. In the second step, conditional network structure identification methods are used to reconstruct the topology for each time interval. This two-step strategy efficiently decouples the change point detection problem and the topology inference problem. Simulation results show that the proposed strategy can detect the change points precisely and recover each individual topology structure effectively. Moreover, computation results with the developmental data of Drosophila Melanogaster show that the proposed change point detection procedure is also able to work effectively in real world applications and the change point estimation accuracy exceeds other existing approaches, which means the suggested strategy may also be helpful in solving actual GRN reconstruction problem.

The thermodynamic and structural properties of metallocenes-type random ethylene copolymers

International Nuclear Information System (INIS)

Simanke, Adriane G.; Mauler, Raquel S.; Galland, Griselda B.; Alamo, Rufina G.

2001-01-01

The properties of a series of random ethylene copolymers prepared with the metallocenes catalytic system rac-Et[Ind] 2 ZrCl 2 /MAO were studied for a large variety of comonomer types. These include the classical 1-alkene type with length up to 10 carbons and those of the cyclic type such as cyclopentadiene and dicyclopentadiene. Under rapid crystallization, the melting temperatures of the newly synthesized copolymers followed the relation of model random copolymers indicating a behavior that conforms to that predicted by Flory's phase equilibrium theory. The molar entropy of fusion is not significantly altered by the comonomer type including the dicyclopentadiene type. All types of comonomers studied showed, for a fixed comonomer content, the same change in properties during annealing, except the ethylene 1-butenes. These latter copolymers and the hydrogenated poly butadiene showed a faster rate of change in thermal properties. This is consistent with a higher molecular diffusion for the butene comonomer than for the rest of comonomers analyzed. The properties of the inter lamellar region were also studied as a function of comonomer type and content following the variation of the amorphous halo extracted from the WAXS diffractograms. The observed systematic decrease in the peak scattering angle with increasing comonomer content indicates a variation of the intermolecular liquid structure. (author)

Randomness in preference orderings, outcomes and attribute tastes: An application to journey time risk

DEFF Research Database (Denmark)

Batley, Richard; Ibáñez Rivas, Juan Nicolás

2012-01-01

estimate a mean ‘reliability ratio’ (ratio of the value of standard deviation of journey time to the value of scheduled journey time) of 2.07, against a median of 0.85. The properties of the distribution of the reliability ratio suggest a predominant behaviour of aversion to journey time risk.......Within the broad area of probabilistic modelling of individual discrete choice, we develop three strands of discussion. First, we outline a theoretical framework for the modelling of individual discrete choice under risk, distinguishing between three specific sources of randomness; in preference...... orderings, in outcomes, and in attribute tastes. Second, we apply this theoretical modelling framework to the domain of journey time risk (or ‘reliability’), a subject which has acquired prominence in the transportation policies of many countries. Third, we apply the modelling framework empirically, based...

Joint optimization of green vehicle scheduling and routing problem with time-varying speeds

Science.gov (United States)

Zhang, Dezhi; Wang, Xin; Ni, Nan; Zhang, Zhuo

2018-01-01

Based on an analysis of the congestion effect and changes in the speed of vehicle flow during morning and evening peaks in a large- or medium-sized city, the piecewise function is used to capture the rules of the time-varying speed of vehicles, which are very important in modelling their fuel consumption and CO2 emission. A joint optimization model of the green vehicle scheduling and routing problem with time-varying speeds is presented in this study. Extra wages during nonworking periods and soft time-window constraints are considered. A heuristic algorithm based on the adaptive large neighborhood search algorithm is also presented. Finally, a numerical simulation example is provided to illustrate the optimization model and its algorithm. Results show that, (1) the shortest route is not necessarily the route that consumes the least energy, (2) the departure time influences the vehicle fuel consumption and CO2 emissions and the optimal departure time saves on fuel consumption and reduces CO2 emissions by up to 5.4%, and (3) extra driver wages have significant effects on routing and departure time slot decisions. PMID:29466370

Continuous-Time Mean-Variance Portfolio Selection with Random Horizon

International Nuclear Information System (INIS)

Yu, Zhiyong

2013-01-01

This paper examines the continuous-time mean-variance optimal portfolio selection problem with random market parameters and random time horizon. Treating this problem as a linearly constrained stochastic linear-quadratic optimal control problem, I explicitly derive the efficient portfolios and efficient frontier in closed forms based on the solutions of two backward stochastic differential equations. Some related issues such as a minimum variance portfolio and a mutual fund theorem are also addressed. All the results are markedly different from those in the problem with deterministic exit time. A key part of my analysis involves proving the global solvability of a stochastic Riccati equation, which is interesting in its own right

Continuous-Time Mean-Variance Portfolio Selection with Random Horizon

Energy Technology Data Exchange (ETDEWEB)

Yu, Zhiyong, E-mail: yuzhiyong@sdu.edu.cn [Shandong University, School of Mathematics (China)

2013-12-15

This paper examines the continuous-time mean-variance optimal portfolio selection problem with random market parameters and random time horizon. Treating this problem as a linearly constrained stochastic linear-quadratic optimal control problem, I explicitly derive the efficient portfolios and efficient frontier in closed forms based on the solutions of two backward stochastic differential equations. Some related issues such as a minimum variance portfolio and a mutual fund theorem are also addressed. All the results are markedly different from those in the problem with deterministic exit time. A key part of my analysis involves proving the global solvability of a stochastic Riccati equation, which is interesting in its own right.

End-of-the-year economic growth and time-varying expected returns

DEFF Research Database (Denmark)

Møller, Stig V.; Rangvid, Jesper

2015-01-01

We show that macroeconomic growth at the end of the year (fourth quarter or December) strongly influences expected returns on risky financial assets, whereas economic growth during the rest of the year does not. We find this pattern for many different asset classes, across different time periods......, and for US and international data. We also show that movements in the surplus consumption ratio of Campbell and Cochrane (1999) , a theoretically well-founded measure of time-varying risk aversion linked to macroeconomic growth, influence expected returns stronger during the fourth quarter than the other...

Novel criteria for global exponential periodicity and stability of recurrent neural networks with time-varying delays

International Nuclear Information System (INIS)

Song Qiankun

2008-01-01

In this paper, the global exponential periodicity and stability of recurrent neural networks with time-varying delays are investigated by applying the idea of vector Lyapunov function, M-matrix theory and inequality technique. We assume neither the global Lipschitz conditions on these activation functions nor the differentiability on these time-varying delays, which were needed in other papers. Several novel criteria are found to ascertain the existence, uniqueness and global exponential stability of periodic solution for recurrent neural network with time-varying delays. Moreover, the exponential convergence rate index is estimated, which depends on the system parameters. Some previous results are improved and generalized, and an example is given to show the effectiveness of our method

An X-ray CCD signal generator with true random arrival time

International Nuclear Information System (INIS)

Huo Jia; Xu Yuming; Chen Yong; Cui Weiwei; Li Wei; Zhang Ziliang; Han Dawei; Wang Yusan; Wang Juan

2011-01-01

An FPGA-based true random signal generator with adjustable amplitude and exponential distribution of time interval is presented. Since traditional true random number generators (TRNG) are resource costly and difficult to transplant, we employed a method of random number generation based on jitter and phase noise in ring oscillators formed by gates in an FPGA. In order to improve the random characteristics, a combination of two different pseudo-random processing circuits is used for post processing. The effects of the design parameters, such as sample frequency are discussed. Statistical tests indicate that the generator can well simulate the timing behavior of random signals with Poisson distribution. The X-ray CCD signal generator will be used in debugging the CCD readout system of the Low Energy X-ray Instrument onboard the Hard X-ray Modulation Telescope (HXMT). (authors)

Online Support Vector Regression with Varying Parameters for Time-Dependent Data

International Nuclear Information System (INIS)

Omitaomu, Olufemi A.; Jeong, Myong K.; Badiru, Adedeji B.

2011-01-01

Support vector regression (SVR) is a machine learning technique that continues to receive interest in several domains including manufacturing, engineering, and medicine. In order to extend its application to problems in which datasets arrive constantly and in which batch processing of the datasets is infeasible or expensive, an accurate online support vector regression (AOSVR) technique was proposed. The AOSVR technique efficiently updates a trained SVR function whenever a sample is added to or removed from the training set without retraining the entire training data. However, the AOSVR technique assumes that the new samples and the training samples are of the same characteristics; hence, the same value of SVR parameters is used for training and prediction. This assumption is not applicable to data samples that are inherently noisy and non-stationary such as sensor data. As a result, we propose Accurate On-line Support Vector Regression with Varying Parameters (AOSVR-VP) that uses varying SVR parameters rather than fixed SVR parameters, and hence accounts for the variability that may exist in the samples. To accomplish this objective, we also propose a generalized weight function to automatically update the weights of SVR parameters in on-line monitoring applications. The proposed function allows for lower and upper bounds for SVR parameters. We tested our proposed approach and compared results with the conventional AOSVR approach using two benchmark time series data and sensor data from nuclear power plant. The results show that using varying SVR parameters is more applicable to time dependent data.

Randomized Caches Can Be Pretty Useful to Hard Real-Time Systems

Directory of Open Access Journals (Sweden)

Enrico Mezzetti

2015-03-01

Full Text Available Cache randomization per se, and its viability for probabilistic timing analysis (PTA of critical real-time systems, are receiving increasingly close attention from the scientific community and the industrial practitioners. In fact, the very notion of introducing randomness and probabilities in time-critical systems has caused strenuous debates owing to the apparent clash that this idea has with the strictly deterministic view traditionally held for those systems. A paper recently appeared in LITES (Reineke, J. (2014. Randomized Caches Considered Harmful in Hard Real-Time Systems. LITES, 1(1, 03:1-03:13. provides a critical analysis of the weaknesses and risks entailed in using randomized caches in hard real-time systems. In order to provide the interested reader with a fuller, balanced appreciation of the subject matter, a critical analysis of the benefits brought about by that innovation should be provided also. This short paper addresses that need by revisiting the array of issues addressed in the cited work, in the light of the latest advances to the relevant state of the art. Accordingly, we show that the potential benefits of randomized caches do offset their limitations, causing them to be - when used in conjunction with PTA - a serious competitor to conventional designs.

Robust Moving Horizon H∞ Control of Discrete Time-Delayed Systems with Interval Time-Varying Delays

Directory of Open Access Journals (Sweden)

F. Yıldız Tascikaraoglu

2014-01-01

Full Text Available In this study, design of a delay-dependent type moving horizon state-feedback control (MHHC is considered for a class of linear discrete-time system subject to time-varying state delays, norm-bounded uncertainties, and disturbances with bounded energies. The closed-loop robust stability and robust performance problems are considered to overcome the instability and poor disturbance rejection performance due to the existence of parametric uncertainties and time-delay appeared in the system dynamics. Utilizing a discrete-time Lyapunov-Krasovskii functional, some delay-dependent linear matrix inequality (LMI based conditions are provided. It is shown that if one can find a feasible solution set for these LMI conditions iteratively at each step of run-time, then we can construct a control law which guarantees the closed-loop asymptotic stability, maximum disturbance rejection performance, and closed-loop dissipativity in view of the actuator limitations. Two numerical examples with simulations on a nominal and uncertain discrete-time, time-delayed systems, are presented at the end, in order to demonstrate the efficiency of the proposed method.

Modelling tourists arrival using time varying parameter

Science.gov (United States)

Suciptawati, P.; Sukarsa, K. G.; Kencana, Eka N.

2017-06-01

The importance of tourism and its related sectors to support economic development and poverty reduction in many countries increase researchers’ attentions to study and model tourists’ arrival. This work is aimed to demonstrate time varying parameter (TVP) technique to model the arrival of Korean’s tourists to Bali. The number of Korean tourists whom visiting Bali for period January 2010 to December 2015 were used to model the number of Korean’s tourists to Bali (KOR) as dependent variable. The predictors are the exchange rate of Won to IDR (WON), the inflation rate in Korea (INFKR), and the inflation rate in Indonesia (INFID). Observing tourists visit to Bali tend to fluctuate by their nationality, then the model was built by applying TVP and its parameters were approximated using Kalman Filter algorithm. The results showed all of predictor variables (WON, INFKR, INFID) significantly affect KOR. For in-sample and out-of-sample forecast with ARIMA’s forecasted values for the predictors, TVP model gave mean absolute percentage error (MAPE) as much as 11.24 percent and 12.86 percent, respectively.

New results on global exponential stability of recurrent neural networks with time-varying delays

International Nuclear Information System (INIS)

Xu Shengyuan; Chu Yuming; Lu Junwei

2006-01-01

This Letter provides new sufficient conditions for the existence, uniqueness and global exponential stability of the equilibrium point of recurrent neural networks with time-varying delays by employing Lyapunov functions and using the Halanay inequality. The time-varying delays are not necessarily differentiable. Both Lipschitz continuous activation functions and monotone nondecreasing activation functions are considered. The derived stability criteria are expressed in terms of linear matrix inequalities (LMIs), which can be checked easily by resorting to recently developed algorithms solving LMIs. Furthermore, the proposed stability results are less conservative than some previous ones in the literature, which is demonstrated via some numerical examples

New results on global exponential stability of recurrent neural networks with time-varying delays

Energy Technology Data Exchange (ETDEWEB)

Xu Shengyuan [Department of Automation, Nanjing University of Science and Technology, Nanjing 210094 (China)]. E-mail: syxu02@yahoo.com.cn; Chu Yuming [Department of Mathematics, Huzhou Teacher' s College, Huzhou, Zhejiang 313000 (China); Lu Junwei [School of Electrical and Automation Engineering, Nanjing Normal University, 78 Bancang Street, Nanjing, 210042 (China)

2006-04-03

This Letter provides new sufficient conditions for the existence, uniqueness and global exponential stability of the equilibrium point of recurrent neural networks with time-varying delays by employing Lyapunov functions and using the Halanay inequality. The time-varying delays are not necessarily differentiable. Both Lipschitz continuous activation functions and monotone nondecreasing activation functions are considered. The derived stability criteria are expressed in terms of linear matrix inequalities (LMIs), which can be checked easily by resorting to recently developed algorithms solving LMIs. Furthermore, the proposed stability results are less conservative than some previous ones in the literature, which is demonstrated via some numerical examples.

Quantum theory for magnons and phonons interactions under time-varying magnetic fields

International Nuclear Information System (INIS)

Guerreiro, S.C.

1971-01-01

The magnon-fonon interaction in a ferromagnetic material submited to a time-varying magnetic field is studied by quantum methods. This problem has already been solved by semi-classical methods, and one of its results is that under certain conditions a state of lattice vibrations may be completely converted into spin oscillations. The main proporties of magnetoelastic waves in static magnetic fields and extend the quantum treatment for the time varying magnetic field case is revised. Field operators whose equations of motion are analogous to the classical ones are introduced. Their equations, which appear as a linear system of first order coupled equations, are converted into equations for complex functions by an expansion of the field operators in a time t as linear combinations of the same operators in a time t 0 prior to the variation of the magnetic field. The quantity g vector obtained from the classical solution is quantized and shown to be the linear momentum density of the magnetoelastic system, the quantum field spin density operator is deduced for the two interacting fields, and finally the results are used to study the magnetization and lattice displacement vector fields in the case of a system described by a coherent state of one of its normal modes

An estimation of U.S. gasoline demand. A smooth time-varying cointegration approach

International Nuclear Information System (INIS)

Park, Sung Y.; Zhao, Guochang

2010-01-01

In this paper the U.S. gasoline demand from 1976 to 2008 is estimated using a time-varying cointegrating regression. We find that price elasticity increased rapidly during the late 1970s and then decreased until 1987. After a relatively small-scaled 'increase-decrease' cycle from 1987 to 2000, the price elasticity rose again after 2000. The time-varying change of the elasticities may be explained by the proportion of gasoline consumption to income and fluctuation of the degree of necessity. The result of the error correction model shows that a deviation from a long-run equilibrium is corrected quickly, and the welfare analysis illustrates there may be a gain by shifting the tax scheme from income tax to gasoline tax. (author)

An estimation of U.S. gasoline demand. A smooth time-varying cointegration approach

Energy Technology Data Exchange (ETDEWEB)

Park, Sung Y. [Department of Economics, University of Illinois, Urbana, IL 61801 (United States); The Wang Yanan Institute for Studies in Economics, Xiamen University, Xiamen, Fujian 361005 (China); Zhao, Guochang [Research School of Economics, College of Business and Economics, The Australian National University, Canberra, ACT 2601 (Australia)

2010-01-15

In this paper the U.S. gasoline demand from 1976 to 2008 is estimated using a time-varying cointegrating regression. We find that price elasticity increased rapidly during the late 1970s and then decreased until 1987. After a relatively small-scaled 'increase-decrease' cycle from 1987 to 2000, the price elasticity rose again after 2000. The time-varying change of the elasticities may be explained by the proportion of gasoline consumption to income and fluctuation of the degree of necessity. The result of the error correction model shows that a deviation from a long-run equilibrium is corrected quickly, and the welfare analysis illustrates there may be a gain by shifting the tax scheme from income tax to gasoline tax. (author)

The biennial life strategy in a random environment

NARCIS (Netherlands)

Roerdink, J.B.T.M.

1988-01-01

A discrete-time population model with two age classes is studied which describes the growth of biennial plants in a randomly varying environment. A fraction of the oldest age class delays its flowering each year. The solution of the model involves products of random matrices. We calculate the exact

Time-frequency analysis of time-varying modulated signals based on improved energy separation by iterative generalized demodulation

Science.gov (United States)

Feng, Zhipeng; Chu, Fulei; Zuo, Ming J.

2011-03-01

Energy separation algorithm is good at tracking instantaneous changes in frequency and amplitude of modulated signals, but it is subject to the constraints of mono-component and narrow band. In most cases, time-varying modulated vibration signals of machinery consist of multiple components, and have so complicated instantaneous frequency trajectories on time-frequency plane that they overlap in frequency domain. For such signals, conventional filters fail to obtain mono-components of narrow band, and their rectangular decomposition of time-frequency plane may split instantaneous frequency trajectories thus resulting in information loss. Regarding the advantage of generalized demodulation method in decomposing multi-component signals into mono-components, an iterative generalized demodulation method is used as a preprocessing tool to separate signals into mono-components, so as to satisfy the requirements by energy separation algorithm. By this improvement, energy separation algorithm can be generalized to a broad range of signals, as long as the instantaneous frequency trajectories of signal components do not intersect on time-frequency plane. Due to the good adaptability of energy separation algorithm to instantaneous changes in signals and the mono-component decomposition nature of generalized demodulation, the derived time-frequency energy distribution has fine resolution and is free from cross term interferences. The good performance of the proposed time-frequency analysis is illustrated by analyses of a simulated signal and the on-site recorded nonstationary vibration signal of a hydroturbine rotor during a shut-down transient process, showing that it has potential to analyze time-varying modulated signals of multi-components.

Resonant e+e- production by time-varying electromagnetic field

International Nuclear Information System (INIS)

Farakos, K.; Koutsoumbas, G.; Tiktopoulos, G.

1990-01-01

As pointed out by Cornwall and Tiktopoulos (CT) strong, time-varying electric fields may produce e + e - pairs in a resonant fashion. This effect could be related to the sharp peaks in the e + e - spectrum observed in the GSI heavy-ion collision experiments. We attempt to go beyond the case of spatially uniform fields discussed by CT. We find that resonant e + e - production indeed takes place for electric fields derived from four-potentials of the form A 1 =A 2 =A 0 =0, A 3 =δ(t)b(x 3 ) provided by b(x) has discontinuities with a jump at least equal to π. (orig.)

Time-Varying Distortions of Binaural Information by Bilateral Hearing Aids

Science.gov (United States)

Rodriguez, Francisco A.; Portnuff, Cory D. F.; Goupell, Matthew J.; Tollin, Daniel J.

2016-01-01

In patients with bilateral hearing loss, the use of two hearing aids (HAs) offers the potential to restore the benefits of binaural hearing, including sound source localization and segregation. However, existing evidence suggests that bilateral HA users’ access to binaural information, namely interaural time and level differences (ITDs and ILDs), can be compromised by device processing. Our objective was to characterize the nature and magnitude of binaural distortions caused by modern digital behind-the-ear HAs using a variety of stimuli and HA program settings. Of particular interest was a common frequency-lowering algorithm known as nonlinear frequency compression, which has not previously been assessed for its effects on binaural information. A binaural beamforming algorithm was also assessed. Wide dynamic range compression was enabled in all programs. HAs were placed on a binaural manikin, and stimuli were presented from an arc of loudspeakers inside an anechoic chamber. Stimuli were broadband noise bursts, 10-Hz sinusoidally amplitude-modulated noise bursts, or consonant–vowel–consonant speech tokens. Binaural information was analyzed in terms of ITDs, ILDs, and interaural coherence, both for whole stimuli and in a time-varying sense (i.e., within a running temporal window) across four different frequency bands (1, 2, 4, and 6 kHz). Key findings were: (a) Nonlinear frequency compression caused distortions of high-frequency envelope ITDs and significantly reduced interaural coherence. (b) For modulated stimuli, all programs caused time-varying distortion of ILDs. (c) HAs altered the relationship between ITDs and ILDs, introducing large ITD–ILD conflicts in some cases. Potential perceptual consequences of measured distortions are discussed. PMID:27698258

Stagewise pseudo-value regression for time-varying effects on the cumulative incidence

DEFF Research Database (Denmark)

Zöller, Daniela; Schmidtmann, Irene; Weinmann, Arndt

2016-01-01

In a competing risks setting, the cumulative incidence of an event of interest describes the absolute risk for this event as a function of time. For regression analysis, one can either choose to model all competing events by separate cause-specific hazard models or directly model the association...... for time-varying effects. This is implemented by coupling variable selection between the grid times, but determining estimates separately. The effect estimates are regularized to also allow for model fitting with a low to moderate number of observations. This technique is illustrated in an application...

Linking the fractional derivative and the Lomnitz creep law to non-Newtonian time-varying viscosity

Science.gov (United States)

Pandey, Vikash; Holm, Sverre

2016-09-01

Many of the most interesting complex media are non-Newtonian and exhibit time-dependent behavior of thixotropy and rheopecty. They may also have temporal responses described by power laws. The material behavior is represented by the relaxation modulus and the creep compliance. On the one hand, it is shown that in the special case of a Maxwell model characterized by a linearly time-varying viscosity, the medium's relaxation modulus is a power law which is similar to that of a fractional derivative element often called a springpot. On the other hand, the creep compliance of the time-varying Maxwell model is identified as Lomnitz's logarithmic creep law, making this possibly its first direct derivation. In this way both fractional derivatives and Lomnitz's creep law are linked to time-varying viscosity. A mechanism which yields fractional viscoelasticity and logarithmic creep behavior has therefore been found. Further, as a result of this linking, the curve-fitting parameters involved in the fractional viscoelastic modeling, and the Lomnitz law gain physical interpretation.

Pollinator effectiveness varies with experimental shifts in flowering time.

Science.gov (United States)

Rafferty, Nicole E; Ives, Anthony R

2012-04-01

The earlier flowering times exhibited by many plant species are a conspicuous sign of climate change. Altered phenologies have caused concern that species could suffer population declines if they flower at times when effective pollinators are unavailable. For two perennial wildflowers, Tradescantia ohiensis and Asclepias incarnata, we used an experimental approach to explore how changing phenology affects the taxonomic composition of the pollinator assemblage and the effectiveness of individual pollinator taxa. After finding in the previous year that fruit set varied with flowering time, we manipulated flowering onset in greenhouses, placed plants in the field over the span of five weeks, and measured pollinator effectiveness as the number of seeds produced after a single visit to a flower. The average effectiveness of pollinators and the expected rates of pollination success were lower for plants of both species flowering earlier than for plants flowering at historical times, suggesting there could be reproductive costs to earlier flowering. Whereas for A. incarnata, differences in average seed set among weeks were due primarily to changes in the composition of the pollinator assemblage, the differences for T. ohiensis were driven by the combined effects of compositional changes and increases over time in the effectiveness of some pollinator taxa. Both species face the possibility of temporal mismatch between the availability of the most effective pollinators and the onset of flowering, and changes in the effectiveness of individual pollinator taxa through time may add an unexpected element to the reproductive consequences of such mismatches.

Memory for Random Time Patterns in Audition, Touch, and Vision.

Science.gov (United States)

Kang, HiJee; Lancelin, Denis; Pressnitzer, Daniel

2018-03-22

Perception deals with temporal sequences of events, like series of phonemes for audition, dynamic changes in pressure for touch textures, or moving objects for vision. Memory processes are thus needed to make sense of the temporal patterning of sensory information. Recently, we have shown that auditory temporal patterns could be learned rapidly and incidentally with repeated exposure [Kang et al., 2017]. Here, we tested whether rapid incidental learning of temporal patterns was specific to audition, or if it was a more general property of sensory systems. We used a same behavioral task in three modalities: audition, touch, and vision, for stimuli having identical temporal statistics. Participants were presented with sequences of acoustic pulses for audition, motion pulses to the fingertips for touch, or light pulses for vision. Pulses were randomly and irregularly spaced, with all inter-pulse intervals in the sub-second range and all constrained to be longer than the temporal acuity in any modality. This led to pulse sequences with an average inter-pulse interval of 166 ms, a minimum inter-pulse interval of 60 ms, and a total duration of 1.2 s. Results showed that, if a random temporal pattern re-occurred at random times during an experimental block, it was rapidly learned, whatever the sensory modality. Moreover, patterns first learned in the auditory modality displayed transfer of learning to either touch or vision. This suggests that sensory systems may be exquisitely tuned to incidentally learn re-occurring temporal patterns, with possible cross-talk between the senses. Copyright © 2018 IBRO. Published by Elsevier Ltd. All rights reserved.

Some Limit Properties of Random Transition Probability for Second-Order Nonhomogeneous Markov Chains Indexed by a Tree

Directory of Open Access Journals (Sweden)

Shi Zhiyan

2009-01-01

Full Text Available We study some limit properties of the harmonic mean of random transition probability for a second-order nonhomogeneous Markov chain and a nonhomogeneous Markov chain indexed by a tree. As corollary, we obtain the property of the harmonic mean of random transition probability for a nonhomogeneous Markov chain.

Computational micromagnetics: prediction of time dependent and thermal properties

International Nuclear Information System (INIS)

Schrefl, T.; Scholz, W.; Suess, Dieter; Fidler, J.

2001-01-01

Finite element modeling treats magnetization processes on a length scale of several nanometers and thus gives a quantitative correlation between the microstructure and the magnetic properties of ferromagnetic materials. This work presents a novel finite element/boundary element micro-magnetics solver that combines a wavelet-based matrix compression technique for magnetostatic field calculations with a BDF/GMRES method for the time integration of the Gilbert equation of motion. The simulations show that metastable energy minima and nonuniform magnetic states within the grains are important factors in the reversal dynamics at finite temperature. The numerical solution of the Gilbert equation shows how reversed domains nucleate and expand. The switching time of submicron magnetic elements depends on the shape of the elements. Elements with slanted ends decrease the overall reversal time, as a transverse demagnetizing field suppresses oscillations of the magnetization. Thermal activated processes can be included adding a random thermal field to the effective magnetic field. Thermally assisted reversal was studied for CoCrPtTa thin-film media

Combined risk assessment of nonstationary monthly water quality based on Markov chain and time-varying copula.

Science.gov (United States)

Shi, Wei; Xia, Jun

2017-02-01

Water quality risk management is a global hot research linkage with the sustainable water resource development. Ammonium nitrogen (NH 3 -N) and permanganate index (COD Mn ) as the focus indicators in Huai River Basin, are selected to reveal their joint transition laws based on Markov theory. The time-varying moments model with either time or land cover index as explanatory variables is applied to build the time-varying marginal distributions of water quality time series. Time-varying copula model, which takes the non-stationarity in the marginal distribution and/or the time variation in dependence structure between water quality series into consideration, is constructed to describe a bivariate frequency analysis for NH 3 -N and COD Mn series at the same monitoring gauge. The larger first-order Markov joint transition probability indicates water quality state Class V w , Class IV and Class III will occur easily in the water body of Bengbu Sluice. Both marginal distribution and copula models are nonstationary, and the explanatory variable time yields better performance than land cover index in describing the non-stationarities in the marginal distributions. In modelling the dependence structure changes, time-varying copula has a better fitting performance than the copula with the constant or the time-trend dependence parameter. The largest synchronous encounter risk probability of NH 3 -N and COD Mn simultaneously reaching Class V is 50.61%, while the asynchronous encounter risk probability is largest when NH 3 -N and COD Mn is inferior to class V and class IV water quality standards, respectively.

Multifractal properties of diffusion-limited aggregates and random multiplicative processes

International Nuclear Information System (INIS)

Canessa, E.

1991-04-01

We consider the multifractal properties of irreversible diffusion-limited aggregation (DLA) from the point of view of the self-similarity of fluctuations in random multiplicative processes. In particular we analyse the breakdown of multifractal behaviour and phase transition associated with the negative moments of the growth probabilities in DLA. (author). 20 refs, 5 figs

Computing and visualizing time-varying merge trees for high-dimensional data

Energy Technology Data Exchange (ETDEWEB)

Oesterling, Patrick [Univ. of Leipzig (Germany); Heine, Christian [Univ. of Kaiserslautern (Germany); Weber, Gunther H. [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Morozov, Dmitry [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Scheuermann, Gerik [Univ. of Leipzig (Germany)

2017-06-03

We introduce a new method that identifies and tracks features in arbitrary dimensions using the merge tree -- a structure for identifying topological features based on thresholding in scalar fields. This method analyzes the evolution of features of the function by tracking changes in the merge tree and relates features by matching subtrees between consecutive time steps. Using the time-varying merge tree, we present a structural visualization of the changing function that illustrates both features and their temporal evolution. We demonstrate the utility of our approach by applying it to temporal cluster analysis of high-dimensional point clouds.

Effect of ball milling time on thermoelectric properties of bismuth telluride nanomaterials

Science.gov (United States)

Khade, Poonam; Bagwaiya, Toshi; Bhattacharaya, Shovit; Singh, Ajay; Jha, Purushottam; Shelke, Vilas

2018-04-01

The effect of different milling time on thermoelectric properties of bismuth telluride (Bi2Te3) was investigated. The nanomaterial was prepared by varying the ball milling time and followed by hot press sintering. The crystal structure and phase formation were verified by X-ray diffraction and Raman Spectroscopy. The experimental results show that electrical conductivity increases whereas thermal conductivity decreases with increasing milling time. The negative sign of seebeck coefficient indicate the n-type nature with majority charge carriers of electrons. A maximum figure of merit about 0.55 is achieved for l5hr ball milled Bi2Te3 sample. The present study demonstrates the simple and cost-effective method for synthesis of Bi2Te3 thermoelectric material at large scale thermoelectric applications.

Augmented brain function by coordinated reset stimulation with slowly varying sequences

Directory of Open Access Journals (Sweden)

Magteld eZeitler

2015-03-01

Full Text Available Several brain disorders are characterized by abnormally strong neuronal synchrony. Coordinated Reset (CR stimulation was developed to selectively counteract abnormal neuronal synchrony by desynchronization. For this, phase resetting stimuli are delivered to different subpopulations in a timely coordinated way. In neural networks with spike timing-dependent plasticity CR stimulation may eventually lead to an anti-kindling, i.e. an unlearning of abnormal synaptic connectivity and abnormal synchrony. The spatiotemporal sequence by which all stimulation sites are stimulated exactly once is called the stimulation site sequence, or briefly sequence. So far, in simulations, pre-clinical and clinical applications CR was applied either with fixed sequences or rapidly varying sequences (RVS. In this computational study we show that appropriate repetition of the sequence with occasional random switching to the next sequence may significantly improve the anti-kindling effect of CR. To this end, a sequence is applied many times before randomly switching to the next sequence. This new method is called SVS CR stimulation, i.e. CR with slowly varying sequences. In a neuronal network with strong short-range excitatory and weak long-range inhibitory dynamic couplings SVS CR stimulation turns out to be superior to CR stimulation with fixed sequences or RVS.

Augmented brain function by coordinated reset stimulation with slowly varying sequences.

Science.gov (United States)

Zeitler, Magteld; Tass, Peter A

2015-01-01

Several brain disorders are characterized by abnormally strong neuronal synchrony. Coordinated Reset (CR) stimulation was developed to selectively counteract abnormal neuronal synchrony by desynchronization. For this, phase resetting stimuli are delivered to different subpopulations in a timely coordinated way. In neural networks with spike timing-dependent plasticity CR stimulation may eventually lead to an anti-kindling, i.e., an unlearning of abnormal synaptic connectivity and abnormal synchrony. The spatiotemporal sequence by which all stimulation sites are stimulated exactly once is called the stimulation site sequence, or briefly sequence. So far, in simulations, pre-clinical and clinical applications CR was applied either with fixed sequences or rapidly varying sequences (RVS). In this computational study we show that appropriate repetition of the sequence with occasional random switching to the next sequence may significantly improve the anti-kindling effect of CR. To this end, a sequence is applied many times before randomly switching to the next sequence. This new method is called SVS CR stimulation, i.e., CR with slowly varying sequences. In a neuronal network with strong short-range excitatory and weak long-range inhibitory dynamic couplings SVS CR stimulation turns out to be superior to CR stimulation with fixed sequences or RVS.

COMPARATIVE STUDY OF THE EFFECTS OF DETONATION NANODIAMONDS WITH VARIED PROPERTIES ON FUNCTIONAL STATE OF BRAIN NERVE TERMINALS

Directory of Open Access Journals (Sweden)

M. A. Galkin

2016-12-01

Full Text Available The aim of the study was to compare the effects of detonation nanodiamond preparations from different batches cleaned from impurities by diverse methods of chemical treatment on the membrane potential and glutamate transport characteristics of rat brain nerve terminals. The size of nanodiamond particles vary from 10–20 nm to 10 μm. There are carbonyl, hydroxyl and carboxyl functional groups on the surface of the particles. Physical-chemical properties such as a magnetic susceptibility and the amount of incombustible residue in samples of detonation nanodia-mond vary depending on the synthesis regime and the method of chemical cleaning of the product and therefore, the neuroactive properties of nanodiamonds from different batches can be different. It was shown by dynamic light scattering analysis that nanodiamond preparations from different batches treated by diverse technologies of chemical treatment had varied average size of particles and distribution of particles by size. Nanodiamond preparations from different batches changed the plasma membrane potential and caused membrane depolarization of nerve terminals. Analysis of the effects of nanodiamonds on transporter-mediated L-[14C]glutamate uptake by nerve terminals also revealed that all studied nanodiamond preparations decreased abovementioned parameter. Therefore, detonation nanodiamonds from different batches have similar principal effects on functional state of nerve terminals, however variability in their physical and chemical properties is associated with diverse strength of these effects.

Exponential networked synchronization of master-slave chaotic systems with time-varying communication topologies

International Nuclear Information System (INIS)

Yang Dong-Sheng; Liu Zhen-Wei; Liu Zhao-Bing; Zhao Yan

2012-01-01

The networked synchronization problem of a class of master-slave chaotic systems with time-varying communication topologies is investigated in this paper. Based on algebraic graph theory and matrix theory, a simple linear state feedback controller is designed to synchronize the master chaotic system and the slave chaotic systems with a time-varying communication topology connection. The exponential stability of the closed-loop networked synchronization error system is guaranteed by applying Lyapunov stability theory. The derived novel criteria are in the form of linear matrix inequalities (LMIs), which are easy to examine and tremendously reduce the computation burden from the feedback matrices. This paper provides an alternative networked secure communication scheme which can be extended conveniently. An illustrative example is given to demonstrate the effectiveness of the proposed networked synchronization method. (general)

Thermodynamical properties of random spin-1/2 XY chain with Dzyaloshinskii-Moriya interaction

International Nuclear Information System (INIS)

Derzhko, O.; Krokhmalskii, T.; Verkholyak, T.

1995-07-01

For computation of the equilibrium statistical properties of finite spin-1/2 XY chains with Dzyaloshinskii-Moriya interaction the suggested earlier approach (JMMM 140-144 (1995) 1623) is generalized. It is applied for calculation of transverse dynamical susceptibility of spin-1/2 Ising chain in non-random and random Gaussian transverse field with Dzyaloshinskii-Moriya interaction. (author). 7 refs, 2 figs

Genealogical Properties of Subsamples in Highly Fecund Populations

Science.gov (United States)

Eldon, Bjarki; Freund, Fabian

2018-03-01

We consider some genealogical properties of nested samples. The complete sample is assumed to have been drawn from a natural population characterised by high fecundity and sweepstakes reproduction (abbreviated HFSR). The random gene genealogies of the samples are—due to our assumption of HFSR—modelled by coalescent processes which admit multiple mergers of ancestral lineages looking back in time. Among the genealogical properties we consider are the probability that the most recent common ancestor is shared between the complete sample and the subsample nested within the complete sample; we also compare the lengths of `internal' branches of nested genealogies between different coalescent processes. The results indicate how `informative' a subsample is about the properties of the larger complete sample, how much information is gained by increasing the sample size, and how the `informativeness' of the subsample varies between different coalescent processes.

Mechanical properties of short random oil palm fibre reinforced epoxy composites

International Nuclear Information System (INIS)

Mohd Zuhri Mohamed Yusoff; Mohd Sapuan Salit; Napsiah Ismail; Riza Wirawan

2010-01-01

This paper presents the study of mechanical properties of short random oil palm fibre reinforced epoxy (OPF/epoxy) composites. Empty fruit bunch (EFB) was selected as the fibre and epoxy as the matrix. Composite plate with four different volume fractions of oil palm fibre was fabricated, (5 vol %, 10 vol %, 15 vol % and 20 vol %). The fabrication was made by hand-lay up techniques. The tensile and flexural properties showed a decreasing trend as the fibre loading was increased. The highest tensile properties was obtained for the composite with fibre loading of 5 vol % and there were no significant effect for addition of more than 5 vol % to the flexural properties. Interaction between fibre and matrix was observed from the scanning electron microscope (SEM) micrograph. (author)

Percepts, not acoustic properties, are the units of auditory short-term memory.

Science.gov (United States)

Mathias, Samuel R; von Kriegstein, Katharina

2014-04-01

For decades, researchers have sought to understand the organizing principles of auditory and visual short-term memory (STM). Previous work in audition has suggested that there are independent memory stores for different sound features, but the nature of the representations retained within these stores is currently unclear. Do they retain perceptual features, or do they instead retain representations of the sound's specific acoustic properties? In the present study we addressed this question by measuring listeners' abilities to keep one of three acoustic properties (interaural time difference [ITD], interaural level difference [ILD], or frequency) in memory when the target sound was followed by interfering sounds that varied randomly in one of the same properties. Critically, ITD and ILD evoked the same percept (spatial location), despite being acoustically different and having different physiological correlates, whereas frequency evoked a different percept (pitch). The results showed that listeners found it difficult to remember the percept of spatial location when the interfering tones varied either in ITD or ILD, but not when they varied in frequency. The study demonstrates that percepts are the units of auditory STM, and provides testable predictions for future neuroscientific work on both auditory and visual STM.

Bank loan components and the time-varying effects of monetary policy shocks

NARCIS (Netherlands)

den Haan, W.J.; Sumner, S.W.; Yamashiro, G.M.

2011-01-01

The impulse response function (IRF) of an aggregate variable is time-varying if the IRFs of its components are different from each other and the relative magnitudes of the components are not constant—two conditions likely to be true in practice. We model the behaviour of loan components and document

Improved Criteria on Delay-Dependent Stability for Discrete-Time Neural Networks with Interval Time-Varying Delays

Directory of Open Access Journals (Sweden)

O. M. Kwon

2012-01-01

Full Text Available The purpose of this paper is to investigate the delay-dependent stability analysis for discrete-time neural networks with interval time-varying delays. Based on Lyapunov method, improved delay-dependent criteria for the stability of the networks are derived in terms of linear matrix inequalities (LMIs by constructing a suitable Lyapunov-Krasovskii functional and utilizing reciprocally convex approach. Also, a new activation condition which has not been considered in the literature is proposed and utilized for derivation of stability criteria. Two numerical examples are given to illustrate the effectiveness of the proposed method.

Visualizing Time-Varying Distribution Data in EOS Application

Science.gov (United States)

Shen, Han-Wei

2004-01-01

In this research, we have developed several novel visualization methods for spatial probability density function data. Our focus has been on 2D spatial datasets, where each pixel is a random variable, and has multiple samples which are the results of experiments on that random variable. We developed novel clustering algorithms as a means to reduce the information contained in these datasets; and investigated different ways of interpreting and clustering the data.

Output-Only Modal Parameter Recursive Estimation of Time-Varying Structures via a Kernel Ridge Regression FS-TARMA Approach

Directory of Open Access Journals (Sweden)

Zhi-Sai Ma

2017-01-01

Full Text Available Modal parameter estimation plays an important role in vibration-based damage detection and is worth more attention and investigation, as changes in modal parameters are usually being used as damage indicators. This paper focuses on the problem of output-only modal parameter recursive estimation of time-varying structures based upon parameterized representations of the time-dependent autoregressive moving average (TARMA. A kernel ridge regression functional series TARMA (FS-TARMA recursive identification scheme is proposed and subsequently employed for the modal parameter estimation of a numerical three-degree-of-freedom time-varying structural system and a laboratory time-varying structure consisting of a simply supported beam and a moving mass sliding on it. The proposed method is comparatively assessed against an existing recursive pseudolinear regression FS-TARMA approach via Monte Carlo experiments and shown to be capable of accurately tracking the time-varying dynamics in a recursive manner.

Time-Varying Market Integration and Expected Returns in Emerging Markets

OpenAIRE

de Jong, Frank; de Roon, Frans

2001-01-01

We use a simple model in which the expected returns in emerging markets depend on their systematic risk as measured by their beta relative to the world portfolio as well as on the level of integration in that market. The level of integration is a time-varying variable that depends on the market value of the assets that can be held by domestic investors only versus the market value of the assets that can be traded freely. Our empirical analysis for 30 emerging markets shows that there are stro...

Time Varying Market Integration and Expected Rteurns in Emerging Markets

OpenAIRE

Jong, F.C.J.M. de; Roon, F.A. de

2001-01-01

We use a simple model in which the expected returns in emerging markets depend on their systematic risk as measured by their beta relative to the world portfolio as well as on the level of integration in that market.The level of integration is a time-varying variable that depends on the market value of the assets that can be held by domestic investors only versus the market value of the assets that can be traded freely.Our empirical analysis for 30 emerging markets shows that there are strong...

Projective synchronization of time-varying delayed neural network with adaptive scaling factors

International Nuclear Information System (INIS)

Ghosh, Dibakar; Banerjee, Santo

2013-01-01

Highlights: • Projective synchronization in coupled delayed neural chaotic systems with modulated delay time is introduced. • An adaptive rule for the scaling factors is introduced. • This scheme is highly applicable in secure communication. -- Abstract: In this work, the projective synchronization between two continuous time delayed neural systems with time varying delay is investigated. A sufficient condition for synchronization for the coupled systems with modulated delay is presented analytically with the help of the Krasovskii–Lyapunov approach. The effect of adaptive scaling factors on synchronization are also studied in details. Numerical simulations verify the effectiveness of the analytic results

Robust convergence of Cohen-Grossberg neural networks with time-varying delays

International Nuclear Information System (INIS)

Xiong Wenjun; Ma Deyi; Liang Jinling

2009-01-01

In this paper, robust convergence is studied for the Cohen-Grossberg neural networks (CGNNs) with time-varying delays. By applying the differential inequality and the Lyapunov method, some delay-independent conditions are derived ensuring the robust CGNNs to converge, globally, uniformly and exponentially, to a ball in the state space with a pre-specified convergence rate. Finally, the effectiveness of our results are verified by an illustrative example.

Specification and testing of Multiplicative Time-Varying GARCH models with applications

DEFF Research Database (Denmark)

Amado, Cristina; Teräsvirta, Timo

2017-01-01

In this article, we develop a specification technique for building multiplicative time-varying GARCH models of Amado and Teräsvirta (2008, 2013). The variance is decomposed into an unconditional and a conditional component such that the unconditional variance component is allowed to evolve smooth...... is illustrated in practice with two real examples: an empirical application to daily exchange rate returns and another one to daily coffee futures returns....

The MIXMAX random number generator

Science.gov (United States)

Savvidy, Konstantin G.

2015-11-01

In this paper, we study the randomness properties of unimodular matrix random number generators. Under well-known conditions, these discrete-time dynamical systems have the highly desirable K-mixing properties which guarantee high quality random numbers. It is found that some widely used random number generators have poor Kolmogorov entropy and consequently fail in empirical tests of randomness. These tests show that the lowest acceptable value of the Kolmogorov entropy is around 50. Next, we provide a solution to the problem of determining the maximal period of unimodular matrix generators of pseudo-random numbers. We formulate the necessary and sufficient condition to attain the maximum period and present a family of specific generators in the MIXMAX family with superior performance and excellent statistical properties. Finally, we construct three efficient algorithms for operations with the MIXMAX matrix which is a multi-dimensional generalization of the famous cat-map. First, allowing to compute the multiplication by the MIXMAX matrix with O(N) operations. Second, to recursively compute its characteristic polynomial with O(N2) operations, and third, to apply skips of large number of steps S to the sequence in O(N2 log(S)) operations.

Adenosine diphosphate-decorated chitosan nanoparticles shorten blood clotting times, influencing the structures and varying the mechanical properties of the clots

Directory of Open Access Journals (Sweden)

Chung TW

2014-03-01

Full Text Available Tze-Wen Chung,1,3 Pei-Yi Lin,2 Shoei-Shen Wang,2 Yen-Fung Chen31Department of Biomedical Engineering, National Yang-Ming University, 2Department of Surgery, National Taiwan University Hospital, Taipei, Taiwan, Republic of China; 3Department of Chemical and Materials Engineering, National Yunlin University of Science and Technology, Yunlin, Taiwan, Republic of ChinaAbstract: Chitosan nanoparticles (NPs decorated with adenosine diphosphate (ADP (ANPs or fibrinogen (FNPs were used to fabricate hemostatic NPs that can shorten blood clotting time and prevent severe local hemorrhage. The structure and mechanical properties of the blood clot induced with ANP (clot/ANP or FNP (clot/FNP were also investigated. The NPs, ANPs, and FNPs, which had particle sizes of 245.1±14.0, 251.0±9.8, and 326.5±14.5 nm and zeta potentials of 24.1±0.5, 20.6±1.9, and 15.3±1.5 mV (n=4, respectively, were fabricated by ionic gelation and then decorated with ADP and fibrinogen. The zeta potentials and Fourier transform infrared (FTIR spectroscopy of the NPs confirmed that their surfaces were successfully coated with ADP and fibrinogen. The scanning electron microscope (SEM micrographs of the structure of the clot induced with "undecorated" chitosan NPs (clot/NP, clot/ANP, and clot/FNP (at 0.05 wt% were different, after citrated bloods had been recalcified by a calcium chloride solution containing NPs, ANPs, or FNPs. This indicated that many NPs adhered on the membrane surfaces of red blood cells, that ANPs induced many platelet aggregates, and that FNPs were incorporated into the fibrin network in the clots. Measurements of the blood clotting times (Tc of blood clot/NPs, clot/ANPs, and clot/FNPs, based on 90% of ultimate frequency shifts measured on a quartz crystal microbalance (QCM, were significantly (P<0.05 (n=4 shorter than that of a clot induced by a phosphate-buffered solution (PBS (clot/PBS (63.6%±3.1%, 48.3%±6.2%, and 63.2%±4.7%, respectively. The ∆F2

Bounds and asymptotics for orthogonal polynomials for varying weights

CERN Document Server

Levin, Eli

2018-01-01

This book establishes bounds and asymptotics under almost minimal conditions on the varying weights, and applies them to universality limits and entropy integrals.  Orthogonal polynomials associated with varying weights play a key role in analyzing random matrices and other topics.  This book will be of use to a wide community of mathematicians, physicists, and statisticians dealing with techniques of potential theory, orthogonal polynomials, approximation theory, as well as random matrices. .

Random walk-percolation-based modeling of two-phase flow in porous media: Breakthrough time and net to gross ratio estimation

Science.gov (United States)

Ganjeh-Ghazvini, Mostafa; Masihi, Mohsen; Ghaedi, Mojtaba

2014-07-01

Fluid flow modeling in porous media has many applications in waste treatment, hydrology and petroleum engineering. In any geological model, flow behavior is controlled by multiple properties. These properties must be known in advance of common flow simulations. When uncertainties are present, deterministic modeling often produces poor results. Percolation and Random Walk (RW) methods have recently been used in flow modeling. Their stochastic basis is useful in dealing with uncertainty problems. They are also useful in finding the relationship between porous media descriptions and flow behavior. This paper employs a simple methodology based on random walk and percolation techniques. The method is applied to a well-defined model reservoir in which the breakthrough time distributions are estimated. The results of this method and the conventional simulation are then compared. The effect of the net to gross ratio on the breakthrough time distribution is studied in terms of Shannon entropy. Use of the entropy plot allows one to assign the appropriate net to gross ratio to any porous medium.

Response of stiff piles to random two-way lateral loading

DEFF Research Database (Denmark)

Bakmar, Christian LeBlanc; Byrne, B.W.; Houlsby, G. T.

2010-01-01

A model for predicting the accumulated rotation of stiff piles under random two-way loading is presented. The model is based on a strain superposition rule similar to Miner's rule and uses rainflow-counting to decompose a random time-series of varying loads into a set of simple load reversals. Th....... The method is consistent with the work of LeBlanc et al. (2010) and is supported by 1g laboratory tests. An example is given for an offshore wind turbine indicating that accumulated pile rotation during the life of the turbine is dominated by the worst expected load.......A model for predicting the accumulated rotation of stiff piles under random two-way loading is presented. The model is based on a strain superposition rule similar to Miner's rule and uses rainflow-counting to decompose a random time-series of varying loads into a set of simple load reversals...

Distributed Event-Triggered Control of Multiagent Systems with Time-Varying Topology

Directory of Open Access Journals (Sweden)

Jingwei Ma

2014-01-01

Full Text Available This paper studies the consensus of first-order discrete-time multiagent systems, where the interaction topology is time-varying. The event-triggered control is used to update the control input of each agent, and the event-triggering condition is designed based on the combination of the relative states of each agent to its neighbors. By applying the common Lyapunov function method, a sufficient condition for consensus, which is expressed as a group of linear matrix inequalities, is obtained and the feasibility of these linear matrix inequalities is further analyzed. Simulation examples are provided to explain the effectiveness of the theoretical results.

Solution to the monoenergetic time-dependent neutron transport equation with a time-varying source

International Nuclear Information System (INIS)

Ganapol, B.D.

1986-01-01

Even though fundamental time-dependent neutron transport problems have existed since the inception of neutron transport theory, it has only been recently that a reliable numerical solution to one of the basic problems has been obtained. Experience in generating numerical solutions to time-dependent transport equations has indicated that the multiple collision formulation is the most versatile numerical technique for model problems. The formulation coupled with a moment reconstruction of each collided flux component has led to benchmark-quality (four- to five-digit accuracy) numerical evaluation of the neutron flux in plane infinite geometry for any degree of scattering anisotropy and for both pulsed isotropic and beam sources. As will be shown in this presentation, this solution can serve as a Green's function, thus extending the previous results to more complicated source situations. Here we will be concerned with a time-varying source at the center of an infinite medium. If accurate, such solutions have both pedagogical and practical uses as benchmarks against which other more approximate solutions designed for a wider class of problems can be compared

Statistical properties of fluctuations of time series representing appearances of words in nationwide blog data and their applications: An example of modeling fluctuation scalings of nonstationary time series.

Science.gov (United States)

Watanabe, Hayafumi; Sano, Yukie; Takayasu, Hideki; Takayasu, Misako

2016-11-01

To elucidate the nontrivial empirical statistical properties of fluctuations of a typical nonsteady time series representing the appearance of words in blogs, we investigated approximately 3×10^{9} Japanese blog articles over a period of six years and analyze some corresponding mathematical models. First, we introduce a solvable nonsteady extension of the random diffusion model, which can be deduced by modeling the behavior of heterogeneous random bloggers. Next, we deduce theoretical expressions for both the temporal and ensemble fluctuation scalings of this model, and demonstrate that these expressions can reproduce all empirical scalings over eight orders of magnitude. Furthermore, we show that the model can reproduce other statistical properties of time series representing the appearance of words in blogs, such as functional forms of the probability density and correlations in the total number of blogs. As an application, we quantify the abnormality of special nationwide events by measuring the fluctuation scalings of 1771 basic adjectives.

Adaptive random walks on the class of Web graphs

Science.gov (United States)

Tadić, B.

2001-09-01

We study random walk with adaptive move strategies on a class of directed graphs with variable wiring diagram. The graphs are grown from the evolution rules compatible with the dynamics of the world-wide Web [B. Tadić, Physica A 293, 273 (2001)], and are characterized by a pair of power-law distributions of out- and in-degree for each value of the parameter β, which measures the degree of rewiring in the graph. The walker adapts its move strategy according to locally available information both on out-degree of the visited node and in-degree of target node. A standard random walk, on the other hand, uses the out-degree only. We compute the distribution of connected subgraphs visited by an ensemble of walkers, the average access time and survival probability of the walks. We discuss these properties of the walk dynamics relative to the changes in the global graph structure when the control parameter β is varied. For β≥ 3, corresponding to the world-wide Web, the access time of the walk to a given level of hierarchy on the graph is much shorter compared to the standard random walk on the same graph. By reducing the amount of rewiring towards rigidity limit β↦βc≲ 0.1, corresponding to the range of naturally occurring biochemical networks, the survival probability of adaptive and standard random walk become increasingly similar. The adaptive random walk can be used as an efficient message-passing algorithm on this class of graphs for large degree of rewiring.

Static transport properties of random alloys: Vertex corrections in conserving approximations

Czech Academy of Sciences Publication Activity Database

Turek, Ilja

2016-01-01

Roč. 93, č. 24 (2016), 245114-1-245114-6 ISSN 2469-9950 R&D Projects: GA ČR GA15-13436S Institutional support: RVO:68081723 Keywords : transport properties * random alloys * coherent-potential approximation Subject RIV: BM - Solid Matter Physics ; Magnetism Impact factor: 3.836, year: 2016

Scalable Video Streaming Adaptive to Time-Varying IEEE 802.11 MAC Parameters

Science.gov (United States)

Lee, Kyung-Jun; Suh, Doug-Young; Park, Gwang-Hoon; Huh, Jae-Doo

This letter proposes a QoS control method for video streaming service over wireless networks. Based on statistical analysis, the time-varying MAC parameters highly related to channel condition are selected to predict available bitrate. Adaptive bitrate control of scalably-encoded video guarantees continuity in streaming service even if the channel condition changes abruptly.

Distributed Time-Varying Formation Robust Tracking for General Linear Multiagent Systems With Parameter Uncertainties and External Disturbances.

Science.gov (United States)

Hua, Yongzhao; Dong, Xiwang; Li, Qingdong; Ren, Zhang

2017-05-18

This paper investigates the time-varying formation robust tracking problems for high-order linear multiagent systems with a leader of unknown control input in the presence of heterogeneous parameter uncertainties and external disturbances. The followers need to accomplish an expected time-varying formation in the state space and track the state trajectory produced by the leader simultaneously. First, a time-varying formation robust tracking protocol with a totally distributed form is proposed utilizing the neighborhood state information. With the adaptive updating mechanism, neither any global knowledge about the communication topology nor the upper bounds of the parameter uncertainties, external disturbances and leader's unknown input are required in the proposed protocol. Then, in order to determine the control parameters, an algorithm with four steps is presented, where feasible conditions for the followers to accomplish the expected time-varying formation tracking are provided. Furthermore, based on the Lyapunov-like analysis theory, it is proved that the formation tracking error can converge to zero asymptotically. Finally, the effectiveness of the theoretical results is verified by simulation examples.

An Exponential Tilt Mixture Model for Time-to-Event Data to Evaluate Treatment Effect Heterogeneity in Randomized Clinical Trials.

Science.gov (United States)

Wang, Chi; Tan, Zhiqiang; Louis, Thomas A

2014-01-01

Evaluating the effect of a treatment on a time-to-event outcome is the focus of many randomized clinical trials. It is often observed that the treatment effect is heterogeneous, where only a subgroup of the patients may respond to the treatment due to some unknown mechanism such as genetic polymorphism. In this paper, we propose a semiparametric exponential tilt mixture model to estimate the proportion of patients who respond to the treatment and to assess the treatment effect. Our model is a natural extension of parametric mixture models to a semiparametric setting with a time-to-event outcome. We propose a nonparametric maximum likelihood estimation approach for inference and establish related asymptotic properties. Our method is illustrated by a randomized clinical trial on biodegradable polymer-delivered chemotherapy for malignant gliomas patients.

Reusable Launch Vehicle Attitude Control Using a Time-Varying Sliding Mode Control Technique

Science.gov (United States)

Shtessel, Yuri B.; Zhu, J. Jim; Daniels, Dan; Jackson, Scott (Technical Monitor)

2002-01-01

In this paper we present a time-varying sliding mode control (TVSMC) technique for reusable launch vehicle (RLV) attitude control in ascent and entry flight phases. In ascent flight the guidance commands Euler roll, pitch and yaw angles, and in entry flight it commands the aerodynamic angles of bank, attack and sideslip. The controller employs a body rate inner loop and the attitude outer loop, which are separated in time-scale by the singular perturbation principle. The novelty of the TVSMC is that both the sliding surface and the boundary layer dynamics can be varied in real time using the PD-eigenvalue assignment technique. This salient feature is used to cope with control command saturation and integrator windup in the presence of severe disturbance or control effector failure, which enhances the robustness and fault tolerance of the controller. The TV-SMC ascent and descent designs are currently being tested with high fidelity, 6-DOF dispersion simulations. The test results will be presented in the final version of this paper.

On the Anonymity Risk of Time-Varying User Profiles

Directory of Open Access Journals (Sweden)

Silvia Puglisi

2017-04-01

Full Text Available Websites and applications use personalisation services to profile their users, collect their patterns and activities and eventually use this data to provide tailored suggestions. User preferences and social interactions are therefore aggregated and analysed. Every time a user publishes a new post or creates a link with another entity, either another user, or some online resource, new information is added to the user profile. Exposing private data does not only reveal information about single users’ preferences, increasing their privacy risk, but can expose more about their network that single actors intended. This mechanism is self-evident in social networks where users receive suggestions based on their friends’ activities. We propose an information-theoretic approach to measure the differential update of the anonymity risk of time-varying user profiles. This expresses how privacy is affected when new content is posted and how much third-party services get to know about the users when a new activity is shared. We use actual Facebook data to show how our model can be applied to a real-world scenario.

Modeling intensive longitudinal data with mixtures of nonparametric trajectories and time-varying effects.

Science.gov (United States)

Dziak, John J; Li, Runze; Tan, Xianming; Shiffman, Saul; Shiyko, Mariya P

2015-12-01

Behavioral scientists increasingly collect intensive longitudinal data (ILD), in which phenomena are measured at high frequency and in real time. In many such studies, it is of interest to describe the pattern of change over time in important variables as well as the changing nature of the relationship between variables. Individuals' trajectories on variables of interest may be far from linear, and the predictive relationship between variables of interest and related covariates may also change over time in a nonlinear way. Time-varying effect models (TVEMs; see Tan, Shiyko, Li, Li, & Dierker, 2012) address these needs by allowing regression coefficients to be smooth, nonlinear functions of time rather than constants. However, it is possible that not only observed covariates but also unknown, latent variables may be related to the outcome. That is, regression coefficients may change over time and also vary for different kinds of individuals. Therefore, we describe a finite mixture version of TVEM for situations in which the population is heterogeneous and in which a single trajectory would conceal important, interindividual differences. This extended approach, MixTVEM, combines finite mixture modeling with non- or semiparametric regression modeling, to describe a complex pattern of change over time for distinct latent classes of individuals. The usefulness of the method is demonstrated in an empirical example from a smoking cessation study. We provide a versatile SAS macro and R function for fitting MixTVEMs. (c) 2015 APA, all rights reserved).

Transport properties of a ladder with two random dimer chains

International Nuclear Information System (INIS)

Hu Dong-Sheng; Zhu Chen-Ping; Zhang Yong-Mei

2011-01-01

We investigate the transport properties of a ladder with two random dimer (RD) chains. It is found that there are two extended states in the ladder with identical RD chains and a critical state regarded as an extended state in the ladder with pairing RD chains. Such a critical state is caused by the chiral symmetry. The ladder with identical RD chains can be decoupled into two isolated RD chains and the ladder with pairing RD chains can not. The analytic expressions of the extended states are presented for the ladder with identical RD chains. (condensed matter: electronic structure, electrical, magnetic, and optical properties)

Delay-dependent exponential stability of cellular neural networks with time-varying delays

International Nuclear Information System (INIS)

Zhang Qiang; Wei Xiaopeng; Xu Jin

2005-01-01

The global exponential stability of cellular neural networks (CNNs) with time-varying delays is analyzed. Two new sufficient conditions ensuring global exponential stability for delayed CNNs are obtained. The conditions presented here are related to the size of delay. The stability results improve the earlier publications. Two examples are given to demonstrate the effectiveness of the obtained results

Pattern formation in individual-based systems with time-varying parameters

Science.gov (United States)

Ashcroft, Peter; Galla, Tobias

2013-12-01

We study the patterns generated in finite-time sweeps across symmetry-breaking bifurcations in individual-based models. Similar to the well-known Kibble-Zurek scenario of defect formation, large-scale patterns are generated when model parameters are varied slowly, whereas fast sweeps produce a large number of small domains. The symmetry breaking is triggered by intrinsic noise, originating from the discrete dynamics at the microlevel. Based on a linear-noise approximation, we calculate the characteristic length scale of these patterns. We demonstrate the applicability of this approach in a simple model of opinion dynamics, a model in evolutionary game theory with a time-dependent fitness structure, and a model of cell differentiation. Our theoretical estimates are confirmed in simulations. In further numerical work, we observe a similar phenomenon when the symmetry-breaking bifurcation is triggered by population growth.

Asymptotic distributions of coalescence times and ancestral lineage numbers for populations with temporally varying size.

Science.gov (United States)

Chen, Hua; Chen, Kun

2013-07-01

The distributions of coalescence times and ancestral lineage numbers play an essential role in coalescent modeling and ancestral inference. Both exact distributions of coalescence times and ancestral lineage numbers are expressed as the sum of alternating series, and the terms in the series become numerically intractable for large samples. More computationally attractive are their asymptotic distributions, which were derived in Griffiths (1984) for populations with constant size. In this article, we derive the asymptotic distributions of coalescence times and ancestral lineage numbers for populations with temporally varying size. For a sample of size n, denote by Tm the mth coalescent time, when m + 1 lineages coalesce into m lineages, and An(t) the number of ancestral lineages at time t back from the current generation. Similar to the results in Griffiths (1984), the number of ancestral lineages, An(t), and the coalescence times, Tm, are asymptotically normal, with the mean and variance of these distributions depending on the population size function, N(t). At the very early stage of the coalescent, when t → 0, the number of coalesced lineages n - An(t) follows a Poisson distribution, and as m → n, $$n\\left(n-1\\right){T}_{m}/2N\\left(0\\right)$$ follows a gamma distribution. We demonstrate the accuracy of the asymptotic approximations by comparing to both exact distributions and coalescent simulations. Several applications of the theoretical results are also shown: deriving statistics related to the properties of gene genealogies, such as the time to the most recent common ancestor (TMRCA) and the total branch length (TBL) of the genealogy, and deriving the allele frequency spectrum for large genealogies. With the advent of genomic-level sequencing data for large samples, the asymptotic distributions are expected to have wide applications in theoretical and methodological development for population genetic inference.

H∞ Consensus for Multiagent Systems with Heterogeneous Time-Varying Delays

Directory of Open Access Journals (Sweden)

Beibei Wang

2013-01-01

Full Text Available We apply the linear matrix inequality method to consensus and H∞ consensus problems of the single integrator multiagent system with heterogeneous delays in directed networks. To overcome the difficulty caused by heterogeneous time-varying delays, we rewrite the multiagent system into a partially reduced-order system and an integral system. As a result, a particular Lyapunov function is constructed to derive sufficient conditions for consensus of multiagent systems with fixed (switched topologies. We also apply this method to the H∞ consensus of multiagent systems with disturbances and heterogeneous delays. Numerical examples are given to illustrate the theoretical results.

Calculation of thermodynamic properties using the random-phase approximation: alpha-N2

NARCIS (Netherlands)

Jansen, A.P.J.; Schoorl, R.

1988-01-01

The random-phase approximation (RPA) for molecular crystals is extended in order to calculate thermodynamic properties. A recursion formula for thermodynamic averages of products of mean-field excitation and deexcitation operators is derived. With this formula the thermodynamic average of any

Closeness-Centrality-Based Synchronization Criteria for Complex Dynamical Networks With Interval Time-Varying Coupling Delays.

Science.gov (United States)

Park, Myeongjin; Lee, Seung-Hoon; Kwon, Oh-Min; Seuret, Alexandre

2017-09-06

This paper investigates synchronization in complex dynamical networks (CDNs) with interval time-varying delays. The CDNs are representative of systems composed of a large number of interconnected dynamical units, and for the purpose of the mathematical analysis, the leading work is to model them as graphs whose nodes represent the dynamical units. At this time, we take note of the importance of each node in networks. One way, in this paper, is that the closeness-centrality mentioned in the field of social science is grafted onto the CDNs. By constructing a suitable Lyapunov-Krasovskii functional, and utilizing some mathematical techniques, the sufficient and closeness-centrality-based conditions for synchronization stability of the networks are established in terms of linear matrix inequalities. Ultimately, the use of the closeness-centrality can be weighted with regard to not only the interconnection relation among the nodes, which was utilized in the existing works but also more information about nodes. Here, the centrality will be added as the concerned information. Moreover, to avoid the computational burden causing the nonconvex term including the square of the time-varying delay, how to deal with it is applied by estimating it to the convex term including time-varying delay. Finally, two illustrative examples are given to show the advantage of the closeness-centrality in point of the robustness on time-delay.

Time of Growth Dependent of ZnO-Nanorods by Self-Assembly Methods and its Structural Properties

Science.gov (United States)

Aprilia, A.; Bahtiar, A.; Safriani, L.; Ayunita, C. C.; Afifah, N.; Syakir, N.; Risdiana; Saragi, T.; Hidayat, S.; Fitrilawati; Siregar, R. E.

2017-05-01

ZnO-nanorods (ZnO-Nrs) have been successfully prepared on glass substrate using self-assembly method by varying deposition time. Zn acetate dehydrate and 2-methoxyethanol was used as raw material and solvent respectively (for ZnO seed layer preparation), meanwhile Zn nitrate hexahydrate and hexametylenetetramine (HMTA) dissolved in deionized water used as solution growth of ZnO-Nanorods (ZnO-Nrs). In this work, deposition times of ZnO-Nrs were varied by 120 min, 150 min, 180 min and 210 minutes at 100°C of annealing temperature. In order to investigate the physical properties of resulting ZnO, several measurements such as x-ray diffraction (XRD), ultra-violet visible spectroscopy and scanning electron microscopy (SEM) were carried out. Based on ZnO nanorods SEM image with varying time depositions, seems that increasing deposition time the nanorod size decrease but when the time reach 210 min, the average size of nanorods turned back increase. From XRD measurement, the average grain size and lattice constant (c) which is assemble the nanorod structure and lattice constant (c) was determined by Debye-Scherrer formula and Bragg law’s respectively. The growth process of ZnO nanorod by 180 min time deposition was known as an appropriate time to produce ZnO nanorods with high crystal quality due to sharp peak intensity of XRD spectrum.

A Robust Pre-Filter and Power Loading Design for Time Reversal UWB Systems over Time-Correlated MIMO Channels

Directory of Open Access Journals (Sweden)

Sajjad Alizadeh

2014-04-01

Full Text Available Conventional Time Reversal (TR technique suffers from performance degradation in time varying Multiple-Input Multiple-Output Ultra-Wideband (MIMO-UWB systems due to outdating Channel State Information (CSI over time progressions. That is, the outdated CSI degrades the TR performance significantly in time varying channels. The correlation property of time correlated channels can improve the TR performance against other traditional TR designs. Based on this property, at first, we propose a robust TR-MIMO-UWB system design for a time-varying channel in which the CSI is updated only at the beginning of each block of data where the CSI is assumed to be known. As the channel varies over time, pre-processor blindly pre-equalizes the channel during the next symbol time by using the correlation property. Then, a novel recursive power allocation strategy is derived over time-correlated time-varying TR-MIMO-UWB channels. We show that the proposed power loading technique, considerably improves the BER performance of TR-MIMO-UWB system in imperfect CSI with robust pre-filter. The proposed algorithms lead to a cost-efficient CSI updating procedure for the TR optimization. Simulation results are provided to confirm the new design performance against traditional method.

Stationary Probability and First-Passage Time of Biased Random Walk

International Nuclear Information System (INIS)

Li Jing-Wen; Tang Shen-Li; Xu Xin-Ping

2016-01-01

In this paper, we consider the stationary probability and first-passage time of biased random walk on 1D chain, where at each step the walker moves to the left and right with probabilities p and q respectively (0 ⩽ p, q ⩽ 1, p + q = 1). We derive exact analytical results for the stationary probability and first-passage time as a function of p and q for the first time. Our results suggest that the first-passage time shows a double power-law F ∼ (N − 1) γ , where the exponent γ = 2 for N < |p − q| −1 and γ = 1 for N > |p − q| −1 . Our study sheds useful insights into the biased random-walk process. (paper)

Influence of Irradiation Time on properties of CdS Nanoparticles Synthesized using Microwave Irradiation

International Nuclear Information System (INIS)

Nayereh Soltani; Elias SSaion; Maryam Erfani; Mohd Zobir Hussein; Robiah Yunus

2011-01-01

Different sizes of cadmium sulfide nanoparticles which exhibit obvious quantum confinement effect have been synthesized of cadmium chloride and thioacetamide through the simple and rapid microwave method. The properties of these CdS nanoparticles were examined with varying irradiation time from 10 to 40 min using a pulse regime. The obtained CdS particles were characterized by X-ray diffraction (XRD), transition electron microscopy (TEM) and UV-visible (UV-Vis) spectroscopy. The effects of irradiation time on the size, degree of crystallinity, yield of reaction and optical band gap of CdS nanoparticles are investigated. (author)

Timing properties of a time-of-flight detector

International Nuclear Information System (INIS)

Nakagawa, Takahide; Yuasa-Nakagawa, Keiko.

1989-01-01

The time resolution of a time-of-flight (T.O.F.) detector which consists of a channel plate detector (CPD) with a central hole and a surface barrier detector (SBD) was measured. A time resolution of 80 psec fwhm was obtained for 8.78 MeV alpha particles. The influence on fast timing of the SBD of alpha particles was carefully studied. The plasma delay time and time resolution of the SBD were found to strongly depend on the electric field strength and properties of the SBD. (author)

Study the effects of varying interference upon the optical properties of turbid samples using NIR spatial light modulation

Science.gov (United States)

Shaul, Oren; Fanrazi-Kahana, Michal; Meitav, Omri; Pinhasi, Gad A.; Abookasis, David

2018-03-01

Optical properties of biological tissues are valuable diagnostic parameters which can provide necessary information regarding tissue state during disease pathogenesis and therapy. However, different sources of interference, such as temperature changes may modify these properties, introducing confounding factors and artifacts to data, consequently skewing their interpretation and misinforming clinical decision-making. In the current study, we apply spatial light modulation, a type of diffuse reflectance hyperspectral imaging technique, to monitor the variation in optical properties of highly scattering turbid media in the presence varying levels of the following sources of interference: scattering concentration, temperature, and pressure. Spatial near-infrared (NIR) light modulation is a wide-field, non-contact emerging optical imaging platform capable of separating the effects of tissue scattering from those of absorption, thereby accurately estimating both parameters. With this technique, periodic NIR illumination patterns at alternately low and high spatial frequencies, at six discrete wavelengths between 690 to 970 nm, were sequentially projected upon the medium while a CCD camera collects the diffusely reflected light. Data analysis based assumptions is then performed off-line to recover the medium's optical properties. We conducted a series of experiments demonstrating the changes in absorption and reduced scattering coefficients of commercially available fresh milk and chicken breast tissue under different interference conditions. In addition, information on the refractive index was study under increased pressure. This work demonstrates the utility of NIR spatial light modulation to detect varying sources of interference upon the optical properties of biological samples.

Calculation of rectal dose surface histograms in the presence of time varying deformations

International Nuclear Information System (INIS)

Roeske, John C.; Spelbring, Danny R.; Vijayakumar, S.; Forman, Jeffrey D.; Chen, George T.Y.

1996-01-01

Purpose: Dose volume (DVH) and dose surface histograms (DSH) of the bladder and rectum are usually calculated from a single treatment planning scan. These DVHs and DSHs will eventually be correlated with complications to determine parameters for normal tissue complication probabilities (NTCP). However, from day to day, the size and shape of the rectum and bladder may vary. The purpose of this study is to compare a more accurate estimate of the time integrated DVHs and DSHs of the rectum (in the presence of daily variations in rectal shape) to initial DVHs/DSHs. Methods: 10 patients were scanned once per week during the course of fractionated radiotherapy, typically accumulating a total of six scans. The rectum and bladder were contoured on each of the studies. The model used to assess effects of rectal contour deformation is as follows: the contour on a given axial slice (see figure) is boxed within a rectangle. A line drawn parallel to the AP axis through the rectangle equally partitions the box. Starting at the intersection of the vertical line and the rectal contour, points on the contour are marked off representing the same rectal dose point, even in the presence of distortion. Corresponding numbered points are used to sample the dose matrix and create a composite DSH. The model assumes uniform stretching of the rectal contour for any given axial cut, and no twist of the structure or vertical displacement. A similar model is developed for the bladder with spherical symmetry. Results: Normalized DSHs (nDSH) for each CT scan were calculated as well as the time averaged nDSH over all scans. These were compared with the nDSH from the initial planning scan. Individual nDSHs differed by 8% surface area irradiated at the 80% dose level, to as much as 20% surface area in the 70-100% dose range. DSH variations are due to position and shape changes in the rectum during different CT scans. The spatial distribution of dose is highly variable, and depends on the field

Determinants of translation speed are randomly distributed across transcripts resulting in a universal scaling of protein synthesis times

Science.gov (United States)

Sharma, Ajeet K.; Ahmed, Nabeel; O'Brien, Edward P.

2018-02-01

Ribosome profiling experiments have found greater than 100-fold variation in ribosome density along mRNA transcripts, indicating that individual codon elongation rates can vary to a similar degree. This wide range of elongation times, coupled with differences in codon usage between transcripts, suggests that the average codon translation-rate per gene can vary widely. Yet, ribosome run-off experiments have found that the average codon translation rate for different groups of transcripts in mouse stem cells is constant at 5.6 AA/s. How these seemingly contradictory results can be reconciled is the focus of this study. Here, we combine knowledge of the molecular factors shown to influence translation speed with genomic information from Escherichia coli, Saccharomyces cerevisiae and Homo sapiens to simulate the synthesis of cytosolic proteins in these organisms. The model recapitulates a near constant average translation rate, which we demonstrate arises because the molecular determinants of translation speed are distributed nearly randomly amongst most of the transcripts. Consequently, codon translation rates are also randomly distributed and fast-translating segments of a transcript are likely to be offset by equally probable slow-translating segments, resulting in similar average elongation rates for most transcripts. We also show that the codon usage bias does not significantly affect the near random distribution of codon translation rates because only about 10 % of the total transcripts in an organism have high codon usage bias while the rest have little to no bias. Analysis of Ribo-Seq data and an in vivo fluorescent assay supports these conclusions.

Properties of a random bond Ising chain in a magnetic field

International Nuclear Information System (INIS)

Landau, D.P.; Blume, M.

1976-01-01

The Ising chain with random bonds in a magnetic field H = -Σ/sub i/J/sub i/sigma/sub i/sigma/sub i + l/ - hΣ/sub i/sigma/sub i/, where J/sub i/ = +- 1 at random, and Σ/sub i/J/sub i/ = 0, represents a model of a magnetic glass, or of heteropolymer melting. Calculations of the thermodynamic properties of the chain as a function of field strength and temperature have been performed by Monte Carlo techniques. These results are compared with perturbation calculations for small and large values of h/T. The Monte Carlo results show, in agreement with the perturbation calculations, that the field-induced magnetization is generally smaller for the random bond model than for a chain of noninteracting spins. As T → 0 the magnetization approaches the result for noninteracting spins

Hybrid Percolation Transition in Cluster Merging Processes: Continuously Varying Exponents

Science.gov (United States)

Cho, Y. S.; Lee, J. S.; Herrmann, H. J.; Kahng, B.

2016-01-01

Consider growing a network, in which every new connection is made between two disconnected nodes. At least one node is chosen randomly from a subset consisting of g fraction of the entire population in the smallest clusters. Here we show that this simple strategy for improving connection exhibits a more unusual phase transition, namely a hybrid percolation transition exhibiting the properties of both first-order and second-order phase transitions. The cluster size distribution of finite clusters at a transition point exhibits power-law behavior with a continuously varying exponent τ in the range 2 power-law behavior of the avalanche size distribution arising in models with link-deleting processes in interdependent networks.

Empirical Evidence on Time-Varying Hedging Effectiveness of Emissions Allowances under Departures from the Cost-of-Carry Theory

Directory of Open Access Journals (Sweden)

Kai Chang

2013-01-01

Full Text Available Under departures from the cost-of-carry theory, traded spot prices and conditional volatility disturbed from futures market have significant impacts on futures price of emissions allowances, and then we propose time-varying hedge ratios and hedging effectiveness estimation using ECM-GARCH model. Our empirical results show that conditional variance, conditional covariance, and their correlation between between spot and futures prices exhibit time-varying trends. Conditional volatility of spot prices, conditional volatility disturbed from futures market, and conditional correlation of market noises implied from spot and futures markets have significant effects on time-varying hedge ratios and hedging effectiveness. In the immature emissions allowances market, market participants optimize portfolio sizes between spot and futures assets using historical market information and then achieve higher risk reduction of assets portfolio revenues; accordingly, we can obtain better hedging effectiveness through time-varying hedge ratios with departures from the cost-of-carry theory.

A new simple technique for improving the random properties of chaos-based cryptosystems

Science.gov (United States)

Garcia-Bosque, M.; Pérez-Resa, A.; Sánchez-Azqueta, C.; Celma, S.

2018-03-01

A new technique for improving the security of chaos-based stream ciphers has been proposed and tested experimentally. This technique manages to improve the randomness properties of the generated keystream by preventing the system to fall into short period cycles due to digitation. In order to test this technique, a stream cipher based on a Skew Tent Map algorithm has been implemented on a Virtex 7 FPGA. The randomness of the keystream generated by this system has been compared to the randomness of the keystream generated by the same system with the proposed randomness-enhancement technique. By subjecting both keystreams to the National Institute of Standards and Technology (NIST) tests, we have proved that our method can considerably improve the randomness of the generated keystreams. In order to incorporate our randomness-enhancement technique, only 41 extra slices have been needed, proving that, apart from effective, this method is also efficient in terms of area and hardware resources.

Microwave single-scattering properties of randomly oriented soft-ice hydrometeors

Directory of Open Access Journals (Sweden)

D. Casella

2008-11-01

Full Text Available Large ice hydrometeors are usually present in intense convective clouds and may significantly affect the upwelling radiances that are measured by satellite-borne microwave radiometers – especially, at millimeter-wavelength frequencies. Thus, interpretation of these measurements (e.g., for precipitation retrieval requires knowledge of the single scattering properties of ice particles. On the other hand, shape and internal structure of these particles (especially, the larger ones is very complex and variable, and therefore it is necessary to resort to simplifying assumptions in order to compute their single-scattering parameters.

In this study, we use the discrete dipole approximation (DDA to compute the absorption and scattering efficiencies and the asymmetry factor of two kinds of quasi-spherical and non-homogeneous soft-ice particles in the frequency range 50–183 GHz. Particles of the first kind are modeled as quasi-spherical ice particles having randomly distributed spherical air inclusions. Particles of the second kind are modeled as random aggregates of ice spheres having random radii. In both cases, particle densities and dimensions are coherent with the snow hydrometeor category that is utilized by the University of Wisconsin – Non-hydrostatic Modeling System (UW-NMS cloud-mesoscale model. Then, we compare our single-scattering results for randomly-oriented soft-ice hydrometeors with corresponding ones that make use of: a effective-medium equivalent spheres, b solid-ice equivalent spheres, and c randomly-oriented aggregates of ice cylinders. Finally, we extend to our particles the scattering formulas that have been developed by other authors for randomly-oriented aggregates of ice cylinders.

Self-rating of daily time management in children: psychometric properties of the Time-S.

Science.gov (United States)

Sköld, Annika; Janeslätt, Gunnel Kristina

2017-05-01

Impaired ability to manage time has been shown in several diagnoses common in childhood. Impaired ability involves activities and participation domain (daily time management, DTM) and body function and structure domain (time-processing ability, TPA). DTM needs to be evaluated from an individual's own perspective. To date, there has been a lack of self-rating instruments for children that focus on DTM. The aim of this study is to describe psychometric properties of Time-S when used in children aged 10-17 years with a diagnosis of ADHD, Autism, CP or mild ID. Further, to test whether TPA correlates with self-rated DTM. Eighty-three children aged 10-17 years participated in the study. Rasch analysis was used to assess psychometric properties. Correlation analysis was performed between Time-S and a measure of TPA. The 21 items of the Time-S questionnaire fit into a unitary construct measuring self-perceived daily management of an individual's time. A non-significant, small correlation was found between TPA and DTM. The results indicate good psychometric properties for the questionnaire. The questionnaire is potentially useful in intervention planning and evaluation.

Testing for Change in Mean of Independent Multivariate Observations with Time Varying Covariance

Directory of Open Access Journals (Sweden)

Mohamed Boutahar

2012-01-01

Full Text Available We consider a nonparametric CUSUM test for change in the mean of multivariate time series with time varying covariance. We prove that under the null, the test statistic has a Kolmogorov limiting distribution. The asymptotic consistency of the test against a large class of alternatives which contains abrupt, smooth and continuous changes is established. We also perform a simulation study to analyze the size distortion and the power of the proposed test.

Robust state estimation for uncertain fuzzy bidirectional associative memory networks with time-varying delays

Science.gov (United States)

Vadivel, P.; Sakthivel, R.; Mathiyalagan, K.; Arunkumar, A.

2013-09-01

This paper addresses the issue of robust state estimation for a class of fuzzy bidirectional associative memory (BAM) neural networks with time-varying delays and parameter uncertainties. By constructing the Lyapunov-Krasovskii functional, which contains the triple-integral term and using the free-weighting matrix technique, a set of sufficient conditions are derived in terms of linear matrix inequalities (LMIs) to estimate the neuron states through available output measurements such that the dynamics of the estimation error system is robustly asymptotically stable. In particular, we consider a generalized activation function in which the traditional assumptions on the boundedness, monotony and differentiability of the activation functions are removed. More precisely, the design of the state estimator for such BAM neural networks can be obtained by solving some LMIs, which are dependent on the size of the time derivative of the time-varying delays. Finally, a numerical example with simulation result is given to illustrate the obtained theoretical results.

Robust state estimation for uncertain fuzzy bidirectional associative memory networks with time-varying delays

International Nuclear Information System (INIS)

Vadivel, P; Sakthivel, R; Mathiyalagan, K; Arunkumar, A

2013-01-01

This paper addresses the issue of robust state estimation for a class of fuzzy bidirectional associative memory (BAM) neural networks with time-varying delays and parameter uncertainties. By constructing the Lyapunov–Krasovskii functional, which contains the triple-integral term and using the free-weighting matrix technique, a set of sufficient conditions are derived in terms of linear matrix inequalities (LMIs) to estimate the neuron states through available output measurements such that the dynamics of the estimation error system is robustly asymptotically stable. In particular, we consider a generalized activation function in which the traditional assumptions on the boundedness, monotony and differentiability of the activation functions are removed. More precisely, the design of the state estimator for such BAM neural networks can be obtained by solving some LMIs, which are dependent on the size of the time derivative of the time-varying delays. Finally, a numerical example with simulation result is given to illustrate the obtained theoretical results. (paper)

Nonlinear Estimation of Discrete-Time Signals Under Random Observation Delay

International Nuclear Information System (INIS)

Caballero-Aguila, R.; Jimenez-Lopez, J. D.; Hermoso-Carazo, A.; Linares-Perez, J.; Nakamori, S.

2008-01-01

This paper presents an approximation to the nonlinear least-squares estimation problem of discrete-time stochastic signals using nonlinear observations with additive white noise which can be randomly delayed by one sampling time. The observation delay is modelled by a sequence of independent Bernoulli random variables whose values, zero or one, indicate that the real observation arrives on time or it is delayed and, hence, the available measurement to estimate the signal is not up-to-date. Assuming that the state-space model generating the signal is unknown and only the covariance functions of the processes involved in the observation equation are ready for use, a filtering algorithm based on linear approximations of the real observations is proposed.

Propagation of a laser beam in a time-varying waveguide

International Nuclear Information System (INIS)

Chapman, J.M.; Kevorkian, J.

1978-01-01

The propagation of an axisymmetric laser beam in a plasma column having a radially parabolic electron density distribution is examined. First, an extended paraxial procedure is developed for the case of an axially uniform waveguide. It is shown that the essential feature of an alternate focusing and defocusing beam is retained, but that the intensity distribution is cumulatively modified at the foci and at the outer portions of the beam as compared to that of the paraxial case. Second, some general features of paraxial beam propagation are examined for the case of axially varying waveguides. Finally, laser plasma coupling is examined for the case when laser heating generates a density distribution that is radially parabolic near the axis and when the energy absorbed over a focal length of a plasma lens is small. It is shown that stable or unstable beam propagation depends upon the relative magnitude of the density fluctuations which exist in the axial variation of the waveguides as a result of laser heating. When the fluctuations are small, the propagation is stable, and a simple algebraic expression is obtained which relates the beam diameter to the axially slow averaged variation in the waveguide. When the fluctuations are large, the propagation stability can be determined only by consistently combining plasma dynamics and beam propagation to interrelate the axial variation of the beam to that of the waveguide. In this case of beam propagation in a time-varying waveguide, it is shown that the global stability of the propagation depends upon the initial fluctuation growth rate compared to the initial time rate of change in the radial curvature of the waveguide

Dynamic IQC-Based Control of Uncertain LFT Systems With Time-Varying State Delay.

Science.gov (United States)

Yuan, Chengzhi; Wu, Fen

2016-12-01

This paper presents a new exact-memory delay control scheme for a class of uncertain systems with time-varying state delay under the integral quadratic constraint (IQC) framework. The uncertain system is described as a linear fractional transformation model including a state-delayed linear time-invariant (LTI) system and time-varying structured uncertainties. The proposed exact-memory delay controller consists of a linear state-feedback control law and an additional term that captures the delay behavior of the plant. We first explore the delay stability and the L 2 -gain performance using dynamic IQCs incorporated with quadratic Lyapunov functions. Then, the design of exact-memory controllers that guarantee desired L 2 -gain performance is examined. The resulting delay control synthesis conditions are formulated in terms of linear matrix inequalities, which are convex on all design variables including the scaling matrices associated with the IQC multipliers. The IQC-based exact-memory control scheme provides a novel approach for delay control designs via convex optimization, and advances existing control methods in two important ways: 1) better controlled performance and 2) simplified design procedure with less computational cost. The effectiveness and advantages of the proposed approach have been demonstrated through numerical studies.

Observer-based output feedback control of networked control systems with non-uniform sampling and time-varying delay

Science.gov (United States)

Meng, Su; Chen, Jie; Sun, Jian

2017-10-01

This paper investigates the problem of observer-based output feedback control for networked control systems with non-uniform sampling and time-varying transmission delay. The sampling intervals are assumed to vary within a given interval. The transmission delay belongs to a known interval. A discrete-time model is first established, which contains time-varying delay and norm-bounded uncertainties coming from non-uniform sampling intervals. It is then converted to an interconnection of two subsystems in which the forward channel is delay-free. The scaled small gain theorem is used to derive the stability condition for the closed-loop system. Moreover, the observer-based output feedback controller design method is proposed by utilising a modified cone complementary linearisation algorithm. Finally, numerical examples illustrate the validity and superiority of the proposed method.

The effect of varying incubation times for hypotonic treatment of lymphocytes in dicentric assay technique

International Nuclear Information System (INIS)

Noraisyah Yusof; Noriah Jamal; Rahimah Abdul Rahim; Juliana Mahamad Napiah

2010-01-01

The International Atomic Energy Agency (IAEA) has recommended that incubation time for the hypotonic treatment of lymphocytes in dicentric assay technique to be between 15 to 20 minutes. Incubation time will effect the hypotonic treatment of lymphocytes and thus, the breakage of cytoplasmic membrane. The objective of this study is to examine the effect of varying incubation times for hypotonic treatment of lymphocytes in dicentric assay technique. In this study, we choose to use our standard protocol for dicentric assay technique. However, for the hypotonic treatment of lymphocytes, the incubation times were varied from 10, 15, 20, 25 and 30 minutes respectively. Lymphocytes were then fixed and stained with Giemsa. The cells were then analyzed for clear background that indicates good metaphases. We found that incubation time of 30 minutes gives the best metaphase images. This incubation time is longer than what has been recommended by the IAEA. This maybe explained by the fact that our country's climate is of higher humidity compared with the European countries. (author)

Size-dependent mechanical properties of 2D random nanofibre networks

International Nuclear Information System (INIS)

Lu, Zixing; Zhu, Man; Liu, Qiang

2014-01-01

The mechanical properties of nanofibre networks (NFNs) are size dependent with respect to different fibre diameters. In this paper, a continuum model is developed to reveal the size-dependent mechanical properties of 2D random NFNs. Since such size-dependent behaviours are attributed to different micromechanical mechanisms, the surface effects and the strain gradient (SG) effects are, respectively, introduced into the mechanical analysis of NFNs. Meanwhile, a modified fibre network model is proposed, in which the axial, bending and shearing deformations are incorporated. The closed-form expressions of effective modulus and Poisson's ratio are obtained for NFNs. Different from the results predicted by conventional fibre network model, the present model predicts the size-dependent mechanical properties of NFNs. It is found that both surface effects and SG effects have significant influences on the effective mechanical properties. Moreover, the present results show that the shearing deformation of fibre segment is also crucial to precisely evaluate the effective mechanical properties of NFNs. This work mainly aims to provide an insight into the micromechanical mechanisms of NFNs. Besides, this work is also expected to provide a more accurate theoretical model for 2D fibre networks. (paper)

Overestimated lead times in cancer screening has led to substantial underestimation of overdiagnosis

DEFF Research Database (Denmark)

Zahl, P-H; Juhl Jørgensen, Karsten; Gøtzsche, P C

2013-01-01

Published lead time estimates in breast cancer screening vary from 1 to 7 years and the percentages of overdiagnosis vary from 0 to 75%. The differences are usually explained as random variations. We study how much can be explained by using different definitions and methods.......Published lead time estimates in breast cancer screening vary from 1 to 7 years and the percentages of overdiagnosis vary from 0 to 75%. The differences are usually explained as random variations. We study how much can be explained by using different definitions and methods....

Quantum random-walk search algorithm

International Nuclear Information System (INIS)

Shenvi, Neil; Whaley, K. Birgitta; Kempe, Julia

2003-01-01

Quantum random walks on graphs have been shown to display many interesting properties, including exponentially fast hitting times when compared with their classical counterparts. However, it is still unclear how to use these novel properties to gain an algorithmic speedup over classical algorithms. In this paper, we present a quantum search algorithm based on the quantum random-walk architecture that provides such a speedup. It will be shown that this algorithm performs an oracle search on a database of N items with O(√(N)) calls to the oracle, yielding a speedup similar to other quantum search algorithms. It appears that the quantum random-walk formulation has considerable flexibility, presenting interesting opportunities for development of other, possibly novel quantum algorithms

Magnetohydrodynamic flow of a rarefied gas near a time-varying accelerated plate

International Nuclear Information System (INIS)

Mishra, S.P.; Mohapatra, Priti

1975-01-01

The flow of an electrically conducting rarefied gas due to the time-varying motion of an infinite flat plate has been studied in the presence of a uniform magnetic field. The magnetic lines of force are taken to be fixed relative to the fluid. General expressions of the velocity and the skin friction have been compared by means of some qraphs and tables. (author)

Scalar Aharonov–Bohm Phase in Ramsey Atom Interferometry under Time-Varying Potential

Directory of Open Access Journals (Sweden)

Atsuo Morinaga

2016-08-01

Full Text Available In a Ramsey atom interferometer excited by two electromagnetic fields, if atoms are under a time-varying scalar potential during the interrogation time, the phase of the Ramsey fringes shifts owing to the scalar Aharonov–Bohm effect. The phase shift was precisely examined using a Ramsey atom interferometer with a two-photon Raman transition under the second-order Zeeman potential, and a formula for the phase shift was derived. Using the derived formula, the frequency shift due to the scalar Aharonov–Bohm effect in the frequency standards utilizing the Ramsey atom interferometer was discussed.

Mapping Soil Properties of Africa at 250 m Resolution: Random Forests Significantly Improve Current Predictions.

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Tomislav Hengl

Full Text Available 80% of arable land in Africa has low soil fertility and suffers from physical soil problems. Additionally, significant amounts of nutrients are lost every year due to unsustainable soil management practices. This is partially the result of insufficient use of soil management knowledge. To help bridge the soil information gap in Africa, the Africa Soil Information Service (AfSIS project was established in 2008. Over the period 2008-2014, the AfSIS project compiled two point data sets: the Africa Soil Profiles (legacy database and the AfSIS Sentinel Site database. These data sets contain over 28 thousand sampling locations and represent the most comprehensive soil sample data sets of the African continent to date. Utilizing these point data sets in combination with a large number of covariates, we have generated a series of spatial predictions of soil properties relevant to the agricultural management--organic carbon, pH, sand, silt and clay fractions, bulk density, cation-exchange capacity, total nitrogen, exchangeable acidity, Al content and exchangeable bases (Ca, K, Mg, Na. We specifically investigate differences between two predictive approaches: random forests and linear regression. Results of 5-fold cross-validation demonstrate that the random forests algorithm consistently outperforms the linear regression algorithm, with average decreases of 15-75% in Root Mean Squared Error (RMSE across soil properties and depths. Fitting and running random forests models takes an order of magnitude more time and the modelling success is sensitive to artifacts in the input data, but as long as quality-controlled point data are provided, an increase in soil mapping accuracy can be expected. Results also indicate that globally predicted soil classes (USDA Soil Taxonomy, especially Alfisols and Mollisols help improve continental scale soil property mapping, and are among the most important predictors. This indicates a promising potential for transferring

Skin Membrane Electrical Impedance Properties under the Influence of a Varying Water Gradient

Science.gov (United States)

Björklund, Sebastian; Ruzgas, Tautgirdas; Nowacka, Agnieszka; Dahi, Ihab; Topgaard, Daniel; Sparr, Emma; Engblom, Johan

2013-01-01

The stratum corneum (SC) is an effective permeability barrier. One strategy to increase drug delivery across skin is to increase the hydration. A detailed description of how hydration affects skin permeability requires characterization of both macroscopic and molecular properties and how they respond to hydration. We explore this issue by performing impedance experiments on excised skin membranes in the frequency range 1 Hz to 0.2 MHz under the influence of a varying gradient in water activity (aw). Hydration/dehydration induces reversible changes of membrane resistance and effective capacitance. On average, the membrane resistance is 14 times lower and the effective capacitance is 1.5 times higher when the outermost SC membrane is exposed to hydrating conditions (aw = 0.992), as compared to the case of more dehydrating conditions (aw = 0.826). Molecular insight into the hydration effects on the SC components is provided by natural-abundance 13C polarization transfer solid-state NMR and x-ray diffraction under similar hydration conditions. Hydration has a significant effect on the dynamics of the keratin filament terminals and increases the interchain spacing of the filaments. The SC lipids are organized into lamellar structures with ∼ 12.6 nm spacing and hexagonal hydrocarbon chain packing with mainly all-trans configuration of the acyl chains, irrespective of hydration state. Subtle changes in the dynamics of the lipids due to mobilization and incorporation of cholesterol and long-chain lipid species into the fluid lipid fraction is suggested to occur upon hydration, which can explain the changes of the impedance response. The results presented here provide information that is useful in explaining the effect of hydration on skin permeability. PMID:23790372

Analysis on Passivity for Uncertain Neural Networks with Time-Varying Delays

Directory of Open Access Journals (Sweden)

O. M. Kwon

2014-01-01

Full Text Available The problem of passivity analysis for neural networks with time-varying delays and parameter uncertainties is considered. By the consideration of newly constructed Lyapunov-Krasovskii functionals, improved sufficient conditions to guarantee the passivity of the concerned networks are proposed with the framework of linear matrix inequalities (LMIs, which can be solved easily by various efficient convex optimization algorithms. The enhancement of the feasible region of the proposed criteria is shown via two numerical examples by the comparison of maximum allowable delay bounds.

Random sampling of evolution time space and Fourier transform processing

International Nuclear Information System (INIS)

Kazimierczuk, Krzysztof; Zawadzka, Anna; Kozminski, Wiktor; Zhukov, Igor

2006-01-01

Application of Fourier Transform for processing 3D NMR spectra with random sampling of evolution time space is presented. The 2D FT is calculated for pairs of frequencies, instead of conventional sequence of one-dimensional transforms. Signal to noise ratios and linewidths for different random distributions were investigated by simulations and experiments. The experimental examples include 3D HNCA, HNCACB and 15 N-edited NOESY-HSQC spectra of 13 C 15 N labeled ubiquitin sample. Obtained results revealed general applicability of proposed method and the significant improvement of resolution in comparison with conventional spectra recorded in the same time

Vector Autoregressions with Parsimoniously Time Varying Parameters and an Application to Monetary Policy

DEFF Research Database (Denmark)

Callot, Laurent; Kristensen, Johannes Tang

the monetary policy response to inflation and business cycle fluctuations in the US by estimating a parsimoniously time varying parameter Taylor rule.We document substantial changes in the policy response of the Fed in the 1970s and 1980s, and since 2007, but also document the stability of this response...

Record statistics of a strongly correlated time series: random walks and Lévy flights

Science.gov (United States)

Godrèche, Claude; Majumdar, Satya N.; Schehr, Grégory

2017-08-01

We review recent advances on the record statistics of strongly correlated time series, whose entries denote the positions of a random walk or a Lévy flight on a line. After a brief survey of the theory of records for independent and identically distributed random variables, we focus on random walks. During the last few years, it was indeed realized that random walks are a very useful ‘laboratory’ to test the effects of correlations on the record statistics. We start with the simple one-dimensional random walk with symmetric jumps (both continuous and discrete) and discuss in detail the statistics of the number of records, as well as of the ages of the records, i.e. the lapses of time between two successive record breaking events. Then we review the results that were obtained for a wide variety of random walk models, including random walks with a linear drift, continuous time random walks, constrained random walks (like the random walk bridge) and the case of multiple independent random walkers. Finally, we discuss further observables related to records, like the record increments, as well as some questions raised by physical applications of record statistics, like the effects of measurement error and noise.

Design, fabrication, and properties of 2-2 connectivity cement/polymer based piezoelectric composites with varied piezoelectric phase distribution

International Nuclear Information System (INIS)

Dongyu, Xu; Xin, Cheng; Shifeng, Huang; Banerjee, Sourav

2014-01-01

The laminated 2-2 connectivity cement/polymer based piezoelectric composites with varied piezoelectric phase distribution were fabricated by employing Lead Zirconium Titanate ceramic as active phase, and mixture of cement powder, epoxy resin, and hardener as matrix phase with a mass proportion of 4:4:1. The dielectric, piezoelectric, and electromechanical coupling properties of the composites were studied. The composites with large total volume fraction of piezoelectric phase have large piezoelectric strain constant and relative permittivity, and the piezoelectric and dielectric properties of the composites are independent of the dimensional variations of the piezoelectric ceramic layer. The composites with small total volume fraction of piezoelectric phase have large piezoelectric voltage constant, but also large dielectric loss. The composite with gradually increased dimension of piezoelectric ceramic layer has the smallest dielectric loss, and that with the gradually increased dimension of matrix layer has the largest piezoelectric voltage constant. The novel piezoelectric composites show potential applications in fabricating ultrasonic transducers with varied surface vibration amplitude of the transducer

Time-varying risk aversion. An application to energy hedging

Energy Technology Data Exchange (ETDEWEB)

Cotter, John [Centre for Financial Markets, School of Business, University College Dublin, Blackrock, Co. Dublin (Ireland); Hanly, Jim [School of Accounting and Finance, Dublin Institute of Technology, Dublin 2 (Ireland)

2010-03-15

Risk aversion is a key element of utility maximizing hedge strategies; however, it has typically been assigned an arbitrary value in the literature. This paper instead applies a GARCH-in-Mean (GARCH-M) model to estimate a time-varying measure of risk aversion that is based on the observed risk preferences of energy hedging market participants. The resulting estimates are applied to derive explicit risk aversion based optimal hedge strategies for both short and long hedgers. Out-of-sample results are also presented based on a unique approach that allows us to forecast risk aversion, thereby estimating hedge strategies that address the potential future needs of energy hedgers. We find that the risk aversion based hedges differ significantly from simpler OLS hedges. When implemented in-sample, risk aversion hedges for short hedgers outperform the OLS hedge ratio in a utility based comparison. (author)

Time-varying risk aversion. An application to energy hedging

International Nuclear Information System (INIS)

Cotter, John; Hanly, Jim

2010-01-01

Risk aversion is a key element of utility maximizing hedge strategies; however, it has typically been assigned an arbitrary value in the literature. This paper instead applies a GARCH-in-Mean (GARCH-M) model to estimate a time-varying measure of risk aversion that is based on the observed risk preferences of energy hedging market participants. The resulting estimates are applied to derive explicit risk aversion based optimal hedge strategies for both short and long hedgers. Out-of-sample results are also presented based on a unique approach that allows us to forecast risk aversion, thereby estimating hedge strategies that address the potential future needs of energy hedgers. We find that the risk aversion based hedges differ significantly from simpler OLS hedges. When implemented in-sample, risk aversion hedges for short hedgers outperform the OLS hedge ratio in a utility based comparison. (author)

A special case of reduced rank models for identification and modelling of time varying effects in survival analysis.

Science.gov (United States)

Perperoglou, Aris

2016-12-10

Flexible survival models are in need when modelling data from long term follow-up studies. In many cases, the assumption of proportionality imposed by a Cox model will not be valid. Instead, a model that can identify time varying effects of fixed covariates can be used. Although there are several approaches that deal with this problem, it is not always straightforward how to choose which covariates should be modelled having time varying effects and which not. At the same time, it is up to the researcher to define appropriate time functions that describe the dynamic pattern of the effects. In this work, we suggest a model that can deal with both fixed and time varying effects and uses simple hypotheses tests to distinguish which covariates do have dynamic effects. The model is an extension of the parsimonious reduced rank model of rank 1. As such, the number of parameters is kept low, and thus, a flexible set of time functions, such as b-splines, can be used. The basic theory is illustrated along with an efficient fitting algorithm. The proposed method is applied to a dataset of breast cancer patients and compared with a multivariate fractional polynomials approach for modelling time-varying effects. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

Study on the Variation of Groundwater Level under Time-varying Recharge

Science.gov (United States)

Wu, Ming-Chang; Hsieh, Ping-Cheng

2017-04-01

The slopes of the suburbs come to important areas by focusing on the work of soil and water conservation in recent years. The water table inside the aquifer is affected by rainfall, geology and topography, which will result in the change of groundwater discharge and water level. Currently, the way to obtain water table information is to set up the observation wells; however, owing to that the cost of equipment and the wells excavated is too expensive, we develop a mathematical model instead, which might help us to simulate the groundwater level variation. In this study, we will discuss the groundwater level change in a sloping unconfined aquifer with impermeable bottom under time-varying rainfall events. Referring to Child (1971), we employ the Boussinesq equation as the governing equation, and apply the General Integral Transforms Method (GITM) to analyzing the groundwater level after linearizing the Boussinesq equation. After comparing the solution with Verhoest & Troch (2000) and Bansal & Das (2010), we get satisfactory results. To sum up, we have presented an alternative approach to solve the linearized Boussinesq equation for the response of groundwater level in a sloping unconfined aquifer. The present analytical results combine the effect of bottom slope and the time-varying recharge pattern on the water table fluctuations. Owing to the limitation and difficulty of measuring the groundwater level directly, we develop such a mathematical model that we can predict or simulate the variation of groundwater level affected by any rainfall events in advance.